bind_tools() — langchain Function Reference

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

Function python LangChainCore LanguageModelBase

Entity Profile

LangChainCore→ LanguageModelBase→ bind_tools() — langchain Function Reference

Dependency Diagram

graph TD
  545f16bd_426f_c50e_470a_f45133e1a080["bind_tools()"]
  f3181e26_0568_4993_612c_5b8d73ad3c37["ChatDeepSeek"]
  545f16bd_426f_c50e_470a_f45133e1a080 -->|defined in| f3181e26_0568_4993_612c_5b8d73ad3c37
  style 545f16bd_426f_c50e_470a_f45133e1a080 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/partners/deepseek/langchain_deepseek/chat_models.py lines 395–437

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

        Overrides parent to use beta endpoint when `strict=True`.

        Args:
            tools: A list of tool definitions to bind to this chat model.
            tool_choice: Which tool to require the model to call.
            strict: If True, uses beta API for strict schema validation.
            parallel_tool_calls: Set to `False` to disable parallel tool use.
            **kwargs: Additional parameters passed to parent `bind_tools`.

        Returns:
            A Runnable that takes same inputs as a chat model.
        """
        # If strict mode is enabled and using default API base, switch to beta endpoint
        if strict is True and self.api_base == DEFAULT_API_BASE:
            # Create a new instance with beta endpoint
            beta_model = self.model_copy(update={"api_base": DEFAULT_BETA_API_BASE})
            return beta_model.bind_tools(
                tools,
                tool_choice=tool_choice,
                strict=strict,
                parallel_tool_calls=parallel_tool_calls,
                **kwargs,
            )

        # Otherwise use parent implementation
        return super().bind_tools(
            tools,
            tool_choice=tool_choice,
            strict=strict,
            parallel_tool_calls=parallel_tool_calls,
            **kwargs,
        )