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refactor: Update MessageInput in multiple components to remove unnecessary input_types

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This commit is contained in:
ogabrielluiz 2024-06-17 21:42:17 -03:00
commit 1a4491574e
16 changed files with 49 additions and 82 deletions
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5
src/backend/base/langflow/components/models/AmazonBedrockModel.py
View file

@ -3,8 +3,7 @@ from langchain_community.chat_models.bedrock import BedrockChat
from langflow.base.constants import STREAM_INFO_TEXT from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent from langflow.base.models.model import LCModelComponent
from langflow.field_typing import BaseLanguageModel, Text from langflow.field_typing import BaseLanguageModel, Text
from langflow.inputs import BoolInput, DictInput, DropdownInput, StrInput from langflow.inputs import BoolInput, DictInput, DropdownInput, MessageInput, StrInput
from langflow.inputs import MessageInput
from langflow.template import Output from langflow.template import Output
@ -14,7 +13,7 @@ class AmazonBedrockComponent(LCModelComponent):
icon = "Amazon" icon = "Amazon"
inputs = [ inputs = [
MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]), MessageInput(name="input_value", display_name="Input"),
DropdownInput( DropdownInput(
name="model_id", name="model_id",
display_name="Model Id", display_name="Model Id",

5
src/backend/base/langflow/components/models/AzureOpenAIModel.py
View file

@ -4,9 +4,8 @@ from pydantic.v1 import SecretStr
from langflow.base.constants import STREAM_INFO_TEXT from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent from langflow.base.models.model import LCModelComponent
from langflow.field_typing import BaseLanguageModel, Text from langflow.field_typing import BaseLanguageModel, Text
from langflow.inputs import BoolInput, DropdownInput, FloatInput, IntInput, StrInput from langflow.inputs import BoolInput, DropdownInput, FloatInput, IntInput, MessageInput, StrInput
from langflow.template import Output from langflow.template import Output
from langflow.inputs import MessageInput
class AzureChatOpenAIComponent(LCModelComponent): class AzureChatOpenAIComponent(LCModelComponent):
@ -66,7 +65,7 @@ class AzureChatOpenAIComponent(LCModelComponent):
advanced=True, advanced=True,
info="The maximum number of tokens to generate. Set to 0 for unlimited tokens.", info="The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
), ),
MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]), MessageInput(name="input_value", display_name="Input"),
BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True), BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True),
StrInput( StrInput(
name="system_message", name="system_message",

7
src/backend/base/langflow/components/models/ChatLiteLLMModel.py
View file

@ -4,10 +4,9 @@ from langchain_community.chat_models.litellm import ChatLiteLLM, ChatLiteLLMExce
from langflow.base.constants import STREAM_INFO_TEXT from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent from langflow.base.models.model import LCModelComponent
from langflow.field_typing import BaseLanguageModel, Text from langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, MessageInput, StrInput
from langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, StrInput from langflow.template import Output
from langflow.template import Output from langflow.template import Output
from langflow.inputs import MessageInput
class ChatLiteLLMModelComponent(LCModelComponent): class ChatLiteLLMModelComponent(LCModelComponent):
@ -17,7 +16,7 @@ class ChatLiteLLMModelComponent(LCModelComponent):
icon = "🚅" icon = "🚅"
inputs = [ inputs = [
MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]), MessageInput(name="input_value", display_name="Input"),
StrInput( StrInput(
name="model", name="model",
display_name="Model name", display_name="Model name",

5
src/backend/base/langflow/components/models/CohereModel.py
View file

@ -4,9 +4,8 @@ from pydantic.v1 import SecretStr
from langflow.base.constants import STREAM_INFO_TEXT from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent from langflow.base.models.model import LCModelComponent
from langflow.field_typing import BaseLanguageModel, Text from langflow.field_typing import BaseLanguageModel, Text
from langflow.inputs import BoolInput, FloatInput, IntInput, SecretStrInput, StrInput from langflow.inputs import BoolInput, FloatInput, IntInput, MessageInput, SecretStrInput, StrInput
from langflow.template import Output from langflow.template import Output
from langflow.inputs import MessageInput
class CohereComponent(LCModelComponent): class CohereComponent(LCModelComponent):
@ -30,7 +29,7 @@ class CohereComponent(LCModelComponent):
info="The maximum number of tokens to generate. Set to 0 for unlimited tokens.", info="The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
), ),
FloatInput(name="temperature", display_name="Temperature", value=0.75), FloatInput(name="temperature", display_name="Temperature", value=0.75),
MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]), MessageInput(name="input_value", display_name="Input"),
BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True), BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True),
StrInput( StrInput(
name="system_message", name="system_message",

