bind_tools() — langchain Function Reference

Architecture documentation for the bind_tools() function in chat_models.py from the langchain codebase.

Function python LangChainCore LanguageModelBase called by 1

Entity Profile

LangChainCore→ LanguageModelBase→ bind_tools() — langchain Function Reference

Dependency Diagram

graph TD
  a2a1473b_d07e_f130_17fd_57f36ea7a804["bind_tools()"]
  d5ca3c3a_3c29_0cb2_a156_35c92a31f5fd["ChatGroq"]
  a2a1473b_d07e_f130_17fd_57f36ea7a804 -->|defined in| d5ca3c3a_3c29_0cb2_a156_35c92a31f5fd
  fd162549_9cc7_f8f4_7877_2bc28c45cf20["with_structured_output()"]
  fd162549_9cc7_f8f4_7877_2bc28c45cf20 -->|calls| a2a1473b_d07e_f130_17fd_57f36ea7a804
  style a2a1473b_d07e_f130_17fd_57f36ea7a804 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/partners/groq/langchain_groq/chat_models.py lines 849–896

    def bind_tools(
        self,
        tools: Sequence[dict[str, Any] | type[BaseModel] | Callable | BaseTool],
        *,
        tool_choice: dict | str | bool | None = None,
        **kwargs: Any,
    ) -> Runnable[LanguageModelInput, AIMessage]:
        """Bind tool-like objects to this chat model.

        Args:
            tools: A list of tool definitions to bind to this chat model.

                Supports any tool definition handled by [`convert_to_openai_tool`][langchain_core.utils.function_calling.convert_to_openai_tool].
            tool_choice: Which tool to require the model to call.
                Must be the name of the single provided function,
                `'auto'` to automatically determine which function to call
                with the option to not call any function, `'any'` to enforce that some
                function is called, or a dict of the form:
                `{"type": "function", "function": {"name": <<tool_name>>}}`.
            **kwargs: Any additional parameters to pass to the
                `langchain.runnable.Runnable` constructor.
        """  # noqa: E501
        # strict tool-calling not supported by Groq
        _ = kwargs.pop("strict", None)

        formatted_tools = [convert_to_openai_tool(tool) for tool in tools]
        if tool_choice is not None and tool_choice:
            if tool_choice == "any":
                tool_choice = "required"
            if isinstance(tool_choice, str) and (
                tool_choice not in ("auto", "none", "required")
            ):
                tool_choice = {"type": "function", "function": {"name": tool_choice}}
            if isinstance(tool_choice, bool):
                if len(tools) > 1:
                    msg = (
                        "tool_choice can only be True when there is one tool. Received "
                        f"{len(tools)} tools."
                    )
                    raise ValueError(msg)
                tool_name = formatted_tools[0]["function"]["name"]
                tool_choice = {
                    "type": "function",
                    "function": {"name": tool_name},
                }

            kwargs["tool_choice"] = tool_choice
        return super().bind(tools=formatted_tools, **kwargs)