refactor: Update MessageInput in multiple components to remove unnecessary input_types
This commit is contained in:
ogabrielluiz
parent
35cb084728
commit
1a4491574e
16 changed files with 49 additions and 82 deletions
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@ -3,8 +3,7 @@ from langchain_community.chat_models.bedrock import BedrockChat
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from langflow.base.constants import STREAM_INFO_TEXT
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from langflow.base.models.model import LCModelComponent
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from langflow.field_typing import BaseLanguageModel, Text
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from langflow.inputs import BoolInput, DictInput, DropdownInput, StrInput
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from langflow.inputs import MessageInput
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from langflow.inputs import BoolInput, DictInput, DropdownInput, MessageInput, StrInput
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from langflow.template import Output
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@ -14,7 +13,7 @@ class AmazonBedrockComponent(LCModelComponent):
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icon = "Amazon"
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inputs = [
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MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]),
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MessageInput(name="input_value", display_name="Input"),
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DropdownInput(
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name="model_id",
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display_name="Model Id",
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@ -4,9 +4,8 @@ from pydantic.v1 import SecretStr
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from langflow.base.constants import STREAM_INFO_TEXT
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from langflow.base.models.model import LCModelComponent
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from langflow.field_typing import BaseLanguageModel, Text
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from langflow.inputs import BoolInput, DropdownInput, FloatInput, IntInput, StrInput
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from langflow.inputs import BoolInput, DropdownInput, FloatInput, IntInput, MessageInput, StrInput
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from langflow.template import Output
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from langflow.inputs import MessageInput
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class AzureChatOpenAIComponent(LCModelComponent):
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@ -66,7 +65,7 @@ class AzureChatOpenAIComponent(LCModelComponent):
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advanced=True,
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info="The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
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),
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MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]),
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MessageInput(name="input_value", display_name="Input"),
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BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True),
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StrInput(
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name="system_message",
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@ -4,10 +4,9 @@ from langchain_community.chat_models.litellm import ChatLiteLLM, ChatLiteLLMExce
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from langflow.base.constants import STREAM_INFO_TEXT
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from langflow.base.models.model import LCModelComponent
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from langflow.field_typing import BaseLanguageModel, Text
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from langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, StrInput
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from langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, MessageInput, StrInput
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from langflow.template import Output
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from langflow.template import Output
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from langflow.inputs import MessageInput
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class ChatLiteLLMModelComponent(LCModelComponent):
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@ -17,7 +16,7 @@ class ChatLiteLLMModelComponent(LCModelComponent):
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icon = "🚅"
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inputs = [
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MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]),
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MessageInput(name="input_value", display_name="Input"),
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StrInput(
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name="model",
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display_name="Model name",
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@ -4,9 +4,8 @@ from pydantic.v1 import SecretStr
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from langflow.base.constants import STREAM_INFO_TEXT
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from langflow.base.models.model import LCModelComponent
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from langflow.field_typing import BaseLanguageModel, Text
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from langflow.inputs import BoolInput, FloatInput, IntInput, SecretStrInput, StrInput
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from langflow.inputs import BoolInput, FloatInput, IntInput, MessageInput, SecretStrInput, StrInput
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from langflow.template import Output
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from langflow.inputs import MessageInput
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class CohereComponent(LCModelComponent):
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@ -30,7 +29,7 @@ class CohereComponent(LCModelComponent):
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info="The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
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),
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FloatInput(name="temperature", display_name="Temperature", value=0.75),
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MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]),
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MessageInput(name="input_value", display_name="Input"),
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BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True),
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StrInput(
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name="system_message",
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@ -4,9 +4,8 @@ from langchain_community.llms.huggingface_endpoint import HuggingFaceEndpoint
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from langflow.base.constants import STREAM_INFO_TEXT
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from langflow.base.models.model import LCModelComponent
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from langflow.field_typing import BaseLanguageModel, Text
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from langflow.inputs import BoolInput, DictInput, DropdownInput, SecretStrInput, StrInput
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from langflow.inputs import BoolInput, DictInput, DropdownInput, MessageInput, SecretStrInput, StrInput
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from langflow.template import Output
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from langflow.inputs import MessageInput
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class HuggingFaceEndpointsComponent(LCModelComponent):
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@ -15,7 +14,7 @@ class HuggingFaceEndpointsComponent(LCModelComponent):
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icon = "HuggingFace"
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inputs = [
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MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]),
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MessageInput(name="input_value", display_name="Input"),
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SecretStrInput(name="endpoint_url", display_name="Endpoint URL", password=True),
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DropdownInput(
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name="task",
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@ -4,20 +4,17 @@ from pydantic.v1 import SecretStr
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from langflow.base.constants import STREAM_INFO_TEXT
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from langflow.base.models.model import LCModelComponent
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from langflow.field_typing import BaseLanguageModel, Text
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from langflow.inputs import BoolInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput
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from langflow.inputs import BoolInput, DropdownInput, FloatInput, IntInput, MessageInput, SecretStrInput, StrInput
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from langflow.template import Output
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from langflow.inputs import MessageInput
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class MistralAIModelComponent(LCModelComponent):
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display_name = "MistralAI"
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description = "Generates text using MistralAI LLMs."
