This repository provides a curated collection of tutorials and examples for learning the LangChain library, targeting developers and researchers interested in building LLM-powered applications. It offers a structured learning path from core concepts to advanced use cases, with accompanying code and video resources to facilitate understanding and practical application.

How It Works

The project organizes LangChain learning into distinct categories: Beginner, Intermediate, and Advanced, with specific projects like "SummarizePaper.com" and "ChatPDF" demonstrating practical applications. Each project includes links to code repositories and video explanations, allowing users to follow along and replicate the implementations. The tutorials cover key LangChain functionalities such as summarization, question answering over documents, data extraction, evaluation, and agent development.

Quick Start & Requirements

• Install: Follow individual project instructions; typically involves pip install langchain and other specific dependencies.
• Prerequisites: Python, Jupyter Notebooks/Colab, and potentially API keys for LLM providers (e.g., OpenAI).
• Resources: Links to YouTube tutorials and code repositories are provided for each project.

Highlighted Details

• Structured learning path from core concepts to advanced use cases.
• Projects categorized by difficulty: Beginner, Intermediate, Advanced.
• Code and video resources available for each tutorial.
• Covers diverse LangChain applications: summarization, Q&A, extraction, agents.

Maintenance & Community

This repository is provided by DataIndependent and managed by Greg Kamradt. Contributions are welcomed via pull requests.

Licensing & Compatibility

The repository itself appears to be open-source, with individual project code likely governed by the licenses of their respective repositories. Compatibility for commercial use depends on the licenses of the underlying LangChain library and any third-party APIs or datasets used.

Limitations & Caveats

The project is a collection of tutorials and examples, not a standalone library. Some projects are marked as "half-baked prototypes" or have "TBD" status, indicating ongoing development or incomplete implementations. Users need to manage dependencies and API keys for each specific example.