This repository provides comprehensive course materials for learning LangChain, developed by Aurelio AI. It targets developers and researchers seeking to master LangChain applications, offering a reproducible environment and structured lessons to accelerate learning and development.

How It Works

The course material is designed for precise environment replication using the uv package manager and a specific Python version (3.12.7). It supports integration with both OpenAI and Ollama for Large Language Model (LLM) backends, allowing users flexibility in their development setup. This approach ensures consistency and minimizes dependency conflicts during the learning process.

Quick Start & Requirements

• Primary Install: Requires installing the uv package manager first, following instructions at https://astral.sh/uv/install.sh. Then, navigate to the course root and execute:

  uv python install 3.12.7
  uv venv --python 3.12.7
  uv sync
  

  A terminal restart may be necessary for uv commands to be recognized. It's recommended to create a new virtual environment for each chapter.
• IDE Integration: For VS Code/Cursor, open the chapter directory (cd example-chapter) and run cursor . or code .. Select the .venv environment within the IDE.
• LLM Backend: Supports OpenAI or Ollama. For Ollama:
  • Install Ollama from ollama.com.
  • Ensure Ollama is running (ollama serve or via the application).
  • Note the server port (default http://localhost:11434).
  • Download required LLMs using ollama pull <model_name> (e.g., ollama pull llama 3.2:3b).
• Prerequisites: Python 3.12.7, uv package manager.

Highlighted Details

• Emphasis on exact environment duplication using uv to prevent "dependency hell."
• Dual LLM backend support (OpenAI and Ollama) for flexibility.
• Clear instructions for VS Code/Cursor integration with the managed virtual environments.

Maintenance & Community

No specific details regarding maintainers, community channels (like Discord/Slack), roadmap, or sponsorships are provided in the README.

Licensing & Compatibility

The README does not specify a software license or any compatibility notes for commercial use or integration with closed-source projects.

Limitations & Caveats

The setup strictly requires Python 3.12.7 and the uv package manager, which might be an adoption barrier for users not using these specific tools. Users must manage LLM downloads separately if using Ollama. The course material is presented as a direct duplicate of the creation environment, implying potential for rapid changes or updates tied to the course's lifecycle.