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  • Tool calling | ️ LangChain
    LangChain allows you to enforce tool choice (using tool_choice), ensuring the model uses either a particular tool or any tool from a given list This is useful for structuring the model's behavior and guiding it towards a desired outcome
  • How to force tool calling behavior | ️ Langchain
    In order to force our LLM to select a specific tool, we can use the tool_choice parameter to ensure certain behavior First, let’s define our model and tools: name: "add", description: "Adds a and b ", schema: z object({ a: z number(), b: z number(), name: "Multiply", description: "Multiplies a and b ", schema: z object({ a: z number(),
  • Standardizing Tool Calling with Chat Models · langchain-ai langchain . . .
    ChatModel bind_tools(): a method for attaching tool definitions to model calls AIMessage tool_calls: an attribute on the AIMessage returned from the model for easily accessing the tool calls the model decided to make create_tool_calling_agent(): an agent constructor that works with ANY model that implements bind_tools and returns tool_calls
  • Tool-Calling AI Agents with Langchain Langgraph | Medium
    Two powerful tools revolutionizing this field are LangChain and LangGraph In this guide, we’ll explore how these technologies can be combined to build a sophisticated AI assistant capable of
  • Tool calling agent | ️ LangChain
    Tool calling allows a model to detect when one or more tools should be called and respond with the inputs that should be passed to those tools In an API call, you can describe tools and have the model intelligently choose to output a structured object like JSON containing arguments to call these tools





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