From bd0957b60bded6a39a17f6e066ed7f1370dd7ea7 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Thu, 12 Jun 2025 11:02:14 -0300 Subject: [PATCH 01/12] feat(auth): update AUTO_LOGIN authentication to enforce API key or JWT requirement * Removed deprecated warning messages and implemented explicit HTTP exceptions for missing API key or JWT in both API and WebSocket authentication methods. * Enhanced error handling to ensure compliance with the new authentication requirements introduced in v1.5. --- .../base/langflow/services/auth/utils.py | 40 +++++++++---------- 1 file changed, 18 insertions(+), 22 deletions(-) diff --git a/src/backend/base/langflow/services/auth/utils.py b/src/backend/base/langflow/services/auth/utils.py index c045384c8919..525d9a4d6e11 100644 --- a/src/backend/base/langflow/services/auth/utils.py +++ b/src/backend/base/langflow/services/auth/utils.py @@ -49,19 +49,15 @@ async def api_key_security( status_code=status.HTTP_400_BAD_REQUEST, detail="Missing first superuser credentials", ) - warnings.warn( - ( - "In v1.5, the default behavior of AUTO_LOGIN authentication will change to require a valid API key" - " or JWT. If you integrated with Langflow prior to v1.5, make sure to update your code to pass an " - "API key or JWT when authenticating with protected endpoints." - ), - DeprecationWarning, - stacklevel=2, - ) - if query_param or header_param: - result = await check_key(db, query_param or header_param) - else: - result = await get_user_by_username(db, settings_service.auth_settings.SUPERUSER) + if not query_param and not header_param: + raise HTTPException( + status_code=status.HTTP_403_FORBIDDEN, + detail=( + "Since v1.5, AUTO_LOGIN requires a valid API key or JWT." + " Please update your authentication method." + ), + ) + result = await check_key(db, query_param or header_param) elif not query_param and not header_param: raise HTTPException( @@ -98,15 +94,15 @@ async def ws_api_key_security( code=status.WS_1011_INTERNAL_ERROR, reason="Missing first superuser credentials", ) - warnings.warn( - ("In v1.5, AUTO_LOGIN will *require* a valid API key or JWT. Please update your clients accordingly."), - DeprecationWarning, - stacklevel=2, - ) - if api_key: - result = await check_key(db, api_key) - else: - result = await get_user_by_username(db, settings.auth_settings.SUPERUSER) + if not api_key: + raise WebSocketException( + code=status.WS_1008_POLICY_VIOLATION, + reason=( + "Since v1.5, AUTO_LOGIN requires a valid API key or JWT." + " Please update your authentication method." + ), + ) + result = await check_key(db, api_key) # normal path: must provide an API key else: From e4b8a4b7590a86bf5e07ef0c9db221d82d2b6804 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Fri, 13 Jun 2025 12:26:55 -0300 Subject: [PATCH 02/12] fix(auth): refine error message for AUTO_LOGIN API key requirement * Updated the error message in the API key security function to clarify that AUTO_LOGIN requires a valid API key, removing the mention of JWT for consistency with the latest authentication requirements. --- src/backend/base/langflow/services/auth/utils.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/src/backend/base/langflow/services/auth/utils.py b/src/backend/base/langflow/services/auth/utils.py index 525d9a4d6e11..27536374621b 100644 --- a/src/backend/base/langflow/services/auth/utils.py +++ b/src/backend/base/langflow/services/auth/utils.py @@ -53,8 +53,7 @@ async def api_key_security( raise HTTPException( status_code=status.HTTP_403_FORBIDDEN, detail=( - "Since v1.5, AUTO_LOGIN requires a valid API key or JWT." - " Please update your authentication method." + "Since v1.5, AUTO_LOGIN requires a valid API key. Please update your authentication method." ), ) result = await check_key(db, query_param or header_param) From 6c545f62bba48bac537e9599330e32004549aa2a Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Fri, 13 Jun 2025 12:35:36 -0300 Subject: [PATCH 03/12] feat(auth): introduce SKIP_AUTH_AUTO_LOGIN setting for enhanced authentication flexibility * Added a new configuration option `SKIP_AUTH_AUTO_LOGIN` to the AuthSettings class, allowing the application to bypass API key validation for auto login. * Updated the API and WebSocket security functions to utilize this setting, improving error handling and providing a fallback for superuser credentials when authentication is skipped. --- .../base/langflow/services/auth/utils.py | 31 +++++++++++-------- .../base/langflow/services/settings/auth.py | 3 ++ 2 files changed, 21 insertions(+), 13 deletions(-) diff --git a/src/backend/base/langflow/services/auth/utils.py b/src/backend/base/langflow/services/auth/utils.py index 27536374621b..63d325adff1c 100644 --- a/src/backend/base/langflow/services/auth/utils.py +++ b/src/backend/base/langflow/services/auth/utils.py @@ -50,12 +50,15 @@ async def api_key_security( detail="Missing first superuser credentials", ) if not query_param and not header_param: - raise HTTPException( - status_code=status.HTTP_403_FORBIDDEN, - detail=( - "Since v1.5, AUTO_LOGIN requires a valid API key. Please update your authentication method." - ), - ) + if settings_service.auth_settings.SKIP_AUTH_AUTO_LOGIN: + result = await get_user_by_username(db, settings_service.auth_settings.SUPERUSER) + else: + raise HTTPException( + status_code=status.HTTP_403_FORBIDDEN, + detail=( + "Since v1.5, AUTO_LOGIN requires a valid API key. Please update your authentication method." + ), + ) result = await check_key(db, query_param or header_param) elif not query_param and not header_param: @@ -94,13 +97,15 @@ async def ws_api_key_security( reason="Missing first superuser credentials", ) if not api_key: - raise WebSocketException( - code=status.WS_1008_POLICY_VIOLATION, - reason=( - "Since v1.5, AUTO_LOGIN requires a valid API key or JWT." - " Please update your authentication method." - ), - ) + if settings.auth_settings.SKIP_AUTH_AUTO_LOGIN: + result = await get_user_by_username(db, settings.auth_settings.SUPERUSER) + else: + raise WebSocketException( + code=status.WS_1008_POLICY_VIOLATION, + reason=( + "Since v1.5, AUTO_LOGIN requires a valid API key. Please update your authentication method." + ), + ) result = await check_key(db, api_key) # normal path: must provide an API key diff --git a/src/backend/base/langflow/services/settings/auth.py b/src/backend/base/langflow/services/settings/auth.py index 25dd338ab895..bbdb272321ab 100644 --- a/src/backend/base/langflow/services/settings/auth.py +++ b/src/backend/base/langflow/services/settings/auth.py @@ -50,6 +50,9 @@ class AuthSettings(BaseSettings): COOKIE_DOMAIN: str | None = None """The domain attribute of the cookies. If None, the domain is not set.""" + SKIP_AUTH_AUTO_LOGIN: bool = True + """If True, the application will skip the authentication auto login. This will be removed in v1.6""" + pwd_context: CryptContext = CryptContext(schemes=["bcrypt"], deprecated="auto") model_config = SettingsConfigDict(validate_assignment=True, extra="ignore", env_prefix="LANGFLOW_") From 0355496ae28643794d73ec82b2fbfa69244f8e6b Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Fri, 13 Jun 2025 12:37:19 -0300 Subject: [PATCH 04/12] refactor(auth): rename SKIP_AUTH_AUTO_LOGIN to skip_auth_auto_login for consistency * Updated the `SKIP_AUTH_AUTO_LOGIN` setting in the `AuthSettings` class to `skip_auth_auto_login` to follow Python naming conventions. * Adjusted references in the API and WebSocket security functions to use the new attribute name, ensuring consistent behavior across the authentication logic. --- src/backend/base/langflow/services/auth/utils.py | 4 ++-- src/backend/base/langflow/services/settings/auth.py | 5 +++-- 2 files changed, 5 insertions(+), 4 deletions(-) diff --git a/src/backend/base/langflow/services/auth/utils.py b/src/backend/base/langflow/services/auth/utils.py index 63d325adff1c..91f912e928a1 100644 --- a/src/backend/base/langflow/services/auth/utils.py +++ b/src/backend/base/langflow/services/auth/utils.py @@ -50,7 +50,7 @@ async def api_key_security( detail="Missing first superuser credentials", ) if not query_param and not header_param: - if settings_service.auth_settings.SKIP_AUTH_AUTO_LOGIN: + if settings_service.auth_settings.skip_auth_auto_login: result = await get_user_by_username(db, settings_service.auth_settings.SUPERUSER) else: raise HTTPException( @@ -97,7 +97,7 @@ async def ws_api_key_security( reason="Missing first superuser credentials", ) if not api_key: - if settings.auth_settings.SKIP_AUTH_AUTO_LOGIN: + if settings.auth_settings.skip_auth_auto_login: result = await get_user_by_username(db, settings.auth_settings.SUPERUSER) else: raise WebSocketException( diff --git a/src/backend/base/langflow/services/settings/auth.py