fix: update type to silence warning and memory chatbot json (#3265)
* fix: update value type in DefaultPromptField from str to Any for increased flexibility in input handling * fix: replace _instantiate_input with instantiate_input for consistency in input instantiation across the codebase * chore: update test durations * update memory chatbot
This commit is contained in:
Gabriel Luiz Freitas Almeida
GitHub
parent
0eb694f1d7
commit
9da2c34551
5 changed files with 369 additions and 361 deletions
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@ -1039,7 +1039,7 @@
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"show": true,
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"show": true,
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"title_case": false,
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"title_case": false,
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"type": "code",
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"type": "code",
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"value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.inputs import HandleInput\nfrom langflow.io import DropdownInput, IntInput, MessageTextInput, MultilineInput, Output\nfrom langflow.memory import get_messages, LCBuiltinChatMemory\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\nfrom langflow.field_typing import BaseChatMemory\nfrom langchain.memory import ConversationBufferMemory\n\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_USER\n\n\nclass MemoryComponent(Component):\n display_name = \"Chat Memory\"\n description = \"Retrieves stored chat messages from Langflow tables or an external memory.\"\n icon = \"message-square-more\"\n name = \"Memory\"\n\n inputs = [\n HandleInput(\n name=\"memory\",\n display_name=\"External Memory\",\n input_types=[\"BaseChatMessageHistory\"],\n info=\"Retrieve messages from an external memory. If empty, it will use the Langflow tables.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER, \"Machine and User\"],\n value=\"Machine and User\",\n info=\"Filter by sender type.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Filter by sender name.\",\n advanced=True,\n ),\n IntInput(\n name=\"n_messages\",\n display_name=\"Number of Messages\",\n value=100,\n info=\"Number of messages to retrieve.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"order\",\n display_name=\"Order\",\n options=[\"Ascending\", \"Descending\"],\n value=\"Ascending\",\n info=\"Order of the messages.\",\n advanced=True,\n ),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.\",\n value=\"{sender_name}: {text}\",\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Messages (Data)\", name=\"messages\", method=\"retrieve_messages\"),\n Output(display_name=\"Messages (Text)\", name=\"messages_text\", method=\"retrieve_messages_as_text\"),\n Output(display_name=\"Memory\", name=\"lc_memory\", method=\"build_lc_memory\"),\n ]\n\n def retrieve_messages(self) -> Data:\n sender = self.sender\n sender_name = self.sender_name\n session_id = self.session_id\n n_messages = self.n_messages\n order = \"DESC\" if self.order == \"Descending\" else \"ASC\"\n\n if sender == \"Machine and User\":\n sender = None\n\n if self.memory:\n # override session_id\n self.memory.session_id = session_id\n\n stored = self.memory.messages\n # langchain memories are supposed to return messages in ascending order\n if order == \"DESC\":\n stored = stored[::-1]\n if n_messages:\n stored = stored[:n_messages]\n stored = [Message.from_lc_message(m) for m in stored]\n if sender:\n expected_type = MESSAGE_SENDER_AI if sender == MESSAGE_SENDER_AI else MESSAGE_SENDER_USER\n stored = [m for m in stored if m.type == expected_type]\n else:\n stored = get_messages(\n sender=sender,\n sender_name=sender_name,\n session_id=session_id,\n limit=n_messages,\n order=order,\n )\n self.status = stored\n return stored\n\n def retrieve_messages_as_text(self) -> Message:\n stored_text = data_to_text(self.template, self.retrieve_messages())\n self.status = stored_text\n return Message(text=stored_text)\n\n def build_lc_memory(self) -> BaseChatMemory:\n if self.memory:\n chat_memory = self.memory\n else:\n chat_memory = LCBuiltinChatMemory(flow_id=self.graph.flow_id, session_id=self.session_id)\n return ConversationBufferMemory(chat_memory=chat_memory)\n"
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"value": "from langchain.memory import ConversationBufferMemory\n\nfrom langflow.custom import Component\nfrom langflow.field_typing import BaseChatMemory\nfrom langflow.helpers.data import data_to_text\nfrom langflow.inputs import HandleInput\nfrom langflow.io import DropdownInput, IntInput, MessageTextInput, MultilineInput, Output\nfrom langflow.memory import LCBuiltinChatMemory, get_messages\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import MESSAGE_SENDER_AI, MESSAGE_SENDER_USER\n\n\nclass MemoryComponent(Component):\n display_name = \"Chat Memory\"\n description = \"Retrieves stored chat messages from Langflow tables or an external memory.