5
src/backend/base/langflow/components/models/HuggingFaceModel.py
View file

@ -4,9 +4,8 @@ from langchain_community.llms.huggingface_endpoint import HuggingFaceEndpoint
from langflow.base.constants import STREAM_INFO_TEXT from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent from langflow.base.models.model import LCModelComponent
from langflow.field_typing import BaseLanguageModel, Text from langflow.field_typing import BaseLanguageModel, Text
from langflow.inputs import BoolInput, DictInput, DropdownInput, SecretStrInput, StrInput from langflow.inputs import BoolInput, DictInput, DropdownInput, MessageInput, SecretStrInput, StrInput
from langflow.template import Output from langflow.template import Output
from langflow.inputs import MessageInput
class HuggingFaceEndpointsComponent(LCModelComponent): class HuggingFaceEndpointsComponent(LCModelComponent):
@ -15,7 +14,7 @@ class HuggingFaceEndpointsComponent(LCModelComponent):
icon = "HuggingFace" icon = "HuggingFace"
inputs = [ inputs = [
MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]), MessageInput(name="input_value", display_name="Input"),
SecretStrInput(name="endpoint_url", display_name="Endpoint URL", password=True), SecretStrInput(name="endpoint_url", display_name="Endpoint URL", password=True),
DropdownInput( DropdownInput(
name="task", name="task",

7
src/backend/base/langflow/components/models/MistralModel.py
View file

@ -4,20 +4,17 @@ from pydantic.v1 import SecretStr
from langflow.base.constants import STREAM_INFO_TEXT from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent from langflow.base.models.model import LCModelComponent
from langflow.field_typing import BaseLanguageModel, Text from langflow.field_typing import BaseLanguageModel, Text
from langflow.inputs import BoolInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput from langflow.inputs import BoolInput, DropdownInput, FloatInput, IntInput, MessageInput, SecretStrInput, StrInput
from langflow.template import Output from langflow.template import Output
from langflow.inputs import MessageInput
class MistralAIModelComponent(LCModelComponent): class MistralAIModelComponent(LCModelComponent):
display_name = "MistralAI" display_name = "MistralAI"
description = "Generates text using MistralAI LLMs." description = "Generates text using MistralAI LLMs."
icon = "MistralAI" icon = "MistralAI"
inputs = [ inputs = [
MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]), MessageInput(name="input_value", display_name="Input"),
IntInput( IntInput(
name="max_tokens", name="max_tokens",
display_name="Max Tokens", display_name="Max Tokens",

2
src/backend/base/langflow/components/models/OpenAIModel.py
View file

@ -24,7 +24,7 @@ class OpenAIModelComponent(LCModelComponent):
icon = "OpenAI" icon = "OpenAI"
inputs = [ inputs = [
MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]), MessageInput(name="input_value", display_name="Input"),
IntInput( IntInput(
name="max_tokens", name="max_tokens",
display_name="Max Tokens", display_name="Max Tokens",

2
src/backend/base/langflow/components/models/VertexAiModel.py
View file

@ -13,7 +13,7 @@ class ChatVertexAIComponent(LCModelComponent):
icon = "VertexAI" icon = "VertexAI"
inputs = [ inputs = [
MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]), MessageInput(name="input_value", display_name="Input"),
StrInput( StrInput(
name="credentials", name="credentials",
display_name="Credentials", display_name="Credentials",

12
src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, world!).json
View file

