This repository provides comprehensive Jupyter notebooks for learning Langchain, a framework for developing applications powered by language models. It targets developers and researchers seeking to understand and implement core Langchain concepts, offering practical examples for building sophisticated LLM applications.

How It Works

The course material is structured around a series of Jupyter notebooks, each dedicated to a specific Langchain module. This modular approach allows users to progressively learn about fundamental components like models, prompts, chains, memory, indexes, and agents, culminating in advanced topics such as ChatGPT plugins, function calling, and open-source model integration.

Quick Start & Requirements

• Install: pip install langchain (and other dependencies as per individual notebooks).
• Prerequisites: Python 3.x, Jupyter Notebook/Lab. Specific notebooks may require API keys (e.g., OpenAI) or specific models (e.g., Falcon 7B).
• Resources: Requires standard Python development environment.

Highlighted Details

• Covers foundational Langchain concepts: models, prompts, chains, memory, indexes, agents.
• Includes advanced topics: ChatGPT plugins, OpenAI function calling, and integration with open-source models like Falcon 7B.
• Features a notebook on data preprocessing with DocTran.
• Provides a notebook dedicated to performance evaluation methods.

Maintenance & Community

No information on maintainers, community channels, or roadmap is available in the provided README.

Licensing & Compatibility

The repository's license is not specified in the README. Compatibility for commercial use or closed-source linking is undetermined.

Limitations & Caveats

The README notes that notebook descriptions are general and may not fully capture content. Specific setup instructions and dependency management for each notebook are not detailed.