fix: Disable tool model by default in various model components (#5989)

* fix: Disable tool model by default in various model components

Update multiple model components to set the `tool_model_enabled` parameter to `False` by default, ensuring a more conservative initial configuration for tool-based models across Anthropic, Google Generative AI, Groq, NVIDIA, and Ollama components.

* [autofix.ci] apply automated fixes

---------

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>

src/backend/base/langflow/components/models/anthropic.py

@@ -63,7 +63,7 @@ class AnthropicModelComponent(LCModelComponent):
                 "Select if you want to use models that can work with tools. If yes, only those models will be shown."
             ),
             advanced=False,
-            value=True,
+            value=False,
             real_time_refresh=True,
         ),
         MessageTextInput(

src/backend/base/langflow/components/models/google_generative_ai.py

@@ -70,6 +70,7 @@ class GoogleGenerativeAIComponent(LCModelComponent):
             name="tool_model_enabled",
             display_name="Tool Model Enabled",
             info="Whether to use the tool model.",
+            value=False,
         ),
     ]
 

src/backend/base/langflow/components/models/groq.py

@@ -70,7 +70,7 @@ class GroqModel(LCModelComponent):
                 "Select if you want to use models that can work with tools. If yes, only those models will be shown."
             ),
             advanced=False,
-            value=True,
+            value=False,
             real_time_refresh=True,
         ),
     ]

src/backend/base/langflow/components/models/nvidia.py

@@ -43,7 +43,7 @@ class NVIDIAModelComponent(LCModelComponent):
                 "Select if you want to use models that can work with tools. If yes, only those models will be shown."
             ),
             advanced=False,
-            value=True,
+            value=False,
             real_time_refresh=True,
         ),
         SecretStrInput(

src/backend/base/langflow/components/models/ollama.py

@@ -118,7 +118,7 @@ class ChatOllamaComponent(LCModelComponent):
             name="tool_model_enabled",
             display_name="Tool Model Enabled",
             info="Whether to enable tool calling in the model.",
-            value=True,
+            value=False,
             real_time_refresh=True,
         ),
         MessageTextInput(

src/backend/base/langflow/initial_setup/starter_projects/Custom Component Maker.json