b/src/backend/base/langflow/services/settings/auth.py index bbdb272321ab..91cb8dcafd61 100644 --- a/src/backend/base/langflow/services/settings/auth.py +++ b/src/backend/base/langflow/services/settings/auth.py @@ -50,8 +50,9 @@ class AuthSettings(BaseSettings): COOKIE_DOMAIN: str | None = None """The domain attribute of the cookies. If None, the domain is not set.""" - SKIP_AUTH_AUTO_LOGIN: bool = True - """If True, the application will skip the authentication auto login. This will be removed in v1.6""" + skip_auth_auto_login: bool = True + """If True, the application will skip the authentication auto login, set this to False to revert to pre-v1.5 + behavior. This will be removed in v1.6""" pwd_context: CryptContext = CryptContext(schemes=["bcrypt"], deprecated="auto") From e9a1441a5b088a0efe8c62d9365f45945ee6f421 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Fri, 13 Jun 2025 12:40:10 -0300 Subject: [PATCH 05/12] feat(auth): add deprecation warning for SKIP_AUTH_AUTO_LOGIN removal * Introduced a warning log in both API and WebSocket security functions to inform users that the `LANGFLOW_SKIP_AUTH_AUTO_LOGIN` feature will be removed in version 1.6, prompting necessary updates to authentication methods. --- src/backend/base/langflow/services/auth/utils.py | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/src/backend/base/langflow/services/auth/utils.py b/src/backend/base/langflow/services/auth/utils.py index 91f912e928a1..914161f38709 100644 --- a/src/backend/base/langflow/services/auth/utils.py +++ b/src/backend/base/langflow/services/auth/utils.py @@ -52,6 +52,10 @@ async def api_key_security( if not query_param and not header_param: if settings_service.auth_settings.skip_auth_auto_login: result = await get_user_by_username(db, settings_service.auth_settings.SUPERUSER) + logger.warning( + "In v1.6 LANGFLOW_SKIP_AUTH_AUTO_LOGIN will be removed. " + "Please update your authentication method." + ) else: raise HTTPException( status_code=status.HTTP_403_FORBIDDEN, @@ -99,6 +103,10 @@ async def ws_api_key_security( if not api_key: if settings.auth_settings.skip_auth_auto_login: result = await get_user_by_username(db, settings.auth_settings.SUPERUSER) + logger.warning( + "In v1.6 LANGFLOW_SKIP_AUTH_AUTO_LOGIN will be removed. " + "Please update your authentication method." + ) else: raise WebSocketException( code=status.WS_1008_POLICY_VIOLATION, From 1d75a8cd70a4312a05850436a6d38af82c721ef6 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Fri, 13 Jun 2025 12:46:55 -0300 Subject: [PATCH 06/12] feat(auth): enhance deprecation warnings for AUTO_LOGIN features * Added constants for deprecation warning and error messages related to `LANGFLOW_SKIP_AUTH_AUTO_LOGIN` and `AUTO_LOGIN` requirements, improving code maintainability and clarity. * Updated API and WebSocket security functions to utilize these constants for logging and exception handling, ensuring consistent messaging across authentication methods. --- .../base/langflow/services/auth/utils.py | 21 +++++++------------ 1 file changed, 7 insertions(+), 14 deletions(-) diff --git a/src/backend/base/langflow/services/auth/utils.py b/src/backend/base/langflow/services/auth/utils.py index 914161f38709..f38a2c6282a6 100644 --- a/src/backend/base/langflow/services/auth/utils.py +++ b/src/backend/base/langflow/services/auth/utils.py @@ -32,6 +32,9 @@ MINIMUM_KEY_LENGTH = 32 +AUTO_LOGIN_WARNING = "In v1.6 LANGFLOW_SKIP_AUTH_AUTO_LOGIN will be removed. Please update your authentication method." +AUTO_LOGIN_ERROR = "Since v1.5, LANGFLOW_AUTO_LOGIN requires a valid API key. Please update your authentication method." + # Source: https://github.com/mrtolkien/fastapi_simple_security/blob/master/fastapi_simple_security/security_api_key.py async def api_key_security( @@ -52,16 +55,11 @@ async def api_key_security( if not query_param and not header_param: if settings_service.auth_settings.skip_auth_auto_login: result = await get_user_by_username(db, settings_service.auth_settings.SUPERUSER) - logger.warning( - "In v1.6 LANGFLOW_SKIP_AUTH_AUTO_LOGIN will be removed. " - "Please update your authentication method." - ) + logger.warning(AUTO_LOGIN_WARNING) else: raise HTTPException( status_code=status.HTTP_403_FORBIDDEN, - detail=( - "Since v1.5, AUTO_LOGIN requires a valid API key. Please update your authentication method." - ), + detail=AUTO_LOGIN_ERROR, ) result = await check_key(db, query_param or header_param) @@ -103,16 +101,11 @@ async def ws_api_key_security( if not api_key: if settings.auth_settings.skip_auth_auto_login: result = await get_user_by_username(db, settings.auth_settings.SUPERUSER) - logger.warning( - "In v1.6 LANGFLOW_SKIP_AUTH_AUTO_LOGIN will be removed. " - "Please update your authentication method." - ) + logger.warning(AUTO_LOGIN_WARNING) else: raise WebSocketException( code=status.WS_1008_POLICY_VIOLATION, - reason=( - "Since v1.5, AUTO_LOGIN requires a valid API key. Please update your authentication method." - ), + reason=AUTO_LOGIN_ERROR, ) result = await check_key(db, api_key) From f17e6ee32963c534372d59ca85bbd3de20e6c8d3 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Fri, 13 Jun 2025 12:58:20 -0300 Subject: [PATCH 07/12] fix(auth): update AUTO_LOGIN_ERROR message to include LANGFLOW_SKIP_AUTH_AUTO_LOGIN usage --- src/backend/base/langflow/services/auth/utils.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/src/backend/base/langflow/services/auth/utils.py b/src/backend/base/langflow/services/auth/utils.py index f38a2c6282a6..d003e055c062 100644 --- a/src/backend/base/langflow/services/auth/utils.py +++ b/src/backend/base/langflow/services/auth/utils.py @@ -31,9 +31,12 @@ api_key_header = APIKeyHeader(name=API_KEY_NAME, scheme_name="API key header", auto_error=False) MINIMUM_KEY_LENGTH = 32 - AUTO_LOGIN_WARNING = "In v1.6 LANGFLOW_SKIP_AUTH_AUTO_LOGIN will be removed. Please update your authentication method." -AUTO_LOGIN_ERROR = "Since v1.5, LANGFLOW_AUTO_LOGIN requires a valid API key. Please update your authentication method." +AUTO_LOGIN_ERROR = ( + "Since v1.5, LANGFLOW_AUTO_LOGIN requires a valid API key. " + "Set LANGFLOW_SKIP_AUTH_AUTO_LOGIN=true to skip this check. " + "Please update your authentication method." +) # Source: https://github.com/mrtolkien/fastapi_simple_security/blob/master/fastapi_simple_security/security_api_key.py From b8abb9085254083e863935a4c9e7f9570c3ed325 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 23 Jun 2025 18:06:05 -0300 Subject: [PATCH 08/12] fix(auth): correct logic for API key validation in WebSocket security function * Adjusted the conditional flow in the `ws_api_key_security` function to ensure that the API key is checked only when necessary, improving the clarity and correctness of the authentication logic. --- src/backend/base/langflow/services/auth/utils.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/src/backend/base/langflow/services/auth/utils.py b/src/backend/base/langflow/services/auth/utils.py index d003e055c062..8394952fa631 100644 --- a/src/backend/base/langflow/services/auth/utils.py +++ b/src/backend/base/langflow/services/auth/utils.py @@ -110,7 +110,8 @@ async def ws_api_key_security( code=status.WS_1008_POLICY_VIOLATION, reason=AUTO_LOGIN_ERROR, ) - result = await check_key(db, api_key) + else: + result = await check_key(db, api_key) # normal path: must provide an API key else: From 3699311a82629b49078833a2f18e61ec1069b61e Mon Sep 17 00:00:00 2001 From: "autofix-ci[bot]" <114827586+autofix-ci[bot]@users.noreply.github.com> Date: Mon, 23 Jun 2025 21:10:58 +0000 Subject: [PATCH 09/12] [autofix.ci] apply automated fixes --- .../Basic Prompt Chaining.json | 22 +++++++++---------- .../starter_projects/Blog Writer.json | 2 +- .../Financial Report Parser.json | 2 +- .../starter_projects/Hybrid Search RAG.json | 4 ++-- .../SEO Keyword Generator.json | 10 ++++----- 5 files changed, 20 insertions(+), 20 deletions(-) diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompt Chaining.json b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompt Chaining.json index 6e2bb8209b51..bf1216e065a9 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompt Chaining.