diff --git a/.github/workflows/py_autofix.yml b/.github/workflows/py_autofix.yml index 7fe391c97..2861b0bed 100644 --- a/.github/workflows/py_autofix.yml +++ b/.github/workflows/py_autofix.yml @@ -19,3 +19,25 @@ jobs: - uses: autofix-ci/action@ff86a557419858bb967097bfc916833f5647fa8c - name: Minimize uv cache run: uv cache prune --ci + + update-starter-projects: + name: Update Starter Projects + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - name: "Setup Environment" + uses: ./.github/actions/setup-uv + + - name: "Install dependencies" + run: | + uv sync --frozen + uv pip install -e . + + - name: Run starter projects update + run: uv run python scripts/ci/update_starter_projects.py + + - uses: autofix-ci/action@ff86a557419858bb967097bfc916833f5647fa8c + + - name: Minimize uv cache + run: uv cache prune --ci + diff --git a/.github/workflows/style-check-py.yml b/.github/workflows/style-check-py.yml index 25abc5e43..392c10f93 100644 --- a/.github/workflows/style-check-py.yml +++ b/.github/workflows/style-check-py.yml @@ -6,10 +6,6 @@ on: paths: - "**/*.py" - - - - jobs: lint: name: Ruff Style Check diff --git a/scripts/ci/update_starter_projects.py b/scripts/ci/update_starter_projects.py new file mode 100644 index 000000000..807df6fd7 --- /dev/null +++ b/scripts/ci/update_starter_projects.py @@ -0,0 +1,43 @@ +"""Script to update Langflow starter projects with the latest component versions.""" + +import asyncio +import os + +import langflow.main # noqa: F401 +from langflow.initial_setup.setup import ( + get_project_data, + load_starter_projects, + update_edges_with_latest_component_versions, + update_project_file, + update_projects_components_with_latest_component_versions, +) +from langflow.interface.types import get_and_cache_all_types_dict +from langflow.services.deps import get_settings_service +from langflow.services.utils import initialize_services + + +async def main(): + """Updates the starter projects with the latest component versions. + + Copies the code from langflow/initial_setup/setup.py. Doesn't use the + create_or_update_starter_projects function directly to avoid sql interactions. + """ + await initialize_services(fix_migration=False) + all_types_dict = await get_and_cache_all_types_dict(get_settings_service()) + + starter_projects = await load_starter_projects() + for project_path, project in starter_projects: + _, _, _, _, project_data, _, _, _, _ = get_project_data(project) + do_update_starter_projects = os.environ.get("LANGFLOW_UPDATE_STARTER_PROJECTS", "true").lower() == "true" + if do_update_starter_projects: + updated_project_data = update_projects_components_with_latest_component_versions( + project_data.copy(), all_types_dict + ) + updated_project_data = update_edges_with_latest_component_versions(updated_project_data) + if updated_project_data != project_data: + project_data = updated_project_data + await update_project_file(project_path, project, updated_project_data) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/src/backend/base/langflow/initial_setup/setup.py b/src/backend/base/langflow/initial_setup/setup.py index 117581c41..ddbdd86d1 100644 --- a/src/backend/base/langflow/initial_setup/setup.py +++ b/src/backend/base/langflow/initial_setup/setup.py @@ -611,7 +611,13 @@ async def find_existing_flow(session, flow_id, flow_endpoint_name): return None -async def create_or_update_starter_projects(all_types_dict: dict) -> None: +async def create_or_update_starter_projects(all_types_dict: dict, *, do_create: bool = True) -> None: + """Create or update starter projects. + + Args: + all_types_dict (dict): Dictionary containing all component types and their templates + do_create (bool, optional): Whether to create new projects. Defaults to True. + """ async with async_session_scope() as session: new_folder = await create_starter_folder(session) starter_projects = await load_starter_projects() @@ -639,7 +645,7 @@ async def create_or_update_starter_projects(all_types_dict: dict) -> None: project_data = updated_project_data # We also need to update the project data in the file await update_project_file(project_path, project, updated_project_data) - if project_name and project_data: + if do_create and project_name and project_data: for existing_project in await get_all_flows_similar_to_project(session, new_folder.id): await session.delete(existing_project) diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompt Chaining.json b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompt Chaining.json index 5128a60a7..a6734568f 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompt Chaining.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompt Chaining.json @@ -252,7 +252,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "template": { "_input_type": "PromptInput", @@ -941,7 +941,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "template": { "_input_type": "PromptInput", @@ -1105,7 +1105,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { "_input_type": "MessageInput", @@ -1225,41 +1225,6 @@ "type": "str", "value": "" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, @@ -1452,7 +1417,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { "_input_type": "MessageInput", @@ -1572,41 +1537,6 @@ "type": "str", "value": "" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, @@ -1756,7 +1686,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "template": { "_input_type": "PromptInput", @@ -1986,7 +1916,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { "_input_type": "MessageInput", @@ -2106,41 +2036,6 @@ "type": "str", "value": "" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting.json b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting.json index 155ff5f79..77c53339e 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting.json @@ -423,7 +423,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "template": { "_input_type": "PromptInput", @@ -651,7 +651,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { "_input_type": "MessageInput", @@ -771,41 +771,6 @@ "type": "str", "value": "" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json b/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json index 7bff175c2..e734aa2ca 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json @@ -481,7 +481,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "instructions": { "advanced": false, @@ -1049,7 +1049,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { "advanced": false, @@ -1155,40 +1155,6 @@ "type": "str", "value": "" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "advanced": true, "display_name": "Seed", diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Custom Component Maker.json b/src/backend/base/langflow/initial_setup/starter_projects/Custom Component Maker.json index 3f4faf94b..c225fd2f0 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Custom Component Maker.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Custom Component Maker.json @@ -920,7 +920,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "template": { "_input_type": "PromptInput", diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Document Q&A.json b/src/backend/base/langflow/initial_setup/starter_projects/Document Q&A.json index 0dd7b8047..8f170e14e 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Document Q&A.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Document Q&A.json @@ -968,7 +968,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { "_input_type": "MessageInput", @@ -1088,41 +1088,6 @@ "type": "str", "value": "" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, @@ -1572,7 +1537,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "template": { "advanced": false, diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Image Sentiment Analysis.json b/src/backend/base/langflow/initial_setup/starter_projects/Image Sentiment Analysis.json index c4963c2e5..5dcffd061 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Image Sentiment Analysis.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Image Sentiment Analysis.json @@ -831,7 +831,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from typing import TYPE_CHECKING, cast\n\nfrom pydantic import BaseModel, Field, create_model\n\nfrom langflow.base.models.chat_result import get_chat_result\nfrom langflow.custom import Component\nfrom langflow.helpers.base_model import build_model_from_schema\nfrom langflow.io import BoolInput, HandleInput, MessageTextInput, Output, StrInput, TableInput\nfrom langflow.schema.data import Data\n\nif TYPE_CHECKING:\n from langflow.field_typing.constants import LanguageModel\n\n\nclass StructuredOutputComponent(Component):\n display_name = \"Structured Output\"\n description = (\n \"Transforms LLM responses into **structured data formats**. Ideal for extracting specific information \"\n \"or creating consistent outputs.\"\n )\n icon = \"braces\"\n\n inputs = [\n HandleInput(\n name=\"llm\",\n display_name=\"Language Model\",\n info=\"The language model to use to generate the structured output.\",\n input_types=[\"LanguageModel\"],\n ),\n MessageTextInput(name=\"input_value\", display_name=\"Input message\"),\n StrInput(\n name=\"schema_name\",\n display_name=\"Schema Name\",\n info=\"Provide a name for the output data schema.\",\n ),\n TableInput(\n name=\"output_schema\",\n display_name=\"Output Schema\",\n info=\"Define the structure and data types for the model's output.\",\n value=[\n {\n \"name\": \"name\",\n \"display_name\": \"Name\",\n \"type\": \"str\",\n \"description\": \"Specify the name of the output field.\",\n },\n {\n \"name\": \"description\",\n \"display_name\": \"Description\",\n \"type\": \"str\",\n \"description\": \"Describe the purpose of the output field.\",\n },\n {\n \"name\": \"type\",\n \"display_name\": \"Type\",\n \"type\": \"str\",\n \"description\": (\n \"Indicate the data type of the output field \" \"(e.g., str, int, float, bool, list, dict).\"\n ),\n \"default\": \"text\",\n },\n {\n \"name\": \"multiple\",\n \"display_name\": \"Multiple\",\n \"type\": \"boolean\",\n \"description\": \"Set to True if this output field should be a list of the specified type.\",\n \"default\": \"False\",\n },\n ],\n ),\n BoolInput(\n name=\"multiple\",\n display_name=\"Generate Multiple\",\n info=\"Set to True if the model should generate a list of outputs instead of a single output.\",\n ),\n ]\n\n outputs = [\n Output(name=\"structured_output\", display_name=\"Structured Output\", method=\"build_structured_output\"),\n ]\n\n def build_structured_output(self) -> Data:\n if not hasattr(self.llm, \"with_structured_output\"):\n msg = \"Language model does not support structured output.\"\n raise TypeError(msg)\n if not self.output_schema:\n msg = \"Output schema cannot be empty\"\n raise ValueError(msg)\n\n output_model_ = build_model_from_schema(self.output_schema)\n if self.multiple:\n output_model = create_model(\n self.schema_name,\n objects=(list[output_model_], Field(description=f\"A list of {self.schema_name}.\")), # type: ignore[valid-type]\n )\n else:\n output_model = output_model_\n try:\n llm_with_structured_output = cast(\"LanguageModel\", self.llm).with_structured_output(schema=output_model) # type: ignore[valid-type, attr-defined]\n\n except NotImplementedError as exc:\n msg = f\"{self.llm.__class__.__name__} does not support structured output.\"\n raise TypeError(msg) from exc\n config_dict = {\n \"run_name\": self.display_name,\n \"project_name\": self.get_project_name(),\n \"callbacks\": self.get_langchain_callbacks(),\n }\n output = get_chat_result(runnable=llm_with_structured_output, input_value=self.input_value, config=config_dict)\n if isinstance(output, BaseModel):\n output_dict = output.model_dump()\n else:\n msg = f\"Output should be a Pydantic BaseModel, got {type(output)} ({output})\"\n raise TypeError(msg)\n return Data(data=output_dict)\n" + "value": "from typing import TYPE_CHECKING, cast\n\nfrom pydantic import BaseModel, Field, create_model\n\nfrom langflow.base.models.chat_result import get_chat_result\nfrom langflow.custom import Component\nfrom langflow.helpers.base_model import build_model_from_schema\nfrom langflow.io import BoolInput, HandleInput, MessageTextInput, Output, StrInput, TableInput\nfrom langflow.schema.data import Data\n\nif TYPE_CHECKING:\n from langflow.field_typing.constants import LanguageModel\n\n\nclass StructuredOutputComponent(Component):\n display_name = \"Structured Output\"\n description = (\n \"Transforms LLM responses into **structured data formats**. Ideal for extracting specific information \"\n \"or creating consistent outputs.\"\n )\n icon = \"braces\"\n\n inputs = [\n HandleInput(\n name=\"llm\",\n display_name=\"Language Model\",\n info=\"The language model to use to generate the structured output.\",\n input_types=[\"LanguageModel\"],\n ),\n MessageTextInput(name=\"input_value\", display_name=\"Input message\"),\n StrInput(\n name=\"schema_name\",\n display_name=\"Schema Name\",\n info=\"Provide a name for the output data schema.\",\n ),\n TableInput(\n name=\"output_schema\",\n display_name=\"Output Schema\",\n info=\"Define the structure and data types for the model's output.\",\n value=[\n {\n \"name\": \"name\",\n \"display_name\": \"Name\",\n \"type\": \"str\",\n \"description\": \"Specify the name of the output field.\",\n },\n {\n \"name\": \"description\",\n \"display_name\": \"Description\",\n \"type\": \"str\",\n \"description\": \"Describe the purpose of the output field.\",\n },\n {\n \"name\": \"type\",\n \"display_name\": \"Type\",\n \"type\": \"str\",\n \"description\": (\n \"Indicate the data type of the output field (e.g., str, int, float, bool, list, dict).\"\n ),\n \"default\": \"text\",\n },\n {\n \"name\": \"multiple\",\n \"display_name\": \"Multiple\",\n \"type\": \"boolean\",\n \"description\": \"Set to True if this output field should be a list of the specified type.\",\n \"default\": \"False\",\n },\n ],\n ),\n BoolInput(\n name=\"multiple\",\n display_name=\"Generate Multiple\",\n info=\"Set to True if the model should generate a list of outputs instead of a single output.\",\n ),\n ]\n\n outputs = [\n Output(name=\"structured_output\", display_name=\"Structured Output\", method=\"build_structured_output\"),\n ]\n\n def build_structured_output(self) -> Data:\n if not hasattr(self.llm, \"with_structured_output\"):\n msg = \"Language model does not support structured output.\"\n raise TypeError(msg)\n if not self.output_schema:\n msg = \"Output schema cannot be empty\"\n raise ValueError(msg)\n\n output_model_ = build_model_from_schema(self.output_schema)\n if self.multiple:\n output_model = create_model(\n self.schema_name,\n objects=(list[output_model_], Field(description=f\"A list of {self.schema_name}.\")), # type: ignore[valid-type]\n )\n else:\n output_model = output_model_\n try:\n llm_with_structured_output = cast(\"LanguageModel\", self.llm).with_structured_output(schema=output_model) # type: ignore[valid-type, attr-defined]\n\n except NotImplementedError as exc:\n msg = f\"{self.llm.__class__.__name__} does not support structured output.\"\n raise TypeError(msg) from exc\n config_dict = {\n \"run_name\": self.display_name,\n \"project_name\": self.get_project_name(),\n \"callbacks\": self.get_langchain_callbacks(),\n }\n output = get_chat_result(runnable=llm_with_structured_output, input_value=self.input_value, config=config_dict)\n if isinstance(output, BaseModel):\n output_dict = output.model_dump()\n else:\n msg = f\"Output should be a Pydantic BaseModel, got {type(output)} ({output})\"\n raise TypeError(msg)\n return Data(data=output_dict)\n" }, "input_value": { "_input_type": "MessageTextInput", @@ -1252,7 +1252,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { "_input_type": "MessageInput", @@ -1372,41 +1372,6 @@ "type": "str", "value": "" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, @@ -1556,7 +1521,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "template": { "_input_type": "PromptInput", diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Instagram Copywriter.json b/src/backend/base/langflow/initial_setup/starter_projects/Instagram Copywriter.json index 1305bee17..27f863e05 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Instagram Copywriter.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Instagram Copywriter.json @@ -632,7 +632,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "context": { "advanced": false, @@ -940,7 +940,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { "_input_type": "MessageInput", @@ -1060,41 +1060,6 @@ "type": "str", "value": "" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, @@ -1246,7 +1211,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "post": { "advanced": false, @@ -1774,7 +1739,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call the component class's update_build_config method\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call each component class's update_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n return build_config\n" + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n async def aupdate_build_config(\n self, build_config: dotdict, field_value: str, field_name: str | None = None\n ) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call the component class's aupdate_build_config method\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call each component class's aupdate_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n return build_config\n" }, "handle_parsing_errors": { "_input_type": "BoolInput", @@ -1983,41 +1948,6 @@ "type": "str", "value": "Ascending" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, @@ -2557,7 +2487,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { "_input_type": "MessageInput", @@ -2677,41 +2607,6 @@ "type": "str", "value": "" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, @@ -2864,7 +2759,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "image_description": { "advanced": false, diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Market Research.json b/src/backend/base/langflow/initial_setup/starter_projects/Market Research.json index 21367631c..552f7d2e2 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Market Research.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Market Research.json @@ -1137,7 +1137,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from typing import TYPE_CHECKING, cast\n\nfrom pydantic import BaseModel, Field, create_model\n\nfrom langflow.base.models.chat_result import get_chat_result\nfrom langflow.custom import Component\nfrom langflow.helpers.base_model import build_model_from_schema\nfrom langflow.io import BoolInput, HandleInput, MessageTextInput, Output, StrInput, TableInput\nfrom langflow.schema.data import Data\n\nif TYPE_CHECKING:\n from langflow.field_typing.constants import LanguageModel\n\n\nclass StructuredOutputComponent(Component):\n display_name = \"Structured Output\"\n description = (\n \"Transforms LLM responses into **structured data formats**. Ideal for extracting specific information \"\n \"or creating consistent outputs.\"\n )\n icon = \"braces\"\n\n inputs = [\n HandleInput(\n name=\"llm\",\n display_name=\"Language Model\",\n info=\"The language model to use to generate the structured output.\",\n input_types=[\"LanguageModel\"],\n ),\n MessageTextInput(name=\"input_value\", display_name=\"Input message\"),\n StrInput(\n name=\"schema_name\",\n display_name=\"Schema Name\",\n info=\"Provide a name for the output data schema.\",\n ),\n TableInput(\n name=\"output_schema\",\n display_name=\"Output Schema\",\n info=\"Define the structure and data types for the model's output.\",\n value=[\n {\n \"name\": \"name\",\n \"display_name\": \"Name\",\n \"type\": \"str\",\n \"description\": \"Specify the name of the output field.\",\n },\n {\n \"name\": \"description\",\n \"display_name\": \"Description\",\n \"type\": \"str\",\n \"description\": \"Describe the purpose of the output field.\",\n },\n {\n \"name\": \"type\",\n \"display_name\": \"Type\",\n \"type\": \"str\",\n \"description\": (\n \"Indicate the data type of the output field \" \"(e.g., str, int, float, bool, list, dict).\"\n ),\n \"default\": \"text\",\n },\n {\n \"name\": \"multiple\",\n \"display_name\": \"Multiple\",\n \"type\": \"boolean\",\n \"description\": \"Set to True if this output field should be a list of the specified type.\",\n \"default\": \"False\",\n },\n ],\n ),\n BoolInput(\n name=\"multiple\",\n display_name=\"Generate Multiple\",\n info=\"Set to True if the model should generate a list of outputs instead of a single output.\",\n ),\n ]\n\n outputs = [\n Output(name=\"structured_output\", display_name=\"Structured Output\", method=\"build_structured_output\"),\n ]\n\n def build_structured_output(self) -> Data:\n if not hasattr(self.llm, \"with_structured_output\"):\n msg = \"Language model does not support structured output.\"\n raise TypeError(msg)\n if not self.output_schema:\n msg = \"Output schema cannot be empty\"\n raise ValueError(msg)\n\n output_model_ = build_model_from_schema(self.output_schema)\n if self.multiple:\n output_model = create_model(\n self.schema_name,\n objects=(list[output_model_], Field(description=f\"A list of {self.schema_name}.\")), # type: ignore[valid-type]\n )\n else:\n output_model = output_model_\n try:\n llm_with_structured_output = cast(\"LanguageModel\", self.llm).with_structured_output(schema=output_model) # type: ignore[valid-type, attr-defined]\n\n except NotImplementedError as exc:\n msg = f\"{self.llm.__class__.__name__} does not support structured output.\"\n raise TypeError(msg) from exc\n config_dict = {\n \"run_name\": self.display_name,\n \"project_name\": self.get_project_name(),\n \"callbacks\": self.get_langchain_callbacks(),\n }\n output = get_chat_result(runnable=llm_with_structured_output, input_value=self.input_value, config=config_dict)\n if isinstance(output, BaseModel):\n output_dict = output.model_dump()\n else:\n msg = f\"Output should be a Pydantic BaseModel, got {type(output)} ({output})\"\n raise TypeError(msg)\n return Data(data=output_dict)\n" + "value": "from typing import TYPE_CHECKING, cast\n\nfrom pydantic import BaseModel, Field, create_model\n\nfrom langflow.base.models.chat_result import get_chat_result\nfrom langflow.custom import Component\nfrom langflow.helpers.base_model import build_model_from_schema\nfrom langflow.io import BoolInput, HandleInput, MessageTextInput, Output, StrInput, TableInput\nfrom langflow.schema.data import Data\n\nif TYPE_CHECKING:\n from langflow.field_typing.constants import LanguageModel\n\n\nclass StructuredOutputComponent(Component):\n display_name = \"Structured Output\"\n description = (\n \"Transforms LLM responses into **structured data formats**. Ideal for extracting specific information \"\n \"or creating consistent outputs.\"\n )\n icon = \"braces\"\n\n inputs = [\n HandleInput(\n name=\"llm\",\n display_name=\"Language Model\",\n info=\"The language model to use to generate the structured output.\",\n input_types=[\"LanguageModel\"],\n ),\n MessageTextInput(name=\"input_value\", display_name=\"Input message\"),\n StrInput(\n name=\"schema_name\",\n display_name=\"Schema Name\",\n info=\"Provide a name for the output data schema.\",\n ),\n TableInput(\n name=\"output_schema\",\n display_name=\"Output Schema\",\n info=\"Define the structure and data types for the model's output.\",\n value=[\n {\n \"name\": \"name\",\n \"display_name\": \"Name\",\n \"type\": \"str\",\n \"description\": \"Specify the name of the output field.\",\n },\n {\n \"name\": \"description\",\n \"display_name\": \"Description\",\n \"type\": \"str\",\n \"description\": \"Describe the purpose of the output field.\",\n },\n {\n \"name\": \"type\",\n \"display_name\": \"Type\",\n \"type\": \"str\",\n \"description\": (\n \"Indicate the data type of the output field (e.g., str, int, float, bool, list, dict).\"\n ),\n \"default\": \"text\",\n },\n {\n \"name\": \"multiple\",\n \"display_name\": \"Multiple\",\n \"type\": \"boolean\",\n \"description\": \"Set to True if this output field should be a list of the specified type.\",\n \"default\": \"False\",\n },\n ],\n ),\n BoolInput(\n name=\"multiple\",\n display_name=\"Generate Multiple\",\n info=\"Set to True if the model should generate a list of outputs instead of a single output.\",\n ),\n ]\n\n outputs = [\n Output(name=\"structured_output\", display_name=\"Structured Output\", method=\"build_structured_output\"),\n ]\n\n def build_structured_output(self) -> Data:\n if not hasattr(self.llm, \"with_structured_output\"):\n msg = \"Language model does not support structured output.\"\n raise TypeError(msg)\n if not self.output_schema:\n msg = \"Output schema cannot be empty\"\n raise ValueError(msg)\n\n output_model_ = build_model_from_schema(self.output_schema)\n if self.multiple:\n output_model = create_model(\n self.schema_name,\n objects=(list[output_model_], Field(description=f\"A list of {self.schema_name}.\")), # type: ignore[valid-type]\n )\n else:\n output_model = output_model_\n try:\n llm_with_structured_output = cast(\"LanguageModel\", self.llm).with_structured_output(schema=output_model) # type: ignore[valid-type, attr-defined]\n\n except NotImplementedError as exc:\n msg = f\"{self.llm.__class__.__name__} does not support structured output.\"\n raise TypeError(msg) from exc\n config_dict = {\n \"run_name\": self.display_name,\n \"project_name\": self.get_project_name(),\n \"callbacks\": self.get_langchain_callbacks(),\n }\n output = get_chat_result(runnable=llm_with_structured_output, input_value=self.input_value, config=config_dict)\n if isinstance(output, BaseModel):\n output_dict = output.model_dump()\n else:\n msg = f\"Output should be a Pydantic BaseModel, got {type(output)} ({output})\"\n raise TypeError(msg)\n return Data(data=output_dict)\n" }, "input_value": { "_input_type": "MessageTextInput", @@ -1455,7 +1455,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { "_input_type": "MessageInput", @@ -1575,41 +1575,6 @@ "type": "str", "value": "" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, @@ -2018,7 +1983,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call the component class's update_build_config method\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call each component class's update_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n return build_config\n" + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n async def aupdate_build_config(\n self, build_config: dotdict, field_value: str, field_name: str | None = None\n ) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call the component class's aupdate_build_config method\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call each component class's aupdate_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n return build_config\n" }, "handle_parsing_errors": { "_input_type": "BoolInput", @@ -2227,41 +2192,6 @@ "type": "str", "value": "Ascending" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json b/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json index 195e37a31..e639fee16 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json @@ -845,7 +845,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { "_input_type": "MessageInput", @@ -965,41 +965,6 @@ "type": "str", "value": "" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, @@ -1395,7 +1360,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "memory": { "advanced": false, diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Research Agent.json b/src/backend/base/langflow/initial_setup/starter_projects/Research Agent.json index 2a50bcf51..eaebb45b8 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Research Agent.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Research Agent.json @@ -346,7 +346,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "previous_response": { "advanced": false, @@ -1061,7 +1061,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "input_value": { "advanced": false, @@ -1507,7 +1507,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { "_input_type": "MessageInput", @@ -1627,41 +1627,6 @@ "type": "str", "value": "" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, @@ -1854,7 +1819,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { "_input_type": "MessageInput", @@ -1974,41 +1939,6 @@ "type": "str", "value": "" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, @@ -2300,7 +2230,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call the component class's update_build_config method\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call each component class's update_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n return build_config\n" + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n async def aupdate_build_config(\n self, build_config: dotdict, field_value: str, field_name: str | None = None\n ) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call the component class's aupdate_build_config method\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call each component class's aupdate_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n return build_config\n" }, "handle_parsing_errors": { "_input_type": "BoolInput", @@ -2509,41 +2439,6 @@ "type": "str", "value": "Ascending" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, @@ -2804,7 +2699,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "template": { "_input_type": "PromptInput", @@ -2925,7 +2820,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "template": { "_input_type": "PromptInput", diff --git a/src/backend/base/langflow/initial_setup/starter_projects/SEO Keyword Generator.json b/src/backend/base/langflow/initial_setup/starter_projects/SEO Keyword Generator.json index 72f45c0c9..71770d481 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/SEO Keyword Generator.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/SEO Keyword Generator.json @@ -153,7 +153,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "current_solutions": { "advanced": false, @@ -443,7 +443,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "template": { "_input_type": "PromptInput", @@ -884,7 +884,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { "_input_type": "MessageInput", @@ -1004,41 +1004,6 @@ "type": "str", "value": "" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, diff --git a/src/backend/base/langflow/initial_setup/starter_projects/SaaS Pricing.json b/src/backend/base/langflow/initial_setup/starter_projects/SaaS Pricing.json index e381644f8..4209e1828 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/SaaS Pricing.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/SaaS Pricing.json @@ -151,7 +151,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "continuous_development_cost": { "advanced": false, @@ -804,7 +804,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call the component class's update_build_config method\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call each component class's update_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n return build_config\n" + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n async def aupdate_build_config(\n self, build_config: dotdict, field_value: str, field_name: str | None = None\n ) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call the component class's aupdate_build_config method\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call each component class's aupdate_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n return build_config\n" }, "handle_parsing_errors": { "_input_type": "BoolInput", @@ -1013,41 +1013,6 @@ "type": "str", "value": "Ascending" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Sequential Tasks Agents .json b/src/backend/base/langflow/initial_setup/starter_projects/Sequential Tasks Agents .json index a7c99c8b4..fdc49173e 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Sequential Tasks Agents .json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Sequential Tasks Agents .json @@ -753,7 +753,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call the component class's update_build_config method\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call each component class's update_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n return build_config\n" + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n async def aupdate_build_config(\n self, build_config: dotdict, field_value: str, field_name: str | None = None\n ) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call the component class's aupdate_build_config method\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call each component class's aupdate_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n return build_config\n" }, "handle_parsing_errors": { "_input_type": "BoolInput", @@ -962,41 +962,6 @@ "type": "str", "value": "Ascending" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, @@ -1366,7 +1331,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call the component class's update_build_config method\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call each component class's update_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n return build_config\n" + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n async def aupdate_build_config(\n self, build_config: dotdict, field_value: str, field_name: str | None = None\n ) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call the component class's aupdate_build_config method\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call each component class's aupdate_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n return build_config\n" }, "handle_parsing_errors": { "_input_type": "BoolInput", @@ -1575,41 +1540,6 @@ "type": "str", "value": "Ascending" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, @@ -1876,7 +1806,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "template": { "_input_type": "PromptInput", @@ -2003,7 +1933,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "template": { "_input_type": "PromptInput", @@ -2133,7 +2063,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "finance_agent_output": { "advanced": false, @@ -3294,7 +3224,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call the component class's update_build_config method\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call each component class's update_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n return build_config\n" + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n async def aupdate_build_config(\n self, build_config: dotdict, field_value: str, field_name: str | None = None\n ) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call the component class's aupdate_build_config method\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call each component class's aupdate_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n return build_config\n" }, "handle_parsing_errors": { "_input_type": "BoolInput", @@ -3503,41 +3433,6 @@ "type": "str", "value": "Ascending" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Simple Agent.json b/src/backend/base/langflow/initial_setup/starter_projects/Simple Agent.json index 641563e29..328d85a27 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Simple Agent.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Simple Agent.json @@ -287,7 +287,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call the component class's update_build_config method\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call each component class's update_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n return build_config\n" + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n async def aupdate_build_config(\n self, build_config: dotdict, field_value: str, field_name: str | None = None\n ) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call the component class's aupdate_build_config method\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call each component class's aupdate_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n return build_config\n" }, "handle_parsing_errors": { "_input_type": "BoolInput", @@ -496,41 +496,6 @@ "type": "str", "value": "Ascending" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Travel Planning Agents.json b/src/backend/base/langflow/initial_setup/starter_projects/Travel Planning Agents.json index 3e8299485..69e1c8fca 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Travel Planning Agents.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Travel Planning Agents.json @@ -1382,7 +1382,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call the component class's update_build_config method\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call each component class's update_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n return build_config\n" + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n async def aupdate_build_config(\n self, build_config: dotdict, field_value: str, field_name: str | None = None\n ) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call the component class's aupdate_build_config method\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call each component class's aupdate_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n return build_config\n" }, "handle_parsing_errors": { "_input_type": "BoolInput", @@ -1960,7 +1960,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call the component class's update_build_config method\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call each component class's update_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n return build_config\n" + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n async def aupdate_build_config(\n self, build_config: dotdict, field_value: str, field_name: str | None = None\n ) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call the component class's aupdate_build_config method\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call each component class's aupdate_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n return build_config\n" }, "handle_parsing_errors": { "_input_type": "BoolInput", @@ -2538,7 +2538,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n def update_build_config(self, build_config: dotdict, field_value: str, field_name: str | None = None) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call the component class's update_build_config method\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call each component class's update_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = component_class.update_build_config(build_config, field_value, field_name)\n\n return build_config\n" + "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_PROVIDERS_DICT,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import (\n ToolCallingAgentComponent,\n)\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n *LCToolsAgentComponent._base_inputs,\n *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n llm_model, display_name = self.get_llm()\n self.model_name = get_model_name(llm_model, display_name=display_name)\n if llm_model is None:\n msg = \"No language model selected\"\n raise ValueError(msg)\n self.chat_history = await self.get_memory_data()\n\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n # Convert CurrentDateComponent to a StructuredTool\n current_date_tool = CurrentDateComponent().to_toolkit()[0]\n if isinstance(current_date_tool, StructuredTool):\n self.tools.append(current_date_tool)\n else:\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise ValueError(msg)\n\n if not self.tools:\n msg = \"Tools are required to run the agent.\"\n raise ValueError(msg)\n self.set(\n llm=llm_model,\n tools=self.tools,\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n async def get_memory_data(self):\n memory_kwargs = {\n component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n }\n\n return await MemoryComponent().set(**memory_kwargs).retrieve_messages()\n\n def get_llm(self):\n if isinstance(self.agent_llm, str):\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n return (\n self._build_llm_model(component_class, inputs, prefix),\n display_name,\n )\n except Exception as e:\n msg = f\"Error building {self.agent_llm} language model\"\n raise ValueError(msg) from e\n return self.agent_llm, None\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n return component.set(**model_kwargs).build_model()\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n async def aupdate_build_config(\n self, build_config: dotdict, field_value: str, field_name: str | None = None\n ) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name == \"agent_llm\":\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call the component class's aupdate_build_config method\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if isinstance(self.agent_llm, str) and self.agent_llm in MODEL_PROVIDERS_DICT:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"aupdate_build_config\"):\n # Call each component class's aupdate_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = await component_class.aupdate_build_config(build_config, field_value, field_name)\n\n return build_config\n" }, "handle_parsing_errors": { "_input_type": "BoolInput", diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Twitter Thread Generator.json b/src/backend/base/langflow/initial_setup/starter_projects/Twitter Thread Generator.json index 4e86d5efa..ab80aa382 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Twitter Thread Generator.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Twitter Thread Generator.json @@ -742,7 +742,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { "_input_type": "MessageInput", @@ -862,41 +862,6 @@ "type": "str", "value": "" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, @@ -1991,7 +1956,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "template": { "_input_type": "PromptInput", diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json b/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json index 0b2b92dba..ed12de346 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json @@ -771,7 +771,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n MessageTextInput(\n name=\"tool_placeholder\",\n display_name=\"Tool Placeholder\",\n tool_mode=True,\n advanced=True,\n info=\"A placeholder input for tool mode.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(self) -> Message:\n prompt = Message.from_template(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"This function is called after the code validation is done.\"\"\"\n frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n" }, "context": { "advanced": false, @@ -1192,7 +1192,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\nfrom langflow.inputs.inputs import HandleInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. \"\n \"You must pass the word JSON in the prompt. \"\n \"If left blank, JSON mode will be disabled. [DEPRECATED]\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n HandleInput(\n name=\"output_parser\",\n display_name=\"Output Parser\",\n info=\"The parser to use to parse the output of the model\",\n advanced=True,\n input_types=[\"OutputParser\"],\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n # self.output_schema is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict) or self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n if output_schema_dict:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n else:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" + "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n name = \"OpenAIModel\"\n\n inputs = [\n *LCModelComponent._base_inputs,\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n range_spec=RangeSpec(min=0, max=128000),\n ),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n advanced=True,\n info=\"If True, it will output JSON regardless of passing a schema.\",\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n advanced=False,\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. \"\n \"Defaults to https://api.openai.com/v1. \"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n SliderInput(\n name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel: # type: ignore[type-var]\n openai_api_key = self.api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n\n api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature if temperature is not None else 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.bind(response_format={\"type\": \"json_object\"})\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"Get a message from an OpenAI exception.\n\n Args:\n e (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n try:\n from openai import BadRequestError\n except ImportError:\n return None\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\")\n if message:\n return message\n return None\n" }, "input_value": { "_input_type": "MessageInput", @@ -1312,41 +1312,6 @@ "type": "str", "value": "" }, - "output_parser": { - "_input_type": "HandleInput", - "advanced": true, - "display_name": "Output Parser", - "dynamic": false, - "info": "The parser to use to parse the output of the model", - "input_types": [ - "OutputParser" - ], - "list": false, - "name": "output_parser", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "output_schema": { - "_input_type": "DictInput", - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled. [DEPRECATED]", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, "seed": { "_input_type": "IntInput", "advanced": true, @@ -3236,7 +3201,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import os\nfrom collections import defaultdict\n\nimport orjson\nfrom astrapy import DataAPIClient\nfrom astrapy.admin import parse_api_endpoint\nfrom langchain_astradb import AstraDBVectorStore\n\nfrom langflow.base.vectorstores.model import LCVectorStoreComponent, check_cached_vector_store\nfrom langflow.helpers import docs_to_data\nfrom langflow.inputs import DictInput, FloatInput, MessageTextInput, NestedDictInput\nfrom langflow.io import (\n BoolInput,\n DataInput,\n DropdownInput,\n HandleInput,\n IntInput,\n MultilineInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.schema import Data\nfrom langflow.utils.version import get_version_info\n\n\nclass AstraDBVectorStoreComponent(LCVectorStoreComponent):\n display_name: str = \"Astra DB\"\n description: str = \"Implementation of Vector Store using Astra DB with search capabilities\"\n documentation: str = \"https://docs.langflow.org/starter-projects-vector-store-rag\"\n name = \"AstraDB\"\n icon: str = \"AstraDB\"\n\n _cached_vector_store: AstraDBVectorStore | None = None\n\n VECTORIZE_PROVIDERS_MAPPING = defaultdict(\n list,\n {\n \"Azure OpenAI\": [\n \"azureOpenAI\",\n [\"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"],\n ],\n \"Hugging Face - Dedicated\": [\"huggingfaceDedicated\", [\"endpoint-defined-model\"]],\n \"Hugging Face - Serverless\": [\n \"huggingface\",\n [\n \"sentence-transformers/all-MiniLM-L6-v2\",\n \"intfloat/multilingual-e5-large\",\n \"intfloat/multilingual-e5-large-instruct\",\n \"BAAI/bge-small-en-v1.5\",\n \"BAAI/bge-base-en-v1.5\",\n \"BAAI/bge-large-en-v1.5\",\n ],\n ],\n \"Jina AI\": [\n \"jinaAI\",\n [\n \"jina-embeddings-v2-base-en\",\n \"jina-embeddings-v2-base-de\",\n \"jina-embeddings-v2-base-es\",\n \"jina-embeddings-v2-base-code\",\n \"jina-embeddings-v2-base-zh\",\n ],\n ],\n \"Mistral AI\": [\"mistral\", [\"mistral-embed\"]],\n \"Nvidia\": [\"nvidia\", [\"NV-Embed-QA\"]],\n \"OpenAI\": [\"openai\", [\"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"]],\n \"Upstage\": [\"upstageAI\", [\"solar-embedding-1-large\"]],\n \"Voyage AI\": [\n \"voyageAI\",\n [\"voyage-large-2-instruct\", \"voyage-law-2\", \"voyage-code-2\", \"voyage-large-2\", \"voyage-2\"],\n ],\n },\n )\n\n inputs = [\n SecretStrInput(\n name=\"token\",\n display_name=\"Astra DB Application Token\",\n info=\"Authentication token for accessing Astra DB.\",\n value=\"ASTRA_DB_APPLICATION_TOKEN\",\n required=True,\n advanced=os.getenv(\"ASTRA_ENHANCED\", \"false\").lower() == \"true\",\n real_time_refresh=True,\n ),\n SecretStrInput(\n name=\"api_endpoint\",\n display_name=\"Database\" if os.getenv(\"ASTRA_ENHANCED\", \"false\").lower() == \"true\" else \"API Endpoint\",\n info=\"API endpoint URL for the Astra DB service.\",\n value=\"ASTRA_DB_API_ENDPOINT\",\n required=True,\n real_time_refresh=True,\n ),\n DropdownInput(\n name=\"collection_name\",\n display_name=\"Collection\",\n info=\"The name of the collection within Astra DB where the vectors will be stored.\",\n required=True,\n refresh_button=True,\n real_time_refresh=True,\n options=[\"+ Create new collection\"],\n value=\"+ Create new collection\",\n ),\n StrInput(\n name=\"collection_name_new\",\n display_name=\"Collection Name\",\n info=\"Name of the new collection to create.\",\n advanced=os.getenv(\"LANGFLOW_HOST\") is not None,\n required=os.getenv(\"LANGFLOW_HOST\") is None,\n ),\n StrInput(\n name=\"keyspace\",\n display_name=\"Keyspace\",\n info=\"Optional keyspace within Astra DB to use for the collection.\",\n advanced=True,\n ),\n MultilineInput(\n name=\"search_input\",\n display_name=\"Search Input\",\n ),\n IntInput(\n name=\"number_of_results\",\n display_name=\"Number of Results\",\n info=\"Number of results to return.\",\n advanced=True,\n value=4,\n ),\n DropdownInput(\n name=\"search_type\",\n display_name=\"Search Type\",\n info=\"Search type to use\",\n options=[\"Similarity\", \"Similarity with score threshold\", \"MMR (Max Marginal Relevance)\"],\n value=\"Similarity\",\n advanced=True,\n ),\n FloatInput(\n name=\"search_score_threshold\",\n display_name=\"Search Score Threshold\",\n info=\"Minimum similarity score threshold for search results. \"\n \"(when using 'Similarity with score threshold')\",\n value=0,\n advanced=True,\n ),\n NestedDictInput(\n name=\"advanced_search_filter\",\n display_name=\"Search Metadata Filter\",\n info=\"Optional dictionary of filters to apply to the search query.\",\n advanced=True,\n ),\n DictInput(\n name=\"search_filter\",\n display_name=\"[DEPRECATED] Search Metadata Filter\",\n info=\"Deprecated: use advanced_search_filter. Optional dictionary of filters to apply to the search query.\",\n advanced=True,\n list=True,\n ),\n DataInput(\n name=\"ingest_data\",\n display_name=\"Ingest Data\",\n ),\n DropdownInput(\n name=\"embedding_choice\",\n display_name=\"Embedding Model or Astra Vectorize\",\n info=\"Determines whether to use Astra Vectorize for the collection.\",\n options=[\"Embedding Model\", \"Astra Vectorize\"],\n real_time_refresh=True,\n value=\"Embedding Model\",\n ),\n HandleInput(\n name=\"embedding_model\",\n display_name=\"Embedding Model\",\n input_types=[\"Embeddings\"],\n info=\"Allows an embedding model configuration.\",\n ),\n DropdownInput(\n name=\"metric\",\n display_name=\"Metric\",\n info=\"Optional distance metric for vector comparisons in the vector store.\",\n options=[\"cosine\", \"dot_product\", \"euclidean\"],\n value=\"cosine\",\n advanced=True,\n ),\n IntInput(\n name=\"batch_size\",\n display_name=\"Batch Size\",\n info=\"Optional number of data to process in a single batch.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_batch_concurrency\",\n display_name=\"Bulk Insert Batch Concurrency\",\n info=\"Optional concurrency level for bulk insert operations.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_overwrite_concurrency\",\n display_name=\"Bulk Insert Overwrite Concurrency\",\n info=\"Optional concurrency level for bulk insert operations that overwrite existing data.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_delete_concurrency\",\n display_name=\"Bulk Delete Concurrency\",\n info=\"Optional concurrency level for bulk delete operations.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"setup_mode\",\n display_name=\"Setup Mode\",\n info=\"Configuration mode for setting up the vector store, with options like 'Sync' or 'Off'.\",\n options=[\"Sync\", \"Off\"],\n advanced=True,\n value=\"Sync\",\n ),\n BoolInput(\n name=\"pre_delete_collection\",\n display_name=\"Pre Delete Collection\",\n info=\"Boolean flag to determine whether to delete the collection before creating a new one.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_include\",\n display_name=\"Metadata Indexing Include\",\n info=\"Optional list of metadata fields to include in the indexing.\",\n list=True,\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_exclude\",\n display_name=\"Metadata Indexing Exclude\",\n info=\"Optional list of metadata fields to exclude from the indexing.\",\n list=True,\n advanced=True,\n ),\n StrInput(\n name=\"collection_indexing_policy\",\n display_name=\"Collection Indexing Policy\",\n info='Optional JSON string for the \"indexing\" field of the collection. '\n \"See https://docs.datastax.com/en/astra-db-serverless/api-reference/collections.html#the-indexing-option\",\n advanced=True,\n ),\n ]\n\n def del_fields(self, build_config, field_list):\n for field in field_list:\n if field in build_config:\n del build_config[field]\n\n return build_config\n\n def insert_in_dict(self, build_config, field_name, new_parameters):\n # Insert the new key-value pair after the found key\n for new_field_name, new_parameter in new_parameters.items():\n # Get all the items as a list of tuples (key, value)\n items = list(build_config.items())\n\n # Find the index of the key to insert after\n idx = len(items)\n for i, (key, _) in enumerate(items):\n if key == field_name:\n idx = i + 1\n break\n\n items.insert(idx, (new_field_name, new_parameter))\n\n # Clear the original dictionary and update with the modified items\n build_config.clear()\n build_config.update(items)\n\n return build_config\n\n def update_providers_mapping(self):\n # If we don't have token or api_endpoint, we can't fetch the list of providers\n if not self.token or not self.api_endpoint:\n self.log(\"Astra DB token and API endpoint are required to fetch the list of Vectorize providers.\")\n\n return self.VECTORIZE_PROVIDERS_MAPPING\n\n try:\n self.log(\"Dynamically updating list of Vectorize providers.\")\n\n # Get the admin object\n client = DataAPIClient(token=self.token)\n admin = client.get_admin()\n\n # Get the embedding providers\n db_admin = admin.get_database_admin(self.api_endpoint)\n embedding_providers = db_admin.find_embedding_providers().as_dict()\n\n vectorize_providers_mapping = {}\n\n # Map the provider display name to the provider key and models\n for provider_key, provider_data in embedding_providers[\"embeddingProviders\"].items():\n display_name = provider_data[\"displayName\"]\n models = [model[\"name\"] for model in provider_data[\"models\"]]\n\n vectorize_providers_mapping[display_name] = [provider_key, models]\n\n # Sort the resulting dictionary\n return defaultdict(list, dict(sorted(vectorize_providers_mapping.items())))\n except Exception as e: # noqa: BLE001\n self.log(f\"Error fetching Vectorize providers: {e}\")\n\n return self.VECTORIZE_PROVIDERS_MAPPING\n\n def get_database(self):\n try:\n client = DataAPIClient(token=self.token)\n\n return client.get_database(\n self.api_endpoint,\n token=self.token,\n )\n except Exception as e: # noqa: BLE001\n self.log(f\"Error getting database: {e}\")\n\n return None\n\n def _initialize_collection_options(self):\n database = self.get_database()\n if database is None:\n return [\"+ Create new collection\"]\n\n try:\n collections = [collection.name for collection in database.list_collections()]\n except Exception as e: # noqa: BLE001\n self.log(f\"Error fetching collections: {e}\")\n\n return [\"+ Create new collection\"]\n\n return [*collections, \"+ Create new collection\"]\n\n def get_collection_choice(self):\n collection_name = self.collection_name\n if collection_name == \"+ Create new collection\":\n return self.collection_name_new\n\n return collection_name\n\n def get_collection_options(self):\n # Only get the options if the collection exists\n database = self.get_database()\n if database is None:\n return None\n\n collection_name = self.get_collection_choice()\n\n try:\n collection = database.get_collection(collection_name)\n collection_options = collection.options()\n except Exception as _: # noqa: BLE001\n return None\n\n return collection_options.vector\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n # Refresh the collection name options\n build_config[\"collection_name\"][\"options\"] = self._initialize_collection_options()\n\n # If the collection name is set to \"+ Create new collection\", show embedding choice\n if field_name == \"collection_name\" and field_value == \"+ Create new collection\":\n build_config[\"embedding_choice\"][\"advanced\"] = False\n build_config[\"embedding_choice\"][\"value\"] = \"Embedding Model\"\n build_config[\"embedding_model\"][\"advanced\"] = False\n\n build_config[\"collection_name_new\"][\"advanced\"] = False\n build_config[\"collection_name_new\"][\"required\"] = True\n\n # But if it's not, hide embedding choice\n elif field_name == \"collection_name\" and field_value != \"+ Create new collection\":\n build_config[\"embedding_choice\"][\"advanced\"] = True\n\n build_config[\"collection_name_new\"][\"advanced\"] = True\n build_config[\"collection_name_new\"][\"required\"] = False\n build_config[\"collection_name_new\"][\"value\"] = \"\"\n\n # Get the collection options for the selected collection\n collection_options = self.get_collection_options()\n\n # If the collection options are available (DB exists), show the advanced options\n if collection_options:\n build_config[\"embedding_choice\"][\"advanced\"] = True\n\n if collection_options.service:\n self.del_fields(\n build_config,\n [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ],\n )\n\n build_config[\"embedding_model\"][\"advanced\"] = True\n build_config[\"embedding_choice\"][\"value\"] = \"Astra Vectorize\"\n else:\n build_config[\"embedding_model\"][\"advanced\"] = False\n build_config[\"embedding_provider\"][\"advanced\"] = False\n build_config[\"embedding_choice\"][\"value\"] = \"Embedding Model\"\n\n elif field_name == \"embedding_choice\":\n if field_value == \"Astra Vectorize\":\n build_config[\"embedding_model\"][\"advanced\"] = True\n\n # Update the providers mapping\n vectorize_providers = self.update_providers_mapping()\n\n new_parameter = DropdownInput(\n name=\"embedding_provider\",\n display_name=\"Embedding Provider\",\n options=vectorize_providers.keys(),\n value=\"\",\n required=True,\n real_time_refresh=True,\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_choice\", {\"embedding_provider\": new_parameter})\n else:\n build_config[\"embedding_model\"][\"advanced\"] = False\n\n self.del_fields(\n build_config,\n [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ],\n )\n\n elif field_name == \"embedding_provider\":\n self.del_fields(\n build_config,\n [\"model\", \"z_01_model_parameters\", \"z_02_api_key_name\", \"z_03_provider_api_key\", \"z_04_authentication\"],\n )\n\n # Update the providers mapping\n vectorize_providers = self.update_providers_mapping()\n model_options = vectorize_providers[field_value][1]\n\n new_parameter = DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n info=\"The embedding model to use for the selected provider. Each provider has a different set of \"\n \"models available (full list at \"\n \"https://docs.datastax.com/en/astra-db-serverless/databases/embedding-generation.html):\\n\\n\"\n f\"{', '.join(model_options)}\",\n options=model_options,\n value=None,\n required=True,\n real_time_refresh=True,\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_provider\", {\"model\": new_parameter})\n\n elif field_name == \"model\":\n self.del_fields(\n build_config,\n [\"z_01_model_parameters\", \"z_02_api_key_name\", \"z_03_provider_api_key\", \"z_04_authentication\"],\n )\n\n new_parameter_1 = DictInput(\n name=\"z_01_model_parameters\",\n display_name=\"Model Parameters\",\n list=True,\n ).to_dict()\n\n new_parameter_2 = MessageTextInput(\n name=\"z_02_api_key_name\",\n display_name=\"API Key Name\",\n info=\"The name of the embeddings provider API key stored on Astra. \"\n \"If set, it will override the 'ProviderKey' in the authentication parameters.\",\n ).to_dict()\n\n new_parameter_3 = SecretStrInput(\n load_from_db=False,\n name=\"z_03_provider_api_key\",\n display_name=\"Provider API Key\",\n info=\"An alternative to the Astra Authentication that passes an API key for the provider \"\n \"with each request to Astra DB. \"\n \"This may be used when Vectorize is configured for the collection, \"\n \"but no corresponding provider secret is stored within Astra's key management system.\",\n ).to_dict()\n\n new_parameter_4 = DictInput(\n name=\"z_04_authentication\",\n display_name=\"Authentication Parameters\",\n list=True,\n ).to_dict()\n\n self.insert_in_dict(\n build_config,\n \"model\",\n {\n \"z_01_model_parameters\": new_parameter_1,\n \"z_02_api_key_name\": new_parameter_2,\n \"z_03_provider_api_key\": new_parameter_3,\n \"z_04_authentication\": new_parameter_4,\n },\n )\n\n return build_config\n\n def build_vectorize_options(self, **kwargs):\n for attribute in [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ]:\n if not hasattr(self, attribute):\n setattr(self, attribute, None)\n\n # Fetch values from kwargs if any self.* attributes are None\n provider_mapping = self.update_providers_mapping()\n provider_value = provider_mapping.get(self.embedding_provider, [None])[0] or kwargs.get(\"embedding_provider\")\n model_name = self.model or kwargs.get(\"model\")\n authentication = {**(self.z_04_authentication or {}), **kwargs.get(\"z_04_authentication\", {})}\n parameters = self.z_01_model_parameters or kwargs.get(\"z_01_model_parameters\", {})\n\n # Set the API key name if provided\n api_key_name = self.z_02_api_key_name or kwargs.get(\"z_02_api_key_name\")\n provider_key = self.z_03_provider_api_key or kwargs.get(\"z_03_provider_api_key\")\n if api_key_name:\n authentication[\"providerKey\"] = api_key_name\n if authentication:\n provider_key = None\n authentication[\"providerKey\"] = authentication[\"providerKey\"].split(\".\")[0]\n\n # Set authentication and parameters to None if no values are provided\n if not authentication:\n authentication = None\n if not parameters:\n parameters = None\n\n return {\n # must match astrapy.info.CollectionVectorServiceOptions\n \"collection_vector_service_options\": {\n \"provider\": provider_value,\n \"modelName\": model_name,\n \"authentication\": authentication,\n \"parameters\": parameters,\n },\n \"collection_embedding_api_key\": provider_key,\n }\n\n @check_cached_vector_store\n def build_vector_store(self, vectorize_options=None):\n try:\n from langchain_astradb import AstraDBVectorStore\n from langchain_astradb.utils.astradb import SetupMode\n except ImportError as e:\n msg = (\n \"Could not import langchain Astra DB integration package. \"\n \"Please install it with `pip install langchain-astradb`.\"\n )\n raise ImportError(msg) from e\n\n try:\n if not self.setup_mode:\n self.setup_mode = self._inputs[\"setup_mode\"].options[0]\n\n setup_mode_value = SetupMode[self.setup_mode.upper()]\n except KeyError as e:\n msg = f\"Invalid setup mode: {self.setup_mode}\"\n raise ValueError(msg) from e\n\n metric_value = self.metric or None\n autodetect = False\n\n if self.embedding_choice == \"Embedding Model\":\n embedding_dict = {\"embedding\": self.embedding_model}\n # Use autodetect if the collection name is NOT set to \"+ Create new collection\"\n elif self.collection_name != \"+ Create new collection\":\n autodetect = True\n metric_value = None\n setup_mode_value = None\n embedding_dict = {}\n else:\n from astrapy.info import CollectionVectorServiceOptions\n\n # Grab the collection options if available\n collection_options = self.get_collection_options()\n\n # Ensure collection_options and its nested attributes are handled safely\n authentication = getattr(self, \"z_04_authentication\", {}) or (\n collection_options.service.authentication\n if collection_options and collection_options.service and collection_options.service.authentication\n else {}\n )\n\n # Build the vectorize options dictionary\n dict_options = vectorize_options or self.build_vectorize_options(\n embedding_provider=(\n getattr(self, \"embedding_provider\", None)\n or (\n collection_options.service.provider\n if collection_options and collection_options.service\n else None\n )\n ),\n model=(\n getattr(self, \"model\", None)\n or (\n collection_options.service.model_name\n if collection_options and collection_options.service\n else None\n )\n ),\n z_01_model_parameters=(\n getattr(self, \"z_01_model_parameters\", None)\n or (\n collection_options.service.parameters\n if collection_options and collection_options.service\n else None\n )\n ),\n z_02_api_key_name=(\n getattr(self, \"z_02_api_key_name\", None)\n or (authentication.get(\"apiKey\") if authentication else None)\n ),\n z_03_provider_api_key=(\n getattr(self, \"z_03_provider_api_key\", None)\n or (authentication.get(\"providerKey\") if authentication else None)\n ),\n z_04_authentication=authentication,\n )\n\n # Set the embedding dictionary\n embedding_dict = {\n \"collection_vector_service_options\": CollectionVectorServiceOptions.from_dict(\n dict_options.get(\"collection_vector_service_options\")\n ),\n \"collection_embedding_api_key\": dict_options.get(\"collection_embedding_api_key\"),\n }\n\n # Get Langflow version and platform information\n __version__ = get_version_info()[\"version\"]\n langflow_prefix = \"\"\n if os.getenv(\"LANGFLOW_HOST\") is not None:\n langflow_prefix = \"ds-\"\n\n try:\n vector_store = AstraDBVectorStore(\n token=self.token,\n api_endpoint=self.api_endpoint,\n namespace=self.keyspace or None,\n collection_name=self.get_collection_choice(),\n autodetect_collection=autodetect,\n environment=(\n parse_api_endpoint(getattr(self, \"api_endpoint\", None)).environment\n if getattr(self, \"api_endpoint\", None)\n else None\n ),\n metric=metric_value,\n batch_size=self.batch_size or None,\n bulk_insert_batch_concurrency=self.bulk_insert_batch_concurrency or None,\n bulk_insert_overwrite_concurrency=self.bulk_insert_overwrite_concurrency or None,\n bulk_delete_concurrency=self.bulk_delete_concurrency or None,\n setup_mode=setup_mode_value,\n pre_delete_collection=self.pre_delete_collection,\n metadata_indexing_include=[s for s in self.metadata_indexing_include if s] or None,\n metadata_indexing_exclude=[s for s in self.metadata_indexing_exclude if s] or None,\n collection_indexing_policy=orjson.dumps(self.collection_indexing_policy)\n if self.collection_indexing_policy\n else None,\n ext_callers=[(f\"{langflow_prefix}langflow\", __version__)],\n **embedding_dict,\n )\n except Exception as e:\n msg = f\"Error initializing AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n\n self._add_documents_to_vector_store(vector_store)\n\n return vector_store\n\n def _add_documents_to_vector_store(self, vector_store) -> None:\n documents = []\n for _input in self.ingest_data or []:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n else:\n msg = \"Vector Store Inputs must be Data objects.\"\n raise TypeError(msg)\n\n if documents:\n self.log(f\"Adding {len(documents)} documents to the Vector Store.\")\n try:\n vector_store.add_documents(documents)\n except Exception as e:\n msg = f\"Error adding documents to AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n else:\n self.log(\"No documents to add to the Vector Store.\")\n\n def _map_search_type(self) -> str:\n if self.search_type == \"Similarity with score threshold\":\n return \"similarity_score_threshold\"\n if self.search_type == \"MMR (Max Marginal Relevance)\":\n return \"mmr\"\n return \"similarity\"\n\n def _build_search_args(self):\n query = self.search_input if isinstance(self.search_input, str) and self.search_input.strip() else None\n search_filter = (\n {k: v for k, v in self.search_filter.items() if k and v and k.strip()} if self.search_filter else None\n )\n\n if query:\n args = {\n \"query\": query,\n \"search_type\": self._map_search_type(),\n \"k\": self.number_of_results,\n \"score_threshold\": self.search_score_threshold,\n }\n elif self.advanced_search_filter or search_filter:\n args = {\n \"n\": self.number_of_results,\n }\n else:\n return {}\n\n filter_arg = self.advanced_search_filter or {}\n\n if search_filter:\n self.log(self.log(f\"`search_filter` is deprecated. Use `advanced_search_filter`. Cleaned: {search_filter}\"))\n filter_arg.update(search_filter)\n\n if filter_arg:\n args[\"filter\"] = filter_arg\n\n return args\n\n def search_documents(self, vector_store=None) -> list[Data]:\n vector_store = vector_store or self.build_vector_store()\n\n self.log(f\"Search input: {self.search_input}\")\n self.log(f\"Search type: {self.search_type}\")\n self.log(f\"Number of results: {self.number_of_results}\")\n\n try:\n search_args = self._build_search_args()\n except Exception as e:\n msg = f\"Error in AstraDBVectorStore._build_search_args: {e}\"\n raise ValueError(msg) from e\n\n if not search_args:\n self.log(\"No search input or filters provided. Skipping search.\")\n return []\n\n docs = []\n search_method = \"search\" if \"query\" in search_args else \"metadata_search\"\n\n try:\n self.log(f\"Calling vector_store.{search_method} with args: {search_args}\")\n docs = getattr(vector_store, search_method)(**search_args)\n except Exception as e:\n msg = f\"Error performing {search_method} in AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n\n self.log(f\"Retrieved documents: {len(docs)}\")\n\n data = docs_to_data(docs)\n self.log(f\"Converted documents to data: {len(data)}\")\n self.status = data\n return data\n\n def get_retriever_kwargs(self):\n search_args = self._build_search_args()\n return {\n \"search_type\": self._map_search_type(),\n \"search_kwargs\": search_args,\n }\n" + "value": "import os\nfrom collections import defaultdict\n\nimport orjson\nfrom astrapy import DataAPIClient\nfrom astrapy.admin import parse_api_endpoint\nfrom langchain_astradb import AstraDBVectorStore\n\nfrom langflow.base.vectorstores.model import LCVectorStoreComponent, check_cached_vector_store\nfrom langflow.helpers import docs_to_data\nfrom langflow.inputs import DictInput, FloatInput, MessageTextInput, NestedDictInput\nfrom langflow.io import (\n BoolInput,\n DataInput,\n DropdownInput,\n HandleInput,\n IntInput,\n MultilineInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.schema import Data\nfrom langflow.utils.version import get_version_info\n\n\nclass AstraDBVectorStoreComponent(LCVectorStoreComponent):\n display_name: str = \"Astra DB\"\n description: str = \"Implementation of Vector Store using Astra DB with search capabilities\"\n documentation: str = \"https://docs.langflow.org/starter-projects-vector-store-rag\"\n name = \"AstraDB\"\n icon: str = \"AstraDB\"\n\n _cached_vector_store: AstraDBVectorStore | None = None\n\n VECTORIZE_PROVIDERS_MAPPING = defaultdict(\n list,\n {\n \"Azure OpenAI\": [\n \"azureOpenAI\",\n [\"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"],\n ],\n \"Hugging Face - Dedicated\": [\"huggingfaceDedicated\", [\"endpoint-defined-model\"]],\n \"Hugging Face - Serverless\": [\n \"huggingface\",\n [\n \"sentence-transformers/all-MiniLM-L6-v2\",\n \"intfloat/multilingual-e5-large\",\n \"intfloat/multilingual-e5-large-instruct\",\n \"BAAI/bge-small-en-v1.5\",\n \"BAAI/bge-base-en-v1.5\",\n \"BAAI/bge-large-en-v1.5\",\n ],\n ],\n \"Jina AI\": [\n \"jinaAI\",\n [\n \"jina-embeddings-v2-base-en\",\n \"jina-embeddings-v2-base-de\",\n \"jina-embeddings-v2-base-es\",\n \"jina-embeddings-v2-base-code\",\n \"jina-embeddings-v2-base-zh\",\n ],\n ],\n \"Mistral AI\": [\"mistral\", [\"mistral-embed\"]],\n \"Nvidia\": [\"nvidia\", [\"NV-Embed-QA\"]],\n \"OpenAI\": [\"openai\", [\"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"]],\n \"Upstage\": [\"upstageAI\", [\"solar-embedding-1-large\"]],\n \"Voyage AI\": [\n \"voyageAI\",\n [\"voyage-large-2-instruct\", \"voyage-law-2\", \"voyage-code-2\", \"voyage-large-2\", \"voyage-2\"],\n ],\n },\n )\n\n inputs = [\n SecretStrInput(\n name=\"token\",\n display_name=\"Astra DB Application Token\",\n info=\"Authentication token for accessing Astra DB.\",\n value=\"ASTRA_DB_APPLICATION_TOKEN\",\n required=True,\n advanced=os.getenv(\"ASTRA_ENHANCED\", \"false\").lower() == \"true\",\n real_time_refresh=True,\n ),\n SecretStrInput(\n name=\"api_endpoint\",\n display_name=\"Database\" if os.getenv(\"ASTRA_ENHANCED\", \"false\").lower() == \"true\" else \"API Endpoint\",\n info=\"API endpoint URL for the Astra DB service.\",\n value=\"ASTRA_DB_API_ENDPOINT\",\n required=True,\n real_time_refresh=True,\n ),\n DropdownInput(\n name=\"collection_name\",\n display_name=\"Collection\",\n info=\"The name of the collection within Astra DB where the vectors will be stored.\",\n required=True,\n refresh_button=True,\n real_time_refresh=True,\n options=[\"+ Create new collection\"],\n value=\"+ Create new collection\",\n ),\n StrInput(\n name=\"collection_name_new\",\n display_name=\"Collection Name\",\n info=\"Name of the new collection to create.\",\n advanced=os.getenv(\"LANGFLOW_HOST\") is not None,\n required=os.getenv(\"LANGFLOW_HOST\") is None,\n ),\n StrInput(\n name=\"keyspace\",\n display_name=\"Keyspace\",\n info=\"Optional keyspace within Astra DB to use for the collection.\",\n advanced=True,\n ),\n MultilineInput(\n name=\"search_input\",\n display_name=\"Search Input\",\n tool_mode=True,\n ),\n IntInput(\n name=\"number_of_results\",\n display_name=\"Number of Results\",\n info=\"Number of results to return.\",\n advanced=True,\n value=4,\n ),\n DropdownInput(\n name=\"search_type\",\n display_name=\"Search Type\",\n info=\"Search type to use\",\n options=[\"Similarity\", \"Similarity with score threshold\", \"MMR (Max Marginal Relevance)\"],\n value=\"Similarity\",\n advanced=True,\n ),\n FloatInput(\n name=\"search_score_threshold\",\n display_name=\"Search Score Threshold\",\n info=\"Minimum similarity score threshold for search results. \"\n \"(when using 'Similarity with score threshold')\",\n value=0,\n advanced=True,\n ),\n NestedDictInput(\n name=\"advanced_search_filter\",\n display_name=\"Search Metadata Filter\",\n info=\"Optional dictionary of filters to apply to the search query.\",\n advanced=True,\n ),\n DictInput(\n name=\"search_filter\",\n display_name=\"[DEPRECATED] Search Metadata Filter\",\n info=\"Deprecated: use advanced_search_filter. Optional dictionary of filters to apply to the search query.\",\n advanced=True,\n list=True,\n ),\n DataInput(\n name=\"ingest_data\",\n display_name=\"Ingest Data\",\n ),\n DropdownInput(\n name=\"embedding_choice\",\n display_name=\"Embedding Model or Astra Vectorize\",\n info=\"Determines whether to use Astra Vectorize for the collection.\",\n options=[\"Embedding Model\", \"Astra Vectorize\"],\n real_time_refresh=True,\n value=\"Embedding Model\",\n ),\n HandleInput(\n name=\"embedding_model\",\n display_name=\"Embedding Model\",\n input_types=[\"Embeddings\"],\n info=\"Allows an embedding model configuration.\",\n ),\n DropdownInput(\n name=\"metric\",\n display_name=\"Metric\",\n info=\"Optional distance metric for vector comparisons in the vector store.\",\n options=[\"cosine\", \"dot_product\", \"euclidean\"],\n value=\"cosine\",\n advanced=True,\n ),\n IntInput(\n name=\"batch_size\",\n display_name=\"Batch Size\",\n info=\"Optional number of data to process in a single batch.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_batch_concurrency\",\n display_name=\"Bulk Insert Batch Concurrency\",\n info=\"Optional concurrency level for bulk insert operations.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_overwrite_concurrency\",\n display_name=\"Bulk Insert Overwrite Concurrency\",\n info=\"Optional concurrency level for bulk insert operations that overwrite existing data.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_delete_concurrency\",\n display_name=\"Bulk Delete Concurrency\",\n info=\"Optional concurrency level for bulk delete operations.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"setup_mode\",\n display_name=\"Setup Mode\",\n info=\"Configuration mode for setting up the vector store, with options like 'Sync' or 'Off'.\",\n options=[\"Sync\", \"Off\"],\n advanced=True,\n value=\"Sync\",\n ),\n BoolInput(\n name=\"pre_delete_collection\",\n display_name=\"Pre Delete Collection\",\n info=\"Boolean flag to determine whether to delete the collection before creating a new one.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_include\",\n display_name=\"Metadata Indexing Include\",\n info=\"Optional list of metadata fields to include in the indexing.\",\n list=True,\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_exclude\",\n display_name=\"Metadata Indexing Exclude\",\n info=\"Optional list of metadata fields to exclude from the indexing.\",\n list=True,\n advanced=True,\n ),\n StrInput(\n name=\"collection_indexing_policy\",\n display_name=\"Collection Indexing Policy\",\n info='Optional JSON string for the \"indexing\" field of the collection. '\n \"See https://docs.datastax.com/en/astra-db-serverless/api-reference/collections.html#the-indexing-option\",\n advanced=True,\n ),\n ]\n\n def del_fields(self, build_config, field_list):\n for field in field_list:\n if field in build_config:\n del build_config[field]\n\n return build_config\n\n def insert_in_dict(self, build_config, field_name, new_parameters):\n # Insert the new key-value pair after the found key\n for new_field_name, new_parameter in new_parameters.items():\n # Get all the items as a list of tuples (key, value)\n items = list(build_config.items())\n\n # Find the index of the key to insert after\n idx = len(items)\n for i, (key, _) in enumerate(items):\n if key == field_name:\n idx = i + 1\n break\n\n items.insert(idx, (new_field_name, new_parameter))\n\n # Clear the original dictionary and update with the modified items\n build_config.clear()\n build_config.update(items)\n\n return build_config\n\n def update_providers_mapping(self):\n # If we don't have token or api_endpoint, we can't fetch the list of providers\n if not self.token or not self.api_endpoint:\n self.log(\"Astra DB token and API endpoint are required to fetch the list of Vectorize providers.\")\n\n return self.VECTORIZE_PROVIDERS_MAPPING\n\n try:\n self.log(\"Dynamically updating list of Vectorize providers.\")\n\n # Get the admin object\n client = DataAPIClient(token=self.token)\n admin = client.get_admin()\n\n # Get the embedding providers\n db_admin = admin.get_database_admin(self.api_endpoint)\n embedding_providers = db_admin.find_embedding_providers().as_dict()\n\n vectorize_providers_mapping = {}\n\n # Map the provider display name to the provider key and models\n for provider_key, provider_data in embedding_providers[\"embeddingProviders\"].items():\n display_name = provider_data[\"displayName\"]\n models = [model[\"name\"] for model in provider_data[\"models\"]]\n\n vectorize_providers_mapping[display_name] = [provider_key, models]\n\n # Sort the resulting dictionary\n return defaultdict(list, dict(sorted(vectorize_providers_mapping.items())))\n except Exception as e: # noqa: BLE001\n self.log(f\"Error fetching Vectorize providers: {e}\")\n\n return self.VECTORIZE_PROVIDERS_MAPPING\n\n def get_database(self):\n try:\n client = DataAPIClient(token=self.token)\n\n return client.get_database(\n self.api_endpoint,\n token=self.token,\n )\n except Exception as e: # noqa: BLE001\n self.log(f\"Error getting database: {e}\")\n\n return None\n\n def _initialize_collection_options(self):\n database = self.get_database()\n if database is None:\n return [\"+ Create new collection\"]\n\n try:\n collections = [collection.name for collection in database.list_collections()]\n except Exception as e: # noqa: BLE001\n self.log(f\"Error fetching collections: {e}\")\n\n return [\"+ Create new collection\"]\n\n return [*collections, \"+ Create new collection\"]\n\n def get_collection_choice(self):\n collection_name = self.collection_name\n if collection_name == \"+ Create new collection\":\n return self.collection_name_new\n\n return collection_name\n\n def get_collection_options(self):\n # Only get the options if the collection exists\n database = self.get_database()\n if database is None:\n return None\n\n collection_name = self.get_collection_choice()\n\n try:\n collection = database.get_collection(collection_name)\n collection_options = collection.options()\n except Exception as _: # noqa: BLE001\n return None\n\n return collection_options.vector\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n # Refresh the collection name options\n build_config[\"collection_name\"][\"options\"] = self._initialize_collection_options()\n\n # If the collection name is set to \"+ Create new collection\", show embedding choice\n if field_name == \"collection_name\" and field_value == \"+ Create new collection\":\n build_config[\"embedding_choice\"][\"advanced\"] = False\n build_config[\"embedding_choice\"][\"value\"] = \"Embedding Model\"\n build_config[\"embedding_model\"][\"advanced\"] = False\n\n build_config[\"collection_name_new\"][\"advanced\"] = False\n build_config[\"collection_name_new\"][\"required\"] = True\n\n # But if it's not, hide embedding choice\n elif field_name == \"collection_name\" and field_value != \"+ Create new collection\":\n build_config[\"embedding_choice\"][\"advanced\"] = True\n\n build_config[\"collection_name_new\"][\"advanced\"] = True\n build_config[\"collection_name_new\"][\"required\"] = False\n build_config[\"collection_name_new\"][\"value\"] = \"\"\n\n # Get the collection options for the selected collection\n collection_options = self.get_collection_options()\n\n # If the collection options are available (DB exists), show the advanced options\n if collection_options:\n build_config[\"embedding_choice\"][\"advanced\"] = True\n\n if collection_options.service:\n self.del_fields(\n build_config,\n [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ],\n )\n\n build_config[\"embedding_model\"][\"advanced\"] = True\n build_config[\"embedding_choice\"][\"value\"] = \"Astra Vectorize\"\n else:\n build_config[\"embedding_model\"][\"advanced\"] = False\n build_config[\"embedding_provider\"][\"advanced\"] = False\n build_config[\"embedding_choice\"][\"value\"] = \"Embedding Model\"\n\n elif field_name == \"embedding_choice\":\n if field_value == \"Astra Vectorize\":\n build_config[\"embedding_model\"][\"advanced\"] = True\n\n # Update the providers mapping\n vectorize_providers = self.update_providers_mapping()\n\n new_parameter = DropdownInput(\n name=\"embedding_provider\",\n display_name=\"Embedding Provider\",\n options=vectorize_providers.keys(),\n value=\"\",\n required=True,\n real_time_refresh=True,\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_choice\", {\"embedding_provider\": new_parameter})\n else:\n build_config[\"embedding_model\"][\"advanced\"] = False\n\n self.del_fields(\n build_config,\n [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ],\n )\n\n elif field_name == \"embedding_provider\":\n self.del_fields(\n build_config,\n [\"model\", \"z_01_model_parameters\", \"z_02_api_key_name\", \"z_03_provider_api_key\", \"z_04_authentication\"],\n )\n\n # Update the providers mapping\n vectorize_providers = self.update_providers_mapping()\n model_options = vectorize_providers[field_value][1]\n\n new_parameter = DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n info=\"The embedding model to use for the selected provider. Each provider has a different set of \"\n \"models available (full list at \"\n \"https://docs.datastax.com/en/astra-db-serverless/databases/embedding-generation.html):\\n\\n\"\n f\"{', '.join(model_options)}\",\n options=model_options,\n value=None,\n required=True,\n real_time_refresh=True,\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_provider\", {\"model\": new_parameter})\n\n elif field_name == \"model\":\n self.del_fields(\n build_config,\n [\"z_01_model_parameters\", \"z_02_api_key_name\", \"z_03_provider_api_key\", \"z_04_authentication\"],\n )\n\n new_parameter_1 = DictInput(\n name=\"z_01_model_parameters\",\n display_name=\"Model Parameters\",\n list=True,\n ).to_dict()\n\n new_parameter_2 = MessageTextInput(\n name=\"z_02_api_key_name\",\n display_name=\"API Key Name\",\n info=\"The name of the embeddings provider API key stored on Astra. \"\n \"If set, it will override the 'ProviderKey' in the authentication parameters.\",\n ).to_dict()\n\n new_parameter_3 = SecretStrInput(\n load_from_db=False,\n name=\"z_03_provider_api_key\",\n display_name=\"Provider API Key\",\n info=\"An alternative to the Astra Authentication that passes an API key for the provider \"\n \"with each request to Astra DB. \"\n \"This may be used when Vectorize is configured for the collection, \"\n \"but no corresponding provider secret is stored within Astra's key management system.\",\n ).to_dict()\n\n new_parameter_4 = DictInput(\n name=\"z_04_authentication\",\n display_name=\"Authentication Parameters\",\n list=True,\n ).to_dict()\n\n self.insert_in_dict(\n build_config,\n \"model\",\n {\n \"z_01_model_parameters\": new_parameter_1,\n \"z_02_api_key_name\": new_parameter_2,\n \"z_03_provider_api_key\": new_parameter_3,\n \"z_04_authentication\": new_parameter_4,\n },\n )\n\n return build_config\n\n def build_vectorize_options(self, **kwargs):\n for attribute in [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ]:\n if not hasattr(self, attribute):\n setattr(self, attribute, None)\n\n # Fetch values from kwargs if any self.* attributes are None\n provider_mapping = self.update_providers_mapping()\n provider_value = provider_mapping.get(self.embedding_provider, [None])[0] or kwargs.get(\"embedding_provider\")\n model_name = self.model or kwargs.get(\"model\")\n authentication = {**(self.z_04_authentication or {}), **kwargs.get(\"z_04_authentication\", {})}\n parameters = self.z_01_model_parameters or kwargs.get(\"z_01_model_parameters\", {})\n\n # Set the API key name if provided\n api_key_name = self.z_02_api_key_name or kwargs.get(\"z_02_api_key_name\")\n provider_key = self.z_03_provider_api_key or kwargs.get(\"z_03_provider_api_key\")\n if api_key_name:\n authentication[\"providerKey\"] = api_key_name\n if authentication:\n provider_key = None\n authentication[\"providerKey\"] = authentication[\"providerKey\"].split(\".\")[0]\n\n # Set authentication and parameters to None if no values are provided\n if not authentication:\n authentication = None\n if not parameters:\n parameters = None\n\n return {\n # must match astrapy.info.CollectionVectorServiceOptions\n \"collection_vector_service_options\": {\n \"provider\": provider_value,\n \"modelName\": model_name,\n \"authentication\": authentication,\n \"parameters\": parameters,\n },\n \"collection_embedding_api_key\": provider_key,\n }\n\n @check_cached_vector_store\n def build_vector_store(self, vectorize_options=None):\n try:\n from langchain_astradb import AstraDBVectorStore\n from langchain_astradb.utils.astradb import SetupMode\n except ImportError as e:\n msg = (\n \"Could not import langchain Astra DB integration package. \"\n \"Please install it with `pip install langchain-astradb`.\"\n )\n raise ImportError(msg) from e\n\n try:\n if not self.setup_mode:\n self.setup_mode = self._inputs[\"setup_mode\"].options[0]\n\n setup_mode_value = SetupMode[self.setup_mode.upper()]\n except KeyError as e:\n msg = f\"Invalid setup mode: {self.setup_mode}\"\n raise ValueError(msg) from e\n\n metric_value = self.metric or None\n autodetect = False\n\n if self.embedding_choice == \"Embedding Model\":\n embedding_dict = {\"embedding\": self.embedding_model}\n # Use autodetect if the collection name is NOT set to \"+ Create new collection\"\n elif self.collection_name != \"+ Create new collection\":\n autodetect = True\n metric_value = None\n setup_mode_value = None\n embedding_dict = {}\n else:\n from astrapy.info import CollectionVectorServiceOptions\n\n # Grab the collection options if available\n collection_options = self.get_collection_options()\n\n # Ensure collection_options and its nested attributes are handled safely\n authentication = getattr(self, \"z_04_authentication\", {}) or (\n collection_options.service.authentication\n if collection_options and collection_options.service and collection_options.service.authentication\n else {}\n )\n\n # Build the vectorize options dictionary\n dict_options = vectorize_options or self.build_vectorize_options(\n embedding_provider=(\n getattr(self, \"embedding_provider\", None)\n or (\n collection_options.service.provider\n if collection_options and collection_options.service\n else None\n )\n ),\n model=(\n getattr(self, \"model\", None)\n or (\n collection_options.service.model_name\n if collection_options and collection_options.service\n else None\n )\n ),\n z_01_model_parameters=(\n getattr(self, \"z_01_model_parameters\", None)\n or (\n collection_options.service.parameters\n if collection_options and collection_options.service\n else None\n )\n ),\n z_02_api_key_name=(\n getattr(self, \"z_02_api_key_name\", None)\n or (authentication.get(\"apiKey\") if authentication else None)\n ),\n z_03_provider_api_key=(\n getattr(self, \"z_03_provider_api_key\", None)\n or (authentication.get(\"providerKey\") if authentication else None)\n ),\n z_04_authentication=authentication,\n )\n\n # Set the embedding dictionary\n embedding_dict = {\n \"collection_vector_service_options\": CollectionVectorServiceOptions.from_dict(\n dict_options.get(\"collection_vector_service_options\")\n ),\n \"collection_embedding_api_key\": dict_options.get(\"collection_embedding_api_key\"),\n }\n\n # Get Langflow version and platform information\n __version__ = get_version_info()[\"version\"]\n langflow_prefix = \"\"\n if os.getenv(\"LANGFLOW_HOST\") is not None:\n langflow_prefix = \"ds-\"\n\n try:\n vector_store = AstraDBVectorStore(\n token=self.token,\n api_endpoint=self.api_endpoint,\n namespace=self.keyspace or None,\n collection_name=self.get_collection_choice(),\n autodetect_collection=autodetect,\n environment=(\n parse_api_endpoint(getattr(self, \"api_endpoint\", None)).environment\n if getattr(self, \"api_endpoint\", None)\n else None\n ),\n metric=metric_value,\n batch_size=self.batch_size or None,\n bulk_insert_batch_concurrency=self.bulk_insert_batch_concurrency or None,\n bulk_insert_overwrite_concurrency=self.bulk_insert_overwrite_concurrency or None,\n bulk_delete_concurrency=self.bulk_delete_concurrency or None,\n setup_mode=setup_mode_value,\n pre_delete_collection=self.pre_delete_collection,\n metadata_indexing_include=[s for s in self.metadata_indexing_include if s] or None,\n metadata_indexing_exclude=[s for s in self.metadata_indexing_exclude if s] or None,\n collection_indexing_policy=orjson.dumps(self.collection_indexing_policy)\n if self.collection_indexing_policy\n else None,\n ext_callers=[(f\"{langflow_prefix}langflow\", __version__)],\n **embedding_dict,\n )\n except Exception as e:\n msg = f\"Error initializing AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n\n self._add_documents_to_vector_store(vector_store)\n\n return vector_store\n\n def _add_documents_to_vector_store(self, vector_store) -> None:\n documents = []\n for _input in self.ingest_data or []:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n else:\n msg = \"Vector Store Inputs must be Data objects.