\"\n icon = \"message-square-more\"\n name = \"Memory\"\n\n inputs = [\n HandleInput(\n name=\"memory\",\n display_name=\"External Memory\",\n input_types=[\"BaseChatMessageHistory\"],\n info=\"Retrieve messages from an external memory. If empty, it will use the Langflow tables.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER, \"Machine and User\"],\n value=\"Machine and User\",\n info=\"Filter by sender type.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Filter by sender name.\",\n advanced=True,\n ),\n IntInput(\n name=\"n_messages\",\n display_name=\"Number of Messages\",\n value=100,\n info=\"Number of messages to retrieve.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"order\",\n display_name=\"Order\",\n options=[\"Ascending\", \"Descending\"],\n value=\"Ascending\",\n info=\"Order of the messages.\",\n advanced=True,\n ),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.\",\n value=\"{sender_name}: {text}\",\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Messages (Data)\", name=\"messages\", method=\"retrieve_messages\"),\n Output(display_name=\"Messages (Text)\", name=\"messages_text\", method=\"retrieve_messages_as_text\"),\n Output(display_name=\"Memory\", name=\"lc_memory\", method=\"build_lc_memory\"),\n ]\n\n def retrieve_messages(self) -> Data:\n sender = self.sender\n sender_name = self.sender_name\n session_id = self.session_id\n n_messages = self.n_messages\n order = \"DESC\" if self.order == \"Descending\" else \"ASC\"\n\n if sender == \"Machine and User\":\n sender = None\n\n if self.memory:\n # override session_id\n self.memory.session_id = session_id\n\n stored = self.memory.messages\n # langchain memories are supposed to return messages in ascending order\n if order == \"DESC\":\n stored = stored[::-1]\n if n_messages:\n stored = stored[:n_messages]\n stored = [Message.from_lc_message(m) for m in stored]\n if sender:\n expected_type = MESSAGE_SENDER_AI if sender == MESSAGE_SENDER_AI else MESSAGE_SENDER_USER\n stored = [m for m in stored if m.type == expected_type]\n else:\n stored = get_messages(\n sender=sender,\n sender_name=sender_name,\n session_id=session_id,\n limit=n_messages,\n order=order,\n )\n self.status = stored\n return stored\n\n def retrieve_messages_as_text(self) -> Message:\n stored_text = data_to_text(self.template, self.retrieve_messages())\n self.status = stored_text\n return Message(text=stored_text)\n\n def build_lc_memory(self) -> BaseChatMemory:\n if self.memory:\n chat_memory = self.memory\n else:\n chat_memory = LCBuiltinChatMemory(flow_id=self.flow_id, session_id=self.session_id)\n return ConversationBufferMemory(chat_memory=chat_memory)\n"
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},
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},
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"memory": {
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"memory": {
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"advanced": false,
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"advanced": false,
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@ -471,7 +471,7 @@ class DefaultPromptField(Input):
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advanced: bool = False
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advanced: bool = False
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multiline: bool = True
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multiline: bool = True
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input_types: list[str] = DEFAULT_PROMPT_INTUT_TYPES
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input_types: list[str] = DEFAULT_PROMPT_INTUT_TYPES
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value: str = "" # Set the value to empty string
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value: Any = "" # Set the value to empty string
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InputTypes = Union[
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InputTypes = Union[
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@ -500,7 +500,7 @@ InputTypes = Union[
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InputTypesMap: dict[str, type[InputTypes]] = {t.__name__: t for t in get_args(InputTypes)}
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InputTypesMap: dict[str, type[InputTypes]] = {t.__name__: t for t in get_args(InputTypes)}
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def _instantiate_input(input_type: str, data: dict) -> InputTypes:
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def instantiate_input(input_type: str, data: dict) -> InputTypes:
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input_type_class = InputTypesMap.get(input_type)
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input_type_class = InputTypesMap.get(input_type)
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if "type" in data:
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if "type" in data:
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# Replate with field_type
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# Replate with field_type
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@ -2,7 +2,7 @@ from typing import Callable, Union, cast
