LangChain Fundamentals

What problem does it solve?

This Skill provides the foundational knowledge and tools to build robust, production-ready AI agents using LangChain's create_agent function, enabling custom workflows and reliable operation.

Core Features & Use Cases

• Agent Creation: Learn to use create_agent() for building agents with LLMs, tools, and system prompts.
• Tool Definition: Define custom functions as tools for agents using @tool (Python) or tool() (TypeScript).
• Middleware Integration: Implement middleware for human-in-the-loop approvals, error handling, and custom logic.
• Persistence: Configure checkpointers for maintaining conversation state and memory.
• Structured Output: Ensure agents return data in a predictable, typed format.
• Use Case: Develop an agent that can search the web, perform calculations, and ask for user confirmation before executing a critical action, ensuring both efficiency and safety.

Quick Start

Create a basic agent that can get the weather for a given location using the create_agent function and the @tool decorator.