\"\n raise TypeError(msg)\n\n if documents:\n self.log(f\"Adding {len(documents)} documents to the Vector Store.\")\n try:\n vector_store.add_documents(documents)\n except Exception as e:\n msg = f\"Error adding documents to AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n else:\n self.log(\"No documents to add to the Vector Store.\")\n\n def _map_search_type(self) -> str:\n if self.search_type == \"Similarity with score threshold\":\n return \"similarity_score_threshold\"\n if self.search_type == \"MMR (Max Marginal Relevance)\":\n return \"mmr\"\n return \"similarity\"\n\n def _build_search_args(self):\n query = self.search_input if isinstance(self.search_input, str) and self.search_input.strip() else None\n search_filter = (\n {k: v for k, v in self.search_filter.items() if k and v and k.strip()} if self.search_filter else None\n )\n\n if query:\n args = {\n \"query\": query,\n \"search_type\": self._map_search_type(),\n \"k\": self.number_of_results,\n \"score_threshold\": self.search_score_threshold,\n }\n elif self.advanced_search_filter or search_filter:\n args = {\n \"n\": self.number_of_results,\n }\n else:\n return {}\n\n filter_arg = self.advanced_search_filter or {}\n\n if search_filter:\n self.log(self.log(f\"`search_filter` is deprecated. Use `advanced_search_filter`. Cleaned: {search_filter}\"))\n filter_arg.update(search_filter)\n\n if filter_arg:\n args[\"filter\"] = filter_arg\n\n return args\n\n def search_documents(self, vector_store=None) -> list[Data]:\n vector_store = vector_store or self.build_vector_store()\n\n self.log(f\"Search input: {self.search_input}\")\n self.log(f\"Search type: {self.search_type}\")\n self.log(f\"Number of results: {self.number_of_results}\")\n\n try:\n search_args = self._build_search_args()\n except Exception as e:\n msg = f\"Error in AstraDBVectorStore._build_search_args: {e}\"\n raise ValueError(msg) from e\n\n if not search_args:\n self.log(\"No search input or filters provided. Skipping search.\")\n return []\n\n docs = []\n search_method = \"search\" if \"query\" in search_args else \"metadata_search\"\n\n try:\n self.log(f\"Calling vector_store.{search_method} with args: {search_args}\")\n docs = getattr(vector_store, search_method)(**search_args)\n except Exception as e:\n msg = f\"Error performing {search_method} in AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n\n self.log(f\"Retrieved documents: {len(docs)}\")\n\n data = docs_to_data(docs)\n self.log(f\"Converted documents to data: {len(data)}\")\n self.status = data\n return data\n\n def get_retriever_kwargs(self):\n search_args = self._build_search_args()\n return {\n \"search_type\": self._map_search_type(),\n \"search_kwargs\": search_args,\n }\n" }, "collection_indexing_policy": { "_input_type": "StrInput", @@ -3783,7 +3748,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import os\nfrom collections import defaultdict\n\nimport orjson\nfrom astrapy import DataAPIClient\nfrom astrapy.admin import parse_api_endpoint\nfrom langchain_astradb import AstraDBVectorStore\n\nfrom langflow.base.vectorstores.model import LCVectorStoreComponent, check_cached_vector_store\nfrom langflow.helpers import docs_to_data\nfrom langflow.inputs import DictInput, FloatInput, MessageTextInput, NestedDictInput\nfrom langflow.io import (\n BoolInput,\n DataInput,\n DropdownInput,\n HandleInput,\n IntInput,\n MultilineInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.schema import Data\nfrom langflow.utils.version import get_version_info\n\n\nclass AstraDBVectorStoreComponent(LCVectorStoreComponent):\n display_name: str = \"Astra DB\"\n description: str = \"Implementation of Vector Store using Astra DB with search capabilities\"\n documentation: str = \"https://docs.langflow.org/starter-projects-vector-store-rag\"\n name = \"AstraDB\"\n icon: str = \"AstraDB\"\n\n _cached_vector_store: AstraDBVectorStore | None = None\n\n VECTORIZE_PROVIDERS_MAPPING = defaultdict(\n list,\n {\n \"Azure OpenAI\": [\n \"azureOpenAI\",\n [\"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"],\n ],\n \"Hugging Face - Dedicated\": [\"huggingfaceDedicated\", [\"endpoint-defined-model\"]],\n \"Hugging Face - Serverless\": [\n \"huggingface\",\n [\n \"sentence-transformers/all-MiniLM-L6-v2\",\n \"intfloat/multilingual-e5-large\",\n \"intfloat/multilingual-e5-large-instruct\",\n \"BAAI/bge-small-en-v1.5\",\n \"BAAI/bge-base-en-v1.5\",\n \"BAAI/bge-large-en-v1.5\",\n ],\n ],\n \"Jina AI\": [\n \"jinaAI\",\n [\n \"jina-embeddings-v2-base-en\",\n \"jina-embeddings-v2-base-de\",\n \"jina-embeddings-v2-base-es\",\n \"jina-embeddings-v2-base-code\",\n \"jina-embeddings-v2-base-zh\",\n ],\n ],\n \"Mistral AI\": [\"mistral\", [\"mistral-embed\"]],\n \"Nvidia\": [\"nvidia\", [\"NV-Embed-QA\"]],\n \"OpenAI\": [\"openai\", [\"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"]],\n \"Upstage\": [\"upstageAI\", [\"solar-embedding-1-large\"]],\n \"Voyage AI\": [\n \"voyageAI\",\n [\"voyage-large-2-instruct\", \"voyage-law-2\", \"voyage-code-2\", \"voyage-large-2\", \"voyage-2\"],\n ],\n },\n )\n\n inputs = [\n SecretStrInput(\n name=\"token\",\n display_name=\"Astra DB Application Token\",\n info=\"Authentication token for accessing Astra DB.\",\n value=\"ASTRA_DB_APPLICATION_TOKEN\",\n required=True,\n advanced=os.getenv(\"ASTRA_ENHANCED\", \"false\").lower() == \"true\",\n real_time_refresh=True,\n ),\n SecretStrInput(\n name=\"api_endpoint\",\n display_name=\"Database\" if os.getenv(\"ASTRA_ENHANCED\", \"false\").lower() == \"true\" else \"API Endpoint\",\n info=\"API endpoint URL for the Astra DB service.\",\n value=\"ASTRA_DB_API_ENDPOINT\",\n required=True,\n real_time_refresh=True,\n ),\n DropdownInput(\n name=\"collection_name\",\n display_name=\"Collection\",\n info=\"The name of the collection within Astra DB where the vectors will be stored.\",\n required=True,\n refresh_button=True,\n real_time_refresh=True,\n options=[\"+ Create new collection\"],\n value=\"+ Create new collection\",\n ),\n StrInput(\n name=\"collection_name_new\",\n display_name=\"Collection Name\",\n info=\"Name of the new collection to create.\",\n advanced=os.getenv(\"LANGFLOW_HOST\") is not None,\n required=os.getenv(\"LANGFLOW_HOST\") is None,\n ),\n StrInput(\n name=\"keyspace\",\n display_name=\"Keyspace\",\n info=\"Optional keyspace within Astra DB to use for the collection.\",\n advanced=True,\n ),\n MultilineInput(\n name=\"search_input\",\n display_name=\"Search Input\",\n ),\n IntInput(\n name=\"number_of_results\",\n display_name=\"Number of Results\",\n info=\"Number of results to return.\",\n advanced=True,\n value=4,\n ),\n DropdownInput(\n name=\"search_type\",\n display_name=\"Search Type\",\n info=\"Search type to use\",\n options=[\"Similarity\", \"Similarity with score threshold\", \"MMR (Max Marginal Relevance)\"],\n value=\"Similarity\",\n advanced=True,\n ),\n FloatInput(\n name=\"search_score_threshold\",\n display_name=\"Search Score Threshold\",\n info=\"Minimum similarity score threshold for search results. \"\n \"(when using 'Similarity with score threshold')\",\n value=0,\n advanced=True,\n ),\n NestedDictInput(\n name=\"advanced_search_filter\",\n display_name=\"Search Metadata Filter\",\n info=\"Optional dictionary of filters to apply to the search query.\",\n advanced=True,\n ),\n DictInput(\n name=\"search_filter\",\n display_name=\"[DEPRECATED] Search Metadata Filter\",\n info=\"Deprecated: use advanced_search_filter. Optional dictionary of filters to apply to the search query.\",\n advanced=True,\n list=True,\n ),\n DataInput(\n name=\"ingest_data\",\n display_name=\"Ingest Data\",\n ),\n DropdownInput(\n name=\"embedding_choice\",\n display_name=\"Embedding Model or Astra Vectorize\",\n info=\"Determines whether to use Astra Vectorize for the collection.\",\n options=[\"Embedding Model\", \"Astra Vectorize\"],\n real_time_refresh=True,\n value=\"Embedding Model\",\n ),\n HandleInput(\n name=\"embedding_model\",\n display_name=\"Embedding Model\",\n input_types=[\"Embeddings\"],\n info=\"Allows an embedding model configuration.\",\n ),\n DropdownInput(\n name=\"metric\",\n display_name=\"Metric\",\n info=\"Optional distance metric for vector comparisons in the vector store.\",\n options=[\"cosine\", \"dot_product\", \"euclidean\"],\n value=\"cosine\",\n advanced=True,\n ),\n IntInput(\n name=\"batch_size\",\n display_name=\"Batch Size\",\n info=\"Optional number of data to process in a single batch.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_batch_concurrency\",\n display_name=\"Bulk Insert Batch Concurrency\",\n info=\"Optional concurrency level for bulk insert operations.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_overwrite_concurrency\",\n display_name=\"Bulk Insert Overwrite Concurrency\",\n info=\"Optional concurrency level for bulk insert operations that overwrite existing data.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_delete_concurrency\",\n display_name=\"Bulk Delete Concurrency\",\n info=\"Optional concurrency level for bulk delete operations.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"setup_mode\",\n display_name=\"Setup Mode\",\n info=\"Configuration mode for setting up the vector store, with options like 'Sync' or 'Off'.\",\n options=[\"Sync\", \"Off\"],\n advanced=True,\n value=\"Sync\",\n ),\n BoolInput(\n name=\"pre_delete_collection\",\n display_name=\"Pre Delete Collection\",\n info=\"Boolean flag to determine whether to delete the collection before creating a new one.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_include\",\n display_name=\"Metadata Indexing Include\",\n info=\"Optional list of metadata fields to include in the indexing.\",\n list=True,\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_exclude\",\n display_name=\"Metadata Indexing Exclude\",\n info=\"Optional list of metadata fields to exclude from the indexing.\",\n list=True,\n advanced=True,\n ),\n StrInput(\n name=\"collection_indexing_policy\",\n display_name=\"Collection Indexing Policy\",\n info='Optional JSON string for the \"indexing\" field of the collection. '\n \"See https://docs.datastax.com/en/astra-db-serverless/api-reference/collections.html#the-indexing-option\",\n advanced=True,\n ),\n ]\n\n def del_fields(self, build_config, field_list):\n for field in field_list:\n if field in build_config:\n del build_config[field]\n\n return build_config\n\n def insert_in_dict(self, build_config, field_name, new_parameters):\n # Insert the new key-value pair after the found key\n for new_field_name, new_parameter in new_parameters.items():\n # Get all the items as a list of tuples (key, value)\n items = list(build_config.items())\n\n # Find the index of the key to insert after\n idx = len(items)\n for i, (key, _) in enumerate(items):\n if key == field_name:\n idx = i + 1\n break\n\n items.insert(idx, (new_field_name, new_parameter))\n\n # Clear the original dictionary and update with the modified items\n build_config.clear()\n build_config.update(items)\n\n return build_config\n\n def update_providers_mapping(self):\n # If we don't have token or api_endpoint, we can't fetch the list of providers\n if not self.token or not self.api_endpoint:\n self.log(\"Astra DB token and API endpoint are required to fetch the list of Vectorize providers.\")\n\n return self.VECTORIZE_PROVIDERS_MAPPING\n\n try:\n self.log(\"Dynamically updating list of Vectorize providers.\")\n\n # Get the admin object\n client = DataAPIClient(token=self.token)\n admin = client.get_admin()\n\n # Get the embedding providers\n db_admin = admin.get_database_admin(self.api_endpoint)\n embedding_providers = db_admin.find_embedding_providers().as_dict()\n\n vectorize_providers_mapping = {}\n\n # Map the provider display name to the provider key and models\n for provider_key, provider_data in embedding_providers[\"embeddingProviders\"].items():\n display_name = provider_data[\"displayName\"]\n models = [model[\"name\"] for model in provider_data[\"models\"]]\n\n vectorize_providers_mapping[display_name] = [provider_key, models]\n\n # Sort the resulting dictionary\n return defaultdict(list, dict(sorted(vectorize_providers_mapping.items())))\n except Exception as e: # noqa: BLE001\n self.log(f\"Error fetching Vectorize providers: {e}\")\n\n return self.VECTORIZE_PROVIDERS_MAPPING\n\n def get_database(self):\n try:\n client = DataAPIClient(token=self.token)\n\n return client.get_database(\n self.api_endpoint,\n token=self.token,\n )\n except Exception as e: # noqa: BLE001\n self.log(f\"Error getting database: {e}\")\n\n return None\n\n def _initialize_collection_options(self):\n database = self.get_database()\n if database is None:\n return [\"+ Create new collection\"]\n\n try:\n collections = [collection.name for collection in database.list_collections()]\n except Exception as e: # noqa: BLE001\n self.log(f\"Error fetching collections: {e}\")\n\n return [\"+ Create new collection\"]\n\n return [*collections, \"+ Create new collection\"]\n\n def get_collection_choice(self):\n collection_name = self.collection_name\n if collection_name == \"+ Create new collection\":\n return self.collection_name_new\n\n return collection_name\n\n def get_collection_options(self):\n # Only get the options if the collection exists\n database = self.get_database()\n if database is None:\n return None\n\n collection_name = self.get_collection_choice()\n\n try:\n collection = database.get_collection(collection_name)\n collection_options = collection.options()\n except Exception as _: # noqa: BLE001\n return None\n\n return collection_options.vector\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n # Refresh the collection name options\n build_config[\"collection_name\"][\"options\"] = self._initialize_collection_options()\n\n # If the collection name is set to \"+ Create new collection\", show embedding choice\n if field_name == \"collection_name\" and field_value == \"+ Create new collection\":\n build_config[\"embedding_choice\"][\"advanced\"] = False\n build_config[\"embedding_choice\"][\"value\"] = \"Embedding Model\"\n build_config[\"embedding_model\"][\"advanced\"] = False\n\n build_config[\"collection_name_new\"][\"advanced\"] = False\n build_config[\"collection_name_new\"][\"required\"] = True\n\n # But if it's not, hide embedding choice\n elif field_name == \"collection_name\" and field_value != \"+ Create new collection\":\n build_config[\"embedding_choice\"][\"advanced\"] = True\n\n build_config[\"collection_name_new\"][\"advanced\"] = True\n build_config[\"collection_name_new\"][\"required\"] = False\n build_config[\"collection_name_new\"][\"value\"] = \"\"\n\n # Get the collection options for the selected collection\n collection_options = self.get_collection_options()\n\n # If the collection options are available (DB exists), show the advanced options\n if collection_options:\n build_config[\"embedding_choice\"][\"advanced\"] = True\n\n if collection_options.service:\n self.del_fields(\n build_config,\n [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ],\n )\n\n build_config[\"embedding_model\"][\"advanced\"] = True\n build_config[\"embedding_choice\"][\"value\"] = \"Astra Vectorize\"\n else:\n build_config[\"embedding_model\"][\"advanced\"] = False\n build_config[\"embedding_provider\"][\"advanced\"] = False\n build_config[\"embedding_choice\"][\"value\"] = \"Embedding Model\"\n\n elif field_name == \"embedding_choice\":\n if field_value == \"Astra Vectorize\":\n build_config[\"embedding_model\"][\"advanced\"] = True\n\n # Update the providers mapping\n vectorize_providers = self.update_providers_mapping()\n\n new_parameter = DropdownInput(\n name=\"embedding_provider\",\n display_name=\"Embedding Provider\",\n options=vectorize_providers.keys(),\n value=\"\",\n required=True,\n real_time_refresh=True,\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_choice\", {\"embedding_provider\": new_parameter})\n else:\n build_config[\"embedding_model\"][\"advanced\"] = False\n\n self.del_fields(\n build_config,\n [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ],\n )\n\n elif field_name == \"embedding_provider\":\n self.del_fields(\n build_config,\n [\"model\", \"z_01_model_parameters\", \"z_02_api_key_name\", \"z_03_provider_api_key\", \"z_04_authentication\"],\n )\n\n # Update the providers mapping\n vectorize_providers = self.update_providers_mapping()\n model_options = vectorize_providers[field_value][1]\n\n new_parameter = DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n info=\"The embedding model to use for the selected provider. Each provider has a different set of \"\n \"models available (full list at \"\n \"https://docs.datastax.com/en/astra-db-serverless/databases/embedding-generation.html):\\n\\n\"\n f\"{', '.join(model_options)}\",\n options=model_options,\n value=None,\n required=True,\n real_time_refresh=True,\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_provider\", {\"model\": new_parameter})\n\n elif field_name == \"model\":\n self.del_fields(\n build_config,\n [\"z_01_model_parameters\", \"z_02_api_key_name\", \"z_03_provider_api_key\", \"z_04_authentication\"],\n )\n\n new_parameter_1 = DictInput(\n name=\"z_01_model_parameters\",\n display_name=\"Model Parameters\",\n list=True,\n ).to_dict()\n\n new_parameter_2 = MessageTextInput(\n name=\"z_02_api_key_name\",\n display_name=\"API Key Name\",\n info=\"The name of the embeddings provider API key stored on Astra. \"\n \"If set, it will override the 'ProviderKey' in the authentication parameters.\",\n ).to_dict()\n\n new_parameter_3 = SecretStrInput(\n load_from_db=False,\n name=\"z_03_provider_api_key\",\n display_name=\"Provider API Key\",\n info=\"An alternative to the Astra Authentication that passes an API key for the provider \"\n \"with each request to Astra DB. \"\n \"This may be used when Vectorize is configured for the collection, \"\n \"but no corresponding provider secret is stored within Astra's key management system.\",\n ).to_dict()\n\n new_parameter_4 = DictInput(\n name=\"z_04_authentication\",\n display_name=\"Authentication Parameters\",\n list=True,\n ).to_dict()\n\n self.insert_in_dict(\n build_config,\n \"model\",\n {\n \"z_01_model_parameters\": new_parameter_1,\n \"z_02_api_key_name\": new_parameter_2,\n \"z_03_provider_api_key\": new_parameter_3,\n \"z_04_authentication\": new_parameter_4,\n },\n )\n\n return build_config\n\n def build_vectorize_options(self, **kwargs):\n for attribute in [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ]:\n if not hasattr(self, attribute):\n setattr(self, attribute, None)\n\n # Fetch values from kwargs if any self.* attributes are None\n provider_mapping = self.update_providers_mapping()\n provider_value = provider_mapping.get(self.embedding_provider, [None])[0] or kwargs.get(\"embedding_provider\")\n model_name = self.model or kwargs.get(\"model\")\n authentication = {**(self.z_04_authentication or {}), **kwargs.get(\"z_04_authentication\", {})}\n parameters = self.z_01_model_parameters or kwargs.get(\"z_01_model_parameters\", {})\n\n # Set the API key name if provided\n api_key_name = self.z_02_api_key_name or kwargs.get(\"z_02_api_key_name\")\n provider_key = self.z_03_provider_api_key or kwargs.get(\"z_03_provider_api_key\")\n if api_key_name:\n authentication[\"providerKey\"] = api_key_name\n if authentication:\n provider_key = None\n authentication[\"providerKey\"] = authentication[\"providerKey\"].split(\".\")[0]\n\n # Set authentication and parameters to None if no values are provided\n if not authentication:\n authentication = None\n if not parameters:\n parameters = None\n\n return {\n # must match astrapy.info.CollectionVectorServiceOptions\n \"collection_vector_service_options\": {\n \"provider\": provider_value,\n \"modelName\": model_name,\n \"authentication\": authentication,\n \"parameters\": parameters,\n },\n \"collection_embedding_api_key\": provider_key,\n }\n\n @check_cached_vector_store\n def build_vector_store(self, vectorize_options=None):\n try:\n from langchain_astradb import AstraDBVectorStore\n from langchain_astradb.utils.astradb import SetupMode\n except ImportError as e:\n msg = (\n \"Could not import langchain Astra DB integration package. \"\n \"Please install it with `pip install langchain-astradb`.\"\n )\n raise ImportError(msg) from e\n\n try:\n if not self.setup_mode:\n self.setup_mode = self._inputs[\"setup_mode\"].options[0]\n\n setup_mode_value = SetupMode[self.setup_mode.upper()]\n except KeyError as e:\n msg = f\"Invalid setup mode: {self.setup_mode}\"\n raise ValueError(msg) from e\n\n metric_value = self.metric or None\n autodetect = False\n\n if self.embedding_choice == \"Embedding Model\":\n embedding_dict = {\"embedding\": self.embedding_model}\n # Use autodetect if the collection name is NOT set to \"+ Create new collection\"\n elif self.collection_name != \"+ Create new collection\":\n autodetect = True\n metric_value = None\n setup_mode_value = None\n embedding_dict = {}\n else:\n from astrapy.info import CollectionVectorServiceOptions\n\n # Grab the collection options if available\n collection_options = self.get_collection_options()\n\n # Ensure collection_options and its nested attributes are handled safely\n authentication = getattr(self, \"z_04_authentication\", {}) or (\n collection_options.service.authentication\n if collection_options and collection_options.service and collection_options.service.authentication\n else {}\n )\n\n # Build the vectorize options dictionary\n dict_options = vectorize_options or self.build_vectorize_options(\n embedding_provider=(\n getattr(self, \"embedding_provider\", None)\n or (\n collection_options.service.provider\n if collection_options and collection_options.service\n else None\n )\n ),\n model=(\n getattr(self, \"model\", None)\n or (\n collection_options.service.model_name\n if collection_options and collection_options.service\n else None\n )\n ),\n z_01_model_parameters=(\n getattr(self, \"z_01_model_parameters\", None)\n or (\n collection_options.service.parameters\n if collection_options and collection_options.service\n else None\n )\n ),\n z_02_api_key_name=(\n getattr(self, \"z_02_api_key_name\", None)\n or (authentication.get(\"apiKey\") if authentication else None)\n ),\n z_03_provider_api_key=(\n getattr(self, \"z_03_provider_api_key\", None)\n or (authentication.get(\"providerKey\") if authentication else None)\n ),\n z_04_authentication=authentication,\n )\n\n # Set the embedding dictionary\n embedding_dict = {\n \"collection_vector_service_options\": CollectionVectorServiceOptions.from_dict(\n dict_options.get(\"collection_vector_service_options\")\n ),\n \"collection_embedding_api_key\": dict_options.get(\"collection_embedding_api_key\"),\n }\n\n # Get Langflow version and platform information\n __version__ = get_version_info()[\"version\"]\n langflow_prefix = \"\"\n if os.getenv(\"LANGFLOW_HOST\") is not None:\n langflow_prefix = \"ds-\"\n\n try:\n vector_store = AstraDBVectorStore(\n token=self.token,\n api_endpoint=self.api_endpoint,\n namespace=self.keyspace or None,\n collection_name=self.get_collection_choice(),\n autodetect_collection=autodetect,\n environment=(\n parse_api_endpoint(getattr(self, \"api_endpoint\", None)).environment\n if getattr(self, \"api_endpoint\", None)\n else None\n ),\n metric=metric_value,\n batch_size=self.batch_size or None,\n bulk_insert_batch_concurrency=self.bulk_insert_batch_concurrency or None,\n bulk_insert_overwrite_concurrency=self.bulk_insert_overwrite_concurrency or None,\n bulk_delete_concurrency=self.bulk_delete_concurrency or None,\n setup_mode=setup_mode_value,\n pre_delete_collection=self.pre_delete_collection,\n metadata_indexing_include=[s for s in self.metadata_indexing_include if s] or None,\n metadata_indexing_exclude=[s for s in self.metadata_indexing_exclude if s] or None,\n collection_indexing_policy=orjson.dumps(self.collection_indexing_policy)\n if self.collection_indexing_policy\n else None,\n ext_callers=[(f\"{langflow_prefix}langflow\", __version__)],\n **embedding_dict,\n )\n except Exception as e:\n msg = f\"Error initializing AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n\n self._add_documents_to_vector_store(vector_store)\n\n return vector_store\n\n def _add_documents_to_vector_store(self, vector_store) -> None:\n documents = []\n for _input in self.ingest_data or []:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n else:\n msg = \"Vector Store Inputs must be Data objects.\"\n raise TypeError(msg)\n\n if documents:\n self.log(f\"Adding {len(documents)} documents to the Vector Store.\")\n try:\n vector_store.add_documents(documents)\n except Exception as e:\n msg = f\"Error adding documents to AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n else:\n self.log(\"No documents to add to the Vector Store.\")\n\n def _map_search_type(self) -> str:\n if self.search_type == \"Similarity with score threshold\":\n return \"similarity_score_threshold\"\n if self.search_type == \"MMR (Max Marginal Relevance)\":\n return \"mmr\"\n return \"similarity\"\n\n def _build_search_args(self):\n query = self.search_input if isinstance(self.search_input, str) and self.search_input.strip() else None\n search_filter = (\n {k: v for k, v in self.search_filter.items() if k and v and k.strip()} if self.search_filter else None\n )\n\n if query:\n args = {\n \"query\": query,\n \"search_type\": self._map_search_type(),\n \"k\": self.number_of_results,\n \"score_threshold\": self.search_score_threshold,\n }\n elif self.advanced_search_filter or search_filter:\n args = {\n \"n\": self.number_of_results,\n }\n else:\n return {}\n\n filter_arg = self.advanced_search_filter or {}\n\n if search_filter:\n self.log(self.log(f\"`search_filter` is deprecated. Use `advanced_search_filter`. Cleaned: {search_filter}\"))\n filter_arg.update(search_filter)\n\n if filter_arg:\n args[\"filter\"] = filter_arg\n\n return args\n\n def search_documents(self, vector_store=None) -> list[Data]:\n vector_store = vector_store or self.build_vector_store()\n\n self.log(f\"Search input: {self.search_input}\")\n self.log(f\"Search type: {self.search_type}\")\n self.log(f\"Number of results: {self.number_of_results}\")\n\n try:\n search_args = self._build_search_args()\n except Exception as e:\n msg = f\"Error in AstraDBVectorStore._build_search_args: {e}\"\n raise ValueError(msg) from e\n\n if not search_args:\n self.log(\"No search input or filters provided. Skipping search.\")\n return []\n\n docs = []\n search_method = \"search\" if \"query\" in search_args else \"metadata_search\"\n\n try:\n self.log(f\"Calling vector_store.{search_method} with args: {search_args}\")\n docs = getattr(vector_store, search_method)(**search_args)\n except Exception as e:\n msg = f\"Error performing {search_method} in AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n\n self.log(f\"Retrieved documents: {len(docs)}\")\n\n data = docs_to_data(docs)\n self.log(f\"Converted documents to data: {len(data)}\")\n self.status = data\n return data\n\n def get_retriever_kwargs(self):\n search_args = self._build_search_args()\n return {\n \"search_type\": self._map_search_type(),\n \"search_kwargs\": search_args,\n }\n" + "value": "import os\nfrom collections import defaultdict\n\nimport orjson\nfrom astrapy import DataAPIClient\nfrom astrapy.admin import parse_api_endpoint\nfrom langchain_astradb import AstraDBVectorStore\n\nfrom langflow.base.vectorstores.model import LCVectorStoreComponent, check_cached_vector_store\nfrom langflow.helpers import docs_to_data\nfrom langflow.inputs import DictInput, FloatInput, MessageTextInput, NestedDictInput\nfrom langflow.io import (\n BoolInput,\n DataInput,\n DropdownInput,\n HandleInput,\n IntInput,\n MultilineInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.schema import Data\nfrom langflow.utils.version import get_version_info\n\n\nclass AstraDBVectorStoreComponent(LCVectorStoreComponent):\n display_name: str = \"Astra DB\"\n description: str = \"Implementation of Vector Store using Astra DB with search capabilities\"\n documentation: str = \"https://docs.langflow.org/starter-projects-vector-store-rag\"\n name = \"AstraDB\"\n icon: str = \"AstraDB\"\n\n _cached_vector_store: AstraDBVectorStore | None = None\n\n VECTORIZE_PROVIDERS_MAPPING = defaultdict(\n list,\n {\n \"Azure OpenAI\": [\n \"azureOpenAI\",\n [\"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"],\n ],\n \"Hugging Face - Dedicated\": [\"huggingfaceDedicated\", [\"endpoint-defined-model\"]],\n \"Hugging Face - Serverless\": [\n \"huggingface\",\n [\n \"sentence-transformers/all-MiniLM-L6-v2\",\n \"intfloat/multilingual-e5-large\",\n \"intfloat/multilingual-e5-large-instruct\",\n \"BAAI/bge-small-en-v1.5\",\n \"BAAI/bge-base-en-v1.5\",\n \"BAAI/bge-large-en-v1.5\",\n ],\n ],\n \"Jina AI\": [\n \"jinaAI\",\n [\n \"jina-embeddings-v2-base-en\",\n \"jina-embeddings-v2-base-de\",\n \"jina-embeddings-v2-base-es\",\n \"jina-embeddings-v2-base-code\",\n \"jina-embeddings-v2-base-zh\",\n ],\n ],\n \"Mistral AI\": [\"mistral\", [\"mistral-embed\"]],\n \"Nvidia\": [\"nvidia\", [\"NV-Embed-QA\"]],\n \"OpenAI\": [\"openai\", [\"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"]],\n \"Upstage\": [\"upstageAI\", [\"solar-embedding-1-large\"]],\n \"Voyage AI\": [\n \"voyageAI\",\n [\"voyage-large-2-instruct\", \"voyage-law-2\", \"voyage-code-2\", \"voyage-large-2\", \"voyage-2\"],\n ],\n },\n )\n\n inputs = [\n SecretStrInput(\n name=\"token\",\n display_name=\"Astra DB Application Token\",\n info=\"Authentication token for accessing Astra DB.\",\n value=\"ASTRA_DB_APPLICATION_TOKEN\",\n required=True,\n advanced=os.getenv(\"ASTRA_ENHANCED\", \"false\").lower() == \"true\",\n real_time_refresh=True,\n ),\n SecretStrInput(\n name=\"api_endpoint\",\n display_name=\"Database\" if os.getenv(\"ASTRA_ENHANCED\", \"false\").lower() == \"true\" else \"API Endpoint\",\n info=\"API endpoint URL for the Astra DB service.\",\n value=\"ASTRA_DB_API_ENDPOINT\",\n required=True,\n real_time_refresh=True,\n ),\n DropdownInput(\n name=\"collection_name\",\n display_name=\"Collection\",\n info=\"The name of the collection within Astra DB where the vectors will be stored.\",\n required=True,\n refresh_button=True,\n real_time_refresh=True,\n options=[\"+ Create new collection\"],\n value=\"+ Create new collection\",\n ),\n StrInput(\n name=\"collection_name_new\",\n display_name=\"Collection Name\",\n info=\"Name of the new collection to create.\",\n advanced=os.getenv(\"LANGFLOW_HOST\") is not None,\n required=os.getenv(\"LANGFLOW_HOST\") is None,\n ),\n StrInput(\n name=\"keyspace\",\n display_name=\"Keyspace\",\n info=\"Optional keyspace within Astra DB to use for the collection.\",\n advanced=True,\n ),\n MultilineInput(\n name=\"search_input\",\n display_name=\"Search Input\",\n tool_mode=True,\n ),\n IntInput(\n name=\"number_of_results\",\n display_name=\"Number of Results\",\n info=\"Number of results to return.\",\n advanced=True,\n value=4,\n ),\n DropdownInput(\n name=\"search_type\",\n display_name=\"Search Type\",\n info=\"Search type to use\",\n options=[\"Similarity\", \"Similarity with score threshold\", \"MMR (Max Marginal Relevance)\"],\n value=\"Similarity\",\n advanced=True,\n ),\n FloatInput(\n name=\"search_score_threshold\",\n display_name=\"Search Score Threshold\",\n info=\"Minimum similarity score threshold for search results. \"\n \"(when using 'Similarity with score threshold')\",\n value=0,\n advanced=True,\n ),\n NestedDictInput(\n name=\"advanced_search_filter\",\n display_name=\"Search Metadata Filter\",\n info=\"Optional dictionary of filters to apply to the search query.\",\n advanced=True,\n ),\n DictInput(\n name=\"search_filter\",\n display_name=\"[DEPRECATED] Search Metadata Filter\",\n info=\"Deprecated: use advanced_search_filter. Optional dictionary of filters to apply to the search query.\",\n advanced=True,\n list=True,\n ),\n DataInput(\n name=\"ingest_data\",\n display_name=\"Ingest Data\",\n ),\n DropdownInput(\n name=\"embedding_choice\",\n display_name=\"Embedding Model or Astra Vectorize\",\n info=\"Determines whether to use Astra Vectorize for the collection.\",\n options=[\"Embedding Model\", \"Astra Vectorize\"],\n real_time_refresh=True,\n value=\"Embedding Model\",\n ),\n HandleInput(\n name=\"embedding_model\",\n display_name=\"Embedding Model\",\n input_types=[\"Embeddings\"],\n info=\"Allows an embedding model configuration.\",\n ),\n DropdownInput(\n name=\"metric\",\n display_name=\"Metric\",\n info=\"Optional distance metric for vector comparisons in the vector store.\",\n options=[\"cosine\", \"dot_product\", \"euclidean\"],\n value=\"cosine\",\n advanced=True,\n ),\n IntInput(\n name=\"batch_size\",\n display_name=\"Batch Size\",\n info=\"Optional number of data to process in a single batch.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_batch_concurrency\",\n display_name=\"Bulk Insert Batch Concurrency\",\n info=\"Optional concurrency level for bulk insert operations.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_overwrite_concurrency\",\n display_name=\"Bulk Insert Overwrite Concurrency\",\n info=\"Optional concurrency level for bulk insert operations that overwrite existing data.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_delete_concurrency\",\n display_name=\"Bulk Delete Concurrency\",\n info=\"Optional concurrency level for bulk delete operations.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"setup_mode\",\n display_name=\"Setup Mode\",\n info=\"Configuration mode for setting up the vector store, with options like 'Sync' or 'Off'.\",\n options=[\"Sync\", \"Off\"],\n advanced=True,\n value=\"Sync\",\n ),\n BoolInput(\n name=\"pre_delete_collection\",\n display_name=\"Pre Delete Collection\",\n info=\"Boolean flag to determine whether to delete the collection before creating a new one.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_include\",\n display_name=\"Metadata Indexing Include\",\n info=\"Optional list of metadata fields to include in the indexing.\",\n list=True,\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_exclude\",\n display_name=\"Metadata Indexing Exclude\",\n info=\"Optional list of metadata fields to exclude from the indexing.\",\n list=True,\n advanced=True,\n ),\n StrInput(\n name=\"collection_indexing_policy\",\n display_name=\"Collection Indexing Policy\",\n info='Optional JSON string for the \"indexing\" field of the collection. '\n \"See https://docs.datastax.com/en/astra-db-serverless/api-reference/collections.html#the-indexing-option\",\n advanced=True,\n ),\n ]\n\n def del_fields(self, build_config, field_list):\n for field in field_list:\n if field in build_config:\n del build_config[field]\n\n return build_config\n\n def insert_in_dict(self, build_config, field_name, new_parameters):\n # Insert the new key-value pair after the found key\n for new_field_name, new_parameter in new_parameters.items():\n # Get all the items as a list of tuples (key, value)\n items = list(build_config.items())\n\n # Find the index of the key to insert after\n idx = len(items)\n for i, (key, _) in enumerate(items):\n if key == field_name:\n idx = i + 1\n break\n\n items.insert(idx, (new_field_name, new_parameter))\n\n # Clear the original dictionary and update with the modified items\n build_config.clear()\n build_config.update(items)\n\n return build_config\n\n def update_providers_mapping(self):\n # If we don't have token or api_endpoint, we can't fetch the list of providers\n if not self.token or not self.api_endpoint:\n self.log(\"Astra DB token and API endpoint are required to fetch the list of Vectorize providers.\")\n\n return self.VECTORIZE_PROVIDERS_MAPPING\n\n try:\n self.log(\"Dynamically updating list of Vectorize providers.\")\n\n # Get the admin object\n client = DataAPIClient(token=self.token)\n admin = client.get_admin()\n\n # Get the embedding providers\n db_admin = admin.get_database_admin(self.api_endpoint)\n embedding_providers = db_admin.find_embedding_providers().as_dict()\n\n vectorize_providers_mapping = {}\n\n # Map the provider display name to the provider key and models\n for provider_key, provider_data in embedding_providers[\"embeddingProviders\"].items():\n display_name = provider_data[\"displayName\"]\n models = [model[\"name\"] for model in provider_data[\"models\"]]\n\n vectorize_providers_mapping[display_name] = [provider_key, models]\n\n # Sort the resulting dictionary\n return defaultdict(list, dict(sorted(vectorize_providers_mapping.items())))\n except Exception as e: # noqa: BLE001\n self.log(f\"Error fetching Vectorize providers: {e}\")\n\n return self.VECTORIZE_PROVIDERS_MAPPING\n\n def get_database(self):\n try:\n client = DataAPIClient(token=self.token)\n\n return client.get_database(\n self.api_endpoint,\n token=self.token,\n )\n except Exception as e: # noqa: BLE001\n self.log(f\"Error getting database: {e}\")\n\n return None\n\n def _initialize_collection_options(self):\n database = self.get_database()\n if database is None:\n return [\"+ Create new collection\"]\n\n try:\n collections = [collection.name for collection in database.list_collections()]\n except Exception as e: # noqa: BLE001\n self.log(f\"Error fetching collections: {e}\")\n\n return [\"+ Create new collection\"]\n\n return [*collections, \"+ Create new collection\"]\n\n def get_collection_choice(self):\n collection_name = self.collection_name\n if collection_name == \"+ Create new collection\":\n return self.collection_name_new\n\n return collection_name\n\n def get_collection_options(self):\n # Only get the options if the collection exists\n database = self.get_database()\n if database is None:\n return None\n\n collection_name = self.get_collection_choice()\n\n try:\n collection = database.get_collection(collection_name)\n collection_options = collection.options()\n except Exception as _: # noqa: BLE001\n return None\n\n return collection_options.vector\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n # Refresh the collection name options\n build_config[\"collection_name\"][\"options\"] = self._initialize_collection_options()\n\n # If the collection name is set to \"+ Create new collection\", show embedding choice\n if field_name == \"collection_name\" and field_value == \"+ Create new collection\":\n build_config[\"embedding_choice\"][\"advanced\"] = False\n build_config[\"embedding_choice\"][\"value\"] = \"Embedding Model\"\n build_config[\"embedding_model\"][\"advanced\"] = False\n\n build_config[\"collection_name_new\"][\"advanced\"] = False\n build_config[\"collection_name_new\"][\"required\"] = True\n\n # But if it's not, hide embedding choice\n elif field_name == \"collection_name\" and field_value != \"+ Create new collection\":\n build_config[\"embedding_choice\"][\"advanced\"] = True\n\n build_config[\"collection_name_new\"][\"advanced\"] = True\n build_config[\"collection_name_new\"][\"required\"] = False\n build_config[\"collection_name_new\"][\"value\"] = \"\"\n\n # Get the collection options for the selected collection\n collection_options = self.get_collection_options()\n\n # If the collection options are available (DB exists), show the advanced options\n if collection_options:\n build_config[\"embedding_choice\"][\"advanced\"] = True\n\n if collection_options.service:\n self.del_fields(\n build_config,\n [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ],\n )\n\n build_config[\"embedding_model\"][\"advanced\"] = True\n build_config[\"embedding_choice\"][\"value\"] = \"Astra Vectorize\"\n else:\n build_config[\"embedding_model\"][\"advanced\"] = False\n build_config[\"embedding_provider\"][\"advanced\"] = False\n build_config[\"embedding_choice\"][\"value\"] = \"Embedding Model\"\n\n elif field_name == \"embedding_choice\":\n if field_value == \"Astra Vectorize\":\n build_config[\"embedding_model\"][\"advanced\"] = True\n\n # Update the providers mapping\n vectorize_providers = self.update_providers_mapping()\n\n new_parameter = DropdownInput(\n name=\"embedding_provider\",\n display_name=\"Embedding Provider\",\n options=vectorize_providers.keys(),\n value=\"\",\n required=True,\n real_time_refresh=True,\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_choice\", {\"embedding_provider\": new_parameter})\n else:\n build_config[\"embedding_model\"][\"advanced\"] = False\n\n self.del_fields(\n build_config,\n [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ],\n )\n\n elif field_name == \"embedding_provider\":\n self.del_fields(\n build_config,\n [\"model\", \"z_01_model_parameters\", \"z_02_api_key_name\", \"z_03_provider_api_key\", \"z_04_authentication\"],\n )\n\n # Update the providers mapping\n vectorize_providers = self.update_providers_mapping()\n model_options = vectorize_providers[field_value][1]\n\n new_parameter = DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n info=\"The embedding model to use for the selected provider. Each provider has a different set of \"\n \"models available (full list at \"\n \"https://docs.datastax.com/en/astra-db-serverless/databases/embedding-generation.html):\\n\\n\"\n f\"{', '.join(model_options)}\",\n options=model_options,\n value=None,\n required=True,\n real_time_refresh=True,\n ).to_dict()\n\n self.insert_in_dict(build_config, \"embedding_provider\", {\"model\": new_parameter})\n\n elif field_name == \"model\":\n self.del_fields(\n build_config,\n [\"z_01_model_parameters\", \"z_02_api_key_name\", \"z_03_provider_api_key\", \"z_04_authentication\"],\n )\n\n new_parameter_1 = DictInput(\n name=\"z_01_model_parameters\",\n display_name=\"Model Parameters\",\n list=True,\n ).to_dict()\n\n new_parameter_2 = MessageTextInput(\n name=\"z_02_api_key_name\",\n display_name=\"API Key Name\",\n info=\"The name of the embeddings provider API key stored on Astra. \"\n \"If set, it will override the 'ProviderKey' in the authentication parameters.\",\n ).to_dict()\n\n new_parameter_3 = SecretStrInput(\n load_from_db=False,\n name=\"z_03_provider_api_key\",\n display_name=\"Provider API Key\",\n info=\"An alternative to the Astra Authentication that passes an API key for the provider \"\n \"with each request to Astra DB. \"\n \"This may be used when Vectorize is configured for the collection, \"\n \"but no corresponding provider secret is stored within Astra's key management system.\",\n ).to_dict()\n\n new_parameter_4 = DictInput(\n name=\"z_04_authentication\",\n display_name=\"Authentication Parameters\",\n list=True,\n ).to_dict()\n\n self.insert_in_dict(\n build_config,\n \"model\",\n {\n \"z_01_model_parameters\": new_parameter_1,\n \"z_02_api_key_name\": new_parameter_2,\n \"z_03_provider_api_key\": new_parameter_3,\n \"z_04_authentication\": new_parameter_4,\n },\n )\n\n return build_config\n\n def build_vectorize_options(self, **kwargs):\n for attribute in [\n \"embedding_provider\",\n \"model\",\n \"z_01_model_parameters\",\n \"z_02_api_key_name\",\n \"z_03_provider_api_key\",\n \"z_04_authentication\",\n ]:\n if not hasattr(self, attribute):\n setattr(self, attribute, None)\n\n # Fetch values from kwargs if any self.* attributes are None\n provider_mapping = self.update_providers_mapping()\n provider_value = provider_mapping.get(self.embedding_provider, [None])[0] or kwargs.get(\"embedding_provider\")\n model_name = self.model or kwargs.get(\"model\")\n authentication = {**(self.z_04_authentication or {}), **kwargs.get(\"z_04_authentication\", {})}\n parameters = self.z_01_model_parameters or kwargs.get(\"z_01_model_parameters\", {})\n\n # Set the API key name if provided\n api_key_name = self.z_02_api_key_name or kwargs.get(\"z_02_api_key_name\")\n provider_key = self.z_03_provider_api_key or kwargs.get(\"z_03_provider_api_key\")\n if api_key_name:\n authentication[\"providerKey\"] = api_key_name\n if authentication:\n provider_key = None\n authentication[\"providerKey\"] = authentication[\"providerKey\"].split(\".\")[0]\n\n # Set authentication and parameters to None if no values are provided\n if not authentication:\n authentication = None\n if not parameters:\n parameters = None\n\n return {\n # must match astrapy.info.CollectionVectorServiceOptions\n \"collection_vector_service_options\": {\n \"provider\": provider_value,\n \"modelName\": model_name,\n \"authentication\": authentication,\n \"parameters\": parameters,\n },\n \"collection_embedding_api_key\": provider_key,\n }\n\n @check_cached_vector_store\n def build_vector_store(self, vectorize_options=None):\n try:\n from langchain_astradb import AstraDBVectorStore\n from langchain_astradb.utils.astradb import SetupMode\n except ImportError as e:\n msg = (\n \"Could not import langchain Astra DB integration package. \"\n \"Please install it with `pip install langchain-astradb`.\"\n )\n raise ImportError(msg) from e\n\n try:\n if not self.setup_mode:\n self.setup_mode = self._inputs[\"setup_mode\"].options[0]\n\n setup_mode_value = SetupMode[self.setup_mode.upper()]\n except KeyError as e:\n msg = f\"Invalid setup mode: {self.setup_mode}\"\n raise ValueError(msg) from e\n\n metric_value = self.metric or None\n autodetect = False\n\n if self.embedding_choice == \"Embedding Model\":\n embedding_dict = {\"embedding\": self.embedding_model}\n # Use autodetect if the collection name is NOT set to \"+ Create new collection\"\n elif self.collection_name != \"+ Create new collection\":\n autodetect = True\n metric_value = None\n setup_mode_value = None\n embedding_dict = {}\n else:\n from astrapy.info import CollectionVectorServiceOptions\n\n # Grab the collection options if available\n collection_options = self.get_collection_options()\n\n # Ensure collection_options and its nested attributes are handled safely\n authentication = getattr(self, \"z_04_authentication\", {}) or (\n collection_options.service.authentication\n if collection_options and collection_options.service and collection_options.service.authentication\n else {}\n )\n\n # Build the vectorize options dictionary\n dict_options = vectorize_options or self.build_vectorize_options(\n embedding_provider=(\n getattr(self, \"embedding_provider\", None)\n or (\n collection_options.service.provider\n if collection_options and collection_options.service\n else None\n )\n ),\n model=(\n getattr(self, \"model\", None)\n or (\n collection_options.service.model_name\n if collection_options and collection_options.service\n else None\n )\n ),\n z_01_model_parameters=(\n getattr(self, \"z_01_model_parameters\", None)\n or (\n collection_options.service.parameters\n if collection_options and collection_options.service\n else None\n )\n ),\n z_02_api_key_name=(\n getattr(self, \"z_02_api_key_name\", None)\n or (authentication.get(\"apiKey\") if authentication else None)\n ),\n z_03_provider_api_key=(\n getattr(self, \"z_03_provider_api_key\", None)\n or (authentication.get(\"providerKey\") if authentication else None)\n ),\n z_04_authentication=authentication,\n )\n\n # Set the embedding dictionary\n embedding_dict = {\n \"collection_vector_service_options\": CollectionVectorServiceOptions.from_dict(\n dict_options.get(\"collection_vector_service_options\")\n ),\n \"collection_embedding_api_key\": dict_options.get(\"collection_embedding_api_key\"),\n }\n\n # Get Langflow version and platform information\n __version__ = get_version_info()[\"version\"]\n langflow_prefix = \"\"\n if os.getenv(\"LANGFLOW_HOST\") is not None:\n langflow_prefix = \"ds-\"\n\n try:\n vector_store = AstraDBVectorStore(\n token=self.token,\n api_endpoint=self.api_endpoint,\n namespace=self.keyspace or None,\n collection_name=self.get_collection_choice(),\n autodetect_collection=autodetect,\n environment=(\n parse_api_endpoint(getattr(self, \"api_endpoint\", None)).environment\n if getattr(self, \"api_endpoint\", None)\n else None\n ),\n metric=metric_value,\n batch_size=self.batch_size or None,\n bulk_insert_batch_concurrency=self.bulk_insert_batch_concurrency or None,\n bulk_insert_overwrite_concurrency=self.bulk_insert_overwrite_concurrency or None,\n bulk_delete_concurrency=self.bulk_delete_concurrency or None,\n setup_mode=setup_mode_value,\n pre_delete_collection=self.pre_delete_collection,\n metadata_indexing_include=[s for s in self.metadata_indexing_include if s] or None,\n metadata_indexing_exclude=[s for s in self.metadata_indexing_exclude if s] or None,\n collection_indexing_policy=orjson.dumps(self.collection_indexing_policy)\n if self.collection_indexing_policy\n else None,\n ext_callers=[(f\"{langflow_prefix}langflow\", __version__)],\n **embedding_dict,\n )\n except Exception as e:\n msg = f\"Error initializing AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n\n self._add_documents_to_vector_store(vector_store)\n\n return vector_store\n\n def _add_documents_to_vector_store(self, vector_store) -> None:\n documents = []\n for _input in self.ingest_data or []:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n else:\n msg = \"Vector Store Inputs must be Data objects.\"\n raise TypeError(msg)\n\n if documents:\n self.log(f\"Adding {len(documents)} documents to the Vector Store.\")\n try:\n vector_store.add_documents(documents)\n except Exception as e:\n msg = f\"Error adding documents to AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n else:\n self.log(\"No documents to add to the Vector Store.\")\n\n def _map_search_type(self) -> str:\n if self.search_type == \"Similarity with score threshold\":\n return \"similarity_score_threshold\"\n if self.search_type == \"MMR (Max Marginal Relevance)\":\n return \"mmr\"\n return \"similarity\"\n\n def _build_search_args(self):\n query = self.search_input if isinstance(self.search_input, str) and self.search_input.strip() else None\n search_filter = (\n {k: v for k, v in self.search_filter.items() if k and v and k.strip()} if self.search_filter else None\n )\n\n if query:\n args = {\n \"query\": query,\n \"search_type\": self._map_search_type(),\n \"k\": self.number_of_results,\n \"score_threshold\": self.search_score_threshold,\n }\n elif self.advanced_search_filter or search_filter:\n args = {\n \"n\": self.number_of_results,\n }\n else:\n return {}\n\n filter_arg = self.advanced_search_filter or {}\n\n if search_filter:\n self.log(self.log(f\"`search_filter` is deprecated. Use `advanced_search_filter`. Cleaned: {search_filter}\"))\n filter_arg.update(search_filter)\n\n if filter_arg:\n args[\"filter\"] = filter_arg\n\n return args\n\n def search_documents(self, vector_store=None) -> list[Data]:\n vector_store = vector_store or self.build_vector_store()\n\n self.log(f\"Search input: {self.search_input}\")\n self.log(f\"Search type: {self.search_type}\")\n self.log(f\"Number of results: {self.number_of_results}\")\n\n try:\n search_args = self._build_search_args()\n except Exception as e:\n msg = f\"Error in AstraDBVectorStore._build_search_args: {e}\"\n raise ValueError(msg) from e\n\n if not search_args:\n self.log(\"No search input or filters provided. Skipping search.\")\n return []\n\n docs = []\n search_method = \"search\" if \"query\" in search_args else \"metadata_search\"\n\n try:\n self.log(f\"Calling vector_store.{search_method} with args: {search_args}\")\n docs = getattr(vector_store, search_method)(**search_args)\n except Exception as e:\n msg = f\"Error performing {search_method} in AstraDBVectorStore: {e}\"\n raise ValueError(msg) from e\n\n self.log(f\"Retrieved documents: {len(docs)}\")\n\n data = docs_to_data(docs)\n self.log(f\"Converted documents to data: {len(data)}\")\n self.status = data\n return data\n\n def get_retriever_kwargs(self):\n search_args = self._build_search_args()\n return {\n \"search_type\": self._map_search_type(),\n \"search_kwargs\": search_args,\n }\n" }, "collection_indexing_policy": { "_input_type": "StrInput", diff --git a/src/backend/base/langflow/services/tracing/arize_phoenix.py b/src/backend/base/langflow/services/tracing/arize_phoenix.py index 475da19c2..b4eb386c3 100644 --- a/src/backend/base/langflow/services/tracing/arize_phoenix.py +++ b/src/backend/base/langflow/services/tracing/arize_phoenix.py @@ -269,9 +269,11 @@ class ArizePhoenixTracer(BaseTracer): if not self._ready: return - def _convert_to_arize_phoenix_types(self, io_dict: dict[str, Any]): + def _convert_to_arize_phoenix_types(self, io_dict: dict[str | Any, Any]) -> dict[str, Any]: """Converts data types to Arize/Phoenix compatible formats.""" - return {key: self._convert_to_arize_phoenix_type(value) for key, value in io_dict.items()} + return { + str(key): self._convert_to_arize_phoenix_type(value) for key, value in io_dict.items() if key is not None + } def _convert_to_arize_phoenix_type(self, value): """Recursively converts a value to a Arize/Phoenix compatible type.""" diff --git a/uv.lock b/uv.lock index 50b7953c6..0d2b01bd2 100644 --- a/uv.lock +++ b/uv.lock @@ -97,11 +97,11 @@ wheels = [ [[package]] name = "aiolimiter" -version = "1.1.0" +version = "1.2.1" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/df/62/6de944a6839a68f7d69e552e26d12234d9c556472e4c277a3a563013640a/aiolimiter-1.1.0.tar.gz", hash = "sha256:461cf02f82a29347340d031626c92853645c099cb5ff85577b831a7bd21132b5", size = 6229 } +sdist = { url = "https://files.pythonhosted.org/packages/f1/23/b52debf471f7a1e42e362d959a3982bdcb4fe13a5d46e63d28868807a79c/aiolimiter-1.2.1.tar.gz", hash = "sha256:e02a37ea1a855d9e832252a105420ad4d15011505512a1a1d814647451b5cca9", size = 7185 } wheels = [ - { url = "https://files.pythonhosted.org/packages/60/69/4b7dea755fafa10b248928da836a2cc8b5cff0762f363234e24218040f8e/aiolimiter-1.1.0-py3-none-any.whl", hash = "sha256:0b4997961fc58b8df40279e739f9cf0d3e255e63e9a44f64df567a8c17241e24", size = 7212 }, + { url = "https://files.pythonhosted.org/packages/f3/ba/df6e8e1045aebc4778d19b8a3a9bc1808adb1619ba94ca354d9ba17d86c3/aiolimiter-1.2.1-py3-none-any.whl", hash = "sha256:d3f249e9059a20badcb56b61601a83556133655c11d1eb3dd3e04ff069e5f3c7", size = 6711 }, ] [[package]] @@ -130,28 +130,28 @@ wheels = [ [[package]] name = "alembic" -version = "1.13.3" +version = "1.14.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "mako" }, { name = "sqlalchemy" }, { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/94/a2/840c3b84382dce8624bc2f0ee67567fc74c32478d0c5a5aea981518c91c3/alembic-1.13.3.tar.gz", hash = "sha256:203503117415561e203aa14541740643a611f641517f0209fcae63e9fa09f1a2", size = 1921223 } +sdist = { url = "https://files.pythonhosted.org/packages/00/1e/8cb8900ba1b6360431e46fb7a89922916d3a1b017a8908a7c0499cc7e5f6/alembic-1.14.0.tar.gz", hash = "sha256:b00892b53b3642d0b8dbedba234dbf1924b69be83a9a769d5a624b01094e304b", size = 1916172 } wheels = [ - { url = "https://files.pythonhosted.org/packages/c2/12/58f4f11385fddafef5d6f7bfaaf2f42899c8da6b4f95c04b7c3b744851a8/alembic-1.13.3-py3-none-any.whl", hash = "sha256:908e905976d15235fae59c9ac42c4c5b75cfcefe3d27c0fbf7ae15a37715d80e", size = 233217 }, + { url = "https://files.pythonhosted.org/packages/cb/06/8b505aea3d77021b18dcbd8133aa1418f1a1e37e432a465b14c46b2c0eaa/alembic-1.14.0-py3-none-any.whl", hash = "sha256:99bd884ca390466db5e27ffccff1d179ec5c05c965cfefc0607e69f9e411cb25", size = 233482 }, ] [[package]] name = "amqp" -version = "5.2.0" +version = "5.3.1" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "vine" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/32/2c/6eb09fbdeb3c060b37bd33f8873832897a83e7a428afe01aad333fc405ec/amqp-5.2.0.tar.gz", hash = "sha256:a1ecff425ad063ad42a486c902807d1482311481c8ad95a72694b2975e75f7fd", size = 128754 } +sdist = { url = "https://files.pythonhosted.org/packages/79/fc/ec94a357dfc6683d8c86f8b4cfa5416a4c36b28052ec8260c77aca96a443/amqp-5.3.1.tar.gz", hash = "sha256:cddc00c725449522023bad949f70fff7b48f0b1ade74d170a6f10ab044739432", size = 129013 } wheels = [ - { url = "https://files.pythonhosted.org/packages/b3/f0/8e5be5d5e0653d9e1d02b1144efa33ff7d2963dfad07049e02c0fa9b2e8d/amqp-5.2.0-py3-none-any.whl", hash = "sha256:827cb12fb0baa892aad844fd95258143bce4027fdac4fccddbc43330fd281637", size = 50917 }, + { url = "https://files.pythonhosted.org/packages/26/99/fc813cd978842c26c82534010ea849eee9ab3a13ea2b74e95cb9c99e747b/amqp-5.3.1-py3-none-any.whl", hash = "sha256:43b3319e1b4e7d1251833a93d672b4af1e40f3d632d479b98661a95f117880a2", size = 50944 }, ] [[package]] @@ -183,17 +183,17 @@ wheels = [ [[package]] name = "anyio" -version = "4.6.0" +version = "4.7.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "exceptiongroup", marker = "python_full_version < '3.11'" }, { name = "idna" }, { name = "sniffio" }, - { name = "typing-extensions", marker = "python_full_version < '3.11'" }, + { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/78/49/f3f17ec11c4a91fe79275c426658e509b07547f874b14c1a526d86a83fc8/anyio-4.6.0.tar.gz", hash = "sha256:137b4559cbb034c477165047febb6ff83f390fc3b20bf181c1fc0a728cb8beeb", size = 170983 } +sdist = { url = "https://files.pythonhosted.org/packages/f6/40/318e58f669b1a9e00f5c4453910682e2d9dd594334539c7b7817dabb765f/anyio-4.7.0.tar.gz", hash = "sha256:2f834749c602966b7d456a7567cafcb309f96482b5081d14ac93ccd457f9dd48", size = 177076 } wheels = [ - { url = "https://files.pythonhosted.org/packages/9e/ef/7a4f225581a0d7886ea28359179cb861d7fbcdefad29663fc1167b86f69f/anyio-4.6.0-py3-none-any.whl", hash = "sha256:c7d2e9d63e31599eeb636c8c5c03a7e108d73b345f064f1c19fdc87b79036a9a", size = 89631 }, + { url = "https://files.pythonhosted.org/packages/a0/7a/4daaf3b6c08ad7ceffea4634ec206faeff697526421c20f07628c7372156/anyio-4.7.0-py3-none-any.whl", hash = "sha256:ea60c3723ab42ba6fff7e8ccb0488c898ec538ff4df1f1d5e642c3601d07e352", size = 93052 }, ] [[package]] @@ -830,33 +830,33 @@ wheels = [ [[package]] name = "clevercsv" -version = "0.8.2" +version = "0.8.3" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "chardet" }, { name = "packaging" }, { name = "regex" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/df/80/6ad1640e50d10b3e5e87e26c338a8c981ae0e6904844d7e776bce0939975/clevercsv-0.8.2.tar.gz", hash = "sha256:fac1b9671bd77e7835f5fe22898df88b1a11cfd924ff71fc2d0f066065dea940", size = 79410 } +sdist = { url = "https://files.pythonhosted.org/packages/11/a6/fced06e19189858f1316f6787375633a92bc1c54e9cd523c0e5db683a1ab/clevercsv-0.8.3.tar.gz", hash = "sha256:7f2737e435b3f64247c65e74578b04d6d2d1e3a53d401a824edfed4c6dbdff2e", size = 81053 } wheels = [ - { url = "https://files.pythonhosted.org/packages/d6/91/989d95b0149bb1b6d30254772ad36094f929cc2762b7adb8ef6e71658df6/clevercsv-0.8.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:67ab7dc8490ed391add1f26db262d09067796be7e76948bde0a9c6f1dddb7508", size = 85610 }, - { url = "https://files.pythonhosted.org/packages/2d/f2/fdfbc51ca6aaddc16b296730bafd6086426af202de370b043952efbd62c1/clevercsv-0.8.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:bcf2402578f2f1c655ed21370e668f44098d9734129804f0fba1779dab7f2c47", size = 75919 }, - { url = "https://files.pythonhosted.org/packages/ed/e0/e011c6df3bdd8fc8cbe97de17076039b5adde5dfd95b960e525d2b4f71ec/clevercsv-0.8.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:7a65d9722303e3db439124418ee312fcab6a75897175842690eae94bdf51b72b", size = 76395 }, - { url = "https://files.pythonhosted.org/packages/b2/b3/530a7d79e9d046f87a17631d1721a86c194a7452fc850818c09afeeb3950/clevercsv-0.8.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:755369a540d40295ea2898343c44dc8a4886e7c9e2fd5f5a780d2995a5516e1d", size = 106959 }, - { url = "https://files.pythonhosted.org/packages/9b/de/31e1cd99a7de986aa6fe9d0b5fc15640313cc11fa8c02d0911759bcc6743/clevercsv-0.8.2-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0fe155a8e39160692869f3b9b8a8bca9ba215cc350b9c804437edaa90ede4d16", size = 106882 }, - { url = "https://files.pythonhosted.org/packages/e0/37/2ace9f7a0ce2c96765f17ac28b60c8794596eef11a6d7dd3fbdd24ac72c9/clevercsv-0.8.2-cp310-cp310-win_amd64.whl", hash = "sha256:1e38761cd3f1977f8298a1a4cac3981c953aaf2226c0f1cc3f1ccf2172100ba4", size = 82451 }, - { url = "https://files.pythonhosted.org/packages/ea/5f/af22e01d37bd7db1c67566ac169bbdb522cd5a3a7ec8ff5ec063034b2b1c/clevercsv-0.8.2-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:3502c7af7a4b7a50b923a5972a9357ae2a37aa857dd96c7489c201d104e5d0b9", size = 85642 }, - { url = "https://files.pythonhosted.org/packages/a0/1f/f3065c5e5156d7e97925af418be373562e3b6de652dc6b3331c0fe53c95a/clevercsv-0.8.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:1ed99467ba2d47a2e1e81e990f74c7542d2cd0da120d922c5c992c17ac3ba026", size = 75958 }, - { url = "https://files.pythonhosted.org/packages/b0/ce/385990e0492fe6512b182a52b6f2714e16e15d2e181f26cbcd01c22ae2b0/clevercsv-0.8.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1be9c6f2e73117a77d0b0491c07738fd177ba5e2bf996ac9a221417b223162d7", size = 76416 }, - { url = "https://files.pythonhosted.org/packages/6e/ce/eeb242b0c2dda4229bd542d3f4079d7e3a3a74a8a518d7e5dff2ba8d057a/clevercsv-0.8.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1b942ee944264e5c4dbf276de579a502d11d3571daec97af5ebe54e6cadf2b77", size = 110878 }, - { url = "https://files.pythonhosted.org/packages/53/be/6992834496c6ab6c62a3af592b717c66c4a170e5fe2abc8274e2abd93ee7/clevercsv-0.8.2-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:48a8a81c1f324e2a5589e0de9b6bd965f1dd19b54b0e9e7f97cab5edf888d486", size = 110620 }, - { url = "https://files.pythonhosted.org/packages/72/71/59c292089e8dc88196781627456cd9627eedfbe213393a679cb69ea8c8fc/clevercsv-0.8.2-cp311-cp311-win_amd64.whl", hash = "sha256:e474cc07167010c4cb6b1a65588309bc855537cae01ab63cdf61a511e69b4722", size = 82457 }, - { url = "https://files.pythonhosted.org/packages/0f/35/5168712a4100d3c7b2c397b14cdf9fba7cca4eee758e0cc0792244bc3095/clevercsv-0.8.2-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:2bfa4fe39b3b51bcf07d2f8cf033d7ac53bac5292ef7b9a88bae7c9e6689f366", size = 85529 }, - { url = "https://files.pythonhosted.org/packages/02/ee/2ab6db72ca337da30e414aa12f1cde36acbab7a515e272483e301195e6aa/clevercsv-0.8.2-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:3e2528f89ee483878c3c8030a2d2da4eef2a8a7ac3036adad0767c1025a99df7", size = 75924 }, - { url = "https://files.pythonhosted.org/packages/78/58/4fce720ae9396c60d60a04e8952cb3e33ad50ae9fb640afe1366b6843bd1/clevercsv-0.8.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8832093b49defb2f224a98158265fe0bbee9ed6a70a8105cf8d7c4b949a8e95b", size = 76317 }, - { url = "https://files.pythonhosted.org/packages/58/79/064318d0867d0a80206bd7ea35810628f15244abb6270c1653cbc7f40099/clevercsv-0.8.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8b68a7fbddef0e1746d3ec5e4d114e1900eb1a86d71250b0b208622daa5d2c7c", size = 111708 }, - { url = "https://files.pythonhosted.org/packages/dc/af/fd362e6064eb2ade6db32efc3a4c84492b18a458ae0542dd1df425b57b69/clevercsv-0.8.2-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9cb807e7bea5a18cca4d51d1abc58e2f975759b7a0bcb78e1677c56ac7827e9a", size = 111813 }, - { url = "https://files.pythonhosted.org/packages/9a/83/fe07edec87eb9db52403baee720ae2b2030acca70560582051ce9a019776/clevercsv-0.8.2-cp312-cp312-win_amd64.whl", hash = "sha256:74133c7225037052247584cf2df99b052fce4659a423c30f0ea84532e0a30924", size = 82414 }, + { url = "https://files.pythonhosted.org/packages/db/35/e89a48d66cd85002305bc48af9db23754ab88e45fe156ca81ec80c22bdcb/clevercsv-0.8.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:f400b61047f345f17fc41b424fba12208507838882bdd6de5ffdc3a9a5699325", size = 87383 }, + { url = "https://files.pythonhosted.org/packages/58/a8/82adb73bfb899ebd05aa02c444fd9fdda83e0cf2502361c856f2cae16483/clevercsv-0.8.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:67fb18834f2a9d84764c7d6df644ddd8d82241668fca4de09bbdfd1671842f5b", size = 78127 }, + { url = "https://files.pythonhosted.org/packages/a0/03/81a1e51b041223c7ee56c9d5fc03d989d9f05eb3c215e53f4607b20726a3/clevercsv-0.8.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:0f7501f2dc5e9b16bda04a600206d13b1dd3c762026182ba8c9e1b03b53f89d0", size = 79087 }, + { url = "https://files.pythonhosted.org/packages/e7/32/173f87930fac9fee447b3e52bfe3cbdb4dff55700258db18c90b2b13b943/clevercsv-0.8.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:276c4b4a28fa327a34dcd2c0f0855604afaf09453bef5fb690f26b6ae99e431e", size = 108457 }, + { url = "https://files.pythonhosted.org/packages/47/74/e948a49f25cd227412d42be2fabc1edc1731962d6fd7ea6342454441066d/clevercsv-0.8.3-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:48ca306aa79b05fcdb40e35bf457f11f643c1b8defc3972d567c9046ac42fbb0", size = 108373 }, + { url = "https://files.pythonhosted.org/packages/51/ff/3e634c330469b9e6f642617b50d3938387ac44d2f4b04edde3190deffa07/clevercsv-0.8.3-cp310-cp310-win_amd64.whl", hash = "sha256:41e45142460bc67b739c044a4860ae7e6d231a5028552f32e5bbce09fdd00cfc", size = 84476 }, + { url = "https://files.pythonhosted.org/packages/8c/f2/768b0abb1d4faa8a9dce1a1443039c7703fd2f100fced47fd09a5d30bba0/clevercsv-0.8.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:9cb6e03a8c426d6deecd067acbac3e596fc4fdb934838cc1dca871480f86fbe3", size = 87173 }, + { url = "https://files.pythonhosted.org/packages/b9/06/10a6c82c7bd47aac2916ac92c61560480dd39414bc67345580e4c6819039/clevercsv-0.8.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:e89cf967060f454ac267ecc173e9aee326e62b8fc3d5818e25d31d237dbb6257", size = 78040 }, + { url = "https://files.pythonhosted.org/packages/69/6e/2ed8fe5e65caef26a23ffda474e95acbeb2367f3768e9baf75794efac676/clevercsv-0.8.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:8a5ed7071051b1a911fb1e77eb607a43b49daf0010ac5b6d76166d2f26515ba8", size = 78954 }, + { url = "https://files.pythonhosted.org/packages/7d/f7/262cfe2fb8e3e104f19685da014895df5881710756f7c3c228be1046241e/clevercsv-0.8.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:140bb7b429c4fbe903f8b789c8904ad7241be82b0d6205d1d0e3d599b0f5a31a", size = 112370 }, + { url = "https://files.pythonhosted.org/packages/f4/ac/0791e50cd884f02b7652517fd0a2253a2edd5ce2448d2c6d3c345d1d04ec/clevercsv-0.8.3-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:315fdadecee4e84268d8577dc9279142afe231f0b0bfb6a8950cca08f25e7f00", size = 112111 }, + { url = "https://files.pythonhosted.org/packages/e7/b8/6b1f6206a46f6a0ea91be9238711c1b208f99ee55c98db9df42dbe8d8885/clevercsv-0.8.3-cp311-cp311-win_amd64.whl", hash = "sha256:bb0d3c4c5b52cf65ae173a475e16ff0a16a10f9ccf45f85d40142607d03dd721", size = 84491 }, + { url = "https://files.pythonhosted.org/packages/49/6a/7d91337083a1020bf9c72800251c6694f13f0f936a02a361f5c3940d6ae3/clevercsv-0.8.3-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:2132d428b6101fd537222546899a688e3559e30da2f26106988644f84f9aa152", size = 87081 }, + { url = "https://files.pythonhosted.org/packages/df/6c/184e2410bc5659c12de10196afba7062ab3857c606ebc2e9d3b64a517569/clevercsv-0.8.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:114c54d1951c580fa7c8ec6f1db6fe3957fabdad5589146c775bc52803a92e43", size = 77996 }, + { url = "https://files.pythonhosted.org/packages/55/8c/bcc2651db860667fea33e99862f77d08840cfd95f6625748b0b37f93c415/clevercsv-0.8.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:c5d449ef53806aeb07e02abaa74bbe305276766000814ae3630005b92f1af405", size = 78892 }, + { url = "https://files.pythonhosted.org/packages/f6/56/18a050eb63130e3fb8dd3f0696e2fb5e38b24dd0e708fbab0838a04890a6/clevercsv-0.8.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b7b6e1f0a7847ca028b84c8cf168cd71637fec25653b90a45ca47727ae113bc2", size = 113216 }, + { url = "https://files.pythonhosted.org/packages/a6/68/9a54452da87e547a0c421e135a20a58c1d15ce438646d93c9a92b57eb504/clevercsv-0.8.3-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4ec679edfc7fb4b915bc91f7bf9784eb61e11eedfaaa8e25f524ba75ea57eca3", size = 113338 }, + { url = "https://files.pythonhosted.org/packages/55/5b/fd3b765515300b69e4139e501af4955f8565f0fa6ceceb304b1a84b3bff6/clevercsv-0.8.3-cp312-cp312-win_amd64.whl", hash = "sha256:6b2a0a0c494460d2cc40c5fb6a567d1d0cfed55441acfd4df9c81ee4aa20b202", size = 84424 }, ] [[package]] @@ -1003,14 +1003,14 @@ wheels = [ [[package]] name = "colorlog" -version = "6.8.2" +version = "6.9.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "colorama", marker = "sys_platform == 'win32'" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/db/38/2992ff192eaa7dd5a793f8b6570d6bbe887c4fbbf7e72702eb0a693a01c8/colorlog-6.8.2.tar.gz", hash = "sha256:3e3e079a41feb5a1b64f978b5ea4f46040a94f11f0e8bbb8261e3dbbeca64d44", size = 16529 } +sdist = { url = "https://files.pythonhosted.org/packages/d3/7a/359f4d5df2353f26172b3cc39ea32daa39af8de522205f512f458923e677/colorlog-6.9.0.tar.gz", hash = "sha256:bfba54a1b93b94f54e1f4fe48395725a3d92fd2a4af702f6bd70946bdc0c6ac2", size = 16624 } wheels = [ - { url = "https://files.pythonhosted.org/packages/f3/18/3e867ab37a24fdf073c1617b9c7830e06ec270b1ea4694a624038fc40a03/colorlog-6.8.2-py3-none-any.whl", hash = "sha256:4dcbb62368e2800cb3c5abd348da7e53f6c362dda502ec27c560b2e58a66bd33", size = 11357 }, + { url = "https://files.pythonhosted.org/packages/e3/51/9b208e85196941db2f0654ad0357ca6388ab3ed67efdbfc799f35d1f83aa/colorlog-6.9.0-py3-none-any.whl", hash = "sha256:5906e71acd67cb07a71e779c47c4bcb45fb8c2993eebe9e5adcd6a6f1b283eff", size = 11424 }, ] [[package]] @@ -1079,67 +1079,67 @@ wheels = [ [[package]] name = "couchbase" -version = "4.3.2" +version = "4.3.4" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/99/68/4aab031f1b2f2da3c661a7e18dd7bd276eee163ae9040cc4b2ab1a6417e1/couchbase-4.3.2.tar.gz", hash = "sha256:6f3c2fc874a8b6ca7e6c8b3aaebcbfa4e14937afdb470aaa9b16724c4746b8d5", size = 6678953 } +sdist = { url = "https://files.pythonhosted.org/packages/50/fe/f800243326a9e6c026c35f34f96ac4c7e02901b6a2dd300ac17564678aa4/couchbase-4.3.4.tar.gz", hash = "sha256:f195958606cf3a255fd96646ca3dd7e2ddcecf3664b3883826c7b89ef680088e", size = 6691719 } wheels = [ - { url = "https://files.pythonhosted.org/packages/df/2a/36704e6fc0e20aa20f8120078bd39bbbc691e83ffdc6c3acfe3a2dba03c4/couchbase-4.3.2-cp310-cp310-macosx_10_15_x86_64.whl", hash = "sha256:85df43305f2646203192d67a9433abb5e1098390cba6adec8c4f675ba9ba7fdc", size = 4832988 }, - { url = "https://files.pythonhosted.org/packages/63/22/31144f89d11120d0c9a7a853b5fc9967202dd192325d76e0df77805518fa/couchbase-4.3.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:5b8ee78c7a4b7451db6fcd534dc24462f2cd0e863f16495e687a23b7aecf8296", size = 4382128 }, - { url = "https://files.pythonhosted.org/packages/8d/43/e49e6760b328b4a9cd0f01d3aa89275fe5e60c87c73efbbfdaf9eb090e3f/couchbase-4.3.2-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:2841b86eb80454279548d8102ce6e71f5bc791eb4a83cb3575b7cf4104c374b2", size = 4923313 }, - { url = "https://files.pythonhosted.org/packages/97/ad/d844d3b5d9befec7f089f06cda5a36662bb1c033040549fc49eab723fb9f/couchbase-4.3.2-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:540545fd867de02985eb16733c1b16228b0e09461e44a9c2bfad0200fdf7d09a", size = 5133723 }, - { url = "https://files.pythonhosted.org/packages/63/df/e75058ec319d3134cb429ca165e5378afe723b6f90e2cf220fc2c18d5716/couchbase-4.3.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:52cdcd65fb6565f51ea4540fe823143f0fb9d650136b96b904b1650b05a06746", size = 5774711 }, - { url = "https://files.pythonhosted.org/packages/31/f3/4f2f14c974db97b07e9647d6a0823c033099ee69aa21b5df4e9f8b1ccef6/couchbase-4.3.2-cp310-cp310-win_amd64.whl", hash = "sha256:3fb88b9f52c2099a4e25fbc30f27734c3da5c86af930de1f4102d03a3df8e77a", size = 4168107 }, - { url = "https://files.pythonhosted.org/packages/5c/e9/53bfb2b4cdf75860e4f546cc5180799455c84687e56db25024f671f10798/couchbase-4.3.2-cp311-cp311-macosx_10_15_x86_64.whl", hash = "sha256:b12288e15326b6fae027a419467403d6c9f3f9641cd9cfee0ab0930a9d2315cd", size = 4893570 }, - { url = "https://files.pythonhosted.org/packages/5b/7a/7881ba48e243518bb1d764819cc5cc0f276f700f7bf41bbe43152d2fee97/couchbase-4.3.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:86e2713759b26ee279574d740151ba4b0ad859a45fc7ac1d13fcdd39d8ee2951", size = 4363576 }, - { url = "https://files.pythonhosted.org/packages/c4/f8/b103f4b81f88bdce0051a06e5c9e010926ed0464265522ba7b8855c84613/couchbase-4.3.2-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:6a43ce67ffe90bbb5460da5c95d778e804bcd81c037cc8a347f2966afc6c4b5a", size = 4923262 }, - { url = "https://files.pythonhosted.org/packages/84/88/9d069fc8c3c93132c90eae69d5314bcb1113f76792aaab0e39a95c9e298e/couchbase-4.3.2-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:401a7d5a442196bf805746b8354636753ec12c788fba918245345c32211bdf0c", size = 5133761 }, - { url = "https://files.pythonhosted.org/packages/09/49/4f4fd75b51ddc2966eb5e083a037ff28d97e717b50fc8c888e12fe349c05/couchbase-4.3.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:aac415f89c38482ac076b4b766537701e99f728cc1c5b2de8c16fa28ce7caa53", size = 5774882 }, - { url = "https://files.pythonhosted.org/packages/aa/30/48870d82e4cda53242e233971e7a3cc824b06686217f7564c3d91e561747/couchbase-4.3.2-cp311-cp311-win_amd64.whl", hash = "sha256:220fe6b75ebbda4651a8e0370642c0f5db5da7f3b0acd9fc8e2b5b31427f9fb1", size = 4168162 }, - { url = "https://files.pythonhosted.org/packages/96/70/3df0bfd638bdd3d363256fb4b504621ad5dc8b598346ef0d91fc1714ee14/couchbase-4.3.2-cp312-cp312-macosx_10_15_x86_64.whl", hash = "sha256:bf5814a8e9efe405c9c81145c8afca7e55b964543984c9d8dc340163597b09b2", size = 4834639 }, - { url = "https://files.pythonhosted.org/packages/34/b1/ef9c6d430ccb588ef2beed1ee073447015a062dc9418c8c404e7862e1b3e/couchbase-4.3.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:bd93d352ccb35c86eec9e5b4d1de015c26c15b52c80204f75189bde627b8b529", size = 4364926 }, - { url = "https://files.pythonhosted.org/packages/85/05/6f428c41eb2eee264079af6b81de3a74493965bf83165202a1df091a0e8d/couchbase-4.3.2-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:bbefa6111be033587b04b2586f5fc8d6db9a76ec138fea5288c8698c8f294bc2", size = 4925735 }, - { url = "https://files.pythonhosted.org/packages/b5/9a/ef3bf52e3c676560143678646cd9a3ac6077edae945527d4764715f8f953/couchbase-4.3.2-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:419a79b2a98bf3d168b264e0dfc1a0949727a2c3ef455e2ffe8e734a2fdc6e7a", size = 5137672 }, - { url = "https://files.pythonhosted.org/packages/98/7d/c9a64538ed1282daa47e0dc21d3fda6d648145598161ff8d4a7dac9ca279/couchbase-4.3.2-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:30115cde63fc18abe587d167bbb0d37e8c253f7430e08e69f64eaca2eb7e4ca0", size = 5773853 }, - { url = "https://files.pythonhosted.org/packages/4f/0c/6b3851f4041049154a1cfbf3093e5b6328084588242222024e8077731deb/couchbase-4.3.2-cp312-cp312-win_amd64.whl", hash = "sha256:5b4eccd4a0ac30d58ea0570a1882a8c0e367a9d54d80c0f6a288e348d1b2b41e", size = 4172214 }, + { url = "https://files.pythonhosted.org/packages/e7/49/31872ccf6747dd59874f0df7b3e48fe048d80db23717e3eef7c85d0513e0/couchbase-4.3.4-cp310-cp310-macosx_10_15_x86_64.whl", hash = "sha256:395e7b05495132a071dce5cdd84a3ec6e803205875f8ee22e85a89a16bb1b5f4", size = 4754167 }, + { url = "https://files.pythonhosted.org/packages/fe/3c/52711a3ad2d892f854da7fe9b1e3fcfc83af77eb18dadb52a68312c5e762/couchbase-4.3.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:263a18307d1f1a141b93ae370b19843b1160dd702559152aea19dd08768f59f5", size = 4295563 }, + { url = "https://files.pythonhosted.org/packages/72/ea/4afaf0162e69da68f214f8c214a17a87bf166bf6f9ef6b520fa233eb4f6b/couchbase-4.3.4-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:16751d4f3b0fe49666515ebed7967e8f38ec3862b329f773f88252acfd7c2b1f", size = 4803647 }, + { url = "https://files.pythonhosted.org/packages/9e/85/62fe50b7c9c44d4c9048f56696ec901ba01e911702b3a598ae0af8e23729/couchbase-4.3.4-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:4dcc7eb9f57825c0097785d1c042e146908d2883f5e733d4ca07ac548bb532a2", size = 5022268 }, + { url = "https://files.pythonhosted.org/packages/f5/1b/c2723a0afef2ff3f1bd67e4549e3ed980b8486f2853c9c4768bba05d8844/couchbase-4.3.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:42f16ca2ec636db9ecacd3b97db85c923be8374eaae2fe097124d8eb92b4293f", size = 5678659 }, + { url = "https://files.pythonhosted.org/packages/b3/f4/cfed2b00486db182d4b82bc80efeff35b6d838b0a781845dd0ada64c725c/couchbase-4.3.4-cp310-cp310-win_amd64.whl", hash = "sha256:8eecc9cdead68efe4119ebe41b065dadf83bc1653ec56470800c5093e378cacc", size = 4014799 }, + { url = "https://files.pythonhosted.org/packages/de/17/b348d21373e49b3becfbc0d6ccc3eef8f9e3a15ff2896c823e25c45be2ea/couchbase-4.3.4-cp311-cp311-macosx_10_15_x86_64.whl", hash = "sha256:1a6d6c4542e4ffe223960553e057bc175cfcee3fe274f63551e9d90d7c2435c5", size = 4754155 }, + { url = "https://files.pythonhosted.org/packages/14/c6/3a33bb2d96ef10e537eb03c16e10b87e5bde103fd56d9995ab574d65a3b5/couchbase-4.3.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:ae44db4ce78b691028075fc54beec2dc1a59829f53a2b282f9a8b3ea6b71ad22", size = 4278953 }, + { url = "https://files.pythonhosted.org/packages/4e/15/b4ca4e7c22fe577d119741caf5088c376da2b6583aa6e20051d3228595c9/couchbase-4.3.4-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:a175f1e447b9aeb7ab5aab66350261be28ad7d9a07fff9c7fe48c55828133ec3", size = 4803803 }, + { url = "https://files.pythonhosted.org/packages/c7/0d/2b30fb58bc749a18cabb8f5637119b7dca06643fb5459833b2cb1c9d4a3d/couchbase-4.3.4-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:efb0170d5e7766593d47292c14a782e201f0167175f0e60cd7ba3b9acd75e349", size = 5022471 }, + { url = "https://files.pythonhosted.org/packages/c9/d8/ec22e4f489b692bbe0bea2a1442b396b4ce390b3a9c59c5c682eb4232189/couchbase-4.3.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:3f7d9e0492727b8560d36f5cb45c2a6ec9507dd2120ddd6313fd21e04cfc2ab9", size = 5678702 }, + { url = "https://files.pythonhosted.org/packages/45/c4/298cacb666c9ed2ef01a71a3fbf67379ece150897eefb63eaa110980d38e/couchbase-4.3.4-cp311-cp311-win_amd64.whl", hash = "sha256:f32e9d87e5157b86af5de85200cab433690789551d2bda1b8e7a25bf2680d511", size = 4014801 }, + { url = "https://files.pythonhosted.org/packages/e8/14/17379edba7702cbd60c4801c029ba2645de9715c183b9da5d790241945dc/couchbase-4.3.4-cp312-cp312-macosx_10_15_x86_64.whl", hash = "sha256:395afab875aa3d293429cebc080cc12ac6e32c665275740d5a8445c688ad84ce", size = 4819405 }, + { url = "https://files.pythonhosted.org/packages/5c/d3/2851a0ce9038775ea2930831e2573dea609d2eb0ae7c4ef018c40ab1b36b/couchbase-4.3.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:852ff1e36668a9b0e0e4dc015df06e3a663bd5e0301a52c25b724969073a1a11", size = 4297796 }, + { url = "https://files.pythonhosted.org/packages/ed/9a/98691dc179695836b10067f1d9952313b92558e06ddf72b77f2c97c1bcd3/couchbase-4.3.4-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:79ab95992829de574e23588ce35fc14ab6f8a5fd378c046522a678b7583a9b29", size = 4805395 }, + { url = "https://files.pythonhosted.org/packages/87/03/d9a8ea299fd557f297db24d1b01b18192044b279cf969a44b9263b2a8b1b/couchbase-4.3.4-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:88827951b4132b89b6f37f1f2706b1e2f04870825c420e931c3caa770fc4a4e8", size = 5027446 }, + { url = "https://files.pythonhosted.org/packages/e4/d0/f18b2cb0ebc3719fadb02a177b0424a2b750ba49c9491d9e5af6afad1945/couchbase-4.3.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:d8f88c731d0d28132a992978aae5e1140a71276cc528ecc2ed408b2e386d1183", size = 5676955 }, + { url = "https://files.pythonhosted.org/packages/2a/fe/71977eea6600b2547e1acd59f7d6e37a1ba60225087b4aa3b067442b03df/couchbase-4.3.4-cp312-cp312-win_amd64.whl", hash = "sha256:fb137358e249c752dbecb44393769696c07fd069eb976b2a9890ddd457d35fcb", size = 4018188 }, ] [[package]] name = "coverage" -version = "7.6.2" +version = "7.6.9" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/9a/60/e781e8302e7b28f21ce06e30af077f856aa2cb4cf2253287dae9a593d509/coverage-7.6.2.tar.gz", hash = "sha256:a5f81e68aa62bc0cfca04f7b19eaa8f9c826b53fc82ab9e2121976dc74f131f3", size = 797872 } +sdist = { url = "https://files.pythonhosted.org/packages/5b/d2/c25011f4d036cf7e8acbbee07a8e09e9018390aee25ba085596c4b83d510/coverage-7.6.9.tar.gz", hash = "sha256:4a8d8977b0c6ef5aeadcb644da9e69ae0dcfe66ec7f368c89c72e058bd71164d", size = 801710 } wheels = [ - { url = "https://files.pythonhosted.org/packages/16/14/fb75c01b8427fb567c90ce920c90ed2bd314ad6960d54e8b377928607fd1/coverage-7.6.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c9df1950fb92d49970cce38100d7e7293c84ed3606eaa16ea0b6bc27175bb667", size = 206561 }, - { url = "https://files.pythonhosted.org/packages/93/b4/dcbf15f5583507415d0a78ce206e19d76699f1161e8b1ff6e1a21e9f9743/coverage-7.6.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:24500f4b0e03aab60ce575c85365beab64b44d4db837021e08339f61d1fbfe52", size = 206994 }, - { url = "https://files.pythonhosted.org/packages/47/ee/57d607e14479fb760721ea1784608ade532665934bd75f260b250dc6c877/coverage-7.6.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a663b180b6669c400b4630a24cc776f23a992d38ce7ae72ede2a397ce6b0f170", size = 235429 }, - { url = "https://files.pythonhosted.org/packages/76/e1/cd263fd750fdb115aab11a086e3584d99d46fca1f201b5493cc3972aea28/coverage-7.6.2-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:bfde025e2793a22efe8c21f807d276bd1d6a4bcc5ba6f19dbdfc4e7a12160909", size = 233329 }, - { url = "https://files.pythonhosted.org/packages/30/3b/a1623d50fcd6ba532cef0c3c1059eec2a08a311676ffa84dbe4beb2b8a33/coverage-7.6.2-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:087932079c065d7b8ebadd3a0160656c55954144af6439886c8bcf78bbbcde7f", size = 234491 }, - { url = "https://files.pythonhosted.org/packages/b1/a6/8f3b3fd1f9b9400f3df38a7159362622546e2d951cc4984cf4617d0fd4d7/coverage-7.6.2-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:9c6b0c1cafd96213a0327cf680acb39f70e452caf8e9a25aeb05316db9c07f89", size = 233589 }, - { url = "https://files.pythonhosted.org/packages/e3/40/37d64093f57b372435d87679956607ecab066d2aede76c6d215815a35fa3/coverage-7.6.2-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:6e85830eed5b5263ffa0c62428e43cb844296f3b4461f09e4bdb0d44ec190bc2", size = 232050 }, - { url = "https://files.pythonhosted.org/packages/80/63/cbb76298b4f42bffe0030f1bc129a26a26255857c6beaa20419259ac07cc/coverage-7.6.2-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:62ab4231c01e156ece1b3a187c87173f31cbeee83a5e1f6dff17f288dca93345", size = 233180 }, - { url = "https://files.pythonhosted.org/packages/7a/6a/eafa81503e905d473b799920927b06aa6ffba12db035fc98735b55bc1741/coverage-7.6.2-cp310-cp310-win32.whl", hash = "sha256:7b80fbb0da3aebde102a37ef0138aeedff45997e22f8962e5f16ae1742852676", size = 209281 }, - { url = "https://files.pythonhosted.org/packages/19/d1/6b354c2cd52e0244944c097aaa71896869878df999f5f8e75fcd37eaf0f3/coverage-7.6.2-cp310-cp310-win_amd64.whl", hash = "sha256:d20c3d1f31f14d6962a4e2f549c21d31e670b90f777ef4171be540fb7fb70f02", size = 210092 }, - { url = "https://files.pythonhosted.org/packages/a5/29/72da824da4182f518b054c21552b7ed2473a4e4c6ac616298209808a1a5c/coverage-7.6.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:bb21bac7783c1bf6f4bbe68b1e0ff0d20e7e7732cfb7995bc8d96e23aa90fc7b", size = 206667 }, - { url = "https://files.pythonhosted.org/packages/23/52/c15dcf3cf575256c7c0992e441cd41092a6c519d65abe1eb5567aab3d8e8/coverage-7.6.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a7b2e437fbd8fae5bc7716b9c7ff97aecc95f0b4d56e4ca08b3c8d8adcaadb84", size = 207111 }, - { url = "https://files.pythonhosted.org/packages/92/61/0d46dc26cf9f711b7b6078a54680665a5c2d62ec15991adb51e79236c699/coverage-7.6.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:536f77f2bf5797983652d1d55f1a7272a29afcc89e3ae51caa99b2db4e89d658", size = 239050 }, - { url = "https://files.pythonhosted.org/packages/3b/cb/9de71bade0343a0793f645f78a0e409248d85a2e5b4c4a9a1697c3b2e3d2/coverage-7.6.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f361296ca7054f0936b02525646b2731b32c8074ba6defab524b79b2b7eeac72", size = 236454 }, - { url = "https://files.pythonhosted.org/packages/f2/81/b0dc02487447c4a56cf2eed5c57735097f77aeff582277a35f1f70713a8d/coverage-7.6.2-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7926d8d034e06b479797c199747dd774d5e86179f2ce44294423327a88d66ca7", size = 238320 }, - { url = "https://files.pythonhosted.org/packages/60/90/76815a76234050a87d0d1438a34820c1b857dd17353855c02bddabbedea8/coverage-7.6.2-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:0bbae11c138585c89fb4e991faefb174a80112e1a7557d507aaa07675c62e66b", size = 237250 }, - { url = "https://files.pythonhosted.org/packages/f6/bd/760a599c08c882d97382855264586bba2604901029c3f6bec5710477ae81/coverage-7.6.2-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:fcad7d5d2bbfeae1026b395036a8aa5abf67e8038ae7e6a25c7d0f88b10a8e6a", size = 235880 }, - { url = "https://files.pythonhosted.org/packages/83/de/41c3b90a779e473ae1ca325542aa5fa5464b7d2061288e9c22ba5f1deaa3/coverage-7.6.2-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:f01e53575f27097d75d42de33b1b289c74b16891ce576d767ad8c48d17aeb5e0", size = 236653 }, - { url = "https://files.pythonhosted.org/packages/f4/90/61fe2721b9a9d9446e6c3ca33b6569e81d2a9a795ddfe786a66bf54035b7/coverage-7.6.2-cp311-cp311-win32.whl", hash = "sha256:7781f4f70c9b0b39e1b129b10c7d43a4e0c91f90c60435e6da8288efc2b73438", size = 209251 }, - { url = "https://files.pythonhosted.org/packages/96/87/d586f2b12b98288fc874d366cd8d5601f5a374cb75853647a3e4d02e4eb0/coverage-7.6.2-cp311-cp311-win_amd64.whl", hash = "sha256:9bcd51eeca35a80e76dc5794a9dd7cb04b97f0e8af620d54711793bfc1fbba4b", size = 210083 }, - { url = "https://files.pythonhosted.org/packages/3f/ac/1cca5ed5cf512a71cdd6e3afb75a5ef196f7ef9772be9192dadaaa5cfc1c/coverage-7.6.2-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:ebc94fadbd4a3f4215993326a6a00e47d79889391f5659bf310f55fe5d9f581c", size = 206856 }, - { url = "https://files.pythonhosted.org/packages/e4/58/030354d250f107a95e7aca24c7fd238709a3c7df3083cb206368798e637a/coverage-7.6.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:9681516288e3dcf0aa7c26231178cc0be6cac9705cac06709f2353c5b406cfea", size = 207098 }, - { url = "https://files.pythonhosted.org/packages/03/df/5f2cd6048d44a54bb5f58f8ece4efbc5b686ed49f8bd8dbf41eb2a6a687f/coverage-7.6.