This repository offers a comprehensive course, "LangChain for Beginners," designed to teach users how to build AI agents using LangChain and Python. It targets developers and researchers aiming to create advanced AI applications, including context-aware chatbots, semantic search systems, and autonomous agents, providing a practical pathway to deploying real-world AI solutions.

How It Works

The course employs an "agent-first progression," starting with foundational concepts like tools and agents before integrating them with document retrieval for Agentic RAG systems. This pedagogical approach mirrors the architecture of modern production AI systems, emphasizing practical application and understanding of core components.

Quick Start & Requirements

• Prerequisites: Python 3.10+, GitHub account, and a code editor (VS Code recommended). Familiarity with basic Generative AI concepts is beneficial.
• Setup: Chapter 0, "Course Setup," guides users through environment configuration, supporting local setups and cloud-based options like Azure AI Foundry and Codespaces.
• Resources: Official LangChain Documentation is available for deeper dives.

Highlighted Details

• Develops context-aware chatbots with streaming responses and customizable behavior.
• Implements semantic search systems that understand meaning beyond keywords.
• Enables AI to leverage external tools and extract structured data via Function Calling.
• Builds autonomous agents capable of reasoning, decision-making, and tool selection.
• Integrates AI with external services using the Model Context Protocol (MCP).
• Constructs Agentic RAG systems where agents intelligently decide when to access knowledge bases.

Maintenance & Community

• Community support and Q&A are available via the Microsoft Foundry Community Discord channel.
• Contributions are welcomed through issues and pull requests, subject to a Contributor License Agreement (CLA) [https://cla.opensource.microsoft.com/].
• The project adheres to the Microsoft Open Source Code of Conduct.

Licensing & Compatibility

• The README does not specify a particular open-source license (e.g., MIT, Apache). A Contributor License Agreement (CLA) is required for contributions.
• Information regarding compatibility for commercial use or linking with closed-source projects is not provided.

Limitations & Caveats

• This repository serves as an educational resource with plans for future expansion. Specific technical limitations or known bugs are not detailed within the README.