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompt Chaining.json @@ -308,8 +308,8 @@ }, "tool_mode": false }, - "type": "Prompt", - "selected_output": "prompt" + "selected_output": "prompt", + "type": "Prompt" }, "dragging": false, "height": 260, @@ -606,8 +606,8 @@ } } }, - "type": "ChatInput", - "selected_output": "message" + "selected_output": "message", + "type": "ChatInput" }, "dragging": false, "height": 234, @@ -1039,8 +1039,8 @@ }, "tool_mode": false }, - "type": "Prompt", - "selected_output": "prompt" + "selected_output": "prompt", + "type": "Prompt" }, "dragging": false, "height": 260, @@ -1168,8 +1168,8 @@ }, "tool_mode": false }, - "type": "Prompt", - "selected_output": "prompt" + "selected_output": "prompt", + "type": "Prompt" }, "dragging": false, "height": 260, @@ -1296,7 +1296,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from typing import Any\n\nfrom langchain_anthropic import ChatAnthropic\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider. \"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\", \"Anthropic\", \"Google\"],\n value=\"OpenAI\",\n info=\"Select the model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}, {\"icon\": \"Anthropic\"}, {\"icon\": \"Google\"}],\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n info=\"Select the model to use\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=True,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n provider = self.provider\n model_name = self.model_name\n temperature = self.temperature\n stream = self.stream\n\n if provider == \"OpenAI\":\n if not self.api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n return ChatOpenAI(\n model_name=model_name,\n temperature=temperature,\n streaming=stream,\n openai_api_key=self.api_key,\n )\n if provider == \"Anthropic\":\n if not self.api_key:\n msg = \"Anthropic API key is required when using Anthropic provider\"\n raise ValueError(msg)\n return ChatAnthropic(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n anthropic_api_key=self.api_key,\n )\n if provider == \"Google\":\n if not self.api_key:\n msg = \"Google API key is required when using Google provider\"\n raise ValueError(msg)\n return ChatGoogleGenerativeAI(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n google_api_key=self.api_key,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\":\n if field_value == \"OpenAI\":\n build_config[\"model_name\"][\"options\"] = OPENAI_MODEL_NAMES\n build_config[\"model_name\"][\"value\"] = OPENAI_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n elif field_value == \"Anthropic\":\n build_config[\"model_name\"][\"options\"] = ANTHROPIC_MODELS\n build_config[\"model_name\"][\"value\"] = ANTHROPIC_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Anthropic API Key\"\n elif field_value == \"Google\":\n build_config[\"model_name\"][\"options\"] = GOOGLE_GENERATIVE_AI_MODELS\n build_config[\"model_name\"][\"value\"] = GOOGLE_GENERATIVE_AI_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Google API Key\"\n return build_config\n" + "value": "from typing import Any\n\nfrom langchain_anthropic import ChatAnthropic\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider. \"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\", \"Anthropic\", \"Google\"],\n value=\"OpenAI\",\n info=\"Select the model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}, {\"icon\": \"Anthropic\"}, {\"icon\": \"GoogleGenerativeAI\"}],\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n info=\"Select the model to use\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=True,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n provider = self.provider\n model_name = self.model_name\n temperature = self.temperature\n stream = self.stream\n\n if provider == \"OpenAI\":\n if not self.api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n return ChatOpenAI(\n model_name=model_name,\n temperature=temperature,\n streaming=stream,\n openai_api_key=self.api_key,\n )\n if provider == \"Anthropic\":\n if not self.api_key:\n msg = \"Anthropic API key is required when using Anthropic provider\"\n raise ValueError(msg)\n return ChatAnthropic(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n anthropic_api_key=self.api_key,\n )\n if provider == \"Google\":\n if not self.api_key:\n msg = \"Google API key is required when using Google provider\"\n raise ValueError(msg)\n return ChatGoogleGenerativeAI(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n google_api_key=self.api_key,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\":\n if field_value == \"OpenAI\":\n build_config[\"model_name\"][\"options\"] = OPENAI_MODEL_NAMES\n build_config[\"model_name\"][\"value\"] = OPENAI_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n elif field_value == \"Anthropic\":\n build_config[\"model_name\"][\"options\"] = ANTHROPIC_MODELS\n build_config[\"model_name\"][\"value\"] = ANTHROPIC_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Anthropic API Key\"\n elif field_value == \"Google\":\n build_config[\"model_name\"][\"options\"] = GOOGLE_GENERATIVE_AI_MODELS\n build_config[\"model_name\"][\"value\"] = GOOGLE_GENERATIVE_AI_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Google API Key\"\n return build_config\n" }, "input_value": { "_input_type": "MessageTextInput", @@ -1583,7 +1583,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from typing import Any\n\nfrom langchain_anthropic import ChatAnthropic\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider. \"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\", \"Anthropic\", \"Google\"],\n value=\"OpenAI\",\n info=\"Select the model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}, {\"icon\": \"Anthropic\"}, {\"icon\": \"Google\"}],\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n info=\"Select the model to use\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=True,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n provider = self.provider\n model_name = self.model_name\n temperature = self.temperature\n stream = self.stream\n\n if provider == \"OpenAI\":\n if not self.api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n return ChatOpenAI(\n model_name=model_name,\n temperature=temperature,\n streaming=stream,\n openai_api_key=self.api_key,\n )\n if provider == \"Anthropic\":\n if not self.api_key:\n msg = \"Anthropic API key is required when using Anthropic provider\"\n raise ValueError(msg)\n return ChatAnthropic(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n anthropic_api_key=self.api_key,\n )\n if provider == \"Google\":\n if not self.api_key:\n msg = \"Google API key is required when using Google provider\"\n raise ValueError(msg)\n return ChatGoogleGenerativeAI(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n google_api_key=self.api_key,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\":\n if field_value == \"OpenAI\":\n build_config[\"model_name\"][\"options\"] = OPENAI_MODEL_NAMES\n build_config[\"model_name\"][\"value\"] = OPENAI_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n elif field_value == \"Anthropic\":\n build_config[\"model_name\"][\"options\"] = ANTHROPIC_MODELS\n build_config[\"model_name\"][\"value\"] = ANTHROPIC_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Anthropic API Key\"\n elif field_value == \"Google\":\n build_config[\"model_name\"][\"options\"] = GOOGLE_GENERATIVE_AI_MODELS\n build_config[\"model_name\"][\"value\"] = GOOGLE_GENERATIVE_AI_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Google API Key\"\n return build_config\n" + "value": "from typing import Any\n\nfrom langchain_anthropic import ChatAnthropic\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider. \"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\", \"Anthropic\", \"Google\"],\n value=\"OpenAI\",\n info=\"Select the model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}, {\"icon\": \"Anthropic\"}, {\"icon\": \"GoogleGenerativeAI\"}],\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n info=\"Select the model to use\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=True,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n provider = self.provider\n model_name = self.model_name\n temperature = self.temperature\n stream = self.stream\n\n if provider == \"OpenAI\":\n if not self.api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n return ChatOpenAI(\n model_name=model_name,\n temperature=temperature,\n streaming=stream,\n openai_api_key=self.api_key,\n )\n if provider == \"Anthropic\":\n if not self.api_key:\n msg = \"Anthropic API key is required when using Anthropic provider\"\n raise ValueError(msg)\n return ChatAnthropic(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n anthropic_api_key=self.api_key,\n )\n if provider == \"Google\":\n if not self.api_key:\n msg = \"Google API key is required when using Google provider\"\n raise ValueError(msg)\n return ChatGoogleGenerativeAI(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n google_api_key=self.api_key,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\":\n if field_value == \"OpenAI\":\n build_config[\"model_name\"][\"options\"] = OPENAI_MODEL_NAMES\n build_config[\"model_name\"][\"value\"] = OPENAI_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n elif field_value == \"Anthropic\":\n build_config[\"model_name\"][\"options\"] = ANTHROPIC_MODELS\n