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8d9c5d13927d77af4fbe453953810db766f75401e764727e73a6ee4f82527b3e", size = 240109 }, - { url = "https://files.pythonhosted.org/packages/d3/18/7c53887643d921faa95529643b1b33e60ebba30ab835c8b5abd4e54d946b/coverage-7.6.2-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b92f9ca04b3e719d69b02dc4a69debb795af84cb7afd09c5eb5d54b4a1ae2191", size = 237141 }, - { url = "https://files.pythonhosted.org/packages/d2/79/339bdf597d128374e6150c089b37436ba694585d769cabf6d5abd73a1365/coverage-7.6.2-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0ff2ef83d6d0b527b5c9dad73819b24a2f76fdddcfd6c4e7a4d7e73ecb0656b4", size = 239210 }, - { url = "https://files.pythonhosted.org/packages/a9/62/7310c6de2bcb8a42f91094d41f0d4793ccda5a54621be3db76a156556cf2/coverage-7.6.2-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:47ccb6e99a3031ffbbd6e7cc041e70770b4fe405370c66a54dbf26a500ded80b", size = 238698 }, - { url = "https://files.pythonhosted.org/packages/f2/cb/ccb23c084d7f581f770dc7ed547dc5b50763334ad6ce26087a9ad0b5b26d/coverage-7.6.2-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:a867d26f06bcd047ef716175b2696b315cb7571ccb951006d61ca80bbc356e9e", size = 237000 }, - { url = "https://files.pythonhosted.org/packages/e7/ab/58de9e2f94e4dc91b84d6e2705aa1e9d5447a2669fe113b4bbce6d2224a1/coverage-7.6.2-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:cdfcf2e914e2ba653101157458afd0ad92a16731eeba9a611b5cbb3e7124e74b", size = 238666 }, - { url = "https://files.pythonhosted.org/packages/6c/dc/8be87b9ed5dbd4892b603f41088b41982768e928734e5bdce67d2ddd460a/coverage-7.6.2-cp312-cp312-win32.whl", hash = "sha256:f9035695dadfb397bee9eeaf1dc7fbeda483bf7664a7397a629846800ce6e276", size = 209489 }, - { url = "https://files.pythonhosted.org/packages/64/3a/3f44e55273a58bfb39b87ad76541bbb81d14de916b034fdb39971cc99ffe/coverage-7.6.2-cp312-cp312-win_amd64.whl", hash = "sha256:5ed69befa9a9fc796fe015a7040c9398722d6b97df73a6b608e9e275fa0932b0", size = 210270 }, - { url = "https://files.pythonhosted.org/packages/9d/5c/88f15b7614ba9ed1dbb1c0bd2c9073184b96c2bead0b93199487b44d04b3/coverage-7.6.2-pp39.pp310-none-any.whl", hash = "sha256:667952739daafe9616db19fbedbdb87917eee253ac4f31d70c7587f7ab531b4e", size = 198799 }, + { url = "https://files.pythonhosted.org/packages/49/f3/f830fb53bf7e4f1d5542756f61d9b740352a188f43854aab9409c8cdeb18/coverage-7.6.9-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:85d9636f72e8991a1706b2b55b06c27545448baf9f6dbf51c4004609aacd7dcb", size = 207024 }, + { url = "https://files.pythonhosted.org/packages/4e/e3/ea5632a3a6efd00ab0a791adc0f3e48512097a757ee7dcbee5505f57bafa/coverage-7.6.9-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:608a7fd78c67bee8936378299a6cb9f5149bb80238c7a566fc3e6717a4e68710", size = 207463 }, + { url = "https://files.pythonhosted.org/packages/e4/ae/18ff8b5580e27e62ebcc888082aa47694c2772782ea7011ddf58e377e98f/coverage-7.6.9-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:96d636c77af18b5cb664ddf12dab9b15a0cfe9c0bde715da38698c8cea748bfa", size = 235902 }, + { url = "https://files.pythonhosted.org/packages/6a/52/57030a8d15ab935624d298360f0a6704885578e39f7b4f68569e59f5902d/coverage-7.6.9-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d75cded8a3cff93da9edc31446872d2997e327921d8eed86641efafd350e1df1", size = 233806 }, + { url = "https://files.pythonhosted.org/packages/d0/c5/4466602195ecaced298d55af1e29abceb812addabefd5bd9116a204f7bab/coverage-7.6.9-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f7b15f589593110ae767ce997775d645b47e5cbbf54fd322f8ebea6277466cec", size = 234966 }, + { url = "https://files.pythonhosted.org/packages/b0/1c/55552c3009b7bf96732e36548596ade771c87f89cf1f5a8e3975b33539b5/coverage-7.6.9-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:44349150f6811b44b25574839b39ae35291f6496eb795b7366fef3bd3cf112d3", size = 234029 }, + { url = "https://files.pythonhosted.org/packages/bb/7d/da3dca6878701182ea42c51df47a47c80eaef2a76f5aa3e891dc2a8cce3f/coverage-7.6.9-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:d891c136b5b310d0e702e186d70cd16d1119ea8927347045124cb286b29297e5", size = 232494 }, + { url = "https://files.pythonhosted.org/packages/28/cc/39de85ac1d5652bc34ff2bee39ae251b1fdcaae53fab4b44cab75a432bc0/coverage-7.6.9-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:db1dab894cc139f67822a92910466531de5ea6034ddfd2b11c0d4c6257168073", size = 233611 }, + { url = "https://files.pythonhosted.org/packages/d1/2b/7eb011a9378911088708f121825a71134d0c15fac96972a0ae7a8f5a4049/coverage-7.6.9-cp310-cp310-win32.whl", hash = "sha256:41ff7b0da5af71a51b53f501a3bac65fb0ec311ebed1632e58fc6107f03b9198", size = 209712 }, + { url = "https://files.pythonhosted.org/packages/5b/35/c3f40a2269b416db34ce1dedf682a7132c26f857e33596830fa4deebabf9/coverage-7.6.9-cp310-cp310-win_amd64.whl", hash = "sha256:35371f8438028fdccfaf3570b31d98e8d9eda8bb1d6ab9473f5a390969e98717", size = 210553 }, + { url = "https://files.pythonhosted.org/packages/b1/91/b3dc2f7f38b5cca1236ab6bbb03e84046dd887707b4ec1db2baa47493b3b/coverage-7.6.9-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:932fc826442132dde42ee52cf66d941f581c685a6313feebed358411238f60f9", size = 207133 }, + { url = "https://files.pythonhosted.org/packages/0d/2b/53fd6cb34d443429a92b3ec737f4953627e38b3bee2a67a3c03425ba8573/coverage-7.6.9-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:085161be5f3b30fd9b3e7b9a8c301f935c8313dcf928a07b116324abea2c1c2c", size = 207577 }, + { url = "https://files.pythonhosted.org/packages/74/f2/68edb1e6826f980a124f21ea5be0d324180bf11de6fd1defcf9604f76df0/coverage-7.6.9-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ccc660a77e1c2bf24ddbce969af9447a9474790160cfb23de6be4fa88e3951c7", size = 239524 }, + { url = "https://files.pythonhosted.org/packages/d3/83/8fec0ee68c2c4a5ab5f0f8527277f84ed6f2bd1310ae8a19d0c5532253ab/coverage-7.6.9-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c69e42c892c018cd3c8d90da61d845f50a8243062b19d228189b0224150018a9", size = 236925 }, + { url = "https://files.pythonhosted.org/packages/8b/20/8f50e7c7ad271144afbc2c1c6ec5541a8c81773f59352f8db544cad1a0ec/coverage-7.6.9-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0824a28ec542a0be22f60c6ac36d679e0e262e5353203bea81d44ee81fe9c6d4", size = 238792 }, + { url = "https://files.pythonhosted.org/packages/6f/62/4ac2e5ad9e7a5c9ec351f38947528e11541f1f00e8a0cdce56f1ba7ae301/coverage-7.6.9-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:4401ae5fc52ad8d26d2a5d8a7428b0f0c72431683f8e63e42e70606374c311a1", size = 237682 }, + { url = "https://files.pythonhosted.org/packages/58/2f/9d2203f012f3b0533c73336c74134b608742be1ce475a5c72012573cfbb4/coverage-7.6.9-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:98caba4476a6c8d59ec1eb00c7dd862ba9beca34085642d46ed503cc2d440d4b", size = 236310 }, + { url = "https://files.pythonhosted.org/packages/33/6d/31f6ab0b4f0f781636075f757eb02141ea1b34466d9d1526dbc586ed7078/coverage-7.6.9-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ee5defd1733fd6ec08b168bd4f5387d5b322f45ca9e0e6c817ea6c4cd36313e3", size = 237096 }, + { url = "https://files.pythonhosted.org/packages/7d/fb/e14c38adebbda9ed8b5f7f8e03340ac05d68d27b24397f8d47478927a333/coverage-7.6.9-cp311-cp311-win32.whl", hash = "sha256:f2d1ec60d6d256bdf298cb86b78dd715980828f50c46701abc3b0a2b3f8a0dc0", size = 209682 }, + { url = "https://files.pythonhosted.org/packages/a4/11/a782af39b019066af83fdc0e8825faaccbe9d7b19a803ddb753114b429cc/coverage-7.6.9-cp311-cp311-win_amd64.whl", hash = "sha256:0d59fd927b1f04de57a2ba0137166d31c1a6dd9e764ad4af552912d70428c92b", size = 210542 }, + { url = "https://files.pythonhosted.org/packages/60/52/b16af8989a2daf0f80a88522bd8e8eed90b5fcbdecf02a6888f3e80f6ba7/coverage-7.6.9-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:99e266ae0b5d15f1ca8d278a668df6f51cc4b854513daab5cae695ed7b721cf8", size = 207325 }, + { url = "https://files.pythonhosted.org/packages/0f/79/6b7826fca8846c1216a113227b9f114ac3e6eacf168b4adcad0cb974aaca/coverage-7.6.9-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:9901d36492009a0a9b94b20e52ebfc8453bf49bb2b27bca2c9706f8b4f5a554a", size = 207563 }, + { url = "https://files.pythonhosted.org/packages/a7/07/0bc73da0ccaf45d0d64ef86d33b7d7fdeef84b4c44bf6b85fb12c215c5a6/coverage-7.6.9-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:abd3e72dd5b97e3af4246cdada7738ef0e608168de952b837b8dd7e90341f015", size = 240580 }, + { url = "https://files.pythonhosted.org/packages/71/8a/9761f409910961647d892454687cedbaccb99aae828f49486734a82ede6e/coverage-7.6.9-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ff74026a461eb0660366fb01c650c1d00f833a086b336bdad7ab00cc952072b3", size = 237613 }, + { url = "https://files.pythonhosted.org/packages/8b/10/ee7d696a17ac94f32f2dbda1e17e730bf798ae9931aec1fc01c1944cd4de/coverage-7.6.9-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:65dad5a248823a4996724a88eb51d4b31587aa7aa428562dbe459c684e5787ae", size = 239684 }, + { url = "https://files.pythonhosted.org/packages/16/60/aa1066040d3c52fff051243c2d6ccda264da72dc6d199d047624d395b2b2/coverage-7.6.9-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:22be16571504c9ccea919fcedb459d5ab20d41172056206eb2994e2ff06118a4", size = 239112 }, + { url = "https://files.pythonhosted.org/packages/4e/e5/69f35344c6f932ba9028bf168d14a79fedb0dd4849b796d43c81ce75a3c9/coverage-7.6.9-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:0f957943bc718b87144ecaee70762bc2bc3f1a7a53c7b861103546d3a403f0a6", size = 237428 }, + { url = "https://files.pythonhosted.org/packages/32/20/adc895523c4a28f63441b8ac645abd74f9bdd499d2d175bef5b41fc7f92d/coverage-7.6.9-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:0ae1387db4aecb1f485fb70a6c0148c6cdaebb6038f1d40089b1fc84a5db556f", size = 239098 }, + { url = "https://files.pythonhosted.org/packages/a9/a6/e0e74230c9bb3549ec8ffc137cfd16ea5d56e993d6bffed2218bff6187e3/coverage-7.6.9-cp312-cp312-win32.whl", hash = "sha256:1a330812d9cc7ac2182586f6d41b4d0fadf9be9049f350e0efb275c8ee8eb692", size = 209940 }, + { url = "https://files.pythonhosted.org/packages/3e/18/cb5b88349d4aa2f41ec78d65f92ea32572b30b3f55bc2b70e87578b8f434/coverage-7.6.9-cp312-cp312-win_amd64.whl", hash = "sha256:b12c6b18269ca471eedd41c1b6a1065b2f7827508edb9a7ed5555e9a56dcfc97", size = 210726 }, + { url = "https://files.pythonhosted.org/packages/15/0e/4ac9035ee2ee08d2b703fdad2d84283ec0bad3b46eb4ad6affb150174cb6/coverage-7.6.9-pp39.pp310-none-any.whl", hash = "sha256:f3ca78518bc6bc92828cd11867b121891d75cae4ea9e908d72030609b996db1b", size = 199270 }, ] [package.optional-dependencies] @@ -1206,35 +1206,35 @@ wheels = [ [[package]] name = "cryptography" -version = "43.0.1" +version = "43.0.3" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "cffi", marker = "platform_python_implementation != 'PyPy'" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/de/ba/0664727028b37e249e73879348cc46d45c5c1a2a2e81e8166462953c5755/cryptography-43.0.1.tar.gz", hash = "sha256:203e92a75716d8cfb491dc47c79e17d0d9207ccffcbcb35f598fbe463ae3444d", size = 686927 } +sdist = { url = "https://files.pythonhosted.org/packages/0d/05/07b55d1fa21ac18c3a8c79f764e2514e6f6a9698f1be44994f5adf0d29db/cryptography-43.0.3.tar.gz", hash = "sha256:315b9001266a492a6ff443b61238f956b214dbec9910a081ba5b6646a055a805", size = 686989 } wheels = [ - { url = "https://files.pythonhosted.org/packages/58/28/b92c98a04ba762f8cdeb54eba5c4c84e63cac037a7c5e70117d337b15ad6/cryptography-43.0.1-cp37-abi3-macosx_10_9_universal2.whl", hash = "sha256:8385d98f6a3bf8bb2d65a73e17ed87a3ba84f6991c155691c51112075f9ffc5d", size = 6223222 }, - { url = "https://files.pythonhosted.org/packages/33/13/1193774705783ba364121aa2a60132fa31a668b8ababd5edfa1662354ccd/cryptography-43.0.1-cp37-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:27e613d7077ac613e399270253259d9d53872aaf657471473ebfc9a52935c062", size = 3794751 }, - { url = "https://files.pythonhosted.org/packages/5e/4b/39bb3c4c8cfb3e94e736b8d8859ce5c81536e91a1033b1d26770c4249000/cryptography-43.0.1-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:68aaecc4178e90719e95298515979814bda0cbada1256a4485414860bd7ab962", size = 3981827 }, - { url = "https://files.pythonhosted.org/packages/ce/dc/1471d4d56608e1013237af334b8a4c35d53895694fbb73882d1c4fd3f55e/cryptography-43.0.1-cp37-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:de41fd81a41e53267cb020bb3a7212861da53a7d39f863585d13ea11049cf277", size = 3780034 }, - { url = "https://files.pythonhosted.org/packages/ad/43/7a9920135b0d5437cc2f8f529fa757431eb6a7736ddfadfdee1cc5890800/cryptography-43.0.1-cp37-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:f98bf604c82c416bc829e490c700ca1553eafdf2912a91e23a79d97d9801372a", size = 3993407 }, - { url = "https://files.pythonhosted.org/packages/cc/42/9ab8467af6c0b76f3d9b8f01d1cf25b9c9f3f2151f4acfab888d21c55a72/cryptography-43.0.1-cp37-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:61ec41068b7b74268fa86e3e9e12b9f0c21fcf65434571dbb13d954bceb08042", size = 3886457 }, - { url = "https://files.pythonhosted.org/packages/a4/65/430509e31700286ec02868a2457d2111d03ccefc20349d24e58d171ae0a7/cryptography-43.0.1-cp37-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:014f58110f53237ace6a408b5beb6c427b64e084eb451ef25a28308270086494", size = 4081499 }, - { url = "https://files.pythonhosted.org/packages/bb/18/a04b6467e6e09df8c73b91dcee8878f4a438a43a3603dc3cd6f8003b92d8/cryptography-43.0.1-cp37-abi3-win32.whl", hash = "sha256:2bd51274dcd59f09dd952afb696bf9c61a7a49dfc764c04dd33ef7a6b502a1e2", size = 2616504 }, - { url = "https://files.pythonhosted.org/packages/cc/73/0eacbdc437202edcbdc07f3576ed8fb8b0ab79d27bf2c5d822d758a72faa/cryptography-43.0.1-cp37-abi3-win_amd64.whl", hash = "sha256:666ae11966643886c2987b3b721899d250855718d6d9ce41b521252a17985f4d", size = 3067456 }, - { url = "https://files.pythonhosted.org/packages/8a/b6/bc54b371f02cffd35ff8dc6baba88304d7cf8e83632566b4b42e00383e03/cryptography-43.0.1-cp39-abi3-macosx_10_9_universal2.whl", hash = "sha256:ac119bb76b9faa00f48128b7f5679e1d8d437365c5d26f1c2c3f0da4ce1b553d", size = 6225263 }, - { url = "https://files.pythonhosted.org/packages/00/0e/8217e348a1fa417ec4c78cd3cdf24154f5e76fd7597343a35bd403650dfd/cryptography-43.0.1-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1bbcce1a551e262dfbafb6e6252f1ae36a248e615ca44ba302df077a846a8806", size = 3794368 }, - { url = "https://files.pythonhosted.org/packages/3d/ed/38b6be7254d8f7251fde8054af597ee8afa14f911da67a9410a45f602fc3/cryptography-43.0.1-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:58d4e9129985185a06d849aa6df265bdd5a74ca6e1b736a77959b498e0505b85", size = 3981750 }, - { url = "https://files.pythonhosted.org/packages/64/f3/b7946c3887cf7436f002f4cbb1e6aec77b8d299b86be48eeadfefb937c4b/cryptography-43.0.1-cp39-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:d03a475165f3134f773d1388aeb19c2d25ba88b6a9733c5c590b9ff7bbfa2e0c", size = 3778925 }, - { url = "https://files.pythonhosted.org/packages/ac/7e/ebda4dd4ae098a0990753efbb4b50954f1d03003846b943ea85070782da7/cryptography-43.0.1-cp39-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:511f4273808ab590912a93ddb4e3914dfd8a388fed883361b02dea3791f292e1", size = 3993152 }, - { url = "https://files.pythonhosted.org/packages/43/f6/feebbd78a3e341e3913846a3bb2c29d0b09b1b3af1573c6baabc2533e147/cryptography-43.0.1-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:80eda8b3e173f0f247f711eef62be51b599b5d425c429b5d4ca6a05e9e856baa", size = 3886392 }, - { url = "https://files.pythonhosted.org/packages/bd/4c/ab0b9407d5247576290b4fd8abd06b7f51bd414f04eef0f2800675512d61/cryptography-43.0.1-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:38926c50cff6f533f8a2dae3d7f19541432610d114a70808f0926d5aaa7121e4", size = 4082606 }, - { url = "https://files.pythonhosted.org/packages/05/36/e532a671998d6fcfdb9122da16434347a58a6bae9465e527e450e0bc60a5/cryptography-43.0.1-cp39-abi3-win32.whl", hash = "sha256:a575913fb06e05e6b4b814d7f7468c2c660e8bb16d8d5a1faf9b33ccc569dd47", size = 2617948 }, - { url = "https://files.pythonhosted.org/packages/b3/c6/c09cee6968add5ff868525c3815e5dccc0e3c6e89eec58dc9135d3c40e88/cryptography-43.0.1-cp39-abi3-win_amd64.whl", hash = "sha256:d75601ad10b059ec832e78823b348bfa1a59f6b8d545db3a24fd44362a1564cb", size = 3070445 }, - { url = "https://files.pythonhosted.org/packages/18/23/4175dcd935e1649865e1af7bd0b827cc9d9769a586dcc84f7cbe96839086/cryptography-43.0.1-pp310-pypy310_pp73-macosx_10_9_x86_64.whl", hash = "sha256:ea25acb556320250756e53f9e20a4177515f012c9eaea17eb7587a8c4d8ae034", size = 3152694 }, - { url = "https://files.pythonhosted.org/packages/ea/45/967da50269954b993d4484bf85026c7377bd551651ebdabba94905972556/cryptography-43.0.1-pp310-pypy310_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:c1332724be35d23a854994ff0b66530119500b6053d0bd3363265f7e5e77288d", size = 3713077 }, - { url = "https://files.pythonhosted.org/packages/df/e6/ccd29a1f9a6b71294e1e9f530c4d779d5dd37c8bb736c05d5fb6d98a971b/cryptography-43.0.1-pp310-pypy310_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:fba1007b3ef89946dbbb515aeeb41e30203b004f0b4b00e5e16078b518563289", size = 3915597 }, - { url = "https://files.pythonhosted.org/packages/a2/80/fb7d668f1be5e4443b7ac191f68390be24f7c2ebd36011741f62c7645eb2/cryptography-43.0.1-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:5b43d1ea6b378b54a1dc99dd8a2b5be47658fe9a7ce0a58ff0b55f4b43ef2b84", size = 2989208 }, + { url = "https://files.pythonhosted.org/packages/1f/f3/01fdf26701a26f4b4dbc337a26883ad5bccaa6f1bbbdd29cd89e22f18a1c/cryptography-43.0.3-cp37-abi3-macosx_10_9_universal2.whl", hash = "sha256:bf7a1932ac4176486eab36a19ed4c0492da5d97123f1406cf15e41b05e787d2e", size = 6225303 }, + { url = "https://files.pythonhosted.org/packages/a3/01/4896f3d1b392025d4fcbecf40fdea92d3df8662123f6835d0af828d148fd/cryptography-43.0.3-cp37-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:63efa177ff54aec6e1c0aefaa1a241232dcd37413835a9b674b6e3f0ae2bfd3e", size = 3760905 }, + { url = "https://files.pythonhosted.org/packages/0a/be/f9a1f673f0ed4b7f6c643164e513dbad28dd4f2dcdf5715004f172ef24b6/cryptography-43.0.3-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7e1ce50266f4f70bf41a2c6dc4358afadae90e2a1e5342d3c08883df1675374f", size = 3977271 }, + { url = "https://files.pythonhosted.org/packages/4e/49/80c3a7b5514d1b416d7350830e8c422a4d667b6d9b16a9392ebfd4a5388a/cryptography-43.0.3-cp37-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:443c4a81bb10daed9a8f334365fe52542771f25aedaf889fd323a853ce7377d6", size = 3746606 }, + { url = "https://files.pythonhosted.org/packages/0e/16/a28ddf78ac6e7e3f25ebcef69ab15c2c6be5ff9743dd0709a69a4f968472/cryptography-43.0.3-cp37-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:74f57f24754fe349223792466a709f8e0c093205ff0dca557af51072ff47ab18", size = 3986484 }, + { url = "https://files.pythonhosted.org/packages/01/f5/69ae8da70c19864a32b0315049866c4d411cce423ec169993d0434218762/cryptography-43.0.3-cp37-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:9762ea51a8fc2a88b70cf2995e5675b38d93bf36bd67d91721c309df184f49bd", size = 3852131 }, + { url = "https://files.pythonhosted.org/packages/fd/db/e74911d95c040f9afd3612b1f732e52b3e517cb80de8bf183be0b7d413c6/cryptography-43.0.3-cp37-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:81ef806b1fef6b06dcebad789f988d3b37ccaee225695cf3e07648eee0fc6b73", size = 4075647 }, + { url = "https://files.pythonhosted.org/packages/56/48/7b6b190f1462818b324e674fa20d1d5ef3e24f2328675b9b16189cbf0b3c/cryptography-43.0.3-cp37-abi3-win32.whl", hash = "sha256:cbeb489927bd7af4aa98d4b261af9a5bc025bd87f0e3547e11584be9e9427be2", size = 2623873 }, + { url = "https://files.pythonhosted.org/packages/eb/b1/0ebff61a004f7f89e7b65ca95f2f2375679d43d0290672f7713ee3162aff/cryptography-43.0.3-cp37-abi3-win_amd64.whl", hash = "sha256:f46304d6f0c6ab8e52770addfa2fc41e6629495548862279641972b6215451cd", size = 3068039 }, + { url = "https://files.pythonhosted.org/packages/30/d5/c8b32c047e2e81dd172138f772e81d852c51f0f2ad2ae8a24f1122e9e9a7/cryptography-43.0.3-cp39-abi3-macosx_10_9_universal2.whl", hash = "sha256:8ac43ae87929a5982f5948ceda07001ee5e83227fd69cf55b109144938d96984", size = 6222984 }, + { url = "https://files.pythonhosted.org/packages/2f/78/55356eb9075d0be6e81b59f45c7b48df87f76a20e73893872170471f3ee8/cryptography-43.0.3-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:846da004a5804145a5f441b8530b4bf35afbf7da70f82409f151695b127213d5", size = 3762968 }, + { url = "https://files.pythonhosted.org/packages/2a/2c/488776a3dc843f95f86d2f957ca0fc3407d0242b50bede7fad1e339be03f/cryptography-43.0.3-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0f996e7268af62598f2fc1204afa98a3b5712313a55c4c9d434aef49cadc91d4", size = 3977754 }, + { url = "https://files.pythonhosted.org/packages/7c/04/2345ca92f7a22f601a9c62961741ef7dd0127c39f7310dffa0041c80f16f/cryptography-43.0.3-cp39-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:f7b178f11ed3664fd0e995a47ed2b5ff0a12d893e41dd0494f406d1cf555cab7", size = 3749458 }, + { url = "https://files.pythonhosted.org/packages/ac/25/e715fa0bc24ac2114ed69da33adf451a38abb6f3f24ec207908112e9ba53/cryptography-43.0.3-cp39-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:c2e6fc39c4ab499049df3bdf567f768a723a5e8464816e8f009f121a5a9f4405", size = 3988220 }, + { url = "https://files.pythonhosted.org/packages/21/ce/b9c9ff56c7164d8e2edfb6c9305045fbc0df4508ccfdb13ee66eb8c95b0e/cryptography-43.0.3-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:e1be4655c7ef6e1bbe6b5d0403526601323420bcf414598955968c9ef3eb7d16", size = 3853898 }, + { url = "https://files.pythonhosted.org/packages/2a/33/b3682992ab2e9476b9c81fff22f02c8b0a1e6e1d49ee1750a67d85fd7ed2/cryptography-43.0.3-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:df6b6c6d742395dd77a23ea3728ab62f98379eff8fb61be2744d4679ab678f73", size = 4076592 }, + { url = "https://files.pythonhosted.org/packages/81/1e/ffcc41b3cebd64ca90b28fd58141c5f68c83d48563c88333ab660e002cd3/cryptography-43.0.3-cp39-abi3-win32.whl", hash = "sha256:d56e96520b1020449bbace2b78b603442e7e378a9b3bd68de65c782db1507995", size = 2623145 }, + { url = "https://files.pythonhosted.org/packages/87/5c/3dab83cc4aba1f4b0e733e3f0c3e7d4386440d660ba5b1e3ff995feb734d/cryptography-43.0.3-cp39-abi3-win_amd64.whl", hash = "sha256:0c580952eef9bf68c4747774cde7ec1d85a6e61de97281f2dba83c7d2c806362", size = 3068026 }, + { url = "https://files.pythonhosted.org/packages/6f/db/d8b8a039483f25fc3b70c90bc8f3e1d4497a99358d610c5067bf3bd4f0af/cryptography-43.0.3-pp310-pypy310_pp73-macosx_10_9_x86_64.whl", hash = "sha256:d03b5621a135bffecad2c73e9f4deb1a0f977b9a8ffe6f8e002bf6c9d07b918c", size = 3144545 }, + { url = "https://files.pythonhosted.org/packages/93/90/116edd5f8ec23b2dc879f7a42443e073cdad22950d3c8ee834e3b8124543/cryptography-43.0.3-pp310-pypy310_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:a2a431ee15799d6db9fe80c82b055bae5a752bef645bba795e8e52687c69efe3", size = 3679828 }, + { url = "https://files.pythonhosted.org/packages/d8/32/1e1d78b316aa22c0ba6493cc271c1c309969e5aa5c22c830a1d7ce3471e6/cryptography-43.0.3-pp310-pypy310_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:281c945d0e28c92ca5e5930664c1cefd85efe80e5c0d2bc58dd63383fda29f83", size = 3908132 }, + { url = "https://files.pythonhosted.org/packages/91/bb/cd2c13be3332e7af3cdf16154147952d39075b9f61ea5e6b5241bf4bf436/cryptography-43.0.3-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:f18c716be16bc1fea8e95def49edf46b82fccaa88587a45f8dc0ff6ab5d8e0a7", size = 2988811 }, ] [[package]] @@ -1289,23 +1289,23 @@ wheels = [ [[package]] name = "debugpy" -version = "1.8.7" +version = "1.8.9" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/6d/00/5a8b5dc8f52617c5e41845e26290ebea1ba06377cc08155b6d245c27b386/debugpy-1.8.7.zip", hash = "sha256:18b8f731ed3e2e1df8e9cdaa23fb1fc9c24e570cd0081625308ec51c82efe42e", size = 4957835 } +sdist = { url = "https://files.pythonhosted.org/packages/88/92/15b454c516c4c53cc8c03967e4be12b65a1ea36db3bb4513a7453f75c8d8/debugpy-1.8.9.zip", hash = "sha256:1339e14c7d980407248f09824d1b25ff5c5616651689f1e0f0e51bdead3ea13e", size = 4921695 } wheels = [ - { url = "https://files.pythonhosted.org/packages/46/50/1850a5a0cab6f65a21e452166ec60bac5f8a995184d17e18bb9dc3789c72/debugpy-1.8.7-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:95fe04a573b8b22896c404365e03f4eda0ce0ba135b7667a1e57bd079793b96b", size = 2090182 }, - { url = "https://files.pythonhosted.org/packages/87/51/ef4d5c55c06689b377678bdee870e3df8eb2a3d9cf0e618b4d7255413c8a/debugpy-1.8.7-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:628a11f4b295ffb4141d8242a9bb52b77ad4a63a2ad19217a93be0f77f2c28c9", size = 3547569 }, - { url = "https://files.pythonhosted.org/packages/eb/df/a4ea1f95022f93522b59b71ec42d6703abe3e0bee753070118816555fee9/debugpy-1.8.7-cp310-cp310-win32.whl", hash = "sha256:85ce9c1d0eebf622f86cc68618ad64bf66c4fc3197d88f74bb695a416837dd55", size = 5153144 }, - { url = "https://files.pythonhosted.org/packages/47/f7/912408b69e83659bd62fa29ebb7984efe81aed4f5e08bfe10e31a1dc3c3a/debugpy-1.8.7-cp310-cp310-win_amd64.whl", hash = "sha256:29e1571c276d643757ea126d014abda081eb5ea4c851628b33de0c2b6245b037", size = 5185605 }, - { url = "https://files.pythonhosted.org/packages/f6/0a/4a4516ef4c07891542cb25620085507cab3c6b23a42b5630c17788fff83e/debugpy-1.8.7-cp311-cp311-macosx_14_0_universal2.whl", hash = "sha256:caf528ff9e7308b74a1749c183d6808ffbedbb9fb6af78b033c28974d9b8831f", size = 2204794 }, - { url = "https://files.pythonhosted.org/packages/46/6f/2bb0bba20b8b74b7c341379dd99275cf6aa7722c1948fa99728716aad1b9/debugpy-1.8.7-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cba1d078cf2e1e0b8402e6bda528bf8fda7ccd158c3dba6c012b7897747c41a0", size = 3122160 }, - { url = "https://files.pythonhosted.org/packages/c0/ce/833351375cef971f0caa63fa82adf3f6949ad85410813026a4a436083a71/debugpy-1.8.7-cp311-cp311-win32.whl", hash = "sha256:171899588bcd412151e593bd40d9907133a7622cd6ecdbdb75f89d1551df13c2", size = 5078675 }, - { url = "https://files.pythonhosted.org/packages/7d/e1/e9ac2d546143a4defbaa2e609e173c912fb989cdfb5385c9771770a6bf5c/debugpy-1.8.7-cp311-cp311-win_amd64.whl", hash = "sha256:6e1c4ffb0c79f66e89dfd97944f335880f0d50ad29525dc792785384923e2211", size = 5102927 }, - { url = "https://files.pythonhosted.org/packages/59/4b/9f52ca1a799601a10cd2673503658bd8c8ecc4a7a43302ee29cf062474ec/debugpy-1.8.7-cp312-cp312-macosx_14_0_universal2.whl", hash = "sha256:4d27d842311353ede0ad572600c62e4bcd74f458ee01ab0dd3a1a4457e7e3706", size = 2529803 }, - { url = "https://files.pythonhosted.org/packages/80/79/8bba39190d2ea17840925d287f1c6c3a7c60b58f5090444e9ecf176c540f/debugpy-1.8.7-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:703c1fd62ae0356e194f3e7b7a92acd931f71fe81c4b3be2c17a7b8a4b546ec2", size = 4170911 }, - { url = "https://files.pythonhosted.org/packages/3b/19/5b3d312936db8eb281310fa27903459328ed722d845d594ba5feaeb2f0b3/debugpy-1.8.7-cp312-cp312-win32.whl", hash = "sha256:2f729228430ef191c1e4df72a75ac94e9bf77413ce5f3f900018712c9da0aaca", size = 5195476 }, - { url = "https://files.pythonhosted.org/packages/9f/49/ad20b29f8c921fd5124530d3d39b8f2077efd51b71339a2eff02bba693e9/debugpy-1.8.7-cp312-cp312-win_amd64.whl", hash = "sha256:45c30aaefb3e1975e8a0258f5bbd26cd40cde9bfe71e9e5a7ac82e79bad64e39", size = 5235031 }, - { url = "https://files.pythonhosted.org/packages/51/b1/a0866521c71a6ae3d3ca320e74835163a4671b1367ba360a55a0a51e5a91/debugpy-1.8.7-py2.py3-none-any.whl", hash = "sha256:57b00de1c8d2c84a61b90880f7e5b6deaf4c312ecbde3a0e8912f2a56c4ac9ae", size = 5210683 }, + { url = "https://files.pythonhosted.org/packages/d0/2e/92fda96b1b773e454daae3e2962726dd9f7aedb1f26d7f2ca353d91a930b/debugpy-1.8.9-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:cfe1e6c6ad7178265f74981edf1154ffce97b69005212fbc90ca22ddfe3d017e", size = 2080529 }, + { url = "https://files.pythonhosted.org/packages/87/c0/d13cdbae394c7ae65ef93d7ccde2ff364445248e367bda93fc0650c08849/debugpy-1.8.9-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ada7fb65102a4d2c9ab62e8908e9e9f12aed9d76ef44880367bc9308ebe49a0f", size = 3565151 }, + { url = "https://files.pythonhosted.org/packages/23/40/237c0a7a68cb982dcced4a0199b7c464630f75b9280d6bebde32490135d1/debugpy-1.8.9-cp310-cp310-win32.whl", hash = "sha256:c36856343cbaa448171cba62a721531e10e7ffb0abff838004701454149bc037", size = 5117068 }, + { url = "https://files.pythonhosted.org/packages/00/89/e0be9f01ee461e3369dde418492244acb1b67adaf04cb5ea98f1380ab101/debugpy-1.8.9-cp310-cp310-win_amd64.whl", hash = "sha256:17c5e0297678442511cf00a745c9709e928ea4ca263d764e90d233208889a19e", size = 5149364 }, + { url = "https://files.pythonhosted.org/packages/f7/bf/c41b688ad490d644b3bcca505a87ea58ec0442234def9a641ba62dce9c11/debugpy-1.8.9-cp311-cp311-macosx_14_0_universal2.whl", hash = "sha256:b74a49753e21e33e7cf030883a92fa607bddc4ede1aa4145172debc637780040", size = 2179080 }, + { url = "https://files.pythonhosted.org/packages/f4/dd/e9de11423db7bde62469fbd932243c64f66d6d87924976f49ec336415522/debugpy-1.8.9-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:62d22dacdb0e296966d7d74a7141aaab4bec123fa43d1a35ddcb39bf9fd29d70", size = 3137893 }, + { url = "https://files.pythonhosted.org/packages/2c/bf/e1f2c81220591728f35585b4abd67e71e9b39b3cb983f428b23d4ca6c22e/debugpy-1.8.9-cp311-cp311-win32.whl", hash = "sha256:8138efff315cd09b8dcd14226a21afda4ca582284bf4215126d87342bba1cc66", size = 5042644 }, + { url = "https://files.pythonhosted.org/packages/96/20/a407252954fd2812771e4ea3ab523f73889fd5027e305dec5ee4f0af149a/debugpy-1.8.9-cp311-cp311-win_amd64.whl", hash = "sha256:ff54ef77ad9f5c425398efb150239f6fe8e20c53ae2f68367eba7ece1e96226d", size = 5066943 }, + { url = "https://files.pythonhosted.org/packages/da/ab/1420baf8404d2b499349a44de5037133e06d489009032ce016fedb66eea1/debugpy-1.8.9-cp312-cp312-macosx_14_0_universal2.whl", hash = "sha256:957363d9a7a6612a37458d9a15e72d03a635047f946e5fceee74b50d52a9c8e2", size = 2504180 }, + { url = "https://files.pythonhosted.org/packages/58/ec/e0f88c6764314bda7887274e0b980812709b3d6363dcae124a49a9ceaa3c/debugpy-1.8.9-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5e565fc54b680292b418bb809f1386f17081d1346dca9a871bf69a8ac4071afe", size = 4224563 }, + { url = "https://files.pythonhosted.org/packages/dd/49/d9ea004ee2e4531d2b528841689ee2ba01c6a4b58840efd15e57dd866a86/debugpy-1.8.9-cp312-cp312-win32.whl", hash = "sha256:3e59842d6c4569c65ceb3751075ff8d7e6a6ada209ceca6308c9bde932bcef11", size = 5163641 }, + { url = "https://files.pythonhosted.org/packages/b1/63/c8b0718024c1187a446316037680e1564bf063c6665c815f17b42c244aba/debugpy-1.8.9-cp312-cp312-win_amd64.whl", hash = "sha256:66eeae42f3137eb428ea3a86d4a55f28da9bd5a4a3d369ba95ecc3a92c1bba53", size = 5203862 }, + { url = "https://files.pythonhosted.org/packages/2d/23/3f5804202da11c950dc0caae4a62d0c9aadabdb2daeb5f7aa09838647b5d/debugpy-1.8.9-py2.py3-none-any.whl", hash = "sha256:cc37a6c9987ad743d9c3a14fa1b1a14b7e4e6041f9dd0c8abf8895fe7a97b899", size = 5166094 }, ] [[package]] @@ -1340,14 +1340,14 @@ wheels = [ [[package]] name = "deprecated" -version = "1.2.14" +version = "1.2.15" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "wrapt" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/92/14/1e41f504a246fc224d2ac264c227975427a85caf37c3979979edb9b1b232/Deprecated-1.2.14.tar.gz", hash = "sha256:e5323eb936458dccc2582dc6f9c322c852a775a27065ff2b0c4970b9d53d01b3", size = 2974416 } +sdist = { url = "https://files.pythonhosted.org/packages/2e/a3/53e7d78a6850ffdd394d7048a31a6f14e44900adedf190f9a165f6b69439/deprecated-1.2.15.tar.gz", hash = "sha256:683e561a90de76239796e6b6feac66b99030d2dd3fcf61ef996330f14bbb9b0d", size = 2977612 } wheels = [ - { url = "https://files.pythonhosted.org/packages/20/8d/778b7d51b981a96554f29136cd59ca7880bf58094338085bcf2a979a0e6a/Deprecated-1.2.14-py2.py3-none-any.whl", hash = "sha256:6fac8b097794a90302bdbb17b9b815e732d3c4720583ff1b198499d78470466c", size = 9561 }, + { url = "https://files.pythonhosted.org/packages/1d/8f/c7f227eb42cfeaddce3eb0c96c60cbca37797fa7b34f8e1aeadf6c5c0983/Deprecated-1.2.15-py2.py3-none-any.whl", hash = "sha256:353bc4a8ac4bfc96800ddab349d89c25dec1079f65fd53acdcc1e0b975b21320", size = 9941 }, ] [[package]] @@ -1461,7 +1461,7 @@ sdist = { url = "https://files.pythonhosted.org/packages/7d/7d/60ee3f2b16d9bfdfa [[package]] name = "dspy" -version = "2.5.6" +version = "2.5.7" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "backoff" }, @@ -1481,9 +1481,9 @@ dependencies = [ { name = "tqdm" }, { name = "ujson" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/3c/48/b3961c74072e313eb38c23b16640ff0d452c7adf3849f0f8ae8f0327bac6/dspy-2.5.6.tar.gz", hash = "sha256:61053285f96486fee0afc74586905b76f4c7ff958f125e3945987911df62d816", size = 260248 } +sdist = { url = "https://files.pythonhosted.org/packages/5f/71/db65b9e1a3f84d5f1e9dc9f110757a09c3e1d01cadbc7ba4d23acf50fcfb/dspy-2.5.7.tar.gz", hash = "sha256:6863f1b9bc561ce272dbcb015954582c0371c9da65e86e22f59880b418e618d5", size = 261009 } wheels = [ - { url = "https://files.pythonhosted.org/packages/1f/75/2e354cd51af9325dd6c1e910afbcb61eafa9006f3218e3f18661402093d6/dspy-2.5.6-py3-none-any.whl", hash = "sha256:545fe64704b84be27e9b310583b0f2d2518e1fcb602e2c6baae799335d154d73", size = 304916 }, + { url = "https://files.pythonhosted.org/packages/60/e3/b167fbc3b5b9b9995eb79644a896bf6411174203af99463c847c1a3daf99/dspy-2.5.7-py3-none-any.whl", hash = "sha256:2b90689ae8de9fe7b16687649d1c137abff724c0b33817fa5228412e95a38294", size = 305025 }, ] [[package]] @@ -1500,34 +1500,34 @@ wheels = [ [[package]] name = "duckdb" -version = "1.1.1" +version = "1.1.3" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/ff/58/6a09fc4dfd8e99e6d36ab6282a75919a63718ed80b54ffee8f895bc65b1a/duckdb-1.1.1.tar.gz", hash = "sha256:74fb07c1334a73e0ead1b0a03646d349921dac655762d916c8e45194c8218d30", size = 12234215 } +sdist = { url = "https://files.pythonhosted.org/packages/a0/d7/ec014b351b6bb026d5f473b1d0ec6bd6ba40786b9abbf530b4c9041d9895/duckdb-1.1.3.tar.gz", hash = "sha256:68c3a46ab08836fe041d15dcbf838f74a990d551db47cb24ab1c4576fc19351c", size = 12240672 } wheels = [ - { url = "https://files.pythonhosted.org/packages/4a/71/ed0128fe6f3235fe376376bf1f833adbc53e4a34ea70dcb7f1910c9dfee4/duckdb-1.1.1-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:e310610b692d30aa7f1f40d7878b26978a5b191f23fa8fa082bd17092c67c2fd", size = 15463553 }, - { url = "https://files.pythonhosted.org/packages/f5/10/49938bdf8f157434cb4e27e7d5e19e58338b12e03098b55d4538512af4b5/duckdb-1.1.1-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:7acc97c3cc995850a4fa59dfa6ce713d7ea187c9696632161aa09d898f001a2b", size = 32296132 }, - { url = "https://files.pythonhosted.org/packages/fd/cb/644b03b2c97f5c9f438502651ba78c2c2ae3921fff0a067e0fd375bb388c/duckdb-1.1.1-cp310-cp310-macosx_12_0_x86_64.whl", hash = "sha256:c0a09d78daea0de7ddf3d6d1113e80ceed8c15537e93f8efaad53024ffbde245", size = 16922432 }, - { url = "https://files.pythonhosted.org/packages/43/6f/2c2589223280b17c1032239d53c6ed8268ef2164df9d244f3770d27750fb/duckdb-1.1.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:50c3b1667b0c73cb076b1b1f8fa0fd88fcef5c2bbb2b9acdef79e2eae429c248", size = 18481881 }, - { url = "https://files.pythonhosted.org/packages/13/c7/b21f64abdcbc3cf1a801a7e941b8d6f08fc9346c253e3b9c1af555b96057/duckdb-1.1.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1499a9b159d4675ea46786b7ebdbabd8287c62b6b116ccfd529112318d47184e", size = 20132672 }, - { url = "https://files.pythonhosted.org/packages/30/c8/9cdb67760c65405a62739fe18d1c4e0d5cdd452768cc9cbbb028448a23a2/duckdb-1.1.1-cp310-cp310-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:876deda2ce97f4a9005a9ac862f0ebee9e5956d51d589a24955802ca91726d49", size = 18269617 }, - { url = "https://files.pythonhosted.org/packages/4b/25/3d04e642341230df82488a4ef74e3355ab3cc1cfde9784982901b8e9ab5d/duckdb-1.1.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:40be901b38c709076f699b0c2f42a0c5663a496647eba350530e3a77f46a239b", size = 21592710 }, - { url = "https://files.pythonhosted.org/packages/82/3f/5f359465a148fe28a68b199e3d70aa9819b59fbea69580e8700cf216ece1/duckdb-1.1.1-cp310-cp310-win_amd64.whl", hash = "sha256:5cb7642c5b21b8165b60029c274fc931c7c29cae3124b9a95ed73d050dd23584", size = 10945428 }, - { url = "https://files.pythonhosted.org/packages/0a/58/f3f37b7c9779fbc573f1fe497e5ae0369981f7cd62d68953a6bf3f8c676b/duckdb-1.1.1-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:959716b65cf1c94fc117ac9c9692eea0bd64ae53bc8ab6538d459087b474dbeb", size = 15465709 }, - { url = "https://files.pythonhosted.org/packages/8f/20/378e6a1912e7087585ea3fff2217e83658a756d792d635e4d49242d369f5/duckdb-1.1.1-cp311-cp311-macosx_12_0_universal2.whl", hash = "sha256:6ff3c52ce0f8d25478155eb01de043ad0a25badbd10e684a2cd74363f1b86cde", size = 32303317 }, - { url = "https://files.pythonhosted.org/packages/1e/47/09941a6fedb3fd74d4b07842293154ae0694512ba5eb40a2ad94519ad3ef/duckdb-1.1.1-cp311-cp311-macosx_12_0_x86_64.whl", hash = "sha256:430294cf11ce866d3b726cf4530462316e20b773fed3cf2de3cf63eb89650da6", size = 16923967 }, - { url = "https://files.pythonhosted.org/packages/d0/cd/4ab2eda90529a625a12101b1478f68f4771b3dd9b332201f825336fe7714/duckdb-1.1.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dc9d48f772fafeea52568a0568cd11314cd79a10214069f3700dbcb31ebdf511", size = 18489074 }, - { url = "https://files.pythonhosted.org/packages/8e/36/5b5bc742d040ca5c2f27d77d3de891128dab1fc0a0f91f507edde4803c60/duckdb-1.1.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:572095739024d9a5aa2dd8336c289af6a624c203004213e49b7e2469275e940f", size = 20139058 }, - { url = "https://files.pythonhosted.org/packages/60/0c/e16eb7b0c6a72a1b0afddfc3c662c985b94e630215b47dd25d9202196d66/duckdb-1.1.1-cp311-cp311-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:660d9baf637b9a15e1ba74bbe02d3b4a20d82e8cbbd7d0712e0d59e3e9d6efea", size = 18276117 }, - { url = "https://files.pythonhosted.org/packages/9d/85/81537de7d6930099b0613d33aeb07ed7e69e452e8c9ea1b80e35730b65ab/duckdb-1.1.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:b91973605c8a30a38c4381a27895e7768cb3caa6700b2534ab76cc6b72cac390", size = 21596998 }, - { url = "https://files.pythonhosted.org/packages/14/f7/d6e09f220a3090617b81252dc64f1ec8ef1ffd7589fee9144de8c3934837/duckdb-1.1.1-cp311-cp311-win_amd64.whl", hash = "sha256:f57c9e070cecf42d379145a75f325ec57fb1d410d6ff6592b5a28c2ff2b5792c", size = 10947093 }, - { url = "https://files.pythonhosted.org/packages/09/50/64c67bb445afe02db2a3969704f2aa19e7c46563df571b162b49fda3cbe1/duckdb-1.1.1-cp312-cp312-macosx_12_0_arm64.whl", hash = "sha256:926a99b81c50b9a4a43ca26dcb781f934d35e773d22913548396601ab8d44c12", size = 15472011 }, - { url = "https://files.pythonhosted.org/packages/87/23/f1796350223ae0dd26a92c6d0248cf0516c0b90c5ee2b1140448084e4958/duckdb-1.1.1-cp312-cp312-macosx_12_0_universal2.whl", hash = "sha256:55a2632d27b5a965f1d9fc74b03383e80a3f8e3dc9596807dfb02c8db08cfcb7", size = 32335916 }, - { url = "https://files.pythonhosted.org/packages/58/87/eccfba6ee3f8f2cedc7cb39f0791e8be5e5c2e4157966d69aaf6c96ee4de/duckdb-1.1.1-cp312-cp312-macosx_12_0_x86_64.whl", hash = "sha256:8d8174fe47caf48d830dc477a45cedc8c970722df09dc1456bddc760ff6ccf68", size = 16943648 }, - { url = "https://files.pythonhosted.org/packages/7f/28/5658ca0abfa8ab047dbdd376c0612a4736b4bdb308b4f2552ea4be4ab8b1/duckdb-1.1.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9ad84023399002222fa8d5264a8dc2083053027910df728da92cabb07494a489", size = 18479706 }, - { url = "https://files.pythonhosted.org/packages/47/1f/e964b4ec19e6e14256dbe5e39cc5cb495bccb937b9cd0d7631219129296b/duckdb-1.1.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1c8adbc8b37444424c72043288f1521c860555a4f151ee4b744e6125f5d05729", size = 20139266 }, - { url = "https://files.pythonhosted.org/packages/cf/63/66c4f5f7cc6acf57c12aa1a7c9eebeb86629d780e6ebb7a960793e718650/duckdb-1.1.1-cp312-cp312-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:550524c1b423eeb7ca0fdf1c2e6d29e723d7ec7cfab3050b9feb55a620ae927f", size = 18281949 }, - { url = "https://files.pythonhosted.org/packages/92/4f/ff756a8270c3f66f46996f4a2d1436e915c55614af0d4d9fc288475d9fb1/duckdb-1.1.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:4064243e4d3f445975b78773677de0ccbe924f9c7058a7c2cfedb24bba2ba939", size = 21606968 }, - { url = "https://files.pythonhosted.org/packages/e2/d6/a08ade8b954c059300b3e649dabd8d343bbbb4f43119139ee64a9d1ec62e/duckdb-1.1.1-cp312-cp312-win_amd64.whl", hash = "sha256:4f64516dc62dd0fcbb9785c5bc7532a4fca3e6016bbcc92a2b235aa972c631f6", size = 10948355 }, + { url = "https://files.pythonhosted.org/packages/de/7e/aef0fa22a80939edb04f66152a1fd5ce7257931576be192a8068e74f0892/duckdb-1.1.3-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:1c0226dc43e2ee4cc3a5a4672fddb2d76fd2cf2694443f395c02dd1bea0b7fce", size = 15469781 }, + { url = "https://files.pythonhosted.org/packages/38/22/df548714ddd915929ebbba9699e8614655ed93cd367f5849f6dbd1b3e160/duckdb-1.1.3-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:7c71169fa804c0b65e49afe423ddc2dc83e198640e3b041028da8110f7cd16f7", size = 32313005 }, + { url = "https://files.pythonhosted.org/packages/9f/38/8de640857f4c55df870faf025835e09c69222d365dc773507e934cee3376/duckdb-1.1.3-cp310-cp310-macosx_12_0_x86_64.whl", hash = "sha256:872d38b65b66e3219d2400c732585c5b4d11b13d7a36cd97908d7981526e9898", size = 16931481 }, + { url = "https://files.pythonhosted.org/packages/41/9b/87fff1341a9f57ab75284d79f902fee8cd6ef3a9135af4c723c90384d307/duckdb-1.1.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:25fb02629418c0d4d94a2bc1776edaa33f6f6ccaa00bd84eb96ecb97ae4b50e9", size = 18491670 }, + { url = "https://files.pythonhosted.org/packages/3e/ee/8f74ccecbafd14e257c634f0f2cdebbc35634d9d74f04bb7ad8a0e142bf8/duckdb-1.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9e3f5cd604e7c39527e6060f430769b72234345baaa0987f9500988b2814f5e4", size = 20144774 }, + { url = "https://files.pythonhosted.org/packages/36/7b/edffb833b8569a7fc1799ceb4392911e0082f18a6076225441e954a95853/duckdb-1.1.3-cp310-cp310-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:08935700e49c187fe0e9b2b86b5aad8a2ccd661069053e38bfaed3b9ff795efd", size = 18287084 }, + { url = "https://files.pythonhosted.org/packages/a9/ab/6367e8c98b3331260bb4389c6b80deef96614c1e21edcdba23a882e45ab0/duckdb-1.1.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:f9b47036945e1db32d70e414a10b1593aec641bd4c5e2056873d971cc21e978b", size = 21614877 }, + { url = "https://files.pythonhosted.org/packages/03/d8/89b1c5f1dbd16342640742f6f6d3f1c827d1a1b966d674774ddfe6a385e2/duckdb-1.1.3-cp310-cp310-win_amd64.whl", hash = "sha256:35c420f58abc79a68a286a20fd6265636175fadeca1ce964fc8ef159f3acc289", size = 10954044 }, + { url = "https://files.pythonhosted.org/packages/57/d0/96127582230183dc36f1209d5e8e67f54b3459b3b9794603305d816f350a/duckdb-1.1.3-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:4f0e2e5a6f5a53b79aee20856c027046fba1d73ada6178ed8467f53c3877d5e0", size = 15469495 }, + { url = "https://files.pythonhosted.org/packages/70/07/b78b435f8fe85c23ee2d49a01dc9599bb4a272c40f2a6bf67ff75958bdad/duckdb-1.1.3-cp311-cp311-macosx_12_0_universal2.whl", hash = "sha256:911d58c22645bfca4a5a049ff53a0afd1537bc18fedb13bc440b2e5af3c46148", size = 32318595 }, + { url = "https://files.pythonhosted.org/packages/6c/d8/253b3483fc554daf72503ba0f112404f75be6bbd7ca7047e804873cbb182/duckdb-1.1.3-cp311-cp311-macosx_12_0_x86_64.whl", hash = "sha256:c443d3d502335e69fc1e35295fcfd1108f72cb984af54c536adfd7875e79cee5", size = 16934057 }, + { url = "https://files.pythonhosted.org/packages/f8/11/908a8fb73cef8304d3f4eab7f27cc489f6fd675f921d382c83c55253be86/duckdb-1.1.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0a55169d2d2e2e88077d91d4875104b58de45eff6a17a59c7dc41562c73df4be", size = 18498214 }, + { url = "https://files.pythonhosted.org/packages/bf/56/f627b6fcd4aa34015a15449d852ccb78d7cc6eda654aa20c1d378e99fa76/duckdb-1.1.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9d0767ada9f06faa5afcf63eb7ba1befaccfbcfdac5ff86f0168c673dd1f47aa", size = 20149376 }, + { url = "https://files.pythonhosted.org/packages/b5/1d/c318dada688119b9ca975d431f9b38bde8dda41b6d18cc06e0dc52123788/duckdb-1.1.3-cp311-cp311-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:51c6d79e05b4a0933672b1cacd6338f882158f45ef9903aef350c4427d9fc898", size = 18293289 }, + { url = "https://files.pythonhosted.org/packages/37/8e/fd346444b270ffe52e06c1af1243eaae30ab651c1d59f51711e3502fd060/duckdb-1.1.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:183ac743f21c6a4d6adfd02b69013d5fd78e5e2cd2b4db023bc8a95457d4bc5d", size = 21622129 }, + { url = "https://files.pythonhosted.org/packages/18/aa/804c1cf5077b6f17d752b23637d9ef53eaad77ea73ee43d4c12bff480e36/duckdb-1.1.3-cp311-cp311-win_amd64.whl", hash = "sha256:a30dd599b8090ea6eafdfb5a9f1b872d78bac318b6914ada2d35c7974d643640", size = 10954756 }, + { url = "https://files.pythonhosted.org/packages/9b/ff/7ee500f4cff0d2a581c1afdf2c12f70ee3bf1a61041fea4d88934a35a7a3/duckdb-1.1.3-cp312-cp312-macosx_12_0_arm64.whl", hash = "sha256:a433ae9e72c5f397c44abdaa3c781d94f94f4065bcbf99ecd39433058c64cb38", size = 15482881 }, + { url = "https://files.pythonhosted.org/packages/28/16/dda10da6bde54562c3cb0002ca3b7678e3108fa73ac9b7509674a02c5249/duckdb-1.1.3-cp312-cp312-macosx_12_0_universal2.whl", hash = "sha256:d08308e0a46c748d9c30f1d67ee1143e9c5ea3fbcccc27a47e115b19e7e78aa9", size = 32349440 }, + { url = "https://files.pythonhosted.org/packages/2e/c2/06f7f7a51a1843c9384e1637abb6bbebc29367710ffccc7e7e52d72b3dd9/duckdb-1.1.3-cp312-cp312-macosx_12_0_x86_64.whl", hash = "sha256:5d57776539211e79b11e94f2f6d63de77885f23f14982e0fac066f2885fcf3ff", size = 16953473 }, + { url = "https://files.pythonhosted.org/packages/1a/84/9991221ef7dde79d85231f20646e1b12d645490cd8be055589276f62847e/duckdb-1.1.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e59087dbbb63705f2483544e01cccf07d5b35afa58be8931b224f3221361d537", size = 18491915 }, + { url = "https://files.pythonhosted.org/packages/aa/76/330fe16f12b7ddda0c664ba9869f3afbc8773dbe17ae750121d407dc0f37/duckdb-1.1.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4ebf5f60ddbd65c13e77cddb85fe4af671d31b851f125a4d002a313696af43f1", size = 20150288 }, + { url = "https://files.pythonhosted.org/packages/c4/88/e4b08b7a5d08c0f65f6c7a6594de64431ce7df38d7258511417ba7989ad3/duckdb-1.1.3-cp312-cp312-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e4ef7ba97a65bd39d66f2a7080e6fb60e7c3e41d4c1e19245f90f53b98e3ac32", size = 18296560 }, + { url = "https://files.pythonhosted.org/packages/1a/32/011e6e3ce14375a1ba01a588c119ad82be757f847c6b60207e0762d9ec3a/duckdb-1.1.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:f58db1b65593ff796c8ea6e63e2e144c944dd3d51c8d8e40dffa7f41693d35d3", size = 21635270 }, + { url = "https://files.pythonhosted.org/packages/f2/eb/58d4e0eccdc7b3523c062d008ad9eef28edccf88591d1a78659c809fe6e8/duckdb-1.1.3-cp312-cp312-win_amd64.whl", hash = "sha256:e86006958e84c5c02f08f9b96f4bc26990514eab329b1b4f71049b3727ce5989", size = 10955715 }, ] [[package]] @@ -1554,7 +1554,7 @@ wheels = [ [[package]] name = "e2b" -version = "1.0.3" +version = "1.0.5" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "attrs" }, @@ -1563,24 +1563,25 @@ dependencies = [ { name = "packaging" }, { name = "protobuf" }, { name = "python-dateutil" }, + { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/26/f4/d77a8e6de008e56f3ecd23ec1a798144b132ffa2f31f61611e4adc2e7977/e2b-1.0.3.tar.gz", hash = "sha256:767233663eadf78462b02eb3fa75d0993800309a43e65eaff40686843d26ecf8", size = 44324 } +sdist = { url = "https://files.pythonhosted.org/packages/b7/28/c05fe7a49005e2e98017941c05df15e2b096e8d57c1abcf2fca05e11abef/e2b-1.0.5.tar.gz", hash = "sha256:43c82705af7b7d4415c2510ff77dab4dc075351e0b769d6adf8e0d7bb4868d13", size = 44374 } wheels = [ - { url = "https://files.pythonhosted.org/packages/2b/de/9e1dc68b0c053f2b3c27e60dcaf51ed8f6ec416f21a0b5b944462ea54852/e2b-1.0.3-py3-none-any.whl", hash = "sha256:7e087a94e0b6bc86fd330815dfb3312f0cc365d4f080f5ff1a6335f3f65426de", size = 81683 }, + { url = "https://files.pythonhosted.org/packages/92/80/35a7050f011f603599ce3d579fe3a5f424c9256574e132f4b75260d9ffb5/e2b-1.0.5-py3-none-any.whl", hash = "sha256:a71bdec46f33d3e38e87d475d7fd2939bd7b6b753b819c9639ca211cd375b79e", size = 81717 }, ] [[package]] name = "e2b-code-interpreter" -version = "1.0.1" +version = "1.0.3" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "attrs" }, { name = "e2b" }, { name = "httpx" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/9a/67/67441008c3a299ab2d5185b96ba054aa888454e31ce3c2c08c2ef368b4b0/e2b_code_interpreter-1.0.1.tar.gz", hash = "sha256:b0c061e41315d21514affe78f80052be335b687204e669dd7ca852b59eeaaea2", size = 9203 } +sdist = { url = "https://files.pythonhosted.org/packages/21/48/cb1e26118c17cc896e9a602f20001310c30eb12b3e7a729a9005d1cdcd28/e2b_code_interpreter-1.0.3.tar.gz", hash = "sha256:36475acc001b1317ed129d65970fce6a7cc2d50e3fd3e8a13ad5d7d3e0fac237", size = 9246 } wheels = [ - { url = "https://files.pythonhosted.org/packages/91/f1/4950f1b68be3748add48240efc83a1514c099e55c340bf27c332d0134f1e/e2b_code_interpreter-1.0.1-py3-none-any.whl", hash = "sha256:e27c40174ba7daac4942388611a73e1ac58300227f0ba6c0555ee54507d4944c", size = 12011 }, + { url = "https://files.pythonhosted.org/packages/28/24/9f59f4d838d0c9830cbcdbc9fdb12bdde600ad5989c89d244658f1532993/e2b_code_interpreter-1.0.3-py3-none-any.whl", hash = "sha256:c638bd4ec1c99d9c4eaac541bc8b15134cf786f6c7c400d979cef96d62e485d8", size = 12034 }, ] [[package]] @@ -1762,29 +1763,29 @@ wheels = [ [[package]] name = "fastapi" -version = "0.115.2" +version = "0.115.6" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "pydantic" }, { name = "starlette" }, { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/22/fa/19e3c7c9b31ac291987c82e959f36f88840bea183fa3dc3bb654669f19c1/fastapi-0.115.2.tar.gz", hash = "sha256:3995739e0b09fa12f984bce8fa9ae197b35d433750d3d312422d846e283697ee", size = 299968 } +sdist = { url = "https://files.pythonhosted.org/packages/93/72/d83b98cd106541e8f5e5bfab8ef2974ab45a62e8a6c5b5e6940f26d2ed4b/fastapi-0.115.6.tar.gz", hash = "sha256:9ec46f7addc14ea472958a96aae5b5de65f39721a46aaf5705c480d9a8b76654", size = 301336 } wheels = [ - { url = "https://files.pythonhosted.org/packages/c9/14/bbe7776356ef01f830f8085ca3ac2aea59c73727b6ffaa757abeb7d2900b/fastapi-0.115.2-py3-none-any.whl", hash = "sha256:61704c71286579cc5a598763905928f24ee98bfcc07aabe84cfefb98812bbc86", size = 94650 }, + { url = "https://files.pythonhosted.org/packages/52/b3/7e4df40e585df024fac2f80d1a2d579c854ac37109675db2b0cc22c0bb9e/fastapi-0.115.6-py3-none-any.whl", hash = "sha256:e9240b29e36fa8f4bb7290316988e90c381e5092e0cbe84e7818cc3713bcf305", size = 94843 }, ] [[package]] name = "fastapi-pagination" -version = "0.12.29" +version = "0.12.32" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "pydantic" }, { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/18/4f/758832457733a75522fe6693b543a1404009bfa19fd5198e80cf6f77f232/fastapi_pagination-0.12.29.tar.gz", hash = "sha256:bbfa8af44636f9cda3ec10f59fe370a89a8f10cfa4035a6dc4da86b9f8d06649", size = 26279 } +sdist = { url = "https://files.pythonhosted.org/packages/56/b6/b431ddef4bec5011231ac3deb2da3a334207ef110987bc4971ac40f59865/fastapi_pagination-0.12.32.tar.gz", hash = "sha256:b808b5b8af493c51d96ae0091b60532b25688cbca1350f39cb72f10d4d69a6ab", size = 26531 } wheels = [ - { url = "https://files.pythonhosted.org/packages/16/8f/3a0ab35dcb73c8e93a7dc66ff0641bcc4af2a6b919ba21f3c1873c642f96/fastapi_pagination-0.12.29-py3-none-any.whl", hash = "sha256:c18e58c91cf7909490236ded4dae1326c68e286a0831de41ba1be170fb24f182", size = 42525 }, + { url = "https://files.pythonhosted.org/packages/83/23/0d57a0a67e3bf51b5d2d91a52c7bb7421bd8006aea694be01e37e9830901/fastapi_pagination-0.12.32-py3-none-any.whl", hash = "sha256:38e7e72abf252cbebbc1beff9081e4929762756c04959c471b2a5866bb7f0aaf", size = 42816 }, ] [[package]] @@ -1833,7 +1834,7 @@ wheels = [ [[package]] name = "firecrawl-py" -version = "1.5.0" +version = "1.6.3" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "nest-asyncio" }, @@ -1841,21 +1842,21 @@ dependencies = [ { name = "requests" }, { name = "websockets" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/0f/d2/806cf45c5bd17d978eec19f5449ea5d0be59ddbe7edbb18d4a9f77c7da96/firecrawl_py-1.5.0.tar.gz", hash = "sha256:b313743c463e6a7a92982053b0b9e1ef1763e4c0945e579e999cf10e387f1889", size = 17418 } +sdist = { url = "https://files.pythonhosted.org/packages/37/97/9837219bc9267b7a1fe03bca53ffe24571bf9b2eb5d1a3f9ad374a802da1/firecrawl_py-1.6.3.tar.gz", hash = "sha256:cb7d82a9a551b84c07f236368e2c8c274c27978ccb10ac91757e97fb6b581bd6", size = 17916 } wheels = [ - { url = "https://files.pythonhosted.org/packages/a1/17/d3bb4536858c286166de9b0f3d6d7ac72c6199fd1a01cff9f138433eb909/firecrawl_py-1.5.0-py3-none-any.whl", hash = "sha256:1787d0ff69aa808498243571d40fa5732b9fb393880d99ea1952dd2aa4dc5679", size = 16429 }, + { url = "https://files.pythonhosted.org/packages/ca/7b/ec6c6a2251f225c6ed01330aa4489e5ee2a54a867d626cdce0a285a0c56f/firecrawl_py-1.6.3-py3-none-any.whl", hash = "sha256:c561c6b3cb4dd6c499c1a5298b1cf7b38ae23f875ee897ae1141cff440e699c9", size = 16876 }, ] [[package]] name = "flaml" -version = "2.3.1" +version = "2.3.2" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "numpy" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/6d/9d/f54feca4e4b7280b222beea3cc9597b10184ed6493982406409d1d1186ff/flaml-2.3.1.tar.gz", hash = "sha256:0349f2b831db27e8f5ae7aa72a221bca552a29db9b9cce8e7ce8f8a0e5f8f207", size = 284739 } +sdist = { url = "https://files.pythonhosted.org/packages/97/d9/938b9b21a0672e976c7e5738f1ad67d77a89b48d604fb062c8fafff02a3c/flaml-2.3.2.tar.gz", hash = "sha256:4a1ec289ddaec36850cfc66f6fb335b8521df49ea31f6adb54ea63a5cebb6865", size = 285196 } wheels = [ - { url = "https://files.pythonhosted.org/packages/91/1e/0f9bc46ad8c93dca2c34ee7814119d9aefb364cff4494995f0e6e44ccc92/FLAML-2.3.1-py3-none-any.whl", hash = "sha256:c633c73bcb4e0ec56d7ccd1db9577c40ccf8247455a51868da2a2b93795bb26a", size = 313347 }, + { url = "https://files.pythonhosted.org/packages/5f/7f/3192ef1e666659605c3886e9e2a756806d1f24f4ca4c5753843c25e344f7/FLAML-2.3.2-py3-none-any.whl", hash = "sha256:1ee6e8e76bf1d741b4da41e2a2a8c0638b36d90b0f60aac323b5568f54dcb9e7", size = 313921 }, ] [[package]] @@ -1891,83 +1892,83 @@ sdist = { url = "https://files.pythonhosted.org/packages/e6/79/d4f20e91327c98096 [[package]] name = "frozendict" -version = "2.4.5" +version = "2.4.6" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/56/06/baebef78b39a4b483f817265ed4fe0ac98bc91e371007de18a3192c8073b/frozendict-2.4.5.tar.gz", hash = "sha256:fd7add309789595c044c0155a0bddfa9d20c77f65de1e33a14aa3033b936ef63", size = 316463 } +sdist = { url = "https://files.pythonhosted.org/packages/bb/59/19eb300ba28e7547538bdf603f1c6c34793240a90e1a7b61b65d8517e35e/frozendict-2.4.6.tar.gz", hash = "sha256:df7cd16470fbd26fc4969a208efadc46319334eb97def1ddf48919b351192b8e", size = 316416 } wheels = [ - { url = "https://files.pythonhosted.org/packages/b1/2a/00fcb10eafd6466becab36547c6d96afc22883911100bc047c360eed1fea/frozendict-2.4.5-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:1f364cfe5ef97523a4434e9f458bb4821594d3531d898621e5acae43463dcb5e", size = 37918 }, - { url = "https://files.pythonhosted.org/packages/f9/b7/9ca50d3e3a158c78427a1dfee8ea2c3489c7b369516e342d63380a1839ac/frozendict-2.4.5-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4f073c926b1f88fa85ed85222101f61f6c4b2180c95d1528ca6ecc7cef835442", size = 37943 }, - { url = "https://files.pythonhosted.org/packages/7b/08/7061bd36a6a068e03a3f48fa9de2e5308e1a08def452a146d189949c78e4/frozendict-2.4.5-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8582f26ca862bb1e40ed790d934adf6afcfc904b0425dcfe01aed2103bed27fb", size = 117649 }, - { url = "https://files.pythonhosted.org/packages/0f/26/00b3aac94d7d29ae0f883533a5d6812e3201391b09a65c2643d5d76443e1/frozendict-2.4.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4b3eea1678607174c468fe4e3b903625bccfb3215ae2b0138220dc1f6ef71f37", size = 117441 }, - { url = "https://files.pythonhosted.org/packages/26/57/d9ab8c394f14ec6974b745505e7543ac098993c449e1cc3ead9a49dc6efb/frozendict-2.4.5-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:3af1b09bad761d5500b096b757c346591b5dfdc8443aa9642c2c02b4885dc09e", size = 116794 }, - { url = "https://files.pythonhosted.org/packages/9b/f6/2f2f18e3558e391fa2941b469e97abeddb5a6ad56e9112b00f53a29256f2/frozendict-2.4.5-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:76c7af5f9db9ae01531edaf38fd3e8faae1bb6b94abbf8fa5bd0326f52e777df", size = 117326 }, - { url = "https://files.pythonhosted.org/packages/b3/e2/2014e00cf0d230de94f586034ebe65f9b52f062ca86f64a67e6707486469/frozendict-2.4.5-cp310-cp310-win_amd64.whl", hash = "sha256:a5448639058157ccd7f26ba83e441066c6ae515beb68b9b99d5b2dbb0bb36b19", size = 37515 }, - { url = "https://files.pythonhosted.org/packages/ff/5a/34099bc02fcea30de7ce246db6233310d23abf42669ff72762c24ef96b2a/frozendict-2.4.5-cp310-cp310-win_arm64.whl", hash = "sha256:24953a1cfe344415e7557413e493e21fa9c4cecbc13284b6f334837aa5601c9f", size = 34050 }, - { url = "https://files.pythonhosted.org/packages/86/20/2a2514d0b504e773078c38d664108bc8ae9056f85ea57c6fff86eee07331/frozendict-2.4.5-py311-none-any.whl", hash = "sha256:6be054ba76e8a49c6846a7369db3eaaa0593c29a644026c25923f13fdea06483", size = 16141 }, - { url = "https://files.pythonhosted.org/packages/0d/7a/df80b17161131c0f59617c7bc460f9846ec3843b7febb66b88f7158ece1a/frozendict-2.4.5-py312-none-any.whl", hash = "sha256:b8481d83a7219e9e14c719113ea2d8321d7840af35af58c72b3864b7123e7de3", size = 16141 }, + { url = "https://files.pythonhosted.org/packages/a6/7f/e80cdbe0db930b2ba9d46ca35a41b0150156da16dfb79edcc05642690c3b/frozendict-2.4.6-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c3a05c0a50cab96b4bb0ea25aa752efbfceed5ccb24c007612bc63e51299336f", size = 37927 }, + { url = "https://files.pythonhosted.org/packages/29/98/27e145ff7e8e63caa95fb8ee4fc56c68acb208bef01a89c3678a66f9a34d/frozendict-2.4.6-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f5b94d5b07c00986f9e37a38dd83c13f5fe3bf3f1ccc8e88edea8fe15d6cd88c", size = 37945 }, + { url = "https://files.pythonhosted.org/packages/ac/f1/a10be024a9d53441c997b3661ea80ecba6e3130adc53812a4b95b607cdd1/frozendict-2.4.6-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f4c789fd70879ccb6289a603cdebdc4953e7e5dea047d30c1b180529b28257b5", size = 117656 }, + { url = "https://files.pythonhosted.org/packages/46/a6/34c760975e6f1cb4db59a990d58dcf22287e10241c851804670c74c6a27a/frozendict-2.4.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:da6a10164c8a50b34b9ab508a9420df38f4edf286b9ca7b7df8a91767baecb34", size = 117444 }, + { url = "https://files.pythonhosted.org/packages/62/dd/64bddd1ffa9617f50e7e63656b2a7ad7f0a46c86b5f4a3d2c714d0006277/frozendict-2.4.6-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:9a8a43036754a941601635ea9c788ebd7a7efbed2becba01b54a887b41b175b9", size = 116801 }, + { url = "https://files.pythonhosted.org/packages/45/ae/af06a8bde1947277aad895c2f26c3b8b8b6ee9c0c2ad988fb58a9d1dde3f/frozendict-2.4.6-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:c9905dcf7aa659e6a11b8051114c9fa76dfde3a6e50e6dc129d5aece75b449a2", size = 117329 }, + { url = "https://files.pythonhosted.org/packages/d2/df/be3fa0457ff661301228f4c59c630699568c8ed9b5480f113b3eea7d0cb3/frozendict-2.4.6-cp310-cp310-win_amd64.whl", hash = "sha256:323f1b674a2cc18f86ab81698e22aba8145d7a755e0ac2cccf142ee2db58620d", size = 37522 }, + { url = "https://files.pythonhosted.org/packages/4a/6f/c22e0266b4c85f58b4613fec024e040e93753880527bf92b0c1bc228c27c/frozendict-2.4.6-cp310-cp310-win_arm64.whl", hash = "sha256:eabd21d8e5db0c58b60d26b4bb9839cac13132e88277e1376970172a85ee04b3", size = 34056 }, + { url = "https://files.pythonhosted.org/packages/04/13/d9839089b900fa7b479cce495d62110cddc4bd5630a04d8469916c0e79c5/frozendict-2.4.6-py311-none-any.whl", hash = "sha256:d065db6a44db2e2375c23eac816f1a022feb2fa98cbb50df44a9e83700accbea", size = 16148 }, + { url = "https://files.pythonhosted.org/packages/ba/d0/d482c39cee2ab2978a892558cf130681d4574ea208e162da8958b31e9250/frozendict-2.4.6-py312-none-any.whl", hash = "sha256:49344abe90fb75f0f9fdefe6d4ef6d4894e640fadab71f11009d52ad97f370b9", size = 16146 }, ] [[package]] name = "frozenlist" -version = "1.4.1" +version = "1.5.0" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/cf/3d/2102257e7acad73efc4a0c306ad3953f68c504c16982bbdfee3ad75d8085/frozenlist-1.4.1.tar.gz", hash = "sha256:c037a86e8513059a2613aaba4d817bb90b9d9b6b69aace3ce9c877e8c8ed402b", size = 37820 } +sdist = { url = "https://files.pythonhosted.org/packages/8f/ed/0f4cec13a93c02c47ec32d81d11c0c1efbadf4a471e3f3ce7cad366cbbd3/frozenlist-1.5.0.tar.gz", hash = "sha256:81d5af29e61b9c8348e876d442253723928dce6433e0e76cd925cd83f1b4b817", size = 39930 } wheels = [ - { url = "https://files.pythonhosted.org/packages/7a/35/1328c7b0f780d34f8afc1d87ebdc2bb065a123b24766a0b475f0d67da637/frozenlist-1.4.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:f9aa1878d1083b276b0196f2dfbe00c9b7e752475ed3b682025ff20c1c1f51ac", size = 94315 }, - { url = "https://files.pythonhosted.org/packages/f4/d6/ca016b0adcf8327714ccef969740688808c86e0287bf3a639ff582f24e82/frozenlist-1.4.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:29acab3f66f0f24674b7dc4736477bcd4bc3ad4b896f5f45379a67bce8b96868", size = 53805 }, - { url = "https://files.pythonhosted.org/packages/ae/83/bcdaa437a9bd693ba658a0310f8cdccff26bd78e45fccf8e49897904a5cd/frozenlist-1.4.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:74fb4bee6880b529a0c6560885fce4dc95936920f9f20f53d99a213f7bf66776", size = 52163 }, - { url = "https://files.pythonhosted.org/packages/d4/e9/759043ab7d169b74fe05ebfbfa9ee5c881c303ebc838e308346204309cd0/frozenlist-1.4.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:590344787a90ae57d62511dd7c736ed56b428f04cd8c161fcc5e7232c130c69a", size = 238595 }, - { url = "https://files.pythonhosted.org/packages/f8/ce/b9de7dc61e753dc318cf0de862181b484178210c5361eae6eaf06792264d/frozenlist-1.4.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:068b63f23b17df8569b7fdca5517edef76171cf3897eb68beb01341131fbd2ad", size = 262428 }, - { url = "https://files.pythonhosted.org/packages/36/ce/dc6f29e0352fa34ebe45421960c8e7352ca63b31630a576e8ffb381e9c08/frozenlist-1.4.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5c849d495bf5154cd8da18a9eb15db127d4dba2968d88831aff6f0331ea9bd4c", size = 258867 }, - { url = "https://files.pythonhosted.org/packages/51/47/159ac53faf8a11ae5ee8bb9db10327575557504e549cfd76f447b969aa91/frozenlist-1.4.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9750cc7fe1ae3b1611bb8cfc3f9ec11d532244235d75901fb6b8e42ce9229dfe", size = 229412 }, - { url = "https://files.pythonhosted.org/packages/ec/25/0c87df2e53c0c5d90f7517ca0ff7aca78d050a8ec4d32c4278e8c0e52e51/frozenlist-1.4.1-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a9b2de4cf0cdd5bd2dee4c4f63a653c61d2408055ab77b151c1957f221cabf2a", size = 239539 }, - { url = "https://files.pythonhosted.org/packages/97/94/a1305fa4716726ae0abf3b1069c2d922fcfd442538cb850f1be543f58766/frozenlist-1.4.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:0633c8d5337cb5c77acbccc6357ac49a1770b8c487e5b3505c57b949b4b82e98", size = 253379 }, - { url = "https://files.pythonhosted.org/packages/53/82/274e19f122e124aee6d113188615f63b0736b4242a875f482a81f91e07e2/frozenlist-1.4.1-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:27657df69e8801be6c3638054e202a135c7f299267f1a55ed3a598934f6c0d75", size = 245901 }, - { url = "https://files.pythonhosted.org/packages/b8/28/899931015b8cffbe155392fe9ca663f981a17e1adc69589ee0e1e7cdc9a2/frozenlist-1.4.1-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:f9a3ea26252bd92f570600098783d1371354d89d5f6b7dfd87359d669f2109b5", size = 263797 }, - { url = "https://files.pythonhosted.org/packages/6e/4f/b8a5a2f10c4a58c52a52a40cf6cf1ffcdbf3a3b64f276f41dab989bf3ab5/frozenlist-1.4.1-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:4f57dab5fe3407b6c0c1cc907ac98e8a189f9e418f3b6e54d65a718aaafe3950", size = 264415 }, - { url = "https://files.pythonhosted.org/packages/b0/2c/7be3bdc59dbae444864dbd9cde82790314390ec54636baf6b9ce212627ad/frozenlist-1.4.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:e02a0e11cf6597299b9f3bbd3f93d79217cb90cfd1411aec33848b13f5c656cc", size = 253964 }, - { url = "https://files.pythonhosted.org/packages/2e/ec/4fb5a88f6b9a352aed45ab824dd7ce4801b7bcd379adcb927c17a8f0a1a8/frozenlist-1.4.1-cp310-cp310-win32.whl", hash = "sha256:a828c57f00f729620a442881cc60e57cfcec6842ba38e1b19fd3e47ac0ff8dc1", size = 44559 }, - { url = "https://files.pythonhosted.org/packages/61/15/2b5d644d81282f00b61e54f7b00a96f9c40224107282efe4cd9d2bf1433a/frozenlist-1.4.1-cp310-cp310-win_amd64.whl", hash = "sha256:f56e2333dda1fe0f909e7cc59f021eba0d2307bc6f012a1ccf2beca6ba362439", size = 50434 }, - { url = "https://files.pythonhosted.org/packages/01/bc/8d33f2d84b9368da83e69e42720cff01c5e199b5a868ba4486189a4d8fa9/frozenlist-1.4.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:a0cb6f11204443f27a1628b0e460f37fb30f624be6051d490fa7d7e26d4af3d0", size = 97060 }, - { url = "https://files.pythonhosted.org/packages/af/b2/904500d6a162b98a70e510e743e7ea992241b4f9add2c8063bf666ca21df/frozenlist-1.4.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:b46c8ae3a8f1f41a0d2ef350c0b6e65822d80772fe46b653ab6b6274f61d4a49", size = 55347 }, - { url = "https://files.pythonhosted.org/packages/5b/9c/f12b69997d3891ddc0d7895999a00b0c6a67f66f79498c0e30f27876435d/frozenlist-1.4.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:fde5bd59ab5357e3853313127f4d3565fc7dad314a74d7b5d43c22c6a5ed2ced", size = 53374 }, - { url = "https://files.pythonhosted.org/packages/ac/6e/e0322317b7c600ba21dec224498c0c5959b2bce3865277a7c0badae340a9/frozenlist-1.4.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:722e1124aec435320ae01ee3ac7bec11a5d47f25d0ed6328f2273d287bc3abb0", size = 273288 }, - { url = "https://files.pythonhosted.org/packages/a7/76/180ee1b021568dad5b35b7678616c24519af130ed3fa1e0f1ed4014e0f93/frozenlist-1.4.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2471c201b70d58a0f0c1f91261542a03d9a5e088ed3dc6c160d614c01649c106", size = 284737 }, - { url = "https://files.pythonhosted.org/packages/05/08/40159d706a6ed983c8aca51922a93fc69f3c27909e82c537dd4054032674/frozenlist-1.4.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c757a9dd70d72b076d6f68efdbb9bc943665ae954dad2801b874c8c69e185068", size = 280267 }, - { url = "https://files.pythonhosted.org/packages/e0/18/9f09f84934c2b2aa37d539a322267939770362d5495f37783440ca9c1b74/frozenlist-1.4.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f146e0911cb2f1da549fc58fc7bcd2b836a44b79ef871980d605ec392ff6b0d2", size = 258778 }, - { url = "https://files.pythonhosted.org/packages/b3/c9/0bc5ee7e1f5cc7358ab67da0b7dfe60fbd05c254cea5c6108e7d1ae28c63/frozenlist-1.4.1-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4f9c515e7914626b2a2e1e311794b4c35720a0be87af52b79ff8e1429fc25f19", size = 272276 }, - { url = "https://files.pythonhosted.org/packages/12/5d/147556b73a53ad4df6da8bbb50715a66ac75c491fdedac3eca8b0b915345/frozenlist-1.4.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:c302220494f5c1ebeb0912ea782bcd5e2f8308037b3c7553fad0e48ebad6ad82", size = 272424 }, - { url = "https://files.pythonhosted.org/packages/83/61/2087bbf24070b66090c0af922685f1d0596c24bb3f3b5223625bdeaf03ca/frozenlist-1.4.1-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:442acde1e068288a4ba7acfe05f5f343e19fac87bfc96d89eb886b0363e977ec", size = 260881 }, - { url = "https://files.pythonhosted.org/packages/a8/be/a235bc937dd803258a370fe21b5aa2dd3e7bfe0287a186a4bec30c6cccd6/frozenlist-1.4.1-cp311-cp311-musllinux_1_1_ppc64le.whl", hash = "sha256:1b280e6507ea8a4fa0c0a7150b4e526a8d113989e28eaaef946cc77ffd7efc0a", size = 282327 }, - { url = "https://files.pythonhosted.org/packages/5d/e7/b2469e71f082948066b9382c7b908c22552cc705b960363c390d2e23f587/frozenlist-1.4.1-cp311-cp311-musllinux_1_1_s390x.whl", hash = "sha256:fe1a06da377e3a1062ae5fe0926e12b84eceb8a50b350ddca72dc85015873f74", size = 281502 }, - { url = "https://files.pythonhosted.org/packages/db/1b/6a5b970e55dffc1a7d0bb54f57b184b2a2a2ad0b7bca16a97ca26d73c5b5/frozenlist-1.4.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:db9e724bebd621d9beca794f2a4ff1d26eed5965b004a97f1f1685a173b869c2", size = 272292 }, - { url = "https://files.pythonhosted.org/packages/1a/05/ebad68130e6b6eb9b287dacad08ea357c33849c74550c015b355b75cc714/frozenlist-1.4.1-cp311-cp311-win32.whl", hash = "sha256:e774d53b1a477a67838a904131c4b0eef6b3d8a651f8b138b04f748fccfefe17", size = 44446 }, - { url = "https://files.pythonhosted.org/packages/b3/21/c5aaffac47fd305d69df46cfbf118768cdf049a92ee6b0b5cb029d449dcf/frozenlist-1.4.1-cp311-cp311-win_amd64.whl", hash = "sha256:fb3c2db03683b5767dedb5769b8a40ebb47d6f7f45b1b3e3b4b51ec8ad9d9825", size = 50459 }, - { url = "https://files.pythonhosted.org/packages/b4/db/4cf37556a735bcdb2582f2c3fa286aefde2322f92d3141e087b8aeb27177/frozenlist-1.4.1-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:1979bc0aeb89b33b588c51c54ab0161791149f2461ea7c7c946d95d5f93b56ae", size = 93937 }, - { url = "https://files.pythonhosted.org/packages/46/03/69eb64642ca8c05f30aa5931d6c55e50b43d0cd13256fdd01510a1f85221/frozenlist-1.4.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:cc7b01b3754ea68a62bd77ce6020afaffb44a590c2289089289363472d13aedb", size = 53656 }, - { url = "https://files.pythonhosted.org/packages/3f/ab/c543c13824a615955f57e082c8a5ee122d2d5368e80084f2834e6f4feced/frozenlist-1.4.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:c9c92be9fd329ac801cc420e08452b70e7aeab94ea4233a4804f0915c14eba9b", size = 51868 }, - { url = "https://files.pythonhosted.org/packages/a9/b8/438cfd92be2a124da8259b13409224d9b19ef8f5a5b2507174fc7e7ea18f/frozenlist-1.4.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5c3894db91f5a489fc8fa6a9991820f368f0b3cbdb9cd8849547ccfab3392d86", size = 280652 }, - { url = "https://files.pythonhosted.org/packages/54/72/716a955521b97a25d48315c6c3653f981041ce7a17ff79f701298195bca3/frozenlist-1.4.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ba60bb19387e13597fb059f32cd4d59445d7b18b69a745b8f8e5db0346f33480", size = 286739 }, - { url = "https://files.pythonhosted.org/packages/65/d8/934c08103637567084568e4d5b4219c1016c60b4d29353b1a5b3587827d6/frozenlist-1.4.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:8aefbba5f69d42246543407ed2461db31006b0f76c4e32dfd6f42215a2c41d09", size = 289447 }, - { url = "https://files.pythonhosted.org/packages/70/bb/d3b98d83ec6ef88f9bd63d77104a305d68a146fd63a683569ea44c3085f6/frozenlist-1.4.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:780d3a35680ced9ce682fbcf4cb9c2bad3136eeff760ab33707b71db84664e3a", size = 265466 }, - { url = "https://files.pythonhosted.org/packages/0b/f2/b8158a0f06faefec33f4dff6345a575c18095a44e52d4f10c678c137d0e0/frozenlist-1.4.1-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9acbb16f06fe7f52f441bb6f413ebae6c37baa6ef9edd49cdd567216da8600cd", size = 281530 }, - { url = "https://files.pythonhosted.org/packages/ea/a2/20882c251e61be653764038ece62029bfb34bd5b842724fff32a5b7a2894/frozenlist-1.4.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:23b701e65c7b36e4bf15546a89279bd4d8675faabc287d06bbcfac7d3c33e1e6", size = 281295 }, - { url = "https://files.pythonhosted.org/packages/4c/f9/8894c05dc927af2a09663bdf31914d4fb5501653f240a5bbaf1e88cab1d3/frozenlist-1.4.1-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:3e0153a805a98f5ada7e09826255ba99fb4f7524bb81bf6b47fb702666484ae1", size = 268054 }, - { url = "https://files.pythonhosted.org/packages/37/ff/a613e58452b60166507d731812f3be253eb1229808e59980f0405d1eafbf/frozenlist-1.4.1-cp312-cp312-musllinux_1_1_ppc64le.whl", hash = "sha256:dd9b1baec094d91bf36ec729445f7769d0d0cf6b64d04d86e45baf89e2b9059b", size = 286904 }, - { url = "https://files.pythonhosted.org/packages/cc/6e/0091d785187f4c2020d5245796d04213f2261ad097e0c1cf35c44317d517/frozenlist-1.4.1-cp312-cp312-musllinux_1_1_s390x.whl", hash = "sha256:1a4471094e146b6790f61b98616ab8e44f72661879cc63fa1049d13ef711e71e", size = 290754 }, - { url = "https://files.pythonhosted.org/packages/a5/c2/e42ad54bae8bcffee22d1e12a8ee6c7717f7d5b5019261a8c861854f4776/frozenlist-1.4.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:5667ed53d68d91920defdf4035d1cdaa3c3121dc0b113255124bcfada1cfa1b8", size = 282602 }, - { url = "https://files.pythonhosted.org/packages/b6/61/56bad8cb94f0357c4bc134acc30822e90e203b5cb8ff82179947de90c17f/frozenlist-1.4.1-cp312-cp312-win32.whl", hash = "sha256:beee944ae828747fd7cb216a70f120767fc9f4f00bacae8543c14a6831673f89", size = 44063 }, - { url = "https://files.pythonhosted.org/packages/3e/dc/96647994a013bc72f3d453abab18340b7f5e222b7b7291e3697ca1fcfbd5/frozenlist-1.4.1-cp312-cp312-win_amd64.whl", hash = "sha256:64536573d0a2cb6e625cf309984e2d873979709f2cf22839bf2d61790b448ad5", size = 50452 }, - { url = "https://files.pythonhosted.org/packages/83/10/466fe96dae1bff622021ee687f68e5524d6392b0a2f80d05001cd3a451ba/frozenlist-1.4.1-py3-none-any.whl", hash = "sha256:04ced3e6a46b4cfffe20f9ae482818e34eba9b5fb0ce4056e4cc9b6e212d09b7", size = 11552 }, + { url = "https://files.pythonhosted.org/packages/54/79/29d44c4af36b2b240725dce566b20f63f9b36ef267aaaa64ee7466f4f2f8/frozenlist-1.5.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:5b6a66c18b5b9dd261ca98dffcb826a525334b2f29e7caa54e182255c5f6a65a", size = 94451 }, + { url = "https://files.pythonhosted.org/packages/47/47/0c999aeace6ead8a44441b4f4173e2261b18219e4ad1fe9a479871ca02fc/frozenlist-1.5.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d1b3eb7b05ea246510b43a7e53ed1653e55c2121019a97e60cad7efb881a97bb", size = 54301 }, + { url = "https://files.pythonhosted.org/packages/8d/60/107a38c1e54176d12e06e9d4b5d755b677d71d1219217cee063911b1384f/frozenlist-1.5.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:15538c0cbf0e4fa11d1e3a71f823524b0c46299aed6e10ebb4c2089abd8c3bec", size = 52213 }, + { url = "https://files.pythonhosted.org/packages/17/62/594a6829ac5679c25755362a9dc93486a8a45241394564309641425d3ff6/frozenlist-1.5.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e79225373c317ff1e35f210dd5f1344ff31066ba8067c307ab60254cd3a78ad5", size = 240946 }, + { url = "https://files.pythonhosted.org/packages/7e/75/6c8419d8f92c80dd0ee3f63bdde2702ce6398b0ac8410ff459f9b6f2f9cb/frozenlist-1.5.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9272fa73ca71266702c4c3e2d4a28553ea03418e591e377a03b8e3659d94fa76", size = 264608 }, + { url = "https://files.pythonhosted.org/packages/88/3e/82a6f0b84bc6fb7e0be240e52863c6d4ab6098cd62e4f5b972cd31e002e8/frozenlist-1.5.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:498524025a5b8ba81695761d78c8dd7382ac0b052f34e66939c42df860b8ff17", size = 261361 }, + { url = "https://files.pythonhosted.org/packages/fd/85/14e5f9ccac1b64ff2f10c927b3ffdf88772aea875882406f9ba0cec8ad84/frozenlist-1.5.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:92b5278ed9d50fe610185ecd23c55d8b307d75ca18e94c0e7de328089ac5dcba", size = 231649 }, + { url = "https://files.pythonhosted.org/packages/ee/59/928322800306f6529d1852323014ee9008551e9bb027cc38d276cbc0b0e7/frozenlist-1.5.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7f3c8c1dacd037df16e85227bac13cca58c30da836c6f936ba1df0c05d046d8d", size = 241853 }, + { url = "https://files.pythonhosted.org/packages/7d/bd/e01fa4f146a6f6c18c5d34cab8abdc4013774a26c4ff851128cd1bd3008e/frozenlist-1.5.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:f2ac49a9bedb996086057b75bf93538240538c6d9b38e57c82d51f75a73409d2", size = 243652 }, + { url = "https://files.pythonhosted.org/packages/a5/bd/e4771fd18a8ec6757033f0fa903e447aecc3fbba54e3630397b61596acf0/frozenlist-1.5.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:e66cc454f97053b79c2ab09c17fbe3c825ea6b4de20baf1be28919460dd7877f", size = 241734 }, + { url = "https://files.pythonhosted.org/packages/21/13/c83821fa5544af4f60c5d3a65d054af3213c26b14d3f5f48e43e5fb48556/frozenlist-1.5.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:5a3ba5f9a0dfed20337d3e966dc359784c9f96503674c2faf015f7fe8e96798c", size = 260959 }, + { url = "https://files.pythonhosted.org/packages/71/f3/1f91c9a9bf7ed0e8edcf52698d23f3c211d8d00291a53c9f115ceb977ab1/frozenlist-1.5.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:6321899477db90bdeb9299ac3627a6a53c7399c8cd58d25da094007402b039ab", size = 262706 }, + { url = "https://files.pythonhosted.org/packages/4c/22/4a256fdf5d9bcb3ae32622c796ee5ff9451b3a13a68cfe3f68e2c95588ce/frozenlist-1.5.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:76e4753701248476e6286f2ef492af900ea67d9706a0155335a40ea21bf3b2f5", size = 250401 }, + { url = "https://files.pythonhosted.org/packages/af/89/c48ebe1f7991bd2be6d5f4ed202d94960c01b3017a03d6954dd5fa9ea1e8/frozenlist-1.5.0-cp310-cp310-win32.whl", hash = "sha256:977701c081c0241d0955c9586ffdd9ce44f7a7795df39b9151cd9a6fd0ce4cfb", size = 45498 }, + { url = "https://files.pythonhosted.org/packages/28/2f/cc27d5f43e023d21fe5c19538e08894db3d7e081cbf582ad5ed366c24446/frozenlist-1.5.0-cp310-cp310-win_amd64.whl", hash = "sha256:189f03b53e64144f90990d29a27ec4f7997d91ed3d01b51fa39d2dbe77540fd4", size = 51622 }, + { url = "https://files.pythonhosted.org/packages/79/43/0bed28bf5eb1c9e4301003b74453b8e7aa85fb293b31dde352aac528dafc/frozenlist-1.5.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:fd74520371c3c4175142d02a976aee0b4cb4a7cc912a60586ffd8d5929979b30", size = 94987 }, + { url = "https://files.pythonhosted.org/packages/bb/bf/b74e38f09a246e8abbe1e90eb65787ed745ccab6eaa58b9c9308e052323d/frozenlist-1.5.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:2f3f7a0fbc219fb4455264cae4d9f01ad41ae6ee8524500f381de64ffaa077d5", size = 54584 }, + { url = "https://files.pythonhosted.org/packages/2c/31/ab01375682f14f7613a1ade30149f684c84f9b8823a4391ed950c8285656/frozenlist-1.5.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:f47c9c9028f55a04ac254346e92977bf0f166c483c74b4232bee19a6697e4778", size = 52499 }, + { url = "https://files.pythonhosted.org/packages/98/a8/d0ac0b9276e1404f58fec3ab6e90a4f76b778a49373ccaf6a563f100dfbc/frozenlist-1.5.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0996c66760924da6e88922756d99b47512a71cfd45215f3570bf1e0b694c206a", size = 276357 }, + { url = "https://files.pythonhosted.org/packages/ad/c9/c7761084fa822f07dac38ac29f841d4587570dd211e2262544aa0b791d21/frozenlist-1.5.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a2fe128eb4edeabe11896cb6af88fca5346059f6c8d807e3b910069f39157869", size = 287516 }, + { url = "https://files.pythonhosted.org/packages/a1/ff/cd7479e703c39df7bdab431798cef89dc75010d8aa0ca2514c5b9321db27/frozenlist-1.5.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1a8ea951bbb6cacd492e3948b8da8c502a3f814f5d20935aae74b5df2b19cf3d", size = 283131 }, + { url = "https://files.pythonhosted.org/packages/59/a0/370941beb47d237eca4fbf27e4e91389fd68699e6f4b0ebcc95da463835b/frozenlist-1.5.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:de537c11e4aa01d37db0d403b57bd6f0546e71a82347a97c6a9f0dcc532b3a45", size = 261320 }, + { url = "https://files.pythonhosted.org/packages/b8/5f/c10123e8d64867bc9b4f2f510a32042a306ff5fcd7e2e09e5ae5100ee333/frozenlist-1.5.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9c2623347b933fcb9095841f1cc5d4ff0b278addd743e0e966cb3d460278840d", size = 274877 }, + { url = "https://files.pythonhosted.org/packages/fa/79/38c505601ae29d4348f21706c5d89755ceded02a745016ba2f58bd5f1ea6/frozenlist-1.5.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:cee6798eaf8b1416ef6909b06f7dc04b60755206bddc599f52232606e18179d3", size = 269592 }, + { url = "https://files.pythonhosted.org/packages/19/e2/39f3a53191b8204ba9f0bb574b926b73dd2efba2a2b9d2d730517e8f7622/frozenlist-1.5.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:f5f9da7f5dbc00a604fe74aa02ae7c98bcede8a3b8b9666f9f86fc13993bc71a", size = 265934 }, + { url = "https://files.pythonhosted.org/packages/d5/c9/3075eb7f7f3a91f1a6b00284af4de0a65a9ae47084930916f5528144c9dd/frozenlist-1.5.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:90646abbc7a5d5c7c19461d2e3eeb76eb0b204919e6ece342feb6032c9325ae9", size = 283859 }, + { url = "https://files.pythonhosted.org/packages/05/f5/549f44d314c29408b962fa2b0e69a1a67c59379fb143b92a0a065ffd1f0f/frozenlist-1.5.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:bdac3c7d9b705d253b2ce370fde941836a5f8b3c5c2b8fd70940a3ea3af7f4f2", size = 287560 }, + { url = "https://files.pythonhosted.org/packages/9d/f8/cb09b3c24a3eac02c4c07a9558e11e9e244fb02bf62c85ac2106d1eb0c0b/frozenlist-1.5.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:03d33c2ddbc1816237a67f66336616416e2bbb6beb306e5f890f2eb22b959cdf", size = 277150 }, + { url = "https://files.pythonhosted.org/packages/37/48/38c2db3f54d1501e692d6fe058f45b6ad1b358d82cd19436efab80cfc965/frozenlist-1.5.0-cp311-cp311-win32.whl", hash = "sha256:237f6b23ee0f44066219dae14c70ae38a63f0440ce6750f868ee08775073f942", size = 45244 }, + { url = "https://files.pythonhosted.org/packages/ca/8c/2ddffeb8b60a4bce3b196c32fcc30d8830d4615e7b492ec2071da801b8ad/frozenlist-1.5.0-cp311-cp311-win_amd64.whl", hash = "sha256:0cc974cc93d32c42e7b0f6cf242a6bd941c57c61b618e78b6c0a96cb72788c1d", size = 51634 }, + { url = "https://files.pythonhosted.org/packages/79/73/fa6d1a96ab7fd6e6d1c3500700963eab46813847f01ef0ccbaa726181dd5/frozenlist-1.5.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:31115ba75889723431aa9a4e77d5f398f5cf976eea3bdf61749731f62d4a4a21", size = 94026 }, + { url = "https://files.pythonhosted.org/packages/ab/04/ea8bf62c8868b8eada363f20ff1b647cf2e93377a7b284d36062d21d81d1/frozenlist-1.5.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7437601c4d89d070eac8323f121fcf25f88674627505334654fd027b091db09d", size = 54150 }, + { url = "https://files.pythonhosted.org/packages/d0/9a/8e479b482a6f2070b26bda572c5e6889bb3ba48977e81beea35b5ae13ece/frozenlist-1.5.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:7948140d9f8ece1745be806f2bfdf390127cf1a763b925c4a805c603df5e697e", size = 51927 }, + { url = "https://files.pythonhosted.org/packages/e3/12/2aad87deb08a4e7ccfb33600871bbe8f0e08cb6d8224371387f3303654d7/frozenlist-1.5.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:feeb64bc9bcc6b45c6311c9e9b99406660a9c05ca8a5b30d14a78555088b0b3a", size = 282647 }, + { url = "https://files.pythonhosted.org/packages/77/f2/07f06b05d8a427ea0060a9cef6e63405ea9e0d761846b95ef3fb3be57111/frozenlist-1.5.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:683173d371daad49cffb8309779e886e59c2f369430ad28fe715f66d08d4ab1a", size = 289052 }, + { url = "https://files.pythonhosted.org/packages/bd/9f/8bf45a2f1cd4aa401acd271b077989c9267ae8463e7c8b1eb0d3f561b65e/frozenlist-1.5.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7d57d8f702221405a9d9b40f9da8ac2e4a1a8b5285aac6100f3393675f0a85ee", size = 291719 }, + { url = "https://files.pythonhosted.org/packages/41/d1/1f20fd05a6c42d3868709b7604c9f15538a29e4f734c694c6bcfc3d3b935/frozenlist-1.5.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:30c72000fbcc35b129cb09956836c7d7abf78ab5416595e4857d1cae8d6251a6", size = 267433 }, + { url = "https://files.pythonhosted.org/packages/af/f2/64b73a9bb86f5a89fb55450e97cd5c1f84a862d4ff90d9fd1a73ab0f64a5/frozenlist-1.5.0-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:000a77d6034fbad9b6bb880f7ec073027908f1b40254b5d6f26210d2dab1240e", size = 283591 }, + { url = "https://files.pythonhosted.org/packages/29/e2/ffbb1fae55a791fd6c2938dd9ea779509c977435ba3940b9f2e8dc9d5316/frozenlist-1.5.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:5d7f5a50342475962eb18b740f3beecc685a15b52c91f7d975257e13e029eca9", size = 273249 }, + { url = "https://files.pythonhosted.org/packages/2e/6e/008136a30798bb63618a114b9321b5971172a5abddff44a100c7edc5ad4f/frozenlist-1.5.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:87f724d055eb4785d9be84e9ebf0f24e392ddfad00b3fe036e43f489fafc9039", size = 271075 }, + { url = "https://files.pythonhosted.org/packages/ae/f0/4e71e54a026b06724cec9b6c54f0b13a4e9e298cc8db0f82ec70e151f5ce/frozenlist-1.5.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:6e9080bb2fb195a046e5177f10d9d82b8a204c0736a97a153c2466127de87784", size = 285398 }, + { url = "https://files.pythonhosted.org/packages/4d/36/70ec246851478b1c0b59f11ef8ade9c482ff447c1363c2bd5fad45098b12/frozenlist-1.5.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:9b93d7aaa36c966fa42efcaf716e6b3900438632a626fb09c049f6a2f09fc631", size = 294445 }, + { url = "https://files.pythonhosted.org/packages/37/e0/47f87544055b3349b633a03c4d94b405956cf2437f4ab46d0928b74b7526/frozenlist-1.5.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:52ef692a4bc60a6dd57f507429636c2af8b6046db8b31b18dac02cbc8f507f7f", size = 280569 }, + { url = "https://files.pythonhosted.org/packages/f9/7c/490133c160fb6b84ed374c266f42800e33b50c3bbab1652764e6e1fc498a/frozenlist-1.5.0-cp312-cp312-win32.whl", hash = "sha256:29d94c256679247b33a3dc96cce0f93cbc69c23bf75ff715919332fdbb6a32b8", size = 44721 }, + { url = "https://files.pythonhosted.org/packages/b1/56/4e45136ffc6bdbfa68c29ca56ef53783ef4c2fd395f7cbf99a2624aa9aaa/frozenlist-1.5.0-cp312-cp312-win_amd64.whl", hash = "sha256:8969190d709e7c48ea386db202d708eb94bdb29207a1f269bab1196ce0dcca1f", size = 51329 }, + { url = "https://files.pythonhosted.org/packages/c6/c8/a5be5b7550c10858fcf9b0ea054baccab474da77d37f1e828ce043a3a5d4/frozenlist-1.5.0-py3-none-any.whl", hash = "sha256:d994863bba198a4a518b467bb971c56e1db3f180a25c6cf7bb1949c267f748c3", size = 11901 }, ] [[package]] name = "fsspec" -version = "2024.9.0" +version = "2024.10.0" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/62/7c/12b0943011daaaa9c35c2a2e22e5eb929ac90002f08f1259d69aedad84de/fsspec-2024.9.0.tar.gz", hash = "sha256:4b0afb90c2f21832df142f292649035d80b421f60a9e1c027802e5a0da2b04e8", size = 286206 } +sdist = { url = "https://files.pythonhosted.org/packages/a0/52/f16a068ebadae42526484c31f4398e62962504e5724a8ba5dc3409483df2/fsspec-2024.10.0.tar.gz", hash = "sha256:eda2d8a4116d4f2429db8550f2457da57279247dd930bb12f821b58391359493", size = 286853 } wheels = [ - { url = "https://files.pythonhosted.org/packages/1d/a0/6aaea0c2fbea2f89bfd5db25fb1e3481896a423002ebe4e55288907a97a3/fsspec-2024.9.0-py3-none-any.whl", hash = "sha256:a0947d552d8a6efa72cc2c730b12c41d043509156966cca4fb157b0f2a0c574b", size = 179253 }, + { url = "https://files.pythonhosted.org/packages/c6/b2/454d6e7f0158951d8a78c2e1eb4f69ae81beb8dca5fee9809c6c99e9d0d0/fsspec-2024.10.0-py3-none-any.whl", hash = "sha256:03b9a6785766a4de40368b88906366755e2819e758b83705c88cd7cb5fe81871", size = 179641 }, ] [package.optional-dependencies] @@ -2038,7 +2039,7 @@ wheels = [ [[package]] name = "google-api-core" -version = "2.21.0" +version = "2.24.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "google-auth" }, @@ -2047,9 +2048,9 @@ dependencies = [ { name = "protobuf" }, { name = "requests" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/28/c8/046abf3ea11ec9cc3ea6d95e235a51161039d4a558484a997df60f9c51e9/google_api_core-2.21.0.tar.gz", hash = "sha256:4a152fd11a9f774ea606388d423b68aa7e6d6a0ffe4c8266f74979613ec09f81", size = 159313 } +sdist = { url = "https://files.pythonhosted.org/packages/81/56/d70d66ed1b5ab5f6c27bf80ec889585ad8f865ff32acbafd3b2ef0bfb5d0/google_api_core-2.24.0.tar.gz", hash = "sha256:e255640547a597a4da010876d333208ddac417d60add22b6851a0c66a831fcaf", size = 162647 } wheels = [ - { url = "https://files.pythonhosted.org/packages/6a/ef/79fa8388c95edbd8fe36c763259dade36e5cb562dcf3e85c0e32070dc9b0/google_api_core-2.21.0-py3-none-any.whl", hash = "sha256:6869eacb2a37720380ba5898312af79a4d30b8bca1548fb4093e0697dc4bdf5d", size = 156437 }, + { url = "https://files.pythonhosted.org/packages/a1/76/65b8b94e74bf1b6d1cc38d916089670c4da5029d25762441d8c5c19e51dd/google_api_core-2.24.0-py3-none-any.whl", hash = "sha256:10d82ac0fca69c82a25b3efdeefccf6f28e02ebb97925a8cce8edbfe379929d9", size = 158576 }, ] [package.optional-dependencies] @@ -2076,16 +2077,16 @@ wheels = [ [[package]] name = "google-auth" -version = "2.35.0" +version = "2.36.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "cachetools" }, { name = "pyasn1-modules" }, { name = "rsa" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/a1/37/c854a8b1b1020cf042db3d67577c6f84cd1e8ff6515e4f5498ae9e444ea5/google_auth-2.35.0.tar.gz", hash = "sha256:f4c64ed4e01e8e8b646ef34c018f8bf3338df0c8e37d8b3bba40e7f574a3278a", size = 267223 } +sdist = { url = "https://files.pythonhosted.org/packages/6a/71/4c5387d8a3e46e3526a8190ae396659484377a73b33030614dd3b28e7ded/google_auth-2.36.0.tar.gz", hash = "sha256:545e9618f2df0bcbb7dcbc45a546485b1212624716975a1ea5ae8149ce769ab1", size = 268336 } wheels = [ - { url = "https://files.pythonhosted.org/packages/27/1f/3a72917afcb0d5cd842cbccb81bf7a8a7b45b4c66d8dc4556ccb3b016bfc/google_auth-2.35.0-py2.py3-none-any.whl", hash = "sha256:25df55f327ef021de8be50bad0dfd4a916ad0de96da86cd05661c9297723ad3f", size = 208968 }, + { url = "https://files.pythonhosted.org/packages/2d/9a/3d5087d27865c2f0431b942b5c4500b7d1b744dd3262fdc973a4c39d099e/google_auth-2.36.0-py2.py3-none-any.whl", hash = "sha256:51a15d47028b66fd36e5c64a82d2d57480075bccc7da37cde257fc94177a61fb", size = 209519 }, ] [[package]] @@ -2116,7 +2117,7 @@ wheels = [ [[package]] name = "google-cloud-aiplatform" -version = "1.70.0" +version = "1.74.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "docstring-parser" }, @@ -2131,14 +2132,14 @@ dependencies = [ { name = "pydantic" }, { name = "shapely" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/88/06/bc8028c03d4bedb85114c780a9f749b67ff06ce29d25dc7f1a99622f2692/google-cloud-aiplatform-1.70.0.tar.gz", hash = "sha256:e8edef6dbc7911380d0ea55c47544e799f62b891cb1a83b504ca1c09fff9884b", size = 6311624 } +sdist = { url = "https://files.pythonhosted.org/packages/10/67/a404c06c3924e6f08962932fe5f3820938165b7b4eacaa482fe9636acd56/google_cloud_aiplatform-1.74.0.tar.gz", hash = "sha256:2202e4e0cbbd2db02835737a1ae9a51ad7bf75c8ed130a3fdbcfced33525e3f0", size = 7768846 } wheels = [ - { url = "https://files.pythonhosted.org/packages/46/d9/280e5a9b5caf69322f64fa55f62bf447d76c5fe30e8df6e93373f22c4bd7/google_cloud_aiplatform-1.70.0-py2.py3-none-any.whl", hash = "sha256:690e6041f03d3aa85102ac3f316c958d6f43a99aefb7fb3f8938dee56d08abd9", size = 5267225 }, + { url = "https://files.pythonhosted.org/packages/95/a8/bc583352dd5020be9651582fe3ebfd46a1e3e2130cb09d638cecf1cd9842/google_cloud_aiplatform-1.74.0-py2.py3-none-any.whl", hash = "sha256:7f37a835e543a4cb4b62505928b983e307c5fee6d949f831cd3804f03c753d87", size = 6454382 }, ] [[package]] name = "google-cloud-bigquery" -version = "3.26.0" +version = "3.27.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "google-api-core", extra = ["grpc"] }, @@ -2149,9 +2150,9 @@ dependencies = [ { name = "python-dateutil" }, { name = "requests" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/7a/b7/86336c193f7de63c68426005ebb130093ab81cdabf45b5e6ca378112c453/google_cloud_bigquery-3.26.0.tar.gz", hash = "sha256:edbdc788beea659e04c0af7fe4dcd6d9155344b98951a0d5055bd2f15da4ba23", size = 455586 } +sdist = { url = "https://files.pythonhosted.org/packages/c0/05/633ce6686b1fed2cd364fa4698bfa6d586263cd4795d012584f8097061e1/google_cloud_bigquery-3.27.0.tar.gz", hash = "sha256:379c524054d7b090fa56d0c22662cc6e6458a6229b6754c0e7177e3a73421d2c", size = 456964 } wheels = [ - { url = "https://files.pythonhosted.org/packages/2a/91/e1c80ae2924efc047ca156662d6b0458d9a9ce99204ae7e719ff9a66123d/google_cloud_bigquery-3.26.0-py2.py3-none-any.whl", hash = "sha256:e0e9ad28afa67a18696e624cbccab284bf2c0a3f6eeb9eeb0426c69b943793a8", size = 239126 }, + { url = "https://files.pythonhosted.org/packages/f5/40/4b11a4a8839de8ce802a3ccd60b34e70ce10d13d434a560534ba98f0ea3f/google_cloud_bigquery-3.27.0-py2.py3-none-any.whl", hash = "sha256:b53b0431e5ba362976a4cd8acce72194b4116cdf8115030c7b339b884603fcc3", size = 240100 }, ] [[package]] @@ -2169,7 +2170,7 @@ wheels = [ [[package]] name = "google-cloud-resource-manager" -version = "1.12.5" +version = "1.13.1" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "google-api-core", extra = ["grpc"] }, @@ -2178,14 +2179,14 @@ dependencies = [ { name = "proto-plus" }, { name = "protobuf" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/62/32/14d345dee1f290a26bd639da8edbca30958865b7cc7207961e10d2f32282/google_cloud_resource_manager-1.12.5.tar.gz", hash = "sha256:b7af4254401ed4efa3aba3a929cb3ddb803fa6baf91a78485e45583597de5891", size = 394678 } +sdist = { url = "https://files.pythonhosted.org/packages/b0/59/34b2333a7a2419239af4b4532e3223a149562e819e00586e90056efd0200/google_cloud_resource_manager-1.13.1.tar.gz", hash = "sha256:bee9f2fb1d856731182b7cc05980d216aae848947ccdadf2848a2c64ccd6bbea", size = 404202 } wheels = [ - { url = "https://files.pythonhosted.org/packages/6a/ab/63ab13fb060714b9d1708ca32e0ee41f9ffe42a62e524e7429cde45cfe61/google_cloud_resource_manager-1.12.5-py2.py3-none-any.whl", hash = "sha256:2708a718b45c79464b7b21559c701b5c92e6b0b1ab2146d0a256277a623dc175", size = 341861 }, + { url = "https://files.pythonhosted.org/packages/dd/cf/68ba6b60d1363a7e3193f457badc3cb4003552b11fa37152be9db2a3d0ac/google_cloud_resource_manager-1.13.1-py2.py3-none-any.whl", hash = "sha256:abdc7d443ab6c0763b8ed49ab59203e223f14c683df69e3748d5eb2237475f5f", size = 358574 }, ] [[package]] name = "google-cloud-storage" -version = "2.18.2" +version = "2.19.