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icon = "MistralAI"
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inputs = [
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MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]),
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MessageInput(name="input_value", display_name="Input"),
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IntInput(
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name="max_tokens",
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display_name="Max Tokens",
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@ -24,7 +24,7 @@ class OpenAIModelComponent(LCModelComponent):
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icon = "OpenAI"
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inputs = [
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MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]),
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MessageInput(name="input_value", display_name="Input"),
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IntInput(
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name="max_tokens",
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display_name="Max Tokens",
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@ -13,7 +13,7 @@ class ChatVertexAIComponent(LCModelComponent):
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icon = "VertexAI"
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inputs = [
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MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]),
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MessageInput(name="input_value", display_name="Input"),
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StrInput(
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name="credentials",
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display_name="Credentials",
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@ -47,9 +47,7 @@
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"fieldName": "input_value",
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"id": "OpenAIModel-SsPHS",
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"inputTypes": [
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"Text",
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"Data",
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"Prompt"
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"Message"
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],
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"type": "str"
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}
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@ -58,7 +56,7 @@
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"source": "Prompt-3QeXa",
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"sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-3QeXaœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}",
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"target": "OpenAIModel-SsPHS",
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"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-SsPHSœ, œinputTypesœ: [œTextœ, œDataœ, œPromptœ], œtypeœ: œstrœ}"
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"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-SsPHSœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
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},
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{
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"data": {
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@ -663,7 +661,7 @@
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"show": true,
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"title_case": false,
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"type": "code",
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"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\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 ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=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. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_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 FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\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 outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\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 if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
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"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\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 ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=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. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_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 FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\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 outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\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 if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
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},
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"input_value": {
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"advanced": false,
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@ -671,9 +669,7 @@
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"dynamic": false,
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"info": "",
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"input_types": [
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"Text",
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"Data",
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"Prompt"
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"Message"
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],
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"list": false,
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"load_from_db": false,
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@ -138,9 +138,7 @@
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"fieldName": "input_value",
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"id": "OpenAIModel-gi29P",
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"inputTypes": [
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"Text",
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"Data",
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"Prompt"
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"Message"
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],
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"type": "str"
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}
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@ -153,7 +151,7 @@
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"stroke": "#555"
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},
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"target": "OpenAIModel-gi29P",
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"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-gi29Pœ, œinputTypesœ: [œTextœ, œDataœ, œPromptœ], œtypeœ: œstrœ}"
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"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-gi29Pœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
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}
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],
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"nodes": [
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@ -697,7 +695,7 @@
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"show": true,
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"title_case": false,
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"type": "code",
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"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\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 ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=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. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_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 FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\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 outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\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 if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
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"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\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 ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=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. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_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 FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\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 outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\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 if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -707,9 +705,7 @@
|
|||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
"Message"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
|
|
|
|||
|
|
@ -71,9 +71,7 @@
|
|||
"fieldName": "input_value",
|
||||
"id": "OpenAIModel-8b6nG",
|
||||
"inputTypes": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
"Message"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
|
|
@ -82,7 +80,7 @@
|
|||
"source": "Prompt-9DNZG",
|
||||
"sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-9DNZGœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}",
|
||||
"target": "OpenAIModel-8b6nG",
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-8b6nGœ, œinputTypesœ: [œTextœ, œDataœ, œPromptœ], œtypeœ: œstrœ}"
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-8b6nGœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
|
|