@ -47,9 +47,7 @@
"fieldName": "input_value", "fieldName": "input_value",
"id": "OpenAIModel-SsPHS", "id": "OpenAIModel-SsPHS",
"inputTypes": [ "inputTypes": [
"Text", "Message"
"Data",
"Prompt"
], ],
"type": "str" "type": "str"
} }
@ -58,7 +56,7 @@
"source": "Prompt-3QeXa", "source": "Prompt-3QeXa",
"sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-3QeXaœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-3QeXaœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}",
"target": "OpenAIModel-SsPHS", "target": "OpenAIModel-SsPHS",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-SsPHSœ, œinputTypesœ: [œTextœ, œDataœ, œPromptœ], œtypeœ: œstrœ}" "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-SsPHSœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
}, },
{ {
"data": { "data": {
@ -663,7 +661,7 @@
"show": true, "show": true,
"title_case": false, "title_case": false,
"type": "code", "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": { "input_value": {
"advanced": false, "advanced": false,
@ -671,9 +669,7 @@
"dynamic": false, "dynamic": false,
"info": "", "info": "",
"input_types": [ "input_types": [
"Text", "Message"
"Data",
"Prompt"
], ],
"list": false, "list": false,
"load_from_db": false, "load_from_db": false,

12
src/backend/base/langflow/initial_setup/starter_projects/Langflow Blog Writter.json
View file

@ -138,9 +138,7 @@
"fieldName": "input_value", "fieldName": "input_value",
"id": "OpenAIModel-gi29P", "id": "OpenAIModel-gi29P",
"inputTypes": [ "inputTypes": [
"Text", "Message"
"Data",
"Prompt"
], ],
"type": "str" "type": "str"
} }
@ -153,7 +151,7 @@
"stroke": "#555" "stroke": "#555"
}, },
"target": "OpenAIModel-gi29P", "target": "OpenAIModel-gi29P",
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-gi29Pœ, œinputTypesœ: [œTextœ, œDataœ, œPromptœ], œtypeœ: œstrœ}" "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-gi29Pœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}"
} }
], ],
"nodes": [ "nodes": [
@ -697,7 +695,7 @@
"show": true, "show": true,
"title_case": false, "title_case": false,
"type": "code", "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": { "input_value": {
"advanced": false, "advanced": false,
@ -707,9 +705,7 @@
"file_path": "", "file_path": "",
"info": "", "info": "",
"input_types": [ "input_types": [
"Text", "Message"
"Data",
"Prompt"
], ],
"list": false, "list": false,
"load_from_db": false, "load_from_db": false,

12
src/backend/base/langflow/initial_setup/starter_projects/Langflow Document QA.json
View file

@ -71,9 +71,7 @@
"fieldName": "input_value", "fieldName": "input_value",
"id": "OpenAIModel-8b6nG", "id": "OpenAIModel-8b6nG",
"inputTypes": [ "inputTypes": [
"Text", "Message"
"Data",
"Prompt"
], ],
"type": "str" "type": "str"
} }
@ -82,7 +80,7 @@
"source": "Prompt-9DNZG", "source": "Prompt-9DNZG",
"sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-9DNZGœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-9DNZGœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}",
"target": "OpenAIModel-8b6nG", "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": { "data": {
@ -837,7 +835,7 @@
"show": true, "show": true,
"title_case": false, "title_case": false,
"type": "code", "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": { "input_value": {
"advanced": false, "advanced": false,
@ -845,9 +843,7 @@
"dynamic": false, "dynamic": false,
"info": "", "info": "",
"input_types": [ "input_types": [
"Text", "Message"
"Data",
"Prompt"
], ],
"list": false, "list": false,
"load_from_db": false, "load_from_db": false,

12
src/backend/base/langflow/initial_setup/starter_projects/Langflow Memory Conversation.json
View file

@ -82,9 +82,7 @@
"fieldName": "input_value", "fieldName": "input_value",
"id": "OpenAIModel-9RykF", "id": "OpenAIModel-9RykF",
"inputTypes": [ "inputTypes": [
"Text", "Message"
"Data",
"Prompt"
], ],
"type": "str" "type": "str"
} }
@ -96,7 +94,7 @@
"stroke": "#555" "stroke": "#555"
}, },
"target": "OpenAIModel-9RykF", "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", "className": "stroke-gray-900 stroke-connection",
@ -967,7 +965,7 @@
"show": true, "show": true,
"title_case": false, "title_case": false,
"type": "code", "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": { "input_value": {
"advanced": false, "advanced": false,
@ -977,9 +975,7 @@
"file_path": "", "file_path": "",
"info": "", "info": "",
"input_types": [ "input_types": [
"Text", "Message"
"Data",
"Prompt"
], ],
"list": false, "list": false,
"load_from_db": false, "load_from_db": false,

24
src/backend/base/langflow/initial_setup/starter_projects/Langflow Prompt Chaining.json
View file