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "google-api-core" }, @@ -2195,9 +2196,9 @@ dependencies = [ { name = "google-resumable-media" }, { name = "requests" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/d6/b7/1554cdeb55d9626a4b8720746cba8119af35527b12e1780164f9ba0f659a/google_cloud_storage-2.18.2.tar.gz", hash = "sha256:aaf7acd70cdad9f274d29332673fcab98708d0e1f4dceb5a5356aaef06af4d99", size = 5532864 } +sdist = { url = "https://files.pythonhosted.org/packages/36/76/4d965702e96bb67976e755bed9828fa50306dca003dbee08b67f41dd265e/google_cloud_storage-2.19.0.tar.gz", hash = "sha256:cd05e9e7191ba6cb68934d8eb76054d9be4562aa89dbc4236feee4d7d51342b2", size = 5535488 } wheels = [ - { url = "https://files.pythonhosted.org/packages/fc/da/95db7bd4f0bd1644378ac1702c565c0210b004754d925a74f526a710c087/google_cloud_storage-2.18.2-py2.py3-none-any.whl", hash = "sha256:97a4d45c368b7d401ed48c4fdfe86e1e1cb96401c9e199e419d289e2c0370166", size = 130466 }, + { url = "https://files.pythonhosted.org/packages/d5/94/6db383d8ee1adf45dc6c73477152b82731fa4c4a46d9c1932cc8757e0fd4/google_cloud_storage-2.19.0-py2.py3-none-any.whl", hash = "sha256:aeb971b5c29cf8ab98445082cbfe7b161a1f48ed275822f59ed3f1524ea54fba", size = 131787 }, ] [[package]] @@ -2267,14 +2268,14 @@ sdist = { url = "https://files.pythonhosted.org/packages/77/30/b3a6f6a2e00f81535 [[package]] name = "googleapis-common-protos" -version = "1.65.0" +version = "1.66.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "protobuf" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/53/3b/1599ceafa875ffb951480c8c74f4b77646a6b80e80970698f2aa93c216ce/googleapis_common_protos-1.65.0.tar.gz", hash = "sha256:334a29d07cddc3aa01dee4988f9afd9b2916ee2ff49d6b757155dc0d197852c0", size = 113657 } +sdist = { url = "https://files.pythonhosted.org/packages/ff/a7/8e9cccdb1c49870de6faea2a2764fa23f627dd290633103540209f03524c/googleapis_common_protos-1.66.0.tar.gz", hash = "sha256:c3e7b33d15fdca5374cc0a7346dd92ffa847425cc4ea941d970f13680052ec8c", size = 114376 } wheels = [ - { url = "https://files.pythonhosted.org/packages/ec/08/49bfe7cf737952cc1a9c43e80cc258ed45dad7f183c5b8276fc94cb3862d/googleapis_common_protos-1.65.0-py2.py3-none-any.whl", hash = "sha256:2972e6c496f435b92590fd54045060867f3fe9be2c82ab148fc8885035479a63", size = 220890 }, + { url = "https://files.pythonhosted.org/packages/a0/0f/c0713fb2b3d28af4b2fded3291df1c4d4f79a00d15c2374a9e010870016c/googleapis_common_protos-1.66.0-py2.py3-none-any.whl", hash = "sha256:d7abcd75fabb2e0ec9f74466401f6c119a0b498e27370e9be4c94cb7e382b8ed", size = 221682 }, ] [package.optional-dependencies] @@ -2284,15 +2285,15 @@ grpc = [ [[package]] name = "gotrue" -version = "2.9.2" +version = "2.11.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "httpx", extra = ["http2"] }, { name = "pydantic" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/e0/59/2f184ea5c79e8fcc33d8ba9a70d3d0395b8629a73c7d1591987098da1c9e/gotrue-2.9.2.tar.gz", hash = "sha256:57b3245e916c5efbf19a21b1181011a903c1276bb1df2d847558f2f24f29abb2", size = 41351 } +sdist = { url = "https://files.pythonhosted.org/packages/99/ee/a88dd953f3c4dd5f3c6ba30bb7cf6e26dee149505539cb89853aa36f5e74/gotrue-2.11.0.tar.gz", hash = "sha256:a0a452748ef741337820c97b934327c25f796e7cd33c0bf4341346bcc5a837f5", size = 41666 } wheels = [ - { url = "https://files.pythonhosted.org/packages/bd/f1/bad557f1f95218412f979458d9414f7afc77da837cdccda253dce75a6c8f/gotrue-2.9.2-py3-none-any.whl", hash = "sha256:fcd5279e8f1cc630f3ac35af5485fe39f8030b23906776920d2c32a4e308cff4", size = 48580 }, + { url = "https://files.pythonhosted.org/packages/62/8d/b753a2541fd0191c35f2b1753cb219dd7d68031a62c77ebc72fbb8fd66f0/gotrue-2.11.0-py3-none-any.whl", hash = "sha256:62177ffd567448b352121bc7e9244ff018d59bb746dad476b51658f856d59cf8", size = 48916 }, ] [[package]] @@ -2367,7 +2368,7 @@ wheels = [ [[package]] name = "groq" -version = "0.11.0" +version = "0.13.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "anyio" }, @@ -2377,9 +2378,9 @@ dependencies = [ { name = "sniffio" }, { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/bb/4d/14b9a0c27695b2aa3bcd7f397a9c6d5aa84165d0bed4e4ca3f08fe59a546/groq-0.11.0.tar.gz", hash = "sha256:dbb9aefedf388ddd4801ec7bf3eba7f5edb67948fec0cd2829d97244059f42a7", size = 104986 } +sdist = { url = "https://files.pythonhosted.org/packages/27/55/31d57ca9fc0c8dd29eed0f2f30112f7477d3b68e9a826a22f7edb5bc5c36/groq-0.13.0.tar.gz", hash = "sha256:aaa213821c94d8974e57bab5fe59cb45c8871875d0cd53ec179afed928bad18e", size = 108654 } wheels = [ - { url = "https://files.pythonhosted.org/packages/94/c3/8bf3cd2987e262f9fd45024313dae1d009edaa7a5b429566edfdaedaa024/groq-0.11.0-py3-none-any.whl", hash = "sha256:e328531c979542e563668c62260aec13b43a6ee0ca9e2fb22dff1d26f8c8ce54", size = 106518 }, + { url = "https://files.pythonhosted.org/packages/fb/d2/2ee77e5c12b39d45df6e053cabcfec62b367e92bc613a9e29d66e74997a9/groq-0.13.0-py3-none-any.whl", hash = "sha256:1c2b16fd1c4665c2d09509ee42ead9cc7d32534b37b2051fee0ea8b6216b899d", size = 108777 }, ] [[package]] @@ -2398,101 +2399,104 @@ wheels = [ [[package]] name = "grpcio" -version = "1.66.2" +version = "1.68.1" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/71/d1/49a96df4eb1d805cf546247df40636515416d2d5c66665e5129c8b4162a8/grpcio-1.66.2.tar.gz", hash = "sha256:563588c587b75c34b928bc428548e5b00ea38c46972181a4d8b75ba7e3f24231", size = 12489713 } +sdist = { url = "https://files.pythonhosted.org/packages/91/ec/b76ff6d86bdfd1737a5ec889394b54c18b1ec3832d91041e25023fbcb67d/grpcio-1.68.1.tar.gz", hash = "sha256:44a8502dd5de653ae6a73e2de50a401d84184f0331d0ac3daeb044e66d5c5054", size = 12694654 } wheels = [ - { url = "https://files.pythonhosted.org/packages/04/b1/3188546f59df6a41998bdbac127373a21c5306a79fbf50bcffb24091fe7f/grpcio-1.66.2-cp310-cp310-linux_armv7l.whl", hash = "sha256:fe96281713168a3270878255983d2cb1a97e034325c8c2c25169a69289d3ecfa", size = 5025654 }, - { url = "https://files.pythonhosted.org/packages/da/b6/5fbf50889358228a344b93fe7c676de72fcf88073983c441e2ea92730adb/grpcio-1.66.2-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:73fc8f8b9b5c4a03e802b3cd0c18b2b06b410d3c1dcbef989fdeb943bd44aff7", size = 10749112 }, - { url = "https://files.pythonhosted.org/packages/9c/8f/b1c53f3cb32ec808c7aa8ce6b4d5dfd8e50c3e85aa7d5d44ae1262294a73/grpcio-1.66.2-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:03b0b307ba26fae695e067b94cbb014e27390f8bc5ac7a3a39b7723fed085604", size = 5541480 }, - { url = "https://files.pythonhosted.org/packages/e9/d8/85e57d340aa40ac6f7b5fb241a7d3805888a42ed96876f3107f6a828c6b7/grpcio-1.66.2-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7d69ce1f324dc2d71e40c9261d3fdbe7d4c9d60f332069ff9b2a4d8a257c7b2b", size = 6133888 }, - { url = "https://files.pythonhosted.org/packages/20/94/fffcd2a14bd79fc74c0c0f2a777299ec1702cc1bee32ca53c42405129bdd/grpcio-1.66.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:05bc2ceadc2529ab0b227b1310d249d95d9001cd106aa4d31e8871ad3c428d73", size = 5793512 }, - { url = "https://files.pythonhosted.org/packages/a3/54/a7fca38e8a71cc7d410873ffdc4e128b2881959d0607afb8a909f2bd7af9/grpcio-1.66.2-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:8ac475e8da31484efa25abb774674d837b343afb78bb3bcdef10f81a93e3d6bf", size = 6460939 }, - { url = "https://files.pythonhosted.org/packages/8e/0d/a83f9e7cbf620bbf99f5ee129a90b0891a967575f7bc2e227cd3376ebc53/grpcio-1.66.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0be4e0490c28da5377283861bed2941d1d20ec017ca397a5df4394d1c31a9b50", size = 6053165 }, - { url = "https://files.pythonhosted.org/packages/c7/72/4021313e996285f4b6349114d107b5390b76acd5a1adefea50dac024a3b1/grpcio-1.66.2-cp310-cp310-win32.whl", hash = "sha256:4e504572433f4e72b12394977679161d495c4c9581ba34a88d843eaf0f2fbd39", size = 3554333 }, - { url = "https://files.pythonhosted.org/packages/24/7a/5cb5fd3db7a5779c44b6e7a267d71f13e65aaafcc6f792c795b06f11e46e/grpcio-1.66.2-cp310-cp310-win_amd64.whl", hash = "sha256:2018b053aa15782db2541ca01a7edb56a0bf18c77efed975392583725974b249", size = 4288611 }, - { url = "https://files.pythonhosted.org/packages/6f/30/eb9c490a1450f30a2f4f988c5227d38df1d3cf1b96bd7f86d1c01b975bd5/grpcio-1.66.2-cp311-cp311-linux_armv7l.whl", hash = "sha256:2335c58560a9e92ac58ff2bc5649952f9b37d0735608242973c7a8b94a6437d8", size = 5035597 }, - { url = "https://files.pythonhosted.org/packages/e4/81/e25c4e06e9c861760801812d60c4839bedfb62a955bbdbf3f4f9e1d21c9e/grpcio-1.66.2-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:45a3d462826f4868b442a6b8fdbe8b87b45eb4f5b5308168c156b21eca43f61c", size = 10815748 }, - { url = "https://files.pythonhosted.org/packages/d5/0e/f3458a4b480a9aa7ee28da8d38621898cb7b9c52bd6d7eeff4e65a9e54fd/grpcio-1.66.2-cp311-cp311-manylinux_2_17_aarch64.whl", hash = "sha256:a9539f01cb04950fd4b5ab458e64a15f84c2acc273670072abe49a3f29bbad54", size = 5535622 }, - { url = "https://files.pythonhosted.org/packages/88/63/83b994a95dec4d45bdd08a2c1ad78287c43ea8e05aa87f12fe73a034bec1/grpcio-1.66.2-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ce89f5876662f146d4c1f695dda29d4433a5d01c8681fbd2539afff535da14d4", size = 6133932 }, - { url = "https://files.pythonhosted.org/packages/35/90/a4f76c14230da281d51ef9eb30eb3ff2df129b83a4a98906756c063578c1/grpcio-1.66.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d25a14af966438cddf498b2e338f88d1c9706f3493b1d73b93f695c99c5f0e2a", size = 5791619 }, - { url = "https://files.pythonhosted.org/packages/ae/16/ae127be201e98a2bda5a602ea94a8e9b6351b2eb998c1177eb489ee03bb6/grpcio-1.66.2-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:6001e575b8bbd89eee11960bb640b6da6ae110cf08113a075f1e2051cc596cae", size = 6457847 }, - { url = "https://files.pythonhosted.org/packages/a0/98/b7c72630458b037f4b03bda4dbc22efcc44f6ce22ac0a90111d464d13849/grpcio-1.66.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:4ea1d062c9230278793820146c95d038dc0f468cbdd172eec3363e42ff1c7d01", size = 6051643 }, - { url = "https://files.pythonhosted.org/packages/53/47/268e0aeec678993a865ae7c14876a830224a1411aa98032969a6921ebd59/grpcio-1.66.2-cp311-cp311-win32.whl", hash = "sha256:38b68498ff579a3b1ee8f93a05eb48dc2595795f2f62716e797dc24774c1aaa8", size = 3555795 }, - { url = "https://files.pythonhosted.org/packages/f8/22/cf3e6ef61c62e631d5567810432a826a3f5752f132d6c3352f6cfbedbedb/grpcio-1.66.2-cp311-cp311-win_amd64.whl", hash = "sha256:6851de821249340bdb100df5eacfecfc4e6075fa85c6df7ee0eb213170ec8e5d", size = 4290733 }, - { url = "https://files.pythonhosted.org/packages/6b/5c/c4da36b7a77dbb15c4bc72228dff7161874752b2c6bddf7bb046d9da1b90/grpcio-1.66.2-cp312-cp312-linux_armv7l.whl", hash = "sha256:802d84fd3d50614170649853d121baaaa305de7b65b3e01759247e768d691ddf", size = 5002933 }, - { url = "https://files.pythonhosted.org/packages/a0/d5/b631445dff250a5301f51ff56c5fc917c7f955cd02fa55379f158a89abeb/grpcio-1.66.2-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:80fd702ba7e432994df208f27514280b4b5c6843e12a48759c9255679ad38db8", size = 10793953 }, - { url = "https://files.pythonhosted.org/packages/c8/1c/2179ac112152e92c02990f98183edf645df14aa3c38b39f1a3a60358b6c6/grpcio-1.66.2-cp312-cp312-manylinux_2_17_aarch64.whl", hash = "sha256:12fda97ffae55e6526825daf25ad0fa37483685952b5d0f910d6405c87e3adb6", size = 5499791 }, - { url = "https://files.pythonhosted.org/packages/0b/53/8d7ab865fbd983309c8242930f00b28a01047f70c2b2e4c79a5c92a46a08/grpcio-1.66.2-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:950da58d7d80abd0ea68757769c9db0a95b31163e53e5bb60438d263f4bed7b7", size = 6109606 }, - { url = "https://files.pythonhosted.org/packages/86/e9/3dfb5a3ff540636d46b8b723345e923e8c553d9b3f6a8d1b09b0d915eb46/grpcio-1.66.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e636ce23273683b00410f1971d209bf3689238cf5538d960adc3cdfe80dd0dbd", size = 5762866 }, - { url = "https://files.pythonhosted.org/packages/f1/cb/c07493ad5dd73d51e4e15b0d483ff212dfec136ee1e4f3b49d115bdc7a13/grpcio-1.66.2-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:a917d26e0fe980b0ac7bfcc1a3c4ad6a9a4612c911d33efb55ed7833c749b0ee", size = 6446819 }, - { url = "https://files.pythonhosted.org/packages/ff/5f/142e19db367a34ea0ee8a8451e43215d0a1a5dbffcfdcae8801f22903301/grpcio-1.66.2-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:49f0ca7ae850f59f828a723a9064cadbed90f1ece179d375966546499b8a2c9c", size = 6040273 }, - { url = "https://files.pythonhosted.org/packages/5c/3b/12fcd752c55002e4b0e0a7bd5faec101bc0a4e3890be3f95a43353142481/grpcio-1.66.2-cp312-cp312-win32.whl", hash = "sha256:31fd163105464797a72d901a06472860845ac157389e10f12631025b3e4d0453", size = 3537988 }, - { url = "https://files.pythonhosted.org/packages/f1/70/76bfea3faa862bfceccba255792e780691ff25b8227180759c9d38769379/grpcio-1.66.2-cp312-cp312-win_amd64.whl", hash = "sha256:ff1f7882e56c40b0d33c4922c15dfa30612f05fb785074a012f7cda74d1c3679", size = 4275553 }, + { url = "https://files.pythonhosted.org/packages/f5/88/d1ac9676a0809e3efec154d45246474ec12a4941686da71ffb3d34190294/grpcio-1.68.1-cp310-cp310-linux_armv7l.whl", hash = "sha256:d35740e3f45f60f3c37b1e6f2f4702c23867b9ce21c6410254c9c682237da68d", size = 5171054 }, + { url = "https://files.pythonhosted.org/packages/ec/cb/94ca41e100201fee8876a4b44d64e43ac7405929909afe1fa943d65b25ef/grpcio-1.68.1-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:d99abcd61760ebb34bdff37e5a3ba333c5cc09feda8c1ad42547bea0416ada78", size = 11078566 }, + { url = "https://files.pythonhosted.org/packages/d5/b0/ad4c66f2e3181b4eab99885686c960c403ae2300bacfe427526282facc07/grpcio-1.68.1-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:f8261fa2a5f679abeb2a0a93ad056d765cdca1c47745eda3f2d87f874ff4b8c9", size = 5690039 }, + { url = "https://files.pythonhosted.org/packages/67/1e/f5d3410674d021831c9fef2d1d7ca2357b08d09c840ad4e054ea8ffc302e/grpcio-1.68.1-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0feb02205a27caca128627bd1df4ee7212db051019a9afa76f4bb6a1a80ca95e", size = 6317470 }, + { url = "https://files.pythonhosted.org/packages/91/93/701d5f33b163a621c8f2d4453f9e22f6c14e996baed54118d0dea93fc8c7/grpcio-1.68.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:919d7f18f63bcad3a0f81146188e90274fde800a94e35d42ffe9eadf6a9a6330", size = 5941884 }, + { url = "https://files.pythonhosted.org/packages/67/44/06917ffaa35ca463b93dde60f324015fe4192312b0f4dd0faec061e7ca7f/grpcio-1.68.1-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:963cc8d7d79b12c56008aabd8b457f400952dbea8997dd185f155e2f228db079", size = 6646332 }, + { url = "https://files.pythonhosted.org/packages/d4/94/074db039532687ec8ef07ebbcc747c46547c94329016e22b97d97b9e5f3b/grpcio-1.68.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:ccf2ebd2de2d6661e2520dae293298a3803a98ebfc099275f113ce1f6c2a80f1", size = 6212515 }, + { url = "https://files.pythonhosted.org/packages/c5/f2/0c939264c36c6038fae1732a2a3e01a7075ba171a2154d86842ee0ac9b0a/grpcio-1.68.1-cp310-cp310-win32.whl", hash = "sha256:2cc1fd04af8399971bcd4f43bd98c22d01029ea2e56e69c34daf2bf8470e47f5", size = 3650459 }, + { url = "https://files.pythonhosted.org/packages/b6/90/b0e9278e88f747879d13b79fb893c9acb381fb90541ad9e416c7816c5eaf/grpcio-1.68.1-cp310-cp310-win_amd64.whl", hash = "sha256:ee2e743e51cb964b4975de572aa8fb95b633f496f9fcb5e257893df3be854746", size = 4399144 }, + { url = "https://files.pythonhosted.org/packages/fe/0d/fde5a5777d65696c39bb3e622fe1239dd0a878589bf6c5066980e7d19154/grpcio-1.68.1-cp311-cp311-linux_armv7l.whl", hash = "sha256:55857c71641064f01ff0541a1776bfe04a59db5558e82897d35a7793e525774c", size = 5180919 }, + { url = "https://files.pythonhosted.org/packages/07/fd/e5fa75b5ddf5d9f16606196973f9c2b4b1adf5a1735117eb7129fc33d2ec/grpcio-1.68.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:4b177f5547f1b995826ef529d2eef89cca2f830dd8b2c99ffd5fde4da734ba73", size = 11150922 }, + { url = "https://files.pythonhosted.org/packages/86/1e/aaf5a1dae87fe47f277c5a1be72b31d2c209d095bebb0ce1d2df5cb8779c/grpcio-1.68.1-cp311-cp311-manylinux_2_17_aarch64.whl", hash = "sha256:3522c77d7e6606d6665ec8d50e867f13f946a4e00c7df46768f1c85089eae515", size = 5685685 }, + { url = "https://files.pythonhosted.org/packages/a9/69/c4fdf87d5c5696207e2ed232e4bdde656d8c99ba91f361927f3f06aa41ca/grpcio-1.68.1-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9d1fae6bbf0816415b81db1e82fb3bf56f7857273c84dcbe68cbe046e58e1ccd", size = 6316535 }, + { url = "https://files.pythonhosted.org/packages/6f/c6/539660516ea7db7bc3d39e07154512ae807961b14ec6b5b0c58d15657ff1/grpcio-1.68.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:298ee7f80e26f9483f0b6f94cc0a046caf54400a11b644713bb5b3d8eb387600", size = 5939920 }, + { url = "https://files.pythonhosted.org/packages/38/f3/97a74dc4dd95bf195168d6da2ca4731ab7d3d0b03078f2833b4ff9c4f48f/grpcio-1.68.1-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:cbb5780e2e740b6b4f2d208e90453591036ff80c02cc605fea1af8e6fc6b1bbe", size = 6644770 }, + { url = "https://files.pythonhosted.org/packages/cb/36/79a5e04073e58106aff442509a0c459151fa4f43202395db3eb8f77b78e9/grpcio-1.68.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:ddda1aa22495d8acd9dfbafff2866438d12faec4d024ebc2e656784d96328ad0", size = 6211743 }, + { url = "https://files.pythonhosted.org/packages/73/0f/2250f4a0de1a0bec0726c47a021cbf71af6105f512ecaf67703e2eb1ad2f/grpcio-1.68.1-cp311-cp311-win32.whl", hash = "sha256:b33bd114fa5a83f03ec6b7b262ef9f5cac549d4126f1dc702078767b10c46ed9", size = 3650734 }, + { url = "https://files.pythonhosted.org/packages/4b/29/061c93a35f498238dc35eb8fb039ce168aa99cac2f0f1ce0c8a0a4bdb274/grpcio-1.68.1-cp311-cp311-win_amd64.whl", hash = "sha256:7f20ebec257af55694d8f993e162ddf0d36bd82d4e57f74b31c67b3c6d63d8b2", size = 4400816 }, + { url = "https://files.pythonhosted.org/packages/f5/15/674a1468fef234fa996989509bbdfc0d695878cbb385b9271f5d690d5cd3/grpcio-1.68.1-cp312-cp312-linux_armv7l.whl", hash = "sha256:8829924fffb25386995a31998ccbbeaa7367223e647e0122043dfc485a87c666", size = 5148351 }, + { url = "https://files.pythonhosted.org/packages/62/f5/edce368682d6d0b3573b883b134df022a44b1c888ea416dd7d78d480ab24/grpcio-1.68.1-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:3aed6544e4d523cd6b3119b0916cef3d15ef2da51e088211e4d1eb91a6c7f4f1", size = 11127559 }, + { url = "https://files.pythonhosted.org/packages/ce/14/a6fde3114eafd9e4e345d1ebd0291c544d83b22f0554b1678a2968ae39e1/grpcio-1.68.1-cp312-cp312-manylinux_2_17_aarch64.whl", hash = "sha256:4efac5481c696d5cb124ff1c119a78bddbfdd13fc499e3bc0ca81e95fc573684", size = 5645221 }, + { url = "https://files.pythonhosted.org/packages/21/21/d1865bd6a22f9a26217e4e1b35f9105f7a0cdfb7a5fffe8be48e1a1afafc/grpcio-1.68.1-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6ab2d912ca39c51f46baf2a0d92aa265aa96b2443266fc50d234fa88bf877d8e", size = 6292270 }, + { url = "https://files.pythonhosted.org/packages/3a/f6/19798be6c3515a7b1fb9570198c91710472e2eb21f1900109a76834829e3/grpcio-1.68.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:95c87ce2a97434dffe7327a4071839ab8e8bffd0054cc74cbe971fba98aedd60", size = 5905978 }, + { url = "https://files.pythonhosted.org/packages/9b/43/c3670a657445cd55be1246f64dbc3a6a33cab0f0141c5836df2e04f794c8/grpcio-1.68.1-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:e4842e4872ae4ae0f5497bf60a0498fa778c192cc7a9e87877abd2814aca9475", size = 6630444 }, + { url = "https://files.pythonhosted.org/packages/80/69/fbbebccffd266bea4268b685f3e8e03613405caba69e93125dc783036465/grpcio-1.68.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:255b1635b0ed81e9f91da4fcc8d43b7ea5520090b9a9ad9340d147066d1d3613", size = 6200324 }, + { url = "https://files.pythonhosted.org/packages/65/5c/27a26c21916f94f0c1585111974a5d5a41d8420dcb42c2717ee514c97a97/grpcio-1.68.1-cp312-cp312-win32.whl", hash = "sha256:7dfc914cc31c906297b30463dde0b9be48e36939575eaf2a0a22a8096e69afe5", size = 3638381 }, + { url = "https://files.pythonhosted.org/packages/a3/ba/ba6b65ccc93c7df1031c6b41e45b79a5a37e46b81d816bb3ea68ba476d77/grpcio-1.68.1-cp312-cp312-win_amd64.whl", hash = "sha256:a0c8ddabef9c8f41617f213e527254c41e8b96ea9d387c632af878d05db9229c", size = 4389959 }, ] [[package]] name = "grpcio-health-checking" -version = "1.62.3" +version = "1.68.1" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "grpcio" }, { name = "protobuf" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/eb/9f/09df9b02fc8eafa3031d878c8a4674a0311293c8c6f1c942cdaeec204126/grpcio-health-checking-1.62.3.tar.gz", hash = "sha256:5074ba0ce8f0dcfe328408ec5c7551b2a835720ffd9b69dade7fa3e0dc1c7a93", size = 15640 } +sdist = { url = "https://files.pythonhosted.org/packages/76/96/75b4adad208b3394a0ad6704604a8604e54afdc10f3dd801b73a5d37f7ef/grpcio_health_checking-1.68.1.tar.gz", hash = "sha256:ea936cfa0c64a24afd8005873ea61b1acc83a941c00b56a6339c9b225c80a1a8", size = 16765 } wheels = [ - { url = "https://files.pythonhosted.org/packages/40/4c/ee3173906196b741ac6ba55a9788ba9ebf2cd05f91715a49b6c3bfbb9d73/grpcio_health_checking-1.62.3-py3-none-any.whl", hash = "sha256:f29da7dd144d73b4465fe48f011a91453e9ff6c8af0d449254cf80021cab3e0d", size = 18547 }, + { url = "https://files.pythonhosted.org/packages/fd/33/8679c26947e6f7ad866eb382e182305827db8e3594da37ed33904980f8b7/grpcio_health_checking-1.68.1-py3-none-any.whl", hash = "sha256:2457627bf1223c7e57efebdbe50970d8e20ce536adfb8866535b21754b216bf4", size = 18923 }, ] [[package]] name = "grpcio-status" -version = "1.62.3" +version = "1.68.1" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "googleapis-common-protos" }, { name = "grpcio" }, { name = "protobuf" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/7c/d7/013ef01c5a1c2fd0932c27c904934162f69f41ca0f28396d3ffe4d386123/grpcio-status-1.62.3.tar.gz", hash = "sha256:289bdd7b2459794a12cf95dc0cb727bd4a1742c37bd823f760236c937e53a485", size = 13063 } +sdist = { url = "https://files.pythonhosted.org/packages/57/db/db3911a9009f03b55e60cf13e3e29dfce423c0e501ec976794c7cbbbcd1b/grpcio_status-1.68.1.tar.gz", hash = "sha256:e1378d036c81a1610d7b4c7a146cd663dd13fcc915cf4d7d053929dba5bbb6e1", size = 13667 } wheels = [ - { url = "https://files.pythonhosted.org/packages/90/40/972271de05f9315c0d69f9f7ebbcadd83bc85322f538637d11bb8c67803d/grpcio_status-1.62.3-py3-none-any.whl", hash = "sha256:f9049b762ba8de6b1086789d8315846e094edac2c50beaf462338b301a8fd4b8", size = 14448 }, + { url = "https://files.pythonhosted.org/packages/86/1c/59dfc81f27f252bef2cd52c57157bf381cb3738185d3087ac4c9ff3376b0/grpcio_status-1.68.1-py3-none-any.whl", hash = "sha256:66f3d8847f665acfd56221333d66f7ad8927903d87242a482996bdb45e8d28fd", size = 14427 }, ] [[package]] name = "grpcio-tools" -version = "1.62.3" +version = "1.68.1" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "grpcio" }, { name = "protobuf" }, { name = "setuptools" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/54/fa/b69bd8040eafc09b88bb0ec0fea59e8aacd1a801e688af087cead213b0d0/grpcio-tools-1.62.3.tar.gz", hash = "sha256:7c7136015c3d62c3eef493efabaf9e3380e3e66d24ee8e94c01cb71377f57833", size = 4538520 } +sdist = { url = "https://files.pythonhosted.org/packages/2a/2f/d2fc30b79d892050a3c40ef8d17d602f4c6eced066d584621c7bbf195b0e/grpcio_tools-1.68.1.tar.gz", hash = "sha256:2413a17ad16c9c821b36e4a67fc64c37b9e4636ab1c3a07778018801378739ba", size = 5275384 } wheels = [ - { url = "https://files.pythonhosted.org/packages/ff/eb/eb0a3aa9480c3689d31fd2ad536df6a828e97a60f667c8a93d05bdf07150/grpcio_tools-1.62.3-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:2f968b049c2849540751ec2100ab05e8086c24bead769ca734fdab58698408c1", size = 5117556 }, - { url = "https://files.pythonhosted.org/packages/f3/fb/8be3dda485f7fab906bfa02db321c3ecef953a87cdb5f6572ca08b187bcb/grpcio_tools-1.62.3-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:0a8c0c4724ae9c2181b7dbc9b186df46e4f62cb18dc184e46d06c0ebeccf569e", size = 2719330 }, - { url = "https://files.pythonhosted.org/packages/63/de/6978f8d10066e240141cd63d1fbfc92818d96bb53427074f47a8eda921e1/grpcio_tools-1.62.3-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5782883a27d3fae8c425b29a9d3dcf5f47d992848a1b76970da3b5a28d424b26", size = 3070818 }, - { url = "https://files.pythonhosted.org/packages/74/34/bb8f816893fc73fd6d830e895e8638d65d13642bb7a434f9175c5ca7da11/grpcio_tools-1.62.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f3d812daffd0c2d2794756bd45a353f89e55dc8f91eb2fc840c51b9f6be62667", size = 2804993 }, - { url = "https://files.pythonhosted.org/packages/78/60/b2198d7db83293cdb9760fc083f077c73e4c182da06433b3b157a1567d06/grpcio_tools-1.62.3-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:b47d0dda1bdb0a0ba7a9a6de88e5a1ed61f07fad613964879954961e36d49193", size = 3684915 }, - { url = "https://files.pythonhosted.org/packages/61/20/56dbdc4ecb14d42a03cd164ff45e6e84572bbe61ee59c50c39f4d556a8d5/grpcio_tools-1.62.3-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:ca246dffeca0498be9b4e1ee169b62e64694b0f92e6d0be2573e65522f39eea9", size = 3297482 }, - { url = "https://files.pythonhosted.org/packages/4a/dc/e417a313c905744ce8cedf1e1edd81c41dc45ff400ae1c45080e18f26712/grpcio_tools-1.62.3-cp310-cp310-win32.whl", hash = "sha256:6a56d344b0bab30bf342a67e33d386b0b3c4e65868ffe93c341c51e1a8853ca5", size = 909793 }, - { url = "https://files.pythonhosted.org/packages/d9/69/75e7ebfd8d755d3e7be5c6d1aa6d13220f5bba3a98965e4b50c329046777/grpcio_tools-1.62.3-cp310-cp310-win_amd64.whl", hash = "sha256:710fecf6a171dcbfa263a0a3e7070e0df65ba73158d4c539cec50978f11dad5d", size = 1052459 }, - { url = "https://files.pythonhosted.org/packages/23/52/2dfe0a46b63f5ebcd976570aa5fc62f793d5a8b169e211c6a5aede72b7ae/grpcio_tools-1.62.3-cp311-cp311-macosx_10_10_universal2.whl", hash = "sha256:703f46e0012af83a36082b5f30341113474ed0d91e36640da713355cd0ea5d23", size = 5147623 }, - { url = "https://files.pythonhosted.org/packages/f0/2e/29fdc6c034e058482e054b4a3c2432f84ff2e2765c1342d4f0aa8a5c5b9a/grpcio_tools-1.62.3-cp311-cp311-manylinux_2_17_aarch64.whl", hash = "sha256:7cc83023acd8bc72cf74c2edbe85b52098501d5b74d8377bfa06f3e929803492", size = 2719538 }, - { url = "https://files.pythonhosted.org/packages/f9/60/abe5deba32d9ec2c76cdf1a2f34e404c50787074a2fee6169568986273f1/grpcio_tools-1.62.3-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7ff7d58a45b75df67d25f8f144936a3e44aabd91afec833ee06826bd02b7fbe7", size = 3070964 }, - { url = "https://files.pythonhosted.org/packages/bc/ad/e2b066684c75f8d9a48508cde080a3a36618064b9cadac16d019ca511444/grpcio_tools-1.62.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7f2483ea232bd72d98a6dc6d7aefd97e5bc80b15cd909b9e356d6f3e326b6e43", size = 2805003 }, - { url = "https://files.pythonhosted.org/packages/9c/3f/59bf7af786eae3f9d24ee05ce75318b87f541d0950190ecb5ffb776a1a58/grpcio_tools-1.62.3-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:962c84b4da0f3b14b3cdb10bc3837ebc5f136b67d919aea8d7bb3fd3df39528a", size = 3685154 }, - { url = "https://files.pythonhosted.org/packages/f1/79/4dd62478b91e27084c67b35a2316ce8a967bd8b6cb8d6ed6c86c3a0df7cb/grpcio_tools-1.62.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:8ad0473af5544f89fc5a1ece8676dd03bdf160fb3230f967e05d0f4bf89620e3", size = 3297942 }, - { url = "https://files.pythonhosted.org/packages/b8/cb/86449ecc58bea056b52c0b891f26977afc8c4464d88c738f9648da941a75/grpcio_tools-1.62.3-cp311-cp311-win32.whl", hash = "sha256:db3bc9fa39afc5e4e2767da4459df82b095ef0cab2f257707be06c44a1c2c3e5", size = 910231 }, - { url = "https://files.pythonhosted.org/packages/45/a4/9736215e3945c30ab6843280b0c6e1bff502910156ea2414cd77fbf1738c/grpcio_tools-1.62.3-cp311-cp311-win_amd64.whl", hash = "sha256:e0898d412a434e768a0c7e365acabe13ff1558b767e400936e26b5b6ed1ee51f", size = 1052496 }, - { url = "https://files.pythonhosted.org/packages/2a/a5/d6887eba415ce318ae5005e8dfac3fa74892400b54b6d37b79e8b4f14f5e/grpcio_tools-1.62.3-cp312-cp312-macosx_10_10_universal2.whl", hash = "sha256:d102b9b21c4e1e40af9a2ab3c6d41afba6bd29c0aa50ca013bf85c99cdc44ac5", size = 5147690 }, - { url = "https://files.pythonhosted.org/packages/8a/7c/3cde447a045e83ceb4b570af8afe67ffc86896a2fe7f59594dc8e5d0a645/grpcio_tools-1.62.3-cp312-cp312-manylinux_2_17_aarch64.whl", hash = "sha256:0a52cc9444df978438b8d2332c0ca99000521895229934a59f94f37ed896b133", size = 2720538 }, - { url = "https://files.pythonhosted.org/packages/88/07/f83f2750d44ac4f06c07c37395b9c1383ef5c994745f73c6bfaf767f0944/grpcio_tools-1.62.3-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:141d028bf5762d4a97f981c501da873589df3f7e02f4c1260e1921e565b376fa", size = 3071571 }, - { url = "https://files.pythonhosted.org/packages/37/74/40175897deb61e54aca716bc2e8919155b48f33aafec8043dda9592d8768/grpcio_tools-1.62.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:47a5c093ab256dec5714a7a345f8cc89315cb57c298b276fa244f37a0ba507f0", size = 2806207 }, - { url = "https://files.pythonhosted.org/packages/ec/ee/d8de915105a217cbcb9084d684abdc032030dcd887277f2ef167372287fe/grpcio_tools-1.62.3-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:f6831fdec2b853c9daa3358535c55eed3694325889aa714070528cf8f92d7d6d", size = 3685815 }, - { url = "https://files.pythonhosted.org/packages/fd/d9/4360a6c12be3d7521b0b8c39e5d3801d622fbb81cc2721dbd3eee31e28c8/grpcio_tools-1.62.3-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:e02d7c1a02e3814c94ba0cfe43d93e872c758bd8fd5c2797f894d0c49b4a1dfc", size = 3298378 }, - { url = "https://files.pythonhosted.org/packages/29/3b/7cdf4a9e5a3e0a35a528b48b111355cd14da601413a4f887aa99b6da468f/grpcio_tools-1.62.3-cp312-cp312-win32.whl", hash = "sha256:b881fd9505a84457e9f7e99362eeedd86497b659030cf57c6f0070df6d9c2b9b", size = 910416 }, - { url = "https://files.pythonhosted.org/packages/6c/66/dd3ec249e44c1cc15e902e783747819ed41ead1336fcba72bf841f72c6e9/grpcio_tools-1.62.3-cp312-cp312-win_amd64.whl", hash = "sha256:11c625eebefd1fd40a228fc8bae385e448c7e32a6ae134e43cf13bbc23f902b7", size = 1052856 }, + { url = "https://files.pythonhosted.org/packages/77/ea/7f40e041c12a26d41fbadaada47f6a3d0c4e04819d89ead62cf60a547414/grpcio_tools-1.68.1-cp310-cp310-linux_armv7l.whl", hash = "sha256:3a93ea324c5cbccdff55110777410d026dc1e69c3d47684ac97f57f7a77b9c70", size = 2342738 }, + { url = "https://files.pythonhosted.org/packages/51/36/33f04c77aa7c1df26031a32cb22e738ac58fd4708ff983cf3cc24b38705a/grpcio_tools-1.68.1-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:94cbfb9482cfd7bdb5f081b94fa137a16e4fe031daa57a2cd85d8cb4e18dce25", size = 5556562 }, + { url = "https://files.pythonhosted.org/packages/3d/27/c5c9f8cab6b0769d758e014dc6e0c0d87da25f9bb4843675050abd094f20/grpcio_tools-1.68.1-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:bbe7e1641859c858d0f4631f7f7c09e7302433f1aa037028d2419c1410945fac", size = 2306481 }, + { url = "https://files.pythonhosted.org/packages/9b/81/2e42ccd1cfb7a38aecd327942775cbd4b412f41d3d8c5e3c8eb33f093d55/grpcio_tools-1.68.1-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:55c0f91c4294c5807796ed26af42509f3d68497942a92d9ee9f43b08768d6c3c", size = 2679631 }, + { url = "https://files.pythonhosted.org/packages/4c/cf/c758ba07d4213bf706e90e4adde3dbf47f93d80cb8407fd449cc662f27aa/grpcio_tools-1.68.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:85adc798fd3b57ab3e998b5897c5daab6840211ac16cdf3ba99901cb9b90094a", size = 2425826 }, + { url = "https://files.pythonhosted.org/packages/fc/c6/a582490a64d9a7f626b83dbbe92eb7f10c2069b35d573ca9b2b622c994bd/grpcio_tools-1.68.1-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:f0bdccb00709bf6180a80a353a99fa844cc0bb2d450cdf7fc6ab22c988bb6b4c", size = 3289537 }, + { url = "https://files.pythonhosted.org/packages/44/53/6318e9ecb495ee1aa922ea66d500c4c2f4cad7218ed67de955cb61fffc38/grpcio_tools-1.68.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:2465e4d347b35dc0c007e074c79d5ded0a89c3aa26651e690f83593e0cc28af8", size = 2903792 }, + { url = "https://files.pythonhosted.org/packages/c1/e1/4e9992d8a3a36c7d1934535aa665b5d4cd2480de8e8f263a602132543df6/grpcio_tools-1.68.1-cp310-cp310-win32.whl", hash = "sha256:83c124a1776c1027da7d36584c8044cfed7a9f10e90f08dafde8d2a4cb822319", size = 946368 }, + { url = "https://files.pythonhosted.org/packages/ff/cc/b8c8fe96afec8fa07f76a9c93e147384f7b8803a5ae2cde06f9cf030fcb9/grpcio_tools-1.68.1-cp310-cp310-win_amd64.whl", hash = "sha256:283fd1359d619d42c3346f1d8f0a70636a036a421178803a1ab8083fa4228a38", size = 1097477 }, + { url = "https://files.pythonhosted.org/packages/2c/a4/427a28cd46f28dbb59cb99d65e3462a0241eb0830033d10eb038585107fa/grpcio_tools-1.68.1-cp311-cp311-linux_armv7l.whl", hash = "sha256:02f04de42834129eb54bb12469160ab631a0395d6a2b77975381c02b994086c3", size = 2342416 }, + { url = "https://files.pythonhosted.org/packages/2f/d0/837814621a1c6304b204e55a8638c79f2979b8d20fc9b471dc94e1fa0f4a/grpcio_tools-1.68.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:92b6aab37095879ef9ee428dd171740ff794f4c7a66bc1cc7280cd0051f8cd96", size = 5587916 }, + { url = "https://files.pythonhosted.org/packages/25/a9/3ef5757103bca0efe16f5cab7bb45aff9131c6af099fdfe72b7a25cb9eb1/grpcio_tools-1.68.1-cp311-cp311-manylinux_2_17_aarch64.whl", hash = "sha256:1f0ac6ac5e1e33b998511981b3ef36489501833413354f3597b97a3452d7d7ba", size = 2306366 }, + { url = "https://files.pythonhosted.org/packages/a6/eb/a0f09fba1b113bbf7b2a252e0f1a41373acee150f4245f4b41fdbab0b93d/grpcio_tools-1.68.1-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:28e0bca3a262af86557f30e30ddf2fadc2324ee05cd7352716924cc7f83541f1", size = 2679521 }, + { url = "https://files.pythonhosted.org/packages/ad/3f/875693dc5094ece347c009e4b720f6076b25d48381de957187ade66265ba/grpcio_tools-1.68.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:12239cf5ca6b7b4937103953cf35c49683d935e32e98596fe52dd35168aa86e6", size = 2425894 }, + { url = "https://files.pythonhosted.org/packages/ca/5f/bfe51ffe1e940dcaf06b98fdc00de558fc3299c5b8c521a825e283dde3f8/grpcio_tools-1.68.1-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:8e48d8884fcf6b182c73d0560a183404458e30a0f479918b88ca8fbd48b8b05f", size = 3288922 }, + { url = "https://files.pythonhosted.org/packages/a8/d2/b597da5421f206fb15fa779e55bb573dad0d0966ff844b230d1a29519304/grpcio_tools-1.68.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:e4e8059469847441855322da16fa2c0f9787b996c237a98778210e31188a8652", size = 2903909 }, + { url = "https://files.pythonhosted.org/packages/eb/60/ba6f428b7038107f263e59204dc06d204382b74caff88feb60c839284841/grpcio_tools-1.68.1-cp311-cp311-win32.whl", hash = "sha256:21815d54a83effbd2600d16382a7897298cfeffe578557fc9a47b642cc8ddafe", size = 946125 }, + { url = "https://files.pythonhosted.org/packages/34/ce/9b5dbf31480999ad815dc9fb923b4318ba7872d27159ed171e90bdd56c1b/grpcio_tools-1.68.1-cp311-cp311-win_amd64.whl", hash = "sha256:2114528723d9f12d3e24af3d433ec6f140deea1dd64d3bb1b4ebced217f1867c", size = 1097283 }, + { url = "https://files.pythonhosted.org/packages/f6/d0/45b59ef7f3b88cbf501558cccc5278ad7048e9ed367b947372a69c05aaf9/grpcio_tools-1.68.1-cp312-cp312-linux_armv7l.whl", hash = "sha256:d67a9d1ad22ff0d22715dba1d5f8f23ebd47cea84ccd20c90bf4690d988adc5b", size = 2342316 }, + { url = "https://files.pythonhosted.org/packages/56/2e/845b627d16833d0117c23c40f54f4d25845ec3457303928e3d4b879f10b9/grpcio_tools-1.68.1-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:c7f1e704ff73eb01afac51b63b74868a35aaa5d6f791fc63bd41af44a51aa232", size = 5585983 }, + { url = "https://files.pythonhosted.org/packages/8c/f1/1c5d01761a41614e56e1872c6727dfec24df6f97de6ea9f0762dc0aa3494/grpcio_tools-1.68.1-cp312-cp312-manylinux_2_17_aarch64.whl", hash = "sha256:e9f69988bd77db014795511c498e89a0db24bd47877e65921364114f88de3bee", size = 2306179 }, + { url = "https://files.pythonhosted.org/packages/8b/84/0a9b64167b6e41f7399bb27c2800124d7a3766682e656384434ceb12dba4/grpcio_tools-1.68.1-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8585ec7d11fcc2bb635b39605a4466ca9fa28dbae0c184fe58f456da72cb9031", size = 2679655 }, + { url = "https://files.pythonhosted.org/packages/98/a7/8a120bf17ed6462461a20f5dd10905e28b99caa5df2ad2c50b0ec3501d31/grpcio_tools-1.68.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c81d0be6c46fcbcd2cd126804060a95531cdf6d779436b2fbc68c8b4a7db2dc1", size = 2425466 }, + { url = "https://files.pythonhosted.org/packages/0b/5d/42e53a214024d85991eeaca3602ed991297c8e0cd361df7394f794dabfa1/grpcio_tools-1.68.1-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:6efdb02e75baf289935b5dad665f0e0f7c3311d86aae0cd2c709e2a8a34bb620", size = 3289402 }, + { url = "https://files.pythonhosted.org/packages/09/f6/2c4f713d140ef1b5085130d468c2a12476e2fc963e0212033ce879d88224/grpcio_tools-1.68.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:8ea367639e771e5a05f7320eb4ae2b27e09d2ec3baeae9819d1c590cc7eaaa08", size = 2903930 }, + { url = "https://files.pythonhosted.org/packages/9f/db/1256e1b75f78833cebd4d764902ba389c1437e9f208766f81d12fa64f473/grpcio_tools-1.68.1-cp312-cp312-win32.whl", hash = "sha256:a5b1021c9942bba7eca1555061e2d308f506198088a3a539fcb3633499c6635f", size = 946040 }, + { url = "https://files.pythonhosted.org/packages/e0/b2/f39c7c18ef4e7cca60a5aadff6e684209cb62e97d50ce66d0b9860090955/grpcio_tools-1.68.1-cp312-cp312-win_amd64.whl", hash = "sha256:315ad9c28940c95e85e57aeca309d298113175c2d5e8221501a05a51072f5477", size = 1096719 }, ] [[package]] @@ -2553,15 +2557,15 @@ wheels = [ [[package]] name = "httpcore" -version = "1.0.6" +version = "1.0.7" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "certifi" }, { name = "h11" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/b6/44/ed0fa6a17845fb033bd885c03e842f08c1b9406c86a2e60ac1ae1b9206a6/httpcore-1.0.6.tar.gz", hash = "sha256:73f6dbd6eb8c21bbf7ef8efad555481853f5f6acdeaff1edb0694289269ee17f", size = 85180 } +sdist = { url = "https://files.pythonhosted.org/packages/6a/41/d7d0a89eb493922c37d343b607bc1b5da7f5be7e383740b4753ad8943e90/httpcore-1.0.7.tar.gz", hash = "sha256:8551cb62a169ec7162ac7be8d4817d561f60e08eaa485234898414bb5a8a0b4c", size = 85196 } wheels = [ - { url = "https://files.pythonhosted.org/packages/06/89/b161908e2f51be56568184aeb4a880fd287178d176fd1c860d2217f41106/httpcore-1.0.6-py3-none-any.whl", hash = "sha256:27b59625743b85577a8c0e10e55b50b5368a4f2cfe8cc7bcfa9cf00829c2682f", size = 78011 }, + { url = "https://files.pythonhosted.org/packages/87/f5/72347bc88306acb359581ac4d52f23c0ef445b57157adedb9aee0cd689d2/httpcore-1.0.7-py3-none-any.whl", hash = "sha256:a3fff8f43dc260d5bd363d9f9cf1830fa3a458b332856f34282de498ed420edd", size = 78551 }, ] [[package]] @@ -2578,31 +2582,31 @@ wheels = [ [[package]] name = "httptools" -version = "0.6.1" +version = "0.6.4" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/67/1d/d77686502fced061b3ead1c35a2d70f6b281b5f723c4eff7a2277c04e4a2/httptools-0.6.1.tar.gz", hash = "sha256:c6e26c30455600b95d94b1b836085138e82f177351454ee841c148f93a9bad5a", size = 191228 } +sdist = { url = "https://files.pythonhosted.org/packages/a7/9a/ce5e1f7e131522e6d3426e8e7a490b3a01f39a6696602e1c4f33f9e94277/httptools-0.6.4.tar.gz", hash = "sha256:4e93eee4add6493b59a5c514da98c939b244fce4a0d8879cd3f466562f4b7d5c", size = 240639 } wheels = [ - { url = "https://files.pythonhosted.org/packages/a9/6a/80bce0216b63babf51cdc34814c3f0f10489e13ab89fb6bc91202736a8a2/httptools-0.6.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:d2f6c3c4cb1948d912538217838f6e9960bc4a521d7f9b323b3da579cd14532f", size = 149778 }, - { url = "https://files.pythonhosted.org/packages/bd/7d/4cd75356dfe0ed0b40ca6873646bf9ff7b5138236c72338dc569dc57d509/httptools-0.6.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:00d5d4b68a717765b1fabfd9ca755bd12bf44105eeb806c03d1962acd9b8e563", size = 77604 }, - { url = "https://files.pythonhosted.org/packages/4e/74/6348ce41fb5c1484f35184c172efb8854a288e6090bb54e2210598268369/httptools-0.6.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:639dc4f381a870c9ec860ce5c45921db50205a37cc3334e756269736ff0aac58", size = 346717 }, - { url = "https://files.pythonhosted.org/packages/65/e7/dd5ba95c84047118a363f0755ad78e639e0529be92424bb020496578aa3b/httptools-0.6.1-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e57997ac7fb7ee43140cc03664de5f268813a481dff6245e0075925adc6aa185", size = 341442 }, - { url = "https://files.pythonhosted.org/packages/d8/97/b37d596bc32be291477a8912bf9d1508d7e8553aa11a30cd871fd89cbae4/httptools-0.6.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:0ac5a0ae3d9f4fe004318d64b8a854edd85ab76cffbf7ef5e32920faef62f142", size = 354531 }, - { url = "https://files.pythonhosted.org/packages/99/c9/53ed7176583ec4b4364d941a08624288f2ae55b4ff58b392cdb68db1e1ed/httptools-0.6.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:3f30d3ce413088a98b9db71c60a6ada2001a08945cb42dd65a9a9fe228627658", size = 347754 }, - { url = "https://files.pythonhosted.org/packages/1e/fc/8a26c2adcd3f141e4729897633f03832b71ebea6f4c31cce67a92ded1961/httptools-0.6.1-cp310-cp310-win_amd64.whl", hash = "sha256:1ed99a373e327f0107cb513b61820102ee4f3675656a37a50083eda05dc9541b", size = 58165 }, - { url = "https://files.pythonhosted.org/packages/f5/d1/53283b96ed823d5e4d89ee9aa0f29df5a1bdf67f148e061549a595d534e4/httptools-0.6.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:7a7ea483c1a4485c71cb5f38be9db078f8b0e8b4c4dc0210f531cdd2ddac1ef1", size = 145855 }, - { url = "https://files.pythonhosted.org/packages/80/dd/cebc9d4b1d4b70e9f3d40d1db0829a28d57ca139d0b04197713816a11996/httptools-0.6.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:85ed077c995e942b6f1b07583e4eb0a8d324d418954fc6af913d36db7c05a5a0", size = 75604 }, - { url = "https://files.pythonhosted.org/packages/76/7a/45c5a9a2e9d21f7381866eb7b6ead5a84d8fe7e54e35208eeb18320a29b4/httptools-0.6.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8b0bb634338334385351a1600a73e558ce619af390c2b38386206ac6a27fecfc", size = 324784 }, - { url = "https://files.pythonhosted.org/packages/59/23/047a89e66045232fb82c50ae57699e40f70e073ae5ccd53f54e532fbd2a2/httptools-0.6.1-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7d9ceb2c957320def533671fc9c715a80c47025139c8d1f3797477decbc6edd2", size = 318547 }, - { url = "https://files.pythonhosted.org/packages/82/f5/50708abc7965d7d93c0ee14a148ccc6d078a508f47fe9357c79d5360f252/httptools-0.6.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:4f0f8271c0a4db459f9dc807acd0eadd4839934a4b9b892f6f160e94da309837", size = 330211 }, - { url = "https://files.pythonhosted.org/packages/e3/1e/9823ca7aab323c0e0e9dd82ce835a6e93b69f69aedffbc94d31e327f4283/httptools-0.6.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:6a4f5ccead6d18ec072ac0b84420e95d27c1cdf5c9f1bc8fbd8daf86bd94f43d", size = 322174 }, - { url = "https://files.pythonhosted.org/packages/14/e4/20d28dfe7f5b5603b6b04c33bb88662ad749de51f0c539a561f235f42666/httptools-0.6.1-cp311-cp311-win_amd64.whl", hash = "sha256:5cceac09f164bcba55c0500a18fe3c47df29b62353198e4f37bbcc5d591172c3", size = 55434 }, - { url = "https://files.pythonhosted.org/packages/60/13/b62e086b650752adf9094b7e62dab97f4cb7701005664544494b7956a51e/httptools-0.6.1-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:75c8022dca7935cba14741a42744eee13ba05db00b27a4b940f0d646bd4d56d0", size = 146354 }, - { url = "https://files.pythonhosted.org/packages/f8/5d/9ad32b79b6c24524087e78aa3f0a2dfcf58c11c90e090e4593b35def8a86/httptools-0.6.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:48ed8129cd9a0d62cf4d1575fcf90fb37e3ff7d5654d3a5814eb3d55f36478c2", size = 75785 }, - { url = "https://files.pythonhosted.org/packages/d0/a4/b503851c40f20bcbd453db24ed35d961f62abdae0dccc8f672cd5d350d87/httptools-0.6.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6f58e335a1402fb5a650e271e8c2d03cfa7cea46ae124649346d17bd30d59c90", size = 345396 }, - { url = "https://files.pythonhosted.org/packages/a2/9a/aa406864f3108e06f7320425a528ff8267124dead1fd72a3e9da2067f893/httptools-0.6.1-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:93ad80d7176aa5788902f207a4e79885f0576134695dfb0fefc15b7a4648d503", size = 344741 }, - { url = "https://files.pythonhosted.org/packages/cf/3a/3fd8dfb987c4247651baf2ac6f28e8e9f889d484ca1a41a9ad0f04dfe300/httptools-0.6.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:9bb68d3a085c2174c2477eb3ffe84ae9fb4fde8792edb7bcd09a1d8467e30a84", size = 345096 }, - { url = "https://files.pythonhosted.org/packages/80/01/379f6466d8e2edb861c1f44ccac255ed1f8a0d4c5c666a1ceb34caad7555/httptools-0.6.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:b512aa728bc02354e5ac086ce76c3ce635b62f5fbc32ab7082b5e582d27867bb", size = 343535 }, - { url = "https://files.pythonhosted.org/packages/d3/97/60860e9ee87a7d4712b98f7e1411730520053b9d69e9e42b0b9751809c17/httptools-0.6.1-cp312-cp312-win_amd64.whl", hash = "sha256:97662ce7fb196c785344d00d638fc9ad69e18ee4bfb4000b35a52efe5adcc949", size = 55660 }, + { url = "https://files.pythonhosted.org/packages/3b/6f/972f8eb0ea7d98a1c6be436e2142d51ad2a64ee18e02b0e7ff1f62171ab1/httptools-0.6.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:3c73ce323711a6ffb0d247dcd5a550b8babf0f757e86a52558fe5b86d6fefcc0", size = 198780 }, + { url = "https://files.pythonhosted.org/packages/6a/b0/17c672b4bc5c7ba7f201eada4e96c71d0a59fbc185e60e42580093a86f21/httptools-0.6.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:345c288418f0944a6fe67be8e6afa9262b18c7626c3ef3c28adc5eabc06a68da", size = 103297 }, + { url = "https://files.pythonhosted.org/packages/92/5e/b4a826fe91971a0b68e8c2bd4e7db3e7519882f5a8ccdb1194be2b3ab98f/httptools-0.6.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:deee0e3343f98ee8047e9f4c5bc7cedbf69f5734454a94c38ee829fb2d5fa3c1", size = 443130 }, + { url = "https://files.pythonhosted.org/packages/b0/51/ce61e531e40289a681a463e1258fa1e05e0be54540e40d91d065a264cd8f/httptools-0.6.4-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ca80b7485c76f768a3bc83ea58373f8db7b015551117375e4918e2aa77ea9b50", size = 442148 }, + { url = "https://files.pythonhosted.org/packages/ea/9e/270b7d767849b0c96f275c695d27ca76c30671f8eb8cc1bab6ced5c5e1d0/httptools-0.6.4-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:90d96a385fa941283ebd231464045187a31ad932ebfa541be8edf5b3c2328959", size = 415949 }, + { url = "https://files.pythonhosted.org/packages/81/86/ced96e3179c48c6f656354e106934e65c8963d48b69be78f355797f0e1b3/httptools-0.6.4-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:59e724f8b332319e2875efd360e61ac07f33b492889284a3e05e6d13746876f4", size = 417591 }, + { url = "https://files.pythonhosted.org/packages/75/73/187a3f620ed3175364ddb56847d7a608a6fc42d551e133197098c0143eca/httptools-0.6.4-cp310-cp310-win_amd64.whl", hash = "sha256:c26f313951f6e26147833fc923f78f95604bbec812a43e5ee37f26dc9e5a686c", size = 88344 }, + { url = "https://files.pythonhosted.org/packages/7b/26/bb526d4d14c2774fe07113ca1db7255737ffbb119315839af2065abfdac3/httptools-0.6.4-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:f47f8ed67cc0ff862b84a1189831d1d33c963fb3ce1ee0c65d3b0cbe7b711069", size = 199029 }, + { url = "https://files.pythonhosted.org/packages/a6/17/3e0d3e9b901c732987a45f4f94d4e2c62b89a041d93db89eafb262afd8d5/httptools-0.6.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:0614154d5454c21b6410fdf5262b4a3ddb0f53f1e1721cfd59d55f32138c578a", size = 103492 }, + { url = "https://files.pythonhosted.org/packages/b7/24/0fe235d7b69c42423c7698d086d4db96475f9b50b6ad26a718ef27a0bce6/httptools-0.6.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f8787367fbdfccae38e35abf7641dafc5310310a5987b689f4c32cc8cc3ee975", size = 462891 }, + { url = "https://files.pythonhosted.org/packages/b1/2f/205d1f2a190b72da6ffb5f41a3736c26d6fa7871101212b15e9b5cd8f61d/httptools-0.6.4-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:40b0f7fe4fd38e6a507bdb751db0379df1e99120c65fbdc8ee6c1d044897a636", size = 459788 }, + { url = "https://files.pythonhosted.org/packages/6e/4c/d09ce0eff09057a206a74575ae8f1e1e2f0364d20e2442224f9e6612c8b9/httptools-0.6.4-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:40a5ec98d3f49904b9fe36827dcf1aadfef3b89e2bd05b0e35e94f97c2b14721", size = 433214 }, + { url = "https://files.pythonhosted.org/packages/3e/d2/84c9e23edbccc4a4c6f96a1b8d99dfd2350289e94f00e9ccc7aadde26fb5/httptools-0.6.4-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:dacdd3d10ea1b4ca9df97a0a303cbacafc04b5cd375fa98732678151643d4988", size = 434120 }, + { url = "https://files.pythonhosted.org/packages/d0/46/4d8e7ba9581416de1c425b8264e2cadd201eb709ec1584c381f3e98f51c1/httptools-0.6.4-cp311-cp311-win_amd64.whl", hash = "sha256:288cd628406cc53f9a541cfaf06041b4c71d751856bab45e3702191f931ccd17", size = 88565 }, + { url = "https://files.pythonhosted.org/packages/bb/0e/d0b71465c66b9185f90a091ab36389a7352985fe857e352801c39d6127c8/httptools-0.6.4-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:df017d6c780287d5c80601dafa31f17bddb170232d85c066604d8558683711a2", size = 200683 }, + { url = "https://files.pythonhosted.org/packages/e2/b8/412a9bb28d0a8988de3296e01efa0bd62068b33856cdda47fe1b5e890954/httptools-0.6.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:85071a1e8c2d051b507161f6c3e26155b5c790e4e28d7f236422dbacc2a9cc44", size = 104337 }, + { url = "https://files.pythonhosted.org/packages/9b/01/6fb20be3196ffdc8eeec4e653bc2a275eca7f36634c86302242c4fbb2760/httptools-0.6.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:69422b7f458c5af875922cdb5bd586cc1f1033295aa9ff63ee196a87519ac8e1", size = 508796 }, + { url = "https://files.pythonhosted.org/packages/f7/d8/b644c44acc1368938317d76ac991c9bba1166311880bcc0ac297cb9d6bd7/httptools-0.6.4-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:16e603a3bff50db08cd578d54f07032ca1631450ceb972c2f834c2b860c28ea2", size = 510837 }, + { url = "https://files.pythonhosted.org/packages/52/d8/254d16a31d543073a0e57f1c329ca7378d8924e7e292eda72d0064987486/httptools-0.6.4-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:ec4f178901fa1834d4a060320d2f3abc5c9e39766953d038f1458cb885f47e81", size = 485289 }, + { url = "https://files.pythonhosted.org/packages/5f/3c/4aee161b4b7a971660b8be71a92c24d6c64372c1ab3ae7f366b3680df20f/httptools-0.6.4-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:f9eb89ecf8b290f2e293325c646a211ff1c2493222798bb80a530c5e7502494f", size = 489779 }, + { url = "https://files.pythonhosted.org/packages/12/b7/5cae71a8868e555f3f67a50ee7f673ce36eac970f029c0c5e9d584352961/httptools-0.6.4-cp312-cp312-win_amd64.whl", hash = "sha256:db78cb9ca56b59b016e64b6031eda5653be0589dba2b1b43453f6e8b405a0970", size = 88634 }, ] [[package]] @@ -2637,7 +2641,7 @@ wheels = [ [[package]] name = "huggingface-hub" -version = "0.25.2" +version = "0.26.5" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "filelock" }, @@ -2648,15 +2652,14 @@ dependencies = [ { name = "tqdm" }, { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/df/fd/5f81bae67096c5ab50d29a0230b8374f0245916cca192f8ee2fada51f4f6/huggingface_hub-0.25.2.tar.gz", hash = "sha256:a1014ea111a5f40ccd23f7f7ba8ac46e20fa3b658ced1f86a00c75c06ec6423c", size = 365806 } +sdist = { url = "https://files.pythonhosted.org/packages/51/21/2be5c66f29e798650a3e66bb350dee63bd9ab02cfc3ed7197cf4a905203e/huggingface_hub-0.26.5.tar.gz", hash = "sha256:1008bd18f60bfb65e8dbc0a97249beeeaa8c99d3c2fa649354df9fa5a13ed83b", size = 375951 } wheels = [ - { url = "https://files.pythonhosted.org/packages/64/09/a535946bf2dc88e61341f39dc507530411bb3ea4eac493e5ec833e8f35bd/huggingface_hub-0.25.2-py3-none-any.whl", hash = "sha256:1897caf88ce7f97fe0110603d8f66ac264e3ba6accdf30cd66cc0fed5282ad25", size = 436575 }, + { url = "https://files.pythonhosted.org/packages/44/5a/dc6af87c61f89b23439eb95521e4e99862636cfd538ae12fd36be5483e5f/huggingface_hub-0.26.5-py3-none-any.whl", hash = "sha256:fb7386090bbe892072e64b85f7c4479fd2d65eea5f2543327c970d5169e83924", size = 447766 }, ] [package.optional-dependencies] inference = [ { name = "aiohttp" }, - { name = "minijinja" }, ] [[package]] @@ -2691,11 +2694,11 @@ wheels = [ [[package]] name = "identify" -version = "2.6.1" +version = "2.6.3" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/29/bb/25024dbcc93516c492b75919e76f389bac754a3e4248682fba32b250c880/identify-2.6.1.tar.gz", hash = "sha256:91478c5fb7c3aac5ff7bf9b4344f803843dc586832d5f110d672b19aa1984c98", size = 99097 } +sdist = { url = "https://files.pythonhosted.org/packages/1a/5f/05f0d167be94585d502b4adf8c7af31f1dc0b1c7e14f9938a88fdbbcf4a7/identify-2.6.3.tar.gz", hash = "sha256:62f5dae9b5fef52c84cc188514e9ea4f3f636b1d8799ab5ebc475471f9e47a02", size = 99179 } wheels = [ - { url = "https://files.pythonhosted.org/packages/7d/0c/4ef72754c050979fdcc06c744715ae70ea37e734816bb6514f79df77a42f/identify-2.6.1-py2.py3-none-any.whl", hash = "sha256:53863bcac7caf8d2ed85bd20312ea5dcfc22226800f6d6881f232d861db5a8f0", size = 98972 }, + { url = "https://files.pythonhosted.org/packages/c9/f5/09644a3ad803fae9eca8efa17e1f2aef380c7f0b02f7ec4e8d446e51d64a/identify-2.6.3-py2.py3-none-any.whl", hash = "sha256:9edba65473324c2ea9684b1f944fe3191db3345e50b6d04571d10ed164f8d7bd", size = 99049 }, ] [[package]] @@ -2755,14 +2758,14 @@ wheels = [ [[package]] name = "importlib-metadata" -version = "8.4.0" +version = "8.5.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "zipp" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/c0/bd/fa8ce65b0a7d4b6d143ec23b0f5fd3f7ab80121078c465bc02baeaab22dc/importlib_metadata-8.4.0.tar.gz", hash = "sha256:9a547d3bc3608b025f93d403fdd1aae741c24fbb8314df4b155675742ce303c5", size = 54320 } +sdist = { url = "https://files.pythonhosted.org/packages/cd/12/33e59336dca5be0c398a7482335911a33aa0e20776128f038019f1a95f1b/importlib_metadata-8.5.0.tar.gz", hash = "sha256:71522656f0abace1d072b9e5481a48f07c138e00f079c38c8f883823f9c26bd7", size = 55304 } wheels = [ - { url = "https://files.pythonhosted.org/packages/c0/14/362d31bf1076b21e1bcdcb0dc61944822ff263937b804a79231df2774d28/importlib_metadata-8.4.0-py3-none-any.whl", hash = "sha256:66f342cc6ac9818fc6ff340576acd24d65ba0b3efabb2b4ac08b598965a4a2f1", size = 26269 }, + { url = "https://files.pythonhosted.org/packages/a0/d9/a1e041c5e7caa9a05c925f4bdbdfb7f006d1f74996af53467bc394c97be7/importlib_metadata-8.5.0-py3-none-any.whl", hash = "sha256:45e54197d28b7a7f1559e60b95e7c567032b602131fbd588f1497f47880aa68b", size = 26514 }, ] [[package]] @@ -2794,7 +2797,7 @@ wheels = [ [[package]] name = "instructor" -version = "1.3.3" +version = "1.3.4" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "aiohttp" }, @@ -2807,9 +2810,9 @@ dependencies = [ { name = "tenacity" }, { name = "typer" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/3d/d1/b8c0d24466d653d371ee13de63644db607b32372e799e354bc4e76941e79/instructor-1.3.3.tar.gz", hash = "sha256:e27bf3c1187b0b2130ea38ecde7c2b4f571d6a5ce1397fb15c27490988b45441", size = 40020 } +sdist = { url = "https://files.pythonhosted.org/packages/18/0b/4f1198a348db956fcad7618f0c74e05911b4d102f783ad7525d4d538f0b9/instructor-1.3.4.tar.gz", hash = "sha256:20242fdb42ed4a691d067db9bf67d317dfa060ee6419751bbe30fdd3c48e7d23", size = 42540 } wheels = [ - { url = "https://files.pythonhosted.org/packages/44/57/10ec9e31dd67e578d1a1f6ed1cf49c00dbbf9b3d06cd233fd7b35d94872f/instructor-1.3.3-py3-none-any.whl", hash = "sha256:94b114b39a1181fa348d162e6e4ff5c4d985324736020c0233fed5d4db444dbd", size = 50204 }, + { url = "https://files.pythonhosted.org/packages/7a/ed/a250a6c98dcfd4a0be0da72048a0d5931ee072ff5486b65ac676c0a142f5/instructor-1.3.4-py3-none-any.whl", hash = "sha256:ca4f36e69a1b147a48417fc4ffbfd63ac01957d4e1f3bb24460b09a024a5f195", size = 53108 }, ] [[package]] @@ -2838,7 +2841,7 @@ wheels = [ [[package]] name = "ipython" -version = "8.28.0" +version = "8.30.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "colorama", marker = "sys_platform == 'win32'" }, @@ -2853,9 +2856,9 @@ dependencies = [ { name = "traitlets" }, { name = "typing-extensions", marker = "python_full_version < '3.12'" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/f7/21/48db7d9dd622b9692575004c7c98f85f5629428f58596c59606d36c51b58/ipython-8.28.0.tar.gz", hash = "sha256:0d0d15ca1e01faeb868ef56bc7ee5a0de5bd66885735682e8a322ae289a13d1a", size = 5495762 } +sdist = { url = "https://files.pythonhosted.org/packages/d8/8b/710af065ab8ed05649afa5bd1e07401637c9ec9fb7cfda9eac7e91e9fbd4/ipython-8.30.0.tar.gz", hash = "sha256:cb0a405a306d2995a5cbb9901894d240784a9f341394c6ba3f4fe8c6eb89ff6e", size = 5592205 } wheels = [ - { url = "https://files.pythonhosted.org/packages/f4/3a/5d8680279ada9571de8469220069d27024ee47624af534e537c9ff49a450/ipython-8.28.0-py3-none-any.whl", hash = "sha256:530ef1e7bb693724d3cdc37287c80b07ad9b25986c007a53aa1857272dac3f35", size = 819456 }, + { url = "https://files.pythonhosted.org/packages/1d/f3/1332ba2f682b07b304ad34cad2f003adcfeb349486103f4b632335074a7c/ipython-8.30.0-py3-none-any.whl", hash = "sha256:85ec56a7e20f6c38fce7727dcca699ae4ffc85985aa7b23635a8008f918ae321", size = 820765 }, ] [[package]] @@ -2872,14 +2875,14 @@ wheels = [ [[package]] name = "jedi" -version = "0.19.1" +version = "0.19.2" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "parso" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/d6/99/99b493cec4bf43176b678de30f81ed003fd6a647a301b9c927280c600f0a/jedi-0.19.1.tar.gz", hash = "sha256:cf0496f3651bc65d7174ac1b7d043eff454892c708a87d1b683e57b569927ffd", size = 1227821 } +sdist = { url = "https://files.pythonhosted.org/packages/72/3a/79a912fbd4d8dd6fbb02bf69afd3bb72cf0c729bb3063c6f4498603db17a/jedi-0.19.2.tar.gz", hash = "sha256:4770dc3de41bde3966b02eb84fbcf557fb33cce26ad23da12c742fb50ecb11f0", size = 1231287 } wheels = [ - { url = "https://files.pythonhosted.org/packages/20/9f/bc63f0f0737ad7a60800bfd472a4836661adae21f9c2535f3957b1e54ceb/jedi-0.19.1-py2.py3-none-any.whl", hash = "sha256:e983c654fe5c02867aef4cdfce5a2fbb4a50adc0af145f70504238f18ef5e7e0", size = 1569361 }, + { url = "https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl", hash = "sha256:a8ef22bde8490f57fe5c7681a3c83cb58874daf72b4784de3cce5b6ef6edb5b9", size = 1572278 }, ] [[package]] @@ -3031,11 +3034,11 @@ wheels = [ [[package]] name = "jsonpickle" -version = "3.3.0" +version = "4.0.0" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/7b/c3/7b43eb963bfb3fa95385e677bb9d027c56d65d395d9f4bd52833affd1a4f/jsonpickle-3.3.0.tar.gz", hash = "sha256:ab467e601e5b1a1cd76f1819d014795165da071744ef30bf3786e9bc549de25a", size = 329715 } +sdist = { url = "https://files.pythonhosted.org/packages/04/b7/9fb3cb5915f7363ceea7eb433866a69e8c01b43201daf368afd5c2ff722b/jsonpickle-4.0.0.tar.gz", hash = "sha256:fc670852b204d77601b08f8f9333149ac37ab6d3fe4e6ed3b578427291f63736", size = 314587 } wheels = [ - { url = "https://files.pythonhosted.org/packages/71/1f/224e27180204282c1ea378b86944585616c1978544b9f5277cf907fdb26c/jsonpickle-3.3.0-py3-none-any.whl", hash = "sha256:287c12143f35571ab00e224fa323aa4b090d5a7f086f5f494d7ee9c7eb1a380a", size = 42370 }, + { url = "https://files.pythonhosted.org/packages/a1/64/815460f86d94c9e1431800a75061719824c6fef14d88a6117eba3126cd5b/jsonpickle-4.0.0-py3-none-any.whl", hash = "sha256:53730b9e094bc41f540bfdd25eaf6e6cf43811590e9e1477abcec44b866ddcd9", size = 46157 }, ] [[package]] @@ -3151,27 +3154,23 @@ wheels = [ [[package]] name = "lancedb" -version = "0.14.0" +version = "0.17.0" source = { registry = "https://pypi.org/simple" } dependencies = [ - { name = "attrs" }, - { name = "cachetools" }, { name = "deprecation" }, { name = "overrides" }, { name = "packaging" }, { name = "pydantic" }, { name = "pylance" }, - { name = "requests" }, - { name = "retry" }, { name = "tqdm" }, ] wheels = [ - { url = "https://files.pythonhosted.org/packages/c8/b0/b0257ef87ccc19ddd29c5827f133c10e155af5944ce8708a2f46488741eb/lancedb-0.14.0-cp38-abi3-macosx_10_15_x86_64.whl", hash = "sha256:6b970e6f503464918789d76c43d70d93d85ef82dc6dbec9685483c60c36ba491", size = 24110162 }, - { url = "https://files.pythonhosted.org/packages/bb/3e/848197dc9eef74ae8015d1a9ed02435740cf467a98423e967dc89cb6315a/lancedb-0.14.0-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:e28932882a0f893a295b391b05b0af9d95918e2cd10d6d58991e3282c06c0bd3", size = 22276153 }, - { url = "https://files.pythonhosted.org/packages/9a/07/d56eab12e3a6b5764dc4b3001cf94720eacb946a1f62804034ee1ca7d878/lancedb-0.14.0-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:faef7fe76af9373656660e2e652e3d330735e84680649f0d74c558a0460f0d55", size = 27532046 }, - { url = "https://files.pythonhosted.org/packages/6c/ed/3eb2934225f125307a5c6ef7f820cff7152a68c029d8878713ba7bdb9ce9/lancedb-0.14.0-cp38-abi3-manylinux_2_24_aarch64.whl", hash = "sha256:777e2d483f13814a2a5624c6824936f400aeab52b961853f1352cc21564f7d6f", size = 26046469 }, - { url = "https://files.pythonhosted.org/packages/26/97/33e7c5f89711a2c62090fc74590827085638dd2f27dc150f4710542990c1/lancedb-0.14.0-cp38-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:31fec6c05edf657542d91c396b895b2ba02f0e6114188ea9bb03a3112907a71e", size = 27004229 }, - { url = "https://files.pythonhosted.org/packages/a9/65/2e4a5cdb897b61497c5da23057f126594a84e6895277429c92db2fb0c287/lancedb-0.14.0-cp38-abi3-win_amd64.whl", hash = "sha256:a4e758156554e2a2a493ad569278d8f938e209f38f215924ed1c5f368d1f402e", size = 24921552 }, + { url = "https://files.pythonhosted.org/packages/fb/ed/58e04eaf815acd6b75ad7db8a6a61d01eccc5cb2191d431c0d5f234cf20a/lancedb-0.17.0-cp39-abi3-macosx_10_15_x86_64.whl", hash = "sha256:40aac1583edda390e51189c4e95bdfd4768d23705234e12a7b81957f1143df42", size = 26393821 }, + { url = "https://files.pythonhosted.org/packages/87/a9/14807f23f0fb415453626ba4ea7431ab62f0906bd0ef1df24680fd5ae2df/lancedb-0.17.0-cp39-abi3-macosx_11_0_arm64.whl", hash = "sha256:895bed499dae61cac1dbfc40ad71a566e06ab5c8d538aa57873a0cba859f8a7a", size = 24846600 }, + { url = "https://files.pythonhosted.org/packages/a5/46/4a5af607b9904d76344b56e62d6799ce7ae8f6c835bf05d1678313ca877f/lancedb-0.17.0-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3ea688d0f63796ee912a7cfe6667f36661e36756fa8340b94dd54d666a7db63f", size = 30443392 }, + { url = "https://files.pythonhosted.org/packages/eb/03/4eb452f02a740ab1cfa334570384f10810890b2670ef6277af7abcb0039d/lancedb-0.17.0-cp39-abi3-manylinux_2_24_aarch64.whl", hash = "sha256:f51a61950ead30a605b5653a81e8362e4aac6fec32705b88b9c9319e9308b2bb", size = 28242872 }, + { url = "https://files.pythonhosted.org/packages/b2/11/c48248f984dfd8dfec0bb074465ca697cf64b6b71b0aa199c15ad0153597/lancedb-0.17.0-cp39-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:07e6f10b3fcbeb6c737996e5ebd68d04c3ca2656a9b8b970111ecf368245e7f6", size = 29925342 }, + { url = "https://files.pythonhosted.org/packages/34/b9/a3d4bfdaefbc9098ef18bff2cf403c6060f70894c5022983464f9c3db367/lancedb-0.17.0-cp39-abi3-win_amd64.whl", hash = "sha256:9d7e82f83f430d906c285d3303729258b21b1cc8da634c9f7017e354bcb7318a", size = 27511050 }, ] [[package]] @@ -3274,11 +3273,12 @@ wheels = [ [[package]] name = "langchain-community" -version = "0.3.3" +version = "0.3.10" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "aiohttp" }, { name = "dataclasses-json" }, + { name = "httpx-sse" }, { name = "langchain" }, { name = "langchain-core" }, { name = "langsmith" }, @@ -3289,14 +3289,14 @@ dependencies = [ { name = "sqlalchemy" }, { name = "tenacity" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/14/f6/6cc1e552268f8426dc7830911cbdc8d1f262392be804dd36af598378b59a/langchain_community-0.3.3.tar.gz", hash = "sha256:bfb3f2b219aed21087e0ecb7d2ebd1c81401c02b92239e11645c822d5be63f80", size = 1623395 } +sdist = { url = "https://files.pythonhosted.org/packages/ba/6b/53f3d7e394e191cc69b11c8c5500e34ed816072e2c31a3c8f01e46b907f6/langchain_community-0.3.10.tar.gz", hash = "sha256:f503e90cbb44ddb14afb141552a93fd9fbd0b216407315a6608f901861a938f9", size = 1672427 } wheels = [ - { url = "https://files.pythonhosted.org/packages/6f/f2/230de86ff6a4de7f6a784f52600bdac3f8d6c18123398e4c073f8d8ceaf8/langchain_community-0.3.3-py3-none-any.whl", hash = "sha256:319cfc2f923a066c91fbb8e02decd7814018af952b6b98298b8ac9d30ea1da56", size = 2383695 }, + { url = "https://files.pythonhosted.org/packages/ee/d2/2a7668a21f8f58f5c29f06452f1d5d5ccd41e06660244268a115902097a2/langchain_community-0.3.10-py3-none-any.whl", hash = "sha256:f718de973f60c6d0f10c71321e461cf41251cc74543f064b7b2ee7ae06b9a43f", size = 2446511 }, ] [[package]] name = "langchain-core" -version = "0.3.23" +version = "0.3.24" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "jsonpatch" }, @@ -3307,9 +3307,9 @@ dependencies = [ { name = "tenacity" }, { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/e4/a1/3f3772789860acf2597993b639e68b6968136736bec67598ddeb39e61585/langchain_core-0.3.23.tar.gz", hash = "sha256:f9e175e3b82063cc3b160c2ca2b155832e1c6f915312e1204828f97d4aabf6e1", size = 329645 } +sdist = { url = "https://files.pythonhosted.org/packages/2f/fc/8ccbaea3d6efa3aca973188f4d765024ecad618ab9eddd22bcc97761ada2/langchain_core-0.3.24.tar.gz", hash = "sha256:460851e8145327f70b70aad7dce2cdbd285e144d14af82b677256b941fc99656", size = 329650 } wheels = [ - { url = "https://files.pythonhosted.org/packages/bf/08/2c727c0c25b9b67d59a1ca94642571e5f83493d695fd088d5bc2eebc9f57/langchain_core-0.3.23-py3-none-any.whl", hash = "sha256:550c0b996990830fa6515a71a1192a8a0343367999afc36d4ede14222941e420", size = 410623 }, + { url = "https://files.pythonhosted.org/packages/a8/eb/b5681dfa46a8f994d2b8d23610d8545ff80c6ad3fe6cabf76cea3256a8ea/langchain_core-0.3.24-py3-none-any.whl", hash = "sha256:97192552ef882a3dd6ae3b870a180a743801d0137a1159173f51ac555eeb7eec", size = 410643 }, ] [[package]] @@ -3327,15 +3327,15 @@ wheels = [ [[package]] name = "langchain-experimental" -version = "0.3.2" +version = "0.3.3" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "langchain-community" }, { name = "langchain-core" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/bf/41/84d3eac564261aaab45bc02bdc43b5e49242439c6f2844a24b81404a17cd/langchain_experimental-0.3.2.tar.gz", hash = "sha256:d41cc28c46f58616d18a1230595929f80a58d1982c4053dc3afe7f1c03f22426", size = 139583 } +sdist = { url = "https://files.pythonhosted.org/packages/8f/ad/a08e4a44d8cebb4406687764e16627813607155ee87cc6d05d3defeb0d9c/langchain_experimental-0.3.3.tar.gz", hash = "sha256:6bbcdcd084581432ef4b5d732294a59d75a858ede1714b50a5b79bcfe31fa306", size = 140300 } wheels = [ - { url = "https://files.pythonhosted.org/packages/63/f6/d80592aa8d335af734054f5cfe130ecd38fdfb9c4f90ba0007f0419f2fce/langchain_experimental-0.3.2-py3-none-any.whl", hash = "sha256:b6a26f2a05e056a27ad30535ed306a6b9d8cc2e3c0326d15030d11b6e7505dbb", size = 208126 }, + { url = "https://files.pythonhosted.org/packages/56/fb/50a7181c318495c5481757d2606c22c6b30a4c50d75236898bb1a5437069/langchain_experimental-0.3.3-py3-none-any.whl", hash = "sha256:da01aafc162631475f306ca368ecae74d5becd93b8039bddb6315e755e274580", size = 208998 }, ] [[package]] @@ -3517,14 +3517,14 @@ wheels = [ [[package]] name = "langchain-text-splitters" -version = "0.3.0" +version = "0.3.2" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "langchain-core" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/57/35/08ac1ca01c58da825f070bd1fdc9192a9ff52c0a048f74c93b05df70c127/langchain_text_splitters-0.3.0.tar.gz", hash = "sha256:f9fe0b4d244db1d6de211e7343d4abc4aa90295aa22e1f0c89e51f33c55cd7ce", size = 20234 } +sdist = { url = "https://files.pythonhosted.org/packages/47/63/0f7dae88d87e924d819e6a6375043499e3bc9931e306edd48b396abb4e42/langchain_text_splitters-0.3.2.tar.gz", hash = "sha256:81e6515d9901d6dd8e35fb31ccd4f30f76d44b771890c789dc835ef9f16204df", size = 20229 } wheels = [ - { url = "https://files.pythonhosted.org/packages/da/6a/d1303b722a3fa7a0a8c2f8f5307e42f0bdbded46d99cca436f3db0df5294/langchain_text_splitters-0.3.0-py3-none-any.whl", hash = "sha256:e84243e45eaff16e5b776cd9c81b6d07c55c010ebcb1965deb3d1792b7358e83", size = 25543 }, + { url = "https://files.pythonhosted.org/packages/ee/c6/5ba25c8bad647e92a92b3066177ab10d78efbd16c0b9919948cdcd18b027/langchain_text_splitters-0.3.2-py3-none-any.whl", hash = "sha256:0db28c53f41d1bc024cdb3b1646741f6d46d5371e90f31e7e7c9fbe75d01c726", size = 25564 }, ] [[package]] @@ -4173,15 +4173,15 @@ sdist = { url = "https://files.pythonhosted.org/packages/1f/19/89836022affc1bf47 [[package]] name = "loguru" -version = "0.7.2" +version = "0.7.3" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "colorama", marker = "sys_platform == 'win32'" }, { name = "win32-setctime", marker = "sys_platform == 'win32'" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/9e/30/d87a423766b24db416a46e9335b9602b054a72b96a88a241f2b09b560fa8/loguru-0.7.2.tar.gz", hash = "sha256:e671a53522515f34fd406340ee968cb9ecafbc4b36c679da03c18fd8d0bd51ac", size = 145103 } +sdist = { url = "https://files.pythonhosted.org/packages/3a/05/a1dae3dffd1116099471c643b8924f5aa6524411dc6c63fdae648c4f1aca/loguru-0.7.3.tar.gz", hash = "sha256:19480589e77d47b8d85b2c827ad95d49bf31b0dcde16593892eb51dd18706eb6", size = 63559 } wheels = [ - { url = "https://files.pythonhosted.org/packages/03/0a/4f6fed21aa246c6b49b561ca55facacc2a44b87d65b8b92362a8e99ba202/loguru-0.7.2-py3-none-any.whl", hash = "sha256:003d71e3d3ed35f0f8984898359d65b79e5b21943f78af86aa5491210429b8eb", size = 62549 }, + { url = "https://files.pythonhosted.org/packages/0c/29/0348de65b8cc732daa3e33e67806420b2ae89bdce2b04af740289c5c6c8c/loguru-0.7.3-py3-none-any.whl", hash = "sha256:31a33c10c8e1e10422bfd431aeb5d351c7cf7fa671e3c4df004162264b28220c", size = 61595 }, ] [[package]] @@ -4301,14 +4301,14 @@ wheels = [ [[package]] name = "mako" -version = "1.3.5" +version = "1.3.8" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "markupsafe" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/67/03/fb5ba97ff65ce64f6d35b582aacffc26b693a98053fa831ab43a437cbddb/Mako-1.3.5.tar.gz", hash = "sha256:48dbc20568c1d276a2698b36d968fa76161bf127194907ea6fc594fa81f943bc", size = 392738 } +sdist = { url = "https://files.pythonhosted.org/packages/5f/d9/8518279534ed7dace1795d5a47e49d5299dd0994eed1053996402a8902f9/mako-1.3.8.tar.gz", hash = "sha256:577b97e414580d3e088d47c2dbbe9594aa7a5146ed2875d4dfa9075af2dd3cc8", size = 392069 } wheels = [ - { url = "https://files.pythonhosted.org/packages/03/62/70f5a0c2dd208f9f3f2f9afd103aec42ee4d9ad2401d78342f75e9b8da36/Mako-1.3.5-py3-none-any.whl", hash = "sha256:260f1dbc3a519453a9c856dedfe4beb4e50bd5a26d96386cb6c80856556bb91a", size = 78565 }, + { url = "https://files.pythonhosted.org/packages/1e/bf/7a6a36ce2e4cafdfb202752be68850e22607fccd692847c45c1ae3c17ba6/Mako-1.3.8-py3-none-any.whl", hash = "sha256:42f48953c7eb91332040ff567eb7eea69b22e7a4affbc5ba8e845e8f730f6627", size = 78569 }, ] [[package]] @@ -4372,14 +4372,14 @@ wheels = [ [[package]] name = "marshmallow" -version = "3.22.0" +version = "3.23.1" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "packaging" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/70/40/faa10dc4500bca85f41ca9d8cefab282dd23d0fcc7a9b5fab40691e72e76/marshmallow-3.22.0.tar.gz", hash = "sha256:4972f529104a220bb8637d595aa4c9762afbe7f7a77d82dc58c1615d70c5823e", size = 176836 } +sdist = { url = "https://files.pythonhosted.org/packages/6d/30/14d8609f65c8aeddddd3181c06d2c9582da6278f063b27c910bbf9903441/marshmallow-3.23.1.tar.gz", hash = "sha256:3a8dfda6edd8dcdbf216c0ede1d1e78d230a6dc9c5a088f58c4083b974a0d468", size = 177488 } wheels = [ - { url = "https://files.pythonhosted.org/packages/3c/78/c1de55eb3311f2c200a8b91724414b8d6f5ae78891c15d9d936ea43c3dba/marshmallow-3.22.0-py3-none-any.whl", hash = "sha256:71a2dce49ef901c3f97ed296ae5051135fd3febd2bf43afe0ae9a82143a494d9", size = 49334 }, + { url = "https://files.pythonhosted.org/packages/ac/a7/a78ff54e67ef92a3d12126b98eb98ab8abab3de4a8c46d240c87e514d6bb/marshmallow-3.23.1-py3-none-any.whl", hash = "sha256:fece2eb2c941180ea1b7fcbd4a83c51bfdd50093fdd3ad2585ee5e1df2508491", size = 49488 }, ] [[package]] @@ -4459,21 +4459,6 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/84/65/639cb552c892ba5fef73301f878b2e7cabb59c918e0c49c9cf3026d49447/milvus_lite-2.4.10-py3-none-manylinux2014_x86_64.whl", hash = "sha256:211d2e334a043f9282bdd9755f76b9b2d93b23bffa7af240919ffce6a8dfe325", size = 49377774 }, ] -[[package]] -name = "minijinja" -version = "2.2.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/59/f5/f6937bd43692348d2825a9c32b1fd84368853b0dfc7fdd6aa28934eac5d0/minijinja-2.2.0.tar.gz", hash = "sha256:4411052c7a60f8d56468cc6d17d45d72be3d5e89e9578a04f8336cc56601523c", size = 203123 } -wheels = [ - { url = "https://files.pythonhosted.org/packages/61/ad/6664b63f56449ba74421544a1cd20c57d3f5877d33a3b923f27721465e31/minijinja-2.2.0-cp38-abi3-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:e4154fcf72e81be01c2733b770e6cb3e584851cb2fa73c58e347b04967d3d7c0", size = 1585656 }, - { url = "https://files.pythonhosted.org/packages/8f/83/46d715217e6d378dac7130e125ec4415a58b0d53ceda6a54d6d105c7c77f/minijinja-2.2.0-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4b05e0070c08b550fa9a09ff9c051f47424674332dd56cc54b997dd602887907", size = 806492 }, - { url = "https://files.pythonhosted.org/packages/48/66/bd31830f087226ae5d223fe287b3e4d24f5772d5ad758e32988fe77e4642/minijinja-2.2.0-cp38-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:360ea4a93fdf1fe327f3e70eed20ecb29f324ca28fae177de0605dcc29869300", size = 807719 }, - { url = "https://files.pythonhosted.org/packages/80/f0/87dbc02dc870d0bf50a064edf41fb255014d248bf118a3ee6b5721fc33dc/minijinja-2.2.0-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c9cad5ccb021ef25b6a271158f4d6636474edb08cd1dd49355aac6b68a48aebb", size = 861873 }, - { url = "https://files.pythonhosted.org/packages/62/ea/6b39d37700d72581d8fa5b843f92a9930016b4b381022461c0de6602859e/minijinja-2.2.0-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:7a85c67c519b413fc4892854782927e1244a24cbbb3a3cb0ac5e57d9fdb1868c", size = 935137 }, - { url = "https://files.pythonhosted.org/packages/fb/a6/c835281b7e96b12ab87b12bac63d0b423caa3b1decd47f698e9317a0a38f/minijinja-2.2.0-cp38-abi3-win32.whl", hash = "sha256:e431a2467dd6e1bcb7c511e9fbad012b02c6e5453acdd9fbd4c4af0d34a3d1c5", size = 729957 }, - { url = "https://files.pythonhosted.org/packages/68/df/ac513277e86e95d454a30ea0f303f32f9ba83a34ac286fa0df6a573da206/minijinja-2.2.0-cp38-abi3-win_amd64.whl", hash = "sha256:d4df7e4a09be4249c8243207fa89e6f4d22b853c2b565a99f48e478a30713822", size = 762232 }, -] - [[package]] name = "mmh3" version = "5.0.1" @@ -4644,31 +4629,31 @@ wheels = [ [[package]] name = "mypy" -version = "1.11.2" +version = "1.13.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "mypy-extensions" }, { name = "tomli", marker = "python_full_version < '3.11'" }, { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/5c/86/5d7cbc4974fd564550b80fbb8103c05501ea11aa7835edf3351d90095896/mypy-1.11.2.tar.gz", hash = "sha256:7f9993ad3e0ffdc95c2a14b66dee63729f021968bff8ad911867579c65d13a79", size = 3078806 } +sdist = { url = "https://files.pythonhosted.org/packages/e8/21/7e9e523537991d145ab8a0a2fd98548d67646dc2aaaf6091c31ad883e7c1/mypy-1.13.0.tar.gz", hash = "sha256:0291a61b6fbf3e6673e3405cfcc0e7650bebc7939659fdca2702958038bd835e", size = 3152532 } wheels = [ - { url = "https://files.pythonhosted.org/packages/78/cd/815368cd83c3a31873e5e55b317551500b12f2d1d7549720632f32630333/mypy-1.11.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d42a6dd818ffce7be66cce644f1dff482f1d97c53ca70908dff0b9ddc120b77a", size = 10939401 }, - { url = "https://files.pythonhosted.org/packages/f1/27/e18c93a195d2fad75eb96e1f1cbc431842c332e8eba2e2b77eaf7313c6b7/mypy-1.11.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:801780c56d1cdb896eacd5619a83e427ce436d86a3bdf9112527f24a66618fef", size = 10111697 }, - { url = "https://files.pythonhosted.org/packages/dc/08/cdc1fc6d0d5a67d354741344cc4aa7d53f7128902ebcbe699ddd4f15a61c/mypy-1.11.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:41ea707d036a5307ac674ea172875f40c9d55c5394f888b168033177fce47383", size = 12500508 }, - { url = "https://files.pythonhosted.org/packages/64/12/aad3af008c92c2d5d0720ea3b6674ba94a98cdb86888d389acdb5f218c30/mypy-1.11.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:6e658bd2d20565ea86da7d91331b0eed6d2eee22dc031579e6297f3e12c758c8", size = 13020712 }, - { url = "https://files.pythonhosted.org/packages/03/e6/a7d97cc124a565be5e9b7d5c2a6ebf082379ffba99646e4863ed5bbcb3c3/mypy-1.11.2-cp310-cp310-win_amd64.whl", hash = "sha256:478db5f5036817fe45adb7332d927daa62417159d49783041338921dcf646fc7", size = 9567319 }, - { url = "https://files.pythonhosted.org/packages/e2/aa/cc56fb53ebe14c64f1fe91d32d838d6f4db948b9494e200d2f61b820b85d/mypy-1.11.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:75746e06d5fa1e91bfd5432448d00d34593b52e7e91a187d981d08d1f33d4385", size = 10859630 }, - { url = "https://files.pythonhosted.org/packages/04/c8/b19a760fab491c22c51975cf74e3d253b8c8ce2be7afaa2490fbf95a8c59/mypy-1.11.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a976775ab2256aadc6add633d44f100a2517d2388906ec4f13231fafbb0eccca", size = 10037973 }, - { url = "https://files.pythonhosted.org/packages/88/57/7e7e39f2619c8f74a22efb9a4c4eff32b09d3798335625a124436d121d89/mypy-1.11.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:cd953f221ac1379050a8a646585a29574488974f79d8082cedef62744f0a0104", size = 12416659 }, - { url = "https://files.pythonhosted.org/packages/fc/a6/37f7544666b63a27e46c48f49caeee388bf3ce95f9c570eb5cfba5234405/mypy-1.11.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:57555a7715c0a34421013144a33d280e73c08df70f3a18a552938587ce9274f4", size = 12897010 }, - { url = "https://files.pythonhosted.org/packages/84/8b/459a513badc4d34acb31c736a0101c22d2bd0697b969796ad93294165cfb/mypy-1.11.2-cp311-cp311-win_amd64.whl", hash = "sha256:36383a4fcbad95f2657642a07ba22ff797de26277158f1cc7bd234821468b1b6", size = 9562873 }, - { url = "https://files.pythonhosted.org/packages/35/3a/ed7b12ecc3f6db2f664ccf85cb2e004d3e90bec928e9d7be6aa2f16b7cdf/mypy-1.11.2-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:e8960dbbbf36906c5c0b7f4fbf2f0c7ffb20f4898e6a879fcf56a41a08b0d318", size = 10990335 }, - { url = "https://files.pythonhosted.org/packages/04/e4/1a9051e2ef10296d206519f1df13d2cc896aea39e8683302f89bf5792a59/mypy-1.11.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:06d26c277962f3fb50e13044674aa10553981ae514288cb7d0a738f495550b36", size = 10007119 }, - { url = "https://files.pythonhosted.org/packages/f3/3c/350a9da895f8a7e87ade0028b962be0252d152e0c2fbaafa6f0658b4d0d4/mypy-1.11.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:6e7184632d89d677973a14d00ae4d03214c8bc301ceefcdaf5c474866814c987", size = 12506856 }, - { url = "https://files.pythonhosted.org/packages/b6/49/ee5adf6a49ff13f4202d949544d3d08abb0ea1f3e7f2a6d5b4c10ba0360a/mypy-1.11.2-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:3a66169b92452f72117e2da3a576087025449018afc2d8e9bfe5ffab865709ca", size = 12952066 }, - { url = "https://files.pythonhosted.org/packages/27/c0/b19d709a42b24004d720db37446a42abadf844d5c46a2c442e2a074d70d9/mypy-1.11.2-cp312-cp312-win_amd64.whl", hash = "sha256:969ea3ef09617aff826885a22ece0ddef69d95852cdad2f60c8bb06bf1f71f70", size = 9664000 }, - { url = "https://files.pythonhosted.org/packages/42/3a/bdf730640ac523229dd6578e8a581795720a9321399de494374afc437ec5/mypy-1.11.2-py3-none-any.whl", hash = "sha256:b499bc07dbdcd3de92b0a8b29fdf592c111276f6a12fe29c30f6c417dd546d12", size = 2619625 }, + { url = "https://files.pythonhosted.org/packages/5e/8c/206de95a27722b5b5a8c85ba3100467bd86299d92a4f71c6b9aa448bfa2f/mypy-1.13.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:6607e0f1dd1fb7f0aca14d936d13fd19eba5e17e1cd2a14f808fa5f8f6d8f60a", size = 11020731 }, + { url = "https://files.pythonhosted.org/packages/ab/bb/b31695a29eea76b1569fd28b4ab141a1adc9842edde080d1e8e1776862c7/mypy-1.13.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8a21be69bd26fa81b1f80a61ee7ab05b076c674d9b18fb56239d72e21d9f4c80", size = 10184276 }, + { url = "https://files.pythonhosted.org/packages/a5/2d/4a23849729bb27934a0e079c9c1aad912167d875c7b070382a408d459651/mypy-1.13.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:7b2353a44d2179846a096e25691d54d59904559f4232519d420d64da6828a3a7", size = 12587706 }, + { url = "https://files.pythonhosted.org/packages/5c/c3/d318e38ada50255e22e23353a469c791379825240e71b0ad03e76ca07ae6/mypy-1.13.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0730d1c6a2739d4511dc4253f8274cdd140c55c32dfb0a4cf8b7a43f40abfa6f", size = 13105586 }, + { url = "https://files.pythonhosted.org/packages/4a/25/3918bc64952370c3dbdbd8c82c363804678127815febd2925b7273d9482c/mypy-1.13.0-cp310-cp310-win_amd64.whl", hash = "sha256:c5fc54dbb712ff5e5a0fca797e6e0aa25726c7e72c6a5850cfd2adbc1eb0a372", size = 9632318 }, + { url = "https://files.pythonhosted.org/packages/d0/19/de0822609e5b93d02579075248c7aa6ceaddcea92f00bf4ea8e4c22e3598/mypy-1.13.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:581665e6f3a8a9078f28d5502f4c334c0c8d802ef55ea0e7276a6e409bc0d82d", size = 10939027 }, + { url = "https://files.pythonhosted.org/packages/c8/71/6950fcc6ca84179137e4cbf7cf41e6b68b4a339a1f5d3e954f8c34e02d66/mypy-1.13.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:3ddb5b9bf82e05cc9a627e84707b528e5c7caaa1c55c69e175abb15a761cec2d", size = 10108699 }, + { url = "https://files.pythonhosted.org/packages/26/50/29d3e7dd166e74dc13d46050b23f7d6d7533acf48f5217663a3719db024e/mypy-1.13.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:20c7ee0bc0d5a9595c46f38beb04201f2620065a93755704e141fcac9f59db2b", size = 12506263 }, + { url = "https://files.pythonhosted.org/packages/3f/1d/676e76f07f7d5ddcd4227af3938a9c9640f293b7d8a44dd4ff41d4db25c1/mypy-1.13.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:3790ded76f0b34bc9c8ba4def8f919dd6a46db0f5a6610fb994fe8efdd447f73", size = 12984688 }, + { url = "https://files.pythonhosted.org/packages/9c/03/5a85a30ae5407b1d28fab51bd3e2103e52ad0918d1e68f02a7778669a307/mypy-1.13.0-cp311-cp311-win_amd64.whl", hash = "sha256:51f869f4b6b538229c1d1bcc1dd7d119817206e2bc54e8e374b3dfa202defcca", size = 9626811 }, + { url = "https://files.pythonhosted.org/packages/fb/31/c526a7bd2e5c710ae47717c7a5f53f616db6d9097caf48ad650581e81748/mypy-1.13.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:5c7051a3461ae84dfb5dd15eff5094640c61c5f22257c8b766794e6dd85e72d5", size = 11077900 }, + { url = "https://files.pythonhosted.org/packages/83/67/b7419c6b503679d10bd26fc67529bc6a1f7a5f220bbb9f292dc10d33352f/mypy-1.13.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:39bb21c69a5d6342f4ce526e4584bc5c197fd20a60d14a8624d8743fffb9472e", size = 10074818 }, + { url = "https://files.pythonhosted.org/packages/ba/07/37d67048786ae84e6612575e173d713c9a05d0ae495dde1e68d972207d98/mypy-1.13.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:164f28cb9d6367439031f4c81e84d3ccaa1e19232d9d05d37cb0bd880d3f93c2", size = 12589275 }, + { url = "https://files.pythonhosted.org/packages/1f/17/b1018c6bb3e9f1ce3956722b3bf91bff86c1cefccca71cec05eae49d6d41/mypy-1.13.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:a4c1bfcdbce96ff5d96fc9b08e3831acb30dc44ab02671eca5953eadad07d6d0", size = 13037783 }, + { url = "https://files.pythonhosted.org/packages/cb/32/cd540755579e54a88099aee0287086d996f5a24281a673f78a0e14dba150/mypy-1.13.0-cp312-cp312-win_amd64.whl", hash = "sha256:a0affb3a79a256b4183ba09811e3577c5163ed06685e4d4b46429a271ba174d2", size = 9726197 }, + { url = "https://files.pythonhosted.org/packages/3b/86/72ce7f57431d87a7ff17d442f521146a6585019eb8f4f31b7c02801f78ad/mypy-1.13.0-py3-none-any.whl", hash = "sha256:9c250883f9fd81d212e0952c92dbfcc96fc237f4b7c92f56ac81fd48460b3e5a", size = 2647043 }, ] [[package]] @@ -4889,11 +4874,11 @@ wheels = [ [[package]] name = "nvidia-nvjitlink-cu12" -version = "12.6.77" +version = "12.6.85" source = { registry = "https://pypi.org/simple" } wheels = [ - { url = "https://files.pythonhosted.org/packages/11/8c/386018fdffdce2ff8d43fedf192ef7d14cab7501cbf78a106dd2e9f1fc1f/nvidia_nvjitlink_cu12-12.6.77-py3-none-manylinux2014_aarch64.whl", hash = "sha256:3bf10d85bb1801e9c894c6e197e44dd137d2a0a9e43f8450e9ad13f2df0dd52d", size = 19270432 }, - { url = "https://files.pythonhosted.org/packages/fe/e4/486de766851d58699bcfeb3ba6a3beb4d89c3809f75b9d423b9508a8760f/nvidia_nvjitlink_cu12-12.6.77-py3-none-manylinux2014_x86_64.whl", hash = "sha256:9ae346d16203ae4ea513be416495167a0101d33d2d14935aa9c1829a3fb45142", size = 19745114 }, + { url = "https://files.pythonhosted.org/packages/9d/d7/c5383e47c7e9bf1c99d5bd2a8c935af2b6d705ad831a7ec5c97db4d82f4f/nvidia_nvjitlink_cu12-12.6.85-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl", hash = "sha256:eedc36df9e88b682efe4309aa16b5b4e78c2407eac59e8c10a6a47535164369a", size = 19744971 }, + { url = "https://files.pythonhosted.org/packages/31/db/dc71113d441f208cdfe7ae10d4983884e13f464a6252450693365e166dcf/nvidia_nvjitlink_cu12-12.6.85-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:cf4eaa7d4b6b543ffd69d6abfb11efdeb2db48270d94dfd3a452c24150829e41", size = 19270338 }, ] [[package]] @@ -4927,7 +4912,7 @@ wheels = [ [[package]] name = "onnxruntime" -version = "1.19.2" +version = "1.20.1" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "coloredlogs" }, @@ -4938,26 +4923,26 @@ dependencies = [ { name = "sympy" }, ] wheels = [ - { url = "https://files.pythonhosted.org/packages/39/18/272d3d7406909141d3c9943796e3e97cafa53f4342d9231c0cfd8cb05702/onnxruntime-1.19.2-cp310-cp310-macosx_11_0_universal2.whl", hash = "sha256:84fa57369c06cadd3c2a538ae2a26d76d583e7c34bdecd5769d71ca5c0fc750e", size = 16776408 }, - { url = "https://files.pythonhosted.org/packages/d8/d3/eb93f4ae511cfc725d0c69e07008800f8ac018de19ea1e497b306f174ccc/onnxruntime-1.19.2-cp310-cp310-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:bdc471a66df0c1cdef774accef69e9f2ca168c851ab5e4f2f3341512c7ef4666", size = 11491779 }, - { url = "https://files.pythonhosted.org/packages/ca/4b/ce5958074abe4b6e8d1da9c10e443e01a681558a9ec17e5cc7619438e094/onnxruntime-1.19.2-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:e3a4ce906105d99ebbe817f536d50a91ed8a4d1592553f49b3c23c4be2560ae6", size = 13170428 }, - { url = "https://files.pythonhosted.org/packages/ce/0f/6df82dfe02467d12adbaa05c2bd17519c29c7df531ed600231f0c741ad22/onnxruntime-1.19.2-cp310-cp310-win32.whl", hash = "sha256:4b3d723cc154c8ddeb9f6d0a8c0d6243774c6b5930847cc83170bfe4678fafb3", size = 9591305 }, - { url = "https://files.pythonhosted.org/packages/3c/d8/68b63dc86b502169d017a86fe8bc718f4b0055ef1f6895bfaddd04f2eead/onnxruntime-1.19.2-cp310-cp310-win_amd64.whl", hash = "sha256:17ed7382d2c58d4b7354fb2b301ff30b9bf308a1c7eac9546449cd122d21cae5", size = 11084902 }, - { url = "https://files.pythonhosted.org/packages/f0/ff/77bee5df55f034ee81d2e1bc58b2b8511b9c54f06ce6566cb562c5d95aa5/onnxruntime-1.19.2-cp311-cp311-macosx_11_0_universal2.whl", hash = "sha256:d863e8acdc7232d705d49e41087e10b274c42f09e259016a46f32c34e06dc4fd", size = 16779187 }, - { url = "https://files.pythonhosted.org/packages/f3/78/e29f5fb76e0f6524f3520e8e5b9d53282784b45d14068c5112db9f712b0a/onnxruntime-1.19.2-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c1dfe4f660a71b31caa81fc298a25f9612815215a47b286236e61d540350d7b6", size = 11496005 }, - { url = "https://files.pythonhosted.org/packages/60/ce/be4152da5c1030ab5a159a4a792ed9abad6ba498d79ef0aeba593ff7b5bf/onnxruntime-1.19.2-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:a36511dc07c5c964b916697e42e366fa43c48cdb3d3503578d78cef30417cb84", size = 13167809 }, - { url = "https://files.pythonhosted.org/packages/e1/00/9740a074eb0e0a21ff13a2c4f32aecc5b21110b2c9b9177d8ac132b66e2d/onnxruntime-1.19.2-cp311-cp311-win32.whl", hash = "sha256:50cbb8dc69d6befad4746a69760e5b00cc3ff0a59c6c3fb27f8afa20e2cab7e7", size = 9591445 }, - { url = "https://files.pythonhosted.org/packages/1e/f5/9d995a685f97508b3254f17015b4a78641b0625e79480a7aed7a7a105d7c/onnxruntime-1.19.2-cp311-cp311-win_amd64.whl", hash = "sha256:1c3e5d415b78337fa0b1b75291e9ea9fb2a4c1f148eb5811e7212fed02cfffa8", size = 11085695 }, - { url = "https://files.pythonhosted.org/packages/f2/a5/2a02687a88fc8a2507bef65876c90e96b9f8de5ba1f810acbf67c140fc67/onnxruntime-1.19.2-cp312-cp312-macosx_11_0_universal2.whl", hash = "sha256:68e7051bef9cfefcbb858d2d2646536829894d72a4130c24019219442b1dd2ed", size = 16790434 }, - { url = "https://files.pythonhosted.org/packages/47/64/da42254ec14452cad2cdd4cf407094841c0a378c0d08944e9a36172197e9/onnxruntime-1.19.2-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d2d366fbcc205ce68a8a3bde2185fd15c604d9645888703785b61ef174265168", size = 11486028 }, - { url = "https://files.pythonhosted.org/packages/b2/92/3574f6836f33b1b25f272293e72538c38451b12c2d9aa08630bb6bc0f057/onnxruntime-1.19.2-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:477b93df4db467e9cbf34051662a4b27c18e131fa1836e05974eae0d6e4cf29b", size = 13175054 }, - { url = "https://files.pythonhosted.org/packages/ff/c9/8c37e413a830cac7f7dc094fffbd0c998c8bcb66a6f0b0a3201a49bc742b/onnxruntime-1.19.2-cp312-cp312-win32.whl", hash = "sha256:9a174073dc5608fad05f7cf7f320b52e8035e73d80b0a23c80f840e5a97c0147", size = 9592681 }, - { url = "https://files.pythonhosted.org/packages/44/c0/59768846533786a82cafb38d8d2f900ad666bc91f0ae634774d286fa3c47/onnxruntime-1.19.2-cp312-cp312-win_amd64.whl", hash = "sha256:190103273ea4507638ffc31d66a980594b237874b65379e273125150eb044857", size = 11086411 }, + { url = "https://files.pythonhosted.org/packages/4e/28/99f903b0eb1cd6f3faa0e343217d9fb9f47b84bca98bd9859884631336ee/onnxruntime-1.20.1-cp310-cp310-macosx_13_0_universal2.whl", hash = "sha256:e50ba5ff7fed4f7d9253a6baf801ca2883cc08491f9d32d78a80da57256a5439", size = 30996314 }, + { url = "https://files.pythonhosted.org/packages/6d/c6/c4c0860bee2fde6037bdd9dcd12d323f6e38cf00fcc9a5065b394337fc55/onnxruntime-1.20.1-cp310-cp310-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:7b2908b50101a19e99c4d4e97ebb9905561daf61829403061c1adc1b588bc0de", size = 11954010 }, + { url = "https://files.pythonhosted.org/packages/63/47/3dc0b075ab539f16b3d8b09df6b504f51836086ee709690a6278d791737d/onnxruntime-1.20.