build_config[\"model_name\"][\"value\"] = ANTHROPIC_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Anthropic API Key\"\n elif field_value == \"Google\":\n build_config[\"model_name\"][\"options\"] = GOOGLE_GENERATIVE_AI_MODELS\n build_config[\"model_name\"][\"value\"] = GOOGLE_GENERATIVE_AI_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Google API Key\"\n return build_config\n" }, "input_value": { "_input_type": "MessageTextInput", @@ -1870,7 +1870,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from typing import Any\n\nfrom langchain_anthropic import ChatAnthropic\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider. \"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\", \"Anthropic\", \"Google\"],\n value=\"OpenAI\",\n info=\"Select the model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}, {\"icon\": \"Anthropic\"}, {\"icon\": \"Google\"}],\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n info=\"Select the model to use\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=True,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n provider = self.provider\n model_name = self.model_name\n temperature = self.temperature\n stream = self.stream\n\n if provider == \"OpenAI\":\n if not self.api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n return ChatOpenAI(\n model_name=model_name,\n temperature=temperature,\n streaming=stream,\n openai_api_key=self.api_key,\n )\n if provider == \"Anthropic\":\n if not self.api_key:\n msg = \"Anthropic API key is required when using Anthropic provider\"\n raise ValueError(msg)\n return ChatAnthropic(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n anthropic_api_key=self.api_key,\n )\n if provider == \"Google\":\n if not self.api_key:\n msg = \"Google API key is required when using Google provider\"\n raise ValueError(msg)\n return ChatGoogleGenerativeAI(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n google_api_key=self.api_key,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\":\n if field_value == \"OpenAI\":\n build_config[\"model_name\"][\"options\"] = OPENAI_MODEL_NAMES\n build_config[\"model_name\"][\"value\"] = OPENAI_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n elif field_value == \"Anthropic\":\n build_config[\"model_name\"][\"options\"] = ANTHROPIC_MODELS\n build_config[\"model_name\"][\"value\"] = ANTHROPIC_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Anthropic API Key\"\n elif field_value == \"Google\":\n build_config[\"model_name\"][\"options\"] = GOOGLE_GENERATIVE_AI_MODELS\n build_config[\"model_name\"][\"value\"] = GOOGLE_GENERATIVE_AI_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Google API Key\"\n return build_config\n" + "value": "from typing import Any\n\nfrom langchain_anthropic import ChatAnthropic\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider. \"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\", \"Anthropic\", \"Google\"],\n value=\"OpenAI\",\n info=\"Select the model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}, {\"icon\": \"Anthropic\"}, {\"icon\": \"GoogleGenerativeAI\"}],\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n info=\"Select the model to use\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=True,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n provider = self.provider\n model_name = self.model_name\n temperature = self.temperature\n stream = self.stream\n\n if provider == \"OpenAI\":\n if not self.api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n return ChatOpenAI(\n model_name=model_name,\n temperature=temperature,\n streaming=stream,\n openai_api_key=self.api_key,\n )\n if provider == \"Anthropic\":\n if not self.api_key:\n msg = \"Anthropic API key is required when using Anthropic provider\"\n raise ValueError(msg)\n return ChatAnthropic(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n anthropic_api_key=self.api_key,\n )\n if provider == \"Google\":\n if not self.api_key:\n msg = \"Google API key is required when using Google provider\"\n raise ValueError(msg)\n return ChatGoogleGenerativeAI(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n google_api_key=self.api_key,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\":\n if field_value == \"OpenAI\":\n build_config[\"model_name\"][\"options\"] = OPENAI_MODEL_NAMES\n build_config[\"model_name\"][\"value\"] = OPENAI_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n elif field_value == \"Anthropic\":\n build_config[\"model_name\"][\"options\"] = ANTHROPIC_MODELS\n build_config[\"model_name\"][\"value\"] = ANTHROPIC_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Anthropic API Key\"\n elif field_value == \"Google\":\n build_config[\"model_name\"][\"options\"] = GOOGLE_GENERATIVE_AI_MODELS\n build_config[\"model_name\"][\"value\"] = GOOGLE_GENERATIVE_AI_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Google API Key\"\n return build_config\n" }, "input_value": { "_input_type": "MessageTextInput", diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json b/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json index f3e3a01755da..19458efc340c 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json @@ -1406,7 +1406,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from typing import Any\n\nfrom langchain_anthropic import ChatAnthropic\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider. \"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\", \"Anthropic\", \"Google\"],\n value=\"OpenAI\",\n info=\"Select the model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}, {\"icon\": \"Anthropic\"}, {\"icon\": \"Google\"}],\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n info=\"Select the model to use\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=True,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n provider = self.provider\n model_name = self.model_name\n temperature = self.temperature\n stream = self.stream\n\n if provider == \"OpenAI\":\n if not self.api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n return ChatOpenAI(\n model_name=model_name,\n temperature=temperature,\n streaming=stream,\n openai_api_key=self.api_key,\n )\n if provider == \"Anthropic\":\n if not self.api_key:\n msg = \"Anthropic API key is required when using Anthropic provider\"\n raise ValueError(msg)\n return ChatAnthropic(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n anthropic_api_key=self.api_key,\n )\n if provider == \"Google\":\n if not self.api_key:\n msg = \"Google API key is required when using Google provider\"\n raise ValueError(msg)\n return ChatGoogleGenerativeAI(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n google_api_key=self.api_key,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\":\n if field_value == \"OpenAI\":\n build_config[\"model_name\"][\"options\"] = OPENAI_MODEL_NAMES\n build_config[\"model_name\"][\"value\"] = OPENAI_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n elif field_value == \"Anthropic\":\n build_config[\"model_name\"][\"options\"] = ANTHROPIC_MODELS\n build_config[\"model_name\"][\"value\"] = ANTHROPIC_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Anthropic API Key\"\n elif field_value == \"Google\":\n build_config[\"model_name\"][\"options\"] = GOOGLE_GENERATIVE_AI_MODELS\n build_config[\"model_name\"][\"value\"] = GOOGLE_GENERATIVE_AI_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Google API Key\"\n return build_config\n" + "value": "from typing import Any\n\nfrom langchain_anthropic import ChatAnthropic\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider. \"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\", \"Anthropic\", \"Google\"],\n value=\"OpenAI\",\n info=\"Select the model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}, {\"icon\": \"Anthropic\"}, {\"icon\": \"GoogleGenerativeAI\"}],\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n info=\"Select the model to use\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=True,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n provider = self.provider\n model_name = self.model_name\n temperature = self.temperature\n stream = self.stream\n\n if provider == \"OpenAI\":\n if not self.api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n return ChatOpenAI(\n model_name=model_name,\n temperature=temperature,\n streaming=stream,\n openai_api_key=self.api_key,\n )\n if provider == \"Anthropic\":\n if not self.api_key:\n msg = \"Anthropic API key is required when using Anthropic provider\"\n raise ValueError(msg)\n return ChatAnthropic(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n anthropic_api_key=self.api_key,\n )\n if provider == \"Google\":\n if not self.api_key:\n msg = \"Google API key is required when using Google provider\"\n raise ValueError(msg)\n return ChatGoogleGenerativeAI(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n google_api_key=self.api_key,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\":\n if field_value == \"OpenAI\":\n build_config[\"model_name\"][\"options\"] = OPENAI_MODEL_NAMES\n build_config[\"model_name\"][\"value\"] = OPENAI_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n elif field_value == \"Anthropic\":\n build_config[\"model_name\"][\"options\"] = ANTHROPIC_MODELS\n build_config[\"model_name\"][\"value\"] = ANTHROPIC_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Anthropic API Key\"\n elif field_value == \"Google\":\n build_config[\"model_name\"][\"options\"] = GOOGLE_GENERATIVE_AI_MODELS\n build_config[\"model_name\"][\"value\"] = GOOGLE_GENERATIVE_AI_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Google API Key\"\n return build_config\n" }, "input_value": { "_input_type": "MessageTextInput", diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Financial Report Parser.json b/src/backend/base/langflow/initial_setup/starter_projects/Financial Report Parser.json index f0d7b98ec8bf..f45ba0bca8c4 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Financial Report Parser.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Financial Report Parser.json @@ -1079,7 +1079,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from typing import Any\n\nfrom langchain_anthropic import ChatAnthropic\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider. \"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\", \"Anthropic\", \"Google\"],\n value=\"OpenAI\",\n info=\"Select the model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}, {\"icon\": \"Anthropic\"}, {\"icon\": \"Google\"}],\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n info=\"Select the model to use\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=True,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n provider = self.provider\n model_name = self.model_name\n temperature = self.temperature\n stream = self.stream\n\n if provider == \"OpenAI\":\n if not self.api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n return ChatOpenAI(\n model_name=model_name,\n temperature=temperature,\n streaming=stream,\n openai_api_key=self.api_key,\n )\n if provider == \"Anthropic\":\n if not self.api_key:\n msg = \"Anthropic API key is required when using Anthropic provider\"\n raise ValueError(msg)\n return ChatAnthropic(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n anthropic_api_key=self.api_key,\n )\n if provider == \"Google\":\n if not self.api_key:\n msg = \"Google API key is required when using Google provider\"\n raise ValueError(msg)\n return ChatGoogleGenerativeAI(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n google_api_key=self.api_key,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\":\n if field_value == \"OpenAI\":\n build_config[\"model_name\"][\"options\"] = OPENAI_MODEL_NAMES\n build_config[\"model_name\"][\"value\"] = OPENAI_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n elif field_value == \"Anthropic\":\n build_config[\"model_name\"][\"options\"] = ANTHROPIC_MODELS\n build_config[\"model_name\"][\"value\"] = ANTHROPIC_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Anthropic API Key\"\n elif field_value == \"Google\":\n build_config[\"model_name\"][\"options\"] = GOOGLE_GENERATIVE_AI_MODELS\n build_config[\"model_name\"][\"value\"] = GOOGLE_GENERATIVE_AI_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Google API Key\"\n return build_config\n" + "value": "from typing import Any\n\nfrom langchain_anthropic import ChatAnthropic\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider. \"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\", \"Anthropic\", \"Google\"],\n value=\"OpenAI\",\n info=\"Select the model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}, {\"icon\": \"Anthropic\"}, {\"icon\": \"GoogleGenerativeAI\"}],\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n info=\"Select the model to use\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=True,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n provider = self.provider\n model_name = self.model_name\n temperature = self.temperature\n stream = self.stream\n\n if provider == \"OpenAI\":\n if not self.api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n return ChatOpenAI(\n model_name=model_name,\n temperature=temperature,\n streaming=stream,\n openai_api_key=self.api_key,\n )\n if provider == \"Anthropic\":\n if not self.api_key:\n msg = \"Anthropic API key is required when using Anthropic provider\"\n raise ValueError(msg)\n return ChatAnthropic(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n anthropic_api_key=self.api_key,\n )\n if provider == \"Google\":\n if not self.api_key:\n msg = \"Google API key is required when using Google provider\"\n raise ValueError(msg)\n return ChatGoogleGenerativeAI(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n google_api_key=self.api_key,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\":\n if field_value == \"OpenAI\":\n build_config[\"model_name\"][\"options\"] = OPENAI_MODEL_NAMES\n build_config[\"model_name\"][\"value\"] = OPENAI_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n elif field_value == \"Anthropic\":\n build_config[\"model_name\"][\"options\"] = ANTHROPIC_MODELS\n build_config[\"model_name\"][\"value\"] = ANTHROPIC_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Anthropic API Key\"\n elif field_value == \"Google\":\n build_config[\"model_name\"][\"options\"] = GOOGLE_GENERATIVE_AI_MODELS\n build_config[\"model_name\"][\"value\"] = GOOGLE_GENERATIVE_AI_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Google API Key\"\n return build_config\n" }, "input_value": { "_input_type": "MessageTextInput", diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Hybrid Search RAG.json b/src/backend/base/langflow/initial_setup/starter_projects/Hybrid Search RAG.json index ed742372645a..0162b2dca1db 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Hybrid Search RAG.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Hybrid Search RAG.json @@ -2050,7 +2050,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from typing import Any\n\nfrom langchain_anthropic import ChatAnthropic\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider. \"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\", \"Anthropic\", \"Google\"],\n value=\"OpenAI\",\n info=\"Select the model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}, {\"icon\": \"Anthropic\"}, {\"icon\": \"Google\"}],\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n info=\"Select the model to use\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=True,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n provider = self.provider\n model_name = self.model_name\n temperature = self.temperature\n stream = self.stream\n\n if provider == \"OpenAI\":\n if not self.api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n return ChatOpenAI(\n model_name=model_name,\n temperature=temperature,\n streaming=stream,\n openai_api_key=self.api_key,\n )\n if provider == \"Anthropic\":\n if not self.api_key:\n msg = \"Anthropic API key is required when using Anthropic provider\"\n raise ValueError(msg)\n return ChatAnthropic(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n anthropic_api_key=self.api_key,\n )\n if provider == \"Google\":\n if not self.api_key:\n msg = \"Google API key is required when using Google provider\"\n raise ValueError(msg)\n return ChatGoogleGenerativeAI(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n google_api_key=self.api_key,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\":\n if field_value == \"OpenAI\":\n build_config[\"model_name\"][\"options\"] = OPENAI_MODEL_NAMES\n build_config[\"model_name\"][\"value\"] = OPENAI_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n elif field_value == \"Anthropic\":\n build_config[\"model_name\"][\"options\"] = ANTHROPIC_MODELS\n build_config[\"model_name\"][\"value\"] = ANTHROPIC_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Anthropic API Key\"\n elif field_value == \"Google\":\n build_config[\"model_name\"][\"options\"] = GOOGLE_GENERATIVE_AI_MODELS\n build_config[\"model_name\"][\"value\"] = GOOGLE_GENERATIVE_AI_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Google API Key\"\n return build_config\n" + "value": "from typing import Any\n\nfrom langchain_anthropic import ChatAnthropic\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider. \"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\", \"Anthropic\", \"Google\"],\n value=\"OpenAI\",\n info=\"Select the