@ -78,9 +78,7 @@
"fieldName": "input_value", "fieldName": "input_value",
"id": "OpenAIModel-uYXZJ", "id": "OpenAIModel-uYXZJ",
"inputTypes": [ "inputTypes": [
"Text", "Message"
"Data",
"Prompt"
], ],
"type": "str" "type": "str"
} }
@ -92,7 +90,7 @@
"stroke": "#555" "stroke": "#555"
}, },
"target": "OpenAIModel-uYXZJ", "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", "className": "stroke-gray-900 stroke-connection",
@ -200,9 +198,7 @@
"fieldName": "input_value", "fieldName": "input_value",
"id": "OpenAIModel-XawYB", "id": "OpenAIModel-XawYB",
"inputTypes": [ "inputTypes": [
"Text", "Message"
"Data",
"Prompt"
], ],
"type": "str" "type": "str"
} }
@ -214,7 +210,7 @@
"stroke": "#555" "stroke": "#555"
}, },
"target": "OpenAIModel-XawYB", "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", "className": "stroke-gray-900 stroke-connection",
@ -1167,7 +1163,7 @@
"show": true, "show": true,
"title_case": false, "title_case": false,
"type": "code", "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": { "input_value": {
"advanced": false, "advanced": false,
@ -1177,9 +1173,7 @@
"file_path": "", "file_path": "",
"info": "", "info": "",
"input_types": [ "input_types": [
"Text", "Message"
"Data",
"Prompt"
], ],
"list": false, "list": false,
"load_from_db": false, "load_from_db": false,
@ -1584,7 +1578,7 @@
"show": true, "show": true,
"title_case": false, "title_case": false,
"type": "code", "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": { "input_value": {
"advanced": false, "advanced": false,
@ -1594,9 +1588,7 @@
"file_path": "", "file_path": "",
"info": "", "info": "",
"input_types": [ "input_types": [
"Text", "Message"
"Data",
"Prompt"
], ],
"list": false, "list": false,
"load_from_db": false, "load_from_db": false,

12
src/backend/base/langflow/initial_setup/starter_projects/VectorStore-RAG-Flows.json
View file

@ -82,9 +82,7 @@
"fieldName": "input_value", "fieldName": "input_value",
"id": "OpenAIModel-EjXlN", "id": "OpenAIModel-EjXlN",
"inputTypes": [ "inputTypes": [
"Text", "Message"
"Data",
"Prompt"
], ],
"type": "str" "type": "str"
} }
@ -97,7 +95,7 @@
"stroke": "#555" "stroke": "#555"
}, },
"target": "OpenAIModel-EjXlN", "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", "className": "stroke-gray-900 stroke-connection",
@ -1078,7 +1076,7 @@
"show": true, "show": true,
"title_case": false, "title_case": false,
"type": "code", "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": { "input_value": {
"advanced": false, "advanced": false,
@ -1088,9 +1086,7 @@
"file_path": "", "file_path": "",
"info": "", "info": "",
"input_types": [ "input_types": [
"Text", "Message"
"Data",
"Prompt"
], ],
"list": false, "list": false,
"load_from_db": false, "load_from_db": false,

7
src/backend/base/langflow/schema/artifact.py
View file

@ -19,8 +19,11 @@ def get_artifact_type(value, build_result=None) -> str:
result = ArtifactType.UNKNOWN result = ArtifactType.UNKNOWN
match value: match value:
case Message(): case Message():
enum_value = get_artifact_type(value.text) if not isinstance(value.text, str):
result = ArtifactType(enum_value) enum_value = get_artifact_type(value.text)
result = ArtifactType(enum_value)
else:
result = ArtifactType.MESSAGE
case Data(): case Data():
enum_value = get_artifact_type(value.data) enum_value = get_artifact_type(value.data)
result = ArtifactType(enum_value) result = ArtifactType(enum_value)

2
src/frontend/tests/end-to-end/dropdownComponent.spec.ts
View file

@ -201,7 +201,7 @@ class AmazonBedrockComponent(LCModelComponent):
icon = "Amazon" icon = "Amazon"
inputs = [ inputs = [
MessageInput(name="input_value", display_name="Input", input_types=["Text", "Data", "Prompt"]), MessageInput(name="input_value", display_name="Input"),
DropdownInput( DropdownInput(
name="model_id", name="model_id",
display_name="Model Id", display_name="Model Id",