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:d82daaec24045a2e87598b8ac2b417b1cce623244e80e663882e9fe1aae86410", size = 13330452 }, + { url = "https://files.pythonhosted.org/packages/27/ef/80fab86289ecc01a734b7ddf115dfb93d8b2e004bd1e1977e12881c72b12/onnxruntime-1.20.1-cp310-cp310-win32.whl", hash = "sha256:4c4b251a725a3b8cf2aab284f7d940c26094ecd9d442f07dd81ab5470e99b83f", size = 9813849 }, + { url = "https://files.pythonhosted.org/packages/a9/e6/33ab10066c9875a29d55e66ae97c3bf91b9b9b987179455d67c32261a49c/onnxruntime-1.20.1-cp310-cp310-win_amd64.whl", hash = "sha256:d3b616bb53a77a9463707bb313637223380fc327f5064c9a782e8ec69c22e6a2", size = 11329702 }, + { url = "https://files.pythonhosted.org/packages/95/8d/2634e2959b34aa8a0037989f4229e9abcfa484e9c228f99633b3241768a6/onnxruntime-1.20.1-cp311-cp311-macosx_13_0_universal2.whl", hash = "sha256:06bfbf02ca9ab5f28946e0f912a562a5f005301d0c419283dc57b3ed7969bb7b", size = 30998725 }, + { url = "https://files.pythonhosted.org/packages/a5/da/c44bf9bd66cd6d9018a921f053f28d819445c4d84b4dd4777271b0fe52a2/onnxruntime-1.20.1-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f6243e34d74423bdd1edf0ae9596dd61023b260f546ee17d701723915f06a9f7", size = 11955227 }, + { url = "https://files.pythonhosted.org/packages/11/ac/4120dfb74c8e45cce1c664fc7f7ce010edd587ba67ac41489f7432eb9381/onnxruntime-1.20.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:5eec64c0269dcdb8d9a9a53dc4d64f87b9e0c19801d9321246a53b7eb5a7d1bc", size = 13331703 }, + { url = "https://files.pythonhosted.org/packages/12/f1/cefacac137f7bb7bfba57c50c478150fcd3c54aca72762ac2c05ce0532c1/onnxruntime-1.20.1-cp311-cp311-win32.whl", hash = "sha256:a19bc6e8c70e2485a1725b3d517a2319603acc14c1f1a017dda0afe6d4665b41", size = 9813977 }, + { url = "https://files.pythonhosted.org/packages/2c/2d/2d4d202c0bcfb3a4cc2b171abb9328672d7f91d7af9ea52572722c6d8d96/onnxruntime-1.20.1-cp311-cp311-win_amd64.whl", hash = "sha256:8508887eb1c5f9537a4071768723ec7c30c28eb2518a00d0adcd32c89dea3221", size = 11329895 }, + { url = "https://files.pythonhosted.org/packages/e5/39/9335e0874f68f7d27103cbffc0e235e32e26759202df6085716375c078bb/onnxruntime-1.20.1-cp312-cp312-macosx_13_0_universal2.whl", hash = "sha256:22b0655e2bf4f2161d52706e31f517a0e54939dc393e92577df51808a7edc8c9", size = 31007580 }, + { url = "https://files.pythonhosted.org/packages/c5/9d/a42a84e10f1744dd27c6f2f9280cc3fb98f869dd19b7cd042e391ee2ab61/onnxruntime-1.20.1-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f1f56e898815963d6dc4ee1c35fc6c36506466eff6d16f3cb9848cea4e8c8172", size = 11952833 }, + { url = "https://files.pythonhosted.org/packages/47/42/2f71f5680834688a9c81becbe5c5bb996fd33eaed5c66ae0606c3b1d6a02/onnxruntime-1.20.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:bb71a814f66517a65628c9e4a2bb530a6edd2cd5d87ffa0af0f6f773a027d99e", size = 13333903 }, + { url = "https://files.pythonhosted.org/packages/c8/f1/aabfdf91d013320aa2fc46cf43c88ca0182860ff15df872b4552254a9680/onnxruntime-1.20.1-cp312-cp312-win32.whl", hash = "sha256:bd386cc9ee5f686ee8a75ba74037750aca55183085bf1941da8efcfe12d5b120", size = 9814562 }, + { url = "https://files.pythonhosted.org/packages/dd/80/76979e0b744307d488c79e41051117634b956612cc731f1028eb17ee7294/onnxruntime-1.20.1-cp312-cp312-win_amd64.whl", hash = "sha256:19c2d843eb074f385e8bbb753a40df780511061a63f9def1b216bf53860223fb", size = 11331482 }, ] [[package]] name = "openai" -version = "1.57.1" +version = "1.57.2" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "anyio" }, @@ -4969,9 +4954,9 @@ dependencies = [ { name = "tqdm" }, { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/42/73/6e2a57b6ea92c8a786d775877c711f067f1d944dc9b1e6bbd166780c8e93/openai-1.57.1.tar.gz", hash = "sha256:a95f22e04ab3df26e64a15d958342265e802314131275908b3b3e36f8c5d4377", size = 315554 } +sdist = { url = "https://files.pythonhosted.org/packages/a9/b6/9a404e1d1043cabbffb020f9d850a44a31f30f284444a528d9a1f0eec9df/openai-1.57.2.tar.gz", hash = "sha256:5f49fd0f38e9f2131cda7deb45dafdd1aee4f52a637e190ce0ecf40147ce8cee", size = 315752 } wheels = [ - { url = "https://files.pythonhosted.org/packages/6b/f0/c25aab1845afc3583a808d0a9b844bb3842245d87b9791e588e6aba8ce3a/openai-1.57.1-py3-none-any.whl", hash = "sha256:3865686c927e93492d1145938d4a24b634951531c4b2769d43ca5dbd4b25d8fd", size = 389846 }, + { url = "https://files.pythonhosted.org/packages/37/e7/95437fb676381e927d4cb3f9f8dd90ed24cfd264f572db4d395037428594/openai-1.57.2-py3-none-any.whl", hash = "sha256:f7326283c156fdee875746e7e54d36959fb198eadc683952ee05e3302fbd638d", size = 389873 }, ] [[package]] @@ -5044,45 +5029,45 @@ wheels = [ [[package]] name = "opentelemetry-api" -version = "1.27.0" +version = "1.29.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "deprecated" }, { name = "importlib-metadata" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/c9/83/93114b6de85a98963aec218a51509a52ed3f8de918fe91eb0f7299805c3f/opentelemetry_api-1.27.0.tar.gz", hash = "sha256:ed673583eaa5f81b5ce5e86ef7cdaf622f88ef65f0b9aab40b843dcae5bef342", size = 62693 } +sdist = { url = "https://files.pythonhosted.org/packages/bc/8e/b886a5e9861afa188d1fe671fb96ff9a1d90a23d57799331e137cc95d573/opentelemetry_api-1.29.0.tar.gz", hash = "sha256:d04a6cf78aad09614f52964ecb38021e248f5714dc32c2e0d8fd99517b4d69cf", size = 62900 } wheels = [ - { url = "https://files.pythonhosted.org/packages/fb/1f/737dcdbc9fea2fa96c1b392ae47275165a7c641663fbb08a8d252968eed2/opentelemetry_api-1.27.0-py3-none-any.whl", hash = "sha256:953d5871815e7c30c81b56d910c707588000fff7a3ca1c73e6531911d53065e7", size = 63970 }, + { url = "https://files.pythonhosted.org/packages/43/53/5249ea860d417a26a3a6f1bdedfc0748c4f081a3adaec3d398bc0f7c6a71/opentelemetry_api-1.29.0-py3-none-any.whl", hash = "sha256:5fcd94c4141cc49c736271f3e1efb777bebe9cc535759c54c936cca4f1b312b8", size = 64304 }, ] [[package]] name = "opentelemetry-exporter-otlp" -version = "1.27.0" +version = "1.29.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "opentelemetry-exporter-otlp-proto-grpc" }, { name = "opentelemetry-exporter-otlp-proto-http" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/fc/d3/8156cc14e8f4573a3572ee7f30badc7aabd02961a09acc72ab5f2c789ef1/opentelemetry_exporter_otlp-1.27.0.tar.gz", hash = "sha256:4a599459e623868cc95d933c301199c2367e530f089750e115599fccd67cb2a1", size = 6166 } +sdist = { url = "https://files.pythonhosted.org/packages/91/23/824e71822969cd3018897f5b0246baf8305bf7635f20df1ce5dfc423c32d/opentelemetry_exporter_otlp-1.29.0.tar.gz", hash = "sha256:ee7dfcccbb5e87ad9b389908452e10b7beeab55f70a83f41ce5b8c4efbde6544", size = 6159 } wheels = [ - { url = "https://files.pythonhosted.org/packages/59/6d/95e1fc2c8d945a734db32e87a5aa7a804f847c1657a21351df9338bd1c9c/opentelemetry_exporter_otlp-1.27.0-py3-none-any.whl", hash = "sha256:7688791cbdd951d71eb6445951d1cfbb7b6b2d7ee5948fac805d404802931145", size = 7001 }, + { url = "https://files.pythonhosted.org/packages/cf/54/2a84533f39bb240958d691bb3ddf1c3fb6a92356654fb2e02a210f65ce6b/opentelemetry_exporter_otlp-1.29.0-py3-none-any.whl", hash = "sha256:b8da6e20f5b0ffe604154b1e16a407eade17ce310c42fb85bb4e1246fc3688ad", size = 7011 }, ] [[package]] name = "opentelemetry-exporter-otlp-proto-common" -version = "1.27.0" +version = "1.29.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "opentelemetry-proto" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/cd/2e/7eaf4ba595fb5213cf639c9158dfb64aacb2e4c7d74bfa664af89fa111f4/opentelemetry_exporter_otlp_proto_common-1.27.0.tar.gz", hash = "sha256:159d27cf49f359e3798c4c3eb8da6ef4020e292571bd8c5604a2a573231dd5c8", size = 17860 } +sdist = { url = "https://files.pythonhosted.org/packages/b1/58/f7fd7eaf592b2521999a4271ab3ce1c82fe37fe9b0dc25c348398d95d66a/opentelemetry_exporter_otlp_proto_common-1.29.0.tar.gz", hash = "sha256:e7c39b5dbd1b78fe199e40ddfe477e6983cb61aa74ba836df09c3869a3e3e163", size = 19133 } wheels = [ - { url = "https://files.pythonhosted.org/packages/41/27/4610ab3d9bb3cde4309b6505f98b3aabca04a26aa480aa18cede23149837/opentelemetry_exporter_otlp_proto_common-1.27.0-py3-none-any.whl", hash = "sha256:675db7fffcb60946f3a5c43e17d1168a3307a94a930ecf8d2ea1f286f3d4f79a", size = 17848 }, + { url = "https://files.pythonhosted.org/packages/9e/75/7609bda3d72bf307839570b226180513e854c01443ebe265ed732a4980fc/opentelemetry_exporter_otlp_proto_common-1.29.0-py3-none-any.whl", hash = "sha256:a9d7376c06b4da9cf350677bcddb9618ed4b8255c3f6476975f5e38274ecd3aa", size = 18459 }, ] [[package]] name = "opentelemetry-exporter-otlp-proto-grpc" -version = "1.27.0" +version = "1.29.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "deprecated" }, @@ -5093,14 +5078,14 @@ dependencies = [ { name = "opentelemetry-proto" }, { name = "opentelemetry-sdk" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/a1/d0/c1e375b292df26e0ffebf194e82cd197e4c26cc298582bda626ce3ce74c5/opentelemetry_exporter_otlp_proto_grpc-1.27.0.tar.gz", hash = "sha256:af6f72f76bcf425dfb5ad11c1a6d6eca2863b91e63575f89bb7b4b55099d968f", size = 26244 } +sdist = { url = "https://files.pythonhosted.org/packages/41/aa/b3f2190613141f35fe15145bf438334fdd1eac8aeeee4f7ecbc887999443/opentelemetry_exporter_otlp_proto_grpc-1.29.0.tar.gz", hash = "sha256:3d324d07d64574d72ed178698de3d717f62a059a93b6b7685ee3e303384e73ea", size = 26224 } wheels = [ - { url = "https://files.pythonhosted.org/packages/8d/80/32217460c2c64c0568cea38410124ff680a9b65f6732867bbf857c4d8626/opentelemetry_exporter_otlp_proto_grpc-1.27.0-py3-none-any.whl", hash = "sha256:56b5bbd5d61aab05e300d9d62a6b3c134827bbd28d0b12f2649c2da368006c9e", size = 18541 }, + { url = "https://files.pythonhosted.org/packages/f2/de/4b4127a25d1594851d99032f3a9acb09cb512d11edec713410fb906607f4/opentelemetry_exporter_otlp_proto_grpc-1.29.0-py3-none-any.whl", hash = "sha256:5a2a3a741a2543ed162676cf3eefc2b4150e6f4f0a193187afb0d0e65039c69c", size = 18520 }, ] [[package]] name = "opentelemetry-exporter-otlp-proto-http" -version = "1.27.0" +version = "1.29.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "deprecated" }, @@ -5111,42 +5096,43 @@ dependencies = [ { name = "opentelemetry-sdk" }, { name = "requests" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/31/0a/f05c55e8913bf58a033583f2580a0ec31a5f4cf2beacc9e286dcb74d6979/opentelemetry_exporter_otlp_proto_http-1.27.0.tar.gz", hash = "sha256:2103479092d8eb18f61f3fbff084f67cc7f2d4a7d37e75304b8b56c1d09ebef5", size = 15059 } +sdist = { url = "https://files.pythonhosted.org/packages/ab/88/e70a2e9fbb1bddb1ab7b6d74fb02c68601bff5948292ce33464c84ee082e/opentelemetry_exporter_otlp_proto_http-1.29.0.tar.gz", hash = "sha256:b10d174e3189716f49d386d66361fbcf6f2b9ad81e05404acdee3f65c8214204", size = 15041 } wheels = [ - { url = "https://files.pythonhosted.org/packages/2d/8d/4755884afc0b1db6000527cac0ca17273063b6142c773ce4ecd307a82e72/opentelemetry_exporter_otlp_proto_http-1.27.0-py3-none-any.whl", hash = "sha256:688027575c9da42e179a69fe17e2d1eba9b14d81de8d13553a21d3114f3b4d75", size = 17203 }, + { url = "https://files.pythonhosted.org/packages/31/49/a1c3d24e8fe73b5f422e21b46c24aed3db7fd9427371c06442e7bdfe4d3b/opentelemetry_exporter_otlp_proto_http-1.29.0-py3-none-any.whl", hash = "sha256:b228bdc0f0cfab82eeea834a7f0ffdd2a258b26aa33d89fb426c29e8e934d9d0", size = 17217 }, ] [[package]] name = "opentelemetry-exporter-prometheus" -version = "0.48b0" +version = "0.50b0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "opentelemetry-api" }, { name = "opentelemetry-sdk" }, { name = "prometheus-client" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/dd/69/a8cc4fda5d620d6c1544f93698a58d1a2871fa41b05d3c2055e715c9ce27/opentelemetry_exporter_prometheus-0.48b0.tar.gz", hash = "sha256:46d2620b2b7223731103fd76faee2dd37d05316602574ce64ec376124aec7c29", size = 14815 } +sdist = { url = "https://files.pythonhosted.org/packages/06/58/bc9bad8fdbb1ec4ef64a6d353eb3798479efbeb1df875f371c714ca6199f/opentelemetry_exporter_prometheus-0.50b0.tar.gz", hash = "sha256:5c5be644e959a0980919778a367d9603892128443489a5b2ced15c90e1733892", size = 14584 } wheels = [ - { url = "https://files.pythonhosted.org/packages/8f/20/c8e467963f45753be784c34d0f26e244d641025f7ac13e7f8316d959fc68/opentelemetry_exporter_prometheus-0.48b0-py3-none-any.whl", hash = "sha256:a54342b597bdaeb799fd5414a789df84bc0d2f033258702d141d731590ab3b2d", size = 12830 }, + { url = "https://files.pythonhosted.org/packages/7e/f0/2861ecd7f32166e574c0f1a36a19e6cfe8ffe8459d3f575ac7e618b805d2/opentelemetry_exporter_prometheus-0.50b0-py3-none-any.whl", hash = "sha256:b44561b44ada38a223b622425e5df71ef1e933b2777f7f399990c333b9464805", size = 12889 }, ] [[package]] name = "opentelemetry-instrumentation" -version = "0.48b0" +version = "0.50b0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "opentelemetry-api" }, - { name = "setuptools" }, + { name = "opentelemetry-semantic-conventions" }, + { name = "packaging" }, { name = "wrapt" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/04/0e/d9394839af5d55c8feb3b22cd11138b953b49739b20678ca96289e30f904/opentelemetry_instrumentation-0.48b0.tar.gz", hash = "sha256:94929685d906380743a71c3970f76b5f07476eea1834abd5dd9d17abfe23cc35", size = 24724 } +sdist = { url = "https://files.pythonhosted.org/packages/79/2e/2e59a7cb636dc394bd7cf1758ada5e8ed87590458ca6bb2f9c26e0243847/opentelemetry_instrumentation-0.50b0.tar.gz", hash = "sha256:7d98af72de8dec5323e5202e46122e5f908592b22c6d24733aad619f07d82979", size = 26539 } wheels = [ - { url = "https://files.pythonhosted.org/packages/0a/7f/405c41d4f359121376c9d5117dcf68149b8122d3f6c718996d037bd4d800/opentelemetry_instrumentation-0.48b0-py3-none-any.whl", hash = "sha256:a69750dc4ba6a5c3eb67986a337185a25b739966d80479befe37b546fc870b44", size = 29449 }, + { url = "https://files.pythonhosted.org/packages/ff/b1/55a77152a83ec8998e520a3a575f44af1020cfe4bdc000b7538583293b85/opentelemetry_instrumentation-0.50b0-py3-none-any.whl", hash = "sha256:b8f9fc8812de36e1c6dffa5bfc6224df258841fb387b6dfe5df15099daa10630", size = 30728 }, ] [[package]] name = "opentelemetry-instrumentation-asgi" -version = "0.48b0" +version = "0.50b0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "asgiref" }, @@ -5155,14 +5141,14 @@ dependencies = [ { name = "opentelemetry-semantic-conventions" }, { name = "opentelemetry-util-http" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/44/ac/fd3d40bab3234ec3f5c052a815100676baaae1832fa1067935f11e5c59c6/opentelemetry_instrumentation_asgi-0.48b0.tar.gz", hash = "sha256:04c32174b23c7fa72ddfe192dad874954968a6a924608079af9952964ecdf785", size = 23435 } +sdist = { url = "https://files.pythonhosted.org/packages/49/cc/a7b2fd243c6d2621803092eba62e450071b6752dfe4f64f530bbfd91a328/opentelemetry_instrumentation_asgi-0.50b0.tar.gz", hash = "sha256:3ca4cb5616ae6a3e8ce86e7d5c360a8d8cc8ed722cf3dc8a5e44300774e87d49", size = 24105 } wheels = [ - { url = "https://files.pythonhosted.org/packages/db/74/a0e0d38622856597dd8e630f2bd793760485eb165708e11b8be1696bbb5a/opentelemetry_instrumentation_asgi-0.48b0-py3-none-any.whl", hash = "sha256:ddb1b5fc800ae66e85a4e2eca4d9ecd66367a8c7b556169d9e7b57e10676e44d", size = 15958 }, + { url = "https://files.pythonhosted.org/packages/d2/81/0899c6b56b1023835f266d909250d439174afa0c34ed5944c5021d3da263/opentelemetry_instrumentation_asgi-0.50b0-py3-none-any.whl", hash = "sha256:2ba1297f746e55dec5a17fe825689da0613662fb25c004c3965a6c54b1d5be22", size = 16304 }, ] [[package]] name = "opentelemetry-instrumentation-fastapi" -version = "0.48b0" +version = "0.50b0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "opentelemetry-api" }, @@ -5171,62 +5157,62 @@ dependencies = [ { name = "opentelemetry-semantic-conventions" }, { name = "opentelemetry-util-http" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/58/20/43477da5850ef2cd3792715d442aecd051e885e0603b6ee5783b2104ba8f/opentelemetry_instrumentation_fastapi-0.48b0.tar.gz", hash = "sha256:21a72563ea412c0b535815aeed75fc580240f1f02ebc72381cfab672648637a2", size = 18497 } +sdist = { url = "https://files.pythonhosted.org/packages/8d/f8/1917b0b3e414e23c7d71c9a33f0ce020f94bc47d22a30f54ace704e07588/opentelemetry_instrumentation_fastapi-0.50b0.tar.gz", hash = "sha256:16b9181682136da210295def2bb304a32fb9bdee9a935cdc9da43567f7c1149e", size = 19214 } wheels = [ - { url = "https://files.pythonhosted.org/packages/ee/50/745ab075a3041b7a5f29a579d2c28eaad54f64b4589d8f9fd364c62cf0f3/opentelemetry_instrumentation_fastapi-0.48b0-py3-none-any.whl", hash = "sha256:afeb820a59e139d3e5d96619600f11ce0187658b8ae9e3480857dd790bc024f2", size = 11777 }, + { url = "https://files.pythonhosted.org/packages/cb/d6/37784bb30b213e2dd6838b9f96c2940907022c1b75ef1ff18a99afe42433/opentelemetry_instrumentation_fastapi-0.50b0-py3-none-any.whl", hash = "sha256:8f03b738495e4705fbae51a2826389c7369629dace89d0f291c06ffefdff5e52", size = 12079 }, ] [[package]] name = "opentelemetry-proto" -version = "1.27.0" +version = "1.29.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "protobuf" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/9a/59/959f0beea798ae0ee9c979b90f220736fbec924eedbefc60ca581232e659/opentelemetry_proto-1.27.0.tar.gz", hash = "sha256:33c9345d91dafd8a74fc3d7576c5a38f18b7fdf8d02983ac67485386132aedd6", size = 34749 } +sdist = { url = "https://files.pythonhosted.org/packages/80/52/fd3b3d79e1b00ad2dcac92db6885e49bedbf7a6828647954e4952d653132/opentelemetry_proto-1.29.0.tar.gz", hash = "sha256:3c136aa293782e9b44978c738fff72877a4b78b5d21a64e879898db7b2d93e5d", size = 34320 } wheels = [ - { url = "https://files.pythonhosted.org/packages/94/56/3d2d826834209b19a5141eed717f7922150224d1a982385d19a9444cbf8d/opentelemetry_proto-1.27.0-py3-none-any.whl", hash = "sha256:b133873de5581a50063e1e4b29cdcf0c5e253a8c2d8dc1229add20a4c3830ace", size = 52464 }, + { url = "https://files.pythonhosted.org/packages/bd/66/a500e38ee322d89fce61c74bd7769c8ef3bebc6c2f43fda5f3fc3441286d/opentelemetry_proto-1.29.0-py3-none-any.whl", hash = "sha256:495069c6f5495cbf732501cdcd3b7f60fda2b9d3d4255706ca99b7ca8dec53ff", size = 55818 }, ] [[package]] name = "opentelemetry-sdk" -version = "1.27.0" +version = "1.29.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "opentelemetry-api" }, { name = "opentelemetry-semantic-conventions" }, { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/0d/9a/82a6ac0f06590f3d72241a587cb8b0b751bd98728e896cc4cbd4847248e6/opentelemetry_sdk-1.27.0.tar.gz", hash = "sha256:d525017dea0ccce9ba4e0245100ec46ecdc043f2d7b8315d56b19aff0904fa6f", size = 145019 } +sdist = { url = "https://files.pythonhosted.org/packages/0c/5a/1ed4c3cf6c09f80565fc085f7e8efa0c222712fd2a9412d07424705dcf72/opentelemetry_sdk-1.29.0.tar.gz", hash = "sha256:b0787ce6aade6ab84315302e72bd7a7f2f014b0fb1b7c3295b88afe014ed0643", size = 157229 } wheels = [ - { url = "https://files.pythonhosted.org/packages/c1/bd/a6602e71e315055d63b2ff07172bd2d012b4cba2d4e00735d74ba42fc4d6/opentelemetry_sdk-1.27.0-py3-none-any.whl", hash = "sha256:365f5e32f920faf0fd9e14fdfd92c086e317eaa5f860edba9cdc17a380d9197d", size = 110505 }, + { url = "https://files.pythonhosted.org/packages/d1/1d/512b86af21795fb463726665e2f61db77d384e8779fdcf4cb0ceec47866d/opentelemetry_sdk-1.29.0-py3-none-any.whl", hash = "sha256:173be3b5d3f8f7d671f20ea37056710217959e774e2749d984355d1f9391a30a", size = 118078 }, ] [[package]] name = "opentelemetry-semantic-conventions" -version = "0.48b0" +version = "0.50b0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "deprecated" }, { name = "opentelemetry-api" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/0a/89/1724ad69f7411772446067cdfa73b598694c8c91f7f8c922e344d96d81f9/opentelemetry_semantic_conventions-0.48b0.tar.gz", hash = "sha256:12d74983783b6878162208be57c9effcb89dc88691c64992d70bb89dc00daa1a", size = 89445 } +sdist = { url = "https://files.pythonhosted.org/packages/e7/4e/d7c7c91ff47cd96fe4095dd7231701aec7347426fd66872ff320d6cd1fcc/opentelemetry_semantic_conventions-0.50b0.tar.gz", hash = "sha256:02dc6dbcb62f082de9b877ff19a3f1ffaa3c306300fa53bfac761c4567c83d38", size = 100459 } wheels = [ - { url = "https://files.pythonhosted.org/packages/b7/7a/4f0063dbb0b6c971568291a8bc19a4ca70d3c185db2d956230dd67429dfc/opentelemetry_semantic_conventions-0.48b0-py3-none-any.whl", hash = "sha256:a0de9f45c413a8669788a38569c7e0a11ce6ce97861a628cca785deecdc32a1f", size = 149685 }, + { url = "https://files.pythonhosted.org/packages/da/fb/dc15fad105450a015e913cfa4f5c27b6a5f1bea8fb649f8cae11e699c8af/opentelemetry_semantic_conventions-0.50b0-py3-none-any.whl", hash = "sha256:e87efba8fdb67fb38113efea6a349531e75ed7ffc01562f65b802fcecb5e115e", size = 166602 }, ] [[package]] name = "opentelemetry-util-http" -version = "0.48b0" +version = "0.50b0" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/d6/d7/185c494754340e0a3928fd39fde2616ee78f2c9d66253affaad62d5b7935/opentelemetry_util_http-0.48b0.tar.gz", hash = "sha256:60312015153580cc20f322e5cdc3d3ecad80a71743235bdb77716e742814623c", size = 7863 } +sdist = { url = "https://files.pythonhosted.org/packages/69/10/ce3f0d1157cedbd819194f0b27a6bbb7c19a8bceb3941e4a4775014076cf/opentelemetry_util_http-0.50b0.tar.gz", hash = "sha256:dc4606027e1bc02aabb9533cc330dd43f874fca492e4175c31d7154f341754af", size = 7859 } wheels = [ - { url = "https://files.pythonhosted.org/packages/ad/2e/36097c0a4d0115b8c7e377c90bab7783ac183bc5cb4071308f8959454311/opentelemetry_util_http-0.48b0-py3-none-any.whl", hash = "sha256:76f598af93aab50328d2a69c786beaedc8b6a7770f7a818cc307eb353debfffb", size = 6946 }, + { url = "https://files.pythonhosted.org/packages/64/8a/9e1b54f50d1fddebbeac9a9b0632f8db6ece7add904fb593ee2e268ee4de/opentelemetry_util_http-0.50b0-py3-none-any.whl", hash = "sha256:21f8aedac861ffa3b850f8c0a6c373026189eb8630ac6e14a2bf8c55695cc090", size = 6942 }, ] [[package]] name = "optuna" -version = "4.0.0" +version = "4.1.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "alembic" }, @@ -5237,9 +5223,9 @@ dependencies = [ { name = "sqlalchemy" }, { name = "tqdm" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/dc/0b/425040287cd9411db6708cfa5baf36acd9374f52caaca9f90da1f3f3b46b/optuna-4.0.0.tar.gz", hash = "sha256:844949f09e2a7353ab414e9cfd783cf0a647a65fc32a7236212ed6a37fe08973", size = 280224 } +sdist = { url = "https://files.pythonhosted.org/packages/6d/e0/52f8b3dfa4bd61e80778ec9f287fe5beafc11af31e6d4cb8f182634f5937/optuna-4.1.0.tar.gz", hash = "sha256:b364e87a2038f9946c5e2770c130597538aac528b4a82c1cab5267f337ea7679", size = 438362 } wheels = [ - { url = "https://files.pythonhosted.org/packages/4e/41/2a2f5ed6c997367ab7055185cf66d536c228b15a12b8e112a274808f48b5/optuna-4.0.0-py3-none-any.whl", hash = "sha256:a825c32d13f6085bcb2229b2724a5078f2e0f61a7533e800e580ce41a8c6c10d", size = 362751 }, + { url = "https://files.pythonhosted.org/packages/e8/30/35111dae435c640694d616a611b7ff6b2482cfd977f8f572ff960a321d66/optuna-4.1.0-py3-none-any.whl", hash = "sha256:1763856b01c9238594d9d21db92611aac9980e9a6300bd658a7c6464712c704e", size = 364429 }, ] [[package]] @@ -5356,15 +5342,15 @@ wheels = [ [[package]] name = "pandas-stubs" -version = "2.2.3.241009" +version = "2.2.3.241126" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "numpy" }, { name = "types-pytz" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/d4/30/1ca31098512cdcfbc6ce366072848dff497880d4285281606b5895244bbc/pandas_stubs-2.2.3.241009.tar.gz", hash = "sha256:d4ab618253f0acf78a5d0d2bfd6dffdd92d91a56a69bdc8144e5a5c6d25be3b5", size = 103801 } +sdist = { url = "https://files.pythonhosted.org/packages/90/86/93c545d149c3e1fe1c4c55478cc3a69859d0ea3467e1d9892e9eb28cb1e7/pandas_stubs-2.2.3.241126.tar.gz", hash = "sha256:cf819383c6d9ae7d4dabf34cd47e1e45525bb2f312e6ad2939c2c204cb708acd", size = 104204 } wheels = [ - { url = "https://files.pythonhosted.org/packages/a3/be/d9ba3109c4c19a78e125f63074c4e436e447f30ece15f0ef1865e7178233/pandas_stubs-2.2.3.241009-py3-none-any.whl", hash = "sha256:3a6f8f142105a42550be677ba741ba532621f4e0acad2155c0e7b2450f114cfa", size = 157883 }, + { url = "https://files.pythonhosted.org/packages/6f/ab/ed42acf15bab2e86e5c49fad4aa038315233c4c2d22f41b49faa4d837516/pandas_stubs-2.2.3.241126-py3-none-any.whl", hash = "sha256:74aa79c167af374fe97068acc90776c0ebec5266a6e5c69fe11e9c2cf51f2267", size = 158280 }, ] [[package]] @@ -5437,9 +5423,9 @@ wheels = [ [[package]] name = "peewee" -version = "3.17.6" +version = "3.17.8" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/bd/be/e9c886b4601a19f4c34a1b75c5fe8b98a2115dd964251a76b24c977c369d/peewee-3.17.6.tar.gz", hash = "sha256:cea5592c6f4da1592b7cff8eaf655be6648a1f5857469e30037bf920c03fb8fb", size = 2954075 } +sdist = { url = "https://files.pythonhosted.org/packages/b4/dc/832bcf4ea5ee2ebc4ea42ef36e44a451de5d80f8b9858bf2066e30738c67/peewee-3.17.8.tar.gz", hash = "sha256:ce1d05db3438830b989a1b9d0d0aa4e7f6134d5f6fd57686eeaa26a3e6485a8c", size = 948249 } [[package]] name = "pexpect" @@ -5598,7 +5584,7 @@ wheels = [ [[package]] name = "posthog" -version = "3.7.0" +version = "3.7.4" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "backoff" }, @@ -5607,9 +5593,9 @@ dependencies = [ { name = "requests" }, { name = "six" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/4c/7a/a6ab0d18f93255a4488196269ff53f2720821b169e1964cbf785d5f54b32/posthog-3.7.0.tar.gz", hash = "sha256:b095d4354ba23f8b346ab5daed8ecfc5108772f922006982dfe8b2d29ebc6e0e", size = 49661 } +sdist = { url = "https://files.pythonhosted.org/packages/77/a0/7607d4fd7c52b086671d8618e76cb5b9a642311fd6f352ebd7eb035319f2/posthog-3.7.4.tar.gz", hash = "sha256:19384bd09d330f9787a7e2446aba14c8057ece56144970ea2791072d4e40cd36", size = 50174 } wheels = [ - { url = "https://files.pythonhosted.org/packages/c2/11/a8d4283b324cda992fbb72611c46c5c68f87902a10383dba1bde91660cc6/posthog-3.7.0-py2.py3-none-any.whl", hash = "sha256:3555161c3a9557b5666f96d8e1f17f410ea0f07db56e399e336a1656d4e5c722", size = 54359 }, + { url = "https://files.pythonhosted.org/packages/d3/f2/5ee24cd69e2120bf87356c02ace0438b4e4fb78229fddcbf6f1c6be377d5/posthog-3.7.4-py2.py3-none-any.whl", hash = "sha256:21c18c6bf43b2de303ea4cd6e95804cc0f24c20cb2a96a8fd09da2ed50b62faa", size = 54777 }, ] [[package]] @@ -5630,27 +5616,27 @@ wheels = [ [[package]] name = "primp" -version = "0.8.2" +version = "0.8.3" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/5a/42/a7bb157e931a0c1782eb5631e84b04e91a07904bdd0041c6b7d5f627dd03/primp-0.8.2.tar.gz", hash = "sha256:572ecd34b77021a89a0574b66b07e1da100afd6ec490d3b519a6763fac6ae6c5", size = 81159 } +sdist = { url = "https://files.pythonhosted.org/packages/89/0e/250e2d49761e4c153029ba19ad6c20a7ff6d1f5fac09f77832c72bcc65b5/primp-0.8.3.tar.gz", hash = "sha256:c6bb6d0186dbfb2e4a1bda1c4bc676966378a9999ee877b7cb20f718c5a9b4ad", size = 84046 } wheels = [ - { url = "https://files.pythonhosted.org/packages/51/d9/fa6d03a70cad5094acbef50bc53463651615945693635b852aa1a17aee22/primp-0.8.2-cp38-abi3-macosx_10_12_x86_64.whl", hash = "sha256:20c4988c6538dfcac804e804f286493696e53498d5705e745a36d9fe436c787c", size = 2860119 }, - { url = "https://files.pythonhosted.org/packages/cb/d0/219f33260705b24d29f026ac2f25bf1fb0330ad8a7f7638be0589a0c67bd/primp-0.8.2-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:dde74d6bf5534a60fd075e81b5828a6591753a647c5bfe69e664883e5c7a28bb", size = 2687956 }, - { url = "https://files.pythonhosted.org/packages/c2/90/7f7ad8e2b5cecb4a93617566aaadd5f8dbf973fc047175ad7bf188a864c1/primp-0.8.2-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f988d7e47d7f63b63f851885d51abd86ba3a2a1981d047466c1e63827753a168", size = 2982835 }, - { url = "https://files.pythonhosted.org/packages/7a/f7/ca361d49397408eb8596d8df09e125e9c2c412ec54eb7a2c3b2f496a728e/primp-0.8.2-cp38-abi3-manylinux_2_34_aarch64.whl", hash = "sha256:965cf0c19986d074d4e20ce18f1b81e5c31818324718814af6317a291a3aba65", size = 2888443 }, - { url = "https://files.pythonhosted.org/packages/f0/16/71e3dab7e9bcd5116f831e1fb6fda4bbac3304b20a6e2275c2cedf22a5b7/primp-0.8.2-cp38-abi3-manylinux_2_34_armv7l.whl", hash = "sha256:afc56989ae09bed76105bf045e666ea2da5f32e2e93dfb967795a4da4fc777e5", size = 2689655 }, - { url = "https://files.pythonhosted.org/packages/cf/a6/829d4753ff32d8023a8272017fa87cc998984afe0ccc4a40f65421e3de4c/primp-0.8.2-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:64e8b9b216ee0f52d2885ac23303000339f798a59eb9b4b3b747dcbbf9187beb", size = 3051679 }, - { url = "https://files.pythonhosted.org/packages/11/ec/6e8d03acbea515ea55e50e462157fb11255059887022ef3619a945c39891/primp-0.8.2-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:b65de6d8fe4c7ef9d5d508e2a9cee3da77455e3a44c9282bdebb2134c55087c9", size = 3228264 }, - { url = "https://files.pythonhosted.org/packages/26/e8/048a315c37647a79b53a4cc1251b934d5a510d7864577bf278a650a2b880/primp-0.8.2-cp38-abi3-win_amd64.whl", hash = "sha256:d686cf4ce21c318bafe2f0574aec9f7f9526d18a4b0c017f507bd007f323e519", size = 2914407 }, + { url = "https://files.pythonhosted.org/packages/99/0f/dd83b552ac46f685622be68a2f4192fa5cb9d98744f380b84fbee5f1a47f/primp-0.8.3-cp38-abi3-macosx_10_12_x86_64.whl", hash = "sha256:3d06e374cfc4ecac7015d3125684e6ddfe28d5a866f9b15c59c8f452419c308e", size = 2875926 }, + { url = "https://files.pythonhosted.org/packages/7c/07/173550d9e3721abb0b8b69db035dfa4f6db55b4b7b4fbcb6b442d542fa8c/primp-0.8.3-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:6ac1ea7b9009f9355d5bfcbc48a20fa3efbf58e9fa0c495d7bd9ac8d03f71632", size = 2701580 }, + { url = "https://files.pythonhosted.org/packages/39/7f/379ab89cd8c507eb25695acb06c500e48e7d2e531b4b3c7b144a1196ddb6/primp-0.8.3-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ee54cf6a9bd2b3a826a03aef83bf4e3fdf63bcf2ae7c4ee2c6ee84d4b0581cd9", size = 2998096 }, + { url = "https://files.pythonhosted.org/packages/3e/0f/ebc173543e90595890e7bd33fba43e91d628578cd34af222dcab2b3d5700/primp-0.8.3-cp38-abi3-manylinux_2_34_aarch64.whl", hash = "sha256:ab2a28832d4ad76d4ec5adf0e768414a1ebe859cc769eae34c5c4183c5cea470", size = 2906820 }, + { url = "https://files.pythonhosted.org/packages/31/1a/80ffce955c355a2d62028a3ff178fec6fb53cf4747ef0930089eb74e161a/primp-0.8.3-cp38-abi3-manylinux_2_34_armv7l.whl", hash = "sha256:f698ad5aea4745d57365519c08305a5df31d7cf0b019377320747c57bdfbbc29", size = 2700105 }, + { url = "https://files.pythonhosted.org/packages/df/d8/e2517f045bc7c8b74fd92b18eedd100276bbf075ee7729dfdab1a6945368/primp-0.8.3-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:4e1a888b1f70402f0b70b516df02097e414e4df9111d1258b47b24023218cca5", size = 3066759 }, + { url = "https://files.pythonhosted.org/packages/c2/24/c19148df53c47b6f3c03cb9ec7dec5da104b7ac025af5a2b4e7edd034f28/primp-0.8.3-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:73ee00f8c403204ff920cc384036539281c045650ec98db3f64bff2204618fa6", size = 3240898 }, + { url = "https://files.pythonhosted.org/packages/56/d4/59725ab578572e506aebcde330825061729ebf016bf9de1cba2ffb273f7e/primp-0.8.3-cp38-abi3-win_amd64.whl", hash = "sha256:cc30d790eab0bb922c1342d3dfd80bec7f79f3163467904cf3d8e0e1ff0af4b3", size = 2926406 }, ] [[package]] name = "prometheus-client" -version = "0.21.0" +version = "0.21.1" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/e1/54/a369868ed7a7f1ea5163030f4fc07d85d22d7a1d270560dab675188fb612/prometheus_client-0.21.0.tar.gz", hash = "sha256:96c83c606b71ff2b0a433c98889d275f51ffec6c5e267de37c7a2b5c9aa9233e", size = 78634 } +sdist = { url = "https://files.pythonhosted.org/packages/62/14/7d0f567991f3a9af8d1cd4f619040c93b68f09a02b6d0b6ab1b2d1ded5fe/prometheus_client-0.21.1.tar.gz", hash = "sha256:252505a722ac04b0456be05c05f75f45d760c2911ffc45f2a06bcaed9f3ae3fb", size = 78551 } wheels = [ - { url = "https://files.pythonhosted.org/packages/84/2d/46ed6436849c2c88228c3111865f44311cff784b4aabcdef4ea2545dbc3d/prometheus_client-0.21.0-py3-none-any.whl", hash = "sha256:4fa6b4dd0ac16d58bb587c04b1caae65b8c5043e85f778f42f5f632f6af2e166", size = 54686 }, + { url = "https://files.pythonhosted.org/packages/ff/c2/ab7d37426c179ceb9aeb109a85cda8948bb269b7561a0be870cc656eefe4/prometheus_client-0.21.1-py3-none-any.whl", hash = "sha256:594b45c410d6f4f8888940fe80b5cc2521b305a1fafe1c58609ef715a001f301", size = 54682 }, ] [[package]] @@ -5667,100 +5653,100 @@ wheels = [ [[package]] name = "propcache" -version = "0.2.0" +version = "0.2.1" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/a9/4d/5e5a60b78dbc1d464f8a7bbaeb30957257afdc8512cbb9dfd5659304f5cd/propcache-0.2.0.tar.gz", hash = "sha256:df81779732feb9d01e5d513fad0122efb3d53bbc75f61b2a4f29a020bc985e70", size = 40951 } +sdist = { url = "https://files.pythonhosted.org/packages/20/c8/2a13f78d82211490855b2fb303b6721348d0787fdd9a12ac46d99d3acde1/propcache-0.2.1.tar.gz", hash = "sha256:3f77ce728b19cb537714499928fe800c3dda29e8d9428778fc7c186da4c09a64", size = 41735 } wheels = [ - { url = "https://files.pythonhosted.org/packages/3a/08/1963dfb932b8d74d5b09098507b37e9b96c835ba89ab8aad35aa330f4ff3/propcache-0.2.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:c5869b8fd70b81835a6f187c5fdbe67917a04d7e52b6e7cc4e5fe39d55c39d58", size = 80712 }, - { url = "https://files.pythonhosted.org/packages/e6/59/49072aba9bf8a8ed958e576182d46f038e595b17ff7408bc7e8807e721e1/propcache-0.2.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:952e0d9d07609d9c5be361f33b0d6d650cd2bae393aabb11d9b719364521984b", size = 46301 }, - { url = "https://files.pythonhosted.org/packages/33/a2/6b1978c2e0d80a678e2c483f45e5443c15fe5d32c483902e92a073314ef1/propcache-0.2.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:33ac8f098df0585c0b53009f039dfd913b38c1d2edafed0cedcc0c32a05aa110", size = 45581 }, - { url = "https://files.pythonhosted.org/packages/43/95/55acc9adff8f997c7572f23d41993042290dfb29e404cdadb07039a4386f/propcache-0.2.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:97e48e8875e6c13909c800fa344cd54cc4b2b0db1d5f911f840458a500fde2c2", size = 208659 }, - { url = "https://files.pythonhosted.org/packages/bd/2c/ef7371ff715e6cd19ea03fdd5637ecefbaa0752fee5b0f2fe8ea8407ee01/propcache-0.2.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:388f3217649d6d59292b722d940d4d2e1e6a7003259eb835724092a1cca0203a", size = 222613 }, - { url = "https://files.pythonhosted.org/packages/5e/1c/fef251f79fd4971a413fa4b1ae369ee07727b4cc2c71e2d90dfcde664fbb/propcache-0.2.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f571aea50ba5623c308aa146eb650eebf7dbe0fd8c5d946e28343cb3b5aad577", size = 221067 }, - { url = "https://files.pythonhosted.org/packages/8d/e7/22e76ae6fc5a1708bdce92bdb49de5ebe89a173db87e4ef597d6bbe9145a/propcache-0.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3dfafb44f7bb35c0c06eda6b2ab4bfd58f02729e7c4045e179f9a861b07c9850", size = 208920 }, - { url = "https://files.pythonhosted.org/packages/04/3e/f10aa562781bcd8a1e0b37683a23bef32bdbe501d9cc7e76969becaac30d/propcache-0.2.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a3ebe9a75be7ab0b7da2464a77bb27febcb4fab46a34f9288f39d74833db7f61", size = 200050 }, - { url = "https://files.pythonhosted.org/packages/d0/98/8ac69f638358c5f2a0043809c917802f96f86026e86726b65006830f3dc6/propcache-0.2.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:d2f0d0f976985f85dfb5f3d685697ef769faa6b71993b46b295cdbbd6be8cc37", size = 202346 }, - { url = "https://files.pythonhosted.org/packages/ee/78/4acfc5544a5075d8e660af4d4e468d60c418bba93203d1363848444511ad/propcache-0.2.0-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:a3dc1a4b165283bd865e8f8cb5f0c64c05001e0718ed06250d8cac9bec115b48", size = 199750 }, - { url = "https://files.pythonhosted.org/packages/a2/8f/90ada38448ca2e9cf25adc2fe05d08358bda1b9446f54a606ea38f41798b/propcache-0.2.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:9e0f07b42d2a50c7dd2d8675d50f7343d998c64008f1da5fef888396b7f84630", size = 201279 }, - { url = "https://files.pythonhosted.org/packages/08/31/0e299f650f73903da851f50f576ef09bfffc8e1519e6a2f1e5ed2d19c591/propcache-0.2.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:e63e3e1e0271f374ed489ff5ee73d4b6e7c60710e1f76af5f0e1a6117cd26394", size = 211035 }, - { url = "https://files.pythonhosted.org/packages/85/3e/e356cc6b09064bff1c06d0b2413593e7c925726f0139bc7acef8a21e87a8/propcache-0.2.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:56bb5c98f058a41bb58eead194b4db8c05b088c93d94d5161728515bd52b052b", size = 215565 }, - { url = "https://files.pythonhosted.org/packages/8b/54/4ef7236cd657e53098bd05aa59cbc3cbf7018fba37b40eaed112c3921e51/propcache-0.2.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7665f04d0c7f26ff8bb534e1c65068409bf4687aa2534faf7104d7182debb336", size = 207604 }, - { url = "https://files.pythonhosted.org/packages/1f/27/d01d7799c068443ee64002f0655d82fb067496897bf74b632e28ee6a32cf/propcache-0.2.0-cp310-cp310-win32.whl", hash = "sha256:7cf18abf9764746b9c8704774d8b06714bcb0a63641518a3a89c7f85cc02c2ad", size = 40526 }, - { url = "https://files.pythonhosted.org/packages/bb/44/6c2add5eeafb7f31ff0d25fbc005d930bea040a1364cf0f5768750ddf4d1/propcache-0.2.0-cp310-cp310-win_amd64.whl", hash = "sha256:cfac69017ef97db2438efb854edf24f5a29fd09a536ff3a992b75990720cdc99", size = 44958 }, - { url = "https://files.pythonhosted.org/packages/e0/1c/71eec730e12aec6511e702ad0cd73c2872eccb7cad39de8ba3ba9de693ef/propcache-0.2.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:63f13bf09cc3336eb04a837490b8f332e0db41da66995c9fd1ba04552e516354", size = 80811 }, - { url = "https://files.pythonhosted.org/packages/89/c3/7e94009f9a4934c48a371632197406a8860b9f08e3f7f7d922ab69e57a41/propcache-0.2.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:608cce1da6f2672a56b24a015b42db4ac612ee709f3d29f27a00c943d9e851de", size = 46365 }, - { url = "https://files.pythonhosted.org/packages/c0/1d/c700d16d1d6903aeab28372fe9999762f074b80b96a0ccc953175b858743/propcache-0.2.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:466c219deee4536fbc83c08d09115249db301550625c7fef1c5563a584c9bc87", size = 45602 }, - { url = "https://files.pythonhosted.org/packages/2e/5e/4a3e96380805bf742712e39a4534689f4cddf5fa2d3a93f22e9fd8001b23/propcache-0.2.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fc2db02409338bf36590aa985a461b2c96fce91f8e7e0f14c50c5fcc4f229016", size = 236161 }, - { url = "https://files.pythonhosted.org/packages/a5/85/90132481183d1436dff6e29f4fa81b891afb6cb89a7306f32ac500a25932/propcache-0.2.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a6ed8db0a556343d566a5c124ee483ae113acc9a557a807d439bcecc44e7dfbb", size = 244938 }, - { url = "https://files.pythonhosted.org/packages/4a/89/c893533cb45c79c970834274e2d0f6d64383ec740be631b6a0a1d2b4ddc0/propcache-0.2.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:91997d9cb4a325b60d4e3f20967f8eb08dfcb32b22554d5ef78e6fd1dda743a2", size = 243576 }, - { url = "https://files.pythonhosted.org/packages/8c/56/98c2054c8526331a05f205bf45cbb2cda4e58e56df70e76d6a509e5d6ec6/propcache-0.2.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4c7dde9e533c0a49d802b4f3f218fa9ad0a1ce21f2c2eb80d5216565202acab4", size = 236011 }, - { url = "https://files.pythonhosted.org/packages/2d/0c/8b8b9f8a6e1abd869c0fa79b907228e7abb966919047d294ef5df0d136cf/propcache-0.2.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ffcad6c564fe6b9b8916c1aefbb37a362deebf9394bd2974e9d84232e3e08504", size = 224834 }, - { url = "https://files.pythonhosted.org/packages/18/bb/397d05a7298b7711b90e13108db697732325cafdcd8484c894885c1bf109/propcache-0.2.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:97a58a28bcf63284e8b4d7b460cbee1edaab24634e82059c7b8c09e65284f178", size = 224946 }, - { url = "https://files.pythonhosted.org/packages/25/19/4fc08dac19297ac58135c03770b42377be211622fd0147f015f78d47cd31/propcache-0.2.0-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:945db8ee295d3af9dbdbb698cce9bbc5c59b5c3fe328bbc4387f59a8a35f998d", size = 217280 }, - { url = "https://files.pythonhosted.org/packages/7e/76/c79276a43df2096ce2aba07ce47576832b1174c0c480fe6b04bd70120e59/propcache-0.2.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:39e104da444a34830751715f45ef9fc537475ba21b7f1f5b0f4d71a3b60d7fe2", size = 220088 }, - { url = "https://files.pythonhosted.org/packages/c3/9a/8a8cf428a91b1336b883f09c8b884e1734c87f724d74b917129a24fe2093/propcache-0.2.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:c5ecca8f9bab618340c8e848d340baf68bcd8ad90a8ecd7a4524a81c1764b3db", size = 233008 }, - { url = "https://files.pythonhosted.org/packages/25/7b/768a8969abd447d5f0f3333df85c6a5d94982a1bc9a89c53c154bf7a8b11/propcache-0.2.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:c436130cc779806bdf5d5fae0d848713105472b8566b75ff70048c47d3961c5b", size = 237719 }, - { url = "https://files.pythonhosted.org/packages/ed/0d/e5d68ccc7976ef8b57d80613ac07bbaf0614d43f4750cf953f0168ef114f/propcache-0.2.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:191db28dc6dcd29d1a3e063c3be0b40688ed76434622c53a284e5427565bbd9b", size = 227729 }, - { url = "https://files.pythonhosted.org/packages/05/64/17eb2796e2d1c3d0c431dc5f40078d7282f4645af0bb4da9097fbb628c6c/propcache-0.2.0-cp311-cp311-win32.whl", hash = "sha256:5f2564ec89058ee7c7989a7b719115bdfe2a2fb8e7a4543b8d1c0cc4cf6478c1", size = 40473 }, - { url = "https://files.pythonhosted.org/packages/83/c5/e89fc428ccdc897ade08cd7605f174c69390147526627a7650fb883e0cd0/propcache-0.2.0-cp311-cp311-win_amd64.whl", hash = "sha256:6e2e54267980349b723cff366d1e29b138b9a60fa376664a157a342689553f71", size = 44921 }, - { url = "https://files.pythonhosted.org/packages/7c/46/a41ca1097769fc548fc9216ec4c1471b772cc39720eb47ed7e38ef0006a9/propcache-0.2.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:2ee7606193fb267be4b2e3b32714f2d58cad27217638db98a60f9efb5efeccc2", size = 80800 }, - { url = "https://files.pythonhosted.org/packages/75/4f/93df46aab9cc473498ff56be39b5f6ee1e33529223d7a4d8c0a6101a9ba2/propcache-0.2.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:91ee8fc02ca52e24bcb77b234f22afc03288e1dafbb1f88fe24db308910c4ac7", size = 46443 }, - { url = "https://files.pythonhosted.org/packages/0b/17/308acc6aee65d0f9a8375e36c4807ac6605d1f38074b1581bd4042b9fb37/propcache-0.2.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:2e900bad2a8456d00a113cad8c13343f3b1f327534e3589acc2219729237a2e8", size = 45676 }, - { url = "https://files.pythonhosted.org/packages/65/44/626599d2854d6c1d4530b9a05e7ff2ee22b790358334b475ed7c89f7d625/propcache-0.2.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f52a68c21363c45297aca15561812d542f8fc683c85201df0bebe209e349f793", size = 246191 }, - { url = "https://files.pythonhosted.org/packages/f2/df/5d996d7cb18df076debae7d76ac3da085c0575a9f2be6b1f707fe227b54c/propcache-0.2.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1e41d67757ff4fbc8ef2af99b338bfb955010444b92929e9e55a6d4dcc3c4f09", size = 251791 }, - { url = "https://files.pythonhosted.org/packages/2e/6d/9f91e5dde8b1f662f6dd4dff36098ed22a1ef4e08e1316f05f4758f1576c/propcache-0.2.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a64e32f8bd94c105cc27f42d3b658902b5bcc947ece3c8fe7bc1b05982f60e89", size = 253434 }, - { url = "https://files.pythonhosted.org/packages/3c/e9/1b54b7e26f50b3e0497cd13d3483d781d284452c2c50dd2a615a92a087a3/propcache-0.2.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:55346705687dbd7ef0d77883ab4f6fabc48232f587925bdaf95219bae072491e", size = 248150 }, - { url = "https://files.pythonhosted.org/packages/a7/ef/a35bf191c8038fe3ce9a414b907371c81d102384eda5dbafe6f4dce0cf9b/propcache-0.2.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:00181262b17e517df2cd85656fcd6b4e70946fe62cd625b9d74ac9977b64d8d9", size = 233568 }, - { url = "https://files.pythonhosted.org/packages/97/d9/d00bb9277a9165a5e6d60f2142cd1a38a750045c9c12e47ae087f686d781/propcache-0.2.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:6994984550eaf25dd7fc7bd1b700ff45c894149341725bb4edc67f0ffa94efa4", size = 229874 }, - { url = "https://files.pythonhosted.org/packages/8e/78/c123cf22469bdc4b18efb78893e69c70a8b16de88e6160b69ca6bdd88b5d/propcache-0.2.0-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:56295eb1e5f3aecd516d91b00cfd8bf3a13991de5a479df9e27dd569ea23959c", size = 225857 }, - { url = "https://files.pythonhosted.org/packages/31/1b/fd6b2f1f36d028820d35475be78859d8c89c8f091ad30e377ac49fd66359/propcache-0.2.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:439e76255daa0f8151d3cb325f6dd4a3e93043e6403e6491813bcaaaa8733887", size = 227604 }, - { url = "https://files.pythonhosted.org/packages/99/36/b07be976edf77a07233ba712e53262937625af02154353171716894a86a6/propcache-0.2.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:f6475a1b2ecb310c98c28d271a30df74f9dd436ee46d09236a6b750a7599ce57", size = 238430 }, - { url = "https://files.pythonhosted.org/packages/0d/64/5822f496c9010e3966e934a011ac08cac8734561842bc7c1f65586e0683c/propcache-0.2.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:3444cdba6628accf384e349014084b1cacd866fbb88433cd9d279d90a54e0b23", size = 244814 }, - { url = "https://files.pythonhosted.org/packages/fd/bd/8657918a35d50b18a9e4d78a5df7b6c82a637a311ab20851eef4326305c1/propcache-0.2.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:4a9d9b4d0a9b38d1c391bb4ad24aa65f306c6f01b512e10a8a34a2dc5675d348", size = 235922 }, - { url = "https://files.pythonhosted.org/packages/a8/6f/ec0095e1647b4727db945213a9f395b1103c442ef65e54c62e92a72a3f75/propcache-0.2.0-cp312-cp312-win32.whl", hash = "sha256:69d3a98eebae99a420d4b28756c8ce6ea5a29291baf2dc9ff9414b42676f61d5", size = 40177 }, - { url = "https://files.pythonhosted.org/packages/20/a2/bd0896fdc4f4c1db46d9bc361c8c79a9bf08ccc08ba054a98e38e7ba1557/propcache-0.2.0-cp312-cp312-win_amd64.whl", hash = "sha256:ad9c9b99b05f163109466638bd30ada1722abb01bbb85c739c50b6dc11f92dc3", size = 44446 }, - { url = "https://files.pythonhosted.org/packages/3d/b6/e6d98278f2d49b22b4d033c9f792eda783b9ab2094b041f013fc69bcde87/propcache-0.2.0-py3-none-any.whl", hash = "sha256:2ccc28197af5313706511fab3a8b66dcd6da067a1331372c82ea1cb74285e036", size = 11603 }, + { url = "https://files.pythonhosted.org/packages/a7/a5/0ea64c9426959ef145a938e38c832fc551843481d356713ececa9a8a64e8/propcache-0.2.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:6b3f39a85d671436ee3d12c017f8fdea38509e4f25b28eb25877293c98c243f6", size = 79296 }, + { url = "https://files.pythonhosted.org/packages/76/5a/916db1aba735f55e5eca4733eea4d1973845cf77dfe67c2381a2ca3ce52d/propcache-0.2.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:39d51fbe4285d5db5d92a929e3e21536ea3dd43732c5b177c7ef03f918dff9f2", size = 45622 }, + { url = "https://files.pythonhosted.org/packages/2d/62/685d3cf268b8401ec12b250b925b21d152b9d193b7bffa5fdc4815c392c2/propcache-0.2.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:6445804cf4ec763dc70de65a3b0d9954e868609e83850a47ca4f0cb64bd79fea", size = 45133 }, + { url = "https://files.pythonhosted.org/packages/4d/3d/31c9c29ee7192defc05aa4d01624fd85a41cf98e5922aaed206017329944/propcache-0.2.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f9479aa06a793c5aeba49ce5c5692ffb51fcd9a7016e017d555d5e2b0045d212", size = 204809 }, + { url = "https://files.pythonhosted.org/packages/10/a1/e4050776f4797fc86140ac9a480d5dc069fbfa9d499fe5c5d2fa1ae71f07/propcache-0.2.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d9631c5e8b5b3a0fda99cb0d29c18133bca1e18aea9effe55adb3da1adef80d3", size = 219109 }, + { url = "https://files.pythonhosted.org/packages/c9/c0/e7ae0df76343d5e107d81e59acc085cea5fd36a48aa53ef09add7503e888/propcache-0.2.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3156628250f46a0895f1f36e1d4fbe062a1af8718ec3ebeb746f1d23f0c5dc4d", size = 217368 }, + { url = "https://files.pythonhosted.org/packages/fc/e1/e0a2ed6394b5772508868a977d3238f4afb2eebaf9976f0b44a8d347ad63/propcache-0.2.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6b6fb63ae352e13748289f04f37868099e69dba4c2b3e271c46061e82c745634", size = 205124 }, + { url = "https://files.pythonhosted.org/packages/50/c1/e388c232d15ca10f233c778bbdc1034ba53ede14c207a72008de45b2db2e/propcache-0.2.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:887d9b0a65404929641a9fabb6452b07fe4572b269d901d622d8a34a4e9043b2", size = 195463 }, + { url = "https://files.pythonhosted.org/packages/0a/fd/71b349b9def426cc73813dbd0f33e266de77305e337c8c12bfb0a2a82bfb/propcache-0.2.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:a96dc1fa45bd8c407a0af03b2d5218392729e1822b0c32e62c5bf7eeb5fb3958", size = 198358 }, + { url = "https://files.pythonhosted.org/packages/02/f2/d7c497cd148ebfc5b0ae32808e6c1af5922215fe38c7a06e4e722fe937c8/propcache-0.2.1-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:a7e65eb5c003a303b94aa2c3852ef130230ec79e349632d030e9571b87c4698c", size = 195560 }, + { url = "https://files.pythonhosted.org/packages/bb/57/f37041bbe5e0dfed80a3f6be2612a3a75b9cfe2652abf2c99bef3455bbad/propcache-0.2.1-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:999779addc413181912e984b942fbcc951be1f5b3663cd80b2687758f434c583", size = 196895 }, + { url = "https://files.pythonhosted.org/packages/83/36/ae3cc3e4f310bff2f064e3d2ed5558935cc7778d6f827dce74dcfa125304/propcache-0.2.1-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:19a0f89a7bb9d8048d9c4370c9c543c396e894c76be5525f5e1ad287f1750ddf", size = 207124 }, + { url = "https://files.pythonhosted.org/packages/8c/c4/811b9f311f10ce9d31a32ff14ce58500458443627e4df4ae9c264defba7f/propcache-0.2.1-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:1ac2f5fe02fa75f56e1ad473f1175e11f475606ec9bd0be2e78e4734ad575034", size = 210442 }, + { url = "https://files.pythonhosted.org/packages/18/dd/a1670d483a61ecac0d7fc4305d91caaac7a8fc1b200ea3965a01cf03bced/propcache-0.2.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:574faa3b79e8ebac7cb1d7930f51184ba1ccf69adfdec53a12f319a06030a68b", size = 203219 }, + { url = "https://files.pythonhosted.org/packages/f9/2d/30ced5afde41b099b2dc0c6573b66b45d16d73090e85655f1a30c5a24e07/propcache-0.2.1-cp310-cp310-win32.whl", hash = "sha256:03ff9d3f665769b2a85e6157ac8b439644f2d7fd17615a82fa55739bc97863f4", size = 40313 }, + { url = "https://files.pythonhosted.org/packages/23/84/bd9b207ac80da237af77aa6e153b08ffa83264b1c7882495984fcbfcf85c/propcache-0.2.1-cp310-cp310-win_amd64.whl", hash = "sha256:2d3af2e79991102678f53e0dbf4c35de99b6b8b58f29a27ca0325816364caaba", size = 44428 }, + { url = "https://files.pythonhosted.org/packages/bc/0f/2913b6791ebefb2b25b4efd4bb2299c985e09786b9f5b19184a88e5778dd/propcache-0.2.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:1ffc3cca89bb438fb9c95c13fc874012f7b9466b89328c3c8b1aa93cdcfadd16", size = 79297 }, + { url = "https://files.pythonhosted.org/packages/cf/73/af2053aeccd40b05d6e19058419ac77674daecdd32478088b79375b9ab54/propcache-0.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:f174bbd484294ed9fdf09437f889f95807e5f229d5d93588d34e92106fbf6717", size = 45611 }, + { url = "https://files.pythonhosted.org/packages/3c/09/8386115ba7775ea3b9537730e8cf718d83bbf95bffe30757ccf37ec4e5da/propcache-0.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:70693319e0b8fd35dd863e3e29513875eb15c51945bf32519ef52927ca883bc3", size = 45146 }, + { url = "https://files.pythonhosted.org/packages/03/7a/793aa12f0537b2e520bf09f4c6833706b63170a211ad042ca71cbf79d9cb/propcache-0.2.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b480c6a4e1138e1aa137c0079b9b6305ec6dcc1098a8ca5196283e8a49df95a9", size = 232136 }, + { url = "https://files.pythonhosted.org/packages/f1/38/b921b3168d72111769f648314100558c2ea1d52eb3d1ba7ea5c4aa6f9848/propcache-0.2.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d27b84d5880f6d8aa9ae3edb253c59d9f6642ffbb2c889b78b60361eed449787", size = 239706 }, + { url = "https://files.pythonhosted.org/packages/14/29/4636f500c69b5edea7786db3c34eb6166f3384b905665ce312a6e42c720c/propcache-0.2.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:857112b22acd417c40fa4595db2fe28ab900c8c5fe4670c7989b1c0230955465", size = 238531 }, + { url = "https://files.pythonhosted.org/packages/85/14/01fe53580a8e1734ebb704a3482b7829a0ef4ea68d356141cf0994d9659b/propcache-0.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cf6c4150f8c0e32d241436526f3c3f9cbd34429492abddbada2ffcff506c51af", size = 231063 }, + { url = "https://files.pythonhosted.org/packages/33/5c/1d961299f3c3b8438301ccfbff0143b69afcc30c05fa28673cface692305/propcache-0.2.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:66d4cfda1d8ed687daa4bc0274fcfd5267873db9a5bc0418c2da19273040eeb7", size = 220134 }, + { url = "https://files.pythonhosted.org/packages/00/d0/ed735e76db279ba67a7d3b45ba4c654e7b02bc2f8050671ec365d8665e21/propcache-0.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:c2f992c07c0fca81655066705beae35fc95a2fa7366467366db627d9f2ee097f", size = 220009 }, + { url = "https://files.pythonhosted.org/packages/75/90/ee8fab7304ad6533872fee982cfff5a53b63d095d78140827d93de22e2d4/propcache-0.2.1-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:4a571d97dbe66ef38e472703067021b1467025ec85707d57e78711c085984e54", size = 212199 }, + { url = "https://files.pythonhosted.org/packages/eb/ec/977ffaf1664f82e90737275873461695d4c9407d52abc2f3c3e24716da13/propcache-0.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:bb6178c241278d5fe853b3de743087be7f5f4c6f7d6d22a3b524d323eecec505", size = 214827 }, + { url = "https://files.pythonhosted.org/packages/57/48/031fb87ab6081764054821a71b71942161619549396224cbb242922525e8/propcache-0.2.1-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:ad1af54a62ffe39cf34db1aa6ed1a1873bd548f6401db39d8e7cd060b9211f82", size = 228009 }, + { url = "https://files.pythonhosted.org/packages/1a/06/ef1390f2524850838f2390421b23a8b298f6ce3396a7cc6d39dedd4047b0/propcache-0.2.1-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:e7048abd75fe40712005bcfc06bb44b9dfcd8e101dda2ecf2f5aa46115ad07ca", size = 231638 }, + { url = "https://files.pythonhosted.org/packages/38/2a/101e6386d5a93358395da1d41642b79c1ee0f3b12e31727932b069282b1d/propcache-0.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:160291c60081f23ee43d44b08a7e5fb76681221a8e10b3139618c5a9a291b84e", size = 222788 }, + { url = "https://files.pythonhosted.org/packages/db/81/786f687951d0979007e05ad9346cd357e50e3d0b0f1a1d6074df334b1bbb/propcache-0.2.1-cp311-cp311-win32.whl", hash = "sha256:819ce3b883b7576ca28da3861c7e1a88afd08cc8c96908e08a3f4dd64a228034", size = 40170 }, + { url = "https://files.pythonhosted.org/packages/cf/59/7cc7037b295d5772eceb426358bb1b86e6cab4616d971bd74275395d100d/propcache-0.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:edc9fc7051e3350643ad929df55c451899bb9ae6d24998a949d2e4c87fb596d3", size = 44404 }, + { url = "https://files.pythonhosted.org/packages/4c/28/1d205fe49be8b1b4df4c50024e62480a442b1a7b818e734308bb0d17e7fb/propcache-0.2.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:081a430aa8d5e8876c6909b67bd2d937bfd531b0382d3fdedb82612c618bc41a", size = 79588 }, + { url = "https://files.pythonhosted.org/packages/21/ee/fc4d893f8d81cd4971affef2a6cb542b36617cd1d8ce56b406112cb80bf7/propcache-0.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:d2ccec9ac47cf4e04897619c0e0c1a48c54a71bdf045117d3a26f80d38ab1fb0", size = 45825 }, + { url = "https://files.pythonhosted.org/packages/4a/de/bbe712f94d088da1d237c35d735f675e494a816fd6f54e9db2f61ef4d03f/propcache-0.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:14d86fe14b7e04fa306e0c43cdbeebe6b2c2156a0c9ce56b815faacc193e320d", size = 45357 }, + { url = "https://files.pythonhosted.org/packages/7f/14/7ae06a6cf2a2f1cb382586d5a99efe66b0b3d0c6f9ac2f759e6f7af9d7cf/propcache-0.2.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:049324ee97bb67285b49632132db351b41e77833678432be52bdd0289c0e05e4", size = 241869 }, + { url = "https://files.pythonhosted.org/packages/cc/59/227a78be960b54a41124e639e2c39e8807ac0c751c735a900e21315f8c2b/propcache-0.2.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1cd9a1d071158de1cc1c71a26014dcdfa7dd3d5f4f88c298c7f90ad6f27bb46d", size = 247884 }, + { url = "https://files.pythonhosted.org/packages/84/58/f62b4ffaedf88dc1b17f04d57d8536601e4e030feb26617228ef930c3279/propcache-0.2.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:98110aa363f1bb4c073e8dcfaefd3a5cea0f0834c2aab23dda657e4dab2f53b5", size = 248486 }, + { url = "https://files.pythonhosted.org/packages/1c/07/ebe102777a830bca91bbb93e3479cd34c2ca5d0361b83be9dbd93104865e/propcache-0.2.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:647894f5ae99c4cf6bb82a1bb3a796f6e06af3caa3d32e26d2350d0e3e3faf24", size = 243649 }, + { url = "https://files.pythonhosted.org/packages/ed/bc/4f7aba7f08f520376c4bb6a20b9a981a581b7f2e385fa0ec9f789bb2d362/propcache-0.2.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:bfd3223c15bebe26518d58ccf9a39b93948d3dcb3e57a20480dfdd315356baff", size = 229103 }, + { url = "https://files.pythonhosted.org/packages/fe/d5/04ac9cd4e51a57a96f78795e03c5a0ddb8f23ec098b86f92de028d7f2a6b/propcache-0.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:d71264a80f3fcf512eb4f18f59423fe82d6e346ee97b90625f283df56aee103f", size = 226607 }, + { url = "https://files.pythonhosted.org/packages/e3/f0/24060d959ea41d7a7cc7fdbf68b31852331aabda914a0c63bdb0e22e96d6/propcache-0.2.1-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:e73091191e4280403bde6c9a52a6999d69cdfde498f1fdf629105247599b57ec", size = 221153 }, + { url = "https://files.pythonhosted.org/packages/77/a7/3ac76045a077b3e4de4859a0753010765e45749bdf53bd02bc4d372da1a0/propcache-0.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:3935bfa5fede35fb202c4b569bb9c042f337ca4ff7bd540a0aa5e37131659348", size = 222151 }, + { url = "https://files.pythonhosted.org/packages/e7/af/5e29da6f80cebab3f5a4dcd2a3240e7f56f2c4abf51cbfcc99be34e17f0b/propcache-0.2.1-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:f508b0491767bb1f2b87fdfacaba5f7eddc2f867740ec69ece6d1946d29029a6", size = 233812 }, + { url = "https://files.pythonhosted.org/packages/8c/89/ebe3ad52642cc5509eaa453e9f4b94b374d81bae3265c59d5c2d98efa1b4/propcache-0.2.1-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:1672137af7c46662a1c2be1e8dc78cb6d224319aaa40271c9257d886be4363a6", size = 238829 }, + { url = "https://files.pythonhosted.org/packages/e9/2f/6b32f273fa02e978b7577159eae7471b3cfb88b48563b1c2578b2d7ca0bb/propcache-0.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b74c261802d3d2b85c9df2dfb2fa81b6f90deeef63c2db9f0e029a3cac50b518", size = 230704 }, + { url = "https://files.pythonhosted.org/packages/5c/2e/f40ae6ff5624a5f77edd7b8359b208b5455ea113f68309e2b00a2e1426b6/propcache-0.2.1-cp312-cp312-win32.whl", hash = "sha256:d09c333d36c1409d56a9d29b3a1b800a42c76a57a5a8907eacdbce3f18768246", size = 40050 }, + { url = "https://files.pythonhosted.org/packages/3b/77/a92c3ef994e47180862b9d7d11e37624fb1c00a16d61faf55115d970628b/propcache-0.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:c214999039d4f2a5b2073ac506bba279945233da8c786e490d411dfc30f855c1", size = 44117 }, + { url = "https://files.pythonhosted.org/packages/41/b6/c5319caea262f4821995dca2107483b94a3345d4607ad797c76cb9c36bcc/propcache-0.2.1-py3-none-any.whl", hash = "sha256:52277518d6aae65536e9cea52d4e7fd2f7a66f4aa2d30ed3f2fcea620ace3c54", size = 11818 }, ] [[package]] name = "proto-plus" -version = "1.24.0" +version = "1.25.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "protobuf" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/3e/fc/e9a65cd52c1330d8d23af6013651a0bc50b6d76bcbdf91fae7cd19c68f29/proto-plus-1.24.0.tar.gz", hash = "sha256:30b72a5ecafe4406b0d339db35b56c4059064e69227b8c3bda7462397f966445", size = 55942 } +sdist = { url = "https://files.pythonhosted.org/packages/7e/05/74417b2061e1bf1b82776037cad97094228fa1c1b6e82d08a78d3fb6ddb6/proto_plus-1.25.0.tar.gz", hash = "sha256:fbb17f57f7bd05a68b7707e745e26528b0b3c34e378db91eef93912c54982d91", size = 56124 } wheels = [ - { url = "https://files.pythonhosted.org/packages/7c/6f/db31f0711c0402aa477257205ce7d29e86a75cb52cd19f7afb585f75cda0/proto_plus-1.24.0-py3-none-any.whl", hash = "sha256:402576830425e5f6ce4c2a6702400ac79897dab0b4343821aa5188b0fab81a12", size = 50080 }, + { url = "https://files.pythonhosted.org/packages/dd/25/0b7cc838ae3d76d46539020ec39fc92bfc9acc29367e58fe912702c2a79e/proto_plus-1.25.0-py3-none-any.whl", hash = "sha256:c91fc4a65074ade8e458e95ef8bac34d4008daa7cce4a12d6707066fca648961", size = 50126 }, ] [[package]] name = "protobuf" -version = "4.25.5" +version = "5.29.1" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/67/dd/48d5fdb68ec74d70fabcc252e434492e56f70944d9f17b6a15e3746d2295/protobuf-4.25.5.tar.gz", hash = "sha256:7f8249476b4a9473645db7f8ab42b02fe1488cbe5fb72fddd445e0665afd8584", size = 380315 } +sdist = { url = "https://files.pythonhosted.org/packages/d2/4f/1639b7b1633d8fd55f216ba01e21bf2c43384ab25ef3ddb35d85a52033e8/protobuf-5.29.1.tar.gz", hash = "sha256:683be02ca21a6ffe80db6dd02c0b5b2892322c59ca57fd6c872d652cb80549cb", size = 424965 } wheels = [ - { url = "https://files.pythonhosted.org/packages/00/35/1b3c5a5e6107859c4ca902f4fbb762e48599b78129a05d20684fef4a4d04/protobuf-4.25.5-cp310-abi3-win32.whl", hash = "sha256:5e61fd921603f58d2f5acb2806a929b4675f8874ff5f330b7d6f7e2e784bbcd8", size = 392457 }, - { url = "https://files.pythonhosted.org/packages/a7/ad/bf3f358e90b7e70bf7fb520702cb15307ef268262292d3bdb16ad8ebc815/protobuf-4.25.5-cp310-abi3-win_amd64.whl", hash = "sha256:4be0571adcbe712b282a330c6e89eae24281344429ae95c6d85e79e84780f5ea", size = 413449 }, - { url = "https://files.pythonhosted.org/packages/51/49/d110f0a43beb365758a252203c43eaaad169fe7749da918869a8c991f726/protobuf-4.25.5-cp37-abi3-macosx_10_9_universal2.whl", hash = "sha256:b2fde3d805354df675ea4c7c6338c1aecd254dfc9925e88c6d31a2bcb97eb173", size = 394248 }, - { url = "https://files.pythonhosted.org/packages/c6/ab/0f384ca0bc6054b1a7b6009000ab75d28a5506e4459378b81280ae7fd358/protobuf-4.25.5-cp37-abi3-manylinux2014_aarch64.whl", hash = "sha256:919ad92d9b0310070f8356c24b855c98df2b8bd207ebc1c0c6fcc9ab1e007f3d", size = 293717 }, - { url = "https://files.pythonhosted.org/packages/05/a6/094a2640be576d760baa34c902dcb8199d89bce9ed7dd7a6af74dcbbd62d/protobuf-4.25.5-cp37-abi3-manylinux2014_x86_64.whl", hash = "sha256:fe14e16c22be926d3abfcb500e60cab068baf10b542b8c858fa27e098123e331", size = 294635 }, - { url = "https://files.pythonhosted.org/packages/33/90/f198a61df8381fb43ae0fe81b3d2718e8dcc51ae8502c7657ab9381fbc4f/protobuf-4.25.5-py3-none-any.whl", hash = "sha256:0aebecb809cae990f8129ada5ca273d9d670b76d9bfc9b1809f0a9c02b7dbf41", size = 156467 }, + { url = "https://files.pythonhosted.org/packages/50/c7/28669b04691a376cf7d0617d612f126aa0fff763d57df0142f9bf474c5b8/protobuf-5.29.1-cp310-abi3-win32.whl", hash = "sha256:22c1f539024241ee545cbcb00ee160ad1877975690b16656ff87dde107b5f110", size = 422706 }, + { url = "https://files.pythonhosted.org/packages/e3/33/dc7a7712f457456b7e0b16420ab8ba1cc8686751d3f28392eb43d0029ab9/protobuf-5.29.1-cp310-abi3-win_amd64.whl", hash = "sha256:1fc55267f086dd4050d18ef839d7bd69300d0d08c2a53ca7df3920cc271a3c34", size = 434505 }, + { url = "https://files.pythonhosted.org/packages/e5/39/44239fb1c6ec557e1731d996a5de89a9eb1ada7a92491fcf9c5d714052ed/protobuf-5.29.1-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:d473655e29c0c4bbf8b69e9a8fb54645bc289dead6d753b952e7aa660254ae18", size = 417822 }, + { url = "https://files.pythonhosted.org/packages/fb/4a/ec56f101d38d4bef2959a9750209809242d86cf8b897db00f2f98bfa360e/protobuf-5.29.1-cp38-abi3-manylinux2014_aarch64.whl", hash = "sha256:b5ba1d0e4c8a40ae0496d0e2ecfdbb82e1776928a205106d14ad6985a09ec155", size = 319572 }, + { url = "https://files.pythonhosted.org/packages/04/52/c97c58a33b3d6c89a8138788576d372a90a6556f354799971c6b4d16d871/protobuf-5.29.1-cp38-abi3-manylinux2014_x86_64.whl", hash = "sha256:8ee1461b3af56145aca2800e6a3e2f928108c749ba8feccc6f5dd0062c410c0d", size = 319671 }, + { url = "https://files.pythonhosted.org/packages/3b/24/c8c49df8f6587719e1d400109b16c10c6902d0c9adddc8fff82840146f99/protobuf-5.29.1-py3-none-any.whl", hash = "sha256:32600ddb9c2a53dedc25b8581ea0f1fd8ea04956373c0c07577ce58d312522e0", size = 172547 }, ] [[package]] name = "psutil" -version = "6.0.0" +version = "6.1.0" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/18/c7/8c6872f7372eb6a6b2e4708b88419fb46b857f7a2e1892966b851cc79fc9/psutil-6.0.0.tar.gz", hash = "sha256:8faae4f310b6d969fa26ca0545338b21f73c6b15db7c4a8d934a5482faa818f2", size = 508067 } +sdist = { url = "https://files.pythonhosted.org/packages/26/10/2a30b13c61e7cf937f4adf90710776b7918ed0a9c434e2c38224732af310/psutil-6.1.0.tar.gz", hash = "sha256:353815f59a7f64cdaca1c0307ee13558a0512f6db064e92fe833784f08539c7a", size = 508565 } wheels = [ - { url = "https://files.pythonhosted.org/packages/0b/37/f8da2fbd29690b3557cca414c1949f92162981920699cd62095a984983bf/psutil-6.0.0-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:c588a7e9b1173b6e866756dde596fd4cad94f9399daf99ad8c3258b3cb2b47a0", size = 250961 }, - { url = "https://files.pythonhosted.org/packages/35/56/72f86175e81c656a01c4401cd3b1c923f891b31fbcebe98985894176d7c9/psutil-6.0.0-cp36-abi3-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6ed2440ada7ef7d0d608f20ad89a04ec47d2d3ab7190896cd62ca5fc4fe08bf0", size = 287478 }, - { url = "https://files.pythonhosted.org/packages/19/74/f59e7e0d392bc1070e9a70e2f9190d652487ac115bb16e2eff6b22ad1d24/psutil-6.0.0-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5fd9a97c8e94059b0ef54a7d4baf13b405011176c3b6ff257c247cae0d560ecd", size = 290455 }, - { url = "https://files.pythonhosted.org/packages/cd/5f/60038e277ff0a9cc8f0c9ea3d0c5eb6ee1d2470ea3f9389d776432888e47/psutil-6.0.0-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e2e8d0054fc88153ca0544f5c4d554d42e33df2e009c4ff42284ac9ebdef4132", size = 292046 }, - { url = "https://files.pythonhosted.org/packages/8b/20/2ff69ad9c35c3df1858ac4e094f20bd2374d33c8643cf41da8fd7cdcb78b/psutil-6.0.0-cp37-abi3-win32.whl", hash = "sha256:a495580d6bae27291324fe60cea0b5a7c23fa36a7cd35035a16d93bdcf076b9d", size = 253560 }, - { url = "https://files.pythonhosted.org/packages/73/44/561092313ae925f3acfaace6f9ddc4f6a9c748704317bad9c8c8f8a36a79/psutil-6.0.0-cp37-abi3-win_amd64.whl", hash = "sha256:33ea5e1c975250a720b3a6609c490db40dae5d83a4eb315170c4fe0d8b1f34b3", size = 257399 }, - { url = "https://files.pythonhosted.org/packages/7c/06/63872a64c312a24fb9b4af123ee7007a306617da63ff13bcc1432386ead7/psutil-6.0.0-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:ffe7fc9b6b36beadc8c322f84e1caff51e8703b88eee1da46d1e3a6ae11b4fd0", size = 251988 }, + { url = "https://files.pythonhosted.org/packages/01/9e/8be43078a171381953cfee33c07c0d628594b5dbfc5157847b85022c2c1b/psutil-6.1.0-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:6e2dcd475ce8b80522e51d923d10c7871e45f20918e027ab682f94f1c6351688", size = 247762 }, + { url = "https://files.pythonhosted.org/packages/1d/cb/313e80644ea407f04f6602a9e23096540d9dc1878755f3952ea8d3d104be/psutil-6.1.0-cp36-abi3-macosx_11_0_arm64.whl", hash = "sha256:0895b8414afafc526712c498bd9de2b063deaac4021a3b3c34566283464aff8e", size = 248777 }, + { url = "https://files.pythonhosted.org/packages/65/8e/bcbe2025c587b5d703369b6a75b65d41d1367553da6e3f788aff91eaf5bd/psutil-6.1.0-cp36-abi3-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9dcbfce5d89f1d1f2546a2090f4fcf87c7f669d1d90aacb7d7582addece9fb38", size = 284259 }, + { url = "https://files.pythonhosted.org/packages/58/4d/8245e6f76a93c98aab285a43ea71ff1b171bcd90c9d238bf81f7021fb233/psutil-6.1.0-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:498c6979f9c6637ebc3a73b3f87f9eb1ec24e1ce53a7c5173b8508981614a90b", size = 287255 }, + { url = "https://files.pythonhosted.org/packages/27/c2/d034856ac47e3b3cdfa9720d0e113902e615f4190d5d1bdb8df4b2015fb2/psutil-6.1.0-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d905186d647b16755a800e7263d43df08b790d709d575105d419f8b6ef65423a", size = 288804 }, + { url = "https://files.pythonhosted.org/packages/ea/55/5389ed243c878725feffc0d6a3bc5ef6764312b6fc7c081faaa2cfa7ef37/psutil-6.1.0-cp37-abi3-win32.whl", hash = "sha256:1ad45a1f5d0b608253b11508f80940985d1d0c8f6111b5cb637533a0e6ddc13e", size = 250386 }, + { url = "https://files.pythonhosted.org/packages/11/91/87fa6f060e649b1e1a7b19a4f5869709fbf750b7c8c262ee776ec32f3028/psutil-6.1.0-cp37-abi3-win_amd64.whl", hash = "sha256:a8fb3752b491d246034fa4d279ff076501588ce8cbcdbb62c32fd7a377d996be", size = 254228 }, ] [[package]] @@ -5823,46 +5809,46 @@ wheels = [ [[package]] name = "psycopg2-binary" -version = "2.9.9" +version = "2.9.10" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/fc/07/e720e53bfab016ebcc34241695ccc06a9e3d91ba19b40ca81317afbdc440/psycopg2-binary-2.9.9.tar.gz", hash = "sha256:7f01846810177d829c7692f1f5ada8096762d9172af1b1a28d4ab5b77c923c1c", size = 384973 } +sdist = { url = "https://files.pythonhosted.org/packages/cb/0e/bdc8274dc0585090b4e3432267d7be4dfbfd8971c0fa59167c711105a6bf/psycopg2-binary-2.9.10.tar.gz", hash = "sha256:4b3df0e6990aa98acda57d983942eff13d824135fe2250e6522edaa782a06de2", size = 385764 } wheels = [ - { url = "https://files.pythonhosted.org/packages/0a/7c/6aaf8c3cb05d86d2c3f407b95bac0c71a43f2718e38c1091972aacb5e1b2/psycopg2_binary-2.9.9-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c2470da5418b76232f02a2fcd2229537bb2d5a7096674ce61859c3229f2eb202", size = 2822503 }, - { url = "https://files.pythonhosted.org/packages/72/3d/acab427845198794aafd963dd073ee35810e2c52606e8a28c12db39821fb/psycopg2_binary-2.9.9-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c6af2a6d4b7ee9615cbb162b0738f6e1fd1f5c3eda7e5da17861eacf4c717ea7", size = 2552645 }, - { url = "https://files.pythonhosted.org/packages/ed/be/6c787962d706e55a528ef1693dd7251de657ae60e4d9d767ed61e8e2975c/psycopg2_binary-2.9.9-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:75723c3c0fbbf34350b46a3199eb50638ab22a0228f93fb472ef4d9becc2382b", size = 2850980 }, - { url = "https://files.pythonhosted.org/packages/83/50/a054076c6358753661cd1da59f4dabc03e83d51690371f3fd1edb9e2cf72/psycopg2_binary-2.9.9-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:83791a65b51ad6ee6cf0845634859d69a038ea9b03d7b26e703f94c7e93dbcf9", size = 3080543 }, - { url = "https://files.pythonhosted.org/packages/9c/02/826dc5cdfc9515423ec912ba00cc2e4eb09f69e0339b177c9c742f2a09a2/psycopg2_binary-2.9.9-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0ef4854e82c09e84cc63084a9e4ccd6d9b154f1dbdd283efb92ecd0b5e2b8c84", size = 3264316 }, - { url = "https://files.pythonhosted.org/packages/bc/0d/486e3fa27f39a00168abfcf14a3d8444f437f4b755cc34316da1124f293d/psycopg2_binary-2.9.9-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ed1184ab8f113e8d660ce49a56390ca181f2981066acc27cf637d5c1e10ce46e", size = 3019508 }, - { url = "https://files.pythonhosted.org/packages/41/af/bce37630c525d2b9cf93f930110fc98616d6aca308d59b833b83b3a38176/psycopg2_binary-2.9.9-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:d2997c458c690ec2bc6b0b7ecbafd02b029b7b4283078d3b32a852a7ce3ddd98", size = 2355821 }, - { url = "https://files.pythonhosted.org/packages/3b/76/e46dae1b2273814ef80231f86d59cadf94ec36fd757045ed713c5b75cde7/psycopg2_binary-2.9.9-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:b58b4710c7f4161b5e9dcbe73bb7c62d65670a87df7bcce9e1faaad43e715245", size = 2534855 }, - { url = "https://files.pythonhosted.org/packages/0e/6d/e97245eabff29d7c2de5fc1fc17cf7ef427beee93d20a5ae114c6e6718bd/psycopg2_binary-2.9.9-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:0c009475ee389757e6e34611d75f6e4f05f0cf5ebb76c6037508318e1a1e0d7e", size = 2486614 }, - { url = "https://files.pythonhosted.org/packages/70/a7/2cd2c9d5e23b556c11e3b7da41895808d9b056f8f34f50de4375a35b4951/psycopg2_binary-2.9.9-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:8dbf6d1bc73f1d04ec1734bae3b4fb0ee3cb2a493d35ede9badbeb901fb40f6f", size = 2454928 }, - { url = "https://files.pythonhosted.org/packages/63/41/815d19767e2adb1a585213b801c954f46102f305c352c4a4f96287342d44/psycopg2_binary-2.9.9-cp310-cp310-win32.whl", hash = "sha256:3f78fd71c4f43a13d342be74ebbc0666fe1f555b8837eb113cb7416856c79682", size = 1025249 }, - { url = "https://files.pythonhosted.org/packages/5e/4c/9233e0e206634a5387f3ab40f334a5325fb8bef2ca4e12ee7dbdeaf96afc/psycopg2_binary-2.9.9-cp310-cp310-win_amd64.whl", hash = "sha256:876801744b0dee379e4e3c38b76fc89f88834bb15bf92ee07d94acd06ec890a0", size = 1163645 }, - { url = "https://files.pythonhosted.org/packages/a5/ac/702d300f3df169b9d0cbef0340d9f34a78bc18dc2dbafbcb39ff0f165cf8/psycopg2_binary-2.9.9-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:ee825e70b1a209475622f7f7b776785bd68f34af6e7a46e2e42f27b659b5bc26", size = 2822581 }, - { url = "https://files.pythonhosted.org/packages/7a/1f/a6cf0cdf944253f7c45d90fbc876cc8bed5cc9942349306245715c0d88d6/psycopg2_binary-2.9.9-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1ea665f8ce695bcc37a90ee52de7a7980be5161375d42a0b6c6abedbf0d81f0f", size = 2552633 }, - { url = "https://files.pythonhosted.org/packages/81/0b/3adf561107c865928455891156d1dde5325253f7f4316fe56cd2c3f73570/psycopg2_binary-2.9.9-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:143072318f793f53819048fdfe30c321890af0c3ec7cb1dfc9cc87aa88241de2", size = 2851075 }, - { url = "https://files.pythonhosted.org/packages/f7/98/c2fedcbf0a9607519a010dcf88571138b2251062dbde3610cdba5ba1eee1/psycopg2_binary-2.9.9-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c332c8d69fb64979ebf76613c66b985414927a40f8defa16cf1bc028b7b0a7b0", size = 3080509 }, - { url = "https://files.pythonhosted.org/packages/c2/05/81e8bc7fca95574c9323e487d9ce1b58a4cfcc17f89b8fe843af46361211/psycopg2_binary-2.9.9-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f7fc5a5acafb7d6ccca13bfa8c90f8c51f13d8fb87d95656d3950f0158d3ce53", size = 3264303 }, - { url = "https://files.pythonhosted.org/packages/ce/85/62825cabc6aad53104b7b6d12eb2ad74737d268630032d07b74d4444cb72/psycopg2_binary-2.9.9-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:977646e05232579d2e7b9c59e21dbe5261f403a88417f6a6512e70d3f8a046be", size = 3019515 }, - { url = "https://files.pythonhosted.org/packages/e9/b0/9ca2b8e01a0912c9a14234fd5df7a241a1e44778c5797bf4b8eaa8dc3d3a/psycopg2_binary-2.9.9-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:b6356793b84728d9d50ead16ab43c187673831e9d4019013f1402c41b1db9b27", size = 2355892 }, - { url = "https://files.pythonhosted.org/packages/73/17/ba28bb0022db5e2015a82d2df1c4b0d419c37fa07a588b3aff3adc4939f6/psycopg2_binary-2.9.9-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:bc7bb56d04601d443f24094e9e31ae6deec9ccb23581f75343feebaf30423359", size = 2534903 }, - { url = "https://files.pythonhosted.org/packages/3b/92/b463556409cdc12791cd8b1dae0072bf8efe817ef68b7ea3d9cf7d0e5656/psycopg2_binary-2.9.9-cp311-cp311-musllinux_1_1_ppc64le.whl", hash = "sha256:77853062a2c45be16fd6b8d6de2a99278ee1d985a7bd8b103e97e41c034006d2", size = 2486597 }, - { url = "https://files.pythonhosted.org/packages/92/57/96576e07132d7f7a1ac1df939575e6fdd8951aea337ee152b586bb51a971/psycopg2_binary-2.9.9-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:78151aa3ec21dccd5cdef6c74c3e73386dcdfaf19bced944169697d7ac7482fc", size = 2454908 }, - { url = "https://files.pythonhosted.org/packages/7c/ae/cedd56e1f4a2b0e37213283caf3733a875c4c76f3372241e19c0d2a87355/psycopg2_binary-2.9.9-cp311-cp311-win32.whl", hash = "sha256:dc4926288b2a3e9fd7b50dc6a1909a13bbdadfc67d93f3374d984e56f885579d", size = 1024240 }, - { url = "https://files.pythonhosted.org/packages/25/1f/7ae31759142999a8d06b3e250c1346c4abcdcada8fa884376775dc1de686/psycopg2_binary-2.9.9-cp311-cp311-win_amd64.whl", hash = "sha256:b76bedd166805480ab069612119ea636f5ab8f8771e640ae103e05a4aae3e417", size = 1163655 }, - { url = "https://files.pythonhosted.org/packages/a7/d0/5f2db14e7b53552276ab613399a83f83f85b173a862d3f20580bc7231139/psycopg2_binary-2.9.9-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:8532fd6e6e2dc57bcb3bc90b079c60de896d2128c5d9d6f24a63875a95a088cf", size = 2823784 }, - { url = "https://files.pythonhosted.org/packages/18/ca/da384fd47233e300e3e485c90e7aab5d7def896d1281239f75901faf87d4/psycopg2_binary-2.9.9-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:b0605eaed3eb239e87df0d5e3c6489daae3f7388d455d0c0b4df899519c6a38d", size = 2553308 }, - { url = "https://files.pythonhosted.org/packages/50/66/fa53d2d3d92f6e1ef469d92afc6a4fe3f6e8a9a04b687aa28fb1f1d954ee/psycopg2_binary-2.9.9-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8f8544b092a29a6ddd72f3556a9fcf249ec412e10ad28be6a0c0d948924f2212", size = 2851283 }, - { url = "https://files.pythonhosted.org/packages/04/37/2429360ac5547378202db14eec0dde76edbe1f6627df5a43c7e164922859/psycopg2_binary-2.9.9-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2d423c8d8a3c82d08fe8af900ad5b613ce3632a1249fd6a223941d0735fce493", size = 3081839 }, - { url = "https://files.pythonhosted.org/packages/62/2a/c0530b59d7e0d09824bc2102ecdcec0456b8ca4d47c0caa82e86fce3ed4c/psycopg2_binary-2.9.9-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2e5afae772c00980525f6d6ecf7cbca55676296b580c0e6abb407f15f3706996", size = 3264488 }, - { url = "https://files.pythonhosted.org/packages/19/57/9f172b900795ea37246c78b5f52e00f4779984370855b3e161600156906d/psycopg2_binary-2.9.9-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6e6f98446430fdf41bd36d4faa6cb409f5140c1c2cf58ce0bbdaf16af7d3f119", size = 3020700 }, - { url = "https://files.pythonhosted.org/packages/94/68/1176fc14ea76861b7b8360be5176e87fb20d5091b137c76570eb4e237324/psycopg2_binary-2.9.9-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:c77e3d1862452565875eb31bdb45ac62502feabbd53429fdc39a1cc341d681ba", size = 2355968 }, - { url = "https://files.pythonhosted.org/packages/70/bb/aec2646a705a09079d008ce88073401cd61fc9b04f92af3eb282caa3a2ec/psycopg2_binary-2.9.9-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:cb16c65dcb648d0a43a2521f2f0a2300f40639f6f8c1ecbc662141e4e3e1ee07", size = 2536101 }, - { url = "https://files.pythonhosted.org/packages/14/33/12818c157e333cb9d9e6753d1b2463b6f60dbc1fade115f8e4dc5c52cac4/psycopg2_binary-2.9.9-cp312-cp312-musllinux_1_1_ppc64le.whl", hash = "sha256:911dda9c487075abd54e644ccdf5e5c16773470a6a5d3826fda76699410066fb", size = 2487064 }, - { url = "https://files.pythonhosted.org/packages/56/a2/7851c68fe8768f3c9c246198b6356ee3e4a8a7f6820cc798443faada3400/psycopg2_binary-2.9.9-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:57fede879f08d23c85140a360c6a77709113efd1c993923c59fde17aa27599fe", size = 2456257 }, - { url = "https://files.pythonhosted.org/packages/6f/ee/3ba07c6dc7c3294e717e94720da1597aedc82a10b1b180203ce183d4631a/psycopg2_binary-2.9.9-cp312-cp312-win32.whl", hash = "sha256:64cf30263844fa208851ebb13b0732ce674d8ec6a0c86a4e160495d299ba3c93", size = 1024709 }, - { url = "https://files.pythonhosted.org/packages/7b/08/9c66c269b0d417a0af9fb969535f0371b8c538633535a7a6a5ca3f9231e2/psycopg2_binary-2.9.9-cp312-cp312-win_amd64.whl", hash = "sha256:81ff62668af011f9a48787564ab7eded4e9fb17a4a6a74af5ffa6a457400d2ab", size = 1163864 }, + { url = "https://files.pythonhosted.org/packages/7a/81/331257dbf2801cdb82105306042f7a1637cc752f65f2bb688188e0de5f0b/psycopg2_binary-2.9.10-cp310-cp310-macosx_12_0_x86_64.whl", hash = "sha256:0ea8e3d0ae83564f2fc554955d327fa081d065c8ca5cc6d2abb643e2c9c1200f", size = 3043397 }, + { url = "https://files.pythonhosted.org/packages/e7/9a/7f4f2f031010bbfe6a02b4a15c01e12eb6b9b7b358ab33229f28baadbfc1/psycopg2_binary-2.9.10-cp310-cp310-macosx_14_0_arm64.whl", hash = "sha256:3e9c76f0ac6f92ecfc79516a8034a544926430f7b080ec5a0537bca389ee0906", size = 3274806 }, + { url = "https://files.pythonhosted.org/packages/e5/57/8ddd4b374fa811a0b0a0f49b6abad1cde9cb34df73ea3348cc283fcd70b4/psycopg2_binary-2.9.10-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2ad26b467a405c798aaa1458ba09d7e2b6e5f96b1ce0ac15d82fd9f95dc38a92", size = 2851361 }, + { url = "https://files.pythonhosted.org/packages/f9/66/d1e52c20d283f1f3a8e7e5c1e06851d432f123ef57b13043b4f9b21ffa1f/psycopg2_binary-2.9.10-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:270934a475a0e4b6925b5f804e3809dd5f90f8613621d062848dd82f9cd62007", size = 3080836 }, + { url = "https://files.pythonhosted.org/packages/a0/cb/592d44a9546aba78f8a1249021fe7c59d3afb8a0ba51434d6610cc3462b6/psycopg2_binary-2.9.10-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:48b338f08d93e7be4ab2b5f1dbe69dc5e9ef07170fe1f86514422076d9c010d0", size = 3264552 }, + { url = "https://files.pythonhosted.org/packages/64/33/c8548560b94b7617f203d7236d6cdf36fe1a5a3645600ada6efd79da946f/psycopg2_binary-2.9.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7f4152f8f76d2023aac16285576a9ecd2b11a9895373a1f10fd9db54b3ff06b4", size = 3019789 }, + { url = "https://files.pythonhosted.org/packages/b0/0e/c2da0db5bea88a3be52307f88b75eec72c4de62814cbe9ee600c29c06334/psycopg2_binary-2.9.10-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:32581b3020c72d7a421009ee1c6bf4a131ef5f0a968fab2e2de0c9d2bb4577f1", size = 2871776 }, + { url = "https://files.pythonhosted.org/packages/15/d7/774afa1eadb787ddf41aab52d4c62785563e29949613c958955031408ae6/psycopg2_binary-2.9.10-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:2ce3e21dc3437b1d960521eca599d57408a695a0d3c26797ea0f72e834c7ffe5", size = 2820959 }, + { url = "https://files.pythonhosted.org/packages/5e/ed/440dc3f5991a8c6172a1cde44850ead0e483a375277a1aef7cfcec00af07/psycopg2_binary-2.9.10-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:e984839e75e0b60cfe75e351db53d6db750b00de45644c5d1f7ee5d1f34a1ce5", size = 2919329 }, + { url = "https://files.pythonhosted.org/packages/03/be/2cc8f4282898306732d2ae7b7378ae14e8df3c1231b53579efa056aae887/psycopg2_binary-2.9.10-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:3c4745a90b78e51d9ba06e2088a2fe0c693ae19cc8cb051ccda44e8df8a6eb53", size = 2957659 }, + { url = "https://files.pythonhosted.org/packages/d0/12/fb8e4f485d98c570e00dad5800e9a2349cfe0f71a767c856857160d343a5/psycopg2_binary-2.9.10-cp310-cp310-win32.whl", hash = "sha256:e5720a5d25e3b99cd0dc5c8a440570469ff82659bb09431c1439b92caf184d3b", size = 1024605 }, + { url = "https://files.pythonhosted.org/packages/22/4f/217cd2471ecf45d82905dd09085e049af8de6cfdc008b6663c3226dc1c98/psycopg2_binary-2.9.10-cp310-cp310-win_amd64.whl", hash = "sha256:3c18f74eb4386bf35e92ab2354a12c17e5eb4d9798e4c0ad3a00783eae7cd9f1", size = 1163817 }, + { url = "https://files.pythonhosted.org/packages/9c/8f/9feb01291d0d7a0a4c6a6bab24094135c2b59c6a81943752f632c75896d6/psycopg2_binary-2.9.10-cp311-cp311-macosx_12_0_x86_64.whl", hash = "sha256:04392983d0bb89a8717772a193cfaac58871321e3ec69514e1c4e0d4957b5aff", size = 3043397 }, + { url = "https://files.pythonhosted.org/packages/15/30/346e4683532011561cd9c8dfeac6a8153dd96452fee0b12666058ab7893c/psycopg2_binary-2.9.10-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:1a6784f0ce3fec4edc64e985865c17778514325074adf5ad8f80636cd029ef7c", size = 3274806 }, + { url = "https://files.pythonhosted.org/packages/66/6e/4efebe76f76aee7ec99166b6c023ff8abdc4e183f7b70913d7c047701b79/psycopg2_binary-2.9.10-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b5f86c56eeb91dc3135b3fd8a95dc7ae14c538a2f3ad77a19645cf55bab1799c", size = 2851370 }, + { url = "https://files.pythonhosted.org/packages/7f/fd/ff83313f86b50f7ca089b161b8e0a22bb3c319974096093cd50680433fdb/psycopg2_binary-2.9.10-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2b3d2491d4d78b6b14f76881905c7a8a8abcf974aad4a8a0b065273a0ed7a2cb", size = 3080780 }, + { url = "https://files.pythonhosted.org/packages/e6/c4/bfadd202dcda8333a7ccafdc51c541dbdfce7c2c7cda89fa2374455d795f/psycopg2_binary-2.9.10-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2286791ececda3a723d1910441c793be44625d86d1a4e79942751197f4d30341", size = 3264583 }, + { url = "https://files.pythonhosted.org/packages/5d/f1/09f45ac25e704ac954862581f9f9ae21303cc5ded3d0b775532b407f0e90/psycopg2_binary-2.9.10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:512d29bb12608891e349af6a0cccedce51677725a921c07dba6342beaf576f9a", size = 3019831 }, + { url = "https://files.pythonhosted.org/packages/9e/2e/9beaea078095cc558f215e38f647c7114987d9febfc25cb2beed7c3582a5/psycopg2_binary-2.9.10-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:5a507320c58903967ef7384355a4da7ff3f28132d679aeb23572753cbf2ec10b", size = 2871822 }, + { url = "https://files.pythonhosted.org/packages/01/9e/ef93c5d93f3dc9fc92786ffab39e323b9aed066ba59fdc34cf85e2722271/psycopg2_binary-2.9.10-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:6d4fa1079cab9018f4d0bd2db307beaa612b0d13ba73b5c6304b9fe2fb441ff7", size = 2820975 }, + { url = "https://files.pythonhosted.org/packages/a5/f0/049e9631e3268fe4c5a387f6fc27e267ebe199acf1bc1bc9cbde4bd6916c/psycopg2_binary-2.9.10-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:851485a42dbb0bdc1edcdabdb8557c09c9655dfa2ca0460ff210522e073e319e", size = 2919320 }, + { url = "https://files.pythonhosted.org/packages/dc/9a/bcb8773b88e45fb5a5ea8339e2104d82c863a3b8558fbb2aadfe66df86b3/psycopg2_binary-2.9.10-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:35958ec9e46432d9076286dda67942ed6d968b9c3a6a2fd62b48939d1d78bf68", size = 2957617 }, + { url = "https://files.pythonhosted.org/packages/e2/6b/144336a9bf08a67d217b3af3246abb1d027095dab726f0687f01f43e8c03/psycopg2_binary-2.9.10-cp311-cp311-win32.whl", hash = "sha256:ecced182e935529727401b24d76634a357c71c9275b356efafd8a2a91ec07392", size = 1024618 }, + { url = "https://files.pythonhosted.org/packages/61/69/3b3d7bd583c6d3cbe5100802efa5beacaacc86e37b653fc708bf3d6853b8/psycopg2_binary-2.9.10-cp311-cp311-win_amd64.whl", hash = "sha256:ee0e8c683a7ff25d23b55b11161c2663d4b099770f6085ff0a20d4505778d6b4", size = 1163816 }, + { url = "https://files.pythonhosted.org/packages/49/7d/465cc9795cf76f6d329efdafca74693714556ea3891813701ac1fee87545/psycopg2_binary-2.9.10-cp312-cp312-macosx_12_0_x86_64.whl", hash = "sha256:880845dfe1f85d9d5f7c412efea7a08946a46894537e4e5d091732eb1d34d9a0", size = 3044771 }, + { url = "https://files.pythonhosted.org/packages/8b/31/6d225b7b641a1a2148e3ed65e1aa74fc86ba3fee850545e27be9e1de893d/psycopg2_binary-2.9.10-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:9440fa522a79356aaa482aa4ba500b65f28e5d0e63b801abf6aa152a29bd842a", size = 3275336 }, + { url = "https://files.pythonhosted.org/packages/30/b7/a68c2b4bff1cbb1728e3ec864b2d92327c77ad52edcd27922535a8366f68/psycopg2_binary-2.9.10-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e3923c1d9870c49a2d44f795df0c889a22380d36ef92440ff618ec315757e539", size = 2851637 }, + { url = "https://files.pythonhosted.org/packages/0b/b1/cfedc0e0e6f9ad61f8657fd173b2f831ce261c02a08c0b09c652b127d813/psycopg2_binary-2.9.10-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7b2c956c028ea5de47ff3a8d6b3cc3330ab45cf0b7c3da35a2d6ff8420896526", size = 3082097 }, + { url = "https://files.pythonhosted.org/packages/18/ed/0a8e4153c9b769f59c02fb5e7914f20f0b2483a19dae7bf2db54b743d0d0/psycopg2_binary-2.9.10-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f758ed67cab30b9a8d2833609513ce4d3bd027641673d4ebc9c067e4d208eec1", size = 3264776 }, + { url = "https://files.pythonhosted.org/packages/10/db/d09da68c6a0cdab41566b74e0a6068a425f077169bed0946559b7348ebe9/psycopg2_binary-2.9.10-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8cd9b4f2cfab88ed4a9106192de509464b75a906462fb846b936eabe45c2063e", size = 3020968 }, + { url = "https://files.pythonhosted.org/packages/94/28/4d6f8c255f0dfffb410db2b3f9ac5218d959a66c715c34cac31081e19b95/psycopg2_binary-2.9.10-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:6dc08420625b5a20b53551c50deae6e231e6371194fa0651dbe0fb206452ae1f", size = 2872334 }, + { url = "https://files.pythonhosted.org/packages/05/f7/20d7bf796593c4fea95e12119d6cc384ff1f6141a24fbb7df5a668d29d29/psycopg2_binary-2.9.10-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:d7cd730dfa7c36dbe8724426bf5612798734bff2d3c3857f36f2733f5bfc7c00", size = 2822722 }, + { url = "https://files.pythonhosted.org/packages/4d/e4/0c407ae919ef626dbdb32835a03b6737013c3cc7240169843965cada2bdf/psycopg2_binary-2.9.10-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:155e69561d54d02b3c3209545fb08938e27889ff5a10c19de8d23eb5a41be8a5", size = 2920132 }, + { url = "https://files.pythonhosted.org/packages/2d/70/aa69c9f69cf09a01da224909ff6ce8b68faeef476f00f7ec377e8f03be70/psycopg2_binary-2.9.10-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:c3cc28a6fd5a4a26224007712e79b81dbaee2ffb90ff406256158ec4d7b52b47", size = 2959312 }, + { url = "https://files.pythonhosted.org/packages/d3/bd/213e59854fafe87ba47814bf413ace0dcee33a89c8c8c814faca6bc7cf3c/psycopg2_binary-2.9.10-cp312-cp312-win32.whl", hash = "sha256:ec8a77f521a17506a24a5f626cb2aee7850f9b69a0afe704586f63a464f3cd64", size = 1025191 }, + { url = "https://files.pythonhosted.org/packages/92/29/06261ea000e2dc1e22907dbbc483a1093665509ea586b29b8986a0e56733/psycopg2_binary-2.9.10-cp312-cp312-win_amd64.whl", hash = "sha256:18c5ee682b9c6dd3696dad6e54cc7ff3a1a9020df6a5c0f861ef8bfd338c3ca0", size = 1164031 }, ] [[package]] @@ -6103,33 +6089,33 @@ wheels = [ [[package]] name = "pyjwt" -version = "2.9.0" +version = "2.10.1" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/fb/68/ce067f09fca4abeca8771fe667d89cc347d1e99da3e093112ac329c6020e/pyjwt-2.9.0.tar.gz", hash = "sha256:7e1e5b56cc735432a7369cbfa0efe50fa113ebecdc04ae6922deba8b84582d0c", size = 78825 } +sdist = { url = "https://files.pythonhosted.org/packages/e7/46/bd74733ff231675599650d3e47f361794b22ef3e3770998dda30d3b63726/pyjwt-2.10.1.tar.gz", hash = "sha256:3cc5772eb20009233caf06e9d8a0577824723b44e6648ee0a2aedb6cf9381953", size = 87785 } wheels = [ - { url = "https://files.pythonhosted.org/packages/79/84/0fdf9b18ba31d69877bd39c9cd6052b47f3761e9910c15de788e519f079f/PyJWT-2.9.0-py3-none-any.whl", hash = "sha256:3b02fb0f44517787776cf48f2ae25d8e14f300e6d7545a4315cee571a415e850", size = 22344 }, + { url = "https://files.pythonhosted.org/packages/61/ad/689f02752eeec26aed679477e80e632ef1b682313be70793d798c1d5fc8f/PyJWT-2.10.1-py3-none-any.whl", hash = "sha256:dcdd193e30abefd5debf142f9adfcdd2b58004e644f25406ffaebd50bd98dacb", size = 22997 }, ] [[package]] name = "pylance" -version = "0.18.2" +version = "0.20.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "numpy" }, { name = "pyarrow" }, ] wheels = [ - { url = "https://files.pythonhosted.org/packages/25/0a/16ae3434c8747028b2adc14cf9e15982005168b173ffa7f181e62af78537/pylance-0.18.2-cp39-abi3-macosx_10_15_x86_64.whl", hash = "sha256:017422b058724dfbe8426c1ac42f0ede77324f3783e177cb4239dc034758b50b", size = 28268045 }, - { url = "https://files.pythonhosted.org/packages/da/9f/d8f6ed331d6d57b53616bdce1d88efe724335663ee3b6337f1412b104e42/pylance-0.18.2-cp39-abi3-macosx_11_0_arm64.whl", hash = "sha256:c4c4049eb6a6075cef721a20dd28ccba6d89b66f13e8d20ef65a284ae1c02e30", size = 26291690 }, - { url = "https://files.pythonhosted.org/packages/0a/1f/4e6df8eba3c9d78bea8c0713e07ae500d837247d9697c0612720d7f048c7/pylance-0.18.2-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:89dcf2dadee940ea86ac0b3bf7ba81c68e9774a449d8de206bc60cdc8804b853", size = 30065809 }, - { url = "https://files.pythonhosted.org/packages/05/c0/83519992d4a56989fc37fa4baf00ba8c5c8f3bea0cc83a85359751572d64/pylance-0.18.2-cp39-abi3-manylinux_2_24_aarch64.whl", hash = "sha256:f37fb7ad0e53076c731014c210a45919f3b2620c967e2f62cf8b7c26fdc9aace", size = 29243695 }, - { url = "https://files.pythonhosted.org/packages/05/40/648f74da0449699b40792b7b9d6db8aedc80fa4e25c61e1f75a8299ec8c5/pylance-0.18.2-cp39-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:a913920f591d8404c46c74e3911fe0c29d47b923b9c3c7e521d3354c1663d812", size = 30017919 }, - { url = "https://files.pythonhosted.org/packages/81/1b/9dcb3d95fd08b2a2ce7f972a3dce25551b29a9fd0e1ee22e39d8bec36b3e/pylance-0.18.2-cp39-abi3-win_amd64.whl", hash = "sha256:72796676d7647ba9f6e86531daf67880f5e69ba8f842e237ad0c1ca419c6378c", size = 28072707 }, + { url = "https://files.pythonhosted.org/packages/c1/d9/f2a5ee73b07df1c2c6bc06b53f67960caa5374f55118ee46fabe35396de5/pylance-0.20.0-cp39-abi3-macosx_10_15_x86_64.whl", hash = "sha256:fbb640b00567ff79d23a5994c0f0bc97587fcf74ece6ca568e77c453f70801c5", size = 31512397 }, + { url = "https://files.pythonhosted.org/packages/01/dc/14c8321a08bbe110789e19aa8b9ba840f52ef8db88d0cdd9c3a29789791b/pylance-0.20.0-cp39-abi3-macosx_11_0_arm64.whl", hash = "sha256:c8e30f1b6429b843429fde8f3d6fb7e715153174161e3bcf29902e2d32ee471f", size = 29266199 }, + { url = "https://files.pythonhosted.org/packages/1e/2c/f262507cdbed70994afc8bcc60beae2b823d10967bc632d9144806f035d4/pylance-0.20.0-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:032242a347ac909db81c0ade6384d82102f4ec61bc892d8caaa04b3d0a7b1613", size = 33539993 }, + { url = "https://files.pythonhosted.org/packages/41/9c/88eb6eb07f1a803dec43930d28c587d9df3dc996337d399fa74bcb3cbb10/pylance-0.20.0-cp39-abi3-manylinux_2_24_aarch64.whl", hash = "sha256:5320f11925524c1a67279afc4638cad60f61c36f11d3d9c2a91651489874be0d", size = 31858413 }, + { url = "https://files.pythonhosted.org/packages/22/d2/acaf3328d1bd55201f9775d8b8a3f7c497966d3f3371e22aabb269cb4f0f/pylance-0.20.0-cp39-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:fa5acd4488c574f6017145eafd5b45b178d611a5cbcd2ed492e01013fc72f5a2", size = 33465409 }, + { url = "https://files.pythonhosted.org/packages/c7/0a/c012ef957c3c99edf7a87d5f77ccf174bdf161d4ae1aac2181d750fcbcd5/pylance-0.20.0-cp39-abi3-win_amd64.whl", hash = "sha256:587850cddd0e669addd9414f378fa30527fc9020010cb73c842f026ea8a9b4ea", size = 31356456 }, ] [[package]] name = "pymilvus" -version = "2.4.7" +version = "2.4.9" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "environs" }, @@ -6140,9 +6126,9 @@ dependencies = [ { name = "setuptools" }, { name = "ujson" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/93/ca/35af82193a15a67b15f634b618e6f24fb4f3a16e56875a63e630dbc4f4ea/pymilvus-2.4.7.tar.gz", hash = "sha256:9ef460b940782a42e1b7b8ae0da03d8cc02d9d80044d13f4b689a7c935ec7aa7", size = 1215012 } +sdist = { url = "https://files.pythonhosted.org/packages/1c/e4/208ac8d384bdcfa1a2983a6394705edccfd15a99f6f0e478ea0400fc1c73/pymilvus-2.4.9.tar.gz", hash = "sha256:0937663700007c23a84cfc0656160b301f6ff9247aaec4c96d599a6b43572136", size = 1219775 } wheels = [ - { url = "https://files.pythonhosted.org/packages/2c/2f/0445d2b8c7947815d9392a15044a5406044f779eab4162e4b6428c3302a8/pymilvus-2.4.7-py3-none-any.whl", hash = "sha256:1e5d377bd40fa7eb459d3958dbd96201758f5cf997d41eb3d2d169d0b7fa462e", size = 198591 }, + { url = "https://files.pythonhosted.org/packages/0e/98/0d79ebcc04e8a469f796e644302edee4368927a268f11afc298b6bd76e1f/pymilvus-2.4.9-py3-none-any.whl", hash = "sha256:45313607d2c164064bdc44e0f933cb6d6afa92e9efcc7f357c5240c57db58fbe", size = 201144 }, ] [[package]] @@ -6205,11 +6191,11 @@ wheels = [ [[package]] name = "pyparsing" -version = "3.1.4" +version = "3.2.0" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/83/08/13f3bce01b2061f2bbd582c9df82723de943784cf719a35ac886c652043a/pyparsing-3.1.4.tar.gz", hash = "sha256:f86ec8d1a83f11977c9a6ea7598e8c27fc5cddfa5b07ea2241edbbde1d7bc032", size = 900231 } +sdist = { url = "https://files.pythonhosted.org/packages/8c/d5/e5aeee5387091148a19e1145f63606619cb5f20b83fccb63efae6474e7b2/pyparsing-3.2.0.tar.gz", hash = "sha256:cbf74e27246d595d9a74b186b810f6fbb86726dbf3b9532efb343f6d7294fe9c", size = 920984 } wheels = [ - { url = "https://files.pythonhosted.org/packages/e5/0c/0e3c05b1c87bb6a1c76d281b0f35e78d2d80ac91b5f8f524cebf77f51049/pyparsing-3.1.4-py3-none-any.whl", hash = "sha256:a6a7ee4235a3f944aa1fa2249307708f893fe5717dc603503c6c7969c070fb7c", size = 104100 }, + { url = "https://files.pythonhosted.org/packages/be/ec/2eb3cd785efd67806c46c13a17339708ddc346cbb684eade7a6e6f79536a/pyparsing-3.2.0-py3-none-any.whl", hash = "sha256:93d9577b88da0bbea8cc8334ee8b918ed014968fd2ec383e868fb8afb1ccef84", size = 106921 }, ] [[package]] @@ -6276,15 +6262,15 @@ wheels = [ [[package]] name = "pyright" -version = "1.1.385" +version = "1.1.390" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "nodeenv" }, { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/29/ca/3238db97766ecfd6b2758fb50727a0b433e7b1bb6be0de090ed08b291fff/pyright-1.1.385.tar.gz", hash = "sha256:1bf042b8f080441534aa02101dea30f8fc2efa8f7b6f1ab05197c21317f5bfa7", size = 21971 } +sdist = { url = "https://files.pythonhosted.org/packages/ba/42/1e0392f35dd275f9f775baf7c86407cef7f6a0d9b8e099a93e5422a7e571/pyright-1.1.390.tar.gz", hash = "sha256:aad7f160c49e0fbf8209507a15e17b781f63a86a1facb69ca877c71ef2e9538d", size = 21950 } wheels = [ - { url = "https://files.pythonhosted.org/packages/e3/39/877484412a1079003a7645375b487bd7c422692f4e5b7c2030dea3e83043/pyright-1.1.385-py3-none-any.whl", hash = "sha256:e5b9a1b8d492e13004d822af94d07d235f2c7c158457293b51ab2214c8c5b375", size = 18579 }, + { url = "https://files.pythonhosted.org/packages/43/20/3f492ca789fb17962ad23619959c7fa642082621751514296c58de3bb801/pyright-1.1.390-py3-none-any.whl", hash = "sha256:ecebfba5b6b50af7c1a44c2ba144ba2ab542c227eb49bc1f16984ff714e0e110", size = 18579 }, ] [[package]] @@ -6316,7 +6302,7 @@ wheels = [ [[package]] name = "pytest" -version = "8.3.3" +version = "8.3.4" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "colorama", marker = "sys_platform == 'win32'" }, @@ -6326,9 +6312,9 @@ dependencies = [ { name = "pluggy" }, { name = "tomli", marker = "python_full_version < '3.11'" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/8b/6c/62bbd536103af674e227c41a8f3dcd022d591f6eed5facb5a0f31ee33bbc/pytest-8.3.3.tar.gz", hash = "sha256:70b98107bd648308a7952b06e6ca9a50bc660be218d53c257cc1fc94fda10181", size = 1442487 } +sdist = { url = "https://files.pythonhosted.org/packages/05/35/30e0d83068951d90a01852cb1cef56e5d8a09d20c7f511634cc2f7e0372a/pytest-8.3.4.tar.gz", hash = "sha256:965370d062bce11e73868e0335abac31b4d3de0e82f4007408d242b4f8610761", size = 1445919 } wheels = [ - { url = "https://files.pythonhosted.org/packages/6b/77/7440a06a8ead44c7757a64362dd22df5760f9b12dc5f11b6188cd2fc27a0/pytest-8.3.3-py3-none-any.whl", hash = "sha256:a6853c7375b2663155079443d2e45de913a911a11d669df02a50814944db57b2", size = 342341 }, + { url = "https://files.pythonhosted.org/packages/11/92/76a1c94d3afee238333bc0a42b82935dd8f9cf8ce9e336ff87ee14d9e1cf/pytest-8.3.4-py3-none-any.whl", hash = "sha256:50e16d954148559c9a74109af1eaf0c945ba2d8f30f0a3d3335edde19788b6f6", size = 343083 }, ] [[package]] @@ -6345,31 +6331,34 @@ wheels = [ [[package]] name = "pytest-codspeed" -version = "3.0.0" +version = "3.1.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "cffi" }, - { name = "filelock" }, { name = "pytest" }, { name = "rich" }, - { name = "setuptools", marker = "python_full_version >= '3.12'" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/ba/78/40e613268cce75b11cd35ea9fdc280fb648e2233fc4187c76112377b1869/pytest_codspeed-3.0.0.tar.gz", hash = "sha256:c5b80100ea32dd44079bb2db298288763eb8fe859eafa1650a8711bd2c32fd06", size = 12540 } +sdist = { url = "https://files.pythonhosted.org/packages/fd/50/0aacd58f566ac04c005200a07bbc294dc2700f6ca021b34e3cc24652a7bf/pytest_codspeed-3.1.0.tar.gz", hash = "sha256:f29641d27b4ded133b1058a4c859e510a2612ad4217ef9a839ba61750abd2f8a", size = 18219 } wheels = [ - { url = "https://files.pythonhosted.org/packages/a6/79/fa067436033410ac16e5d14b61b1a5f355688930ca8c6a8c61a52b2cbe0a/pytest_codspeed-3.0.0-py3-none-any.whl", hash = "sha256:ab1b8cb9da72e0d394718333d1abc7bea38524e09fd4854bc70a91abbcdcb20e", size = 15640 }, + { url = "https://files.pythonhosted.org/packages/a0/ef/973d9d336647475fa72d3d8d6bd9e404dae11d974335205324d03d490aea/pytest_codspeed-3.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:1cb7c16e5a64cb30bad30f5204c7690f3cbc9ae5b9839ce187ef1727aa5d2d9c", size = 26737 }, + { url = "https://files.pythonhosted.org/packages/ea/e2/73fecf80e888e1396c8fc11bd6e2269a6f8260b22be2352c9bc03a0b6d8b/pytest_codspeed-3.1.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:4d23910893c22ceef6efbdf85d80e803b7fb4a231c9e7676ab08f5ddfc228438", size = 25376 }, + { url = "https://files.pythonhosted.org/packages/9f/b9/87741a1de7167dd56a703f886e48cdc7c71e530c12573db08acd978edc57/pytest_codspeed-3.1.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:fb1495a633a33e15268a1f97d91a4809c868de06319db50cf97b4e9fa426372c", size = 26745 }, + { url = "https://files.pythonhosted.org/packages/d8/87/5d74d9df7e005dd61a2784c8d83511e69c8e38dd4321f5289c43ba3ee665/pytest_codspeed-3.1.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:dbd8a54b99207bd25a4c3f64d9a83ac0f3def91cdd87204ca70a49f822ba919c", size = 25376 }, + { url = "https://files.pythonhosted.org/packages/71/0c/15b26540ed79d07acb51ecd28ad9493b1b284fce269e4d7f0967c82dfa65/pytest_codspeed-3.1.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c4d1ac896ebaea5b365e69b41319b4d09b57dab85ec6234f6ff26116b3795f03", size = 27117 }, + { url = "https://files.pythonhosted.org/packages/1e/67/25012e5408c079415f2afdd36a3a2d468d4cc61d840de0838db9b46fcb69/pytest_codspeed-3.1.0-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:5f0c1857a0a6cce6a23c49f98c588c2eef66db353c76ecbb2fb65c1a2b33a8d5", size = 25872 }, ] [[package]] name = "pytest-cov" -version = "5.0.0" +version = "6.0.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "coverage", extra = ["toml"] }, { name = "pytest" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/74/67/00efc8d11b630c56f15f4ad9c7f9223f1e5ec275aaae3fa9118c6a223ad2/pytest-cov-5.0.0.tar.gz", hash = "sha256:5837b58e9f6ebd335b0f8060eecce69b662415b16dc503883a02f45dfeb14857", size = 63042 } +sdist = { url = "https://files.pythonhosted.org/packages/be/45/9b538de8cef30e17c7b45ef42f538a94889ed6a16f2387a6c89e73220651/pytest-cov-6.0.0.tar.gz", hash = "sha256:fde0b595ca248bb8e2d76f020b465f3b107c9632e6a1d1705f17834c89dcadc0", size = 66945 } wheels = [ - { url = "https://files.pythonhosted.org/packages/78/3a/af5b4fa5961d9a1e6237b530eb87dd04aea6eb83da09d2a4073d81b54ccf/pytest_cov-5.0.0-py3-none-any.whl", hash = "sha256:4f0764a1219df53214206bf1feea4633c3b558a2925c8b59f144f682861ce652", size = 21990 }, + { url = "https://files.pythonhosted.org/packages/36/3b/48e79f2cd6a61dbbd4807b4ed46cb564b4fd50a76166b1c4ea5c1d9e2371/pytest_cov-6.0.0-py3-none-any.whl", hash = "sha256:eee6f1b9e61008bd34975a4d5bab25801eb31898b032dd55addc93e96fcaaa35", size = 22949 }, ] [[package]] @@ -6422,28 +6411,28 @@ wheels = [ [[package]] name = "pytest-profiling" -version = "1.7.0" +version = "1.8.1" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "gprof2dot" }, { name = "pytest" }, { name = "six" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/39/70/22a4b33739f07f1732a63e33bbfbf68e0fa58cfba9d200e76d01921eddbf/pytest-profiling-1.7.0.tar.gz", hash = "sha256:93938f147662225d2b8bd5af89587b979652426a8a6ffd7e73ec4a23e24b7f29", size = 30985 } +sdist = { url = "https://files.pythonhosted.org/packages/44/74/806cafd6f2108d37979ec71e73b2ff7f7db88eabd19d3b79c5d6cc229c36/pytest-profiling-1.8.1.tar.gz", hash = "sha256:3f171fa69d5c82fa9aab76d66abd5f59da69135c37d6ae5bf7557f1b154cb08d", size = 33135 } wheels = [ - { url = "https://files.pythonhosted.org/packages/d9/71/cdb746eaee0d3be65fd777b4ac821f5f051063f3084d4a200ecfd7f7ab40/pytest_profiling-1.7.0-py2.py3-none-any.whl", hash = "sha256:999cc9ac94f2e528e3f5d43465da277429984a1c237ae9818f8cfd0b06acb019", size = 8255 }, + { url = "https://files.pythonhosted.org/packages/e3/ac/c428c66241a144617a8af7a28e2e055e1438d23b949b62ac4b401a69fb79/pytest_profiling-1.8.1-py3-none-any.whl", hash = "sha256:3dd8713a96298b42d83de8f5951df3ada3e61b3e5d2a06956684175529e17aea", size = 9929 }, ] [[package]] name = "pytest-split" -version = "0.9.0" +version = "0.10.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "pytest" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/5e/a9/7b8327a605a48d5094b331de10e01f1f1aec0cb8c5790b5e4d98ac327f05/pytest_split-0.9.0.tar.gz", hash = "sha256:ca52527e4d9024f6ec3aba723527bd276d12096024999b1f5b8445a38da1e81c", size = 13599 } +sdist = { url = "https://files.pythonhosted.org/packages/46/d7/e30ba44adf83f15aee3f636daea54efadf735769edc0f0a7d98163f61038/pytest_split-0.10.0.tar.gz", hash = "sha256:adf80ba9fef7be89500d571e705b4f963dfa05038edf35e4925817e6b34ea66f", size = 13903 } wheels = [ - { url = "https://files.pythonhosted.org/packages/6b/67/8cff7bf04d78ac7fbb88b0985061347943dc3cbeafada27b4accb4527579/pytest_split-0.9.0-py3-none-any.whl", hash = "sha256:9e197df601828d76a1ab615158d9c6253ec9f96e46c1d3ea27187aa5ac0ef9de", size = 11790 }, + { url = "https://files.pythonhosted.org/packages/d6/a7/cad88e9c1109a5c2a320d608daa32e5ee008ccbc766310f54b1cd6b3d69c/pytest_split-0.10.0-py3-none-any.whl", hash = "sha256:466096b086a7147bcd423c6e6c2e57fc62af1c5ea2e256b4ed50fc030fc3dddc", size = 11961 }, ] [[package]] @@ -6535,11 +6524,11 @@ wheels = [ [[package]] name = "python-multipart" -version = "0.0.12" +version = "0.0.19" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/16/6e/7ecfe1366b9270f7f475c76fcfa28812493a6a1abd489b2433851a444f4f/python_multipart-0.0.12.tar.gz", hash = "sha256:045e1f98d719c1ce085ed7f7e1ef9d8ccc8c02ba02b5566d5f7521410ced58cb", size = 35713 } +sdist = { url = "https://files.pythonhosted.org/packages/c1/19/93bfb43a3c41b1dd0fa1fa66a08286f6467d36d30297a7aaab8c0b176a26/python_multipart-0.0.19.tar.gz", hash = "sha256:905502ef39050557b7a6af411f454bc19526529ca46ae6831508438890ce12cc", size = 36886 } wheels = [ - { url = "https://files.pythonhosted.org/packages/f5/0b/c316262244abea7481f95f1e91d7575f3dfcf6455d56d1ffe9839c582eb1/python_multipart-0.0.12-py3-none-any.whl", hash = "sha256:43dcf96cf65888a9cd3423544dd0d75ac10f7aa0c3c28a175bbcd00c9ce1aebf", size = 23246 }, + { url = "https://files.pythonhosted.org/packages/e1/f4/ddd0fcdc454cf3870153ae16a818256523d31c3c8136e216bc6836ed4cd1/python_multipart-0.0.19-py3-none-any.whl", hash = "sha256:f8d5b0b9c618575bf9df01c684ded1d94a338839bdd8223838afacfb4bb2082d", size = 24448 }, ] [[package]] @@ -6776,56 +6765,56 @@ wheels = [ [[package]] name = "regex" -version = "2024.9.11" +version = "2024.11.6" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/f9/38/148df33b4dbca3bd069b963acab5e0fa1a9dbd6820f8c322d0dd6faeff96/regex-2024.9.11.tar.gz", hash = "sha256:6c188c307e8433bcb63dc1915022deb553b4203a70722fc542c363bf120a01fd", size = 399403 } +sdist = { url = "https://files.pythonhosted.org/packages/8e/5f/bd69653fbfb76cf8604468d3b4ec4c403197144c7bfe0e6a5fc9e02a07cb/regex-2024.11.6.tar.gz", hash = "sha256:7ab159b063c52a0333c884e4679f8d7a85112ee3078fe3d9004b2dd875585519", size = 399494 } wheels = [ - { url = "https://files.pythonhosted.org/packages/63/12/497bd6599ce8a239ade68678132296aec5ee25ebea45fc8ba91aa60fceec/regex-2024.9.11-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:1494fa8725c285a81d01dc8c06b55287a1ee5e0e382d8413adc0a9197aac6408", size = 482488 }, - { url = "https://files.pythonhosted.org/packages/c1/24/595ddb9bec2a9b151cdaf9565b0c9f3da9f0cb1dca6c158bc5175332ddf8/regex-2024.9.11-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:0e12c481ad92d129c78f13a2a3662317e46ee7ef96c94fd332e1c29131875b7d", size = 287443 }, - { url = "https://files.pythonhosted.org/packages/69/a8/b2fb45d9715b1469383a0da7968f8cacc2f83e9fbbcd6b8713752dd980a6/regex-2024.9.11-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:16e13a7929791ac1216afde26f712802e3df7bf0360b32e4914dca3ab8baeea5", size = 284561 }, - { url = "https://files.pythonhosted.org/packages/88/87/1ce4a5357216b19b7055e7d3b0efc75a6e426133bf1e7d094321df514257/regex-2024.9.11-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:46989629904bad940bbec2106528140a218b4a36bb3042d8406980be1941429c", size = 783177 }, - { url = "https://files.pythonhosted.org/packages/3c/65/b9f002ab32f7b68e7d1dcabb67926f3f47325b8dbc22cc50b6a043e1d07c/regex-2024.9.11-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a906ed5e47a0ce5f04b2c981af1c9acf9e8696066900bf03b9d7879a6f679fc8", size = 823193 }, - { url = "https://files.pythonhosted.org/packages/22/91/8339dd3abce101204d246e31bc26cdd7ec07c9f91598472459a3a902aa41/regex-2024.9.11-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e9a091b0550b3b0207784a7d6d0f1a00d1d1c8a11699c1a4d93db3fbefc3ad35", size = 809950 }, - { url = "https://files.pythonhosted.org/packages/cb/19/556638aa11c2ec9968a1da998f07f27ec0abb9bf3c647d7c7985ca0b8eea/regex-2024.9.11-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5ddcd9a179c0a6fa8add279a4444015acddcd7f232a49071ae57fa6e278f1f71", size = 782661 }, - { url = "https://files.pythonhosted.org/packages/d1/e9/7a5bc4c6ef8d9cd2bdd83a667888fc35320da96a4cc4da5fa084330f53db/regex-2024.9.11-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6b41e1adc61fa347662b09398e31ad446afadff932a24807d3ceb955ed865cc8", size = 772348 }, - { url = "https://files.pythonhosted.org/packages/f1/0b/29f2105bfac3ed08e704914c38e93b07c784a6655f8a015297ee7173e95b/regex-2024.9.11-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:ced479f601cd2f8ca1fd7b23925a7e0ad512a56d6e9476f79b8f381d9d37090a", size = 697460 }, - { url = "https://files.pythonhosted.org/packages/71/3a/52ff61054d15a4722605f5872ad03962b319a04c1ebaebe570b8b9b7dde1/regex-2024.9.11-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:635a1d96665f84b292e401c3d62775851aedc31d4f8784117b3c68c4fcd4118d", size = 769151 }, - { url = "https://files.pythonhosted.org/packages/97/07/37e460ab5ca84be8e1e197c3b526c5c86993dcc9e13cbc805c35fc2463c1/regex-2024.9.11-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:c0256beda696edcf7d97ef16b2a33a8e5a875affd6fa6567b54f7c577b30a137", size = 777478 }, - { url = "https://files.pythonhosted.org/packages/65/7b/953075723dd5ab00780043ac2f9de667306ff9e2a85332975e9f19279174/regex-2024.9.11-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:3ce4f1185db3fbde8ed8aa223fc9620f276c58de8b0d4f8cc86fd1360829edb6", size = 845373 }, - { url = "https://files.pythonhosted.org/packages/40/b8/3e9484c6230b8b6e8f816ab7c9a080e631124991a4ae2c27a81631777db0/regex-2024.9.11-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:09d77559e80dcc9d24570da3745ab859a9cf91953062e4ab126ba9d5993688ca", size = 845369 }, - { url = "https://files.pythonhosted.org/packages/b7/99/38434984d912edbd2e1969d116257e869578f67461bd7462b894c45ed874/regex-2024.9.11-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7a22ccefd4db3f12b526eccb129390942fe874a3a9fdbdd24cf55773a1faab1a", size = 773935 }, - { url = "https://files.pythonhosted.org/packages/ab/67/43174d2b46fa947b7b9dfe56b6c8a8a76d44223f35b1d64645a732fd1d6f/regex-2024.9.11-cp310-cp310-win32.whl", hash = "sha256:f745ec09bc1b0bd15cfc73df6fa4f726dcc26bb16c23a03f9e3367d357eeedd0", size = 261624 }, - { url = "https://files.pythonhosted.org/packages/c4/2a/4f9c47d9395b6aff24874c761d8d620c0232f97c43ef3cf668c8b355e7a7/regex-2024.9.11-cp310-cp310-win_amd64.whl", hash = "sha256:01c2acb51f8a7d6494c8c5eafe3d8e06d76563d8a8a4643b37e9b2dd8a2ff623", size = 274020 }, - { url = "https://files.pythonhosted.org/packages/86/a1/d526b7b6095a0019aa360948c143aacfeb029919c898701ce7763bbe4c15/regex-2024.9.11-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:2cce2449e5927a0bf084d346da6cd5eb016b2beca10d0013ab50e3c226ffc0df", size = 482483 }, - { url = "https://files.pythonhosted.org/packages/32/d9/bfdd153179867c275719e381e1e8e84a97bd186740456a0dcb3e7125c205/regex-2024.9.11-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:3b37fa423beefa44919e009745ccbf353d8c981516e807995b2bd11c2c77d268", size = 287442 }, - { url = "https://files.pythonhosted.org/packages/33/c4/60f3370735135e3a8d673ddcdb2507a8560d0e759e1398d366e43d000253/regex-2024.9.11-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:64ce2799bd75039b480cc0360907c4fb2f50022f030bf9e7a8705b636e408fad", size = 284561 }, - { url = "https://files.pythonhosted.org/packages/b1/51/91a5ebdff17f9ec4973cb0aa9d37635efec1c6868654bbc25d1543aca4ec/regex-2024.9.11-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a4cc92bb6db56ab0c1cbd17294e14f5e9224f0cc6521167ef388332604e92679", size = 791779 }, - { url = "https://files.pythonhosted.org/packages/07/4a/022c5e6f0891a90cd7eb3d664d6c58ce2aba48bff107b00013f3d6167069/regex-2024.9.11-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d05ac6fa06959c4172eccd99a222e1fbf17b5670c4d596cb1e5cde99600674c4", size = 832605 }, - { url = "https://files.pythonhosted.org/packages/ac/1c/3793990c8c83ca04e018151ddda83b83ecc41d89964f0f17749f027fc44d/regex-2024.9.11-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:040562757795eeea356394a7fb13076ad4f99d3c62ab0f8bdfb21f99a1f85664", size = 818556 }, - { url = "https://files.pythonhosted.org/packages/e9/5c/8b385afbfacb853730682c57be56225f9fe275c5bf02ac1fc88edbff316d/regex-2024.9.11-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6113c008a7780792efc80f9dfe10ba0cd043cbf8dc9a76ef757850f51b4edc50", size = 792808 }, - { url = "https://files.pythonhosted.org/packages/9b/8b/a4723a838b53c771e9240951adde6af58c829fb6a6a28f554e8131f53839/regex-2024.9.11-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8e5fb5f77c8745a60105403a774fe2c1759b71d3e7b4ca237a5e67ad066c7199", size = 781115 }, - { url = "https://files.pythonhosted.org/packages/83/5f/031a04b6017033d65b261259c09043c06f4ef2d4eac841d0649d76d69541/regex-2024.9.11-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:54d9ff35d4515debf14bc27f1e3b38bfc453eff3220f5bce159642fa762fe5d4", size = 778155 }, - { url = "https://files.pythonhosted.org/packages/fd/cd/4660756070b03ce4a66663a43f6c6e7ebc2266cc6b4c586c167917185eb4/regex-2024.9.11-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:df5cbb1fbc74a8305b6065d4ade43b993be03dbe0f8b30032cced0d7740994bd", size = 784614 }, - { url = "https://files.pythonhosted.org/packages/93/8d/65b9bea7df120a7be8337c415b6d256ba786cbc9107cebba3bf8ff09da99/regex-2024.9.11-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:7fb89ee5d106e4a7a51bce305ac4efb981536301895f7bdcf93ec92ae0d91c7f", size = 853744 }, - { url = "https://files.pythonhosted.org/packages/96/a7/fba1eae75eb53a704475baf11bd44b3e6ccb95b316955027eb7748f24ef8/regex-2024.9.11-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:a738b937d512b30bf75995c0159c0ddf9eec0775c9d72ac0202076c72f24aa96", size = 855890 }, - { url = "https://files.pythonhosted.org/packages/45/14/d864b2db80a1a3358534392373e8a281d95b28c29c87d8548aed58813910/regex-2024.9.11-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:e28f9faeb14b6f23ac55bfbbfd3643f5c7c18ede093977f1df249f73fd22c7b1", size = 781887 }, - { url = "https://files.pythonhosted.org/packages/4d/a9/bfb29b3de3eb11dc9b412603437023b8e6c02fb4e11311863d9bf62c403a/regex-2024.9.11-cp311-cp311-win32.whl", hash = "sha256:18e707ce6c92d7282dfce370cd205098384b8ee21544e7cb29b8aab955b66fa9", size = 261644 }, - { url = "https://files.pythonhosted.org/packages/c7/ab/1ad2511cf6a208fde57fafe49829cab8ca018128ab0d0b48973d8218634a/regex-2024.9.11-cp311-cp311-win_amd64.whl", hash = "sha256:313ea15e5ff2a8cbbad96ccef6be638393041b0a7863183c2d31e0c6116688cf", size = 274033 }, - { url = "https://files.pythonhosted.org/packages/6e/92/407531450762bed778eedbde04407f68cbd75d13cee96c6f8d6903d9c6c1/regex-2024.9.11-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:b0d0a6c64fcc4ef9c69bd5b3b3626cc3776520a1637d8abaa62b9edc147a58f7", size = 483590 }, - { url = "https://files.pythonhosted.org/packages/8e/a2/048acbc5ae1f615adc6cba36cc45734e679b5f1e4e58c3c77f0ed611d4e2/regex-2024.9.11-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:49b0e06786ea663f933f3710a51e9385ce0cba0ea56b67107fd841a55d56a231", size = 288175 }, - { url = "https://files.pythonhosted.org/packages/8a/ea/909d8620329ab710dfaf7b4adee41242ab7c9b95ea8d838e9bfe76244259/regex-2024.9.11-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5b513b6997a0b2f10e4fd3a1313568e373926e8c252bd76c960f96fd039cd28d", size = 284749 }, - { url = "https://files.pythonhosted.org/packages/ca/fa/521eb683b916389b4975337873e66954e0f6d8f91bd5774164a57b503185/regex-2024.9.11-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ee439691d8c23e76f9802c42a95cfeebf9d47cf4ffd06f18489122dbb0a7ad64", size = 795181 }, - { url = "https://files.pythonhosted.org/packages/28/db/63047feddc3280cc242f9c74f7aeddc6ee662b1835f00046f57d5630c827/regex-2024.9.11-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a8f877c89719d759e52783f7fe6e1c67121076b87b40542966c02de5503ace42", size = 835842 }, - { url = "https://files.pythonhosted.org/packages/e3/94/86adc259ff8ec26edf35fcca7e334566c1805c7493b192cb09679f9c3dee/regex-2024.9.11-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:23b30c62d0f16827f2ae9f2bb87619bc4fba2044911e2e6c2eb1af0161cdb766", size = 823533 }, - { url = "https://files.pythonhosted.org/packages/29/52/84662b6636061277cb857f658518aa7db6672bc6d1a3f503ccd5aefc581e/regex-2024.9.11-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:85ab7824093d8f10d44330fe1e6493f756f252d145323dd17ab6b48733ff6c0a", size = 797037 }, - { url = "https://files.pythonhosted.org/packages/c3/2a/cd4675dd987e4a7505f0364a958bc41f3b84942de9efaad0ef9a2646681c/regex-2024.9.11-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8dee5b4810a89447151999428fe096977346cf2f29f4d5e29609d2e19e0199c9", size = 784106 }, - { url = "https://files.pythonhosted.org/packages/6f/75/3ea7ec29de0bbf42f21f812f48781d41e627d57a634f3f23947c9a46e303/regex-2024.9.11-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:98eeee2f2e63edae2181c886d7911ce502e1292794f4c5ee71e60e23e8d26b5d", size = 782468 }, - { url = "https://files.pythonhosted.org/packages/d3/67/15519d69b52c252b270e679cb578e22e0c02b8dd4e361f2b04efcc7f2335/regex-2024.9.11-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:57fdd2e0b2694ce6fc2e5ccf189789c3e2962916fb38779d3e3521ff8fe7a822", size = 790324 }, - { url = "https://files.pythonhosted.org/packages/9c/71/eff77d3fe7ba08ab0672920059ec30d63fa7e41aa0fb61c562726e9bd721/regex-2024.9.11-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:d552c78411f60b1fdaafd117a1fca2f02e562e309223b9d44b7de8be451ec5e0", size = 860214 }, - { url = "https://files.pythonhosted.org/packages/81/11/e1bdf84a72372e56f1ea4b833dd583b822a23138a616ace7ab57a0e11556/regex-2024.9.11-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:a0b2b80321c2ed3fcf0385ec9e51a12253c50f146fddb2abbb10f033fe3d049a", size = 859420 }, - { url = "https://files.pythonhosted.org/packages/ea/75/9753e9dcebfa7c3645563ef5c8a58f3a47e799c872165f37c55737dadd3e/regex-2024.9.11-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:18406efb2f5a0e57e3a5881cd9354c1512d3bb4f5c45d96d110a66114d84d23a", size = 787333 }, - { url = "https://files.pythonhosted.org/packages/bc/4e/ba1cbca93141f7416624b3ae63573e785d4bc1834c8be44a8f0747919eca/regex-2024.9.11-cp312-cp312-win32.whl", hash = "sha256:e464b467f1588e2c42d26814231edecbcfe77f5ac414d92cbf4e7b55b2c2a776", size = 262058 }, - { url = "https://files.pythonhosted.org/packages/6e/16/efc5f194778bf43e5888209e5cec4b258005d37c613b67ae137df3b89c53/regex-2024.9.11-cp312-cp312-win_amd64.whl", hash = "sha256:9e8719792ca63c6b8340380352c24dcb8cd7ec49dae36e963742a275dfae6009", size = 273526 }, + { url = "https://files.pythonhosted.org/packages/95/3c/4651f6b130c6842a8f3df82461a8950f923925db8b6961063e82744bddcc/regex-2024.11.6-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:ff590880083d60acc0433f9c3f713c51f7ac6ebb9adf889c79a261ecf541aa91", size = 482674 }, + { url = "https://files.pythonhosted.org/packages/15/51/9f35d12da8434b489c7b7bffc205c474a0a9432a889457026e9bc06a297a/regex-2024.11.6-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:658f90550f38270639e83ce492f27d2c8d2cd63805c65a13a14d36ca126753f0", size = 287684 }, + { url = "https://files.pythonhosted.org/packages/bd/18/b731f5510d1b8fb63c6b6d3484bfa9a59b84cc578ac8b5172970e05ae07c/regex-2024.11.6-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:164d8b7b3b4bcb2068b97428060b2a53be050085ef94eca7f240e7947f1b080e", size = 284589 }, + { url = "https://files.pythonhosted.org/packages/78/a2/6dd36e16341ab95e4c6073426561b9bfdeb1a9c9b63ab1b579c2e96cb105/regex-2024.11.6-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d3660c82f209655a06b587d55e723f0b813d3a7db2e32e5e7dc64ac2a9e86fde", size = 782511 }, + { url = "https://files.pythonhosted.org/packages/1b/2b/323e72d5d2fd8de0d9baa443e1ed70363ed7e7b2fb526f5950c5cb99c364/regex-2024.11.6-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d22326fcdef5e08c154280b71163ced384b428343ae16a5ab2b3354aed12436e", size = 821149 }, + { url = "https://files.pythonhosted.org/packages/90/30/63373b9ea468fbef8a907fd273e5c329b8c9535fee36fc8dba5fecac475d/regex-2024.11.6-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f1ac758ef6aebfc8943560194e9fd0fa18bcb34d89fd8bd2af18183afd8da3a2", size = 809707 }, + { url = "https://files.pythonhosted.org/packages/f2/98/26d3830875b53071f1f0ae6d547f1d98e964dd29ad35cbf94439120bb67a/regex-2024.11.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:997d6a487ff00807ba810e0f8332c18b4eb8d29463cfb7c820dc4b6e7562d0cf", size = 781702 }, + { url = "https://files.pythonhosted.org/packages/87/55/eb2a068334274db86208ab9d5599ffa63631b9f0f67ed70ea7c82a69bbc8/regex-2024.11.6-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:02a02d2bb04fec86ad61f3ea7f49c015a0681bf76abb9857f945d26159d2968c", size = 771976 }, + { url = "https://files.pythonhosted.org/packages/74/c0/be707bcfe98254d8f9d2cff55d216e946f4ea48ad2fd8cf1428f8c5332ba/regex-2024.11.6-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:f02f93b92358ee3f78660e43b4b0091229260c5d5c408d17d60bf26b6c900e86", size = 697397 }, + { url = "https://files.pythonhosted.org/packages/49/dc/bb45572ceb49e0f6509f7596e4ba7031f6819ecb26bc7610979af5a77f45/regex-2024.11.6-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:06eb1be98df10e81ebaded73fcd51989dcf534e3c753466e4b60c4697a003b67", size = 768726 }, + { url = "https://files.pythonhosted.org/packages/5a/db/f43fd75dc4c0c2d96d0881967897926942e935d700863666f3c844a72ce6/regex-2024.11.6-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:040df6fe1a5504eb0f04f048e6d09cd7c7110fef851d7c567a6b6e09942feb7d", size = 775098 }, + { url = "https://files.pythonhosted.org/packages/99/d7/f94154db29ab5a89d69ff893159b19ada89e76b915c1293e98603d39838c/regex-2024.11.6-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:fdabbfc59f2c6edba2a6622c647b716e34e8e3867e0ab975412c5c2f79b82da2", size = 839325 }, + { url = "https://files.pythonhosted.org/packages/f7/17/3cbfab1f23356fbbf07708220ab438a7efa1e0f34195bf857433f79f1788/regex-2024.11.6-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:8447d2d39b5abe381419319f942de20b7ecd60ce86f16a23b0698f22e1b70008", size = 843277 }, + { url = "https://files.pythonhosted.org/packages/7e/f2/48b393b51900456155de3ad001900f94298965e1cad1c772b87f9cfea011/regex-2024.11.6-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:da8f5fc57d1933de22a9e23eec290a0d8a5927a5370d24bda9a6abe50683fe62", size = 773197 }, + { url = "https://files.pythonhosted.org/packages/45/3f/ef9589aba93e084cd3f8471fded352826dcae8489b650d0b9b27bc5bba8a/regex-2024.11.6-cp310-cp310-win32.whl", hash = "sha256:b489578720afb782f6ccf2840920f3a32e31ba28a4b162e13900c3e6bd3f930e", size = 261714 }, + { url = "https://files.pythonhosted.org/packages/42/7e/5f1b92c8468290c465fd50c5318da64319133231415a8aa6ea5ab995a815/regex-2024.11.6-cp310-cp310-win_amd64.whl", hash = "sha256:5071b2093e793357c9d8b2929dfc13ac5f0a6c650559503bb81189d0a3814519", size = 274042 }, + { url = "https://files.pythonhosted.org/packages/58/58/7e4d9493a66c88a7da6d205768119f51af0f684fe7be7bac8328e217a52c/regex-2024.11.6-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:5478c6962ad548b54a591778e93cd7c456a7a29f8eca9c49e4f9a806dcc5d638", size = 482669 }, + { url = "https://files.pythonhosted.org/packages/34/4c/8f8e631fcdc2ff978609eaeef1d6994bf2f028b59d9ac67640ed051f1218/regex-2024.11.6-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:2c89a8cc122b25ce6945f0423dc1352cb9593c68abd19223eebbd4e56612c5b7", size = 287684 }, + { url = "https://files.pythonhosted.org/packages/c5/1b/f0e4d13e6adf866ce9b069e191f303a30ab1277e037037a365c3aad5cc9c/regex-2024.11.6-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:94d87b689cdd831934fa3ce16cc15cd65748e6d689f5d2b8f4f4df2065c9fa20", size = 284589 }, + { url = "https://files.pythonhosted.org/packages/25/4d/ab21047f446693887f25510887e6820b93f791992994f6498b0318904d4a/regex-2024.11.6-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1062b39a0a2b75a9c694f7a08e7183a80c63c0d62b301418ffd9c35f55aaa114", size = 792121 }, + { url = "https://files.pythonhosted.org/packages/45/ee/c867e15cd894985cb32b731d89576c41a4642a57850c162490ea34b78c3b/regex-2024.11.6-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:167ed4852351d8a750da48712c3930b031f6efdaa0f22fa1933716bfcd6bf4a3", size = 831275 }, + { url = "https://files.pythonhosted.org/packages/b3/12/b0f480726cf1c60f6536fa5e1c95275a77624f3ac8fdccf79e6727499e28/regex-2024.11.6-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2d548dafee61f06ebdb584080621f3e0c23fff312f0de1afc776e2a2ba99a74f", size = 818257 }, + { url = "https://files.pythonhosted.org/packages/bf/ce/0d0e61429f603bac433910d99ef1a02ce45a8967ffbe3cbee48599e62d88/regex-2024.11.6-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f2a19f302cd1ce5dd01a9099aaa19cae6173306d1302a43b627f62e21cf18ac0", size = 792727 }, + { url = "https://files.pythonhosted.org/packages/e4/c1/243c83c53d4a419c1556f43777ccb552bccdf79d08fda3980e4e77dd9137/regex-2024.11.6-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:bec9931dfb61ddd8ef2ebc05646293812cb6b16b60cf7c9511a832b6f1854b55", size = 780667 }, + { url = "https://files.pythonhosted.org/packages/c5/f4/75eb0dd4ce4b37f04928987f1d22547ddaf6c4bae697623c1b05da67a8aa/regex-2024.11.6-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:9714398225f299aa85267fd222f7142fcb5c769e73d7733344efc46f2ef5cf89", size = 776963 }, + { url = "https://files.pythonhosted.org/packages/16/5d/95c568574e630e141a69ff8a254c2f188b4398e813c40d49228c9bbd9875/regex-2024.11.6-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:202eb32e89f60fc147a41e55cb086db2a3f8cb82f9a9a88440dcfc5d37faae8d", size = 784700 }, + { url = "https://files.pythonhosted.org/packages/8e/b5/f8495c7917f15cc6fee1e7f395e324ec3e00ab3c665a7dc9d27562fd5290/regex-2024.11.6-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:4181b814e56078e9b00427ca358ec44333765f5ca1b45597ec7446d3a1ef6e34", size = 848592 }, + { url = "https://files.pythonhosted.org/packages/1c/80/6dd7118e8cb212c3c60b191b932dc57db93fb2e36fb9e0e92f72a5909af9/regex-2024.11.6-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:068376da5a7e4da51968ce4c122a7cd31afaaec4fccc7856c92f63876e57b51d", size = 852929 }, + { url = "https://files.pythonhosted.org/packages/11/9b/5a05d2040297d2d254baf95eeeb6df83554e5e1df03bc1a6687fc4ba1f66/regex-2024.11.6-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ac10f2c4184420d881a3475fb2c6f4d95d53a8d50209a2500723d831036f7c45", size = 781213 }, + { url = "https://files.pythonhosted.org/packages/26/b7/b14e2440156ab39e0177506c08c18accaf2b8932e39fb092074de733d868/regex-2024.11.6-cp311-cp311-win32.whl", hash = "sha256:c36f9b6f5f8649bb251a5f3f66564438977b7ef8386a52460ae77e6070d309d9", size = 261734 }, + { url = "https://files.pythonhosted.org/packages/80/32/763a6cc01d21fb3819227a1cc3f60fd251c13c37c27a73b8ff4315433a8e/regex-2024.11.6-cp311-cp311-win_amd64.whl", hash = "sha256:02e28184be537f0e75c1f9b2f8847dc51e08e6e171c6bde130b2687e0c33cf60", size = 274052 }, + { url = "https://files.pythonhosted.org/packages/ba/30/9a87ce8336b172cc232a0db89a3af97929d06c11ceaa19d97d84fa90a8f8/regex-2024.11.6-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:52fb28f528778f184f870b7cf8f225f5eef0a8f6e3778529bdd40c7b3920796a", size = 483781 }, + { url = "https://files.pythonhosted.org/packages/01/e8/00008ad4ff4be8b1844786ba6636035f7ef926db5686e4c0f98093612add/regex-2024.11.6-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:fdd6028445d2460f33136c55eeb1f601ab06d74cb3347132e1c24250187500d9", size = 288455 }, + { url = "https://files.pythonhosted.org/packages/60/85/cebcc0aff603ea0a201667b203f13ba75d9fc8668fab917ac5b2de3967bc/regex-2024.11.6-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:805e6b60c54bf766b251e94526ebad60b7de0c70f70a4e6210ee2891acb70bf2", size = 284759 }, + { url = "https://files.pythonhosted.org/packages/94/2b/701a4b0585cb05472a4da28ee28fdfe155f3638f5e1ec92306d924e5faf0/regex-2024.11.6-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b85c2530be953a890eaffde05485238f07029600e8f098cdf1848d414a8b45e4", size = 794976 }, + { url = "https://files.pythonhosted.org/packages/4b/bf/fa87e563bf5fee75db8915f7352e1887b1249126a1be4813837f5dbec965/regex-2024.11.6-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:bb26437975da7dc36b7efad18aa9dd4ea569d2357ae6b783bf1118dabd9ea577", size = 833077 }, + { url = "https://files.pythonhosted.org/packages/a1/56/7295e6bad94b047f4d0834e4779491b81216583c00c288252ef625c01d23/regex-2024.11.6-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:abfa5080c374a76a251ba60683242bc17eeb2c9818d0d30117b4486be10c59d3", size = 823160 }, + { url = "https://files.pythonhosted.org/packages/fb/13/e3b075031a738c9598c51cfbc4c7879e26729c53aa9cca59211c44235314/regex-2024.11.6-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:70b7fa6606c2881c1db9479b0eaa11ed5dfa11c8d60a474ff0e095099f39d98e", size = 796896 }, + { url = "https://files.pythonhosted.org/packages/24/56/0b3f1b66d592be6efec23a795b37732682520b47c53da5a32c33ed7d84e3/regex-2024.11.6-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0c32f75920cf99fe6b6c539c399a4a128452eaf1af27f39bce8909c9a3fd8cbe", size = 783997 }, + { url = "https://files.pythonhosted.org/packages/f9/a1/eb378dada8b91c0e4c5f08ffb56f25fcae47bf52ad18f9b2f33b83e6d498/regex-2024.11.6-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:982e6d21414e78e1f51cf595d7f321dcd14de1f2881c5dc6a6e23bbbbd68435e", size = 781725 }, + { url = "https://files.pythonhosted.org/packages/83/f2/033e7dec0cfd6dda93390089864732a3409246ffe8b042e9554afa9bff4e/regex-2024.11.6-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:a7c2155f790e2fb448faed6dd241386719802296ec588a8b9051c1f5c481bc29", size = 789481 }, + { url = "https://files.pythonhosted.org/packages/83/23/15d4552ea28990a74e7696780c438aadd73a20318c47e527b47a4a5a596d/regex-2024.11.6-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:149f5008d286636e48cd0b1dd65018548944e495b0265b45e1bffecce1ef7f39", size = 852896 }, + { url = "https://files.pythonhosted.org/packages/e3/39/ed4416bc90deedbfdada2568b2cb0bc1fdb98efe11f5378d9892b2a88f8f/regex-2024.11.6-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:e5364a4502efca094731680e80009632ad6624084aff9a23ce8c8c6820de3e51", size = 860138 }, + { url = "https://files.pythonhosted.org/packages/93/2d/dd56bb76bd8e95bbce684326302f287455b56242a4f9c61f1bc76e28360e/regex-2024.11.6-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:0a86e7eeca091c09e021db8eb72d54751e527fa47b8d5787caf96d9831bd02ad", size = 787692 }, + { url = "https://files.pythonhosted.org/packages/0b/55/31877a249ab7a5156758246b9c59539abbeba22461b7d8adc9e8475ff73e/regex-2024.11.6-cp312-cp312-win32.whl", hash = "sha256:32f9a4c643baad4efa81d549c2aadefaeba12249b2adc5af541759237eee1c54", size = 262135 }, + { url = "https://files.pythonhosted.org/packages/38/ec/ad2d7de49a600cdb8dd78434a1aeffe28b9d6fc42eb36afab4a27ad23384/regex-2024.11.6-cp312-cp312-win_amd64.whl", hash = "sha256:a93c194e2df18f7d264092dc8539b8ffb86b45b899ab976aa15d48214138e81b", size = 273567 }, ] [[package]] @@ -6908,75 +6897,75 @@ wheels = [ [[package]] name = "rich" -version = "13.9.2" +version = "13.9.4" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "markdown-it-py" }, { name = "pygments" }, { name = "typing-extensions", marker = "python_full_version < '3.11'" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/aa/9e/1784d15b057b0075e5136445aaea92d23955aad2c93eaede673718a40d95/rich-13.9.2.tar.gz", hash = "sha256:51a2c62057461aaf7152b4d611168f93a9fc73068f8ded2790f29fe2b5366d0c", size = 222843 } +sdist = { url = "https://files.pythonhosted.org/packages/ab/3a/0316b28d0761c6734d6bc14e770d85506c986c85ffb239e688eeaab2c2bc/rich-13.9.4.tar.gz", hash = "sha256:439594978a49a09530cff7ebc4b5c7103ef57baf48d5ea3184f21d9a2befa098", size = 223149 } wheels = [ - { url = "https://files.pythonhosted.org/packages/67/91/5474b84e505a6ccc295b2d322d90ff6aa0746745717839ee0c5fb4fdcceb/rich-13.9.2-py3-none-any.whl", hash = "sha256:8c82a3d3f8dcfe9e734771313e606b39d8247bb6b826e196f4914b333b743cf1", size = 242117 }, + { url = "https://files.pythonhosted.org/packages/19/71/39c7c0d87f8d4e6c020a393182060eaefeeae6c01dab6a84ec346f2567df/rich-13.9.4-py3-none-any.whl", hash = "sha256:6049d5e6ec054bf2779ab3358186963bac2ea89175919d699e378b99738c2a90", size = 242424 }, ] [[package]] name = "rpds-py" -version = "0.20.0" +version = "0.22.3" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/55/64/b693f262791b818880d17268f3f8181ef799b0d187f6f731b1772e05a29a/rpds_py-0.20.0.tar.gz", hash = "sha256:d72a210824facfdaf8768cf2d7ca25a042c30320b3020de2fa04640920d4e121", size = 25814 } +sdist = { url = "https://files.pythonhosted.org/packages/01/80/cce854d0921ff2f0a9fa831ba3ad3c65cee3a46711addf39a2af52df2cfd/rpds_py-0.22.3.tar.gz", hash = "sha256:e32fee8ab45d3c2db6da19a5323bc3362237c8b653c70194414b892fd06a080d", size = 26771 } wheels = [ - { url = "https://files.pythonhosted.org/packages/71/2d/a7e60483b72b91909e18f29a5c5ae847bac4e2ae95b77bb77e1f41819a58/rpds_py-0.20.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:3ad0fda1635f8439cde85c700f964b23ed5fc2d28016b32b9ee5fe30da5c84e2", size = 318432 }, - { url = "https://files.pythonhosted.org/packages/b5/b4/f15b0c55a6d880ce74170e7e28c3ed6c5acdbbd118df50b91d1dabf86008/rpds_py-0.20.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:9bb4a0d90fdb03437c109a17eade42dfbf6190408f29b2744114d11586611d6f", size = 311333 }, - { url = "https://files.pythonhosted.org/packages/36/10/3f4e490fe6eb069c07c22357d0b4804cd94cb9f8d01345ef9b1d93482b9d/rpds_py-0.20.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c6377e647bbfd0a0b159fe557f2c6c602c159fc752fa316572f012fc0bf67150", size = 366697 }, - { url = "https://files.pythonhosted.org/packages/f5/c8/cd6ab31b4424c7fab3b17e153b6ea7d1bb0d7cabea5c1ef683cc8adb8bc2/rpds_py-0.20.0-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:eb851b7df9dda52dc1415ebee12362047ce771fc36914586b2e9fcbd7d293b3e", size = 368386 }, - { url = "https://files.pythonhosted.org/packages/60/5e/642a44fda6dda90b5237af7a0ef1d088159c30a504852b94b0396eb62125/rpds_py-0.20.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1e0f80b739e5a8f54837be5d5c924483996b603d5502bfff79bf33da06164ee2", size = 395374 }, - { url = "https://files.pythonhosted.org/packages/7c/b5/ff18c093c9e72630f6d6242e5ccb0728ef8265ba0a154b5972f89d23790a/rpds_py-0.20.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5a8c94dad2e45324fc74dce25e1645d4d14df9a4e54a30fa0ae8bad9a63928e3", size = 433189 }, - { url = "https://files.pythonhosted.org/packages/4a/6d/1166a157b227f2333f8e8ae320b6b7ea2a6a38fbe7a3563ad76dffc8608d/rpds_py-0.20.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f8e604fe73ba048c06085beaf51147eaec7df856824bfe7b98657cf436623daf", size = 354849 }, - { url = "https://files.pythonhosted.org/packages/70/a4/70ea49863ea09ae4c2971f2eef58e80b757e3c0f2f618c5815bb751f7847/rpds_py-0.20.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:df3de6b7726b52966edf29663e57306b23ef775faf0ac01a3e9f4012a24a4140", size = 373233 }, - { url = "https://files.pythonhosted.org/packages/3b/d3/822a28152a1e7e2ba0dc5d06cf8736f4cd64b191bb6ec47fb51d1c3c5ccf/rpds_py-0.20.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:cf258ede5bc22a45c8e726b29835b9303c285ab46fc7c3a4cc770736b5304c9f", size = 541852 }, - { url = "https://files.pythonhosted.org/packages/c6/a5/6ef91e4425dc8b3445ff77d292fc4c5e37046462434a0423c4e0a596a8bd/rpds_py-0.20.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:55fea87029cded5df854ca7e192ec7bdb7ecd1d9a3f63d5c4eb09148acf4a7ce", size = 547630 }, - { url = "https://files.pythonhosted.org/packages/72/f8/d5625ee05c4e5c478954a16d9359069c66fe8ac8cd5ddf28f80d3b321837/rpds_py-0.20.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:ae94bd0b2f02c28e199e9bc51485d0c5601f58780636185660f86bf80c89af94", size = 525766 }, - { url = "https://files.pythonhosted.org/packages/94/3c/1ff1ed6ae323b3e16fdfcdae0f0a67f373a6c3d991229dc32b499edeffb7/rpds_py-0.20.0-cp310-none-win32.whl", hash = "sha256:28527c685f237c05445efec62426d285e47a58fb05ba0090a4340b73ecda6dee", size = 199174 }, - { url = "https://files.pythonhosted.org/packages/ec/ba/5762c0aee2403dfea14ed74b0f8a2415cfdbb21cf745d600d9a8ac952c5b/rpds_py-0.20.0-cp310-none-win_amd64.whl", hash = "sha256:238a2d5b1cad28cdc6ed15faf93a998336eb041c4e440dd7f902528b8891b399", size = 213543 }, - { url = "https://files.pythonhosted.org/packages/ab/2a/191374c52d7be0b056cc2a04d718d2244c152f915d4a8d2db2aacc526189/rpds_py-0.20.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:ac2f4f7a98934c2ed6505aead07b979e6f999389f16b714448fb39bbaa86a489", size = 318369 }, - { url = "https://files.pythonhosted.org/packages/0e/6a/2c9fdcc6d235ac0d61ec4fd9981184689c3e682abd05e3caa49bccb9c298/rpds_py-0.20.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:220002c1b846db9afd83371d08d239fdc865e8f8c5795bbaec20916a76db3318", size = 311303 }, - { url = "https://files.pythonhosted.org/packages/d2/b2/725487d29633f64ef8f9cbf4729111a0b61702c8f8e94db1653930f52cce/rpds_py-0.20.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8d7919548df3f25374a1f5d01fbcd38dacab338ef5f33e044744b5c36729c8db", size = 366424 }, - { url = "https://files.pythonhosted.org/packages/7a/8c/668195ab9226d01b7cf7cd9e59c1c0be1df05d602df7ec0cf46f857dcf59/rpds_py-0.20.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:758406267907b3781beee0f0edfe4a179fbd97c0be2e9b1154d7f0a1279cf8e5", size = 368359 }, - { url = "https://files.pythonhosted.org/packages/52/28/356f6a39c1adeb02cf3e5dd526f5e8e54e17899bef045397abcfbf50dffa/rpds_py-0.20.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3d61339e9f84a3f0767b1995adfb171a0d00a1185192718a17af6e124728e0f5", size = 394886 }, - { url = "https://files.pythonhosted.org/packages/a2/65/640fb1a89080a8fb6f4bebd3dafb65a2edba82e2e44c33e6eb0f3e7956f1/rpds_py-0.20.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1259c7b3705ac0a0bd38197565a5d603218591d3f6cee6e614e380b6ba61c6f6", size = 432416 }, - { url = "https://files.pythonhosted.org/packages/a7/e8/85835077b782555d6b3416874b702ea6ebd7db1f145283c9252968670dd5/rpds_py-0.20.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5c1dc0f53856b9cc9a0ccca0a7cc61d3d20a7088201c0937f3f4048c1718a209", size = 354819 }, - { url = "https://files.pythonhosted.org/packages/4f/87/1ac631e923d65cbf36fbcfc6eaa702a169496de1311e54be142f178e53ee/rpds_py-0.20.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:7e60cb630f674a31f0368ed32b2a6b4331b8350d67de53c0359992444b116dd3", size = 373282 }, - { url = "https://files.pythonhosted.org/packages/e4/ce/cb316f7970189e217b998191c7cf0da2ede3d5437932c86a7210dc1e9994/rpds_py-0.20.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:dbe982f38565bb50cb7fb061ebf762c2f254ca3d8c20d4006878766e84266272", size = 541540 }, - { url = "https://files.pythonhosted.org/packages/90/d7/4112d7655ec8aff168ecc91d4ceb51c557336edde7e6ccf6463691a2f253/rpds_py-0.20.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:514b3293b64187172bc77c8fb0cdae26981618021053b30d8371c3a902d4d5ad", size = 547640 }, - { url = "https://files.pythonhosted.org/packages/ab/44/4f61d64dfed98cc71623f3a7fcb612df636a208b4b2c6611eaa985e130a9/rpds_py-0.20.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:d0a26ffe9d4dd35e4dfdd1e71f46401cff0181c75ac174711ccff0459135fa58", size = 525555 }, - { url = "https://files.pythonhosted.org/packages/35/f2/a862d81eacb21f340d584cd1c749c289979f9a60e9229f78bffc0418a199/rpds_py-0.20.0-cp311-none-win32.whl", hash = "sha256:89c19a494bf3ad08c1da49445cc5d13d8fefc265f48ee7e7556839acdacf69d0", size = 199338 }, - { url = "https://files.pythonhosted.org/packages/cc/ec/77d0674f9af4872919f3738018558dd9d37ad3f7ad792d062eadd4af7cba/rpds_py-0.20.0-cp311-none-win_amd64.whl", hash = "sha256:c638144ce971df84650d3ed0096e2ae7af8e62ecbbb7b201c8935c370df00a2c", size = 213585 }, - { url = "https://files.pythonhosted.org/packages/89/b7/f9682c5cc37fcc035f4a0fc33c1fe92ec9cbfdee0cdfd071cf948f53e0df/rpds_py-0.20.0-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:a84ab91cbe7aab97f7446652d0ed37d35b68a465aeef8fc41932a9d7eee2c1a6", size = 321468 }, - { url = "https://files.pythonhosted.org/packages/b8/ad/fc82be4eaceb8d444cb6fc1956ce972b3a0795104279de05e0e4131d0a47/rpds_py-0.20.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:56e27147a5a4c2c21633ff8475d185734c0e4befd1c989b5b95a5d0db699b21b", size = 313062 }, - { url = "https://files.pythonhosted.org/packages/0e/1c/6039e80b13a08569a304dc13476dc986352dca4598e909384db043b4e2bb/rpds_py-0.20.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2580b0c34583b85efec8c5c5ec9edf2dfe817330cc882ee972ae650e7b5ef739", size = 370168 }, - { url = "https://files.pythonhosted.org/packages/dc/c9/5b9aa35acfb58946b4b785bc8e700ac313669e02fb100f3efa6176a83e81/rpds_py-0.20.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:b80d4a7900cf6b66bb9cee5c352b2d708e29e5a37fe9bf784fa97fc11504bf6c", size = 371376 }, - { url = "https://files.pythonhosted.org/packages/7b/dd/0e0dbeb70d8a5357d2814764d467ded98d81d90d3570de4fb05ec7224f6b/rpds_py-0.20.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:50eccbf054e62a7b2209b28dc7a22d6254860209d6753e6b78cfaeb0075d7bee", size = 397200 }, - { url = "https://files.pythonhosted.org/packages/e4/da/a47d931eb688ccfd77a7389e45935c79c41e8098d984d87335004baccb1d/rpds_py-0.20.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:49a8063ea4296b3a7e81a5dfb8f7b2d73f0b1c20c2af401fb0cdf22e14711a96", size = 426824 }, - { url = "https://files.pythonhosted.org/packages/0f/f7/a59a673594e6c2ff2dbc44b00fd4ecdec2fc399bb6a7bd82d612699a0121/rpds_py-0.20.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ea438162a9fcbee3ecf36c23e6c68237479f89f962f82dae83dc15feeceb37e4", size = 357967 }, - { url = "https://files.pythonhosted.org/packages/5f/61/3ba1905396b2cb7088f9503a460b87da33452da54d478cb9241f6ad16d00/rpds_py-0.20.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:18d7585c463087bddcfa74c2ba267339f14f2515158ac4db30b1f9cbdb62c8ef", size = 378905 }, - { url = "https://files.pythonhosted.org/packages/08/31/6d0df9356b4edb0a3a077f1ef714e25ad21f9f5382fc490c2383691885ea/rpds_py-0.20.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:d4c7d1a051eeb39f5c9547e82ea27cbcc28338482242e3e0b7768033cb083821", size = 546348 }, - { url = "https://files.pythonhosted.org/packages/ae/15/d33c021de5cb793101df9961c3c746dfc476953dbbf5db337d8010dffd4e/rpds_py-0.20.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:e4df1e3b3bec320790f699890d41c59d250f6beda159ea3c44c3f5bac1976940", size = 553152 }, - { url = "https://files.pythonhosted.org/packages/70/2d/5536d28c507a4679179ab15aa0049440e4d3dd6752050fa0843ed11e9354/rpds_py-0.20.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:2cf126d33a91ee6eedc7f3197b53e87a2acdac63602c0f03a02dd69e4b138174", size = 528807 }, - { url = "https://files.pythonhosted.org/packages/e3/62/7ebe6ec0d3dd6130921f8cffb7e34afb7f71b3819aa0446a24c5e81245ec/rpds_py-0.20.0-cp312-none-win32.whl", hash = "sha256:8bc7690f7caee50b04a79bf017a8d020c1f48c2a1077ffe172abec59870f1139", size = 200993 }, - { url = "https://files.pythonhosted.org/packages/ec/2f/b938864d66b86a6e4acadefdc56de75ef56f7cafdfd568a6464605457bd5/rpds_py-0.20.0-cp312-none-win_amd64.whl", hash = "sha256:0e13e6952ef264c40587d510ad676a988df19adea20444c2b295e536457bc585", size = 214458 }, - { url = "https://files.pythonhosted.org/packages/06/39/bf1f664c347c946ef56cecaa896e3693d91acc741afa78ebb3fdb7aba08b/rpds_py-0.20.0-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:617c7357272c67696fd052811e352ac54ed1d9b49ab370261a80d3b6ce385045", size = 319444 }, - { url = "https://files.pythonhosted.org/packages/c1/71/876135d3cb90d62468540b84e8e83ff4dc92052ab309bfdea7ea0b9221ad/rpds_py-0.20.0-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:9426133526f69fcaba6e42146b4e12d6bc6c839b8b555097020e2b78ce908dcc", size = 311699 }, - { url = "https://files.pythonhosted.org/packages/f7/da/8ccaeba6a3dda7467aebaf893de9eafd56275e2c90773c83bf15fb0b8374/rpds_py-0.20.0-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:deb62214c42a261cb3eb04d474f7155279c1a8a8c30ac89b7dcb1721d92c3c02", size = 367825 }, - { url = "https://files.pythonhosted.org/packages/04/b6/02a54c47c178d180395b3c9a8bfb3b93906e08f9acf7b4a1067d27c3fae0/rpds_py-0.20.0-pp310-pypy310_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:fcaeb7b57f1a1e071ebd748984359fef83ecb026325b9d4ca847c95bc7311c92", size = 369046 }, - { url = "https://files.pythonhosted.org/packages/a7/64/df4966743aa4def8727dc13d06527c8b13eb7412c1429def2d4701bee520/rpds_py-0.20.0-pp310-pypy310_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d454b8749b4bd70dd0a79f428731ee263fa6995f83ccb8bada706e8d1d3ff89d", size = 395896 }, - { url = "https://files.pythonhosted.org/packages/6f/d9/7ff03ff3642c600f27ff94512bb158a8d815fea5ed4162c75a7e850d6003/rpds_py-0.20.0-pp310-pypy310_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d807dc2051abe041b6649681dce568f8e10668e3c1c6543ebae58f2d7e617855", size = 432427 }, - { url = "https://files.pythonhosted.org/packages/b8/c6/e1b886f7277b3454e55e85332e165091c19114eecb5377b88d892fd36ccf/rpds_py-0.20.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c3c20f0ddeb6e29126d45f89206b8291352b8c5b44384e78a6499d68b52ae511", size = 355403 }, - { url = "https://files.pythonhosted.org/packages/e2/62/e26bd5b944e547c7bfd0b6ca7e306bfa430f8bd298ab72a1217976a7ca8d/rpds_py-0.20.0-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b7f19250ceef892adf27f0399b9e5afad019288e9be756d6919cb58892129f51", size = 374491 }, - { url = "https://files.pythonhosted.org/packages/c3/92/93c5a530898d3a5d1ce087455071ba714b77806ed9ffee4070d0c7a53b7e/rpds_py-0.20.0-pp310-pypy310_pp73-musllinux_1_2_aarch64.whl", hash = "sha256:4f1ed4749a08379555cebf4650453f14452eaa9c43d0a95c49db50c18b7da075", size = 543622 }, - { url = "https://files.pythonhosted.org/packages/01/9e/d68fba289625b5d3c9d1925825d7da716fbf812bda2133ac409021d5db13/rpds_py-0.20.0-pp310-pypy310_pp73-musllinux_1_2_i686.whl", hash = "sha256:dcedf0b42bcb4cfff4101d7771a10532415a6106062f005ab97d1d0ab5681c60", size = 548558 }, - { url = "https://files.pythonhosted.org/packages/bf/d6/4b2fad4898154365f0f2bd72ffd190349274a4c1d6a6f94f02a83bb2b8f1/rpds_py-0.20.0-pp310-pypy310_pp73-musllinux_1_2_x86_64.whl", hash = "sha256:39ed0d010457a78f54090fafb5d108501b5aa5604cc22408fc1c0c77eac14344", size = 525753 }, - { url = "https://files.pythonhosted.org/packages/d2/ea/6f121d1802f3adae1981aea4209ea66f9d3c7f2f6d6b85ef4f13a61d17ef/rpds_py-0.20.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:bb273176be34a746bdac0b0d7e4e2c467323d13640b736c4c477881a3220a989", size = 213529 }, + { url = "https://files.pythonhosted.org/packages/42/2a/ead1d09e57449b99dcc190d8d2323e3a167421d8f8fdf0f217c6f6befe47/rpds_py-0.22.3-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:6c7b99ca52c2c1752b544e310101b98a659b720b21db00e65edca34483259967", size = 359514 }, + { url = "https://files.pythonhosted.org/packages/8f/7e/1254f406b7793b586c68e217a6a24ec79040f85e030fff7e9049069284f4/rpds_py-0.22.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:be2eb3f2495ba669d2a985f9b426c1797b7d48d6963899276d22f23e33d47e37", size = 349031 }, + { url = "https://files.pythonhosted.org/packages/aa/da/17c6a2c73730d426df53675ff9cc6653ac7a60b6438d03c18e1c822a576a/rpds_py-0.22.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:70eb60b3ae9245ddea20f8a4190bd79c705a22f8028aaf8bbdebe4716c3fab24", size = 381485 }, + { url = "https://files.pythonhosted.org/packages/aa/13/2dbacd820466aa2a3c4b747afb18d71209523d353cf865bf8f4796c969ea/rpds_py-0.22.3-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4041711832360a9b75cfb11b25a6a97c8fb49c07b8bd43d0d02b45d0b499a4ff", size = 386794 }, + { url = "https://files.pythonhosted.org/packages/6d/62/96905d0a35ad4e4bc3c098b2f34b2e7266e211d08635baa690643d2227be/rpds_py-0.22.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:64607d4cbf1b7e3c3c8a14948b99345eda0e161b852e122c6bb71aab6d1d798c", size = 423523 }, + { url = "https://files.pythonhosted.org/packages/eb/1b/d12770f2b6a9fc2c3ec0d810d7d440f6d465ccd8b7f16ae5385952c28b89/rpds_py-0.22.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:81e69b0a0e2537f26d73b4e43ad7bc8c8efb39621639b4434b76a3de50c6966e", size = 446695 }, + { url = "https://files.pythonhosted.org/packages/4d/cf/96f1fd75512a017f8e07408b6d5dbeb492d9ed46bfe0555544294f3681b3/rpds_py-0.22.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc27863442d388870c1809a87507727b799c8460573cfbb6dc0eeaef5a11b5ec", size = 381959 }, + { url = "https://files.pythonhosted.org/packages/ab/f0/d1c5b501c8aea85aeb938b555bfdf7612110a2f8cdc21ae0482c93dd0c24/rpds_py-0.22.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:e79dd39f1e8c3504be0607e5fc6e86bb60fe3584bec8b782578c3b0fde8d932c", size = 410420 }, + { url = "https://files.pythonhosted.org/packages/33/3b/45b6c58fb6aad5a569ae40fb890fc494c6b02203505a5008ee6dc68e65f7/rpds_py-0.22.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:e0fa2d4ec53dc51cf7d3bb22e0aa0143966119f42a0c3e4998293a3dd2856b09", size = 557620 }, + { url = "https://files.pythonhosted.org/packages/83/62/3fdd2d3d47bf0bb9b931c4c73036b4ab3ec77b25e016ae26fab0f02be2af/rpds_py-0.22.3-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:fda7cb070f442bf80b642cd56483b5548e43d366fe3f39b98e67cce780cded00", size = 584202 }, + { url = "https://files.pythonhosted.org/packages/04/f2/5dced98b64874b84ca824292f9cee2e3f30f3bcf231d15a903126684f74d/rpds_py-0.22.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:cff63a0272fcd259dcc3be1657b07c929c466b067ceb1c20060e8d10af56f5bf", size = 552787 }, + { url = "https://files.pythonhosted.org/packages/67/13/2273dea1204eda0aea0ef55145da96a9aa28b3f88bb5c70e994f69eda7c3/rpds_py-0.22.3-cp310-cp310-win32.whl", hash = "sha256:9bd7228827ec7bb817089e2eb301d907c0d9827a9e558f22f762bb690b131652", size = 220088 }, + { url = "https://files.pythonhosted.org/packages/4e/80/8c8176b67ad7f4a894967a7a4014ba039626d96f1d4874d53e409b58d69f/rpds_py-0.22.3-cp310-cp310-win_amd64.whl", hash = "sha256:9beeb01d8c190d7581a4d59522cd3d4b6887040dcfc744af99aa59fef3e041a8", size = 231737 }, + { url = "https://files.pythonhosted.org/packages/15/ad/8d1ddf78f2805a71253fcd388017e7b4a0615c22c762b6d35301fef20106/rpds_py-0.22.3-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:d20cfb4e099748ea39e6f7b16c91ab057989712d31761d3300d43134e26e165f", size = 359773 }, + { url = "https://files.pythonhosted.org/packages/c8/75/68c15732293a8485d79fe4ebe9045525502a067865fa4278f178851b2d87/rpds_py-0.22.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:68049202f67380ff9aa52f12e92b1c30115f32e6895cd7198fa2a7961621fc5a", size = 349214 }, + { url = "https://files.pythonhosted.org/packages/3c/4c/7ce50f3070083c2e1b2bbd0fb7046f3da55f510d19e283222f8f33d7d5f4/rpds_py-0.22.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fb4f868f712b2dd4bcc538b0a0c1f63a2b1d584c925e69a224d759e7070a12d5", size = 380477 }, + { url = "https://files.pythonhosted.org/packages/9a/e9/835196a69cb229d5c31c13b8ae603bd2da9a6695f35fe4270d398e1db44c/rpds_py-0.22.3-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bc51abd01f08117283c5ebf64844a35144a0843ff7b2983e0648e4d3d9f10dbb", size = 386171 }, + { url = "https://files.pythonhosted.org/packages/f9/8e/33fc4eba6683db71e91e6d594a2cf3a8fbceb5316629f0477f7ece5e3f75/rpds_py-0.22.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0f3cec041684de9a4684b1572fe28c7267410e02450f4561700ca5a3bc6695a2", size = 422676 }, + { url = "https://files.pythonhosted.org/packages/37/47/2e82d58f8046a98bb9497a8319604c92b827b94d558df30877c4b3c6ccb3/rpds_py-0.22.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7ef9d9da710be50ff6809fed8f1963fecdfecc8b86656cadfca3bc24289414b0", size = 446152 }, + { url = "https://files.pythonhosted.org/packages/e1/78/79c128c3e71abbc8e9739ac27af11dc0f91840a86fce67ff83c65d1ba195/rpds_py-0.22.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:59f4a79c19232a5774aee369a0c296712ad0e77f24e62cad53160312b1c1eaa1", size = 381300 }, + { url = "https://files.pythonhosted.org/packages/c9/5b/2e193be0e8b228c1207f31fa3ea79de64dadb4f6a4833111af8145a6bc33/rpds_py-0.22.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:1a60bce91f81ddaac922a40bbb571a12c1070cb20ebd6d49c48e0b101d87300d", size = 409636 }, + { url = "https://files.pythonhosted.org/packages/c2/3f/687c7100b762d62186a1c1100ffdf99825f6fa5ea94556844bbbd2d0f3a9/rpds_py-0.22.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:e89391e6d60251560f0a8f4bd32137b077a80d9b7dbe6d5cab1cd80d2746f648", size = 556708 }, + { url = "https://files.pythonhosted.org/packages/8c/a2/c00cbc4b857e8b3d5e7f7fc4c81e23afd8c138b930f4f3ccf9a41a23e9e4/rpds_py-0.22.3-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:e3fb866d9932a3d7d0c82da76d816996d1667c44891bd861a0f97ba27e84fc74", size = 583554 }, + { url = "https://files.pythonhosted.org/packages/d0/08/696c9872cf56effdad9ed617ac072f6774a898d46b8b8964eab39ec562d2/rpds_py-0.22.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:1352ae4f7c717ae8cba93421a63373e582d19d55d2ee2cbb184344c82d2ae55a", size = 552105 }, + { url = "https://files.pythonhosted.org/packages/18/1f/4df560be1e994f5adf56cabd6c117e02de7c88ee238bb4ce03ed50da9d56/rpds_py-0.22.3-cp311-cp311-win32.whl", hash = "sha256:b0b4136a252cadfa1adb705bb81524eee47d9f6aab4f2ee4fa1e9d3cd4581f64", size = 220199 }, + { url = "https://files.pythonhosted.org/packages/b8/1b/c29b570bc5db8237553002788dc734d6bd71443a2ceac2a58202ec06ef12/rpds_py-0.22.3-cp311-cp311-win_amd64.whl", hash = "sha256:8bd7c8cfc0b8247c8799080fbff54e0b9619e17cdfeb0478ba7295d43f635d7c", size = 231775 }, + { url = "https://files.pythonhosted.org/packages/75/47/3383ee3bd787a2a5e65a9b9edc37ccf8505c0a00170e3a5e6ea5fbcd97f7/rpds_py-0.22.3-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:27e98004595899949bd7a7b34e91fa7c44d7a97c40fcaf1d874168bb652ec67e", size = 352334 }, + { url = "https://files.pythonhosted.org/packages/40/14/aa6400fa8158b90a5a250a77f2077c0d0cd8a76fce31d9f2b289f04c6dec/rpds_py-0.22.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:1978d0021e943aae58b9b0b196fb4895a25cc53d3956b8e35e0b7682eefb6d56", size = 342111 }, + { url = "https://files.pythonhosted.org/packages/7d/06/395a13bfaa8a28b302fb433fb285a67ce0ea2004959a027aea8f9c52bad4/rpds_py-0.22.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:655ca44a831ecb238d124e0402d98f6212ac527a0ba6c55ca26f616604e60a45", size = 384286 }, + { url = "https://files.pythonhosted.org/packages/43/52/d8eeaffab047e6b7b7ef7f00d5ead074a07973968ffa2d5820fa131d7852/rpds_py-0.22.3-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:feea821ee2a9273771bae61194004ee2fc33f8ec7db08117ef9147d4bbcbca8e", size = 391739 }, + { url = "https://files.pythonhosted.org/packages/83/31/52dc4bde85c60b63719610ed6f6d61877effdb5113a72007679b786377b8/rpds_py-0.22.3-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:22bebe05a9ffc70ebfa127efbc429bc26ec9e9b4ee4d15a740033efda515cf3d", size = 427306 }, + { url = "https://files.pythonhosted.org/packages/70/d5/1bab8e389c2261dba1764e9e793ed6830a63f830fdbec581a242c7c46bda/rpds_py-0.22.3-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3af6e48651c4e0d2d166dc1b033b7042ea3f871504b6805ba5f4fe31581d8d38", size = 442717 }, + { url = "https://files.pythonhosted.org/packages/82/a1/a45f3e30835b553379b3a56ea6c4eb622cf11e72008229af840e4596a8ea/rpds_py-0.22.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e67ba3c290821343c192f7eae1d8fd5999ca2dc99994114643e2f2d3e6138b15", size = 385721 }, + { url = "https://files.pythonhosted.org/packages/a6/27/780c942de3120bdd4d0e69583f9c96e179dfff082f6ecbb46b8d6488841f/rpds_py-0.22.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:02fbb9c288ae08bcb34fb41d516d5eeb0455ac35b5512d03181d755d80810059", size = 415824 }, + { url = "https://files.pythonhosted.org/packages/94/0b/aa0542ca88ad20ea719b06520f925bae348ea5c1fdf201b7e7202d20871d/rpds_py-0.22.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:f56a6b404f74ab372da986d240e2e002769a7d7102cc73eb238a4f72eec5284e", size = 561227 }, + { url = "https://files.pythonhosted.org/packages/0d/92/3ed77d215f82c8f844d7f98929d56cc321bb0bcfaf8f166559b8ec56e5f1/rpds_py-0.22.3-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:0a0461200769ab3b9ab7e513f6013b7a97fdeee41c29b9db343f3c5a8e2b9e61", size = 587424 }, + { url = "https://files.pythonhosted.org/packages/09/42/cacaeb047a22cab6241f107644f230e2935d4efecf6488859a7dd82fc47d/rpds_py-0.22.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:8633e471c6207a039eff6aa116e35f69f3156b3989ea3e2d755f7bc41754a4a7", size = 555953 }, + { url = "https://files.pythonhosted.org/packages/e6/52/c921dc6d5f5d45b212a456c1f5b17df1a471127e8037eb0972379e39dff4/rpds_py-0.22.3-cp312-cp312-win32.whl", hash = "sha256:593eba61ba0c3baae5bc9be2f5232430453fb4432048de28399ca7376de9c627", size = 221339 }, + { url = "https://files.pythonhosted.org/packages/f2/c7/f82b5be1e8456600395366f86104d1bd8d0faed3802ad511ef6d60c30d98/rpds_py-0.22.3-cp312-cp312-win_amd64.whl", hash = "sha256:d115bffdd417c6d806ea9069237a4ae02f513b778e3789a359bc5856e0404cc4", size = 235786 }, + { url = "https://files.pythonhosted.org/packages/8b/63/e29f8ee14fcf383574f73b6bbdcbec0fbc2e5fc36b4de44d1ac389b1de62/rpds_py-0.22.3-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:d48424e39c2611ee1b84ad0f44fb3b2b53d473e65de061e3f460fc0be5f1939d", size = 360786 }, + { url = "https://files.pythonhosted.org/packages/d3/e0/771ee28b02a24e81c8c0e645796a371350a2bb6672753144f36ae2d2afc9/rpds_py-0.22.3-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:24e8abb5878e250f2eb0d7859a8e561846f98910326d06c0d51381fed59357bd", size = 350589 }, + { url = "https://files.pythonhosted.org/packages/cf/49/abad4c4a1e6f3adf04785a99c247bfabe55ed868133e2d1881200aa5d381/rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4b232061ca880db21fa14defe219840ad9b74b6158adb52ddf0e87bead9e8493", size = 381848 }, + { url = "https://files.pythonhosted.org/packages/3a/7d/f4bc6d6fbe6af7a0d2b5f2ee77079efef7c8528712745659ec0026888998/rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ac0a03221cdb5058ce0167ecc92a8c89e8d0decdc9e99a2ec23380793c4dcb96", size = 387879 }, + { url = "https://files.pythonhosted.org/packages/13/b0/575c797377fdcd26cedbb00a3324232e4cb2c5d121f6e4b0dbf8468b12ef/rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:eb0c341fa71df5a4595f9501df4ac5abfb5a09580081dffbd1ddd4654e6e9123", size = 423916 }, + { url = "https://files.pythonhosted.org/packages/54/78/87157fa39d58f32a68d3326f8a81ad8fb99f49fe2aa7ad9a1b7d544f9478/rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bf9db5488121b596dbfc6718c76092fda77b703c1f7533a226a5a9f65248f8ad", size = 448410 }, + { url = "https://files.pythonhosted.org/packages/59/69/860f89996065a88be1b6ff2d60e96a02b920a262d8aadab99e7903986597/rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0b8db6b5b2d4491ad5b6bdc2bc7c017eec108acbf4e6785f42a9eb0ba234f4c9", size = 382841 }, + { url = "https://files.pythonhosted.org/packages/bd/d7/bc144e10d27e3cb350f98df2492a319edd3caaf52ddfe1293f37a9afbfd7/rpds_py-0.22.3-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b3d504047aba448d70cf6fa22e06cb09f7cbd761939fdd47604f5e007675c24e", size = 409662 }, + { url = "https://files.pythonhosted.org/packages/14/2a/6bed0b05233c291a94c7e89bc76ffa1c619d4e1979fbfe5d96024020c1fb/rpds_py-0.22.3-pp310-pypy310_pp73-musllinux_1_2_aarch64.whl", hash = "sha256:e61b02c3f7a1e0b75e20c3978f7135fd13cb6cf551bf4a6d29b999a88830a338", size = 558221 }, + { url = "https://files.pythonhosted.org/packages/11/23/cd8f566de444a137bc1ee5795e47069a947e60810ba4152886fe5308e1b7/rpds_py-0.22.3-pp310-pypy310_pp73-musllinux_1_2_i686.whl", hash = "sha256:e35ba67d65d49080e8e5a1dd40101fccdd9798adb9b050ff670b7d74fa41c566", size = 583780 }, + { url = "https://files.pythonhosted.org/packages/8d/63/79c3602afd14d501f751e615a74a59040328da5ef29ed5754ae80d236b84/rpds_py-0.22.3-pp310-pypy310_pp73-musllinux_1_2_x86_64.whl", hash = "sha256:26fd7cac7dd51011a245f29a2cc6489c4608b5a8ce8d75661bb4a1066c52dfbe", size = 553619 }, + { url = "https://files.pythonhosted.org/packages/9f/2e/c5c1689e80298d4e94c75b70faada4c25445739d91b94c211244a3ed7ed1/rpds_py-0.22.3-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:177c7c0fce2855833819c98e43c262007f42ce86651ffbb84f37883308cb0e7d", size = 233338 }, ] [[package]] @@ -7018,14 +7007,14 @@ wheels = [ [[package]] name = "s3transfer" -version = "0.10.3" +version = "0.10.4" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "botocore" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/a0/a8/e0a98fd7bd874914f0608ef7c90ffde17e116aefad765021de0f012690a2/s3transfer-0.10.3.tar.gz", hash = "sha256:4f50ed74ab84d474ce614475e0b8d5047ff080810aac5d01ea25231cfc944b0c", size = 144591 } +sdist = { url = "https://files.pythonhosted.org/packages/c0/0a/1cdbabf9edd0ea7747efdf6c9ab4e7061b085aa7f9bfc36bb1601563b069/s3transfer-0.10.4.tar.gz", hash = "sha256:29edc09801743c21eb5ecbc617a152df41d3c287f67b615f73e5f750583666a7", size = 145287 } wheels = [ - { url = "https://files.pythonhosted.org/packages/e5/c0/b0fba8259b61c938c9733da9346b9f93e00881a9db22aafdd72f6ae0ec05/s3transfer-0.10.3-py3-none-any.whl", hash = "sha256:263ed587a5803c6c708d3ce44dc4dfedaab4c1a32e8329bab818933d79ddcf5d", size = 82625 }, + { url = "https://files.pythonhosted.org/packages/66/05/7957af15543b8c9799209506df4660cba7afc4cf94bfb60513827e96bed6/s3transfer-0.10.4-py3-none-any.whl", hash = "sha256:244a76a24355363a68164241438de1b72f8781664920260c48465896b712a41e", size = 83175 }, ] [[package]] @@ -7090,7 +7079,7 @@ wheels = [ [[package]] name = "scikit-learn" -version = "1.5.2" +version = "1.6.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "joblib" }, @@ -7098,23 +7087,23 @@ dependencies = [ { name = "scipy" }, { name = "threadpoolctl" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/37/59/44985a2bdc95c74e34fef3d10cb5d93ce13b0e2a7baefffe1b53853b502d/scikit_learn-1.5.2.tar.gz", hash = "sha256:b4237ed7b3fdd0a4882792e68ef2545d5baa50aca3bb45aa7df468138ad8f94d", size = 7001680 } +sdist = { url = "https://files.pythonhosted.org/packages/fa/19/5aa2002044afc297ecaf1e3517ed07bba4aece3b5613b5160c1212995fc8/scikit_learn-1.6.0.tar.gz", hash = "sha256:9d58481f9f7499dff4196927aedd4285a0baec8caa3790efbe205f13de37dd6e", size = 7074944 } wheels = [ - { url = "https://files.pythonhosted.org/packages/98/89/be41419b4bec629a4691183a5eb1796f91252a13a5ffa243fd958cad7e91/scikit_learn-1.5.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:299406827fb9a4f862626d0fe6c122f5f87f8910b86fe5daa4c32dcd742139b6", size = 12106070 }, - { url = "https://files.pythonhosted.org/packages/bf/e0/3b6d777d375f3b685f433c93384cdb724fb078e1dc8f8ff0950467e56c30/scikit_learn-1.5.2-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:2d4cad1119c77930b235579ad0dc25e65c917e756fe80cab96aa3b9428bd3fb0", size = 10971758 }, - { url = "https://files.pythonhosted.org/packages/7b/31/eb7dd56c371640753953277de11356c46a3149bfeebb3d7dcd90b993715a/scikit_learn-1.5.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8c412ccc2ad9bf3755915e3908e677b367ebc8d010acbb3f182814524f2e5540", size = 12500080 }, - { url = "https://files.pythonhosted.org/packages/4c/1e/a7c7357e704459c7d56a18df4a0bf08669442d1f8878cc0864beccd6306a/scikit_learn-1.5.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3a686885a4b3818d9e62904d91b57fa757fc2bed3e465c8b177be652f4dd37c8", size = 13347241 }, - { url = "https://files.pythonhosted.org/packages/48/76/154ebda6794faf0b0f3ccb1b5cd9a19f0a63cb9e1f3d2c61b6114002677b/scikit_learn-1.5.2-cp310-cp310-win_amd64.whl", hash = "sha256:c15b1ca23d7c5f33cc2cb0a0d6aaacf893792271cddff0edbd6a40e8319bc113", size = 11000477 }, - { url = "https://files.pythonhosted.org/packages/ff/91/609961972f694cb9520c4c3d201e377a26583e1eb83bc5a334c893729214/scikit_learn-1.5.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:03b6158efa3faaf1feea3faa884c840ebd61b6484167c711548fce208ea09445", size = 12088580 }, - { url = "https://files.pythonhosted.org/packages/cd/7a/19fe32c810c5ceddafcfda16276d98df299c8649e24e84d4f00df4a91e01/scikit_learn-1.5.2-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:1ff45e26928d3b4eb767a8f14a9a6efbf1cbff7c05d1fb0f95f211a89fd4f5de", size = 10975994 }, - { url = "https://files.pythonhosted.org/packages/4c/75/62e49f8a62bf3c60b0e64d0fce540578ee4f0e752765beb2e1dc7c6d6098/scikit_learn-1.5.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f763897fe92d0e903aa4847b0aec0e68cadfff77e8a0687cabd946c89d17e675", size = 12465782 }, - { url = "https://files.pythonhosted.org/packages/49/21/3723de321531c9745e40f1badafd821e029d346155b6c79704e0b7197552/scikit_learn-1.5.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f8b0ccd4a902836493e026c03256e8b206656f91fbcc4fde28c57a5b752561f1", size = 13322034 }, - { url = "https://files.pythonhosted.org/packages/17/1c/ccdd103cfcc9435a18819856fbbe0c20b8fa60bfc3343580de4be13f0668/scikit_learn-1.5.2-cp311-cp311-win_amd64.whl", hash = "sha256:6c16d84a0d45e4894832b3c4d0bf73050939e21b99b01b6fd59cbb0cf39163b6", size = 11015224 }, - { url = "https://files.pythonhosted.org/packages/a4/db/b485c1ac54ff3bd9e7e6b39d3cc6609c4c76a65f52ab0a7b22b6c3ab0e9d/scikit_learn-1.5.2-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:f932a02c3f4956dfb981391ab24bda1dbd90fe3d628e4b42caef3e041c67707a", size = 12110344 }, - { url = "https://files.pythonhosted.org/packages/54/1a/7deb52fa23aebb855431ad659b3c6a2e1709ece582cb3a63d66905e735fe/scikit_learn-1.5.2-cp312-cp312-macosx_12_0_arm64.whl", hash = "sha256:3b923d119d65b7bd555c73be5423bf06c0105678ce7e1f558cb4b40b0a5502b1", size = 11033502 }, - { url = "https://files.pythonhosted.org/packages/a1/32/4a7a205b14c11225609b75b28402c196e4396ac754dab6a81971b811781c/scikit_learn-1.5.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f60021ec1574e56632be2a36b946f8143bf4e5e6af4a06d85281adc22938e0dd", size = 12085794 }, - { url = "https://files.pythonhosted.org/packages/c6/29/044048c5e911373827c0e1d3051321b9183b2a4f8d4e2f11c08fcff83f13/scikit_learn-1.5.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:394397841449853c2290a32050382edaec3da89e35b3e03d6cc966aebc6a8ae6", size = 12945797 }, - { url = "https://files.pythonhosted.org/packages/aa/ce/c0b912f2f31aeb1b756a6ba56bcd84dd1f8a148470526a48515a3f4d48cd/scikit_learn-1.5.2-cp312-cp312-win_amd64.whl", hash = "sha256:57cc1786cfd6bd118220a92ede80270132aa353647684efa385a74244a41e3b1", size = 10985467 }, + { url = "https://files.pythonhosted.org/packages/c0/97/55060f91a5e7c4df945e5a69b16148b5f2256e6e1ea3f17da8e27edf9953/scikit_learn-1.6.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:366fb3fa47dce90afed3d6106183f4978d6f24cfd595c2373424171b915ee718", size = 12060299 }, + { url = "https://files.pythonhosted.org/packages/36/7b/8c5dfc64a8344ebf2ae493d59af4b3650588051f654e164ff4f9952877b3/scikit_learn-1.6.0-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:59cd96a8d9f8dfd546f5d6e9787e1b989e981388d7803abbc9efdcde61e47460", size = 11105443 }, + { url = "https://files.pythonhosted.org/packages/25/9f/61544f2a5cae1bc27c97f0ec9ffcc9837e469f215817608840a4ccbb277a/scikit_learn-1.6.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:efa7a579606c73a0b3d210e33ea410ea9e1af7933fe324cb7e6fbafae4ea5948", size = 12637137 }, + { url = "https://files.pythonhosted.org/packages/50/79/d21599fc44d2d497ced440480670b6314ebc00308e3bae0d0ebca44cd481/scikit_learn-1.6.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a46d3ca0f11a540b8eaddaf5e38172d8cd65a86cb3e3632161ec96c0cffb774c", size = 13490128 }, + { url = "https://files.pythonhosted.org/packages/ff/87/788da20cfefcd261123d4bb015b2de076e49cdd3b811b55e6811acd3cb21/scikit_learn-1.6.0-cp310-cp310-win_amd64.whl", hash = "sha256:5be4577769c5dde6e1b53de8e6520f9b664ab5861dd57acee47ad119fd7405d6", size = 11118524 }, + { url = "https://files.pythonhosted.org/packages/07/95/070d6e70f735d13f1c10afebb65ba3526125b7d6c6fc7022651a4a061148/scikit_learn-1.6.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:1f50b4f24cf12a81c3c09958ae3b864d7534934ca66ded3822de4996d25d7285", size = 12095168 }, + { url = "https://files.pythonhosted.org/packages/72/3d/0381e3a59ebd4154e6a61b0ceaf299c3c141035033dd3b868776cd9af02d/scikit_learn-1.6.0-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:eb9ae21f387826da14b0b9cb1034f5048ddb9182da429c689f5f4a87dc96930b", size = 11108880 }, + { url = "https://files.pythonhosted.org/packages/fe/2d/0999ae3eed2ac67b1b3cd7fc33370bd5ca59a7514ffe43ae2b6f3cd85b9b/scikit_learn-1.6.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0baa91eeb8c32632628874a5c91885eaedd23b71504d24227925080da075837a", size = 12585449 }, + { url = "https://files.pythonhosted.org/packages/0e/ec/1b15b59c6cc7a993320a52234369e787f50345a4753e50d5a015a91e1a20/scikit_learn-1.6.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3c716d13ba0a2f8762d96ff78d3e0cde90bc9c9b5c13d6ab6bb9b2d6ca6705fd", size = 13489728 }, + { url = "https://files.pythonhosted.org/packages/96/a2/cbfb5743de748d574ffdfd557e9cb29ba4f8b8a3e07836c6c176f713de2f/scikit_learn-1.6.0-cp311-cp311-win_amd64.whl", hash = "sha256:9aafd94bafc841b626681e626be27bf1233d5a0f20f0a6fdb4bee1a1963c6643", size = 11132946 }, + { url = "https://files.pythonhosted.org/packages/18/0c/a5de627aa57b028aea7026cb3bbeaf63be3158adc118212d6cc7843d939a/scikit_learn-1.6.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:04a5ba45c12a5ff81518aa4f1604e826a45d20e53da47b15871526cda4ff5174", size = 12096999 }, + { url = "https://files.pythonhosted.org/packages/a3/7d/02a96e6fb28ddb213e84b1b4a44148d26ec96fc9db9c74e050277e009892/scikit_learn-1.6.0-cp312-cp312-macosx_12_0_arm64.whl", hash = "sha256:21fadfc2ad7a1ce8bd1d90f23d17875b84ec765eecbbfc924ff11fb73db582ce", size = 11160579 }, + { url = "https://files.pythonhosted.org/packages/70/28/77b071f541d75247e6c3403f19aaa634371e972691f6aa1838ca9fd4cc52/scikit_learn-1.6.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:30f34bb5fde90e020653bb84dcb38b6c83f90c70680dbd8c38bd9becbad7a127", size = 12246543 }, + { url = "https://files.pythonhosted.org/packages/17/0e/e6bb84074f1081245a165c0ee775ecef24beae9d2f2e24bcac0c9f155f13/scikit_learn-1.6.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1dad624cffe3062276a0881d4e441bc9e3b19d02d17757cd6ae79a9d192a0027", size = 13140402 }, + { url = "https://files.pythonhosted.org/packages/21/1d/3df58df8bd425f425df9f90b316618ace62b7f1f838ac1580191025cc735/scikit_learn-1.6.0-cp312-cp312-win_amd64.whl", hash = "sha256:2fce7950a3fad85e0a61dc403df0f9345b53432ac0e47c50da210d22c60b6d85", size = 11103596 }, ] [[package]] @@ -7154,7 +7143,7 @@ wheels = [ [[package]] name = "selenium" -version = "4.25.0" +version = "4.27.1" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "certifi" }, @@ -7164,9 +7153,9 @@ dependencies = [ { name = "urllib3", extra = ["socks"] }, { name = "websocket-client" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/0e/5a/d3735b189b91715fd0f5a9b8d55e2605061309849470e96ab830f02cba40/selenium-4.25.0.tar.gz", hash = "sha256:95d08d3b82fb353f3c474895154516604c7f0e6a9a565ae6498ef36c9bac6921", size = 957765 } +sdist = { url = "https://files.pythonhosted.org/packages/44/8c/62c47c91072aa03af1c3b7d7f1c59b987db41c9fec0f158fb03a0da51aa6/selenium-4.27.1.tar.gz", hash = "sha256:5296c425a75ff1b44d0d5199042b36a6d1ef76c04fb775b97b40be739a9caae2", size = 973526 } wheels = [ - { url = "https://files.pythonhosted.org/packages/aa/85/fa44f23dd5d5066a72f7c4304cce4b5ff9a6e7fd92431a48b2c63fbf63ec/selenium-4.25.0-py3-none-any.whl", hash = "sha256:3798d2d12b4a570bc5790163ba57fef10b2afee958bf1d80f2a3cf07c4141f33", size = 9693127 }, + { url = "https://files.pythonhosted.org/packages/a6/1e/5f1a5dd2a28528c4b3ec6e076b58e4c035810c805328f9936123283ca14e/selenium-4.27.1-py3-none-any.whl", hash = "sha256:b89b1f62b5cfe8025868556fe82360d6b649d464f75d2655cb966c8f8447ea18", size = 9707007 }, ] [[package]] @@ -7180,7 +7169,7 @@ wheels = [ [[package]] name = "sentence-transformers" -version = "3.2.0" +version = "3.3.1" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "huggingface-hub" }, @@ -7191,22 +7180,22 @@ dependencies = [ { name = "tqdm" }, { name = "transformers" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/77/aa/ccd95cc81156e19173d7e102fa96137560b5fbef4f7c640076f201b712d5/sentence_transformers-3.2.0.tar.gz", hash = "sha256:4da78ba340fffc48d60a25415145cbe665216d374c948ec54c3163bd352bcc27", size = 202337 } +sdist = { url = "https://files.pythonhosted.org/packages/79/0a/c677efe908b20e7e8d4ed6cce3a3447eebc7dc5e348e458f5f9a44a72b00/sentence_transformers-3.3.1.tar.gz", hash = "sha256:9635dbfb11c6b01d036b9cfcee29f7716ab64cf2407ad9f403a2e607da2ac48b", size = 217914 } wheels = [ - { url = "https://files.pythonhosted.org/packages/e7/78/2835963e7c03865392e88008629d9b81db386fedfcfac006d5c6454b8ecf/sentence_transformers-3.2.0-py3-none-any.whl", hash = "sha256:02dbe96d669d30084ea11af94e7c17895c31748e86f20af4dbcc4ea6522b3506", size = 255175 }, + { url = "https://files.pythonhosted.org/packages/8b/c8/990e22a465e4771338da434d799578865d6d7ef1fdb50bd844b7ecdcfa19/sentence_transformers-3.3.1-py3-none-any.whl", hash = "sha256:abffcc79dab37b7d18d21a26d5914223dd42239cfe18cb5e111c66c54b658ae7", size = 268797 }, ] [[package]] name = "sentry-sdk" -version = "2.16.0" +version = "2.19.2" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "certifi" }, { name = "urllib3" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/80/63/59640a54963747d2c4b2d149412b2024abed13bacd4e8d16ae5babb97da0/sentry_sdk-2.16.0.tar.gz", hash = "sha256:90f733b32e15dfc1999e6b7aca67a38688a567329de4d6e184154a73f96c6892", size = 290180 } +sdist = { url = "https://files.pythonhosted.org/packages/36/4a/eccdcb8c2649d53440ae1902447b86e2e2ad1bc84207c80af9696fa07614/sentry_sdk-2.19.2.tar.gz", hash = "sha256:467df6e126ba242d39952375dd816fbee0f217d119bf454a8ce74cf1e7909e8d", size = 299047 } wheels = [ - { url = "https://files.pythonhosted.org/packages/b3/aa/9f8dce2aec2e95d48c057ff3bcac48958cd15f67d4e9e80e74b46c324abf/sentry_sdk-2.16.0-py2.py3-none-any.whl", hash = "sha256:49139c31ebcd398f4f6396b18910610a0c1602f6e67083240c33019d1f6aa30c", size = 313785 }, + { url = "https://files.pythonhosted.org/packages/31/4d/74597bb6bcc23abc774b8901277652c61331a9d4d0a8d1bdb20679b9bbcb/sentry_sdk-2.19.2-py2.py3-none-any.whl", hash = "sha256:ebdc08228b4d131128e568d696c210d846e5b9d70aa0327dec6b1272d9d40b84", size = 322942 }, ] [package.optional-dependencies] @@ -7219,11 +7208,11 @@ loguru = [ [[package]] name = "setuptools" -version = "75.1.0" +version = "75.6.0" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/27/b8/f21073fde99492b33ca357876430822e4800cdf522011f18041351dfa74b/setuptools-75.1.0.tar.gz", hash = "sha256:d59a21b17a275fb872a9c3dae73963160ae079f1049ed956880cd7c09b120538", size = 1348057 } +sdist = { url = "https://files.pythonhosted.org/packages/43/54/292f26c208734e9a7f067aea4a7e282c080750c4546559b58e2e45413ca0/setuptools-75.6.0.tar.gz", hash = "sha256:8199222558df7c86216af4f84c30e9b34a61d8ba19366cc914424cdbd28252f6", size = 1337429 } wheels = [ - { url = "https://files.pythonhosted.org/packages/ff/ae/f19306b5a221f6a436d8f2238d5b80925004093fa3edea59835b514d9057/setuptools-75.1.0-py3-none-any.whl", hash = "sha256:35ab7fd3bcd95e6b7fd704e4a1539513edad446c097797f2985e0e4b960772f2", size = 1248506 }, + { url = "https://files.pythonhosted.org/packages/55/21/47d163f615df1d30c094f6c8bbb353619274edccf0327b185cc2493c2c33/setuptools-75.6.0-py3-none-any.whl", hash = "sha256:ce74b49e8f7110f9bf04883b730f4765b774ef3ef28f722cce7c273d253aaf7d", size = 1224032 }, ] [[package]] @@ -7266,70 +7255,70 @@ wheels = [ [[package]] name = "simsimd" -version = "5.6.4" +version = "6.2.1" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/bd/4d/be090e03589fb35bcf0775b3830402d0c91f07a92992c5950103b9f79555/simsimd-5.6.4.tar.gz", hash = "sha256:6be41006c84792ea91775529a618f291c958bd4ba3678d2a562517af97132deb", size = 122579 } +sdist = { url = "https://files.pythonhosted.org/packages/da/1c/90e6ec0f0de20108fdd7d5665ac2916b1e8c893ce2f8d7481fd37eabbb97/simsimd-6.2.1.tar.gz", hash = "sha256:5e202c5386a4141946b7aee05faac8ebc2e36bca0a360b24080e57b59bc4ef6a", size = 165828 } wheels = [ - { url = "https://files.pythonhosted.org/packages/92/57/e1170f9ce097f0c2076dcc46f8e3c3affba9b747939211a268e9fee181fd/simsimd-5.6.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:a4b8f2bbbd99c449132c30f5a941c686ef6a834bed35c07e7834d845f8d0a451", size = 103143 }, - { url = "https://files.pythonhosted.org/packages/8b/77/8f6c0986d20b956b8d1a389fbfce2bb328b23e2db74e1bc012c4a02fac2b/simsimd-5.6.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:3721f1021b679e647dea0ec429c45da68721e431833dde0ffede28e670aaea42", size = 63225 }, - { url = "https://files.pythonhosted.org/packages/ae/66/a8d3a2ba1c9fd394167f044ee8c71602373ba5e6345defe578cc350ebbdb/simsimd-5.6.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:073808694aba436ab9318c387a57993f68c57ce3d8e115ea1554093a092d3662", size = 62559 }, - { url = "https://files.pythonhosted.org/packages/f2/b0/0cda55e782c26f7b8db38914cbfbe8ff9759edc1dff20136a8b2cab3190c/simsimd-5.6.4-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5ebffbcc1ba92ec9246a00401fca0d17781de8d47a44d728b7862c426dbd75f4", size = 191581 }, - { url = "https://files.pythonhosted.org/packages/a1/50/c54322e9d7329a8e8c30235d49fa015f8562aa359b1f2f3e4916620eb13f/simsimd-5.6.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e596f46d46d367b43ce6502c41845cb54cd7dfd186358142c4bdef31940b66b9", size = 226753 }, - { url = "https://files.pythonhosted.org/packages/25/8e/9baf50a883f72aa001dddc01506178f28a927da3099e67e83121dee31dfe/simsimd-5.6.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e4faf04a966b8c5adf21ee45d89f997280533ad18677cc516dff58077f14052b", size = 185114 }, - { url = "https://files.pythonhosted.org/packages/1c/db/6c3de38024080984adb34c2f4e108438994e307f89675d157bc3ab248567/simsimd-5.6.4-cp310-cp310-manylinux_2_28_aarch64.whl", hash = "sha256:e70dbd0d4ef6937710441bea149756ae9af221876f6337dd80408dcdcb2e35fb", size = 314146 }, - { url = "https://files.pythonhosted.org/packages/ef/2c/f768619915a1cd27e580efda5c739c9eb76e8be7b528bea0cc40043f3cc0/simsimd-5.6.4-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:bcfb7a671485b513e37a6615c6ca31725c324a3b8e98e273506edace24b9686c", size = 498930 }, - { url = "https://files.pythonhosted.org/packages/cf/c0/8c1208664dcbcd6e00c9c5f7a95891cff1d66a02dc76cdddf140cd494e96/simsimd-5.6.4-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:f1939b97202b319246aaf53eade38aa6e8925ffc5e227d0d083b3648239a123e", size = 353551 }, - { url = "https://files.pythonhosted.org/packages/fd/08/96ebba3835bd2788decf8f08d2397a8906f144e609c3ff7e52afe67fb6bb/simsimd-5.6.4-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:7c5af13fc2542f8b2b204b7431e1a03b886be9d39c6f05b8f2abe41e76e6d52d", size = 228757 }, - { url = "https://files.pythonhosted.org/packages/6a/b9/6f5a105287e16bcb81dc1419075e7136da4938fa5f81f5fc73d9a9f6f6b9/simsimd-5.6.4-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:40d99cff402a356f630158770f63946c31de98f307d9ab1516482c86b53d3759", size = 280872 }, - { url = "https://files.pythonhosted.org/packages/08/02/6d609fdee3669806a862315fc35294b63ed85d221392e35478b0be4d1d43/simsimd-5.6.4-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:9b3f93d524234bfdef61dfec72a62d52684010d33a801d2e114208d109363c45", size = 318079 }, - { url = "https://files.pythonhosted.org/packages/cb/e0/fad4fc08500c05376d8b555965c8b24d54fdbd2a9617c0bd02ddd2737ca3/simsimd-5.6.4-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:99b07e697d01df62585f333aa46222b6c6a7e7b17f311353430604dc5eba4df3", size = 274927 }, - { url = "https://files.pythonhosted.org/packages/6f/af/73dcc7c158427cfd873d6a7e501b964ba55752d658b29bca9574e85811dd/simsimd-5.6.4-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:aa1e5cb7331e7d194eb583b5aab341d559d654189ff39108c094c92fb763ce57", size = 435932 }, - { url = "https://files.pythonhosted.org/packages/47/64/97d76657554679f85f012f3ff240b4963eb44620a2f10be9ea6ea32cec0f/simsimd-5.6.4-cp310-cp310-win32.whl", hash = "sha256:598f988d2d3795d540ab9d1d299fbbbe222d37bfd8d4e0a075d4eac22973b71a", size = 45914 }, - { url = "https://files.pythonhosted.org/packages/61/87/436435f4af27a132205022c8648557c0e9eba2b269e43750a7b9b8502b3c/simsimd-5.6.4-cp310-cp310-win_amd64.whl", hash = "sha256:ab9a4d441b0bb157a9452673b27f2f14943f168daa66d966cd156208146d9622", size = 60662 }, - { url = "https://files.pythonhosted.org/packages/8d/bd/077b06017b24985d68600dc86f0f3cbe05cfce85547b9be0bf892c0786ed/simsimd-5.6.4-cp310-cp310-win_arm64.whl", hash = "sha256:88aace4ac2b1be79ac49c19cae5b836a8700a369d7031fb2c2ba38dfade21905", size = 47449 }, - { url = "https://files.pythonhosted.org/packages/81/be/0a9d1a0f827ac1e81c64c74d97a0cab00e1c0f6859f1fe0903a006680cd1/simsimd-5.6.4-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:0f39be1f94afb25713a4b585ec5e73cb2e7ced00c4f7752ba5ed57037795427f", size = 103142 }, - { url = "https://files.pythonhosted.org/packages/58/64/72ee47d9088a1c97e07517c91ce6aa4db129bf30ab5594fb033b4b1343f6/simsimd-5.6.4-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:14a3d3627bb5eb851393fe5547eb09a528e261e622d5c8fc86a18d79003812aa", size = 63223 }, - { url = "https://files.pythonhosted.org/packages/ce/b9/37e075e834e60f84c6df729c1bf6d6930acc08363711a71d59d6e3ef5dd8/simsimd-5.6.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c7640d1ddd58efefef28ea18e96af9ab4c072851d7b89ed5ffd211b9af1f164f", size = 62568 }, - { url = "https://files.pythonhosted.org/packages/dc/89/f4df97f0f308e6bb0aa0f8ba8e8f74b88424c3327a6b89794a23673854d5/simsimd-5.6.4-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6b38121de49d4315a8b81380abc9ed9601e77f38a3a175cb191347a49beb9509", size = 191667 }, - { url = "https://files.pythonhosted.org/packages/e8/6c/0e0c8245b0e85b6a80d8eb70b1a56bf9464d06d34b92470895e8e3ff8188/simsimd-5.6.