model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}, {\"icon\": \"Anthropic\"}, {\"icon\": \"GoogleGenerativeAI\"}],\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n info=\"Select the model to use\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=True,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n provider = self.provider\n model_name = self.model_name\n temperature = self.temperature\n stream = self.stream\n\n if provider == \"OpenAI\":\n if not self.api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n return ChatOpenAI(\n model_name=model_name,\n temperature=temperature,\n streaming=stream,\n openai_api_key=self.api_key,\n )\n if provider == \"Anthropic\":\n if not self.api_key:\n msg = \"Anthropic API key is required when using Anthropic provider\"\n raise ValueError(msg)\n return ChatAnthropic(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n anthropic_api_key=self.api_key,\n )\n if provider == \"Google\":\n if not self.api_key:\n msg = \"Google API key is required when using Google provider\"\n raise ValueError(msg)\n return ChatGoogleGenerativeAI(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n google_api_key=self.api_key,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\":\n if field_value == \"OpenAI\":\n build_config[\"model_name\"][\"options\"] = OPENAI_MODEL_NAMES\n build_config[\"model_name\"][\"value\"] = OPENAI_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n elif field_value == \"Anthropic\":\n build_config[\"model_name\"][\"options\"] = ANTHROPIC_MODELS\n build_config[\"model_name\"][\"value\"] = ANTHROPIC_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Anthropic API Key\"\n elif field_value == \"Google\":\n build_config[\"model_name\"][\"options\"] = GOOGLE_GENERATIVE_AI_MODELS\n build_config[\"model_name\"][\"value\"] = GOOGLE_GENERATIVE_AI_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Google API Key\"\n return build_config\n" }, "input_value": { "_input_type": "MessageInput", @@ -2338,7 +2338,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from typing import Any\n\nfrom langchain_anthropic import ChatAnthropic\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider. \"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\", \"Anthropic\", \"Google\"],\n value=\"OpenAI\",\n info=\"Select the model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}, {\"icon\": \"Anthropic\"}, {\"icon\": \"Google\"}],\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n info=\"Select the model to use\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=True,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n provider = self.provider\n model_name = self.model_name\n temperature = self.temperature\n stream = self.stream\n\n if provider == \"OpenAI\":\n if not self.api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n return ChatOpenAI(\n model_name=model_name,\n temperature=temperature,\n streaming=stream,\n openai_api_key=self.api_key,\n )\n if provider == \"Anthropic\":\n if not self.api_key:\n msg = \"Anthropic API key is required when using Anthropic provider\"\n raise ValueError(msg)\n return ChatAnthropic(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n anthropic_api_key=self.api_key,\n )\n if provider == \"Google\":\n if not self.api_key:\n msg = \"Google API key is required when using Google provider\"\n raise ValueError(msg)\n return ChatGoogleGenerativeAI(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n google_api_key=self.api_key,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\":\n if field_value == \"OpenAI\":\n build_config[\"model_name\"][\"options\"] = OPENAI_MODEL_NAMES\n build_config[\"model_name\"][\"value\"] = OPENAI_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n elif field_value == \"Anthropic\":\n build_config[\"model_name\"][\"options\"] = ANTHROPIC_MODELS\n build_config[\"model_name\"][\"value\"] = ANTHROPIC_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Anthropic API Key\"\n elif field_value == \"Google\":\n build_config[\"model_name\"][\"options\"] = GOOGLE_GENERATIVE_AI_MODELS\n build_config[\"model_name\"][\"value\"] = GOOGLE_GENERATIVE_AI_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Google API Key\"\n return build_config\n" + "value": "from typing import Any\n\nfrom langchain_anthropic import ChatAnthropic\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider. \"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\", \"Anthropic\", \"Google\"],\n value=\"OpenAI\",\n info=\"Select the model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}, {\"icon\": \"Anthropic\"}, {\"icon\": \"GoogleGenerativeAI\"}],\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n info=\"Select the model to use\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=True,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n provider = self.provider\n model_name = self.model_name\n temperature = self.temperature\n stream = self.stream\n\n if provider == \"OpenAI\":\n if not self.api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n return ChatOpenAI(\n model_name=model_name,\n temperature=temperature,\n streaming=stream,\n openai_api_key=self.api_key,\n )\n if provider == \"Anthropic\":\n if not self.api_key:\n msg = \"Anthropic API key is required when using Anthropic provider\"\n raise ValueError(msg)\n return ChatAnthropic(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n anthropic_api_key=self.api_key,\n )\n if provider == \"Google\":\n if not self.api_key:\n msg = \"Google API key is required when using Google provider\"\n raise ValueError(msg)\n return ChatGoogleGenerativeAI(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n google_api_key=self.api_key,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\":\n if field_value == \"OpenAI\":\n build_config[\"model_name\"][\"options\"] = OPENAI_MODEL_NAMES\n build_config[\"model_name\"][\"value\"] = OPENAI_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n elif field_value == \"Anthropic\":\n build_config[\"model_name\"][\"options\"] = ANTHROPIC_MODELS\n build_config[\"model_name\"][\"value\"] = ANTHROPIC_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Anthropic API Key\"\n elif field_value == \"Google\":\n build_config[\"model_name\"][\"options\"] = GOOGLE_GENERATIVE_AI_MODELS\n build_config[\"model_name\"][\"value\"] = GOOGLE_GENERATIVE_AI_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Google API Key\"\n return build_config\n" }, "input_value": { "_input_type": "MessageInput", diff --git a/src/backend/base/langflow/initial_setup/starter_projects/SEO Keyword Generator.json b/src/backend/base/langflow/initial_setup/starter_projects/SEO Keyword Generator.json index 0ec42a571cee..491c49ccaeea 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/SEO Keyword Generator.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/SEO Keyword Generator.json @@ -341,8 +341,8 @@ }, "tool_mode": false }, - "type": "Prompt", - "selected_output": "prompt" + "selected_output": "prompt", + "type": "Prompt" }, "dragging": false, "height": 779, @@ -505,8 +505,8 @@ }, "tool_mode": false }, - "type": "Prompt", - "selected_output": "prompt" + "selected_output": "prompt", + "type": "Prompt" }, "dragging": false, "height": 260, @@ -963,7 +963,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from typing import Any\n\nfrom langchain_anthropic import ChatAnthropic\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider. \"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\", \"Anthropic\", \"Google\"],\n value=\"OpenAI\",\n info=\"Select the model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}, {\"icon\": \"Anthropic\"}, {\"icon\": \"Google\"}],\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n info=\"Select the model to use\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=True,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n provider = self.provider\n model_name = self.model_name\n temperature = self.temperature\n stream = self.stream\n\n if provider == \"OpenAI\":\n if not self.api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n return ChatOpenAI(\n model_name=model_name,\n temperature=temperature,\n streaming=stream,\n openai_api_key=self.api_key,\n )\n if provider == \"Anthropic\":\n if not self.api_key:\n msg = \"Anthropic API key is required when using Anthropic provider\"\n raise ValueError(msg)\n return ChatAnthropic(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n anthropic_api_key=self.api_key,\n )\n if provider == \"Google\":\n if not self.api_key:\n msg = \"Google API key is required when using Google provider\"\n raise ValueError(msg)\n return ChatGoogleGenerativeAI(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n google_api_key=self.api_key,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\":\n