This repository provides a curated collection of example applications built with the LangChain LLM framework. It targets developers looking to quickly prototype and deploy various generative AI use cases, such as chatbots, summarization, and question-answering, by leveraging pre-built integrations and patterns.

How It Works

The project showcases diverse applications, each demonstrating specific LangChain capabilities and integrations with external tools and databases. Examples include document summarization with Chroma or Pinecone, question-answering with Gemini, and news summarization using Serper API, all typically wrapped in user-friendly Streamlit interfaces.

Quick Start & Requirements

• Install dependencies via pip install -r requirements.txt.
• Requires Python 3.7+.
• Many examples require API keys for services like OpenAI, Gemini, Serper, Tavily, or Pinecone.
• Official documentation and demos are not explicitly linked in the README.

Highlighted Details

• Demonstrates LangChain integration with multiple vector stores (Chroma, Pinecone).
• Showcases LLM observability with Helicone.
• Features examples for news search and general web search APIs (Serper, Tavily, SerpApi).
• Utilizes Streamlit for creating interactive web UIs for each application.

Maintenance & Community

The repository is maintained by alphasecio. No specific community channels or roadmap details are provided in the README.

Licensing & Compatibility

The repository's license is not specified in the provided README.

Limitations & Caveats

The README does not specify a license, which may impact commercial use or integration into closed-source projects. Some examples require specific, potentially costly, API keys to function.