@ -837,7 +835,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\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 ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=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. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_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 FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\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 outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\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 if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\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 ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=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. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_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 FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\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 outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\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 if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -845,9 +843,7 @@
|
|||
"dynamic": false,
|
||||
"info": "",
|
||||
"input_types": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
"Message"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
|
|
|
|||
|
|
@ -82,9 +82,7 @@
|
|||
"fieldName": "input_value",
|
||||
"id": "OpenAIModel-9RykF",
|
||||
"inputTypes": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
"Message"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
|
|
@ -96,7 +94,7 @@
|
|||
"stroke": "#555"
|
||||
},
|
||||
"target": "OpenAIModel-9RykF",
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-9RykFœ, œinputTypesœ: [œTextœ, œDataœ, œPromptœ], œtypeœ: œstrœ}"
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-9RykFœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
|
||||
},
|
||||
{
|
||||
"className": "stroke-gray-900 stroke-connection",
|
||||
|
|
@ -967,7 +965,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\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 ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=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. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_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 FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\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 outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\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 if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\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 ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=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. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_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 FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\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 outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\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 if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -977,9 +975,7 @@
|
|||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
"Message"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
|
|
|
|||
|
|
@ -78,9 +78,7 @@
|
|||
"fieldName": "input_value",
|
||||
"id": "OpenAIModel-uYXZJ",
|
||||
"inputTypes": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
"Message"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
|
|
@ -92,7 +90,7 @@
|
|||
"stroke": "#555"
|
||||
},
|
||||
"target": "OpenAIModel-uYXZJ",
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-uYXZJœ, œinputTypesœ: [œTextœ, œDataœ, œPromptœ], œtypeœ: œstrœ}"
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-uYXZJœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
|
||||
},
|
||||
{
|
||||
"className": "stroke-gray-900 stroke-connection",
|
||||
|
|
@ -200,9 +198,7 @@
|
|||
"fieldName": "input_value",
|
||||
"id": "OpenAIModel-XawYB",
|
||||
"inputTypes": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
"Message"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
|
|
@ -214,7 +210,7 @@
|
|||
"stroke": "#555"
|
||||
},
|
||||
"target": "OpenAIModel-XawYB",
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-XawYBœ, œinputTypesœ: [œTextœ, œDataœ, œPromptœ], œtypeœ: œstrœ}"
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-XawYBœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
|
||||
},
|
||||
{
|
||||
"className": "stroke-gray-900 stroke-connection",
|
||||
|
|
@ -1167,7 +1163,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\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 ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=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. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_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 FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\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 outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\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 if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\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 ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=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. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_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 FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\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 outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\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 if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -1177,9 +1173,7 @@
|
|||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
"Message"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
|
|
@ -1584,7 +1578,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\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 ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=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. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_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 FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\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 outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\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 if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\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 ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=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. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_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 FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\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 outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\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 if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -1594,9 +1588,7 @@
|
|||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
"Message"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
|
|
|
|||
|
|
@ -82,9 +82,7 @@
|
|||
"fieldName": "input_value",
|
||||
"id": "OpenAIModel-EjXlN",
|
||||
"inputTypes": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
"Message"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
|
|
@ -97,7 +95,7 @@
|
|||
"stroke": "#555"
|
||||
},
|
||||
"target": "OpenAIModel-EjXlN",
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-EjXlNœ, œinputTypesœ: [œTextœ, œDataœ, œPromptœ], œtypeœ: œstrœ}"
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-EjXlNœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
|
||||
},
|
||||
{
|
||||
"className": "stroke-gray-900 stroke-connection",
|
||||
|
|
@ -1078,7 +1076,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\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 ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=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. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_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 FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\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 outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\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 if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\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 ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=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. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_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 FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\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 outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\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 if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -1088,9 +1086,7 @@
|
|||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
"Message"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
|
|
|
|||
|
|
@ -19,8 +19,11 @@ def get_artifact_type(value, build_result=None) -> str:
|
|||
result = ArtifactType.UNKNOWN
|
||||
match value:
|
||||
case Message():
|
||||
enum_value = get_artifact_type(value.text)
|
||||
result = ArtifactType(enum_value)
|
||||
if not isinstance(value.text, str):
|
||||
enum_value = get_artifact_type(value.text)
|
||||
result = ArtifactType(enum_value)
|
||||
else:
|
||||
result = ArtifactType.MESSAGE
|
||||
case Data():
|
||||
enum_value = get_artifact_type(value.data)
|
||||
result = ArtifactType(enum_value)
|
||||
|
|
|
|||
|
|
@ -201,7 +201,7 @@ class AmazonBedrockComponent(LCModelComponent):
|
|||
icon = "Amazon"
|
||||
|
||||
inputs = [
|
||||
MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]),
|
||||
MessageInput(name="input_value", display_name="Input"),
|
||||
DropdownInput(
|
||||
name="model_id",
|
||||
display_name="Model Id",
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue