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Release Notes - v0.1.0

🎉 Initial Public Release

This is the first official release of RAG_Ollama_Mac - a lightweight, private, and customizable retrieval-augmented chatbot running entirely on your Mac.

✨ Features

Core Functionality

  • 🤖 Local RAG Implementation: Complete retrieval-augmented generation system using Ollama
  • 📄 PDF Processing: Load and process multiple PDF documents from the data directory
  • 💬 Interactive Chat: Clean and intuitive Streamlit-based chat interface
  • 🔍 Smart Retrieval: ChromaDB-powered vector storage for efficient document retrieval
  • 🔒 Privacy First: All processing happens locally - no cloud API calls

Technical Details

  • Embedding Model: nomic-embed-text-v2-moe for high-quality document embeddings
  • LLM: gemma3n for intelligent, context-aware responses
  • Vector Database: ChromaDB for persistent vector storage
  • UI Framework: Streamlit for interactive web interface

📋 What's Included

  • ✅ Complete source code for RAG chatbot
  • ✅ Document loading and processing utilities
  • ✅ Configurable text chunking (800 chars with 80 char overlap)
  • ✅ Vector database management with reset functionality
  • ✅ Interactive chat interface with message history
  • ✅ Comprehensive documentation and setup guide
  • ✅ MIT License

🛠️ Installation

# Clone the repository
git clone https://github.com/eplt/RAG_Ollama_Mac.git
cd RAG_Ollama_Mac

# Create virtual environment
python3 -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r ./src/requirements.txt

🚀 Quick Start

  1. Start Ollama and pull required models:

    ollama serve
ollama pull gemma3n
ollama pull toshk0/nomic-embed-text-v2-moe:Q6_K

  2. Load your documents:

    python ./src/load_docs.py

  3. Launch the chatbot:

    streamlit run ./src/UI.py

💻 System Requirements

  • Operating System: macOS (optimized for Mac, but works on other platforms)
  • Python: 3.7 or higher
  • RAM: At least 16GB recommended (24GB+ for optimal performance)
  • Ollama: Latest version with required models installed

📦 Dependencies

Key dependencies included in this release:

  • langchain (0.3.26)
  • langchain-ollama (0.3.5)
  • langchain-chroma (0.2.4)
  • chromadb (1.0.15)
  • streamlit (1.41.1)
  • ollama (0.5.1)

See src/requirements.txt for complete list.

🎯 Use Cases

  • Research: Query academic papers and research documents
  • Documentation: Get instant answers from technical documentation
  • Books: Ask questions about long-form content
  • Privacy-Sensitive Work: Process confidential documents locally

🔮 Future Plans

  • Support for additional file formats (Markdown, .txt, HTML)
  • Multiple LLM model support (phi-3, mistral, llama3)
  • Chat history persistence
  • Enhanced document management
  • User authentication options

🙏 Acknowledgments

This project is based on the excellent work by pruthvirajcyn.

📄 License

Released under the MIT License. See LICENSE for details.

🐛 Known Issues

None reported for this initial release.

📝 Changelog

For detailed changes, see CHANGELOG.md.

Full Changelog: https://github.com/eplt/RAG_Ollama_Mac/commits/v0.1.0