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:76e12b3c0c3ddac7a1812cc14e7642b9094a0c787c1756fbfd397760813f6975", size = 226832 }, - { url = "https://files.pythonhosted.org/packages/f2/11/ae82e87f6797fb7c6703c2ddf65f58c99f1d846b0439c2ea8761b31f2fc8/simsimd-5.6.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a503ad5831c8e80ab94b9f66728778c92a254d0256e2a90b582080e1f3ac45dd", size = 185165 }, - { url = "https://files.pythonhosted.org/packages/24/e8/a732d2b60359d896a29c94e21de19353808fba594a4987371ca7b6fc42d4/simsimd-5.6.4-cp311-cp311-manylinux_2_28_aarch64.whl", hash = "sha256:b769c0cc84c7025687bf88367329bfe3b1e7cb78486b6b192686022fd2674e3b", size = 314233 }, - { url = "https://files.pythonhosted.org/packages/38/94/e4eb4e43fba43150c56f9aeea704e552a89c2a1bf33ed918d91672496224/simsimd-5.6.4-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:491b9e81d8881565105c9a0fc5409f4a86bfe23d69c950378fbca57d6ab17b94", size = 499027 }, - { url = "https://files.pythonhosted.org/packages/89/e8/631d5b6327a90c9ad85a971ee4103d85c3f90e92a6aa28391c34e3620467/simsimd-5.6.4-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8f67a64de381d37b9bf731e0ceac72dd42acb21744b607041e1b5b84e29fcf0a", size = 353670 }, - { url = "https://files.pythonhosted.org/packages/e1/e4/c5368e4ae5e9316a2f7b568a52a44c3e7b63d95cfc7a491000a8d7ba2587/simsimd-5.6.4-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:d6ee5f581f77c07effd4405f04df6c05a17819abf61222fea922adbec135afe7", size = 228859 }, - { url = "https://files.pythonhosted.org/packages/aa/6a/5434a186472c4bc081da0d1ae1599f401ef4c56ead71ae0993103e8ae3cb/simsimd-5.6.4-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:400a6fb2ff0dd5faa65946d1bee4e8c77a26b666104c998c2ff4782ab7677ec8", size = 281043 }, - { url = "https://files.pythonhosted.org/packages/d3/8b/fccfebaa25120f2bd90fae97b8cfdf50490eb27269577bf8206c54f6919a/simsimd-5.6.4-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:50ec3185995844d93d3b0d9decd50b0c218bf4d12d0471c5b5bd93a9ad446fef", size = 318219 }, - { url = "https://files.pythonhosted.org/packages/24/58/c8354f011469e0ee6d9eba718bac5df30cc11525f47a29dc8138031f393e/simsimd-5.6.4-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:261f961912250dd695beb4606bf0c3809be238ba0a8d52a7267269bf8d7f6e1c", size = 275002 }, - { url = "https://files.pythonhosted.org/packages/aa/15/2a59a432020799889d08a1be00d2b74724f9d653b24e13e76842793c0a65/simsimd-5.6.4-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:15dcfdf0b2b440d45f7b6ba7d04e2fcad9eb4ef3b1d12777a94238eb63aa46be", size = 436023 }, - { url = "https://files.pythonhosted.org/packages/5e/76/7a06e4b2a57230ce87c464cdf7fa19e988c49c4324054831c6ed3d709b70/simsimd-5.6.4-cp311-cp311-win32.whl", hash = "sha256:c68dc988c70dd1428360ea913b94ed6c9a7ae407aae77dc42fec84ae133c4a4d", size = 45914 }, - { url = "https://files.pythonhosted.org/packages/a0/f1/faf507c72a4e7d2cb0b68537a60e4f9c54e5de4600e98af5d9bf474f270a/simsimd-5.6.4-cp311-cp311-win_amd64.whl", hash = "sha256:c081a036a69e7a97df1f4d8c57e04370616164cd7e78ef6a249c63686810901a", size = 60663 }, - { url = "https://files.pythonhosted.org/packages/44/94/004de92f4785d8a1c06cc1dce80862725f57f842d58ab23b52035bbda0eb/simsimd-5.6.4-cp311-cp311-win_arm64.whl", hash = "sha256:521e303a1c8ceaf1c2f6d7903b3a0d04a73fb56673ee488e3c2bd7eac463acc9", size = 47451 }, - { url = "https://files.pythonhosted.org/packages/85/3c/fe974dc86468bc614aabc9d883d64067ad6ba520bb491d3e686e7cc3dbc8/simsimd-5.6.4-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:b42c1a93ad3b61cdf6aff3ff4d273e55813117fcad139ea8f598b4759f31cf8e", size = 103399 }, - { url = "https://files.pythonhosted.org/packages/e1/60/879f8243a63bcbae28e694651a3f8210c00242e54609ec94a2d77242aa35/simsimd-5.6.4-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:a78f3824f159504883a8ed37a9b0c1360d2a2a022e695e6552ec47c081fdd390", size = 63467 }, - { url = "https://files.pythonhosted.org/packages/d1/aa/622c208d97500be92957e6d5ff89fd9131d166df8c69bf8495cb0a45cf4d/simsimd-5.6.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:6814fb39c43fbb568509c255eb1390766f64f12cd9f72951527d490a9a8a2320", size = 62566 }, - { url = "https://files.pythonhosted.org/packages/3a/7e/aa7b4f4f9ca060c4aca954a1c8d1be2a42b95a86668cf91d03686cf41320/simsimd-5.6.4-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:eb4839189779822e93da8dc5ac7a973136b1814f6ac6d58532b65cad595d0599", size = 191904 }, - { url = "https://files.pythonhosted.org/packages/7a/98/8d03fbc526722345eca1ceca9770a8ace5770944fb9463b32f4fe7e918b8/simsimd-5.6.4-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2f1a49fd83d23884330f02b901f8187a3eee51aac0506fc20a4ca13710ea70e6", size = 227175 }, - { url = "https://files.pythonhosted.org/packages/aa/65/708ee6be078882a2f786771517792c79904890c5b85240fd9e22a054cc6c/simsimd-5.6.4-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a497fee2135e8e88748336ba3c2f4af00106ddd8c7ace3b13493bda1765057ce", size = 185564 }, - { url = "https://files.pythonhosted.org/packages/29/e9/0c5aeedf05117980184d89695b3c9e3fc246219c67639ec220c3fa9c7939/simsimd-5.6.4-cp312-cp312-manylinux_2_28_aarch64.whl", hash = "sha256:1ea493800dc0d417b45673248d2858b1e799eef8f02dc8940cd9f113d62da172", size = 314424 }, - { url = "https://files.pythonhosted.org/packages/a1/51/562c11fe7ad10614d228f180e75c0b583ffa4f616b578ceb77d1ed0127cc/simsimd-5.6.4-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:59d66a1369c382b5b1228f1ee45e01a6b5dcdc36543aa9e4e7047669e932764e", size = 499392 }, - { url = "https://files.pythonhosted.org/packages/ef/74/922b8c0f0a39df48a6ba643ca7992ec91f447e3ee3877ebf0de91a18ed30/simsimd-5.6.4-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:3cfd10698fe9106941bca5c520086bfa9d23c497d307f6abf9cbc4e5dc1ddc61", size = 353925 }, - { url = "https://files.pythonhosted.org/packages/0e/29/5406f126541cbc0faa05eff73e92d82064ab711b01907c5606aac7d0b4c1/simsimd-5.6.4-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:0811cc9dc5f32e6e32fc1ae5d0c31bb545f774c98012903c2f124a86cb2d8481", size = 229039 }, - { url = "https://files.pythonhosted.org/packages/0e/dc/eeed5e03c70184a5ebc1aab74c542fd7469374a4c54984ef60b39bb586d8/simsimd-5.6.4-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:5ba8cd9d682bc4bad00f50e4202232d890fe4c59b7558b5d31f8d5893ed437ff", size = 281190 }, - { url = "https://files.pythonhosted.org/packages/5a/75/f13c11694dc44cd0ab1afaadd931e2136c78e85da8d83379a5bd32386093/simsimd-5.6.4-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:382a09025c709071765a2f3b756764e45bbbec6a90fc5027cdb8db80ab24e089", size = 318344 }, - { url = "https://files.pythonhosted.org/packages/9a/e7/ed00b91a116c3a31e2f2012a0d128a22b80bce35a2da5663687499fc847a/simsimd-5.6.4-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:1d13f412b298dc392282e01fa8f588ed447299c36fd3df0c189478be4458786b", size = 275323 }, - { url = "https://files.pythonhosted.org/packages/4a/10/e0764cc925dfedf9066bf8c560d8c27d085eb78cc4b7420ef154676a8917/simsimd-5.6.4-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:6f80c21d45a73e5422e11c871a00a53752e89268aee452172d93c66e6e48e7c1", size = 436247 }, - { url = "https://files.pythonhosted.org/packages/1f/67/6493680b0de6ed3bbac2a03719f50fbe40e08ce680995546512da11174b4/simsimd-5.6.4-cp312-cp312-win32.whl", hash = "sha256:e16630b6a3c8682df6525398cb59101c5934a773aeef9f866336340655402049", size = 45914 }, - { url = "https://files.pythonhosted.org/packages/90/f1/1196be53fc014c0c589db4067bd2dba2cf5c38c97c643505d7fb63146efe/simsimd-5.6.4-cp312-cp312-win_amd64.whl", hash = "sha256:e9cb779d03edfd73e36668f6894a3762c89ab4c5679476d8e291b6c207b1d89f", size = 60919 }, - { url = "https://files.pythonhosted.org/packages/6b/92/a78ae8d1742d76a8ac2bd1d91bb19013bd8565a7d40d373e89cbbe14b6c1/simsimd-5.6.4-cp312-cp312-win_arm64.whl", hash = "sha256:7a268e7c73aa128301d7aa3481c6e19dafc6a34b548a406572f5c07c9a12807a", size = 47465 }, + { url = "https://files.pythonhosted.org/packages/36/95/66c0485fd0734c6d77a96a11b7ec52a21c8a368b48f8400dcc8b5593685e/simsimd-6.2.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:9c79486cf75eb06c5e1f623e8315f9fb73620ac63b846d5a6c843f14905de43f", size = 170242 }, + { url = "https://files.pythonhosted.org/packages/fb/c1/7c535b65aa1bcb0aef18407859f188ec5afc9404f6ad57e79e6ce74321a4/simsimd-6.2.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:104d53f2489dcbf569b8260d678e2183af605510115dc2b22ed0340aa47fe892", size = 102331 }, + { url = "https://files.pythonhosted.org/packages/44/c5/fe1915c70f82733782f57e9410bd92936a51ba6f5d2408aa98204a16885c/simsimd-6.2.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:fef886c8220d3566b9f43d441226ca267a11682dea5496bb6e007f655eee1fd1", size = 93455 }, + { url = "https://files.pythonhosted.org/packages/a7/b0/9a7df126e36bf1397c31f1e2482857183b5eac61141cf72041d730fd5b4d/simsimd-6.2.1-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:522e56451481bff3468653c2818ad1240b4cb13cff0ec76bc88d8860bfc775c9", size = 251045 }, + { url = "https://files.pythonhosted.org/packages/16/6a/15578d772bb4b5506b5617d078557296fce74b7206bb1c9d3fe6db0e47c8/simsimd-6.2.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a5dfb02fa141a6e039803044930753aef1df5ed05cae8b14fe348cdc160cef1e", size = 302448 }, + { url = "https://files.pythonhosted.org/packages/49/51/cbf5f43c8cb1c9e173a040004ebb7726b87936e5110b15916510c1b7fa32/simsimd-6.2.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:39eb6abdd44adfddec181a713e9cfad8742d03abbc6247c4e5ca2caee38e4775", size = 227246 }, + { url = "https://files.pythonhosted.org/packages/9e/56/3f3609cbeaf9393158ef5ee5cf60b8e2190bb87925e21a43dd321c52a05f/simsimd-6.2.1-cp310-cp310-manylinux_2_28_aarch64.whl", hash = "sha256:9ca68b9d2cc1c19af6afe6f01a764861fc8bb919d688a64cf0b0ac0abae7e0fa", size = 432346 }, + { url = "https://files.pythonhosted.org/packages/56/53/13629d84b95b9373b7ce1447c43fc09da448d521bfa93eb02a8806ec0a50/simsimd-6.2.1-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:2b56b1ca7b76c0d4515938a036e688b73a866b19e6f6eb743596144fdf498a0c", size = 632661 }, + { url = "https://files.pythonhosted.org/packages/d7/52/6361628a462b6e753f1ed9d5de9c4e1f3d35ced2922c7e196ce4e45d81fa/simsimd-6.2.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:02d7b7c7afecc63ddf501460f09c1da90625bfd59b4da5fda126c1aa5c54bb95", size = 468411 }, + { url = "https://files.pythonhosted.org/packages/ef/f1/f56395d5885a3a19268d8f62589e3cc5b37b7c0f407fcf89bacf1d57397c/simsimd-6.2.1-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:8abc529daf0a61649ca4a237cd9e63723f3355394686898654c643bd63846cf5", size = 268931 }, + { url = "https://files.pythonhosted.org/packages/b1/90/597c8756697b7fdb7f4b6e7d7e4c85207b449c286b6bf8a6c3815798bc33/simsimd-6.2.1-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:9ea60422d0f45d3a1899984c3fc3a14dbd248cfca8f67c24751029441464a806", size = 344281 }, + { url = "https://files.pythonhosted.org/packages/16/fb/9b976f87db319ad95b541f94232a1cc6d0d3c16b01f910e1f8b967b241d5/simsimd-6.2.1-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:98e38a0ca4805c1de2882d0641b54e249eabca4ed2980c82465822130d7f8c98", size = 389374 }, + { url = "https://files.pythonhosted.org/packages/da/e1/d3e41accb2a4a3b6fd46c7900c49e36b7d426e20e49e06b3418316eba2b9/simsimd-6.2.1-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:cbbc2434286493b88f3b8211e922d37b46588b34d4cc28f3262f154c8ca1141c", size = 316688 }, + { url = "https://files.pythonhosted.org/packages/28/1f/c8cc75df5d386071e067ca22d54b6629eb6d600879e223bba3ddf96849d7/simsimd-6.2.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:4f2ecd459f4917facdb287c42c5e68030b21cb98edac0fec9919a7215968e38a", size = 669697 }, + { url = "https://files.pythonhosted.org/packages/ab/cc/d4a0f90706432fa3b5cbde390ec7f213e7639ce6cf87be0f9f19ff8a23d9/simsimd-6.2.1-cp310-cp310-win32.whl", hash = "sha256:4ec31c076dc839114bff5d83526ddf46551d4720cc8cd0f16516896809a4fca6", size = 55008 }, + { url = "https://files.pythonhosted.org/packages/9b/e6/33ea89f17e83a8743f9461c85f926203ef5a82782c4a72263571b7186427/simsimd-6.2.1-cp310-cp310-win_amd64.whl", hash = "sha256:94282e040be985c993d415290371f6b22bec3eeadafe747a6d8dfbd2c317f35e", size = 86852 }, + { url = "https://files.pythonhosted.org/packages/ad/30/65252e79ef62807c33e22f1df04b3dbd16ceda5ecc88bf46de239a4516c3/simsimd-6.2.1-cp310-cp310-win_arm64.whl", hash = "sha256:0784e98ca48a0075fb0cbd7782df11eaa17ce15c60f09a65e8477864208afb8a", size = 60194 }, + { url = "https://files.pythonhosted.org/packages/a7/5f/361cee272fd6c88f33e14e233792f59dd58836ea8c776344f7445a829ca2/simsimd-6.2.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:e9614309af75be4d08a051dc61ed5cf41b5239b8303b37dc2f9c8a7223534392", size = 170254 }, + { url = "https://files.pythonhosted.org/packages/b8/88/edf4442ec655765d570bfb6cef81dfb12c8829c28e580459bac8a4847fb5/simsimd-6.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:ea4f0f68be5f85bbcf4322bfdd1b449176cf5fdd99960c546514457635632443", size = 102331 }, + { url = "https://files.pythonhosted.org/packages/5d/2b/9e7d42ac54bdb32d76953db3bc83eec29bd5d5c9a4069d380b18e200d6bd/simsimd-6.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:12a8d60ccc8991dfbbf056c221ce4f02135f5892492894972f421a6f155015d9", size = 93455 }, + { url = "https://files.pythonhosted.org/packages/13/9c/fac1167e80328d1e332f515c9cd62da4a0e12b9aa8ee90d448eb4ad5a47f/simsimd-6.2.1-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a74142ea21a6fd3ec5c64e4d4acf1ec6f4d80c0bb1a5989d68af6e84f7ac612e", size = 251040 }, + { url = "https://files.pythonhosted.org/packages/31/93/b374e5538fc65cf381920bdba7603769b1b71e42afe2bb4939e9c338c423/simsimd-6.2.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:298f7c793fc2a1eeedcefa1278eb2ef6f52ce0b36aaa8780885f96a39ce1a4e8", size = 302428 }, + { url = "https://files.pythonhosted.org/packages/e6/42/2733a0e11b660c6b10f3ec90d7fac6f96267368b961b1a43dda0456fa9f2/simsimd-6.2.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4025ebad36fb3fa5cffcd48d33375d5e5decc59c1129a259b74fed097eab1ab5", size = 227200 }, + { url = "https://files.pythonhosted.org/packages/eb/ae/40e0804d06a351efe27bb6f8e4d332daeb1681d3f398ca10d8a2b087ab78/simsimd-6.2.1-cp311-cp311-manylinux_2_28_aarch64.whl", hash = "sha256:f486682aa7a8918d86df411d3c11c635db4b67d514cb6bb499c0edab7fb8ec58", size = 432333 }, + { url = "https://files.pythonhosted.org/packages/a7/eb/a823b0227b5dc43de8125f502237dd8e844b1e803a74e46aa7c3d0f24f83/simsimd-6.2.1-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:173e66699597a4fcf6fa50b52cced40216fdcfba15f60b761a2bd9cb1d98a444", size = 632659 }, + { url = "https://files.pythonhosted.org/packages/0a/aa/aee48063c4a98aaea062316dedf598d0d9e09fa9edc28baab6886ae0afa8/simsimd-6.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:5b5c6f79f797cc020a2ff64950162dfb6d130c51a07cdac5ad97ec836e85ce50", size = 468407 }, + { url = "https://files.pythonhosted.org/packages/d4/84/e89bc71456aa2d48e5acf3795b2384f597de643f17d00d752aa8217af233/simsimd-6.2.1-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:25812637f43feaef1a33ae00b81a4d2b0116aadae3a08267486c1e57236fc368", size = 268908 }, + { url = "https://files.pythonhosted.org/packages/94/eb/774debec7ee727f436f15e5b5416b781c78564fff97c81a5fb3b636b4298/simsimd-6.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:592a578c788a9cb7877eff41487cc7f50474e00f774de74bea8590fa95c804ae", size = 344256 }, + { url = "https://files.pythonhosted.org/packages/62/03/fec040e7fbb66fa4766ca959cfd766a22d7a00a4e9371f046d8fcc62d846/simsimd-6.2.1-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:191c020f312350ac06eee829376b11d8c1282da8fefb4381fe0625edfb678d8d", size = 389403 }, + { url = "https://files.pythonhosted.org/packages/55/f0/ad441d90a4dde6e100155931fa4468e33cc23276c3caef6330d2a34b866c/simsimd-6.2.1-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:e9ad2c247ed58ba9bb170a01295cb315a45c817775cc7e51ad342f70978a1057", size = 316665 }, + { url = "https://files.pythonhosted.org/packages/05/27/843adbc6a468a58178dcb7907e72c670c8a7c36a06d8a4c5eac9573f5d2d/simsimd-6.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:0ff603134600da12175e66b842b7a7331c827fa070d1d8b63386a40bc8d09fcd", size = 669697 }, + { url = "https://files.pythonhosted.org/packages/6d/db/d2369e0d3b9ca469b923bc81d57dcfed922193e4e4d7cf5f7637df14dd51/simsimd-6.2.1-cp311-cp311-win32.whl", hash = "sha256:99dff4e04663c82284152ecc2e8bf76b2825f3f17e179abf7892e06196061056", size = 55007 }, + { url = "https://files.pythonhosted.org/packages/73/9f/13d6fca5a32a062e84db0a68433ae416073986c8e1d20b5b936cad18bece/simsimd-6.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:0efc6343c440a26cf16463c4c667655af9597bcbd55ad66f33a80b2b84de7412", size = 86855 }, + { url = "https://files.pythonhosted.org/packages/64/e9/7e0514f32c9a0e42261f598775b34a858477e0fcffccf32cc11f94e78ee2/simsimd-6.2.1-cp311-cp311-win_arm64.whl", hash = "sha256:2d364f2c24dd38578bf0eec436c4b901c900ae1893680f46eb5632e01330d814", size = 60195 }, + { url = "https://files.pythonhosted.org/packages/81/87/1f521d471d9079d89dd6860b9dd5d0f39c1633675a30b71acd0bd37cbba5/simsimd-6.2.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:9b3315e41bb759dc038ecd6f4fa7bcf278bf72ee7d982f752482cdc732aea271", size = 169397 }, + { url = "https://files.pythonhosted.org/packages/4b/1a/b0627589737dc75ccd2ed58893e9e7f8b8e082531bd34d319481d88018d5/simsimd-6.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:8d476c874bafa0d12d4c8c5c47faf17407f3c96140616384421c2aa980342b6f", size = 101478 }, + { url = "https://files.pythonhosted.org/packages/e0/b7/e766f0ce9b595927ae1c534f1409b768187e8af567f4412ca220b67c1155/simsimd-6.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:e9d4f15c06cc221d29e181197c7bbf92c5e829220cbeb3cd1cf080de78b04f2a", size = 93439 }, + { url = "https://files.pythonhosted.org/packages/ae/48/3b5ec9b3a6063bae2f280f5168aca7099a44fa7ec8b42875b98c79c1d49b/simsimd-6.2.1-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d286fd4538cb1a1c70e69da00a3acee301519d578931b41161f4f1379d1195c6", size = 251469 }, + { url = "https://files.pythonhosted.org/packages/70/86/16e8d5b9bdd34f75c7515adfad249f394653131bd1a1366076cf6113e84b/simsimd-6.2.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:050f68cfa85f1fb2cfa156280928e42926e3977034b755023ce1315bf59e87ff", size = 302974 }, + { url = "https://files.pythonhosted.org/packages/02/09/3f4240f2b43957aa0d72a2203b2549c0326c7baf97b7f78c72d48d4cd3d2/simsimd-6.2.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:67bb4b17e04919545f29c7b708faaccbe027f164f8b5c9f4328604fa8f5560ea", size = 227864 }, + { url = "https://files.pythonhosted.org/packages/07/4a/8c46806493c3a98025f01d81d9f55e0e574f11279c2ad77be919262ea9eb/simsimd-6.2.1-cp312-cp312-manylinux_2_28_aarch64.whl", hash = "sha256:3d6bffd999dbb36e606b065e0180365efac2606049c4f7818e4cba2d34c3678f", size = 432491 }, + { url = "https://files.pythonhosted.org/packages/13/44/b56f207031405af52c6158c40e9f1121fe3a716d98946d9fa5919cf00266/simsimd-6.2.1-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:25adb244fb75dbf49af0d1bcac4ed4a3fef8e847d78449faa5595af0a3e20d61", size = 633061 }, + { url = "https://files.pythonhosted.org/packages/4c/ad/241f87641af09a1789af8df559aa86b45218d087e09c37c2dd8c013819d6/simsimd-6.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:b4542cee77e801a9c27370fc36ae271514fc0fb2ce14a35f8b25f47989e3d267", size = 468544 }, + { url = "https://files.pythonhosted.org/packages/e2/3e/357aca7df85ed1092dfa50b91cf1b7c0df6f70b384a0e3798132dd824b5c/simsimd-6.2.1-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:4f665228f8ff4911790b485e74b00fa9586a141dde6011970be71bb303b5a22f", size = 269133 }, + { url = "https://files.pythonhosted.org/packages/f0/67/079ca2c58bbc5812802c6ac1b332a6ef889d73cf1188726f36edc27898f6/simsimd-6.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:783b4308f80ae00763b0eaa0dac26196958f9c2df60d35a0347ebd2f82ece46d", size = 344412 }, + { url = "https://files.pythonhosted.org/packages/3c/f0/500c9002276259c17e3a6a13a7c7f84e5119602decadbf40429c978655b0/simsimd-6.2.1-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:95055e72cfe313c1c8694783bf8a631cc15673b3b775abef367e396d931db0b8", size = 389546 }, + { url = "https://files.pythonhosted.org/packages/55/a2/d3f4c6aabba0430758367b3de5bbab59b979bf3525c039b882001f1d2ade/simsimd-6.2.1-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:a98f2b383f51b4f4ee568a637fc7958a347fdae0bd184cff8faa8030b6454a39", size = 316912 }, + { url = "https://files.pythonhosted.org/packages/f8/a3/2514189c3aaa1beb1714b36be86e2d3af7067c3c95152d78cc4cffff6d87/simsimd-6.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:2e474fd10ceb38e2c9f826108a7762f8ff7912974846d86f08c4e7b19cd35ed4", size = 670006 }, + { url = "https://files.pythonhosted.org/packages/ef/23/dbf7c4aed7542260784dc7bc2056a4e5b6d716a14a9b40989d5c3096990a/simsimd-6.2.1-cp312-cp312-win32.whl", hash = "sha256:b2530ea44fffeab25e5752bec6a5991f30fbc430b04647980db5b195c0971d48", size = 55019 }, + { url = "https://files.pythonhosted.org/packages/a0/d8/57304c2317822634abd475f5912584a3cfa13363740e9ec72c0622c894f1/simsimd-6.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:dc23283235d5b8f0373b95a547e26da2d7785647a5d0fa15c282fc8c49c0dcb0", size = 87133 }, + { url = "https://files.pythonhosted.org/packages/3f/7b/ca333232a8bc87d1e846fa2feb9f0d4778500c30493726cb48f04551dfab/simsimd-6.2.1-cp312-cp312-win_arm64.whl", hash = "sha256:5692ce7e56253178eea9dbd58191734918409b83d54b07cfdcecf868d0150a73", size = 60401 }, ] [[package]] name = "six" -version = "1.16.0" +version = "1.17.0" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/71/39/171f1c67cd00715f190ba0b100d606d440a28c93c7714febeca8b79af85e/six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926", size = 34041 } +sdist = { url = "https://files.pythonhosted.org/packages/94/e7/b2c673351809dca68a0e064b6af791aa332cf192da575fd474ed7d6f16a2/six-1.17.0.tar.gz", hash = "sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81", size = 34031 } wheels = [ - { url = "https://files.pythonhosted.org/packages/d9/5a/e7c31adbe875f2abbb91bd84cf2dc52d792b5a01506781dbcf25c91daf11/six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254", size = 11053 }, + { url = "https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl", hash = "sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274", size = 11050 }, ] [[package]] @@ -7468,14 +7457,14 @@ wheels = [ [[package]] name = "starlette" -version = "0.38.6" +version = "0.41.3" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "anyio" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/42/b4/e25c3b688ef703d85e55017c6edd0cbf38e5770ab748234363d54ff0251a/starlette-0.38.6.tar.gz", hash = "sha256:863a1588f5574e70a821dadefb41e4881ea451a47a3cd1b4df359d4ffefe5ead", size = 2569491 } +sdist = { url = "https://files.pythonhosted.org/packages/1a/4c/9b5764bd22eec91c4039ef4c55334e9187085da2d8a2df7bd570869aae18/starlette-0.41.3.tar.gz", hash = "sha256:0e4ab3d16522a255be6b28260b938eae2482f98ce5cc934cb08dce8dc3ba5835", size = 2574159 } wheels = [ - { url = "https://files.pythonhosted.org/packages/b7/9c/93f7bc03ff03199074e81974cc148908ead60dcf189f68ba1761a0ee35cf/starlette-0.38.6-py3-none-any.whl", hash = "sha256:4517a1409e2e73ee4951214ba012052b9e16f60e90d73cfb06192c19203bbb05", size = 71451 }, + { url = "https://files.pythonhosted.org/packages/96/00/2b325970b3060c7cecebab6d295afe763365822b1306a12eeab198f74323/starlette-0.41.3-py3-none-any.whl", hash = "sha256:44cedb2b7c77a9de33a8b74b2b90e9f50d11fcf25d8270ea525ad71a25374ff7", size = 73225 }, ] [[package]] @@ -7562,11 +7551,11 @@ wheels = [ [[package]] name = "tenacity" -version = "8.3.0" +version = "8.5.0" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/32/6c/57df6196ce52c464cf8556e8f697fec5d3469bb8cd319c1685c0a090e0b4/tenacity-8.3.0.tar.gz", hash = "sha256:953d4e6ad24357bceffbc9707bc74349aca9d245f68eb65419cf0c249a1949a2", size = 43608 } +sdist = { url = "https://files.pythonhosted.org/packages/a3/4d/6a19536c50b849338fcbe9290d562b52cbdcf30d8963d3588a68a4107df1/tenacity-8.5.0.tar.gz", hash = "sha256:8bc6c0c8a09b31e6cad13c47afbed1a567518250a9a171418582ed8d9c20ca78", size = 47309 } wheels = [ - { url = "https://files.pythonhosted.org/packages/61/a1/6bb0cbebefb23641f068bb58a2bc56da9beb2b1c550242e3c540b37698f3/tenacity-8.3.0-py3-none-any.whl", hash = "sha256:3649f6443dbc0d9b01b9d8020a9c4ec7a1ff5f6f3c6c8a036ef371f573fe9185", size = 25934 }, + { url = "https://files.pythonhosted.org/packages/d2/3f/8ba87d9e287b9d385a02a7114ddcef61b26f86411e121c9003eb509a1773/tenacity-8.5.0-py3-none-any.whl", hash = "sha256:b594c2a5945830c267ce6b79a166228323ed52718f30302c1359836112346687", size = 28165 }, ] [[package]] @@ -7622,56 +7611,56 @@ wheels = [ [[package]] name = "tokenizers" -version = "0.20.1" +version = "0.20.3" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "huggingface-hub" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/d7/fb/373b66ba58cbf5eda371480e4e051d8892ea1433a73f1f92c48657a699a6/tokenizers-0.20.1.tar.gz", hash = "sha256:84edcc7cdeeee45ceedb65d518fffb77aec69311c9c8e30f77ad84da3025f002", size = 339552 } +sdist = { url = "https://files.pythonhosted.org/packages/da/25/b1681c1c30ea3ea6e584ae3fffd552430b12faa599b558c4c4783f56d7ff/tokenizers-0.20.3.tar.gz", hash = "sha256:2278b34c5d0dd78e087e1ca7f9b1dcbf129d80211afa645f214bd6e051037539", size = 340513 } wheels = [ - { url = "https://files.pythonhosted.org/packages/72/d2/3c05efeeccefa833b82038ce49ee736756eed10ab66fc723ce423a747b0e/tokenizers-0.20.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:439261da7c0a5c88bda97acb284d49fbdaf67e9d3b623c0bfd107512d22787a9", size = 2673220 }, - { url = "https://files.pythonhosted.org/packages/24/d4/a529aa06db71600c1688210ce035cbff637ece919dcaca599c9235ad832d/tokenizers-0.20.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:03dae629d99068b1ea5416d50de0fea13008f04129cc79af77a2a6392792d93c", size = 2563056 }, - { url = "https://files.pythonhosted.org/packages/25/e2/5046ad3b0426548b37c96cc4262a7f2ba6ac9593ee10be69effc78a91764/tokenizers-0.20.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b61f561f329ffe4b28367798b89d60c4abf3f815d37413b6352bc6412a359867", size = 2943369 }, - { url = "https://files.pythonhosted.org/packages/5f/f0/c1ed45ff90088eba4f15eca9763b5e439cb86b71fc9e66a827318b61e44d/tokenizers-0.20.1-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ec870fce1ee5248a10be69f7a8408a234d6f2109f8ea827b4f7ecdbf08c9fd15", size = 2827000 }, - { url = "https://files.pythonhosted.org/packages/22/09/6e0a378a35f215b40ae1c04b4d0fe43e9ddfaf3a08a2b7d7fab8953a6587/tokenizers-0.20.1-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d388d1ea8b7447da784e32e3b86a75cce55887e3b22b31c19d0b186b1c677800", size = 3090881 }, - { url = "https://files.pythonhosted.org/packages/cf/03/801e91d41e2134a32089af2d382a6c40b3d8b932b42fa96443d77258ab28/tokenizers-0.20.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:299c85c1d21135bc01542237979bf25c32efa0d66595dd0069ae259b97fb2dbe", size = 3096826 }, - { url = "https://files.pythonhosted.org/packages/2a/39/3d11780b82d9ba4d8fda093daa48622ed5f2616d6ac8cb638ac290d39d95/tokenizers-0.20.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e96f6c14c9752bb82145636b614d5a78e9cde95edfbe0a85dad0dd5ddd6ec95c", size = 3417666 }, - { url = "https://files.pythonhosted.org/packages/4b/35/326b9642307a53b3d9ae145b5c7f157aae9ecaa930888f920124412e0bd2/tokenizers-0.20.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fc9e95ad49c932b80abfbfeaf63b155761e695ad9f8a58c52a47d962d76e310f", size = 2984468 }, - { url = "https://files.pythonhosted.org/packages/db/b2/5e45632799d816291de4d04149decf19cf6c2faf42bb99574d80050c87bd/tokenizers-0.20.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:f22dee205329a636148c325921c73cf3e412e87d31f4d9c3153b302a0200057b", size = 8981675 }, - { url = "https://files.pythonhosted.org/packages/df/f7/8c0ec102f0a723d09347ff6cd617c7e5e8d44efd342305f52a7fcd3e30e2/tokenizers-0.20.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:a2ffd9a8895575ac636d44500c66dffaef133823b6b25067604fa73bbc5ec09d", size = 9300378 }, - { url = "https://files.pythonhosted.org/packages/e8/54/22825bc3d00ae8a801314a6d96e7e83c180b626a40299179073364c7eac7/tokenizers-0.20.1-cp310-none-win32.whl", hash = "sha256:2847843c53f445e0f19ea842a4e48b89dd0db4e62ba6e1e47a2749d6ec11f50d", size = 2203820 }, - { url = "https://files.pythonhosted.org/packages/7a/da/c7728bb6be0ccfbd5662f054ee28d8ba7883558cc9fcd102e6cdce07bbbf/tokenizers-0.20.1-cp310-none-win_amd64.whl", hash = "sha256:f9aa93eacd865f2798b9e62f7ce4533cfff4f5fbd50c02926a78e81c74e432cd", size = 2384778 }, - { url = "https://files.pythonhosted.org/packages/61/9a/be5f00cd37ad4fab0e5d1dbf31404a66ac2c1c33973beda9fc8e248a37ab/tokenizers-0.20.1-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:4a717dcb08f2dabbf27ae4b6b20cbbb2ad7ed78ce05a829fae100ff4b3c7ff15", size = 2673182 }, - { url = "https://files.pythonhosted.org/packages/26/a2/92af8a5f19d0e8bc480759a9975489ebd429b94a81ad46e1422c7927f246/tokenizers-0.20.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:3f84dad1ff1863c648d80628b1b55353d16303431283e4efbb6ab1af56a75832", size = 2562556 }, - { url = "https://files.pythonhosted.org/packages/2d/ca/f3a294ed89f2a1b900fba072ef4cb5331d4f156e2d5ea2d34f60160ef5bd/tokenizers-0.20.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:929c8f3afa16a5130a81ab5079c589226273ec618949cce79b46d96e59a84f61", size = 2943343 }, - { url = "https://files.pythonhosted.org/packages/31/88/740a6a069e997dc3e96941083fe3264162f4d198a5e5841acb625f84adbd/tokenizers-0.20.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:d10766473954397e2d370f215ebed1cc46dcf6fd3906a2a116aa1d6219bfedc3", size = 2825954 }, - { url = "https://files.pythonhosted.org/packages/ff/71/b220deba78e42e483e2856c9cc83a8352c7c5d7322dad61eed4e1ca09c49/tokenizers-0.20.1-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9300fac73ddc7e4b0330acbdda4efaabf74929a4a61e119a32a181f534a11b47", size = 3091324 }, - { url = "https://files.pythonhosted.org/packages/fe/f4/4302dce958ce0e7f2d85a4725cebe6b02161c2d82990a89317580e17469a/tokenizers-0.20.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0ecaf7b0e39caeb1aa6dd6e0975c405716c82c1312b55ac4f716ef563a906969", size = 3098587 }, - { url = "https://files.pythonhosted.org/packages/7e/0f/9136bc0ea492d29f1d72217c6231dc584bccd3ba41dde12d4a85c75eb12a/tokenizers-0.20.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5170be9ec942f3d1d317817ced8d749b3e1202670865e4fd465e35d8c259de83", size = 3414366 }, - { url = "https://files.pythonhosted.org/packages/09/6c/1b573998fe3f0e18ac5d434e43966de2d225d6837f099ce0df7df4274c87/tokenizers-0.20.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ef3f1ae08fa9aea5891cbd69df29913e11d3841798e0bfb1ff78b78e4e7ea0a4", size = 2984510 }, - { url = "https://files.pythonhosted.org/packages/d3/92/e5b80e42c24e564ac892c9135e4b9ec34bbcd6cdf0cc7a04735c44fe2ced/tokenizers-0.20.1-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:ee86d4095d3542d73579e953c2e5e07d9321af2ffea6ecc097d16d538a2dea16", size = 8982324 }, - { url = "https://files.pythonhosted.org/packages/d0/42/c287d28ebcb3ba4f712e7a58d8f170a7b569528acf2d2a8fd1f684c24c0c/tokenizers-0.20.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:86dcd08da163912e17b27bbaba5efdc71b4fbffb841530fdb74c5707f3c49216", size = 9301853 }, - { url = "https://files.pythonhosted.org/packages/ea/48/7d4ac79588b5b1c3651b753b0a1bdd1343d81af57be18138dfdb304a710a/tokenizers-0.20.1-cp311-none-win32.whl", hash = "sha256:9af2dc4ee97d037bc6b05fa4429ddc87532c706316c5e11ce2f0596dfcfa77af", size = 2201968 }, - { url = "https://files.pythonhosted.org/packages/f1/95/f1b56f4b1fbd54bd7f170aa64258d0650500e9f45de217ffe4d4663809b6/tokenizers-0.20.1-cp311-none-win_amd64.whl", hash = "sha256:899152a78b095559c287b4c6d0099469573bb2055347bb8154db106651296f39", size = 2384963 }, - { url = "https://files.pythonhosted.org/packages/8e/8d/a051f979f955c6717099718054d7f51fea0a92d807a7d078a48f2684e54f/tokenizers-0.20.1-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:407ab666b38e02228fa785e81f7cf79ef929f104bcccf68a64525a54a93ceac9", size = 2667300 }, - { url = "https://files.pythonhosted.org/packages/99/c3/2132487ca51148392f0d1ed7f35c23179f67d66fd64c233ff50f091258b4/tokenizers-0.20.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:2f13a2d16032ebc8bd812eb8099b035ac65887d8f0c207261472803b9633cf3e", size = 2556581 }, - { url = "https://files.pythonhosted.org/packages/f4/6e/9dfd1afcfd38fcc5b3a84bca54c33025561f7cab8ea375fa88f03407adc1/tokenizers-0.20.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e98eee4dca22849fbb56a80acaa899eec5b72055d79637dd6aa15d5e4b8628c9", size = 2937857 }, - { url = "https://files.pythonhosted.org/packages/28/51/92e3b25eb41be7fd65219c832c4ff61bf5c8cc1c3d0543e9a117d63a0876/tokenizers-0.20.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:47c1bcdd61e61136087459cb9e0b069ff23b5568b008265e5cbc927eae3387ce", size = 2823012 }, - { url = "https://files.pythonhosted.org/packages/f7/59/185ff0bb35d46d88613e87bd76b03989ef8537ebf4f39876bddf9bed2fc1/tokenizers-0.20.1-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:128c1110e950534426e2274837fc06b118ab5f2fa61c3436e60e0aada0ccfd67", size = 3086473 }, - { url = "https://files.pythonhosted.org/packages/a4/2a/da72c32446ad7f3e6e5cb3c625222a5b9b0bc10b50456f6cb79f6230ae1f/tokenizers-0.20.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e2e2d47a819d2954f2c1cd0ad51bb58ffac6f53a872d5d82d65d79bf76b9896d", size = 3101655 }, - { url = "https://files.pythonhosted.org/packages/cf/7d/c895f076e552cb39ea0491f62ff6551cb3e60323a7496017182bd57cc314/tokenizers-0.20.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bdd67a0e3503a9a7cf8bc5a4a49cdde5fa5bada09a51e4c7e1c73900297539bd", size = 3405410 }, - { url = "https://files.pythonhosted.org/packages/24/59/664121cb41b4f738479e2e1271013a2a7c9160955922536fb723a9c690b7/tokenizers-0.20.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:689b93d2e26d04da337ac407acec8b5d081d8d135e3e5066a88edd5bdb5aff89", size = 2977249 }, - { url = "https://files.pythonhosted.org/packages/d4/ab/ceb7bdb3394431e92b18123faef9862877009f61377bfa45ffe5135747a5/tokenizers-0.20.1-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:0c6a796ddcd9a19ad13cf146997cd5895a421fe6aec8fd970d69f9117bddb45c", size = 8989781 }, - { url = "https://files.pythonhosted.org/packages/bb/37/eaa072b848471d31ae3df6e6d5be5ae594ed5fe39ca921e65cabf193dbde/tokenizers-0.20.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:3ea919687aa7001a8ff1ba36ac64f165c4e89035f57998fa6cedcfd877be619d", size = 9304427 }, - { url = "https://files.pythonhosted.org/packages/41/ff/4aeb924d09f6561209b57af9123a0a28fa69472cc71ee40415f036253203/tokenizers-0.20.1-cp312-none-win32.whl", hash = "sha256:6d3ac5c1f48358ffe20086bf065e843c0d0a9fce0d7f0f45d5f2f9fba3609ca5", size = 2195986 }, - { url = "https://files.pythonhosted.org/packages/7e/ba/18bf6a7ad04f8225b71aa862b57188748d1d81e268de4a9aac1aed237246/tokenizers-0.20.1-cp312-none-win_amd64.whl", hash = "sha256:b0874481aea54a178f2bccc45aa2d0c99cd3f79143a0948af6a9a21dcc49173b", size = 2377984 }, - { url = "https://files.pythonhosted.org/packages/4b/9e/cf0911565ae302e4e4ed3d53bba28f2db75a9418f4e89e2434246723f01a/tokenizers-0.20.1-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:48689da7a395df41114f516208d6550e3e905e1239cc5ad386686d9358e9cef0", size = 2666975 }, - { url = "https://files.pythonhosted.org/packages/37/98/8221a62aed679aefcbc1793ed8bb33f1e060f8b7d95bb20809db1b5c0e0e/tokenizers-0.20.1-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:712f90ea33f9bd2586b4a90d697c26d56d0a22fd3c91104c5858c4b5b6489a79", size = 2557365 }, - { url = "https://files.pythonhosted.org/packages/97/e3/167ca1981b3f512030a28f591b8ef786585b625d45f0fbf1c42723474ecd/tokenizers-0.20.1-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:359eceb6a620c965988fc559cebc0a98db26713758ec4df43fb76d41486a8ed5", size = 2940885 }, - { url = "https://files.pythonhosted.org/packages/c1/e6/ec76a7761eb7ba3cf95e2485cb2e7999a8eb0900d771616c0efa61beb1cd/tokenizers-0.20.1-pp310-pypy310_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0d3caf244ce89d24c87545aafc3448be15870096e796c703a0d68547187192e1", size = 3092338 }, - { url = "https://files.pythonhosted.org/packages/9c/2c/9f04aa030ba8994d478ab35464f8c541aad264556811f12afce9369cc0d3/tokenizers-0.20.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:03b03cf8b9a32254b1bf8a305fb95c6daf1baae0c1f93b27f2b08c9759f41dee", size = 2981389 }, - { url = "https://files.pythonhosted.org/packages/cb/f7/79a74f8c54d1232ddbd68967ce56a00cc9589a31b94bee4cf9f34af91ace/tokenizers-0.20.1-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:218e5a3561561ea0f0ef1559c6d95b825308dbec23fb55b70b92589e7ff2e1e8", size = 8986321 }, - { url = "https://files.pythonhosted.org/packages/d4/f2/ea998aaf69966a87f92e31db7cba887125994bb9cd9a4dfcc83ac202d446/tokenizers-0.20.1-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f40df5e0294a95131cc5f0e0eb91fe86d88837abfbee46b9b3610b09860195a7", size = 9300207 }, + { url = "https://files.pythonhosted.org/packages/c8/51/421bb0052fc4333f7c1e3231d8c6607552933d919b628c8fabd06f60ba1e/tokenizers-0.20.3-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:31ccab28dbb1a9fe539787210b0026e22debeab1662970f61c2d921f7557f7e4", size = 2674308 }, + { url = "https://files.pythonhosted.org/packages/a6/e9/f651f8d27614fd59af387f4dfa568b55207e5fac8d06eec106dc00b921c4/tokenizers-0.20.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c6361191f762bda98c773da418cf511cbaa0cb8d0a1196f16f8c0119bde68ff8", size = 2559363 }, + { url = "https://files.pythonhosted.org/packages/e3/e8/0e9f81a09ab79f409eabfd99391ca519e315496694671bebca24c3e90448/tokenizers-0.20.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f128d5da1202b78fa0a10d8d938610472487da01b57098d48f7e944384362514", size = 2892896 }, + { url = "https://files.pythonhosted.org/packages/b0/72/15fdbc149e05005e99431ecd471807db2241983deafe1e704020f608f40e/tokenizers-0.20.3-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:79c4121a2e9433ad7ef0769b9ca1f7dd7fa4c0cd501763d0a030afcbc6384481", size = 2802785 }, + { url = "https://files.pythonhosted.org/packages/26/44/1f8aea48f9bb117d966b7272484671b33a509f6217a8e8544d79442c90db/tokenizers-0.20.3-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b7850fde24197fe5cd6556e2fdba53a6d3bae67c531ea33a3d7c420b90904141", size = 3086060 }, + { url = "https://files.pythonhosted.org/packages/2e/83/82ba40da99870b3a0b801cffaf4f099f088a84c7e07d32cc6ca751ce08e6/tokenizers-0.20.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b357970c095dc134978a68c67d845a1e3803ab7c4fbb39195bde914e7e13cf8b", size = 3096760 }, + { url = "https://files.pythonhosted.org/packages/f3/46/7a025404201d937f86548928616c0a164308aa3998e546efdf798bf5ee9c/tokenizers-0.20.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a333d878c4970b72d6c07848b90c05f6b045cf9273fc2bc04a27211721ad6118", size = 3380165 }, + { url = "https://files.pythonhosted.org/packages/aa/49/15fae66ac62e49255eeedbb7f4127564b2c3f3aef2009913f525732d1a08/tokenizers-0.20.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1fd9fee817f655a8f50049f685e224828abfadd436b8ff67979fc1d054b435f1", size = 2994038 }, + { url = "https://files.pythonhosted.org/packages/f4/64/693afc9ba2393c2eed85c02bacb44762f06a29f0d1a5591fa5b40b39c0a2/tokenizers-0.20.3-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:9e7816808b402129393a435ea2a509679b41246175d6e5e9f25b8692bfaa272b", size = 8977285 }, + { url = "https://files.pythonhosted.org/packages/be/7e/6126c18694310fe07970717929e889898767c41fbdd95b9078e8aec0f9ef/tokenizers-0.20.3-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:ba96367db9d8a730d3a1d5996b4b7babb846c3994b8ef14008cd8660f55db59d", size = 9294890 }, + { url = "https://files.pythonhosted.org/packages/71/7d/5e3307a1091c8608a1e58043dff49521bc19553c6e9548c7fac6840cc2c4/tokenizers-0.20.3-cp310-none-win32.whl", hash = "sha256:ee31ba9d7df6a98619426283e80c6359f167e2e9882d9ce1b0254937dbd32f3f", size = 2196883 }, + { url = "https://files.pythonhosted.org/packages/47/62/aaf5b2a526b3b10c20985d9568ff8c8f27159345eaef3347831e78cd5894/tokenizers-0.20.3-cp310-none-win_amd64.whl", hash = "sha256:a845c08fdad554fe0871d1255df85772f91236e5fd6b9287ef8b64f5807dbd0c", size = 2381637 }, + { url = "https://files.pythonhosted.org/packages/c6/93/6742ef9206409d5ce1fdf44d5ca1687cdc3847ba0485424e2c731e6bcf67/tokenizers-0.20.3-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:585b51e06ca1f4839ce7759941e66766d7b060dccfdc57c4ca1e5b9a33013a90", size = 2674224 }, + { url = "https://files.pythonhosted.org/packages/aa/14/e75ece72e99f6ef9ae07777ca9fdd78608f69466a5cecf636e9bd2f25d5c/tokenizers-0.20.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:61cbf11954f3b481d08723ebd048ba4b11e582986f9be74d2c3bdd9293a4538d", size = 2558991 }, + { url = "https://files.pythonhosted.org/packages/46/54/033b5b2ba0c3ae01e026c6f7ced147d41a2fa1c573d00a66cb97f6d7f9b3/tokenizers-0.20.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ef820880d5e4e8484e2fa54ff8d297bb32519eaa7815694dc835ace9130a3eea", size = 2892476 }, + { url = "https://files.pythonhosted.org/packages/e6/b0/cc369fb3297d61f3311cab523d16d48c869dc2f0ba32985dbf03ff811041/tokenizers-0.20.3-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:67ef4dcb8841a4988cd00dd288fb95dfc8e22ed021f01f37348fd51c2b055ba9", size = 2802775 }, + { url = "https://files.pythonhosted.org/packages/1a/74/62ad983e8ea6a63e04ed9c5be0b605056bf8aac2f0125f9b5e0b3e2b89fa/tokenizers-0.20.3-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ff1ef8bd47a02b0dc191688ccb4da53600df5d4c9a05a4b68e1e3de4823e78eb", size = 3086138 }, + { url = "https://files.pythonhosted.org/packages/6b/ac/4637ba619db25094998523f9e6f5b456e1db1f8faa770a3d925d436db0c3/tokenizers-0.20.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:444d188186eab3148baf0615b522461b41b1f0cd58cd57b862ec94b6ac9780f1", size = 3098076 }, + { url = "https://files.pythonhosted.org/packages/58/ce/9793f2dc2ce529369807c9c74e42722b05034af411d60f5730b720388c7d/tokenizers-0.20.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:37c04c032c1442740b2c2d925f1857885c07619224a533123ac7ea71ca5713da", size = 3379650 }, + { url = "https://files.pythonhosted.org/packages/50/f6/2841de926bc4118af996eaf0bdf0ea5b012245044766ffc0347e6c968e63/tokenizers-0.20.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:453c7769d22231960ee0e883d1005c93c68015025a5e4ae56275406d94a3c907", size = 2994005 }, + { url = "https://files.pythonhosted.org/packages/a3/b2/00915c4fed08e9505d37cf6eaab45b12b4bff8f6719d459abcb9ead86a4b/tokenizers-0.20.3-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:4bb31f7b2847e439766aaa9cc7bccf7ac7088052deccdb2275c952d96f691c6a", size = 8977488 }, + { url = "https://files.pythonhosted.org/packages/e9/ac/1c069e7808181ff57bcf2d39e9b6fbee9133a55410e6ebdaa89f67c32e83/tokenizers-0.20.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:843729bf0f991b29655a069a2ff58a4c24375a553c70955e15e37a90dd4e045c", size = 9294935 }, + { url = "https://files.pythonhosted.org/packages/50/47/722feb70ee68d1c4412b12d0ea4acc2713179fd63f054913990f9e259492/tokenizers-0.20.3-cp311-none-win32.whl", hash = "sha256:efcce3a927b1e20ca694ba13f7a68c59b0bd859ef71e441db68ee42cf20c2442", size = 2197175 }, + { url = "https://files.pythonhosted.org/packages/75/68/1b4f928b15a36ed278332ac75d66d7eb65d865bf344d049c452c18447bf9/tokenizers-0.20.3-cp311-none-win_amd64.whl", hash = "sha256:88301aa0801f225725b6df5dea3d77c80365ff2362ca7e252583f2b4809c4cc0", size = 2381616 }, + { url = "https://files.pythonhosted.org/packages/07/00/92a08af2a6b0c88c50f1ab47d7189e695722ad9714b0ee78ea5e1e2e1def/tokenizers-0.20.3-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:49d12a32e190fad0e79e5bdb788d05da2f20d8e006b13a70859ac47fecf6ab2f", size = 2667951 }, + { url = "https://files.pythonhosted.org/packages/ec/9a/e17a352f0bffbf415cf7d73756f5c73a3219225fc5957bc2f39d52c61684/tokenizers-0.20.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:282848cacfb9c06d5e51489f38ec5aa0b3cd1e247a023061945f71f41d949d73", size = 2555167 }, + { url = "https://files.pythonhosted.org/packages/27/37/d108df55daf4f0fcf1f58554692ff71687c273d870a34693066f0847be96/tokenizers-0.20.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:abe4e08c7d0cd6154c795deb5bf81d2122f36daf075e0c12a8b050d824ef0a64", size = 2898389 }, + { url = "https://files.pythonhosted.org/packages/b2/27/32f29da16d28f59472fa7fb38e7782069748c7e9ab9854522db20341624c/tokenizers-0.20.3-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ca94fc1b73b3883c98f0c88c77700b13d55b49f1071dfd57df2b06f3ff7afd64", size = 2795866 }, + { url = "https://files.pythonhosted.org/packages/29/4e/8a9a3c89e128c4a40f247b501c10279d2d7ade685953407c4d94c8c0f7a7/tokenizers-0.20.3-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ef279c7e239f95c8bdd6ff319d9870f30f0d24915b04895f55b1adcf96d6c60d", size = 3085446 }, + { url = "https://files.pythonhosted.org/packages/b4/3b/a2a7962c496ebcd95860ca99e423254f760f382cd4bd376f8895783afaf5/tokenizers-0.20.3-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:16384073973f6ccbde9852157a4fdfe632bb65208139c9d0c0bd0176a71fd67f", size = 3094378 }, + { url = "https://files.pythonhosted.org/packages/1f/f4/a8a33f0192a1629a3bd0afcad17d4d221bbf9276da4b95d226364208d5eb/tokenizers-0.20.3-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:312d522caeb8a1a42ebdec87118d99b22667782b67898a76c963c058a7e41d4f", size = 3385755 }, + { url = "https://files.pythonhosted.org/packages/9e/65/c83cb3545a65a9eaa2e13b22c93d5e00bd7624b354a44adbdc93d5d9bd91/tokenizers-0.20.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f2b7cb962564785a83dafbba0144ecb7f579f1d57d8c406cdaa7f32fe32f18ad", size = 2997679 }, + { url = "https://files.pythonhosted.org/packages/55/e9/a80d4e592307688a67c7c59ab77e03687b6a8bd92eb5db763a2c80f93f57/tokenizers-0.20.3-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:124c5882ebb88dadae1fc788a582299fcd3a8bd84fc3e260b9918cf28b8751f5", size = 8989296 }, + { url = "https://files.pythonhosted.org/packages/90/af/60c957af8d2244321124e893828f1a4817cde1a2d08d09d423b73f19bd2f/tokenizers-0.20.3-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:2b6e54e71f84c4202111a489879005cb14b92616a87417f6c102c833af961ea2", size = 9303621 }, + { url = "https://files.pythonhosted.org/packages/be/a9/96172310ee141009646d63a1ca267c099c462d747fe5ef7e33f74e27a683/tokenizers-0.20.3-cp312-none-win32.whl", hash = "sha256:83d9bfbe9af86f2d9df4833c22e94d94750f1d0cd9bfb22a7bb90a86f61cdb1c", size = 2188979 }, + { url = "https://files.pythonhosted.org/packages/bd/68/61d85ae7ae96dde7d0974ff3538db75d5cdc29be2e4329cd7fc51a283e22/tokenizers-0.20.3-cp312-none-win_amd64.whl", hash = "sha256:44def74cee574d609a36e17c8914311d1b5dbcfe37c55fd29369d42591b91cf2", size = 2380725 }, + { url = "https://files.pythonhosted.org/packages/29/cd/ff1586dd572aaf1637d59968df3f6f6532fa255f4638fbc29f6d27e0b690/tokenizers-0.20.3-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:e919f2e3e68bb51dc31de4fcbbeff3bdf9c1cad489044c75e2b982a91059bd3c", size = 2672044 }, + { url = "https://files.pythonhosted.org/packages/b5/9e/7a2c00abbc8edb021ee0b1f12aab76a7b7824b49f94bcd9f075d0818d4b0/tokenizers-0.20.3-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:b8e9608f2773996cc272156e305bd79066163a66b0390fe21750aff62df1ac07", size = 2558841 }, + { url = "https://files.pythonhosted.org/packages/8e/c1/6af62ef61316f33ecf785bbb2bee4292f34ea62b491d4480ad9b09acf6b6/tokenizers-0.20.3-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:39270a7050deaf50f7caff4c532c01b3c48f6608d42b3eacdebdc6795478c8df", size = 2897936 }, + { url = "https://files.pythonhosted.org/packages/9a/0b/c076b2ff3ee6dc70c805181fbe325668b89cfee856f8dfa24cc9aa293c84/tokenizers-0.20.3-pp310-pypy310_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e005466632b1c5d2d2120f6de8aa768cc9d36cd1ab7d51d0c27a114c91a1e6ee", size = 3082688 }, + { url = "https://files.pythonhosted.org/packages/0a/60/56510124933136c2e90879e1c81603cfa753ae5a87830e3ef95056b20d8f/tokenizers-0.20.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a07962340b36189b6c8feda552ea1bfeee6cf067ff922a1d7760662c2ee229e5", size = 2998924 }, + { url = "https://files.pythonhosted.org/packages/68/60/4107b618b7b9155cb34ad2e0fc90946b7e71f041b642122fb6314f660688/tokenizers-0.20.3-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:55046ad3dd5f2b3c67501fcc8c9cbe3e901d8355f08a3b745e9b57894855f85b", size = 8989514 }, + { url = "https://files.pythonhosted.org/packages/e8/bd/48475818e614b73316baf37ac1e4e51b578bbdf58651812d7e55f43b88d8/tokenizers-0.20.3-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:efcf0eb939988b627558aaf2b9dc3e56d759cad2e0cfa04fcab378e4b48fc4fd", size = 9303476 }, ] [[package]] @@ -7685,11 +7674,31 @@ wheels = [ [[package]] name = "tomli" -version = "2.0.2" +version = "2.2.1" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/35/b9/de2a5c0144d7d75a57ff355c0c24054f965b2dc3036456ae03a51ea6264b/tomli-2.0.2.tar.gz", hash = "sha256:d46d457a85337051c36524bc5349dd91b1877838e2979ac5ced3e710ed8a60ed", size = 16096 } +sdist = { url = "https://files.pythonhosted.org/packages/18/87/302344fed471e44a87289cf4967697d07e532f2421fdaf868a303cbae4ff/tomli-2.2.1.tar.gz", hash = "sha256:cd45e1dc79c835ce60f7404ec8119f2eb06d38b1deba146f07ced3bbc44505ff", size = 17175 } wheels = [ - { url = "https://files.pythonhosted.org/packages/cf/db/ce8eda256fa131af12e0a76d481711abe4681b6923c27efb9a255c9e4594/tomli-2.0.2-py3-none-any.whl", hash = "sha256:2ebe24485c53d303f690b0ec092806a085f07af5a5aa1464f3931eec36caaa38", size = 13237 }, + { url = "https://files.pythonhosted.org/packages/43/ca/75707e6efa2b37c77dadb324ae7d9571cb424e61ea73fad7c56c2d14527f/tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249", size = 131077 }, + { url = "https://files.pythonhosted.org/packages/c7/16/51ae563a8615d472fdbffc43a3f3d46588c264ac4f024f63f01283becfbb/tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6", size = 123429 }, + { url = "https://files.pythonhosted.org/packages/f1/dd/4f6cd1e7b160041db83c694abc78e100473c15d54620083dbd5aae7b990e/tomli-2.2.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ece47d672db52ac607a3d9599a9d48dcb2f2f735c6c2d1f34130085bb12b112a", size = 226067 }, + { url = "https://files.pythonhosted.org/packages/a9/6b/c54ede5dc70d648cc6361eaf429304b02f2871a345bbdd51e993d6cdf550/tomli-2.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6972ca9c9cc9f0acaa56a8ca1ff51e7af152a9f87fb64623e31d5c83700080ee", size = 236030 }, + { url = "https://files.pythonhosted.org/packages/1f/47/999514fa49cfaf7a92c805a86c3c43f4215621855d151b61c602abb38091/tomli-2.2.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c954d2250168d28797dd4e3ac5cf812a406cd5a92674ee4c8f123c889786aa8e", size = 240898 }, + { url = "https://files.pythonhosted.org/packages/73/41/0a01279a7ae09ee1573b423318e7934674ce06eb33f50936655071d81a24/tomli-2.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8dd28b3e155b80f4d54beb40a441d366adcfe740969820caf156c019fb5c7ec4", size = 229894 }, + { url = "https://files.pythonhosted.org/packages/55/18/5d8bc5b0a0362311ce4d18830a5d28943667599a60d20118074ea1b01bb7/tomli-2.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:e59e304978767a54663af13c07b3d1af22ddee3bb2fb0618ca1593e4f593a106", size = 245319 }, + { url = "https://files.pythonhosted.org/packages/92/a3/7ade0576d17f3cdf5ff44d61390d4b3febb8a9fc2b480c75c47ea048c646/tomli-2.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:33580bccab0338d00994d7f16f4c4ec25b776af3ffaac1ed74e0b3fc95e885a8", size = 238273 }, + { url = "https://files.pythonhosted.org/packages/72/6f/fa64ef058ac1446a1e51110c375339b3ec6be245af9d14c87c4a6412dd32/tomli-2.2.1-cp311-cp311-win32.whl", hash = "sha256:465af0e0875402f1d226519c9904f37254b3045fc5084697cefb9bdde1ff99ff", size = 98310 }, + { url = "https://files.pythonhosted.org/packages/6a/1c/4a2dcde4a51b81be3530565e92eda625d94dafb46dbeb15069df4caffc34/tomli-2.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:2d0f2fdd22b02c6d81637a3c95f8cd77f995846af7414c5c4b8d0545afa1bc4b", size = 108309 }, + { url = "https://files.pythonhosted.org/packages/52/e1/f8af4c2fcde17500422858155aeb0d7e93477a0d59a98e56cbfe75070fd0/tomli-2.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:4a8f6e44de52d5e6c657c9fe83b562f5f4256d8ebbfe4ff922c495620a7f6cea", size = 132762 }, + { url = "https://files.pythonhosted.org/packages/03/b8/152c68bb84fc00396b83e7bbddd5ec0bd3dd409db4195e2a9b3e398ad2e3/tomli-2.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8d57ca8095a641b8237d5b079147646153d22552f1c637fd3ba7f4b0b29167a8", size = 123453 }, + { url = "https://files.pythonhosted.org/packages/c8/d6/fc9267af9166f79ac528ff7e8c55c8181ded34eb4b0e93daa767b8841573/tomli-2.2.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4e340144ad7ae1533cb897d406382b4b6fede8890a03738ff1683af800d54192", size = 233486 }, + { url = "https://files.pythonhosted.org/packages/5c/51/51c3f2884d7bab89af25f678447ea7d297b53b5a3b5730a7cb2ef6069f07/tomli-2.2.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:db2b95f9de79181805df90bedc5a5ab4c165e6ec3fe99f970d0e302f384ad222", size = 242349 }, + { url = "https://files.pythonhosted.org/packages/ab/df/bfa89627d13a5cc22402e441e8a931ef2108403db390ff3345c05253935e/tomli-2.2.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:40741994320b232529c802f8bc86da4e1aa9f413db394617b9a256ae0f9a7f77", size = 252159 }, + { url = "https://files.pythonhosted.org/packages/9e/6e/fa2b916dced65763a5168c6ccb91066f7639bdc88b48adda990db10c8c0b/tomli-2.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:400e720fe168c0f8521520190686ef8ef033fb19fc493da09779e592861b78c6", size = 237243 }, + { url = "https://files.pythonhosted.org/packages/b4/04/885d3b1f650e1153cbb93a6a9782c58a972b94ea4483ae4ac5cedd5e4a09/tomli-2.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:02abe224de6ae62c19f090f68da4e27b10af2b93213d36cf44e6e1c5abd19fdd", size = 259645 }, + { url = "https://files.pythonhosted.org/packages/9c/de/6b432d66e986e501586da298e28ebeefd3edc2c780f3ad73d22566034239/tomli-2.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b82ebccc8c8a36f2094e969560a1b836758481f3dc360ce9a3277c65f374285e", size = 244584 }, + { url = "https://files.pythonhosted.org/packages/1c/9a/47c0449b98e6e7d1be6cbac02f93dd79003234ddc4aaab6ba07a9a7482e2/tomli-2.2.1-cp312-cp312-win32.whl", hash = "sha256:889f80ef92701b9dbb224e49ec87c645ce5df3fa2cc548664eb8a25e03127a98", size = 98875 }, + { url = "https://files.pythonhosted.org/packages/ef/60/9b9638f081c6f1261e2688bd487625cd1e660d0a85bd469e91d8db969734/tomli-2.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:7fc04e92e1d624a4a63c76474610238576942d6b8950a2d7f908a340494e67e4", size = 109418 }, + { url = "https://files.pythonhosted.org/packages/6e/c2/61d3e0f47e2b74ef40a68b9e6ad5984f6241a942f7cd3bbfbdbd03861ea9/tomli-2.2.1-py3-none-any.whl", hash = "sha256:cb55c73c5f4408779d0cf3eef9f762b9c9f147a77de7b258bef0a5628adc85cc", size = 14257 }, ] [[package]] @@ -7742,32 +7751,32 @@ wheels = [ [[package]] name = "tornado" -version = "6.4.1" +version = "6.4.2" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/ee/66/398ac7167f1c7835406888a386f6d0d26ee5dbf197d8a571300be57662d3/tornado-6.4.1.tar.gz", hash = "sha256:92d3ab53183d8c50f8204a51e6f91d18a15d5ef261e84d452800d4ff6fc504e9", size = 500623 } +sdist = { url = "https://files.pythonhosted.org/packages/59/45/a0daf161f7d6f36c3ea5fc0c2de619746cc3dd4c76402e9db545bd920f63/tornado-6.4.2.tar.gz", hash = "sha256:92bad5b4746e9879fd7bf1eb21dce4e3fc5128d71601f80005afa39237ad620b", size = 501135 } wheels = [ - { url = "https://files.pythonhosted.org/packages/00/d9/c33be3c1a7564f7d42d87a8d186371a75fd142097076767a5c27da941fef/tornado-6.4.1-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:163b0aafc8e23d8cdc3c9dfb24c5368af84a81e3364745ccb4427669bf84aec8", size = 435924 }, - { url = "https://files.pythonhosted.org/packages/2e/0f/721e113a2fac2f1d7d124b3279a1da4c77622e104084f56119875019ffab/tornado-6.4.1-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:6d5ce3437e18a2b66fbadb183c1d3364fb03f2be71299e7d10dbeeb69f4b2a14", size = 433883 }, - { url = "https://files.pythonhosted.org/packages/13/cf/786b8f1e6fe1c7c675e79657448178ad65e41c1c9765ef82e7f6f765c4c5/tornado-6.4.1-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e2e20b9113cd7293f164dc46fffb13535266e713cdb87bd2d15ddb336e96cfc4", size = 437224 }, - { url = "https://files.pythonhosted.org/packages/e4/8e/a6ce4b8d5935558828b0f30f3afcb2d980566718837b3365d98e34f6067e/tornado-6.4.1-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8ae50a504a740365267b2a8d1a90c9fbc86b780a39170feca9bcc1787ff80842", size = 436597 }, - { url = "https://files.pythonhosted.org/packages/22/d4/54f9d12668b58336bd30defe0307e6c61589a3e687b05c366f804b7faaf0/tornado-6.4.1-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:613bf4ddf5c7a95509218b149b555621497a6cc0d46ac341b30bd9ec19eac7f3", size = 436797 }, - { url = "https://files.pythonhosted.org/packages/cf/3f/2c792e7afa7dd8b24fad7a2ed3c2f24a5ec5110c7b43a64cb6095cc106b8/tornado-6.4.1-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:25486eb223babe3eed4b8aecbac33b37e3dd6d776bc730ca14e1bf93888b979f", size = 437516 }, - { url = "https://files.pythonhosted.org/packages/71/63/c8fc62745e669ac9009044b889fc531b6f88ac0f5f183cac79eaa950bb23/tornado-6.4.1-cp38-abi3-musllinux_1_2_i686.whl", hash = "sha256:454db8a7ecfcf2ff6042dde58404164d969b6f5d58b926da15e6b23817950fc4", size = 436958 }, - { url = "https://files.pythonhosted.org/packages/94/d4/f8ac1f5bd22c15fad3b527e025ce219bd526acdbd903f52053df2baecc8b/tornado-6.4.1-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:a02a08cc7a9314b006f653ce40483b9b3c12cda222d6a46d4ac63bb6c9057698", size = 436882 }, - { url = "https://files.pythonhosted.org/packages/4b/3e/a8124c21cc0bbf144d7903d2a0cadab15cadaf683fa39a0f92bc567f0d4d/tornado-6.4.1-cp38-abi3-win32.whl", hash = "sha256:d9a566c40b89757c9aa8e6f032bcdb8ca8795d7c1a9762910c722b1635c9de4d", size = 438092 }, - { url = "https://files.pythonhosted.org/packages/d9/2f/3f2f05e84a7aff787a96d5fb06821323feb370fe0baed4db6ea7b1088f32/tornado-6.4.1-cp38-abi3-win_amd64.whl", hash = "sha256:b24b8982ed444378d7f21d563f4180a2de31ced9d8d84443907a0a64da2072e7", size = 438532 }, + { url = "https://files.pythonhosted.org/packages/26/7e/71f604d8cea1b58f82ba3590290b66da1e72d840aeb37e0d5f7291bd30db/tornado-6.4.2-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:e828cce1123e9e44ae2a50a9de3055497ab1d0aeb440c5ac23064d9e44880da1", size = 436299 }, + { url = "https://files.pythonhosted.org/packages/96/44/87543a3b99016d0bf54fdaab30d24bf0af2e848f1d13d34a3a5380aabe16/tornado-6.4.2-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:072ce12ada169c5b00b7d92a99ba089447ccc993ea2143c9ede887e0937aa803", size = 434253 }, + { url = "https://files.pythonhosted.org/packages/cb/fb/fdf679b4ce51bcb7210801ef4f11fdac96e9885daa402861751353beea6e/tornado-6.4.2-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1a017d239bd1bb0919f72af256a970624241f070496635784d9bf0db640d3fec", size = 437602 }, + { url = "https://files.pythonhosted.org/packages/4f/3b/e31aeffffc22b475a64dbeb273026a21b5b566f74dee48742817626c47dc/tornado-6.4.2-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c36e62ce8f63409301537222faffcef7dfc5284f27eec227389f2ad11b09d946", size = 436972 }, + { url = "https://files.pythonhosted.org/packages/22/55/b78a464de78051a30599ceb6983b01d8f732e6f69bf37b4ed07f642ac0fc/tornado-6.4.2-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bca9eb02196e789c9cb5c3c7c0f04fb447dc2adffd95265b2c7223a8a615ccbf", size = 437173 }, + { url = "https://files.pythonhosted.org/packages/79/5e/be4fb0d1684eb822c9a62fb18a3e44a06188f78aa466b2ad991d2ee31104/tornado-6.4.2-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:304463bd0772442ff4d0f5149c6f1c2135a1fae045adf070821c6cdc76980634", size = 437892 }, + { url = "https://files.pythonhosted.org/packages/f5/33/4f91fdd94ea36e1d796147003b490fe60a0215ac5737b6f9c65e160d4fe0/tornado-6.4.2-cp38-abi3-musllinux_1_2_i686.whl", hash = "sha256:c82c46813ba483a385ab2a99caeaedf92585a1f90defb5693351fa7e4ea0bf73", size = 437334 }, + { url = "https://files.pythonhosted.org/packages/2b/ae/c1b22d4524b0e10da2f29a176fb2890386f7bd1f63aacf186444873a88a0/tornado-6.4.2-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:932d195ca9015956fa502c6b56af9eb06106140d844a335590c1ec7f5277d10c", size = 437261 }, + { url = "https://files.pythonhosted.org/packages/b5/25/36dbd49ab6d179bcfc4c6c093a51795a4f3bed380543a8242ac3517a1751/tornado-6.4.2-cp38-abi3-win32.whl", hash = "sha256:2876cef82e6c5978fde1e0d5b1f919d756968d5b4282418f3146b79b58556482", size = 438463 }, + { url = "https://files.pythonhosted.org/packages/61/cc/58b1adeb1bb46228442081e746fcdbc4540905c87e8add7c277540934edb/tornado-6.4.2-cp38-abi3-win_amd64.whl", hash = "sha256:908b71bf3ff37d81073356a5fadcc660eb10c1476ee6e2725588626ce7e5ca38", size = 438907 }, ] [[package]] name = "tqdm" -version = "4.66.5" +version = "4.67.1" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "colorama", marker = "platform_system == 'Windows'" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/58/83/6ba9844a41128c62e810fddddd72473201f3eacde02046066142a2d96cc5/tqdm-4.66.5.tar.gz", hash = "sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad", size = 169504 } +sdist = { url = "https://files.pythonhosted.org/packages/a8/4b/29b4ef32e036bb34e4ab51796dd745cdba7ed47ad142a9f4a1eb8e0c744d/tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2", size = 169737 } wheels = [ - { url = "https://files.pythonhosted.org/packages/48/5d/acf5905c36149bbaec41ccf7f2b68814647347b72075ac0b1fe3022fdc73/tqdm-4.66.5-py3-none-any.whl", hash = "sha256:90279a3770753eafc9194a0364852159802111925aa30eb3f9d85b0e805ac7cd", size = 78351 }, + { url = "https://files.pythonhosted.org/packages/d0/30/dc54f88dd4a2b5dc8a0279bdd7270e735851848b762aeb1c1184ed1f6b14/tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2", size = 78540 }, ] [[package]] @@ -7781,7 +7790,7 @@ wheels = [ [[package]] name = "transformers" -version = "4.45.2" +version = "4.46.3" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "filelock" }, @@ -7795,56 +7804,56 @@ dependencies = [ { name = "tokenizers" }, { name = "tqdm" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/4b/4c/3862b2dd6cdf83b187897bd351da0f7fb74d0df642b03c6f5d06353a3ca0/transformers-4.45.2.tar.gz", hash = "sha256:72bc390f6b203892561f05f86bbfaa0e234aab8e927a83e62b9d92ea7e3ae101", size = 8478357 } +sdist = { url = "https://files.pythonhosted.org/packages/37/5a/58f96c83e566f907ae39f16d4401bbefd8bb85c60bd1e6a95c419752ab90/transformers-4.46.3.tar.gz", hash = "sha256:8ee4b3ae943fe33e82afff8e837f4b052058b07ca9be3cb5b729ed31295f72cc", size = 8627944 } wheels = [ - { url = "https://files.pythonhosted.org/packages/f9/9d/030cc1b3e88172967e22ee1d012e0d5e0384eb70d2a098d1669d549aea29/transformers-4.45.2-py3-none-any.whl", hash = "sha256:c551b33660cfc815bae1f9f097ecfd1e65be623f13c6ee0dda372bd881460210", size = 9881312 }, + { url = "https://files.pythonhosted.org/packages/51/51/b87caa939fedf307496e4dbf412f4b909af3d9ca8b189fc3b65c1faa456f/transformers-4.46.3-py3-none-any.whl", hash = "sha256:a12ef6f52841fd190a3e5602145b542d03507222f2c64ebb7ee92e8788093aef", size = 10034536 }, ] [[package]] name = "tree-sitter" -version = "0.23.1" +version = "0.23.2" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/01/23/e001538062ece748d7ab1fcfbcd9fa766d85f60f0d5ae014a7caf4f07c70/tree-sitter-0.23.1.tar.gz", hash = "sha256:28fe02aff6676b203cbe4213ca7116db0aaac08d6ca4c0b1f1af038991631838", size = 165822 } +sdist = { url = "https://files.pythonhosted.org/packages/0f/50/fd5fafa42b884f741b28d9e6fd366c3f34e15d2ed3aa9633b34e388379e2/tree-sitter-0.23.2.tar.gz", hash = "sha256:66bae8dd47f1fed7bdef816115146d3a41c39b5c482d7bad36d9ba1def088450", size = 166800 } wheels = [ - { url = "https://files.pythonhosted.org/packages/53/b9/9b3f4d24d2678a7f5a02d45cec22c10334d8d5753b3201a9e998c857b6d1/tree_sitter-0.23.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:81ae139e032a0e1dd450affb8cc299e3d2e948614b970aad15e7704a532e8bcd", size = 137173 }, - { url = "https://files.pythonhosted.org/packages/30/ec/4048be36558c5a31499dc923355e33f04a461a3eb2264e930d428efec73e/tree_sitter-0.23.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:82c2a873654ba771bbbff6067af090e36453fac0e4bfeff80dc3bd803d2a1dc8", size = 130498 }, - { url = "https://files.pythonhosted.org/packages/a2/d0/bfb2a7443674c32e95b81103d76c02d7ef9801b24f9fc6c80e6d90ec25fe/tree_sitter-0.23.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:560ed2eb122b9cef12ec4b9f9eec555976ed75ce9347e95286c56e0ef2a66d8f", size = 546809 }, - { url = "https://files.pythonhosted.org/packages/42/b5/82f772fcc0fb38f488c81566abb041f645fc44c00f595189dcd96f10782b/tree_sitter-0.23.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7386b510c55cae43961532df8ddb8478b365b8cbc4486082bca0a6b0eb49d717", size = 560837 }, - { url = "https://files.pythonhosted.org/packages/06/a0/809ba2818b9e4a67435d618080da2cf362e848dbb5b9c5777cee7cc1bbaf/tree_sitter-0.23.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:ade4f2c083286d50ecf79eb97d89a185e43e370a5b27f7c160080014ebb2aabe", size = 551282 }, - { url = "https://files.pythonhosted.org/packages/aa/38/7f73979903b3e5dbd6eca046a5b9965366f0f6ec6fd3a862e00e1f0da1ad/tree_sitter-0.23.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:00555c016e5deae8befec12a01797fb06954435e48bfc707fc250c71c12d5780", size = 561137 }, - { url = "https://files.pythonhosted.org/packages/9d/89/c366ed62a2c3c1684b1aa1dcac5a0ec2f4a6772d91842dd016ea9acf7c79/tree_sitter-0.23.1-cp310-cp310-win_amd64.whl", hash = "sha256:75268cf478544ed2adb19aa85fed8832cd7c94792bd6010ac5919a86e0c1872b", size = 117161 }, - { url = "https://files.pythonhosted.org/packages/7f/c1/ae9e9154398d09aadd49bfcbd9147722be858b8ae8409c4451394d35df0f/tree_sitter-0.23.1-cp310-cp310-win_arm64.whl", hash = "sha256:92b9da86047bc0bba8571042f1f2e89d28968f840ad5bb431dc7bc412d06b634", size = 101746 }, - { url = "https://files.pythonhosted.org/packages/c4/8e/9a0fa47fdd1aea7ee0ed93dd504a0c6cc377c00d9951097260653ef0fe5a/tree_sitter-0.23.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:a7805207eebd4b877713708d3a684b1b619bdd9da794348a668be2e126aeb1e4", size = 136984 }, - { url = "https://files.pythonhosted.org/packages/6c/f2/e56280349740763ee8a4114c48d9de2ba688fc1bebfc0d3db3e83b2ef991/tree_sitter-0.23.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:8a027435291336db0fd10ddcb6b38952c278533cb659500ac134fbd5edc8564d", size = 130366 }, - { url = "https://files.pythonhosted.org/packages/9c/72/d7ef26bea37239a739507e32381fea0071633771308f448b2d17ff9229ef/tree_sitter-0.23.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c95581fbd111a793cd2b12af261abd5f291a16b1e43a4abc3011d206c126bd19", size = 548038 }, - { url = "https://files.pythonhosted.org/packages/8c/94/eef80fdb8d137ef740508a0c6ae7c9a8af7e39a8d1cb666a75768605f6cb/tree_sitter-0.23.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2196816e80f8b280b2a2f9084329153175a95f229104a9f0e534efbe601d5a9f", size = 561937 }, - { url = "https://files.pythonhosted.org/packages/07/27/d629eab59dc65ce24fbf64b74cd0399c0bd2c42c856e8e93d52c87e9f500/tree_sitter-0.23.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:b64bf264bc2381aaed97982e53dd7b2071e86c1e35be47aff80bbcdbd933434a", size = 552641 }, - { url = "https://files.pythonhosted.org/packages/07/73/6ad67affb0b769411387ef71033175044045e05cc79a8c5c252b48c5db98/tree_sitter-0.23.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:5cfe4f4682f0d21298a685f22b4a539b513311cb4d7bf3e64c66f0fe6034db49", size = 562643 }, - { url = "https://files.pythonhosted.org/packages/39/75/8272ab2b02b7266c9518762482c4f0a99a02c068d53130fde864c04acaf4/tree_sitter-0.23.1-cp311-cp311-win_amd64.whl", hash = "sha256:080ffaf8df305925a7ea792bd9b9e71729ea85f3bf97d9a2efde4e44bad989a9", size = 117032 }, - { url = "https://files.pythonhosted.org/packages/6d/60/b2d42c6ef4c01b36e7215f7542ef56eb341452e327ae87567bb269bc3bd1/tree_sitter-0.23.1-cp311-cp311-win_arm64.whl", hash = "sha256:ac46271c93a811c56897fbe3bb2dfccdb487045ca0f26d38cb9ef4fdbeabedf2", size = 101673 }, - { url = "https://files.pythonhosted.org/packages/5d/69/6c257bc713e93303382e6d75c46ec940bcd7001b12fbb2deedec33a0b812/tree_sitter-0.23.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:af768b0c70b0ce53a725135c7f6e36745a964d4e2e8adb20bdc7211756a6aae6", size = 137144 }, - { url = "https://files.pythonhosted.org/packages/68/85/3169006cfce9fe99b271a370eb2a83daa0f64ac3d2d7afb4bd4cee1d8968/tree_sitter-0.23.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:95bb56f5ff20fe6cfc9580dfa4497d3c9ee9dd37dbc683d3b853323c19acd130", size = 130093 }, - { url = "https://files.pythonhosted.org/packages/4a/54/e8c6404b79e4273c89a239c492941bddc6a4dc5dc3688f9d8f5d892b5b56/tree_sitter-0.23.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fdf0cbbb3d19ceedc7ce0a4bc3726ea835f673f491b4f630bdd22d3ce209fcfc", size = 550927 }, - { url = "https://files.pythonhosted.org/packages/91/79/6526dab6e86431880669f90481cddc45455de827ebf4ee5321a7d9901f2d/tree_sitter-0.23.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:522742a786f3223cdb8ee272e648cbfcac3af4d0119f2e9de6626df7c8605a9d", size = 565220 }, - { url = "https://files.pythonhosted.org/packages/bf/17/eb0370b8e3d5a7b0619241bedf3380cb04567fdd0b823836cc85c163aa04/tree_sitter-0.23.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:a03b166330c09dc2941b26f4f7819e3314e5a0f70e7a496e76ff5961953676b9", size = 555208 }, - { url = "https://files.pythonhosted.org/packages/da/63/4d4ef8a05f494f89f202b2502815921fe35f1668eb7e3ed14ebac415b525/tree_sitter-0.23.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:0c8e09804455b5091cb0ec2e1a27e972ca26d65fbbbc74aa79f3f70f6075af51", size = 566986 }, - { url = "https://files.pythonhosted.org/packages/d6/8c/6e1147412d53262284680ced69bdef2622d0e19c9c53e4fd10f6cd9510e5/tree_sitter-0.23.1-cp312-cp312-win_amd64.whl", hash = "sha256:c50227ef6f8d8b1442c595f443b487c40a2445dac54db0d9a9a01df347c3e100", size = 117134 }, - { url = "https://files.pythonhosted.org/packages/df/a8/403c977f5dcddf3c7805ca0f4ade91b057c1a8d8f440d99c8a9cfa313857/tree_sitter-0.23.1-cp312-cp312-win_arm64.whl", hash = "sha256:c4caeba0abae929a1372092bbdf11c58fb008a931b52c2fe861b9fb98ebdc8d3", size = 101560 }, + { url = "https://files.pythonhosted.org/packages/91/04/2068a7b725265ecfcbf63ecdae038f1d4124ebccd55b8a7ce145b70e2b6a/tree_sitter-0.23.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:3a937f5d8727bc1c74c4bf2a9d1c25ace049e8628273016ad0d45914ae904e10", size = 139289 }, + { url = "https://files.pythonhosted.org/packages/a8/07/a5b943121f674fe1ac77694a698e71ce95353830c1f3f4ce45da7ef3e406/tree_sitter-0.23.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2c7eae7fe2af215645a38660d2d57d257a4c461fe3ec827cca99a79478284e80", size = 132379 }, + { url = "https://files.pythonhosted.org/packages/d4/96/fcc72c33d464a2d722db1e95b74a53ced771a47b3cfde60aced29764a783/tree_sitter-0.23.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3a71d607595270b6870eaf778a1032d146b2aa79bfcfa60f57a82a7b7584a4c7", size = 552884 }, + { url = "https://files.pythonhosted.org/packages/d0/af/b0e787a52767155b4643a55d6de03c1e4ae77abb61e1dc1629ad983e0a40/tree_sitter-0.23.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6fe9b9ea7a0aa23b52fd97354da95d1b2580065bc12a4ac868f9164a127211d6", size = 566561 }, + { url = "https://files.pythonhosted.org/packages/65/fd/05e966b5317b1c6679c071c5b0203f28af9d26c9363700cb9682e1bcf343/tree_sitter-0.23.2-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:d74d00a8021719eae14d10d1b1e28649e15d8b958c01c2b2c3dad7a2ebc4dbae", size = 558273 }, + { url = "https://files.pythonhosted.org/packages/60/bc/19145efdf3f47711aa3f1bf06f0b50593f97f1108550d38694841fd97b7c/tree_sitter-0.23.2-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:6de18d8d8a7f67ab71f472d1fcb01cc506e080cbb5e13d52929e4b6fdce6bbee", size = 569176 }, + { url = "https://files.pythonhosted.org/packages/32/08/3553d8e488ae9284a0762effafb7d2639a306e184963b7f99853923084d6/tree_sitter-0.23.2-cp310-cp310-win_amd64.whl", hash = "sha256:12b60dca70d2282af942b650a6d781be487485454668c7c956338a367b98cdee", size = 117902 }, + { url = "https://files.pythonhosted.org/packages/1d/39/836fa485e985c33e8aa1cc3abbf7a84be1c2c382e69547a765631fdd7ce3/tree_sitter-0.23.2-cp310-cp310-win_arm64.whl", hash = "sha256:3346a4dd0447a42aabb863443b0fd8c92b909baf40ed2344fae4b94b625d5955", size = 102644 }, + { url = "https://files.pythonhosted.org/packages/55/8d/2d4fb04408772be0919441d66f700673ce7cb76b9ab6682e226d740fb88d/tree_sitter-0.23.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:91fda41d4f8824335cc43c64e2c37d8089c8c563bd3900a512d2852d075af719", size = 139142 }, + { url = "https://files.pythonhosted.org/packages/32/52/b8a44bfff7b0203256e5dbc8d3a372ee8896128b8ed7d3a89e1ef17b2065/tree_sitter-0.23.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:92b2b489d5ce54b41f94c6f23fbaf592bd6e84dc2877048fd1cb060480fa53f7", size = 132198 }, + { url = "https://files.pythonhosted.org/packages/5d/54/746f2ee5acf6191a4a0be7f5843329f0d713bfe5196f5fc6fe2ea69cb44c/tree_sitter-0.23.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:64859bd4aa1567d0d6016a811b2b49c59d4a4427d096e3d8c84b2521455f62b7", size = 554303 }, + { url = "https://files.pythonhosted.org/packages/2f/5a/3169d9933be813776a9b4b3f2e671d3d50fa27e589dee5578f6ecef7ff6d/tree_sitter-0.23.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:614590611636044e071d3a0b748046d52676dbda3bc9fa431216231e11dd98f7", size = 567626 }, + { url = "https://files.pythonhosted.org/packages/32/0d/23f363b3b0bc3fa0e7a4a294bf119957ac1ab02737d57815e1e8b7b3e196/tree_sitter-0.23.2-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:08466953c78ae57be61057188fb88c89791b0a562856010228e0ccf60e2ac453", size = 559803 }, + { url = "https://files.pythonhosted.org/packages/6f/b3/1ffba0f17a7ff2c9114d91a1ecc15e0748f217817797564d31fbb61d7458/tree_sitter-0.23.2-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:8a33f03a562de91f7fd05eefcedd8994a06cd44c62f7aabace811ad82bc11cbd", size = 570987 }, + { url = "https://files.pythonhosted.org/packages/59/4b/085bcb8a11ea18003aacc4dbc91c301d1536c5e2deedb95393e8ef26f1f7/tree_sitter-0.23.2-cp311-cp311-win_amd64.whl", hash = "sha256:03b70296b569ef64f7b92b42ca5da9bf86d81bee2afd480bea35092687f51dae", size = 117771 }, + { url = "https://files.pythonhosted.org/packages/4b/e5/90adc4081f49ccb6bea89a800dc9b0dcc5b6953b0da423e8eff28f63fddf/tree_sitter-0.23.2-cp311-cp311-win_arm64.whl", hash = "sha256:7cb4bb953ea7c0b50eeafc4454783e030357179d2a93c3dd5ebed2da5588ddd0", size = 102555 }, + { url = "https://files.pythonhosted.org/packages/07/a7/57e0fe87b49a78c670a7b4483f70e44c000c65c29b138001096b22e7dd87/tree_sitter-0.23.2-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:a014498b6a9e6003fae8c6eb72f5927d62da9dcb72b28b3ce8cd15c6ff6a6572", size = 139259 }, + { url = "https://files.pythonhosted.org/packages/b4/b9/bc8513d818ffb54993a017a36c8739300bc5739a13677acf90b54995e7db/tree_sitter-0.23.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:04f8699b131d4bcbe3805c37e4ef3d159ee9a82a0e700587625623999ba0ea53", size = 131951 }, + { url = "https://files.pythonhosted.org/packages/d7/6a/eab01bb6b1ce3c9acf16d72922ffc29a904af485eb3e60baf3a3e04edd30/tree_sitter-0.23.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4471577df285059c71686ecb208bc50fb472099b38dcc8e849b0e86652891e87", size = 557952 }, + { url = "https://files.pythonhosted.org/packages/bd/95/f2f73332623cf63200d57800f85273170bc5f99d28ea3f234afd5b0048df/tree_sitter-0.23.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f342c925290dd4e20ecd5787ef7ae8749981597ab364783a1eb73173efe65226", size = 571199 }, + { url = "https://files.pythonhosted.org/packages/04/ac/bd6e6cfdd0421156e86f5c93848629af1c7323083077e1a95b27d32d5811/tree_sitter-0.23.2-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:a4e9e53d07dd076bede72e4f7d3a0173d7b9ad6576572dd86da008a740a9bb22", size = 562129 }, + { url = "https://files.pythonhosted.org/packages/7b/bd/8a9edcbcf8a76b0bf58e3b927ed291e3598e063d56667367762833cc8709/tree_sitter-0.23.2-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:8caebe65bc358759dac2500d8f8feed3aed939c4ade9a684a1783fe07bc7d5db", size = 574307 }, + { url = "https://files.pythonhosted.org/packages/0c/c2/3fb2c6c0ae2f59a7411dc6d3e7945e3cb6f34c8552688708acc8b2b13f83/tree_sitter-0.23.2-cp312-cp312-win_amd64.whl", hash = "sha256:fc5a72eb50d43485000dbbb309acb350467b7467e66dc747c6bb82ce63041582", size = 117858 }, + { url = "https://files.pythonhosted.org/packages/e2/18/4ca2c0f4a0c802ebcb3a92264cc436f1d54b394fa24dfa76bf57cdeaca9e/tree_sitter-0.23.2-cp312-cp312-win_arm64.whl", hash = "sha256:a0320eb6c7993359c5f7b371d22719ccd273f440d41cf1bd65dac5e9587f2046", size = 102496 }, ] [[package]] name = "tree-sitter-python" -version = "0.23.2" +version = "0.23.5" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/fe/fe/34663adbaeb139410f7fc5fbab7c16391c56458cc8083a91e85bb768fc39/tree_sitter_python-0.23.2.tar.gz", hash = "sha256:da6abb90a8061d70651f170403e19aed1db4e6e5bcf4b9396245421899c94070", size = 154745 } +sdist = { url = "https://files.pythonhosted.org/packages/50/a4/09802e767caed47edeeacb5b2055b0fbde700df5f62df53e49cafee003c4/tree_sitter_python-0.23.5.tar.gz", hash = "sha256:bd18325d93d633b4d411f24bb5e7d34ee653cd3254e5963fb3c2738ee3c4a1ee", size = 154776 } wheels = [ - { url = "https://files.pythonhosted.org/packages/b9/6a/7d66f1f04b8ae95ea1c9e21047b8a7f32394d009a65c701d5e66958617f9/tree_sitter_python-0.23.2-cp39-abi3-macosx_10_9_x86_64.whl", hash = "sha256:64d733c029db4356aeecd4b2160e793066490f07a9ce549b53aa8100d49d6083", size = 73808 }, - { url = "https://files.pythonhosted.org/packages/2f/00/672604186dca780fbdc702c485f4e954940c78587d736e7da948094fabc3/tree_sitter_python-0.23.2-cp39-abi3-macosx_11_0_arm64.whl", hash = "sha256:c7a75736b0b8704c7e1eb7edeff8c8d1dc17832de76a65ae375fd59c01b2fc84", size = 75865 }, - { url = "https://files.pythonhosted.org/packages/55/9b/49d2931f52fad677425c871ce17e01c7e4263d9bd5c386ae3f48857d4ef0/tree_sitter_python-0.23.2-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ba8ddaf42ad390bda21c25f243b60f906a4c681b450400f689481f0e2b914028", size = 111401 }, - { url = "https://files.pythonhosted.org/packages/63/5f/1ecb751a356d67141f4d65dbc6c154492c8c77ebc313cf3eed01048cd5d2/tree_sitter_python-0.23.2-cp39-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fc14405a4e83c110939aafdf21b0c7814a1534e2e6a22599bc2f6b44abc72fdd", size = 111894 }, - { url = "https://files.pythonhosted.org/packages/01/4d/1d8f12740c9b6f1ff7ad767561d42a1c5678054f1cc14b2f576d61d22a0d/tree_sitter_python-0.23.2-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:d09c4d6074825c707414bc10c1e90dc5764281cc080bfb7a0ab7c04d0610dbca", size = 111013 }, - { url = "https://files.pythonhosted.org/packages/f1/5f/c7782a151e16ca89069857a5a7b06062cd55e9c56faeb11b5116136fd88e/tree_sitter_python-0.23.2-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:3ee327eaa85b61ea34f878c46fd55a8b1bcbc21d9683782b4f2e7ae9bb23ea51", size = 108920 }, - { url = "https://files.pythonhosted.org/packages/ed/2a/542b50ca33b63b6eb9b0bdfab849715effea91bcd7c5246caa3f07dd53ac/tree_sitter_python-0.23.2-cp39-abi3-win_amd64.whl", hash = "sha256:a427c3e5b107febd9f0bfc8df4d91854bda110192d50d741d135f6d37b28fcbd", size = 75354 }, + { url = "https://files.pythonhosted.org/packages/f5/05/074c5a710a752ae4d333bf2d59b333a41115274b4ca19ba98a3cf09545e1/tree_sitter_python-0.23.5-cp39-abi3-macosx_10_9_x86_64.whl", hash = "sha256:095d104f7f13694ee95ca8540b39a77a57bf9f037797c2658b8400c5b5ece117", size = 73804 }, + { url = "https://files.pythonhosted.org/packages/a2/de/51e3a0400516971ae6c17ab026701e6b5f5366055dd0abeefe3d2d98c4e6/tree_sitter_python-0.23.5-cp39-abi3-macosx_11_0_arm64.whl", hash = "sha256:a27f874083b2a204a5c1aa85ebe15e23a441816ee60a6bcf6a4daad7044176ca", size = 75861 }, + { url = "https://files.pythonhosted.org/packages/b8/a1/972d24196beb519ea9da3e664a09fb4b918ee7ba567e1c30df9af5f73830/tree_sitter_python-0.23.5-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3cb5aebdd64a30e3557e481bd0f6d553a1570e088626529fac5a70165a67b84e", size = 111279 }, + { url = "https://files.pythonhosted.org/packages/89/37/75a67be73a05e620e9fb9e5dd7c429da99e19d06a0babdafbca468189046/tree_sitter_python-0.23.5-cp39-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:040c0cbebf127b578e183ce084feb8f0ca7e9e26bcd0a4f6cf1a8f47e13b0b5a", size = 111767 }, + { url = "https://files.pythonhosted.org/packages/12/4a/b96ab60c6b4450bb03083631e22e4ec72a1a8bc0d734037f8eb4f6dd2da1/tree_sitter_python-0.23.5-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:c62262e96e67f6f63467f74b37c6fa4b618b3d2ddd7ad16280c101d1f9be8a8a", size = 108791 }, + { url = "https://files.pythonhosted.org/packages/d1/7b/0f9e440a5e7fef8dd92fc96b9fd5a610d6d0a8f70af50b286e237fff63cc/tree_sitter_python-0.23.5-cp39-abi3-win_amd64.whl", hash = "sha256:2b52ec8279193b0f8979aef4b0ac60c99e2856ab02eeeb1a62b55a03c012e3fd", size = 75355 }, + { url = "https://files.pythonhosted.org/packages/9a/60/b293cfefe7b469e0ecff9a755fd3dc36a77c07f94a715e608c5b41802661/tree_sitter_python-0.23.5-cp39-abi3-win_arm64.whl", hash = "sha256:efd1a1a44322c46b27ff439e6103d8199d53ffc38c021e7856067c9c90617460", size = 73077 }, ] [[package]] @@ -7894,7 +7903,7 @@ wheels = [ [[package]] name = "typer" -version = "0.13.0" +version = "0.15.1" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "click" }, @@ -7902,9 +7911,9 @@ dependencies = [ { name = "shellingham" }, { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/e7/87/9eb07fdfa14e22ec7658b5b1147836d22df3848a22c85a4e18ed272303a5/typer-0.13.0.tar.gz", hash = "sha256:f1c7198347939361eec90139ffa0fd8b3df3a2259d5852a0f7400e476d95985c", size = 97572 } +sdist = { url = "https://files.pythonhosted.org/packages/cb/ce/dca7b219718afd37a0068f4f2530a727c2b74a8b6e8e0c0080a4c0de4fcd/typer-0.15.1.tar.gz", hash = "sha256:a0588c0a7fa68a1978a069818657778f86abe6ff5ea6abf472f940a08bfe4f0a", size = 99789 } wheels = [ - { url = "https://files.pythonhosted.org/packages/18/7e/c8bfa8cbcd3ea1d25d2beb359b5c5a3f4339a7e2e5d9e3ef3e29ba3ab3b9/typer-0.13.0-py3-none-any.whl", hash = "sha256:d85fe0b777b2517cc99c8055ed735452f2659cd45e451507c76f48ce5c1d00e2", size = 44194 }, + { url = "https://files.pythonhosted.org/packages/d0/cc/0a838ba5ca64dc832aa43f727bd586309846b0ffb2ce52422543e6075e8a/typer-0.15.1-py3-none-any.whl", hash = "sha256:7994fb7b8155b64d3402518560648446072864beefd44aa2dc36972a5972e847", size = 44908 }, ] [[package]] @@ -7939,20 +7948,20 @@ wheels = [ [[package]] name = "types-google-cloud-ndb" -version = "2.3.0.20240813" +version = "2.3.0.20241103" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/9f/48/37fb4586c437768b55385fed2bcd696d742c7a37c8728ae644fbac2d3363/types-google-cloud-ndb-2.3.0.20240813.tar.gz", hash = "sha256:f69b4f1abc4a2c423b288ffc48d2994b59358bfc151824614abc1d3f7f19f18d", size = 14673 } +sdist = { url = "https://files.pythonhosted.org/packages/dc/72/2f5c1bc4ebeb1bd9c5e9242384207f647c7ccff5403f3f954f3a443639e9/types-google-cloud-ndb-2.3.0.20241103.tar.gz", hash = "sha256:9be12236e2a4e2dc6990b08c757d08a301d432301701f0136cc88445e93540ee", size = 14803 } wheels = [ - { url = "https://files.pythonhosted.org/packages/83/3f/c794e4a6500ea79d1866868c4801319f843503a31b1dc34deace81ad3b7c/types_google_cloud_ndb-2.3.0.20240813-py3-none-any.whl", hash = "sha256:79404e04e97324d0b6466f297e92e734a38fb9cd064c2f3816820311bc6c3f57", size = 18010 }, + { url = "https://files.pythonhosted.org/packages/71/88/6fed5132683e3e39bf4e33c4108765a915e3c3c90d32c7fbbe487cf20922/types_google_cloud_ndb-2.3.0.20241103-py3-none-any.whl", hash = "sha256:bd957c5f363b74ce994e5409db3cdcf15bb37857e1d0a4a8b40af5e8a4331d2b", size = 18049 }, ] [[package]] name = "types-markdown" -version = "3.7.0.20240822" +version = "3.7.0.20241204" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/37/5d/2ac1b166d6f251d67c3e5d4b6095e122bafea0e184d54122aa13efc2dd27/types-Markdown-3.7.0.20240822.tar.gz", hash = "sha256:183557c9f4f865bdefd8f5f96a38145c31819271cde111d35557c3bd2069e78d", size = 13187 } +sdist = { url = "https://files.pythonhosted.org/packages/d4/3c/874ac6ce93f4e6bd0283a5df2c8065f4e623c6c3bc0b2fb98c098313cb73/types_markdown-3.7.0.20241204.tar.gz", hash = "sha256:ecca2b25cd23163fd28ed5ba34d183d731da03e8a5ed3a20b60daded304c5410", size = 17820 } wheels = [ - { url = "https://files.pythonhosted.org/packages/49/25/381b2e70da6f14084b64578a1f251b50f1ccd3197a3353389b5b6189b4db/types_Markdown-3.7.0.20240822-py3-none-any.whl", hash = "sha256:bec91c410aaf2470ffdb103e38438fbcc53689b00133f19e64869eb138432ad7", size = 18976 }, + { url = "https://files.pythonhosted.org/packages/04/26/3c9730e845cfd0d587e0dfa9c1975f02f9f49407afbf30800094bdac0286/types_Markdown-3.7.0.20241204-py3-none-any.whl", hash = "sha256:f96146c367ea9c82bfe9903559d72706555cc2a1a3474c58ebba03b418ab18da", size = 23572 }, ] [[package]] @@ -8018,11 +8027,11 @@ wheels = [ [[package]] name = "types-pywin32" -version = "307.0.0.20241009" +version = "308.0.0.20241128" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/ec/19/4e10c9f54370ab7af95c91dbe58cc95c25a4e1006b0be4a692e3ec5bcadb/types-pywin32-307.0.0.20241009.tar.gz", hash = "sha256:d8d95e82d2b24814b8654bc296d3b1db53f59ad132e0199946954ec6ed8e7cf1", size = 254563 } +sdist = { url = "https://files.pythonhosted.org/packages/d4/17/21a3703775b56dbf07a704f29b1881e350e15d544490cfa35e9c9cae5084/types_pywin32-308.0.0.20241128.tar.gz", hash = "sha256:c52a3161df3fbee7961c940cdc6dc3c706f54e21955a22b2ef1714bfea66702a", size = 260017 } wheels = [ - { url = "https://files.pythonhosted.org/packages/06/82/d5ed32c225570b68559116b88cf1b54c96cf4b2648aec288dd848a0b86f3/types_pywin32-307.0.0.20241009-py3-none-any.whl", hash = "sha256:3a09e17bafd0fce742d7ff2391463c16def297956929e797370df8ce9859cf83", size = 316925 }, + { url = "https://files.pythonhosted.org/packages/26/d3/4b1d6c4e928c8d04a2f1e1cf51ed037d41966a7b95efba453cde81895c18/types_pywin32-308.0.0.20241128-py3-none-any.whl", hash = "sha256:1e9fb02efc73177c2e2550116c847d0862bb6231f2c61e34e5362c7572eb248d", size = 322922 }, ] [[package]] @@ -8049,23 +8058,23 @@ wheels = [ [[package]] name = "types-requests" -version = "2.32.0.20240914" +version = "2.32.0.20241016" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "urllib3" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/9b/9e/aea33405c230cc3984c9f1065012d3a2003cef910730c367a0e91e7a4901/types-requests-2.32.0.20240914.tar.gz", hash = "sha256:2850e178db3919d9bf809e434eef65ba49d0e7e33ac92d588f4a5e295fffd405", size = 18030 } +sdist = { url = "https://files.pythonhosted.org/packages/fa/3c/4f2a430c01a22abd49a583b6b944173e39e7d01b688190a5618bd59a2e22/types-requests-2.32.0.20241016.tar.gz", hash = "sha256:0d9cad2f27515d0e3e3da7134a1b6f28fb97129d86b867f24d9c726452634d95", size = 18065 } wheels = [ - { url = "https://files.pythonhosted.org/packages/8f/55/ea44dad71b9d92f86198f7448f5ba46ac919355f4f69bb1c0fa1af02b1b4/types_requests-2.32.0.20240914-py3-none-any.whl", hash = "sha256:59c2f673eb55f32a99b2894faf6020e1a9f4a402ad0f192bfee0b64469054310", size = 15838 }, + { url = "https://files.pythonhosted.org/packages/d7/01/485b3026ff90e5190b5e24f1711522e06c79f4a56c8f4b95848ac072e20f/types_requests-2.32.0.20241016-py3-none-any.whl", hash = "sha256:4195d62d6d3e043a4eaaf08ff8a62184584d2e8684e9d2aa178c7915a7da3747", size = 15836 }, ] [[package]] name = "types-setuptools" -version = "75.1.0.20240917" +version = "75.6.0.20241126" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/48/91/c1168caa2a5ba14c01b146b516fab2d8646887cb5db7e78e13b9c6da88d2/types-setuptools-75.1.0.20240917.tar.gz", hash = "sha256:12f12a165e7ed383f31def705e5c0fa1c26215dd466b0af34bd042f7d5331f55", size = 42585 } +sdist = { url = "https://files.pythonhosted.org/packages/c2/d2/15ede73bc3faf647af2c7bfefa90dde563a4b6bb580b1199f6255463c272/types_setuptools-75.6.0.20241126.tar.gz", hash = "sha256:7bf25ad4be39740e469f9268b6beddda6e088891fa5a27e985c6ce68bf62ace0", size = 48569 } wheels = [ - { url = "https://files.pythonhosted.org/packages/40/4c/a4c87d86ba18ff00773ab8591c79c23a6938293ab3e2cec2b2eb4ca5b644/types_setuptools-75.1.0.20240917-py3-none-any.whl", hash = "sha256:06f78307e68d1bbde6938072c57b81cf8a99bc84bd6dc7e4c5014730b097dc0c", size = 65516 }, + { url = "https://files.pythonhosted.org/packages/3b/a0/898a1363592d372d4103b76b7c723d84fcbde5fa4ed0c3a29102805ed7db/types_setuptools-75.6.0.20241126-py3-none-any.whl", hash = "sha256:aaae310a0e27033c1da8457d4d26ac673b0c8a0de7272d6d4708e263f2ea3b9b", size = 72732 }, ] [[package]] @@ -8233,41 +8242,40 @@ wheels = [ [[package]] name = "uv" -version = "0.4.25" +version = "0.5.8" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/d0/bc/1a013408b7f9f437385705652f404b6b15127ecf108327d13be493bdfb81/uv-0.4.25.tar.gz", hash = "sha256:d39077cdfe3246885fcdf32e7066ae731a166101d063629f9cea08738f79e6a3", size = 2064863 } +sdist = { url = "https://files.pythonhosted.org/packages/14/31/24c4d8d0d15f5a596fefb39a45e5628e2a4ac4b9c0a6044b4710d118673a/uv-0.5.8.tar.gz", hash = "sha256:2ee40bc9c08fea0e71092838c0fc36df83f741807d8be9acf2fd4c4757b3171e", size = 2494559 } wheels = [ - { url = "https://files.pythonhosted.org/packages/84/18/9c9056d373620b1cf5182ce9b2d258e86d117d667cf8883e12870f2a5edf/uv-0.4.25-py3-none-linux_armv6l.whl", hash = "sha256:94fb2b454afa6bdfeeea4b4581c878944ca9cf3a13712e6762f245f5fbaaf952", size = 13028246 }, - { url = "https://files.pythonhosted.org/packages/a1/19/8a3f09aba30ac5433dfecde55d5241a07c96bb12340c3b810bc58188a12e/uv-0.4.25-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:a7c3a18c20ddb527d296d1222bddf42b78031c50b5b4609d426569b5fb61f5b0", size = 13175265 }, - { url = "https://files.pythonhosted.org/packages/e8/c9/2f924bb29bd53c51b839c1c6126bd2cf4c451d4a7d8f34be078f9e31c57e/uv-0.4.25-py3-none-macosx_11_0_arm64.whl", hash = "sha256:18100f0f36419a154306ed6211e3490bf18384cdf3f1a0950848bf64b62fa251", size = 12255610 }, - { url = "https://files.pythonhosted.org/packages/b2/5a/d8f8971aeb3389679505cf633a786cd72a96ce232f80f14cfe5a693b4c64/uv-0.4.25-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.musllinux_1_1_aarch64.whl", hash = "sha256:6e981b1465e30102e41946adede9cb08051a5d70c6daf09f91a7ea84f0b75c08", size = 12506511 }, - { url = "https://files.pythonhosted.org/packages/e3/96/8c73520daeba5022cec8749e44afd4ca9ef774bf728af9c258bddec3577f/uv-0.4.25-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:578ae385fad6bd6f3868828e33d54994c716b315b1bc49106ec1f54c640837e4", size = 12836250 }, - { url = "https://files.pythonhosted.org/packages/67/3d/b0e810d365fb154fe1d380a0f43ee35a683cf9162f2501396d711bec2621/uv-0.4.25-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2d29a78f011ecc2f31c13605acb6574c2894c06d258b0f8d0dbb899986800450", size = 13521303 }, - { url = "https://files.pythonhosted.org/packages/2d/f4/dd3830ec7fc6e7e5237c184f30f2dbfed4f93605e472147eca1373bcc72b/uv-0.4.25-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:ec181be2bda10651a3558156409ac481549983e0276d0e3645e3b1464e7f8715", size = 14105308 }, - { url = "https://files.pythonhosted.org/packages/f4/4e/0fca02f8681e4870beda172552e747e0424f6e9186546b00a5e92525fea9/uv-0.4.25-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:50c7d0d9e7f392f81b13bf3b7e37768d1486f2fc9d533a54982aa0ed11e4db23", size = 13859475 }, - { url = "https://files.pythonhosted.org/packages/33/07/1100e9bc652f2850930f466869515d16ffe9582aaaaa99bac332ebdfe3ea/uv-0.4.25-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2fc35b5273f1e018aecd66b70e0fd7d2eb6698853dde3e2fc644e7ebf9f825b1", size = 18100840 }, - { url = "https://files.pythonhosted.org/packages/fa/98/ba1cb7dd2aa639a064a9e49721e08f12a3424456d60dde1327e7c6437930/uv-0.4.25-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a7022a71ff63a3838796f40e954b76bf7820fc27e96fe002c537e75ff8e34f1d", size = 13645464 }, - { url = "https://files.pythonhosted.org/packages/0d/05/b97fb8c828a070e8291826922b2712d1146b11563b4860bc9ba80f5635d1/uv-0.4.25-py3-none-manylinux_2_28_aarch64.whl", hash = "sha256:e02afb0f6d4b58718347f7d7cfa5a801e985ce42181ba971ed85ef149f6658ca", size = 12694995 }, - { url = "https://files.pythonhosted.org/packages/b3/97/63df050811379130202898f60e735a1a331ba3a93b8aa1e9bb466f533913/uv-0.4.25-py3-none-musllinux_1_1_armv7l.whl", hash = "sha256:3d7680795ea78cdbabbcce73d039b2651cf1fa635ddc1aa3082660f6d6255c50", size = 12831737 }, - { url = "https://files.pythonhosted.org/packages/dc/e0/08352dcffa6e8435328861ea60b2c05e8bd030f1e93998443ba66209db7b/uv-0.4.25-py3-none-musllinux_1_1_i686.whl", hash = "sha256:aae9dcafd20d5ba978c8a4939ab942e8e2e155c109e9945207fbbd81d2892c9e", size = 13273529 }, - { url = "https://files.pythonhosted.org/packages/25/f4/eaf95e5eee4e2e69884df0953d094deae07216f72068ef1df08c0f49841d/uv-0.4.25-py3-none-musllinux_1_1_ppc64le.whl", hash = "sha256:4c55040e67470f2b73e95e432aba06f103a0b348ea0b9c6689b1029c8d9e89fd", size = 15039860 }, - { url = "https://files.pythonhosted.org/packages/69/04/482b1cc9e8d599c7d766c4ba2d7a512ed3989921443792f92f26b8d44fe6/uv-0.4.25-py3-none-musllinux_1_1_x86_64.whl", hash = "sha256:bdbfd0c476b9e80a3f89af96aed6dd7d2782646311317a9c72614ccce99bb2ad", size = 13776302 }, - { url = "https://files.pythonhosted.org/packages/cd/7e/3d1cb735cc3df6341ac884b73eeec1f51a29192721be40be8e9b1d82666d/uv-0.4.25-py3-none-win32.whl", hash = "sha256:7d266e02fefef930609328c31c075084295c3cb472bab3f69549fad4fd9d82b3", size = 12970553 }, - { url = "https://files.pythonhosted.org/packages/04/e9/c00d2bb4a286b13fad0f06488ea9cbe9e76d0efcd81e7a907f72195d5b83/uv-0.4.25-py3-none-win_amd64.whl", hash = "sha256:be2a4fc4fcade9ea5e67e51738c95644360d6e59b6394b74fc579fb617f902f7", size = 14702875 }, + { url = "https://files.pythonhosted.org/packages/da/46/7a1310877b6ae012461c0bcc72629ee34a7c78749235ebf67d7856f24a91/uv-0.5.8-py3-none-linux_armv6l.whl", hash = "sha256:defd5da3685f43f74698634ffc197aaf9b836b8ba0de0e57b34d7bc74d856fa9", size = 14287864 }, + { url = "https://files.pythonhosted.org/packages/0f/b5/d02c8ce6bf46d648e9ef912308718a30ecff631904ba03acd11e5ec6412d/uv-0.5.8-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:e146062e4cc39db334cbde38d56d2c6301dd9cf6739ce07ce5a4d71b4cbc2d00", size = 14290268 }, + { url = "https://files.pythonhosted.org/packages/fb/5e/7277f92ee0aa8549e41152d9a0a7863d84e7b7b8de9b08cb397bfe1e37f6/uv-0.5.8-py3-none-macosx_11_0_arm64.whl", hash = "sha256:0f2bcdd00a49ad1669e217a2787448cac1653c9968d74bfa3732f3c25ca26f69", size = 13255149 }, + { url = "https://files.pythonhosted.org/packages/08/5b/72be4ba38e8e6cd2be60e97fd799629228afd3f46404767b0e1cfcf1236e/uv-0.5.8-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.musllinux_1_1_aarch64.whl", hash = "sha256:c91d0a2b8218af2aa0385b867da8c13a620db22077686793c7231f012cb40619", size = 13541600 }, + { url = "https://files.pythonhosted.org/packages/4d/cb/92485fea5f3fffb0f93820fe808b56ceeef1020ae234f8e2ba64f091ed4e/uv-0.5.8-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:8058ab06d2f69355694f6e9a36edc45164474c516b4e2895bd67f8232d9022ed", size = 14090419 }, + { url = "https://files.pythonhosted.org/packages/ac/b0/09a3a3d93299728485121b975a84b893aebdb6b712f65f43491bba7f82d0/uv-0.5.8-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c56022edc0f61febbdef89e6f699a0e991932c493b7293635b4814e102d040d2", size = 14638200 }, + { url = "https://files.pythonhosted.org/packages/3c/52/1082d3ca50d336035b5ef6c54caa4936aa2a6ad050ea61fca3068dd986b3/uv-0.5.8-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:84f26ce1736d075d1df34f7c3f6b0b728cecd9a4da3e5160d5d887587830e7ce", size = 15336063 }, + { url = "https://files.pythonhosted.org/packages/06/b5/d9d9a95646ca2404da11fa8f1e9953827ad793d8b92b65bb870f4c0de541/uv-0.5.8-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a7956787658fb9253fba49741886409402a48039bee64b1697397d27284919af", size = 15068797 }, + { url = "https://files.pythonhosted.org/packages/96/18/f92f7bf7b8769f8010ae4a9b545a0a183a806133174f65c46996e23c8268/uv-0.5.8-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5989bbbbca072edc1875036c76aed74ec3dfc4741de7d1f060e181717efea6ac", size = 19540106 }, + { url = "https://files.pythonhosted.org/packages/a4/d8/757959dc58abfbf09afe024fbcf1ffb639b8537ea830d09a99d0300ee53c/uv-0.5.8-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2b3076c79746d4f83257c9dea5ba0833b0711aeff8e6695670eadd140a0cf67f", size = 14760582 }, + { url = "https://files.pythonhosted.org/packages/be/20/8b97777fbe6b983a845237c3132e4b540b9dcde73c2bc7c7c6f96ff46f29/uv-0.5.8-py3-none-manylinux_2_28_aarch64.whl", hash = "sha256:aa03c338e19456d3a6544a94293bd2905837ae22720cc161c83ea0fd13c3b09f", size = 13738416 }, + { url = "https://files.pythonhosted.org/packages/b4/fe/fd462516eeb6d58acf5736ea4e7b1b397454344d99c9a0c279bb96436c7b/uv-0.5.8-py3-none-musllinux_1_1_armv7l.whl", hash = "sha256:8a8cbe1ffa0ef5c2f1c90622e07211a8f93f48daa2be1bd4592bb8cda52b0285", size = 14044658 }, + { url = "https://files.pythonhosted.org/packages/be/d0/215c4fcd68e02f39c50557829365e75e60de2c246884753f1382bd75513e/uv-0.5.8-py3-none-musllinux_1_1_i686.whl", hash = "sha256:365eb6bbb551c5623a73b1ed530f4e69083016f70f0cf5ca1a30ec66413bcda2", size = 14359764 }, + { url = "https://files.pythonhosted.org/packages/41/3e/3d96e9c41cee4acf16aee39f4cae81f5651754ac6ca383be2031efc90eeb/uv-0.5.8-py3-none-musllinux_1_1_x86_64.whl", hash = "sha256:56715389d240ac989af2188cd3bfc2b603d31b42330e915dacfe113b34d8e65b", size = 14943042 }, + { url = "https://files.pythonhosted.org/packages/51/3e/3826d2e7c653649eec649262d5548b7ed6bdb5af7bed2a8bb5a127ac67bd/uv-0.5.8-py3-none-win32.whl", hash = "sha256:f8ade0430b6618ae0e21e52f61f6f3943dd6f3184ef6dc4491087b27940427f9", size = 14201492 }, + { url = "https://files.pythonhosted.org/packages/2f/d3/8ab1383ceccbc9f31bb9a265f90dfda4f6214229768ea9608df8a8c66e15/uv-0.5.8-py3-none-win_amd64.whl", hash = "sha256:4a3325af8ed1effa7076967472c063b0000d609fd6f561c7751e43bab30297f1", size = 15995992 }, ] [[package]] name = "uvicorn" -version = "0.31.1" +version = "0.32.1" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "click" }, { name = "h11" }, { name = "typing-extensions", marker = "python_full_version < '3.11'" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/76/87/a886eda9ed495a3a4506d5a125cd07c54524280718c4969bde88f075fe98/uvicorn-0.31.1.tar.gz", hash = "sha256:f5167919867b161b7bcaf32646c6a94cdbd4c3aa2eb5c17d36bb9aa5cfd8c493", size = 77368 } +sdist = { url = "https://files.pythonhosted.org/packages/6a/3c/21dba3e7d76138725ef307e3d7ddd29b763119b3aa459d02cc05fefcff75/uvicorn-0.32.1.tar.gz", hash = "sha256:ee9519c246a72b1c084cea8d3b44ed6026e78a4a309cbedae9c37e4cb9fbb175", size = 77630 } wheels = [ - { url = "https://files.pythonhosted.org/packages/3c/55/37407280931038a3f21fa0245d60edeaa76f18419581aa3f4397761c78df/uvicorn-0.31.1-py3-none-any.whl", hash = "sha256:adc42d9cac80cf3e51af97c1851648066841e7cfb6993a4ca8de29ac1548ed41", size = 63666 }, + { url = "https://files.pythonhosted.org/packages/50/c1/2d27b0a15826c2b71dcf6e2f5402181ef85acf439617bb2f1453125ce1f3/uvicorn-0.32.1-py3-none-any.whl", hash = "sha256:82ad92fd58da0d12af7482ecdb5f2470a04c9c9a53ced65b9bbb4a205377602e", size = 63828 }, ] [package.optional-dependencies] @@ -8283,28 +8291,28 @@ standard = [ [[package]] name = "uvloop" -version = "0.20.0" +version = "0.21.0" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/bc/f1/dc9577455e011ad43d9379e836ee73f40b4f99c02946849a44f7ae64835e/uvloop-0.20.0.tar.gz", hash = "sha256:4603ca714a754fc8d9b197e325db25b2ea045385e8a3ad05d3463de725fdf469", size = 2329938 } +sdist = { url = "https://files.pythonhosted.org/packages/af/c0/854216d09d33c543f12a44b393c402e89a920b1a0a7dc634c42de91b9cf6/uvloop-0.21.0.tar.gz", hash = "sha256:3bf12b0fda68447806a7ad847bfa591613177275d35b6724b1ee573faa3704e3", size = 2492741 } wheels = [ - { url = "https://files.pythonhosted.org/packages/f3/69/cc1ad125ea8ce4a4d3ba7d9836062c3fc9063cf163ddf0f168e73f3268e3/uvloop-0.20.