@@ -1932,7 +1932,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from typing import Any\n\nimport requests\nfrom loguru import logger\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.io import BoolInput, DropdownInput, IntInput, MessageTextInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass AnthropicModelComponent(LCModelComponent):\n    display_name = \"Anthropic\"\n    description = \"Generate text using Anthropic Chat&Completion LLMs with prefill support.\"\n    icon = \"Anthropic\"\n    name = \"AnthropicModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            value=4096,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            options=ANTHROPIC_MODELS,\n            refresh_button=True,\n            value=ANTHROPIC_MODELS[0],\n            combobox=True,\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"Anthropic API Key\",\n            info=\"Your Anthropic API key.\",\n            value=None,\n            required=True,\n            real_time_refresh=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            info=\"Run inference with this temperature. Must by in the closed interval [0.0, 1.0].\",\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n        ),\n        MessageTextInput(\n            name=\"base_url\",\n            display_name=\"Anthropic API URL\",\n            info=\"Endpoint of the Anthropic API. Defaults to 'https://api.anthropic.com' if not specified.\",\n            value=\"https://api.anthropic.com\",\n            real_time_refresh=True,\n        ),\n        BoolInput(\n            name=\"tool_model_enabled\",\n            display_name=\"Enable Tool Models\",\n            info=(\n                \"Select if you want to use models that can work with tools. If yes, only those models will be shown.\"\n            ),\n            advanced=False,\n            value=True,\n            real_time_refresh=True,\n        ),\n        MessageTextInput(\n            name=\"prefill\", display_name=\"Prefill\", info=\"Prefill text to guide the model's response.\", advanced=True\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        try:\n            from langchain_anthropic.chat_models import ChatAnthropic\n        except ImportError as e:\n            msg = \"langchain_anthropic is not installed. Please install it with `pip install langchain_anthropic`.\"\n            raise ImportError(msg) from e\n        try:\n            output = ChatAnthropic(\n                model=self.model_name,\n                anthropic_api_key=self.api_key,\n                max_tokens_to_sample=self.max_tokens,\n                temperature=self.temperature,\n                anthropic_api_url=self.base_url,\n                streaming=self.stream,\n            )\n        except Exception as e:\n            msg = \"Could not connect to Anthropic API.\"\n            raise ValueError(msg) from e\n\n        return output\n\n    def get_models(self, tool_model_enabled: bool | None = None) -> list[str]:\n        try:\n            import anthropic\n\n            client = anthropic.Anthropic(api_key=self.api_key)\n            models = client.models.list(limit=20).data\n            model_ids = [model.id for model in models]\n        except (ImportError, ValueError, requests.exceptions.RequestException) as e:\n            logger.exception(f\"Error getting model names: {e}\")\n            model_ids = ANTHROPIC_MODELS\n        if tool_model_enabled:\n            try:\n                from langchain_anthropic.chat_models import ChatAnthropic\n            except ImportError as e:\n                msg = \"langchain_anthropic is not installed. Please install it with `pip install langchain_anthropic`.\"\n                raise ImportError(msg) from e\n            for model in model_ids:\n                model_with_tool = ChatAnthropic(\n                    model=self.model_name,\n                    anthropic_api_key=self.api_key,\n                    anthropic_api_url=self.base_url,\n                )\n                if not self.supports_tool_calling(model_with_tool):\n                    model_ids.remove(model)\n        return model_ids\n\n    def _get_exception_message(self, exception: Exception) -> str | None:\n        \"\"\"Get a message from an Anthropic exception.\n\n        Args:\n            exception (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from anthropic import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(exception, BadRequestError):\n            message = exception.body.get(\"error\", {}).get(\"message\")\n            if message:\n                return message\n        return None\n\n    def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None):\n        if field_name in (\"base_url\", \"model_name\", \"tool_model_enabled\", \"api_key\") and field_value:\n            try:\n                if len(self.api_key) == 0:\n                    ids = ANTHROPIC_MODELS\n                else:\n                    try:\n                        ids = self.get_models(tool_model_enabled=self.tool_model_enabled)\n                    except (ImportError, ValueError, requests.exceptions.RequestException) as e:\n                        logger.exception(f\"Error getting model names: {e}\")\n                        ids = ANTHROPIC_MODELS\n                build_config[\"model_name\"][\"options\"] = ids\n                build_config[\"model_name\"][\"value\"] = ids[0]\n            except Exception as e:\n                msg = f\"Error getting model names: {e}\"\n                raise ValueError(msg) from e\n        return build_config\n"
+                "value": "from typing import Any\n\nimport requests\nfrom loguru import logger\n\nfrom langflow.base.models.anthropic_constants import ANTHROPIC_MODELS\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.io import BoolInput, DropdownInput, IntInput, MessageTextInput, SecretStrInput, SliderInput\nfrom langflow.schema.dotdict import dotdict\n\n\nclass AnthropicModelComponent(LCModelComponent):\n    display_name = \"Anthropic\"\n    description = \"Generate text using Anthropic Chat&Completion LLMs with prefill support.\"\n    icon = \"Anthropic\"\n    name = \"AnthropicModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            value=4096,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            options=ANTHROPIC_MODELS,\n            refresh_button=True,\n            value=ANTHROPIC_MODELS[0],\n            combobox=True,\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"Anthropic API Key\",\n            info=\"Your Anthropic API key.\",\n            value=None,\n            required=True,\n            real_time_refresh=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            info=\"Run inference with this temperature. Must by in the closed interval [0.0, 1.0].\",\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n        ),\n        MessageTextInput(\n            name=\"base_url\",\n            display_name=\"Anthropic API URL\",\n            info=\"Endpoint of the Anthropic API. Defaults to 'https://api.anthropic.com' if not specified.\",\n            value=\"https://api.anthropic.com\",\n            real_time_refresh=True,\n        ),\n        BoolInput(\n            name=\"tool_model_enabled\",\n            display_name=\"Enable Tool Models\",\n            info=(\n                \"Select if you want to use models that can work with tools. If yes, only those models will be shown.\"\n            ),\n            advanced=False,\n            value=False,\n            real_time_refresh=True,\n        ),\n        MessageTextInput(\n            name=\"prefill\", display_name=\"Prefill\", info=\"Prefill text to guide the model's response.\", advanced=True\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        try:\n            from langchain_anthropic.chat_models import ChatAnthropic\n        except ImportError as e:\n            msg = \"langchain_anthropic is not installed. Please install it with `pip install langchain_anthropic`.\"\n            raise ImportError(msg) from e\n        try:\n            output = ChatAnthropic(\n                model=self.model_name,\n                anthropic_api_key=self.api_key,\n                max_tokens_to_sample=self.max_tokens,\n                temperature=self.temperature,\n                anthropic_api_url=self.base_url,\n                streaming=self.stream,\n            )\n        except Exception as e:\n            msg = \"Could not connect to Anthropic API.\"\n            raise ValueError(msg) from e\n\n        return output\n\n    def get_models(self, tool_model_enabled: bool | None = None) -> list[str]:\n        try:\n            import anthropic\n\n            client = anthropic.Anthropic(api_key=self.api_key)\n            models = client.models.list(limit=20).data\n            model_ids = [model.id for model in models]\n        except (ImportError, ValueError, requests.exceptions.RequestException) as e:\n            logger.exception(f\"Error getting model names: {e}\")\n            model_ids = ANTHROPIC_MODELS\n        if tool_model_enabled:\n            try:\n                from langchain_anthropic.chat_models import ChatAnthropic\n            except ImportError as e:\n                msg = \"langchain_anthropic is not installed. Please install it with `pip install langchain_anthropic`.\"\n                raise ImportError(msg) from e\n            for model in model_ids:\n                model_with_tool = ChatAnthropic(\n                    model=self.model_name,\n                    anthropic_api_key=self.api_key,\n                    anthropic_api_url=self.base_url,\n                )\n                if not self.supports_tool_calling(model_with_tool):\n                    model_ids.remove(model)\n        return model_ids\n\n    def _get_exception_message(self, exception: Exception) -> str | None:\n        \"\"\"Get a message from an Anthropic exception.\n\n        Args:\n            exception (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from anthropic import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(exception, BadRequestError):\n            message = exception.body.get(\"error\", {}).get(\"message\")\n            if message:\n                return message\n        return None\n\n    def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None):\n        if field_name in (\"base_url\", \"model_name\", \"tool_model_enabled\", \"api_key\") and field_value:\n            try:\n                if len(self.api_key) == 0:\n                    ids = ANTHROPIC_MODELS\n                else:\n                    try:\n                        ids = self.get_models(tool_model_enabled=self.tool_model_enabled)\n                    except (ImportError, ValueError, requests.exceptions.RequestException) as e:\n                        logger.exception(f\"Error getting model names: {e}\")\n                        ids = ANTHROPIC_MODELS\n                build_config[\"model_name\"][\"options\"] = ids\n                build_config[\"model_name\"][\"value\"] = ids[0]\n            except Exception as e:\n                msg = f\"Error getting model names: {e}\"\n                raise ValueError(msg) from e\n        return build_config\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",