if field_value == \"OpenAI\":\n build_config[\"model_name\"][\"options\"] = OPENAI_MODEL_NAMES\n build_config[\"model_name\"][\"value\"] = OPENAI_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n elif field_value == \"Anthropic\":\n build_config[\"model_name\"][\"options\"] = ANTHROPIC_MODELS\n build_config[\"model_name\"][\"value\"] = ANTHROPIC_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Anthropic API Key\"\n elif field_value == \"Google\":\n build_config[\"model_name\"][\"options\"] = GOOGLE_GENERATIVE_AI_MODELS\n build_config[\"model_name\"][\"value\"] = GOOGLE_GENERATIVE_AI_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Google API Key\"\n return build_config\n" + "value": "from typing import Any\n\nfrom langchain_anthropic import ChatAnthropic\nfrom langchain_google_genai import ChatGoogleGenerativeAI\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider. \"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\", \"Anthropic\", \"Google\"],\n value=\"OpenAI\",\n info=\"Select the model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}, {\"icon\": \"Anthropic\"}, {\"icon\": \"GoogleGenerativeAI\"}],\n ),\n DropdownInput(\n name=\"model_name\",\n display_name=\"Model Name\",\n options=OPENAI_MODEL_NAMES,\n value=OPENAI_MODEL_NAMES[0],\n info=\"Select the model to use\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=True,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n provider = self.provider\n model_name = self.model_name\n temperature = self.temperature\n stream = self.stream\n\n if provider == \"OpenAI\":\n if not self.api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n return ChatOpenAI(\n model_name=model_name,\n temperature=temperature,\n streaming=stream,\n openai_api_key=self.api_key,\n )\n if provider == \"Anthropic\":\n if not self.api_key:\n msg = \"Anthropic API key is required when using Anthropic provider\"\n raise ValueError(msg)\n return ChatAnthropic(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n anthropic_api_key=self.api_key,\n )\n if provider == \"Google\":\n if not self.api_key:\n msg = \"Google API key is required when using Google provider\"\n raise ValueError(msg)\n return ChatGoogleGenerativeAI(\n model=model_name,\n temperature=temperature,\n streaming=stream,\n google_api_key=self.api_key,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\":\n if field_value == \"OpenAI\":\n build_config[\"model_name\"][\"options\"] = OPENAI_MODEL_NAMES\n build_config[\"model_name\"][\"value\"] = OPENAI_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n elif field_value == \"Anthropic\":\n build_config[\"model_name\"][\"options\"] = ANTHROPIC_MODELS\n build_config[\"model_name\"][\"value\"] = ANTHROPIC_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Anthropic API Key\"\n elif field_value == \"Google\":\n build_config[\"model_name\"][\"options\"] = GOOGLE_GENERATIVE_AI_MODELS\n build_config[\"model_name\"][\"value\"] = GOOGLE_GENERATIVE_AI_MODELS[0]\n build_config[\"api_key\"][\"display_name\"] = \"Google API Key\"\n return build_config\n" }, "input_value": { "_input_type": "MessageTextInput", From e994f27c8d3d8995267069cae96bc8a761869185 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 23 Jun 2025 20:50:31 -0300 Subject: [PATCH 10/12] feat(tests): add authentication token retrieval for starter projects integration tests * Implemented a helper function to obtain a JWT token for API requests, enhancing the security of the integration tests. * Updated the test for starter projects to include the token in API requests, ensuring proper authentication during testing. --- .../integrations/starter-projects.spec.ts | 35 +++++++++++++++++-- 1 file changed, 33 insertions(+), 2 deletions(-) diff --git a/src/frontend/tests/core/integrations/starter-projects.spec.ts b/src/frontend/tests/core/integrations/starter-projects.spec.ts index 065ed1166e7a..e783b4eb8206 100644 --- a/src/frontend/tests/core/integrations/starter-projects.spec.ts +++ b/src/frontend/tests/core/integrations/starter-projects.spec.ts @@ -1,11 +1,36 @@ import { expect, test } from "@playwright/test"; import { awaitBootstrapTest } from "../../utils/await-bootstrap-test"; +// Helper function to get JWT token for API requests +async function getAuthToken(request: any) { + const formData = new URLSearchParams(); + formData.append("username", "langflow"); + formData.append("password", "langflow"); + + const loginResponse = await request.post("/api/v1/login", { + headers: { + "Content-Type": "application/x-www-form-urlencoded", + }, + data: formData.toString(), + }); + + expect(loginResponse.status()).toBe(200); + const tokenData = await loginResponse.json(); + return tokenData.access_token; +} + test( "vector store from starter projects should have its connections and nodes on the flow", { tag: ["@release", "@starter-projects"] }, async ({ page, request }) => { - const response = await request.get("/api/v1/starter-projects"); + // Get authentication token + const authToken = await getAuthToken(request); + + const response = await request.get("/api/v1/starter-projects", { + headers: { + Authorization: `Bearer ${authToken}`, + }, + }); expect(response.status()).toBe(200); const responseBody = await response.json(); @@ -18,7 +43,13 @@ test( await page.route("**/api/v1/flows/", async (route) => { if (route.request().method() === "GET") { try { - const response = await route.fetch(); + // Add authorization header to the request + const headers = route.request().headers(); + headers["Authorization"] = `Bearer ${authToken}`; + + const response = await route.fetch({ + headers: headers, + }); const flowsData = await response.json(); const modifiedFlows = flowsData.map((flow) => { From bd02e350b8e2b93618816db9c95e3aeb47c53dcf Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Tue, 24 Jun 2025 10:08:21 -0300 Subject: [PATCH 11/12] feat(auth): add MCP-specific user authentication and active user dependency * Introduced `get_current_user_mcp` function for MCP-specific user authentication, allowing fallback to username lookup when no API key is provided. * Added `get_current_active_user_mcp` dependency to manage active user checks for MCP, ensuring proper integration with the authentication flow. --- src/backend/base/langflow/api/utils.py | 3 +- .../base/langflow/services/auth/utils.py | 78 +++++++++++++++++++ 2 files changed, 80 insertions(+), 1 deletion(-) diff --git a/src/backend/base/langflow/api/utils.py b/src/backend/base/langflow/api/utils.py index d78edd6cd194..755613b75e6b 100644 --- a/src/backend/base/langflow/api/utils.py +++ b/src/backend/base/langflow/api/utils.py @@ -13,7 +13,7 @@ from sqlmodel.ext.asyncio.session import AsyncSession from langflow.graph.graph.base import Graph -from langflow.services.auth.utils import get_current_active_user +from langflow.services.auth.utils import get_current_active_user, get_current_active_user_mcp from langflow.services.database.models.flow.model import Flow from langflow.services.database.models.message.model import MessageTable from langflow.services.database.models.transactions.model import TransactionTable @@ -33,6 +33,7 @@ MIN_PAGE_SIZE = 1 CurrentActiveUser = Annotated[User, Depends(get_current_active_user)] +CurrentActiveMCPUser = Annotated[User, Depends(get_current_active_user_mcp)] DbSession = Annotated[AsyncSession, Depends(get_session)] diff --git a/src/backend/base/langflow/services/auth/utils.py b/src/backend/base/langflow/services/auth/utils.py index 8394952fa631..695ba3290f75 100644 --- a/src/backend/base/langflow/services/auth/utils.py +++ b/src/backend/base/langflow/services/auth/utils.py @@ -478,3 +478,81 @@ def decrypt_api_key(encrypted_api_key: str, settings_service: SettingsService): ) return fernet.decrypt(encrypted_api_key).decode() return "" + + +# MCP-specific authentication functions that always behave as if skip_auth_auto_login is True +async def get_current_user_mcp( + token: Annotated[str, Security(oauth2_login)], + query_param: Annotated[str, Security(api_key_query)], + header_param: Annotated[str, Security(api_key_header)], + db: Annotated[AsyncSession, Depends(get_session)], +) -> User: + """MCP-specific user authentication that always allows fallback to username lookup. + + This function provides authentication for MCP endpoints with special handling: + - If a JWT token is provided, it uses standard JWT authentication + - If no API key is provided and AUTO_LOGIN is enabled, it falls back to + username lookup using the configured superuser credentials + - Otherwise, it validates the provided API key (from query param or header) + """ + if token: + return await get_current_user_by_jwt(token, db) + + # MCP-specific authentication logic - always behaves as if skip_auth_auto_login