LangChain messages abstract provider-specific tool call formats by using a unified AIMessage.tool_calls field that normalizes different API responses into a consistent structure (list of {name, args, id}), and ToolMessage for returning results. You never need to handle provider differences directly.
LangChain's message objects provide an abstraction layer over the raw API responses from different providers. When you call model.bind_tools() and invoke the model, the returned AIMessage will always have a tool_calls attribute, regardless of whether the underlying provider is OpenAI, Anthropic, or Google Gemini. This attribute is a list of dictionaries each containing name, args, and id. Similarly, you use ToolMessage to return results, and LangChain serializes it correctly for each provider. Behind the scenes, LangChain uses convert_to_openai_tool, convert_to_anthropic_tool, etc., to transform the unified representation. This allows you to write provider-agnostic agent code.