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:9ebafa0b96c62881d5cafa02d9da2e44c23f9f0cd829f3a32a6aff771449c996", size = 1363922 }, - { url = "https://files.pythonhosted.org/packages/f7/45/5a3f7a32372e4a90dfd83f30507183ec38990b8c5930ed7e36c6a15af47b/uvloop-0.20.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:35968fc697b0527a06e134999eef859b4034b37aebca537daeb598b9d45a137b", size = 760386 }, - { url = "https://files.pythonhosted.org/packages/9e/a5/9e973b25ade12c938940751bce71d0cb36efee3489014471f7d9c0a3c379/uvloop-0.20.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b16696f10e59d7580979b420eedf6650010a4a9c3bd8113f24a103dfdb770b10", size = 3432586 }, - { url = "https://files.pythonhosted.org/packages/a9/e0/0bec8a25b2e9cf14fdfcf0229637b437c923b4e5ca22f8e988363c49bb51/uvloop-0.20.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9b04d96188d365151d1af41fa2d23257b674e7ead68cfd61c725a422764062ae", size = 3431802 }, - { url = "https://files.pythonhosted.org/packages/95/3b/14cef46dcec6237d858666a4a1fdb171361528c70fcd930bfc312920e7a9/uvloop-0.20.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:94707205efbe809dfa3a0d09c08bef1352f5d3d6612a506f10a319933757c006", size = 4144444 }, - { url = "https://files.pythonhosted.org/packages/9d/5a/0ac516562ff783f760cab3b061f10fdeb4a9f985ad4b44e7e4564ff11691/uvloop-0.20.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:89e8d33bb88d7263f74dc57d69f0063e06b5a5ce50bb9a6b32f5fcbe655f9e73", size = 4147039 }, - { url = "https://files.pythonhosted.org/packages/64/bf/45828beccf685b7ed9638d9b77ef382b470c6ca3b5bff78067e02ffd5663/uvloop-0.20.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:e50289c101495e0d1bb0bfcb4a60adde56e32f4449a67216a1ab2750aa84f037", size = 1320593 }, - { url = "https://files.pythonhosted.org/packages/27/c0/3c24e50bee7802a2add96ca9f0d5eb0ebab07e0a5615539d38aeb89499b9/uvloop-0.20.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:e237f9c1e8a00e7d9ddaa288e535dc337a39bcbf679f290aee9d26df9e72bce9", size = 736676 }, - { url = "https://files.pythonhosted.org/packages/83/ce/ffa3c72954eae36825acfafd2b6a9221d79abd2670c0d25e04d6ef4a2007/uvloop-0.20.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:746242cd703dc2b37f9d8b9f173749c15e9a918ddb021575a0205ec29a38d31e", size = 3494573 }, - { url = "https://files.pythonhosted.org/packages/46/6d/4caab3a36199ba52b98d519feccfcf48921d7a6649daf14a93c7e77497e9/uvloop-0.20.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:82edbfd3df39fb3d108fc079ebc461330f7c2e33dbd002d146bf7c445ba6e756", size = 3489932 }, - { url = "https://files.pythonhosted.org/packages/e4/4f/49c51595bd794945c88613df88922c38076eae2d7653f4624aa6f4980b07/uvloop-0.20.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:80dc1b139516be2077b3e57ce1cb65bfed09149e1d175e0478e7a987863b68f0", size = 4185596 }, - { url = "https://files.pythonhosted.org/packages/b8/94/7e256731260d313f5049717d1c4582d52a3b132424c95e16954a50ab95d3/uvloop-0.20.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:4f44af67bf39af25db4c1ac27e82e9665717f9c26af2369c404be865c8818dcf", size = 4185746 }, - { url = "https://files.pythonhosted.org/packages/2d/64/31cbd379d6e260ac8de3f672f904e924f09715c3f192b09f26cc8e9f574c/uvloop-0.20.0-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:4b75f2950ddb6feed85336412b9a0c310a2edbcf4cf931aa5cfe29034829676d", size = 1324302 }, - { url = "https://files.pythonhosted.org/packages/1e/6b/9207e7177ff30f78299401f2e1163ea41130d4fd29bcdc6d12572c06b728/uvloop-0.20.0-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:77fbc69c287596880ecec2d4c7a62346bef08b6209749bf6ce8c22bbaca0239e", size = 738105 }, - { url = "https://files.pythonhosted.org/packages/c1/ba/b64b10f577519d875992dc07e2365899a1a4c0d28327059ce1e1bdfb6854/uvloop-0.20.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6462c95f48e2d8d4c993a2950cd3d31ab061864d1c226bbf0ee2f1a8f36674b9", size = 4090658 }, - { url = "https://files.pythonhosted.org/packages/0a/f8/5ceea6876154d926604f10c1dd896adf9bce6d55a55911364337b8a5ed8d/uvloop-0.20.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:649c33034979273fa71aa25d0fe120ad1777c551d8c4cd2c0c9851d88fcb13ab", size = 4173357 }, - { url = "https://files.pythonhosted.org/packages/18/b2/117ab6bfb18274753fbc319607bf06e216bd7eea8be81d5bac22c912d6a7/uvloop-0.20.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:3a609780e942d43a275a617c0839d85f95c334bad29c4c0918252085113285b5", size = 4029868 }, - { url = "https://files.pythonhosted.org/packages/6f/52/deb4be09060637ef4752adaa0b75bf770c20c823e8108705792f99cd4a6f/uvloop-0.20.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:aea15c78e0d9ad6555ed201344ae36db5c63d428818b4b2a42842b3870127c00", size = 4115980 }, + { url = "https://files.pythonhosted.org/packages/3d/76/44a55515e8c9505aa1420aebacf4dd82552e5e15691654894e90d0bd051a/uvloop-0.21.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:ec7e6b09a6fdded42403182ab6b832b71f4edaf7f37a9a0e371a01db5f0cb45f", size = 1442019 }, + { url = "https://files.pythonhosted.org/packages/35/5a/62d5800358a78cc25c8a6c72ef8b10851bdb8cca22e14d9c74167b7f86da/uvloop-0.21.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:196274f2adb9689a289ad7d65700d37df0c0930fd8e4e743fa4834e850d7719d", size = 801898 }, + { url = "https://files.pythonhosted.org/packages/f3/96/63695e0ebd7da6c741ccd4489b5947394435e198a1382349c17b1146bb97/uvloop-0.21.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f38b2e090258d051d68a5b14d1da7203a3c3677321cf32a95a6f4db4dd8b6f26", size = 3827735 }, + { url = "https://files.pythonhosted.org/packages/61/e0/f0f8ec84979068ffae132c58c79af1de9cceeb664076beea86d941af1a30/uvloop-0.21.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:87c43e0f13022b998eb9b973b5e97200c8b90823454d4bc06ab33829e09fb9bb", size = 3825126 }, + { url = "https://files.pythonhosted.org/packages/bf/fe/5e94a977d058a54a19df95f12f7161ab6e323ad49f4dabc28822eb2df7ea/uvloop-0.21.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:10d66943def5fcb6e7b37310eb6b5639fd2ccbc38df1177262b0640c3ca68c1f", size = 3705789 }, + { url = "https://files.pythonhosted.org/packages/26/dd/c7179618e46092a77e036650c1f056041a028a35c4d76945089fcfc38af8/uvloop-0.21.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:67dd654b8ca23aed0a8e99010b4c34aca62f4b7fce88f39d452ed7622c94845c", size = 3800523 }, + { url = "https://files.pythonhosted.org/packages/57/a7/4cf0334105c1160dd6819f3297f8700fda7fc30ab4f61fbf3e725acbc7cc/uvloop-0.21.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:c0f3fa6200b3108919f8bdabb9a7f87f20e7097ea3c543754cabc7d717d95cf8", size = 1447410 }, + { url = "https://files.pythonhosted.org/packages/8c/7c/1517b0bbc2dbe784b563d6ab54f2ef88c890fdad77232c98ed490aa07132/uvloop-0.21.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:0878c2640cf341b269b7e128b1a5fed890adc4455513ca710d77d5e93aa6d6a0", size = 805476 }, + { url = "https://files.pythonhosted.org/packages/ee/ea/0bfae1aceb82a503f358d8d2fa126ca9dbdb2ba9c7866974faec1cb5875c/uvloop-0.21.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b9fb766bb57b7388745d8bcc53a359b116b8a04c83a2288069809d2b3466c37e", size = 3960855 }, + { url = "https://files.pythonhosted.org/packages/8a/ca/0864176a649838b838f36d44bf31c451597ab363b60dc9e09c9630619d41/uvloop-0.21.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8a375441696e2eda1c43c44ccb66e04d61ceeffcd76e4929e527b7fa401b90fb", size = 3973185 }, + { url = "https://files.pythonhosted.org/packages/30/bf/08ad29979a936d63787ba47a540de2132169f140d54aa25bc8c3df3e67f4/uvloop-0.21.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:baa0e6291d91649c6ba4ed4b2f982f9fa165b5bbd50a9e203c416a2797bab3c6", size = 3820256 }, + { url = "https://files.pythonhosted.org/packages/da/e2/5cf6ef37e3daf2f06e651aae5ea108ad30df3cb269102678b61ebf1fdf42/uvloop-0.21.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:4509360fcc4c3bd2c70d87573ad472de40c13387f5fda8cb58350a1d7475e58d", size = 3937323 }, + { url = "https://files.pythonhosted.org/packages/8c/4c/03f93178830dc7ce8b4cdee1d36770d2f5ebb6f3d37d354e061eefc73545/uvloop-0.21.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:359ec2c888397b9e592a889c4d72ba3d6befba8b2bb01743f72fffbde663b59c", size = 1471284 }, + { url = "https://files.pythonhosted.org/packages/43/3e/92c03f4d05e50f09251bd8b2b2b584a2a7f8fe600008bcc4523337abe676/uvloop-0.21.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:f7089d2dc73179ce5ac255bdf37c236a9f914b264825fdaacaded6990a7fb4c2", size = 821349 }, + { url = "https://files.pythonhosted.org/packages/a6/ef/a02ec5da49909dbbfb1fd205a9a1ac4e88ea92dcae885e7c961847cd51e2/uvloop-0.21.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:baa4dcdbd9ae0a372f2167a207cd98c9f9a1ea1188a8a526431eef2f8116cc8d", size = 4580089 }, + { url = "https://files.pythonhosted.org/packages/06/a7/b4e6a19925c900be9f98bec0a75e6e8f79bb53bdeb891916609ab3958967/uvloop-0.21.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:86975dca1c773a2c9864f4c52c5a55631038e387b47eaf56210f873887b6c8dc", size = 4693770 }, + { url = "https://files.pythonhosted.org/packages/ce/0c/f07435a18a4b94ce6bd0677d8319cd3de61f3a9eeb1e5f8ab4e8b5edfcb3/uvloop-0.21.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:461d9ae6660fbbafedd07559c6a2e57cd553b34b0065b6550685f6653a98c1cb", size = 4451321 }, + { url = "https://files.pythonhosted.org/packages/8f/eb/f7032be105877bcf924709c97b1bf3b90255b4ec251f9340cef912559f28/uvloop-0.21.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:183aef7c8730e54c9a3ee3227464daed66e37ba13040bb3f350bc2ddc040f22f", size = 4659022 }, ] [[package]] @@ -8327,81 +8335,81 @@ wheels = [ [[package]] name = "virtualenv" -version = "20.26.6" +version = "20.28.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "distlib" }, { name = "filelock" }, { name = "platformdirs" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/3f/40/abc5a766da6b0b2457f819feab8e9203cbeae29327bd241359f866a3da9d/virtualenv-20.26.6.tar.gz", hash = "sha256:280aede09a2a5c317e409a00102e7077c6432c5a38f0ef938e643805a7ad2c48", size = 9372482 } +sdist = { url = "https://files.pythonhosted.org/packages/bf/75/53316a5a8050069228a2f6d11f32046cfa94fbb6cc3f08703f59b873de2e/virtualenv-20.28.0.tar.gz", hash = "sha256:2c9c3262bb8e7b87ea801d715fae4495e6032450c71d2309be9550e7364049aa", size = 7650368 } wheels = [ - { url = "https://files.pythonhosted.org/packages/59/90/57b8ac0c8a231545adc7698c64c5a36fa7cd8e376c691b9bde877269f2eb/virtualenv-20.26.6-py3-none-any.whl", hash = "sha256:7345cc5b25405607a624d8418154577459c3e0277f5466dd79c49d5e492995f2", size = 5999862 }, + { url = "https://files.pythonhosted.org/packages/10/f9/0919cf6f1432a8c4baa62511f8f8da8225432d22e83e3476f5be1a1edc6e/virtualenv-20.28.0-py3-none-any.whl", hash = "sha256:23eae1b4516ecd610481eda647f3a7c09aea295055337331bb4e6892ecce47b0", size = 4276702 }, ] [[package]] name = "vulture" -version = "2.13" +version = "2.14" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "tomli", marker = "python_full_version < '3.11'" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/1d/7d/e78586863119fe28741c347988f892301319ce05edd11dbe0b45b18cc3b9/vulture-2.13.tar.gz", hash = "sha256:78248bf58f5eaffcc2ade306141ead73f437339950f80045dce7f8b078e5a1aa", size = 57066 } +sdist = { url = "https://files.pythonhosted.org/packages/8e/25/925f35db758a0f9199113aaf61d703de891676b082bd7cf73ea01d6000f7/vulture-2.14.tar.gz", hash = "sha256:cb8277902a1138deeab796ec5bef7076a6e0248ca3607a3f3dee0b6d9e9b8415", size = 58823 } wheels = [ - { url = "https://files.pythonhosted.org/packages/fd/1b/bc096603b79edbac62899cbe852bd5ccdf0f8e8a7faa9f7390ee1995cedb/vulture-2.13-py2.py3-none-any.whl", hash = "sha256:34793ba60488e7cccbecdef3a7fe151656372ef94fdac9fe004c52a4000a6d44", size = 27714 }, + { url = "https://files.pythonhosted.org/packages/a0/56/0cc15b8ff2613c1d5c3dc1f3f576ede1c43868c1bc2e5ccaa2d4bcd7974d/vulture-2.14-py2.py3-none-any.whl", hash = "sha256:d9a90dba89607489548a49d557f8bac8112bd25d3cbc8aeef23e860811bd5ed9", size = 28915 }, ] [[package]] name = "watchfiles" -version = "0.24.0" +version = "1.0.3" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "anyio" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/c8/27/2ba23c8cc85796e2d41976439b08d52f691655fdb9401362099502d1f0cf/watchfiles-0.24.0.tar.gz", hash = "sha256:afb72325b74fa7a428c009c1b8be4b4d7c2afedafb2982827ef2156646df2fe1", size = 37870 } +sdist = { url = "https://files.pythonhosted.org/packages/3c/7e/4569184ea04b501840771b8fcecee19b2233a8b72c196061263c0ef23c0b/watchfiles-1.0.3.tar.gz", hash = "sha256:f3ff7da165c99a5412fe5dd2304dd2dbaaaa5da718aad942dcb3a178eaa70c56", size = 38185 } wheels = [ - { url = "https://files.pythonhosted.org/packages/89/a1/631c12626378b9f1538664aa221feb5c60dfafbd7f60b451f8d0bdbcdedd/watchfiles-0.24.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:083dc77dbdeef09fa44bb0f4d1df571d2e12d8a8f985dccde71ac3ac9ac067a0", size = 375096 }, - { url = "https://files.pythonhosted.org/packages/f7/5c/f27c979c8a10aaa2822286c1bffdce3db731cd1aa4224b9f86623e94bbfe/watchfiles-0.24.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e94e98c7cb94cfa6e071d401ea3342767f28eb5a06a58fafdc0d2a4974f4f35c", size = 367425 }, - { url = "https://files.pythonhosted.org/packages/74/0d/1889e5649885484d29f6c792ef274454d0a26b20d6ed5fdba5409335ccb6/watchfiles-0.24.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:82ae557a8c037c42a6ef26c494d0631cacca040934b101d001100ed93d43f361", size = 437705 }, - { url = "https://files.pythonhosted.org/packages/85/8a/01d9a22e839f0d1d547af11b1fcac6ba6f889513f1b2e6f221d9d60d9585/watchfiles-0.24.0-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:acbfa31e315a8f14fe33e3542cbcafc55703b8f5dcbb7c1eecd30f141df50db3", size = 433636 }, - { url = "https://files.pythonhosted.org/packages/62/32/a93db78d340c7ef86cde469deb20e36c6b2a873edee81f610e94bbba4e06/watchfiles-0.24.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b74fdffce9dfcf2dc296dec8743e5b0332d15df19ae464f0e249aa871fc1c571", size = 451069 }, - { url = "https://files.pythonhosted.org/packages/99/c2/e9e2754fae3c2721c9a7736f92dab73723f1968ed72535fff29e70776008/watchfiles-0.24.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:449f43f49c8ddca87c6b3980c9284cab6bd1f5c9d9a2b00012adaaccd5e7decd", size = 469306 }, - { url = "https://files.pythonhosted.org/packages/4c/45/f317d9e3affb06c3c27c478de99f7110143e87f0f001f0f72e18d0e1ddce/watchfiles-0.24.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4abf4ad269856618f82dee296ac66b0cd1d71450fc3c98532d93798e73399b7a", size = 476187 }, - { url = "https://files.pythonhosted.org/packages/ac/d3/f1f37248abe0114916921e638f71c7d21fe77e3f2f61750e8057d0b68ef2/watchfiles-0.24.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9f895d785eb6164678ff4bb5cc60c5996b3ee6df3edb28dcdeba86a13ea0465e", size = 425743 }, - { url = "https://files.pythonhosted.org/packages/2b/e8/c7037ea38d838fd81a59cd25761f106ee3ef2cfd3261787bee0c68908171/watchfiles-0.24.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:7ae3e208b31be8ce7f4c2c0034f33406dd24fbce3467f77223d10cd86778471c", size = 612327 }, - { url = "https://files.pythonhosted.org/packages/a0/c5/0e6e228aafe01a7995fbfd2a4edb221bb11a2744803b65a5663fb85e5063/watchfiles-0.24.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:2efec17819b0046dde35d13fb8ac7a3ad877af41ae4640f4109d9154ed30a188", size = 595096 }, - { url = "https://files.pythonhosted.org/packages/63/d5/4780e8bf3de3b4b46e7428a29654f7dc041cad6b19fd86d083e4b6f64bbe/watchfiles-0.24.0-cp310-none-win32.whl", hash = "sha256:6bdcfa3cd6fdbdd1a068a52820f46a815401cbc2cb187dd006cb076675e7b735", size = 264149 }, - { url = "https://files.pythonhosted.org/packages/fe/1b/5148898ba55fc9c111a2a4a5fb67ad3fa7eb2b3d7f0618241ed88749313d/watchfiles-0.24.0-cp310-none-win_amd64.whl", hash = "sha256:54ca90a9ae6597ae6dc00e7ed0a040ef723f84ec517d3e7ce13e63e4bc82fa04", size = 277542 }, - { url = "https://files.pythonhosted.org/packages/85/02/366ae902cd81ca5befcd1854b5c7477b378f68861597cef854bd6dc69fbe/watchfiles-0.24.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:bdcd5538e27f188dd3c804b4a8d5f52a7fc7f87e7fd6b374b8e36a4ca03db428", size = 375579 }, - { url = "https://files.pythonhosted.org/packages/bc/67/d8c9d256791fe312fea118a8a051411337c948101a24586e2df237507976/watchfiles-0.24.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:2dadf8a8014fde6addfd3c379e6ed1a981c8f0a48292d662e27cabfe4239c83c", size = 367726 }, - { url = "https://files.pythonhosted.org/packages/b1/dc/a8427b21ef46386adf824a9fec4be9d16a475b850616cfd98cf09a97a2ef/watchfiles-0.24.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6509ed3f467b79d95fc62a98229f79b1a60d1b93f101e1c61d10c95a46a84f43", size = 437735 }, - { url = "https://files.pythonhosted.org/packages/3a/21/0b20bef581a9fbfef290a822c8be645432ceb05fb0741bf3c032e0d90d9a/watchfiles-0.24.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:8360f7314a070c30e4c976b183d1d8d1585a4a50c5cb603f431cebcbb4f66327", size = 433644 }, - { url = "https://files.pythonhosted.org/packages/1c/e8/d5e5f71cc443c85a72e70b24269a30e529227986096abe091040d6358ea9/watchfiles-0.24.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:316449aefacf40147a9efaf3bd7c9bdd35aaba9ac5d708bd1eb5763c9a02bef5", size = 450928 }, - { url = "https://files.pythonhosted.org/packages/61/ee/bf17f5a370c2fcff49e1fec987a6a43fd798d8427ea754ce45b38f9e117a/watchfiles-0.24.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:73bde715f940bea845a95247ea3e5eb17769ba1010efdc938ffcb967c634fa61", size = 469072 }, - { url = "https://files.pythonhosted.org/packages/a3/34/03b66d425986de3fc6077e74a74c78da298f8cb598887f664a4485e55543/watchfiles-0.24.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3770e260b18e7f4e576edca4c0a639f704088602e0bc921c5c2e721e3acb8d15", size = 475517 }, - { url = "https://files.pythonhosted.org/packages/70/eb/82f089c4f44b3171ad87a1b433abb4696f18eb67292909630d886e073abe/watchfiles-0.24.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:aa0fd7248cf533c259e59dc593a60973a73e881162b1a2f73360547132742823", size = 425480 }, - { url = "https://files.pythonhosted.org/packages/53/20/20509c8f5291e14e8a13104b1808cd7cf5c44acd5feaecb427a49d387774/watchfiles-0.24.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:d7a2e3b7f5703ffbd500dabdefcbc9eafeff4b9444bbdd5d83d79eedf8428fab", size = 612322 }, - { url = "https://files.pythonhosted.org/packages/df/2b/5f65014a8cecc0a120f5587722068a975a692cadbe9fe4ea56b3d8e43f14/watchfiles-0.24.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d831ee0a50946d24a53821819b2327d5751b0c938b12c0653ea5be7dea9c82ec", size = 595094 }, - { url = "https://files.pythonhosted.org/packages/18/98/006d8043a82c0a09d282d669c88e587b3a05cabdd7f4900e402250a249ac/watchfiles-0.24.0-cp311-none-win32.whl", hash = "sha256:49d617df841a63b4445790a254013aea2120357ccacbed00253f9c2b5dc24e2d", size = 264191 }, - { url = "https://files.pythonhosted.org/packages/8a/8b/badd9247d6ec25f5f634a9b3d0d92e39c045824ec7e8afcedca8ee52c1e2/watchfiles-0.24.0-cp311-none-win_amd64.whl", hash = "sha256:d3dcb774e3568477275cc76554b5a565024b8ba3a0322f77c246bc7111c5bb9c", size = 277527 }, - { url = "https://files.pythonhosted.org/packages/af/19/35c957c84ee69d904299a38bae3614f7cede45f07f174f6d5a2f4dbd6033/watchfiles-0.24.0-cp311-none-win_arm64.whl", hash = "sha256:9301c689051a4857d5b10777da23fafb8e8e921bcf3abe6448a058d27fb67633", size = 266253 }, - { url = "https://files.pythonhosted.org/packages/35/82/92a7bb6dc82d183e304a5f84ae5437b59ee72d48cee805a9adda2488b237/watchfiles-0.24.0-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:7211b463695d1e995ca3feb38b69227e46dbd03947172585ecb0588f19b0d87a", size = 374137 }, - { url = "https://files.pythonhosted.org/packages/87/91/49e9a497ddaf4da5e3802d51ed67ff33024597c28f652b8ab1e7c0f5718b/watchfiles-0.24.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:4b8693502d1967b00f2fb82fc1e744df128ba22f530e15b763c8d82baee15370", size = 367733 }, - { url = "https://files.pythonhosted.org/packages/0d/d8/90eb950ab4998effea2df4cf3a705dc594f6bc501c5a353073aa990be965/watchfiles-0.24.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cdab9555053399318b953a1fe1f586e945bc8d635ce9d05e617fd9fe3a4687d6", size = 437322 }, - { url = "https://files.pythonhosted.org/packages/6c/a2/300b22e7bc2a222dd91fce121cefa7b49aa0d26a627b2777e7bdfcf1110b/watchfiles-0.24.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:34e19e56d68b0dad5cff62273107cf5d9fbaf9d75c46277aa5d803b3ef8a9e9b", size = 433409 }, - { url = "https://files.pythonhosted.org/packages/99/44/27d7708a43538ed6c26708bcccdde757da8b7efb93f4871d4cc39cffa1cc/watchfiles-0.24.0-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:41face41f036fee09eba33a5b53a73e9a43d5cb2c53dad8e61fa6c9f91b5a51e", size = 452142 }, - { url = "https://files.pythonhosted.org/packages/b0/ec/c4e04f755be003129a2c5f3520d2c47026f00da5ecb9ef1e4f9449637571/watchfiles-0.24.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5148c2f1ea043db13ce9b0c28456e18ecc8f14f41325aa624314095b6aa2e9ea", size = 469414 }, - { url = "https://files.pythonhosted.org/packages/c5/4e/cdd7de3e7ac6432b0abf282ec4c1a1a2ec62dfe423cf269b86861667752d/watchfiles-0.24.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7e4bd963a935aaf40b625c2499f3f4f6bbd0c3776f6d3bc7c853d04824ff1c9f", size = 472962 }, - { url = "https://files.pythonhosted.org/packages/27/69/e1da9d34da7fc59db358424f5d89a56aaafe09f6961b64e36457a80a7194/watchfiles-0.24.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c79d7719d027b7a42817c5d96461a99b6a49979c143839fc37aa5748c322f234", size = 425705 }, - { url = "https://files.pythonhosted.org/packages/e8/c1/24d0f7357be89be4a43e0a656259676ea3d7a074901f47022f32e2957798/watchfiles-0.24.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:32aa53a9a63b7f01ed32e316e354e81e9da0e6267435c7243bf8ae0f10b428ef", size = 612851 }, - { url = "https://files.pythonhosted.org/packages/c7/af/175ba9b268dec56f821639c9893b506c69fd999fe6a2e2c51de420eb2f01/watchfiles-0.24.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:ce72dba6a20e39a0c628258b5c308779b8697f7676c254a845715e2a1039b968", size = 594868 }, - { url = "https://files.pythonhosted.org/packages/44/81/1f701323a9f70805bc81c74c990137123344a80ea23ab9504a99492907f8/watchfiles-0.24.0-cp312-none-win32.whl", hash = "sha256:d9018153cf57fc302a2a34cb7564870b859ed9a732d16b41a9b5cb2ebed2d444", size = 264109 }, - { url = "https://files.pythonhosted.org/packages/b4/0b/32cde5bc2ebd9f351be326837c61bdeb05ad652b793f25c91cac0b48a60b/watchfiles-0.24.0-cp312-none-win_amd64.whl", hash = "sha256:551ec3ee2a3ac9cbcf48a4ec76e42c2ef938a7e905a35b42a1267fa4b1645896", size = 277055 }, - { url = "https://files.pythonhosted.org/packages/4b/81/daade76ce33d21dbec7a15afd7479de8db786e5f7b7d249263b4ea174e08/watchfiles-0.24.0-cp312-none-win_arm64.whl", hash = "sha256:b52a65e4ea43c6d149c5f8ddb0bef8d4a1e779b77591a458a893eb416624a418", size = 266169 }, - { url = "https://files.pythonhosted.org/packages/df/94/1ad200e937ec91b2a9d6b39ae1cf9c2b1a9cc88d5ceb43aa5c6962eb3c11/watchfiles-0.24.0-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:632676574429bee8c26be8af52af20e0c718cc7f5f67f3fb658c71928ccd4f7f", size = 376986 }, - { url = "https://files.pythonhosted.org/packages/ee/fd/d9e020d687ccf90fe95efc513fbb39a8049cf5a3ff51f53c59fcf4c47a5d/watchfiles-0.24.0-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:a2a9891723a735d3e2540651184be6fd5b96880c08ffe1a98bae5017e65b544b", size = 369445 }, - { url = "https://files.pythonhosted.org/packages/43/cb/c0279b35053555d10ef03559c5aebfcb0c703d9c70a7b4e532df74b9b0e8/watchfiles-0.24.0-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4a7fa2bc0efef3e209a8199fd111b8969fe9db9c711acc46636686331eda7dd4", size = 439383 }, - { url = "https://files.pythonhosted.org/packages/8b/c4/08b3c2cda45db5169148a981c2100c744a4a222fa7ae7644937c0c002069/watchfiles-0.24.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:01550ccf1d0aed6ea375ef259706af76ad009ef5b0203a3a4cce0f6024f9b68a", size = 426804 }, + { url = "https://files.pythonhosted.org/packages/cd/6c/7be04641c81209ea281b83b1174aa9d5ba53bec2a896d75a6b10428b4063/watchfiles-1.0.3-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:1da46bb1eefb5a37a8fb6fd52ad5d14822d67c498d99bda8754222396164ae42", size = 395213 }, + { url = "https://files.pythonhosted.org/packages/bd/d6/99438baa225891bda882adefefc14c9023ef3cdaf9772cd47973bb566e96/watchfiles-1.0.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2b961b86cd3973f5822826017cad7f5a75795168cb645c3a6b30c349094e02e3", size = 384755 }, + { url = "https://files.pythonhosted.org/packages/88/93/b10295ce8696e5e37f480ba4ae89e387e88ba425d72808c87d30f4cdefb1/watchfiles-1.0.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:34e87c7b3464d02af87f1059fedda5484e43b153ef519e4085fe1a03dd94801e", size = 441701 }, + { url = "https://files.pythonhosted.org/packages/c5/3a/0359b7bddb1b7cbe6fb7096805b6e2f859f0de3d6130dcab9ac635db87e2/watchfiles-1.0.3-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:d9dd2b89a16cf7ab9c1170b5863e68de6bf83db51544875b25a5f05a7269e678", size = 447540 }, + { url = "https://files.pythonhosted.org/packages/e2/a7/3400b4f105c68804495b76398165ffe6c00af93eab395279285f43cd0e42/watchfiles-1.0.3-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2b4691234d31686dca133c920f94e478b548a8e7c750f28dbbc2e4333e0d3da9", size = 472467 }, + { url = "https://files.pythonhosted.org/packages/c3/1a/8f928800d038d4fdb1e9df6e0c380c8cee17e6fb180e1faceb3f94de6df7/watchfiles-1.0.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:90b0fe1fcea9bd6e3084b44875e179b4adcc4057a3b81402658d0eb58c98edf8", size = 494467 }, + { url = "https://files.pythonhosted.org/packages/13/70/af75edf5b763f09e31a0f19ce045f3731db22599cb521807760b7d82b196/watchfiles-1.0.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0b90651b4cf9e158d01faa0833b073e2e37719264bcee3eac49fc3c74e7d304b", size = 492671 }, + { url = "https://files.pythonhosted.org/packages/4a/6e/8723f4b0967cc8d94f33fc531c33d66b596090b024f449983d3a8d97cfca/watchfiles-1.0.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c2e9fe695ff151b42ab06501820f40d01310fbd58ba24da8923ace79cf6d702d", size = 443811 }, + { url = "https://files.pythonhosted.org/packages/ee/5d/f3ca68a71d978d43168a65a1b4e1f72290c5350379aa148917e4ed0b2c46/watchfiles-1.0.3-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:62691f1c0894b001c7cde1195c03b7801aaa794a837bd6eef24da87d1542838d", size = 615477 }, + { url = "https://files.pythonhosted.org/packages/0d/d0/3d27a26f276ef07ca4cd3c6766684444317ddd147943e00bdb157cfdf3c3/watchfiles-1.0.3-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:275c1b0e942d335fccb6014d79267d1b9fa45b5ac0639c297f1e856f2f532552", size = 614237 }, + { url = "https://files.pythonhosted.org/packages/97/e9/ff30b210099d75cfa407924b3c265d3054f14b83ddf02072bd637394aab6/watchfiles-1.0.3-cp310-cp310-win32.whl", hash = "sha256:06ce08549e49ba69ccc36fc5659a3d0ff4e3a07d542b895b8a9013fcab46c2dc", size = 270798 }, + { url = "https://files.pythonhosted.org/packages/ed/86/694f07eb91d3e81a359661b48ff6984543e50be767c50c08196155d417bf/watchfiles-1.0.3-cp310-cp310-win_amd64.whl", hash = "sha256:f280b02827adc9d87f764972fbeb701cf5611f80b619c20568e1982a277d6146", size = 284192 }, + { url = "https://files.pythonhosted.org/packages/24/a8/06e2d5f840b285718a09be7c71ea19b7177b005cec87b8923dd7e8541b20/watchfiles-1.0.3-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:ffe709b1d0bc2e9921257569675674cafb3a5f8af689ab9f3f2b3f88775b960f", size = 394821 }, + { url = "https://files.pythonhosted.org/packages/57/9f/f98a57ada3d4b1fcd0e325aa6c307e2248ecb048f71c96fba34a602f02e7/watchfiles-1.0.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:418c5ce332f74939ff60691e5293e27c206c8164ce2b8ce0d9abf013003fb7fe", size = 384898 }, + { url = "https://files.pythonhosted.org/packages/a3/31/33ba914010cbfd01033ca3727aff6585b6b2ea2b051b6fbaecdf4e2160b9/watchfiles-1.0.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2f492d2907263d6d0d52f897a68647195bc093dafed14508a8d6817973586b6b", size = 441710 }, + { url = "https://files.pythonhosted.org/packages/d9/dd/e56b2ef07c2c34e4152950f0ce98a1081215ef027cf39e5dab61a0f8bd95/watchfiles-1.0.3-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:48c9f3bc90c556a854f4cab6a79c16974099ccfa3e3e150673d82d47a4bc92c9", size = 447681 }, + { url = "https://files.pythonhosted.org/packages/60/8f/3837df33f3d0cbef8ae59559891d688490bf2960373ea077ff11cbf79115/watchfiles-1.0.3-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:75d3bcfa90454dba8df12adc86b13b6d85fda97d90e708efc036c2760cc6ba44", size = 472312 }, + { url = "https://files.pythonhosted.org/packages/5a/b3/95d103e5bb609b20f175e8acdf8b32c4b091f96f781c066fd3bff2b17778/watchfiles-1.0.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5691340f259b8f76b45fb31b98e594d46c36d1dc8285efa7975f7f50230c9093", size = 494779 }, + { url = "https://files.pythonhosted.org/packages/4f/f0/9fdc60daf5abf7b0deb225c9b0a37fd72dc407fa33f071ae2f70e84e268c/watchfiles-1.0.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1e263cc718545b7f897baeac1f00299ab6fabe3e18caaacacb0edf6d5f35513c", size = 492090 }, + { url = "https://files.pythonhosted.org/packages/96/e5/a9967e77f173280ab1abbfd7ead90f2b94060574968baf5e6d7cbe9dd490/watchfiles-1.0.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1c6cf7709ed3e55704cc06f6e835bf43c03bc8e3cb8ff946bf69a2e0a78d9d77", size = 443713 }, + { url = "https://files.pythonhosted.org/packages/60/38/e5390d4633a558878113e45d32e39d30cf58eb94e0359f41737be209321b/watchfiles-1.0.3-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:703aa5e50e465be901e0e0f9d5739add15e696d8c26c53bc6fc00eb65d7b9469", size = 615306 }, + { url = "https://files.pythonhosted.org/packages/5c/27/8a1ee74544c93e3242ca073087b45c64367aeb6897b622e43c8172c2b421/watchfiles-1.0.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:bfcae6aecd9e0cb425f5145afee871465b98b75862e038d42fe91fd753ddd780", size = 614333 }, + { url = "https://files.pythonhosted.org/packages/fc/f8/25698f5b734907662b50acf3e81996053abdfe26fcf38804d028412876a8/watchfiles-1.0.3-cp311-cp311-win32.whl", hash = "sha256:6a76494d2c5311584f22416c5a87c1e2cb954ff9b5f0988027bc4ef2a8a67181", size = 270987 }, + { url = "https://files.pythonhosted.org/packages/39/78/f600dee7b387e6088c8d1f4c898a4340d07aecfe6406bd90ec4c1925ef08/watchfiles-1.0.3-cp311-cp311-win_amd64.whl", hash = "sha256:cf745cbfad6389c0e331786e5fe9ae3f06e9d9c2ce2432378e1267954793975c", size = 284098 }, + { url = "https://files.pythonhosted.org/packages/ca/6f/27ba8aec0a4b45a6063454465eefb42777158081d9df18eab5f1d6a3bd8a/watchfiles-1.0.3-cp311-cp311-win_arm64.whl", hash = "sha256:2dcc3f60c445f8ce14156854a072ceb36b83807ed803d37fdea2a50e898635d6", size = 276804 }, + { url = "https://files.pythonhosted.org/packages/bf/a9/c8b5ab33444306e1a324cb2b51644f8458dd459e30c3841f925012893e6a/watchfiles-1.0.3-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:93436ed550e429da007fbafb723e0769f25bae178fbb287a94cb4ccdf42d3af3", size = 391395 }, + { url = "https://files.pythonhosted.org/packages/ad/d3/403af5f07359863c03951796ddab265ee8cce1a6147510203d0bf43950e7/watchfiles-1.0.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:c18f3502ad0737813c7dad70e3e1cc966cc147fbaeef47a09463bbffe70b0a00", size = 381432 }, + { url = "https://files.pythonhosted.org/packages/f6/5f/921f2f2beabaf24b1ad81ac22bb69df8dd5771fdb68d6f34a5912a420941/watchfiles-1.0.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6a5bc3ca468bb58a2ef50441f953e1f77b9a61bd1b8c347c8223403dc9b4ac9a", size = 441448 }, + { url = "https://files.pythonhosted.org/packages/63/d7/67d0d750b246f248ccdb400a85a253e93e419ea5b6cbe968fa48b97a5f30/watchfiles-1.0.3-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:0d1ec043f02ca04bf21b1b32cab155ce90c651aaf5540db8eb8ad7f7e645cba8", size = 446852 }, + { url = "https://files.pythonhosted.org/packages/53/7c/d7cd94c7d0905f1e2f1c2232ea9bc39b1a48affd007e09c547ead96edb8f/watchfiles-1.0.3-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f58d3bfafecf3d81c15d99fc0ecf4319e80ac712c77cf0ce2661c8cf8bf84066", size = 471662 }, + { url = "https://files.pythonhosted.org/packages/26/81/738f8e66f7525753996b8aa292f78dcec1ef77887d62e6cdfb04cc2f352f/watchfiles-1.0.3-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1df924ba82ae9e77340101c28d56cbaff2c991bd6fe8444a545d24075abb0a87", size = 493765 }, + { url = "https://files.pythonhosted.org/packages/d2/50/78e21f5da24ab39114e9b24f7b0945ea1c6fc7bc9ae86cd87f8eaeb47325/watchfiles-1.0.3-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:632a52dcaee44792d0965c17bdfe5dc0edad5b86d6a29e53d6ad4bf92dc0ff49", size = 490558 }, + { url = "https://files.pythonhosted.org/packages/a8/93/1873fea6354b2858eae8970991d64e9a449d87726d596490d46bf00af8ed/watchfiles-1.0.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:80bf4b459d94a0387617a1b499f314aa04d8a64b7a0747d15d425b8c8b151da0", size = 442808 }, + { url = "https://files.pythonhosted.org/packages/4f/b4/2fc4c92fb28b029f66d04a4d430fe929284e9ff717b04bb7a3bb8a7a5605/watchfiles-1.0.3-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:ca94c85911601b097d53caeeec30201736ad69a93f30d15672b967558df02885", size = 615287 }, + { url = "https://files.pythonhosted.org/packages/1e/d4/93da24db39257e440240d338b617c5153ad11d361c34108f5c0e1e0743eb/watchfiles-1.0.3-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:65ab1fb635476f6170b07e8e21db0424de94877e4b76b7feabfe11f9a5fc12b5", size = 612812 }, + { url = "https://files.pythonhosted.org/packages/c6/67/9fd3661c2dc0309abd6021876653d91e8b64fb279529e2cadaa3520ef3e3/watchfiles-1.0.3-cp312-cp312-win32.whl", hash = "sha256:49bc1bc26abf4f32e132652f4b3bfeec77d8f8f62f57652703ef127e85a3e38d", size = 271642 }, + { url = "https://files.pythonhosted.org/packages/ae/aa/8c887edb78cd67f5d4d6a35c3aeb46d748643ebf962163130fb1871e2ee0/watchfiles-1.0.3-cp312-cp312-win_amd64.whl", hash = "sha256:48681c86f2cb08348631fed788a116c89c787fdf1e6381c5febafd782f6c3b44", size = 285505 }, + { url = "https://files.pythonhosted.org/packages/7b/31/d212fa6390f0e73a91913ada0b925b294a78d67794795371208baf73f0b5/watchfiles-1.0.3-cp312-cp312-win_arm64.whl", hash = "sha256:9e080cf917b35b20c889225a13f290f2716748362f6071b859b60b8847a6aa43", size = 277263 }, + { url = "https://files.pythonhosted.org/packages/26/48/5a75b18ad40cc69ea6e0003bb748db162a3215bbe44a1293e073876d51bd/watchfiles-1.0.3-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:84fac88278f42d61c519a6c75fb5296fd56710b05bbdcc74bdf85db409a03780", size = 396233 }, + { url = "https://files.pythonhosted.org/packages/dc/b2/03ce3447a3271483b030b8bafc39be19739f9a4a23edec31c6688e8a066d/watchfiles-1.0.3-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:c68be72b1666d93b266714f2d4092d78dc53bd11cf91ed5a3c16527587a52e29", size = 386050 }, + { url = "https://files.pythonhosted.org/packages/ab/0c/38914f56a95aa6ec911bb7cee617762d93aaf5a11efecadbb698d6b0b9a2/watchfiles-1.0.3-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:889a37e2acf43c377b5124166bece139b4c731b61492ab22e64d371cce0e6e80", size = 442404 }, + { url = "https://files.pythonhosted.org/packages/4d/8c/a95d3ba1ccfa33a43649668f699150cce1ea795e4300c33b4c3e974a444b/watchfiles-1.0.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7ca05cacf2e5c4a97d02a2878a24020daca21dbb8823b023b978210a75c79098", size = 444461 }, ] [[package]] @@ -8509,11 +8517,11 @@ sdist = { url = "https://files.pythonhosted.org/packages/67/35/25e68fbc99e672127 [[package]] name = "win32-setctime" -version = "1.1.0" +version = "1.2.0" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/6b/dd/f95a13d2b235a28d613ba23ebad55191514550debb968b46aab99f2e3a30/win32_setctime-1.1.0.tar.gz", hash = "sha256:15cf5750465118d6929ae4de4eb46e8edae9a5634350c01ba582df868e932cb2", size = 3676 } +sdist = { url = "https://files.pythonhosted.org/packages/b3/8f/705086c9d734d3b663af0e9bb3d4de6578d08f46b1b101c2442fd9aecaa2/win32_setctime-1.2.0.tar.gz", hash = "sha256:ae1fdf948f5640aae05c511ade119313fb6a30d7eabe25fef9764dca5873c4c0", size = 4867 } wheels = [ - { url = "https://files.pythonhosted.org/packages/0a/e6/a7d828fef907843b2a5773ebff47fb79ac0c1c88d60c0ca9530ee941e248/win32_setctime-1.1.0-py3-none-any.whl", hash = "sha256:231db239e959c2fe7eb1d7dc129f11172354f98361c4fa2d6d2d7e278baa8aad", size = 3604 }, + { url = "https://files.pythonhosted.org/packages/e1/07/c6fe3ad3e685340704d314d765b7912993bcb8dc198f0e7a89382d37974b/win32_setctime-1.2.0-py3-none-any.whl", hash = "sha256:95d644c4e708aba81dc3704a116d8cbc974d70b3bdb8be1d150e36be6e9d1390", size = 4083 }, ] [[package]] @@ -8534,41 +8542,38 @@ wheels = [ [[package]] name = "wrapt" -version = "1.16.0" +version = "1.17.0" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/95/4c/063a912e20bcef7124e0df97282a8af3ff3e4b603ce84c481d6d7346be0a/wrapt-1.16.0.tar.gz", hash = "sha256:5f370f952971e7d17c7d1ead40e49f32345a7f7a5373571ef44d800d06b1899d", size = 53972 } +sdist = { url = "https://files.pythonhosted.org/packages/24/a1/fc03dca9b0432725c2e8cdbf91a349d2194cf03d8523c124faebe581de09/wrapt-1.17.0.tar.gz", hash = "sha256:16187aa2317c731170a88ef35e8937ae0f533c402872c1ee5e6d079fcf320801", size = 55542 } wheels = [ - { url = "https://files.pythonhosted.org/packages/a8/c6/5375258add3777494671d8cec27cdf5402abd91016dee24aa2972c61fedf/wrapt-1.16.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:ffa565331890b90056c01db69c0fe634a776f8019c143a5ae265f9c6bc4bd6d4", size = 37315 }, - { url = "https://files.pythonhosted.org/packages/32/12/e11adfde33444986135d8881b401e4de6cbb4cced046edc6b464e6ad7547/wrapt-1.16.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e4fdb9275308292e880dcbeb12546df7f3e0f96c6b41197e0cf37d2826359020", size = 38160 }, - { url = "https://files.pythonhosted.org/packages/70/7d/3dcc4a7e96f8d3e398450ec7703db384413f79bd6c0196e0e139055ce00f/wrapt-1.16.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bb2dee3874a500de01c93d5c71415fcaef1d858370d405824783e7a8ef5db440", size = 80419 }, - { url = "https://files.pythonhosted.org/packages/d1/c4/8dfdc3c2f0b38be85c8d9fdf0011ebad2f54e40897f9549a356bebb63a97/wrapt-1.16.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2a88e6010048489cda82b1326889ec075a8c856c2e6a256072b28eaee3ccf487", size = 72669 }, - { url = "https://files.pythonhosted.org/packages/49/83/b40bc1ad04a868b5b5bcec86349f06c1ee1ea7afe51dc3e46131e4f39308/wrapt-1.16.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ac83a914ebaf589b69f7d0a1277602ff494e21f4c2f743313414378f8f50a4cf", size = 80271 }, - { url = "https://files.pythonhosted.org/packages/19/d4/cd33d3a82df73a064c9b6401d14f346e1d2fb372885f0295516ec08ed2ee/wrapt-1.16.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:73aa7d98215d39b8455f103de64391cb79dfcad601701a3aa0dddacf74911d72", size = 84748 }, - { url = "https://files.pythonhosted.org/packages/ef/58/2fde309415b5fa98fd8f5f4a11886cbf276824c4c64d45a39da342fff6fe/wrapt-1.16.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:807cc8543a477ab7422f1120a217054f958a66ef7314f76dd9e77d3f02cdccd0", size = 77522 }, - { url = "https://files.pythonhosted.org/packages/07/44/359e4724a92369b88dbf09878a7cde7393cf3da885567ea898e5904049a3/wrapt-1.16.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:bf5703fdeb350e36885f2875d853ce13172ae281c56e509f4e6eca049bdfb136", size = 84780 }, - { url = "https://files.pythonhosted.org/packages/88/8f/706f2fee019360cc1da652353330350c76aa5746b4e191082e45d6838faf/wrapt-1.16.0-cp310-cp310-win32.whl", hash = "sha256:f6b2d0c6703c988d334f297aa5df18c45e97b0af3679bb75059e0e0bd8b1069d", size = 35335 }, - { url = "https://files.pythonhosted.org/packages/19/2b/548d23362e3002ebbfaefe649b833fa43f6ca37ac3e95472130c4b69e0b4/wrapt-1.16.0-cp310-cp310-win_amd64.whl", hash = "sha256:decbfa2f618fa8ed81c95ee18a387ff973143c656ef800c9f24fb7e9c16054e2", size = 37528 }, - { url = "https://files.pythonhosted.org/packages/fd/03/c188ac517f402775b90d6f312955a5e53b866c964b32119f2ed76315697e/wrapt-1.16.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:1a5db485fe2de4403f13fafdc231b0dbae5eca4359232d2efc79025527375b09", size = 37313 }, - { url = "https://files.pythonhosted.org/packages/0f/16/ea627d7817394db04518f62934a5de59874b587b792300991b3c347ff5e0/wrapt-1.16.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:75ea7d0ee2a15733684badb16de6794894ed9c55aa5e9903260922f0482e687d", size = 38164 }, - { url = "https://files.pythonhosted.org/packages/7f/a7/f1212ba098f3de0fd244e2de0f8791ad2539c03bef6c05a9fcb03e45b089/wrapt-1.16.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a452f9ca3e3267cd4d0fcf2edd0d035b1934ac2bd7e0e57ac91ad6b95c0c6389", size = 80890 }, - { url = "https://files.pythonhosted.org/packages/b7/96/bb5e08b3d6db003c9ab219c487714c13a237ee7dcc572a555eaf1ce7dc82/wrapt-1.16.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:43aa59eadec7890d9958748db829df269f0368521ba6dc68cc172d5d03ed8060", size = 73118 }, - { url = "https://files.pythonhosted.org/packages/6e/52/2da48b35193e39ac53cfb141467d9f259851522d0e8c87153f0ba4205fb1/wrapt-1.16.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:72554a23c78a8e7aa02abbd699d129eead8b147a23c56e08d08dfc29cfdddca1", size = 80746 }, - { url = "https://files.pythonhosted.org/packages/11/fb/18ec40265ab81c0e82a934de04596b6ce972c27ba2592c8b53d5585e6bcd/wrapt-1.16.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:d2efee35b4b0a347e0d99d28e884dfd82797852d62fcd7ebdeee26f3ceb72cf3", size = 85668 }, - { url = "https://files.pythonhosted.org/packages/0f/ef/0ecb1fa23145560431b970418dce575cfaec555ab08617d82eb92afc7ccf/wrapt-1.16.0-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:6dcfcffe73710be01d90cae08c3e548d90932d37b39ef83969ae135d36ef3956", size = 78556 }, - { url = "https://files.pythonhosted.org/packages/25/62/cd284b2b747f175b5a96cbd8092b32e7369edab0644c45784871528eb852/wrapt-1.16.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:eb6e651000a19c96f452c85132811d25e9264d836951022d6e81df2fff38337d", size = 85712 }, - { url = "https://files.pythonhosted.org/packages/e5/a7/47b7ff74fbadf81b696872d5ba504966591a3468f1bc86bca2f407baef68/wrapt-1.16.0-cp311-cp311-win32.whl", hash = "sha256:66027d667efe95cc4fa945af59f92c5a02c6f5bb6012bff9e60542c74c75c362", size = 35327 }, - { url = "https://files.pythonhosted.org/packages/cf/c3/0084351951d9579ae83a3d9e38c140371e4c6b038136909235079f2e6e78/wrapt-1.16.0-cp311-cp311-win_amd64.whl", hash = "sha256:aefbc4cb0a54f91af643660a0a150ce2c090d3652cf4052a5397fb2de549cd89", size = 37523 }, - { url = "https://files.pythonhosted.org/packages/92/17/224132494c1e23521868cdd57cd1e903f3b6a7ba6996b7b8f077ff8ac7fe/wrapt-1.16.0-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:5eb404d89131ec9b4f748fa5cfb5346802e5ee8836f57d516576e61f304f3b7b", size = 37614 }, - { url = "https://files.pythonhosted.org/packages/6a/d7/cfcd73e8f4858079ac59d9db1ec5a1349bc486ae8e9ba55698cc1f4a1dff/wrapt-1.16.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:9090c9e676d5236a6948330e83cb89969f433b1943a558968f659ead07cb3b36", size = 38316 }, - { url = "https://files.pythonhosted.org/packages/7e/79/5ff0a5c54bda5aec75b36453d06be4f83d5cd4932cc84b7cb2b52cee23e2/wrapt-1.16.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:94265b00870aa407bd0cbcfd536f17ecde43b94fb8d228560a1e9d3041462d73", size = 86322 }, - { url = "https://files.pythonhosted.org/packages/c4/81/e799bf5d419f422d8712108837c1d9bf6ebe3cb2a81ad94413449543a923/wrapt-1.16.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f2058f813d4f2b5e3a9eb2eb3faf8f1d99b81c3e51aeda4b168406443e8ba809", size = 79055 }, - { url = "https://files.pythonhosted.org/packages/62/62/30ca2405de6a20448ee557ab2cd61ab9c5900be7cbd18a2639db595f0b98/wrapt-1.16.0-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98b5e1f498a8ca1858a1cdbffb023bfd954da4e3fa2c0cb5853d40014557248b", size = 87291 }, - { url = "https://files.pythonhosted.org/packages/49/4e/5d2f6d7b57fc9956bf06e944eb00463551f7d52fc73ca35cfc4c2cdb7aed/wrapt-1.16.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:14d7dc606219cdd7405133c713f2c218d4252f2a469003f8c46bb92d5d095d81", size = 90374 }, - { url = "https://files.pythonhosted.org/packages/a6/9b/c2c21b44ff5b9bf14a83252a8b973fb84923764ff63db3e6dfc3895cf2e0/wrapt-1.16.0-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:49aac49dc4782cb04f58986e81ea0b4768e4ff197b57324dcbd7699c5dfb40b9", size = 83896 }, - { url = "https://files.pythonhosted.org/packages/14/26/93a9fa02c6f257df54d7570dfe8011995138118d11939a4ecd82cb849613/wrapt-1.16.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:418abb18146475c310d7a6dc71143d6f7adec5b004ac9ce08dc7a34e2babdc5c", size = 91738 }, - { url = "https://files.pythonhosted.org/packages/a2/5b/4660897233eb2c8c4de3dc7cefed114c61bacb3c28327e64150dc44ee2f6/wrapt-1.16.0-cp312-cp312-win32.whl", hash = "sha256:685f568fa5e627e93f3b52fda002c7ed2fa1800b50ce51f6ed1d572d8ab3e7fc", size = 35568 }, - { url = "https://files.pythonhosted.org/packages/5c/cc/8297f9658506b224aa4bd71906447dea6bb0ba629861a758c28f67428b91/wrapt-1.16.0-cp312-cp312-win_amd64.whl", hash = "sha256:dcdba5c86e368442528f7060039eda390cc4091bfd1dca41e8046af7c910dda8", size = 37653 }, - { url = "https://files.pythonhosted.org/packages/ff/21/abdedb4cdf6ff41ebf01a74087740a709e2edb146490e4d9beea054b0b7a/wrapt-1.16.0-py3-none-any.whl", hash = "sha256:6906c4100a8fcbf2fa735f6059214bb13b97f75b1a61777fcf6432121ef12ef1", size = 23362 }, + { url = "https://files.pythonhosted.org/packages/99/f9/85220321e9bb1a5f72ccce6604395ae75fcb463d87dad0014dc1010bd1f1/wrapt-1.17.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2a0c23b8319848426f305f9cb0c98a6e32ee68a36264f45948ccf8e7d2b941f8", size = 38766 }, + { url = "https://files.pythonhosted.org/packages/ff/71/ff624ff3bde91ceb65db6952cdf8947bc0111d91bd2359343bc2fa7c57fd/wrapt-1.17.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b1ca5f060e205f72bec57faae5bd817a1560fcfc4af03f414b08fa29106b7e2d", size = 83262 }, + { url = "https://files.pythonhosted.org/packages/9f/0a/814d4a121a643af99cfe55a43e9e6dd08f4a47cdac8e8f0912c018794715/wrapt-1.17.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e185ec6060e301a7e5f8461c86fb3640a7beb1a0f0208ffde7a65ec4074931df", size = 74990 }, + { url = "https://files.pythonhosted.org/packages/cd/c7/b8c89bf5ca5c4e6a2d0565d149d549cdb4cffb8916d1d1b546b62fb79281/wrapt-1.17.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bb90765dd91aed05b53cd7a87bd7f5c188fcd95960914bae0d32c5e7f899719d", size = 82712 }, + { url = "https://files.pythonhosted.org/packages/19/7c/5977aefa8460906c1ff914fd42b11cf6c09ded5388e46e1cc6cea4ab15e9/wrapt-1.17.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:879591c2b5ab0a7184258274c42a126b74a2c3d5a329df16d69f9cee07bba6ea", size = 81705 }, + { url = "https://files.pythonhosted.org/packages/ae/e7/233402d7bd805096bb4a8ec471f5a141421a01de3c8c957cce569772c056/wrapt-1.17.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:fce6fee67c318fdfb7f285c29a82d84782ae2579c0e1b385b7f36c6e8074fffb", size = 74636 }, + { url = "https://files.pythonhosted.org/packages/93/81/b6c32d8387d9cfbc0134f01585dee7583315c3b46dfd3ae64d47693cd078/wrapt-1.17.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:0698d3a86f68abc894d537887b9bbf84d29bcfbc759e23f4644be27acf6da301", size = 81299 }, + { url = "https://files.pythonhosted.org/packages/d1/c3/1fae15d453468c98f09519076f8d401b476d18d8d94379e839eed14c4c8b/wrapt-1.17.0-cp310-cp310-win32.whl", hash = "sha256:69d093792dc34a9c4c8a70e4973a3361c7a7578e9cd86961b2bbf38ca71e4e22", size = 36425 }, + { url = "https://files.pythonhosted.org/packages/c6/f4/77e0886c95556f2b4caa8908ea8eb85f713fc68296a2113f8c63d50fe0fb/wrapt-1.17.0-cp310-cp310-win_amd64.whl", hash = "sha256:f28b29dc158ca5d6ac396c8e0a2ef45c4e97bb7e65522bfc04c989e6fe814575", size = 38748 }, + { url = "https://files.pythonhosted.org/packages/0e/40/def56538acddc2f764c157d565b9f989072a1d2f2a8e384324e2e104fc7d/wrapt-1.17.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:74bf625b1b4caaa7bad51d9003f8b07a468a704e0644a700e936c357c17dd45a", size = 38766 }, + { url = "https://files.pythonhosted.org/packages/89/e2/8c299f384ae4364193724e2adad99f9504599d02a73ec9199bf3f406549d/wrapt-1.17.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0f2a28eb35cf99d5f5bd12f5dd44a0f41d206db226535b37b0c60e9da162c3ed", size = 83730 }, + { url = "https://files.pythonhosted.org/packages/29/ef/fcdb776b12df5ea7180d065b28fa6bb27ac785dddcd7202a0b6962bbdb47/wrapt-1.17.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:81b1289e99cf4bad07c23393ab447e5e96db0ab50974a280f7954b071d41b489", size = 75470 }, + { url = "https://files.pythonhosted.org/packages/55/b5/698bd0bf9fbb3ddb3a2feefbb7ad0dea1205f5d7d05b9cbab54f5db731aa/wrapt-1.17.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9f2939cd4a2a52ca32bc0b359015718472d7f6de870760342e7ba295be9ebaf9", size = 83168 }, + { url = "https://files.pythonhosted.org/packages/ce/07/701a5cee28cb4d5df030d4b2649319e36f3d9fdd8000ef1d84eb06b9860d/wrapt-1.17.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:6a9653131bda68a1f029c52157fd81e11f07d485df55410401f745007bd6d339", size = 82307 }, + { url = "https://files.pythonhosted.org/packages/42/92/c48ba92cda6f74cb914dc3c5bba9650dc80b790e121c4b987f3a46b028f5/wrapt-1.17.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:4e4b4385363de9052dac1a67bfb535c376f3d19c238b5f36bddc95efae15e12d", size = 75101 }, + { url = "https://files.pythonhosted.org/packages/8a/0a/9276d3269334138b88a2947efaaf6335f61d547698e50dff672ade24f2c6/wrapt-1.17.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:bdf62d25234290db1837875d4dceb2151e4ea7f9fff2ed41c0fde23ed542eb5b", size = 81835 }, + { url = "https://files.pythonhosted.org/packages/b9/4c/39595e692753ef656ea94b51382cc9aea662fef59d7910128f5906486f0e/wrapt-1.17.0-cp311-cp311-win32.whl", hash = "sha256:5d8fd17635b262448ab8f99230fe4dac991af1dabdbb92f7a70a6afac8a7e346", size = 36412 }, + { url = "https://files.pythonhosted.org/packages/63/bb/c293a67fb765a2ada48f48cd0f2bb957da8161439da4c03ea123b9894c02/wrapt-1.17.0-cp311-cp311-win_amd64.whl", hash = "sha256:92a3d214d5e53cb1db8b015f30d544bc9d3f7179a05feb8f16df713cecc2620a", size = 38744 }, + { url = "https://files.pythonhosted.org/packages/85/82/518605474beafff11f1a34759f6410ab429abff9f7881858a447e0d20712/wrapt-1.17.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:89fc28495896097622c3fc238915c79365dd0ede02f9a82ce436b13bd0ab7569", size = 38904 }, + { url = "https://files.pythonhosted.org/packages/80/6c/17c3b2fed28edfd96d8417c865ef0b4c955dc52c4e375d86f459f14340f1/wrapt-1.17.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:875d240fdbdbe9e11f9831901fb8719da0bd4e6131f83aa9f69b96d18fae7504", size = 88622 }, + { url = "https://files.pythonhosted.org/packages/4a/11/60ecdf3b0fd3dca18978d89acb5d095a05f23299216e925fcd2717c81d93/wrapt-1.17.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e5ed16d95fd142e9c72b6c10b06514ad30e846a0d0917ab406186541fe68b451", size = 80920 }, + { url = "https://files.pythonhosted.org/packages/d2/50/dbef1a651578a3520d4534c1e434989e3620380c1ad97e309576b47f0ada/wrapt-1.17.0-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:18b956061b8db634120b58f668592a772e87e2e78bc1f6a906cfcaa0cc7991c1", size = 89170 }, + { url = "https://files.pythonhosted.org/packages/44/a2/78c5956bf39955288c9e0dd62e807b308c3aa15a0f611fbff52aa8d6b5ea/wrapt-1.17.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:daba396199399ccabafbfc509037ac635a6bc18510ad1add8fd16d4739cdd106", size = 86748 }, + { url = "https://files.pythonhosted.org/packages/99/49/2ee413c78fc0bdfebe5bee590bf3becdc1fab0096a7a9c3b5c9666b2415f/wrapt-1.17.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:4d63f4d446e10ad19ed01188d6c1e1bb134cde8c18b0aa2acfd973d41fcc5ada", size = 79734 }, + { url = "https://files.pythonhosted.org/packages/c0/8c/4221b7b270e36be90f0930fe15a4755a6ea24093f90b510166e9ed7861ea/wrapt-1.17.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:8a5e7cc39a45fc430af1aefc4d77ee6bad72c5bcdb1322cfde852c15192b8bd4", size = 87552 }, + { url = "https://files.pythonhosted.org/packages/4c/6b/1aaccf3efe58eb95e10ce8e77c8909b7a6b0da93449a92c4e6d6d10b3a3d/wrapt-1.17.0-cp312-cp312-win32.whl", hash = "sha256:0a0a1a1ec28b641f2a3a2c35cbe86c00051c04fffcfcc577ffcdd707df3f8635", size = 36647 }, + { url = "https://files.pythonhosted.org/packages/b3/4f/243f88ac49df005b9129194c6511b3642818b3e6271ddea47a15e2ee4934/wrapt-1.17.0-cp312-cp312-win_amd64.whl", hash = "sha256:3c34f6896a01b84bab196f7119770fd8466c8ae3dfa73c59c0bb281e7b588ce7", size = 38830 }, + { url = "https://files.pythonhosted.org/packages/4b/d9/a8ba5e9507a9af1917285d118388c5eb7a81834873f45df213a6fe923774/wrapt-1.17.0-py3-none-any.whl", hash = "sha256:d2c63b93548eda58abf5188e505ffed0229bf675f7c3090f8e36ad55b8cbc371", size = 23592 }, ] [[package]] @@ -8585,11 +8590,11 @@ wheels = [ [[package]] name = "xmltodict" -version = "0.14.1" +version = "0.14.2" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/98/f7/d29b8cdc9d8d075673be0f800013c1161e2fd4234546a140855a1bcc9eb4/xmltodict-0.14.1.tar.gz", hash = "sha256:338c8431e4fc554517651972d62f06958718f6262b04316917008e8fd677a6b0", size = 51919 } +sdist = { url = "https://files.pythonhosted.org/packages/50/05/51dcca9a9bf5e1bce52582683ce50980bcadbc4fa5143b9f2b19ab99958f/xmltodict-0.14.2.tar.gz", hash = "sha256:201e7c28bb210e374999d1dde6382923ab0ed1a8a5faeece48ab525b7810a553", size = 51942 } wheels = [ - { url = "https://files.pythonhosted.org/packages/83/33/ce3c404fece93880135ab9a07414d57f642e9340717130362bcd4ecee3c1/xmltodict-0.14.1-py2.py3-none-any.whl", hash = "sha256:3ef4a7b71c08f19047fcbea572e1d7f4207ab269da1565b5d40e9823d3894e63", size = 9982 }, + { url = "https://files.pythonhosted.org/packages/d6/45/fc303eb433e8a2a271739c98e953728422fa61a3c1f36077a49e395c972e/xmltodict-0.14.2-py2.py3-none-any.whl", hash = "sha256:20cc7d723ed729276e808f26fb6b3599f786cbc37e06c65e192ba77c40f20aac", size = 9981 }, ] [[package]] @@ -8652,61 +8657,64 @@ wheels = [ [[package]] name = "yarl" -version = "1.14.0" +version = "1.18.3" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "idna" }, { name = "multidict" }, { name = "propcache" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/46/fe/2ca2e5ef45952f3e8adb95659821a4e9169d8bbafab97eb662602ee12834/yarl-1.14.0.tar.gz", hash = "sha256:88c7d9d58aab0724b979ab5617330acb1c7030b79379c8138c1c8c94e121d1b3", size = 166127 } +sdist = { url = "https://files.pythonhosted.org/packages/b7/9d/4b94a8e6d2b51b599516a5cb88e5bc99b4d8d4583e468057eaa29d5f0918/yarl-1.18.3.tar.gz", hash = "sha256:ac1801c45cbf77b6c99242eeff4fffb5e4e73a800b5c4ad4fc0be5def634d2e1", size = 181062 } wheels = [ - { url = "https://files.pythonhosted.org/packages/8c/27/dc4f4eabb51cf82f3ba8f8d977fba0e06006d66cee907ea12982c4c85904/yarl-1.14.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:1bfc25aa6a7c99cf86564210f79a0b7d4484159c67e01232b116e445b3036547", size = 135762 }, - { url = "https://files.pythonhosted.org/packages/e7/32/e524d6c4b3acd05c88a5454cb3221b74bf7460b593deccf88f3b27361200/yarl-1.14.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:0cf21f46a15d445417de8fc89f2568852cf57fe8ca1ab3d19ddb24d45c0383ae", size = 87946 }, - { url = "https://files.pythonhosted.org/packages/7f/ae/42c5fe1ae66eade3f17e442e5adce36b0d098867d5bd98e08527ff026d52/yarl-1.14.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:1dda53508df0de87b6e6b0a52d6718ff6c62a5aca8f5552748404963df639269", size = 85854 }, - { url = "https://files.pythonhosted.org/packages/57/21/d653108b654daec3b9359a27f61959cf020839f97248bd345bf1ec7f1490/yarl-1.14.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:587c3cc59bc148a9b1c07a019346eda2549bc9f468acd2f9824d185749acf0a6", size = 306502 }, - { url = "https://files.pythonhosted.org/packages/8f/0b/996f04d9de5523735661a90ead48ea21d7557e1a71b1f757d1b2e3baae17/yarl-1.14.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3007a5b75cb50140708420fe688c393e71139324df599434633019314ceb8b59", size = 320849 }, - { url = "https://files.pythonhosted.org/packages/7b/10/b720945c7cd294283f8809dd0407e4cd56218949a4cca3ff04995cae6f0a/yarl-1.14.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:06ff23462398333c78b6f4f8d3d70410d657a471c2c5bbe6086133be43fc8f1a", size = 318727 }, - { url = "https://files.pythonhosted.org/packages/d3/3a/0c65820d2d73649d99970e1c150e4be6c057a624cb545613ce75c3ebe2a6/yarl-1.14.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:689a99a42ee4583fcb0d3a67a0204664aa1539684aed72bdafcbd505197a91c4", size = 309599 }, - { url = "https://files.pythonhosted.org/packages/43/01/00f44df69b99e23790096aba5e16651694b8de087af12418578dc00730bd/yarl-1.14.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b0547ab1e9345dc468cac8368d88ea4c5bd473ebc1d8d755347d7401982b5dd8", size = 299716 }, - { url = "https://files.pythonhosted.org/packages/41/1e/9c9e06f53d91f0b5ac6e69162e92d0fdd0851d4cc360f08716e29201802a/yarl-1.14.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:742aef0a99844faaac200564ea6f5e08facb285d37ea18bd1a5acf2771f3255a", size = 306355 }, - { url = "https://files.pythonhosted.org/packages/65/43/db5da311d287691cc02a4f66be8ac5859bce9627d51f8d553fc4f2beb601/yarl-1.14.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:176110bff341b6730f64a1eb3a7070e12b373cf1c910a9337e7c3240497db76f", size = 310309 }, - { url = "https://files.pythonhosted.org/packages/47/0c/271fdc45a5c2d13f9d138b039a264e35283a4ead36e7a538aefce4050d5e/yarl-1.14.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:46a9772a1efa93f9cd170ad33101c1817c77e0e9914d4fe33e2da299d7cf0f9b", size = 325571 }, - { url = "https://files.pythonhosted.org/packages/64/7f/bde078ab75deba8387d260f387864b0f549fcdb8d5bee0d9b30406b1b7fe/yarl-1.14.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:ee2c68e4f2dd1b1c15b849ba1c96fac105fca6ffdb7c1e8be51da6fabbdeafb9", size = 323477 }, - { url = "https://files.pythonhosted.org/packages/bb/f3/9fcf03b8826893275d2b46360986b2afba131e74eb6d722574b34b479144/yarl-1.14.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:047b258e00b99091b6f90355521f026238c63bd76dcf996d93527bb13320eefd", size = 316299 }, - { url = "https://files.pythonhosted.org/packages/22/77/b3d0410dfeb0bd779d6013afc1609ba17bff4d15479cab72cc16b11af4fa/yarl-1.14.0-cp310-cp310-win32.whl", hash = "sha256:0aa92e3e30a04f9462a25077db689c4ac5ea9ab6cc68a2e563881b987d42f16d", size = 77408 }, - { url = "https://files.pythonhosted.org/packages/92/69/29f5c9399d705254b2095bf117d7fb758f80057ad359b4e3224aa711b966/yarl-1.14.0-cp310-cp310-win_amd64.whl", hash = "sha256:d9baec588f015d0ee564057aa7574313c53a530662ffad930b7886becc85abdf", size = 83511 }, - { url = "https://files.pythonhosted.org/packages/92/aa/64fcae3d4a081e4ee07902e9e9a3b597c2577283bf6c5b59c06ef0829d90/yarl-1.14.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:07f9eaf57719d6721ab15805d85f4b01a5b509a0868d7320134371bcb652152d", size = 135761 }, - { url = "https://files.pythonhosted.org/packages/93/a0/5537a1da2c0ec8e11006efa0d133cdaded5ebb94ca71e87e3564b59f6c7f/yarl-1.14.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:c14b504a74e58e2deb0378b3eca10f3d076635c100f45b113c18c770b4a47a50", size = 87888 }, - { url = "https://files.pythonhosted.org/packages/e3/25/1d12bec8ebdc8287a3464f506ded23b30ad75a5fea3ba49526e8b473057f/yarl-1.14.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:16a682a127930f3fc4e42583becca6049e1d7214bcad23520c590edd741d2114", size = 85883 }, - { url = "https://files.pythonhosted.org/packages/75/85/01c2eb9a6ed755e073ef7d455151edf0ddd89618fca7d653894f7580b538/yarl-1.14.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:73bedd2be05f48af19f0f2e9e1353921ce0c83f4a1c9e8556ecdcf1f1eae4892", size = 333347 }, - { url = "https://files.pythonhosted.org/packages/38/c7/6c3634ef216f01f928d7eec7b7de5bde56658292c8cbdcd29cc28d830f4d/yarl-1.14.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f3ab950f8814f3b7b5e3eebc117986f817ec933676f68f0a6c5b2137dd7c9c69", size = 346644 }, - { url = "https://files.pythonhosted.org/packages/f4/ce/d1b1c441e41c652ce8081299db4f9b856f25a04b9c1885b3ba2e6edd3102/yarl-1.14.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b693c63e7e64b524f54aa4888403c680342d1ad0d97be1707c531584d6aeeb4f", size = 344078 }, - { url = "https://files.pythonhosted.org/packages/f0/ec/520686b83b51127792ca507d67ae1090c919c8cb8388c78d1e7c63c98a4a/yarl-1.14.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:85cb3e40eaa98489f1e2e8b29f5ad02ee1ee40d6ce6b88d50cf0f205de1d9d2c", size = 336398 }, - { url = "https://files.pythonhosted.org/packages/30/4d/e842066d3336203299a3dc1730f2d062061e7b8a4497f4b6977d9076d263/yarl-1.14.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4f24f08b6c9b9818fd80612c97857d28f9779f0d1211653ece9844fc7b414df2", size = 325519 }, - { url = "https://files.pythonhosted.org/packages/46/c7/83b9c0e5717ddd99b203dbb61c56450f475ab4a7d4d6b61b4af0a03c54d9/yarl-1.14.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:29a84a46ec3ebae7a1c024c055612b11e9363a8a23238b3e905552d77a2bc51b", size = 335487 }, - { url = "https://files.pythonhosted.org/packages/5e/58/2c5f0c840ab3bb364ebe5a6233bfe77ed9fcef6b34c19f3809dd15dae972/yarl-1.14.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:5cd5dad8366e0168e0fd23d10705a603790484a6dbb9eb272b33673b8f2cce72", size = 334259 }, - { url = "https://files.pythonhosted.org/packages/6a/6b/95d7a85b5a20d90ffd42a174ff52772f6d046d60b85e4cd506e0baa58341/yarl-1.14.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:a152751af7ef7b5d5fa6d215756e508dd05eb07d0cf2ba51f3e740076aa74373", size = 355310 }, - { url = "https://files.pythonhosted.org/packages/77/14/dd4cc5fe69b8d0708f3c43a2b8c8cca5364f2205e220908ba79be202f61c/yarl-1.14.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:3d569f877ed9a708e4c71a2d13d2940cb0791da309f70bd970ac1a5c088a0a92", size = 356970 }, - { url = "https://files.pythonhosted.org/packages/1a/5e/aa5c615abbc6366c787f7abf5af2ffefd5ebe1ffc381850065624e5072fe/yarl-1.14.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:6a615cad11ec3428020fb3c5a88d85ce1b5c69fd66e9fcb91a7daa5e855325dd", size = 344806 }, - { url = "https://files.pythonhosted.org/packages/f3/10/7b9d14b5165d7f3a7b6f474cafab6993fe7a76a908a7f02d34099e915c74/yarl-1.14.0-cp311-cp311-win32.whl", hash = "sha256:bab03192091681d54e8225c53f270b0517637915d9297028409a2a5114ff4634", size = 77527 }, - { url = "https://files.pythonhosted.org/packages/ae/bb/277d3d6d44882614cbbe108474d33c0d0ffe1ea6760e710b4237147840a2/yarl-1.14.0-cp311-cp311-win_amd64.whl", hash = "sha256:985623575e5c4ea763056ffe0e2d63836f771a8c294b3de06d09480538316b13", size = 83765 }, - { url = "https://files.pythonhosted.org/packages/9a/3e/8c8bcb19d6a61a7e91cf9209e2c7349572125496e4d4de205dcad5b11753/yarl-1.14.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:fc2c80bc87fba076e6cbb926216c27fba274dae7100a7b9a0983b53132dd99f2", size = 136002 }, - { url = "https://files.pythonhosted.org/packages/34/07/23fe08dfc56651ec1d77643b4df5ad41d4a1fc4f24fd066b182c660620f9/yarl-1.14.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:55c144d363ad4626ca744556c049c94e2b95096041ac87098bb363dcc8635e8d", size = 88223 }, - { url = "https://files.pythonhosted.org/packages/f2/dc/daa1b58bb858f3ce32ca9aaeb6011d7535af01d5c0f5e6b52aa698c608e3/yarl-1.14.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:b03384eed107dbeb5f625a99dc3a7de8be04fc8480c9ad42fccbc73434170b20", size = 85967 }, - { url = "https://files.pythonhosted.org/packages/6e/05/7461a7005bd2e969746a3f5218b876a414e4b2d9929b797afd157cd27c29/yarl-1.14.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f72a0d746d38cb299b79ce3d4d60ba0892c84bbc905d0d49c13df5bace1b65f8", size = 325031 }, - { url = "https://files.pythonhosted.org/packages/15/c2/54a710b97e14f99d36f82e574c8749b93ad881df120ed791fdcd1f2e1989/yarl-1.14.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8648180b34faaea4aa5b5ca7e871d9eb1277033fa439693855cf0ea9195f85f1", size = 334314 }, - { url = "https://files.pythonhosted.org/packages/60/24/6015e5a365ef6cab2d00058895cea37fe796936f04266de83b434f9a9a2e/yarl-1.14.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:9557c9322aaa33174d285b0c1961fb32499d65ad1866155b7845edc876c3c835", size = 333516 }, - { url = "https://files.pythonhosted.org/packages/3d/4d/9a369945088ac7141dc9ca2fae6a10bd205f0ea8a925996ec465d3afddcd/yarl-1.14.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8f50eb3837012a937a2b649ec872b66ba9541ad9d6f103ddcafb8231cfcafd22", size = 329437 }, - { url = "https://files.pythonhosted.org/packages/b1/38/a71b7a7a8a95d3727075472ab4b88e2d0f3223b649bcb233f6022c42593d/yarl-1.14.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8892fa575ac9b1b25fae7b221bc4792a273877b9b56a99ee2d8d03eeb3dbb1d2", size = 316742 }, - { url = "https://files.pythonhosted.org/packages/02/e7/b3baf612d964b4abd492594a51e75ba5cd08243a834cbc21e1013c8ac229/yarl-1.14.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:e6a2c5c5bb2556dfbfffffc2bcfb9c235fd2b566d5006dfb2a37afc7e3278a07", size = 330168 }, - { url = "https://files.pythonhosted.org/packages/1a/a0/896eb6007cc54347f4097e8c2f31e3907de262ced9c3f56866d8dd79a8ff/yarl-1.14.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:ab3abc0b78a5dfaa4795a6afbe7b282b6aa88d81cf8c1bb5e394993d7cae3457", size = 331898 }, - { url = "https://files.pythonhosted.org/packages/1a/73/94ee96a0e8518c7efee84e745567770371add4af65466c38d3646df86f1f/yarl-1.14.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:47eede5d11d669ab3759b63afb70d28d5328c14744b8edba3323e27dc52d298d", size = 343316 }, - { url = "https://files.pythonhosted.org/packages/68/6e/4cf1b32b3605fa4ce263ea338852e89e9959affaffb38eb1a7057d0a95f1/yarl-1.14.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:fe4d2536c827f508348d7b40c08767e8c7071614250927233bf0c92170451c0a", size = 351596 }, - { url = "https://files.pythonhosted.org/packages/16/e7/1ec09b0977e3a4a0a80e319aa30359bd4f8beb543527d8ddf9a2e799541e/yarl-1.14.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:0fd7b941dd1b00b5f0acb97455fea2c4b7aac2dd31ea43fb9d155e9bc7b78664", size = 343016 }, - { url = "https://files.pythonhosted.org/packages/de/d0/a2502a37555251c7e10df51eb425f1892f3b2acb6fa598348b96f74f3566/yarl-1.14.0-cp312-cp312-win32.whl", hash = "sha256:99ff3744f5fe48288be6bc402533b38e89749623a43208e1d57091fc96b783b9", size = 77322 }, - { url = "https://files.pythonhosted.org/packages/c0/1f/201f46e02dd074ff36ce7cd764bb8241a19f94ba88adfd6d410cededca13/yarl-1.14.0-cp312-cp312-win_amd64.whl", hash = "sha256:1ca3894e9e9f72da93544f64988d9c052254a338a9f855165f37f51edb6591de", size = 83589 }, - { url = "https://files.pythonhosted.org/packages/fd/37/6c30afb708ab45f3da32229c77d9a25dfc8ead2ae3ec1f1ea9425172d070/yarl-1.14.0-py3-none-any.whl", hash = "sha256:c8ed4034f0765f8861620c1f2f2364d2e58520ea288497084dae880424fc0d9f", size = 38166 }, + { url = "https://files.pythonhosted.org/packages/d2/98/e005bc608765a8a5569f58e650961314873c8469c333616eb40bff19ae97/yarl-1.18.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7df647e8edd71f000a5208fe6ff8c382a1de8edfbccdbbfe649d263de07d8c34", size = 141458 }, + { url = "https://files.pythonhosted.org/packages/df/5d/f8106b263b8ae8a866b46d9be869ac01f9b3fb7f2325f3ecb3df8003f796/yarl-1.18.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c69697d3adff5aa4f874b19c0e4ed65180ceed6318ec856ebc423aa5850d84f7", size = 94365 }, + { url = "https://files.pythonhosted.org/packages/56/3e/d8637ddb9ba69bf851f765a3ee288676f7cf64fb3be13760c18cbc9d10bd/yarl-1.18.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:602d98f2c2d929f8e697ed274fbadc09902c4025c5a9963bf4e9edfc3ab6f7ed", size = 92181 }, + { url = "https://files.pythonhosted.org/packages/76/f9/d616a5c2daae281171de10fba41e1c0e2d8207166fc3547252f7d469b4e1/yarl-1.18.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c654d5207c78e0bd6d749f6dae1dcbbfde3403ad3a4b11f3c5544d9906969dde", size = 315349 }, + { url = "https://files.pythonhosted.org/packages/bb/b4/3ea5e7b6f08f698b3769a06054783e434f6d59857181b5c4e145de83f59b/yarl-1.18.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5094d9206c64181d0f6e76ebd8fb2f8fe274950a63890ee9e0ebfd58bf9d787b", size = 330494 }, + { url = "https://files.pythonhosted.org/packages/55/f1/e0fc810554877b1b67420568afff51b967baed5b53bcc983ab164eebf9c9/yarl-1.18.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:35098b24e0327fc4ebdc8ffe336cee0a87a700c24ffed13161af80124b7dc8e5", size = 326927 }, + { url = "https://files.pythonhosted.org/packages/a9/42/b1753949b327b36f210899f2dd0a0947c0c74e42a32de3f8eb5c7d93edca/yarl-1.18.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3236da9272872443f81fedc389bace88408f64f89f75d1bdb2256069a8730ccc", size = 319703 }, + { url = "https://files.pythonhosted.org/packages/f0/6d/e87c62dc9635daefb064b56f5c97df55a2e9cc947a2b3afd4fd2f3b841c7/yarl-1.18.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e2c08cc9b16f4f4bc522771d96734c7901e7ebef70c6c5c35dd0f10845270bcd", size = 310246 }, + { url = "https://files.pythonhosted.org/packages/e3/ef/e2e8d1785cdcbd986f7622d7f0098205f3644546da7919c24b95790ec65a/yarl-1.18.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:80316a8bd5109320d38eef8833ccf5f89608c9107d02d2a7f985f98ed6876990", size = 319730 }, + { url = "https://files.pythonhosted.org/packages/fc/15/8723e22345bc160dfde68c4b3ae8b236e868f9963c74015f1bc8a614101c/yarl-1.18.3-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:c1e1cc06da1491e6734f0ea1e6294ce00792193c463350626571c287c9a704db", size = 321681 }, + { url = "https://files.pythonhosted.org/packages/86/09/bf764e974f1516efa0ae2801494a5951e959f1610dd41edbfc07e5e0f978/yarl-1.18.3-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:fea09ca13323376a2fdfb353a5fa2e59f90cd18d7ca4eaa1fd31f0a8b4f91e62", size = 324812 }, + { url = "https://files.pythonhosted.org/packages/f6/4c/20a0187e3b903c97d857cf0272d687c1b08b03438968ae8ffc50fe78b0d6/yarl-1.18.3-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:e3b9fd71836999aad54084906f8663dffcd2a7fb5cdafd6c37713b2e72be1760", size = 337011 }, + { url = "https://files.pythonhosted.org/packages/c9/71/6244599a6e1cc4c9f73254a627234e0dad3883ece40cc33dce6265977461/yarl-1.18.3-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:757e81cae69244257d125ff31663249b3013b5dc0a8520d73694aed497fb195b", size = 338132 }, + { url = "https://files.pythonhosted.org/packages/af/f5/e0c3efaf74566c4b4a41cb76d27097df424052a064216beccae8d303c90f/yarl-1.18.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:b1771de9944d875f1b98a745bc547e684b863abf8f8287da8466cf470ef52690", size = 331849 }, + { url = "https://files.pythonhosted.org/packages/8a/b8/3d16209c2014c2f98a8f658850a57b716efb97930aebf1ca0d9325933731/yarl-1.18.3-cp310-cp310-win32.whl", hash = "sha256:8874027a53e3aea659a6d62751800cf6e63314c160fd607489ba5c2edd753cf6", size = 84309 }, + { url = "https://files.pythonhosted.org/packages/fd/b7/2e9a5b18eb0fe24c3a0e8bae994e812ed9852ab4fd067c0107fadde0d5f0/yarl-1.18.3-cp310-cp310-win_amd64.whl", hash = "sha256:93b2e109287f93db79210f86deb6b9bbb81ac32fc97236b16f7433db7fc437d8", size = 90484 }, + { url = "https://files.pythonhosted.org/packages/40/93/282b5f4898d8e8efaf0790ba6d10e2245d2c9f30e199d1a85cae9356098c/yarl-1.18.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:8503ad47387b8ebd39cbbbdf0bf113e17330ffd339ba1144074da24c545f0069", size = 141555 }, + { url = "https://files.pythonhosted.org/packages/6d/9c/0a49af78df099c283ca3444560f10718fadb8a18dc8b3edf8c7bd9fd7d89/yarl-1.18.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:02ddb6756f8f4517a2d5e99d8b2f272488e18dd0bfbc802f31c16c6c20f22193", size = 94351 }, + { url = "https://files.pythonhosted.org/packages/5a/a1/205ab51e148fdcedad189ca8dd587794c6f119882437d04c33c01a75dece/yarl-1.18.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:67a283dd2882ac98cc6318384f565bffc751ab564605959df4752d42483ad889", size = 92286 }, + { url = "https://files.pythonhosted.org/packages/ed/fe/88b690b30f3f59275fb674f5f93ddd4a3ae796c2b62e5bb9ece8a4914b83/yarl-1.18.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d980e0325b6eddc81331d3f4551e2a333999fb176fd153e075c6d1c2530aa8a8", size = 340649 }, + { url = "https://files.pythonhosted.org/packages/07/eb/3b65499b568e01f36e847cebdc8d7ccb51fff716dbda1ae83c3cbb8ca1c9/yarl-1.18.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b643562c12680b01e17239be267bc306bbc6aac1f34f6444d1bded0c5ce438ca", size = 356623 }, + { url = "https://files.pythonhosted.org/packages/33/46/f559dc184280b745fc76ec6b1954de2c55595f0ec0a7614238b9ebf69618/yarl-1.18.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c017a3b6df3a1bd45b9fa49a0f54005e53fbcad16633870104b66fa1a30a29d8", size = 354007 }, + { url = "https://files.pythonhosted.org/packages/af/ba/1865d85212351ad160f19fb99808acf23aab9a0f8ff31c8c9f1b4d671fc9/yarl-1.18.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75674776d96d7b851b6498f17824ba17849d790a44d282929c42dbb77d4f17ae", size = 344145 }, + { url = "https://files.pythonhosted.org/packages/94/cb/5c3e975d77755d7b3d5193e92056b19d83752ea2da7ab394e22260a7b824/yarl-1.18.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ccaa3a4b521b780a7e771cc336a2dba389a0861592bbce09a476190bb0c8b4b3", size = 336133 }, + { url = "https://files.pythonhosted.org/packages/19/89/b77d3fd249ab52a5c40859815765d35c91425b6bb82e7427ab2f78f5ff55/yarl-1.18.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:2d06d3005e668744e11ed80812e61efd77d70bb7f03e33c1598c301eea20efbb", size = 347967 }, + { url = "https://files.pythonhosted.org/packages/35/bd/f6b7630ba2cc06c319c3235634c582a6ab014d52311e7d7c22f9518189b5/yarl-1.18.3-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:9d41beda9dc97ca9ab0b9888cb71f7539124bc05df02c0cff6e5acc5a19dcc6e", size = 346397 }, + { url = "https://files.pythonhosted.org/packages/18/1a/0b4e367d5a72d1f095318344848e93ea70da728118221f84f1bf6c1e39e7/yarl-1.18.3-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:ba23302c0c61a9999784e73809427c9dbedd79f66a13d84ad1b1943802eaaf59", size = 350206 }, + { url = "https://files.pythonhosted.org/packages/b5/cf/320fff4367341fb77809a2d8d7fe75b5d323a8e1b35710aafe41fdbf327b/yarl-1.18.3-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:6748dbf9bfa5ba1afcc7556b71cda0d7ce5f24768043a02a58846e4a443d808d", size = 362089 }, + { url = "https://files.pythonhosted.org/packages/57/cf/aadba261d8b920253204085268bad5e8cdd86b50162fcb1b10c10834885a/yarl-1.18.3-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:0b0cad37311123211dc91eadcb322ef4d4a66008d3e1bdc404808992260e1a0e", size = 366267 }, + { url = "https://files.pythonhosted.org/packages/54/58/fb4cadd81acdee6dafe14abeb258f876e4dd410518099ae9a35c88d8097c/yarl-1.18.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:0fb2171a4486bb075316ee754c6d8382ea6eb8b399d4ec62fde2b591f879778a", size = 359141 }, + { url = "https://files.pythonhosted.org/packages/9a/7a/4c571597589da4cd5c14ed2a0b17ac56ec9ee7ee615013f74653169e702d/yarl-1.18.3-cp311-cp311-win32.whl", hash = "sha256:61b1a825a13bef4a5f10b1885245377d3cd0bf87cba068e1d9a88c2ae36880e1", size = 84402 }, + { url = "https://files.pythonhosted.org/packages/ae/7b/8600250b3d89b625f1121d897062f629883c2f45339623b69b1747ec65fa/yarl-1.18.3-cp311-cp311-win_amd64.whl", hash = "sha256:b9d60031cf568c627d028239693fd718025719c02c9f55df0a53e587aab951b5", size = 91030 }, + { url = "https://files.pythonhosted.org/packages/33/85/bd2e2729752ff4c77338e0102914897512e92496375e079ce0150a6dc306/yarl-1.18.3-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:1dd4bdd05407ced96fed3d7f25dbbf88d2ffb045a0db60dbc247f5b3c5c25d50", size = 142644 }, + { url = "https://files.pythonhosted.org/packages/ff/74/1178322cc0f10288d7eefa6e4a85d8d2e28187ccab13d5b844e8b5d7c88d/yarl-1.18.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7c33dd1931a95e5d9a772d0ac5e44cac8957eaf58e3c8da8c1414de7dd27c576", size = 94962 }, + { url = "https://files.pythonhosted.org/packages/be/75/79c6acc0261e2c2ae8a1c41cf12265e91628c8c58ae91f5ff59e29c0787f/yarl-1.18.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:25b411eddcfd56a2f0cd6a384e9f4f7aa3efee14b188de13048c25b5e91f1640", size = 92795 }, + { url = "https://files.pythonhosted.org/packages/6b/32/927b2d67a412c31199e83fefdce6e645247b4fb164aa1ecb35a0f9eb2058/yarl-1.18.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:436c4fc0a4d66b2badc6c5fc5ef4e47bb10e4fd9bf0c79524ac719a01f3607c2", size = 332368 }, + { url = "https://files.pythonhosted.org/packages/19/e5/859fca07169d6eceeaa4fde1997c91d8abde4e9a7c018e371640c2da2b71/yarl-1.18.3-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e35ef8683211db69ffe129a25d5634319a677570ab6b2eba4afa860f54eeaf75", size = 342314 }, + { url = "https://files.pythonhosted.org/packages/08/75/76b63ccd91c9e03ab213ef27ae6add2e3400e77e5cdddf8ed2dbc36e3f21/yarl-1.18.3-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84b2deecba4a3f1a398df819151eb72d29bfeb3b69abb145a00ddc8d30094512", size = 341987 }, + { url = "https://files.pythonhosted.org/packages/1a/e1/a097d5755d3ea8479a42856f51d97eeff7a3a7160593332d98f2709b3580/yarl-1.18.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:00e5a1fea0fd4f5bfa7440a47eff01d9822a65b4488f7cff83155a0f31a2ecba", size = 336914 }, + { url = "https://files.pythonhosted.org/packages/0b/42/e1b4d0e396b7987feceebe565286c27bc085bf07d61a59508cdaf2d45e63/yarl-1.18.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d0e883008013c0e4aef84dcfe2a0b172c4d23c2669412cf5b3371003941f72bb", size = 325765 }, + { url = "https://files.pythonhosted.org/packages/7e/18/03a5834ccc9177f97ca1bbb245b93c13e58e8225276f01eedc4cc98ab820/yarl-1.18.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:5a3f356548e34a70b0172d8890006c37be92995f62d95a07b4a42e90fba54272", size = 344444 }, + { url = "https://files.pythonhosted.org/packages/c8/03/a713633bdde0640b0472aa197b5b86e90fbc4c5bc05b727b714cd8a40e6d/yarl-1.18.3-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ccd17349166b1bee6e529b4add61727d3f55edb7babbe4069b5764c9587a8cc6", size = 340760 }, + { url = "https://files.pythonhosted.org/packages/eb/99/f6567e3f3bbad8fd101886ea0276c68ecb86a2b58be0f64077396cd4b95e/yarl-1.18.3-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:b958ddd075ddba5b09bb0be8a6d9906d2ce933aee81100db289badbeb966f54e", size = 346484 }, + { url = "https://files.pythonhosted.org/packages/8e/a9/84717c896b2fc6cb15bd4eecd64e34a2f0a9fd6669e69170c73a8b46795a/yarl-1.18.3-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:c7d79f7d9aabd6011004e33b22bc13056a3e3fb54794d138af57f5ee9d9032cb", size = 359864 }, + { url = "https://files.pythonhosted.org/packages/1e/2e/d0f5f1bef7ee93ed17e739ec8dbcb47794af891f7d165fa6014517b48169/yarl-1.18.3-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:4891ed92157e5430874dad17b15eb1fda57627710756c27422200c52d8a4e393", size = 364537 }, + { url = "https://files.pythonhosted.org/packages/97/8a/568d07c5d4964da5b02621a517532adb8ec5ba181ad1687191fffeda0ab6/yarl-1.18.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:ce1af883b94304f493698b00d0f006d56aea98aeb49d75ec7d98cd4a777e9285", size = 357861 }, + { url = "https://files.pythonhosted.org/packages/7d/e3/924c3f64b6b3077889df9a1ece1ed8947e7b61b0a933f2ec93041990a677/yarl-1.18.3-cp312-cp312-win32.whl", hash = "sha256:f91c4803173928a25e1a55b943c81f55b8872f0018be83e3ad4938adffb77dd2", size = 84097 }, + { url = "https://files.pythonhosted.org/packages/34/45/0e055320daaabfc169b21ff6174567b2c910c45617b0d79c68d7ab349b02/yarl-1.18.3-cp312-cp312-win_amd64.whl", hash = "sha256:7e2ee16578af3b52ac2f334c3b1f92262f47e02cc6193c598502bd46f5cd1477", size = 90399 }, + { url = "https://files.pythonhosted.org/packages/f5/4b/a06e0ec3d155924f77835ed2d167ebd3b211a7b0853da1cf8d8414d784ef/yarl-1.18.3-py3-none-any.whl", hash = "sha256:b57f4f58099328dfb26c6a771d09fb20dbbae81d20cfb66141251ea063bd101b", size = 45109 }, ] [[package]] @@ -8760,11 +8768,11 @@ wheels = [ [[package]] name = "zipp" -version = "3.20.2" +version = "3.21.0" source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/54/bf/5c0000c44ebc80123ecbdddba1f5dcd94a5ada602a9c225d84b5aaa55e86/zipp-3.20.2.tar.gz", hash = "sha256:bc9eb26f4506fda01b81bcde0ca78103b6e62f991b381fec825435c836edbc29", size = 24199 } +sdist = { url = "https://files.pythonhosted.org/packages/3f/50/bad581df71744867e9468ebd0bcd6505de3b275e06f202c2cb016e3ff56f/zipp-3.21.0.tar.gz", hash = "sha256:2c9958f6430a2040341a52eb608ed6dd93ef4392e02ffe219417c1b28b5dd1f4", size = 24545 } wheels = [ - { url = "https://files.pythonhosted.org/packages/62/8b/5ba542fa83c90e09eac972fc9baca7a88e7e7ca4b221a89251954019308b/zipp-3.20.2-py3-none-any.whl", hash = "sha256:a817ac80d6cf4b23bf7f2828b7cabf326f15a001bea8b1f9b49631780ba28350", size = 9200 }, + { url = "https://files.pythonhosted.org/packages/b7/1a/7e4798e9339adc931158c9d69ecc34f5e6791489d469f5e50ec15e35f458/zipp-3.21.0-py3-none-any.whl", hash = "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931", size = 9630 }, ] [[package]]