is True + settings_service = get_settings_service() + result: ApiKey | User | None + + if settings_service.auth_settings.AUTO_LOGIN: + # Get the first user + if not settings_service.auth_settings.SUPERUSER: + raise HTTPException( + status_code=status.HTTP_400_BAD_REQUEST, + detail="Missing first superuser credentials", + ) + if not query_param and not header_param: + # For MCP endpoints, always fall back to username lookup when no API key is provided + result = await get_user_by_username(db, settings_service.auth_settings.SUPERUSER) + if result: + logger.warning(AUTO_LOGIN_WARNING) + return result + else: + result = await check_key(db, query_param or header_param) + + elif not query_param and not header_param: + raise HTTPException( + status_code=status.HTTP_403_FORBIDDEN, + detail="An API key must be passed as query or header", + ) + + elif query_param: + result = await check_key(db, query_param) + + else: + result = await check_key(db, header_param) + + if not result: + raise HTTPException( + status_code=status.HTTP_403_FORBIDDEN, + detail="Invalid or missing API key", + ) + + # If result is a User, return it directly + if isinstance(result, User): + return result + + # If result is an ApiKey, we need to get the associated user + # This should not happen in normal flow, but adding for completeness + raise HTTPException( + status_code=status.HTTP_403_FORBIDDEN, + detail="Invalid authentication result", + ) + + +async def get_current_active_user_mcp(current_user: Annotated[User, Depends(get_current_user_mcp)]): + """MCP-specific active user dependency. + + This dependency is temporary and will be removed once MCP is fully integrated. + """ + if not current_user.is_active: + raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="Inactive user") + return current_user From aa53ec689ff32ea7105e104b0c33aa4d36ae2378 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Tue, 24 Jun 2025 10:08:38 -0300 Subject: [PATCH 12/12] refactor(api): replace user dependency with CurrentActiveMCPUser in mcp project endpoints * Updated project-related API endpoints to use CurrentActiveMCPUser for user authentication, enhancing clarity and consistency in user management. * Removed unused imports and dependencies related to the previous user authentication method, streamlining the codebase. --- src/backend/base/langflow/api/v1/mcp.py | 8 +++--- .../base/langflow/api/v1/mcp_projects.py | 25 ++++++++----------- 2 files changed, 14 insertions(+), 19 deletions(-) diff --git a/src/backend/base/langflow/api/v1/mcp.py b/src/backend/base/langflow/api/v1/mcp.py index 3b6296130239..5c1eb6dfe36f 100644 --- a/src/backend/base/langflow/api/v1/mcp.py +++ b/src/backend/base/langflow/api/v1/mcp.py @@ -3,13 +3,13 @@ from collections.abc import Awaitable, Callable from contextvars import ContextVar from functools import wraps -from typing import Annotated, Any, ParamSpec, TypeVar +from typing import Any, ParamSpec, TypeVar from urllib.parse import quote, unquote, urlparse from uuid import uuid4 import pydantic from anyio import BrokenResourceError -from fastapi import APIRouter, Depends, HTTPException, Request, Response +from fastapi import APIRouter, HTTPException, Request, Response from fastapi.responses import HTMLResponse, StreamingResponse from loguru import logger from mcp import types @@ -17,13 +17,13 @@ from mcp.server.sse import SseServerTransport from sqlmodel import select +from langflow.api.utils import CurrentActiveMCPUser from langflow.api.v1.endpoints import simple_run_flow from langflow.api.v1.schemas import SimplifiedAPIRequest from langflow.base.mcp.constants import MAX_MCP_TOOL_NAME_LENGTH from langflow.base.mcp.util import get_flow_snake_case from langflow.helpers.flow import json_schema_from_flow from langflow.schema.message import Message -from langflow.services.auth.utils import get_current_active_user from langflow.services.database.models.flow.model import Flow from langflow.services.database.models.user.model import User from langflow.services.deps import ( @@ -345,7 +345,7 @@ async def im_alive(): @router.get("/sse", response_class=StreamingResponse) -async def handle_sse(request: Request, current_user: Annotated[User, Depends(get_current_active_user)]): +async def handle_sse(request: Request, current_user: CurrentActiveMCPUser): msg = f"Starting SSE connection, server name: {server.name}" logger.info(msg) token = current_user_ctx.set(current_user) diff --git a/src/backend/base/langflow/api/v1/mcp_projects.py b/src/backend/base/langflow/api/v1/mcp_projects.py index 4b7ea39fe6a0..6e3b34e81202 100644 --- a/src/backend/base/langflow/api/v1/mcp_projects.py +++ b/src/backend/base/langflow/api/v1/mcp_projects.py @@ -9,12 +9,11 @@ from datetime import datetime, timezone from ipaddress import ip_address from pathlib import Path -from typing import Annotated from urllib.parse import quote, unquote, urlparse from uuid import UUID, uuid4 from anyio import BrokenResourceError -from fastapi import APIRouter, Depends, HTTPException, Request, Response +from fastapi import APIRouter, HTTPException, Request, Response from fastapi.responses import HTMLResponse from mcp import types from mcp.server import NotificationOptions, Server @@ -22,6 +21,7 @@ from sqlalchemy.orm import selectinload from sqlmodel import select +from langflow.api.utils import CurrentActiveMCPUser from langflow.api.v1.endpoints import simple_run_flow from langflow.api.v1.mcp import ( current_user_ctx, @@ -34,8 +34,7 @@ from langflow.base.mcp.util import get_flow_snake_case, get_unique_name from langflow.helpers.flow import json_schema_from_flow from langflow.schema.message import Message -from langflow.services.auth.utils import get_current_active_user -from langflow.services.database.models import Flow, Folder, User +from langflow.services.database.models import Flow, Folder from langflow.services.database.models.folder.constants import DEFAULT_FOLDER_NAME, NEW_FOLDER_NAME from langflow.services.deps import get_settings_service, get_storage_service, session_scope from langflow.services.storage.utils import build_content_type_from_extension @@ -62,7 +61,7 @@ def get_project_sse(project_id: UUID) -> SseServerTransport: @router.get("/{project_id}") async def list_project_tools( project_id: UUID, - current_user: Annotated[User, Depends(get_current_active_user)], + current_user: CurrentActiveMCPUser, *, mcp_enabled: bool = True, ) -> list[MCPSettings]: @@ -136,7 +135,7 @@ async def im_alive(): async def handle_project_sse( project_id: UUID, request: Request, - current_user: Annotated[User, Depends(get_current_active_user)], + current_user: CurrentActiveMCPUser, ): """Handle SSE connections for a specific project.""" # Verify project exists and user has access @@ -187,9 +186,7 @@ async def handle_project_sse( @router.post("/{project_id}") -async def handle_project_messages( - project_id: UUID, request: Request, current_user: Annotated[User, Depends(get_current_active_user)] -): +async def handle_project_messages(project_id: UUID, request: Request, current_user: CurrentActiveMCPUser): """Handle POST messages for a project-specific MCP server.""" # Verify project exists and user has access async with session_scope() as session: @@ -216,9 +213,7 @@ async def handle_project_messages( @router.post("/{project_id}/") -async def handle_project_messages_with_slash( - project_id: UUID, request: Request, current_user: Annotated[User, Depends(get_current_active_user)] -): +async def handle_project_messages_with_slash(project_id: UUID, request: Request, current_user: CurrentActiveMCPUser): """Handle POST messages for a project-specific MCP server with trailing slash.""" # Call the original handler return await handle_project_messages(project_id, request, current_user) @@ -228,7 +223,7 @@ async def handle_project_messages_with_slash( async def update_project_mcp_settings( project_id: UUID, settings: list[MCPSettings], - current_user: Annotated[User, Depends(get_current_active_user)], + current_user: CurrentActiveMCPUser, ): """Update the MCP settings of all flows in a project.""" try: @@ -329,7 +324,7 @@ async def install_mcp_config( project_id: UUID, body: MCPInstallRequest, request: Request, - current_user: Annotated[User, Depends(get_current_active_user)], + current_user: CurrentActiveMCPUser, ): """Install MCP server configuration for Cursor or Claude.""" # Check if the request is coming from a local IP address @@ -452,7 +447,7 @@ async def install_mcp_config( @router.get("/{project_id}/installed") async def check_installed_mcp_servers( project_id: UUID, - current_user: Annotated[User, Depends(get_current_active_user)], + current_user: CurrentActiveMCPUser, ): """Check if MCP server configuration is installed for this project in Cursor or Claude.""" try: