lightrag-exploration 0.1.0

A lightweight RAG exploration tool.

LightRAG Exploration

LightRAG Exploration is a Python FastAPI application for exploring Retrieval-Augmented Generation (RAG) workflows. It provides a modern web interface for chat, graph visualization, and RAG experimentation using local LLMs via Ollama. The app is designed for easy local use and sharing as a pipx CLI tool.

Features

• RAG Chat: Interact with a RAG pipeline using your own documents and local LLMs.
• Classic Chat: Simple chat interface with model selection and context summarization.
• Graph Viewer: Visualize the entity/relation graph extracted from your research data.
• Modern Web UI: Clean, responsive interface built with Tailwind CSS.
• Easy Setup: Installable as a pipx CLI for global use.
• Ollama Integration: Uses Ollama for local LLM inference and embeddings.
• Configurable: Uses .env for research output directory and Ollama host.

Prerequisites

• Python 3.9+
• pipx
• Ollama installed and running with required models (e.g. gemma3:1b, nomic-embed-text:latest)

Install system dependencies (macOS example)

brew install pipx
pipx ensurepath
source ~/.zshrc  # or restart your terminal

Install with pipx

pipx install lightrag-exploration

Usage

• The API will run on http://localhost:8080 by default.
• Open your browser and navigate to:
  • /frontend — Home page
  • /frontend/chat — Classic chat interface
  • /frontend/rag-chat — RAG chat interface
  • /frontend/graph-viewer — Graph visualization
  • /docs — FastAPI API docs

How It Works

• RAG Pipeline: Uses LightRAG and Ollama for retrieval, embedding, and LLM completion.
• Templates: Web UI is served from the templates/ directory.
• Config: Set research_output_dir and ollama_host in .env or .env.example.

Development

• All source code is in the root and routers/ directory.
• The entrypoint is main.py, which runs the FastAPI app.
• You can run locally with:

  python main.py
  

• Or install and run globally with pipx as above.

Packaging & Distribution

To build and publish to PyPI:

1. Upgrade build and twine:

   python -m pip install --upgrade build twine
   

2. Build your package:

   python -m build
   

3. (Optional) Check your package:

   python -m twine check dist/*
   

4. Upload to PyPI:

   python -m twine upload dist/*
   

Troubleshooting

• If you see errors about missing templates, ensure you installed with pipx after running pipx ensurepath and that your terminal session is up to date.
• Make sure Ollama is running and the required models are pulled.
• If you see errors about missing research output, check your .env and that the directory exists.

License

MIT