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from pydantic import BaseModel, Field, model_serializer
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from pydantic import BaseModel, Field, model_serializer
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from langflow.inputs.inputs import InputTypes, _instantiate_input
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from langflow.inputs.inputs import InputTypes, instantiate_input
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from langflow.template.field.base import Input
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from langflow.template.field.base import Input
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from langflow.utils.constants import DIRECT_TYPES
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from langflow.utils.constants import DIRECT_TYPES
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@ -48,7 +48,7 @@ class Template(BaseModel):
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input_type = value.pop("_input_type", None)
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input_type = value.pop("_input_type", None)
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if input_type:
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if input_type:
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try:
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try:
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_input = _instantiate_input(input_type, value)
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_input = instantiate_input(input_type, value)
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except Exception as e:
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except Exception as e:
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raise ValueError(f"Error instantiating input {input_type}: {e}")
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raise ValueError(f"Error instantiating input {input_type}: {e}")
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else:
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else:
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@ -1,354 +1,362 @@
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{
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{
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"src/backend/tests/test_endpoints.py::test_build_vertex_invalid_flow_id": 3.1494096249807626,
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"src/backend/tests/test_endpoints.py::test_build_vertex_invalid_flow_id": 1.8161861660000795,
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"src/backend/tests/test_endpoints.py::test_build_vertex_invalid_vertex_id": 3.0606157919974066,
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"src/backend/tests/test_endpoints.py::test_build_vertex_invalid_vertex_id": 1.6184064170001875,
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"src/backend/tests/test_endpoints.py::test_get_all": 10.10167008501594,
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"src/backend/tests/test_endpoints.py::test_get_all": 3.8724166670003797,
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"src/backend/tests/test_endpoints.py::test_get_vertices": 4.5017141660209745,
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"src/backend/tests/test_endpoints.py::test_get_vertices": 2.3527110839995657,
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"src/backend/tests/test_endpoints.py::test_get_vertices_flow_not_found": 3.7886676250200253,
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"src/backend/tests/test_endpoints.py::test_get_vertices_flow_not_found": 1.781084457999441,
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"src/backend/tests/test_endpoints.py::test_invalid_flow_id": 4.073716707964195,
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"src/backend/tests/test_endpoints.py::test_invalid_flow_id": 1.8902806239998426,
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"src/backend/tests/test_endpoints.py::test_invalid_prompt": 2.7002592499775346,
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"src/backend/tests/test_endpoints.py::test_invalid_prompt": 1.104316251000455,
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"src/backend/tests/test_endpoints.py::test_invalid_run_with_input_type_chat": 2.987766916019609,
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"src/backend/tests/test_endpoints.py::test_invalid_run_with_input_type_chat": 1.7665630830001646,
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"src/backend/tests/test_endpoints.py::test_post_validate_code": 3.0467621669813525,
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"src/backend/tests/test_endpoints.py::test_post_validate_code": 1.2675197489998027,
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"src/backend/tests/test_endpoints.py::test_successful_run_with_input_type_any": 14.8548604179814,
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"src/backend/tests/test_endpoints.py::test_successful_run_with_input_type_any": 4.90430141699926,
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"src/backend/tests/test_endpoints.py::test_successful_run_with_input_type_chat": 6.242352208995726,
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"src/backend/tests/test_endpoints.py::test_successful_run_with_input_type_chat": 5.548072499999762,
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"src/backend/tests/test_endpoints.py::test_successful_run_with_input_type_text": 5.7594154170074034,
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"src/backend/tests/test_endpoints.py::test_successful_run_with_input_type_text": 6.992585209000026,
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"src/backend/tests/test_endpoints.py::test_successful_run_with_output_type_any": 7.347130999987712,
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"src/backend/tests/test_endpoints.py::test_successful_run_with_output_type_any": 6.90225587499981,
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"src/backend/tests/test_endpoints.py::test_successful_run_with_output_type_debug": 6.291947416990297,
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"src/backend/tests/test_endpoints.py::test_successful_run_with_output_type_debug": 6.666685292999773,
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"src/backend/tests/test_endpoints.py::test_successful_run_with_output_type_text": 14.872085083043203,
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"src/backend/tests/test_endpoints.py::test_successful_run_with_output_type_text": 6.525266874999943,
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"src/backend/tests/test_endpoints.py::test_valid_prompt": 2.7850471249839757,
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"src/backend/tests/test_endpoints.py::test_valid_prompt": 1.0876984590004213,
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"src/backend/tests/test_endpoints.py::test_various_prompts[The weather is {weather} today.-expected_input_variables1]": 2.535564499994507,
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"src/backend/tests/test_endpoints.py::test_various_prompts[The weather is {weather} today.-expected_input_variables1]": 1.0912359599997217,
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"src/backend/tests/test_endpoints.py::test_various_prompts[This prompt has no variables.-expected_input_variables2]": 9.15231529099401,
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"src/backend/tests/test_endpoints.py::test_various_prompts[This prompt has no variables.-expected_input_variables2]": 1.0882312500002627,
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"src/backend/tests/test_endpoints.py::test_various_prompts[{a}, {b}, and {c} are variables.-expected_input_variables3]": 2.640623040992068,
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"src/backend/tests/test_endpoints.py::test_various_prompts[{a}, {b}, and {c} are variables.-expected_input_variables3]": 1.1277481249994707,
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"src/backend/tests/test_endpoints.py::test_various_prompts[{color} is my favorite color.-expected_input_variables0]": 2.079908042011084,
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"src/backend/tests/test_endpoints.py::test_various_prompts[{color} is my favorite color.-expected_input_variables0]": 1.2742332080001688,
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"src/backend/tests/test_messages_endpoints.py::test_delete_messages": 2.515260499989381,
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"src/backend/tests/test_messages_endpoints.py::test_delete_messages": 1.5091020420009045,
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"src/backend/tests/test_messages_endpoints.py::test_delete_messages_session": 2.3651068749895785,
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"src/backend/tests/test_messages_endpoints.py::test_delete_messages_session": 1.510577208000086,
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"src/backend/tests/test_messages_endpoints.py::test_update_message": 2.5627032090269495,
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"src/backend/tests/test_messages_endpoints.py::test_update_message": 1.5425646240005335,
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"src/backend/tests/test_messages_endpoints.py::test_update_message_not_found": 3.504595792008331,
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"src/backend/tests/test_messages_endpoints.py::test_update_message_not_found": 1.5310995830000138,
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"src/backend/tests/test_schema.py::TestInput::test_field_type_str": 0.0005162910092622042,
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"src/backend/tests/test_schema.py::TestInput::test_field_type_str": 0.00023554100016554003,
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"src/backend/tests/test_schema.py::TestInput::test_field_type_type": 0.0002682080084923655,
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"src/backend/tests/test_schema.py::TestInput::test_field_type_type": 0.00021875100037505035,
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"src/backend/tests/test_schema.py::TestInput::test_input_to_dict": 0.0003857500269077718,
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"src/backend/tests/test_schema.py::TestInput::test_input_to_dict": 0.00020670800040534232,
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"src/backend/tests/test_schema.py::TestInput::test_invalid_field_type": 0.00031291699269786477,
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"src/backend/tests/test_schema.py::TestInput::test_invalid_field_type": 0.00023608299989064108,
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"src/backend/tests/test_schema.py::TestInput::test_post_process_type_function": 0.0005505419976543635,
|
"src/backend/tests/test_schema.py::TestInput::test_post_process_type_function": 0.00020749999976032996,
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||||||
"src/backend/tests/test_schema.py::TestInput::test_serialize_field_type": 0.0002683750062715262,
|
"src/backend/tests/test_schema.py::TestInput::test_serialize_field_type": 0.0001787500000318687,
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"src/backend/tests/test_schema.py::TestInput::test_validate_type_class": 0.0003414590028114617,
|
"src/backend/tests/test_schema.py::TestInput::test_validate_type_class": 0.00018495699941922794,
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"src/backend/tests/test_schema.py::TestInput::test_validate_type_string": 0.0002427089784760028,
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"src/backend/tests/test_schema.py::TestInput::test_validate_type_string": 0.00019104300008621067,
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"src/backend/tests/test_schema.py::TestOutput::test_output_add_types": 0.000245749979512766,
|
"src/backend/tests/test_schema.py::TestOutput::test_output_add_types": 0.00017562499988343916,
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"src/backend/tests/test_schema.py::TestOutput::test_output_default": 0.00026183397858403623,
|
"src/backend/tests/test_schema.py::TestOutput::test_output_default": 0.00018087499984176247,
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"src/backend/tests/test_schema.py::TestOutput::test_output_set_selected": 0.0003107920056208968,
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"src/backend/tests/test_schema.py::TestOutput::test_output_set_selected": 0.00019041600035052397,
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"src/backend/tests/test_schema.py::TestOutput::test_output_to_dict": 0.0004964589898008853,
|
"src/backend/tests/test_schema.py::TestOutput::test_output_to_dict": 0.00018754199982140562,
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"src/backend/tests/test_schema.py::TestOutput::test_output_validate_display_name": 0.0005334159650374204,
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"src/backend/tests/test_schema.py::TestOutput::test_output_validate_display_name": 0.00018495800031814724,
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"src/backend/tests/test_schema.py::TestOutput::test_output_validate_model": 0.00029370796983130276,
|
"src/backend/tests/test_schema.py::TestOutput::test_output_validate_model": 0.00020916699941153638,
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"src/backend/tests/test_schema.py::TestPostProcessType::test_custom_type": 0.001362041017273441,
|
"src/backend/tests/test_schema.py::TestPostProcessType::test_custom_type": 0.00018125099950339063,
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||||||
"src/backend/tests/test_schema.py::TestPostProcessType::test_int_type": 0.00023837501066736877,
|
"src/backend/tests/test_schema.py::TestPostProcessType::test_int_type": 0.0001939999992828234,
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"src/backend/tests/test_schema.py::TestPostProcessType::test_list_custom_type": 0.004543458024272695,
|
"src/backend/tests/test_schema.py::TestPostProcessType::test_list_custom_type": 0.00017420900030629127,
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"src/backend/tests/test_schema.py::TestPostProcessType::test_list_int_type": 0.0002362079976592213,
|
"src/backend/tests/test_schema.py::TestPostProcessType::test_list_int_type": 0.00018208300025435165,
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"src/backend/tests/test_schema.py::TestPostProcessType::test_union_custom_type": 0.0005842499958816916,
|
"src/backend/tests/test_schema.py::TestPostProcessType::test_union_custom_type": 0.00019349999956830288,
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"src/backend/tests/test_schema.py::TestPostProcessType::test_union_type": 0.003973040962591767,
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"src/backend/tests/test_schema.py::TestPostProcessType::test_union_type": 0.00017558299941811129,
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"src/backend/tests/test_user.py::test_add_user": 3.298028166987933,
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"src/backend/tests/test_user.py::test_add_user": 1.7881504160000077,
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"src/backend/tests/test_user.py::test_data_consistency_after_delete": 10.030325876054121,
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"src/backend/tests/test_user.py::test_data_consistency_after_delete": 1.5578057500001705,
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"src/backend/tests/test_user.py::test_data_consistency_after_update": 2.9754588740179315,
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"src/backend/tests/test_user.py::test_data_consistency_after_update": 1.7415219580002486,
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"src/backend/tests/test_user.py::test_deactivated_user_cannot_access": 3.544328290998237,
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"src/backend/tests/test_user.py::test_deactivated_user_cannot_access": 1.7204212500000722,
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"src/backend/tests/test_user.py::test_deactivated_user_cannot_login": 3.9071091239748057,
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"src/backend/tests/test_user.py::test_deactivated_user_cannot_login": 1.3222801250003613,
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"src/backend/tests/test_user.py::test_delete_user": 4.161238500004401,
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"src/backend/tests/test_user.py::test_delete_user": 1.5755463759996928,
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"src/backend/tests/test_user.py::test_delete_user_wrong_id": 2.7632550839625765,
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"src/backend/tests/test_user.py::test_delete_user_wrong_id": 2.0808037919996423,
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|
"src/backend/tests/unit/test_telemetry.py::test_gauge": 1.081740833999902,
|
||||||
"src/backend/tests/unit/test_telemetry.py::test_gauge_with_historgram_method": 2.6113254159863573,
|
"src/backend/tests/unit/test_telemetry.py::test_gauge_with_counter_method": 1.056230042000152,
|
||||||
"src/backend/tests/unit/test_telemetry.py::test_gauge_with_up_down_counter_method": 2.225708084035432,
|
"src/backend/tests/unit/test_telemetry.py::test_gauge_with_historgram_method": 1.110880250000264,
|
||||||
"src/backend/tests/unit/test_telemetry.py::test_increment_counter": 2.130592000001343,
|
"src/backend/tests/unit/test_telemetry.py::test_gauge_with_up_down_counter_method": 1.1089114589999554,
|
||||||
"src/backend/tests/unit/test_telemetry.py::test_increment_counter_empty_label": 2.2976541249954607,
|
"src/backend/tests/unit/test_telemetry.py::test_increment_counter": 1.091222834000746,
|
||||||
"src/backend/tests/unit/test_telemetry.py::test_increment_counter_missing_mandatory_label": 2.443581625993829,
|
"src/backend/tests/unit/test_telemetry.py::test_increment_counter_empty_label": 1.0598395000001801,
|
||||||
"src/backend/tests/unit/test_telemetry.py::test_increment_counter_unregisted_metric": 2.630037208989961,
|
"src/backend/tests/unit/test_telemetry.py::test_increment_counter_missing_mandatory_label": 1.0523453739997422,
|
||||||
"src/backend/tests/unit/test_telemetry.py::test_init": 2.1476573330292013,
|
"src/backend/tests/unit/test_telemetry.py::test_increment_counter_unregisted_metric": 1.060642084000392,
|
||||||
"src/backend/tests/unit/test_telemetry.py::test_missing_labels": 2.3570764580217656,
|
"src/backend/tests/unit/test_telemetry.py::test_init": 1.0586442910002916,
|
||||||
"src/backend/tests/unit/test_telemetry.py::test_multithreaded_singleton": 2.390594750002492,
|
"src/backend/tests/unit/test_telemetry.py::test_missing_labels": 1.0542013740000584,
|
||||||
"src/backend/tests/unit/test_telemetry.py::test_multithreaded_singleton_race_condition": 2.437567832006607,
|
"src/backend/tests/unit/test_telemetry.py::test_multithreaded_singleton": 1.0596915410001202,
|
||||||
"src/backend/tests/unit/test_telemetry.py::test_opentelementry_singleton": 3.0913529580284376,
|
"src/backend/tests/unit/test_telemetry.py::test_multithreaded_singleton_race_condition": 1.078360167000028,
|
||||||
"src/backend/tests/unit/test_template.py::test_build_template_from_function": 2.9347434579976834,
|
"src/backend/tests/unit/test_telemetry.py::test_opentelementry_singleton": 1.0586542500004725,
|
||||||
"src/backend/tests/unit/test_template.py::test_get_base_classes": 2.118878333014436,
|
"src/backend/tests/unit/test_template.py::test_build_template_from_function": 1.0667507910002314,
|
||||||
"src/backend/tests/unit/test_template.py::test_get_default_factory": 2.143760042003123,
|
"src/backend/tests/unit/test_template.py::test_get_base_classes": 1.0488440839994837,
|
||||||
"src/backend/tests/unit/test_validate_code.py::test_create_function": 2.2330028339929413,
|
"src/backend/tests/unit/test_template.py::test_get_default_factory": 1.061691208999946,
|
||||||
"src/backend/tests/unit/test_validate_code.py::test_execute_function_missing_function": 1.7509510009840596,
|
"src/backend/tests/unit/test_validate_code.py::test_create_function": 3.7202681249996203,
|
||||||
"src/backend/tests/unit/test_validate_code.py::test_execute_function_missing_module": 1.850503541965736,
|
"src/backend/tests/unit/test_validate_code.py::test_execute_function_missing_function": 1.0697480410003664,
|
||||||
"src/backend/tests/unit/test_validate_code.py::test_execute_function_missing_schema": 1.81301379200886,
|
"src/backend/tests/unit/test_validate_code.py::test_execute_function_missing_module": 1.0638055839999652,
|
||||||
"src/backend/tests/unit/test_validate_code.py::test_execute_function_success": 2.074162457982311,
|
"src/backend/tests/unit/test_validate_code.py::test_execute_function_missing_schema": 1.0542077080003764,
|
||||||
"src/backend/tests/unit/test_validate_code.py::test_validate_code": 2.2336132919881493,
|
"src/backend/tests/unit/test_validate_code.py::test_execute_function_success": 1.0714820839998538,
|
||||||
"src/backend/tests/unit/test_version.py::test_compute_main": 2.139949625969166,
|
"src/backend/tests/unit/test_validate_code.py::test_validate_code": 1.0665104990002874,
|
||||||
"src/backend/tests/unit/test_version.py::test_version": 1.6260940420324914,
|
"src/backend/tests/unit/test_version.py::test_compute_main": 1.0618379169995933,
|
||||||
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol::password@host-protocol::password@host]": 0.0012022080190945417,
|
"src/backend/tests/unit/test_version.py::test_version": 1.0611935000001722,
|
||||||
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user:pa:ss:word@host-protocol:user:pa:ss:word@host]": 0.000848833005875349,
|
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol::password@host-protocol::password@host]": 0.0002089159997922252,
|
||||||
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user:pa@ss@word@host-protocol:user:pa%40ss%40word@host]": 0.001619456976186484,
|
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user:pa:ss:word@host-protocol:user:pa:ss:word@host]": 0.0002251249998153071,
|
||||||
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user:pass@word@host-protocol:user:pass%40word@host]": 0.000586748996283859,
|
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user:pa@ss@word@host-protocol:user:pa%40ss%40word@host]": 0.0002600429997983156,
|
||||||
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user:password@-protocol:user:password@]": 0.0025060399784706533,
|
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user:pass@word@host-protocol:user:pass%40word@host]": 0.0002567910000834672,
|
||||||
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user:password@host-protocol:user:password@host]": 0.0007859579636715353,
|
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user:password@-protocol:user:password@]": 0.0002196240002376726,
|
||||||
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user@host-protocol:user@host]": 0.0004099990183021873,
|
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user:password@host-protocol:user:password@host]": 0.0002557500001785229,
|
||||||
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[user:password@host-user:password@host]": 0.0005190849769860506
|
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user@host-protocol:user@host]": 0.00021862499943381408,
|
||||||
|
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[user:password@host-user:password@host]": 0.0002157910003006691
|
||||||
}
|
}
|
||||||
|
|
@ -20,7 +20,7 @@ from langflow.inputs.inputs import (
|
||||||
SecretStrInput,
|
SecretStrInput,
|
||||||
StrInput,
|
StrInput,
|
||||||
TableInput,
|
TableInput,
|
||||||
_instantiate_input,
|
instantiate_input,
|
||||||
)
|
)
|
||||||
from langflow.schema.message import Message
|
from langflow.schema.message import Message
|
||||||
|
|
||||||
|
|
@ -69,14 +69,14 @@ def test_message_text_input_invalid():
|
||||||
|
|
||||||
def test_instantiate_input_valid():
|
def test_instantiate_input_valid():
|
||||||
data = {"name": "valid_input", "value": "This is a string"}
|
data = {"name": "valid_input", "value": "This is a string"}
|
||||||
input_instance = _instantiate_input("StrInput", data)
|
input_instance = instantiate_input("StrInput", data)
|
||||||
assert isinstance(input_instance, StrInput)
|
assert isinstance(input_instance, StrInput)
|
||||||
assert input_instance.value == "This is a string"
|
assert input_instance.value == "This is a string"
|
||||||
|
|
||||||
|
|
||||||
def test_instantiate_input_invalid():
|
def test_instantiate_input_invalid():
|
||||||
with pytest.raises(ValueError):
|
with pytest.raises(ValueError):
|
||||||
_instantiate_input("InvalidInput", {"name": "invalid_input", "value": "This is a string"})
|
instantiate_input("InvalidInput", {"name": "invalid_input", "value": "This is a string"})
|
||||||
|
|
||||||
|
|
||||||
def test_handle_input_valid():
|
def test_handle_input_valid():
|
||||||
|
|
@ -218,8 +218,8 @@ def test_instantiate_input_comprehensive():
|
||||||
}
|
}
|
||||||
|
|
||||||
for input_type, data in valid_data.items():
|
for input_type, data in valid_data.items():
|
||||||
input_instance = _instantiate_input(input_type, data)
|
input_instance = instantiate_input(input_type, data)
|
||||||
assert isinstance(input_instance, InputTypesMap[input_type])
|
assert isinstance(input_instance, InputTypesMap[input_type])
|
||||||
|
|
||||||
with pytest.raises(ValueError):
|
with pytest.raises(ValueError):
|
||||||
_instantiate_input("InvalidInput", {"name": "invalid_input", "value": "Invalid"})
|
instantiate_input("InvalidInput", {"name": "invalid_input", "value": "Invalid"})
|
||||||
|
|
|
||||||
Loading…
Add table
Add a link
Reference in a new issue