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https://github.com/alexisbalayre/ragdocs
An AI-powered search engine to interact with documentation using RAG and local LLMs. Privately deployable with vector search and a modern frontend.
https://github.com/alexisbalayre/ragdocs
chatbots documentation fastapi information-retrieval knowledge-base llm local-llm machine-learning milvus natural-language-processing nextjs ollama private-gpt python rag retrieval-augmented-generation self-hosted technical-documentation vector-database vector-search
Last synced: 18 days ago
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An AI-powered search engine to interact with documentation using RAG and local LLMs. Privately deployable with vector search and a modern frontend.
- Host: GitHub
- URL: https://github.com/alexisbalayre/ragdocs
- Owner: AlexisBalayre
- License: apache-2.0
- Created: 2024-11-14T15:24:31.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-11-14T18:43:47.000Z (3 months ago)
- Last Synced: 2024-12-03T17:16:11.354Z (2 months ago)
- Topics: chatbots, documentation, fastapi, information-retrieval, knowledge-base, llm, local-llm, machine-learning, milvus, natural-language-processing, nextjs, ollama, private-gpt, python, rag, retrieval-augmented-generation, self-hosted, technical-documentation, vector-database, vector-search
- Language: MDX
- Homepage:
- Size: 10.8 MB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# RagDocs
**RagDocs** is a cutting-edge open-source solution that revolutionizes how you interact with documentation. By combining the power of **local LLMs** with state-of-the-art **Retrieval-Augmented Generation (RAG)**, developers can instantly get accurate answers from their documentation without any API costs.
Say goodbye to expensive API calls and privacy concerns. With **RagDocs**, all your documentation stays private while providing ChatGPT-like interactions. Built with Milvus vector search and Next.js, it's production-ready and easy to deploy. Experience the future of documentation search with complete data privacy and no usage fees.
https://github.com/user-attachments/assets/24c25726-6599-4be5-9fa5-c7b8af6a4c55
## 🌟 Features
- **🤖 Intelligent Chat Interface**: Conversational interface tailored for technical documentation.
- **🔍 Cutting-Edge Retrieval Augmented Generation**: Accurate and context-aware responses.
- **💾 Local LLM Support**: Integrated with Ollama for privacy and efficiency.
- **🎯 Vector Search Powered by Milvus**: Rapid and scalable document querying.
- **🚀 Modern Next.js Frontend**: Sleek, real-time user experience.
- **📚 Multi-Document Support**: Seamless handling of diverse tech stacks.
- **⚡ Fast Document Processing**: Efficient ingestion and analysis of updates.
- **🔄 Incremental Updates**: Keep your documentation in sync effortlessly.
---
## 🏗️ Architecture
```
ragdocs/
├── data/ # Documentation storage
│ ├── milvus_docs/ # Milvus documentation
│ ├── qdrant_docs/ # Qdrant documentation
│ └── weaviate_docs/ # Weaviate documentation
├── milvus/ # Milvus standalone setup
│ └── standalone_embed.sh # Milvus standalone script
├── ragdocs_api/ # FastAPI backend
│ ├── conversation_api.py # Chat API endpoints
│ ├── file_tracker.py # Document change tracking
│ ├── llm_provider.py # LLM integration (Ollama)
│ ├── markdown_processor.py # Markdown processing
│ └── rag_system.py # Core RAG implementation
└── ragdocs_frontend/ # Next.js frontend
└── src/ # Frontend source code
```
---
## 🚀 Getting Started
### Prerequisites
- Python 3.12+
- Node.js 20.17.0
- Milvus 2.0+
- Ollama (for local LLM support)
Install Node.js with **nvm**:
```bash
nvm install 20.17.0
nvm use 20.17.0
```
---
### Installation
1. **Clone the Repository**:
```bash
git clone https://github.com/AlexisBalayre/RagDocs.git
cd RagDocs
```
2. **Install Python Dependencies**:
```bash
# Install poetry if not already installed
curl -sSL https://install.python-poetry.org | python3 -
# Install project dependencies
poetry install
poetry shell
```
> **Key Dependencies:**
> - llama-index: 0.11.22
> - fastapi: 0.115.4
> - milvus-lite: 2.4.10
> - sentence-transformers: 2.7.0
> - torch: 2.5.1
3. **Install Frontend Dependencies**:
```bash
cd ragdocs_frontend
yarn
```
4. **Set Up Environment Variables**:
```bash
cp example.env.local .env.local
# Edit .env.local with your configuration
```
5. **Start Milvus**:
```bash
cd milvus
bash standalone_embed.sh start
```
6. **Run the Backend**:
```bash
poetry run uvicorn ragdocs_api.conversation_api:app --reload
```
7. **Run the Frontend**:
```bash
cd ragdocs_frontend
yarn dev
```
---
## 💡 Usage
1. **Add Documentation**: Place files in the respective folders under `data/`.
2. **Start Chatting**: Use the frontend to chat with and explore your documentation.
3. **Compare Tech Stacks**: Leverage built-in comparison features for analysis.
---
## 🔧 Configuration
Edit the `.env.local` file for key settings:
```env
MILVUS_HOST=localhost
MILVUS_PORT=19530
OLLAMA_MODEL=llama3.2
```
---
## 🤝 Contributing
Contributions are encouraged! Follow these steps:
1. Fork the repository.
2. Create a feature branch:
```bash
git checkout -b feature/AmazingFeature
```
3. Commit your changes:
```bash
git commit -m 'Add some AmazingFeature'
```
4. Push your branch:
```bash
git push origin feature/AmazingFeature
```
5. Open a Pull Request.
---
## 📝 License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
---
## 🙏 Acknowledgments
- [Vercel AI Chatbot](https://github.com/vercel/ai-chatbot) - Template inspiration for the frontend.
- [LlamaIndex](https://github.com/jerryjliu/llama_index) - Powering RAG capabilities.
- [Milvus](https://github.com/milvus-io/milvus) - Efficient vector search backend.
- [Ollama](https://github.com/jmorganca/ollama) - Local LLM support.
---
## ⭐ Support
If this project adds value to your work, **please give it a star!**
Your support makes a difference and encourages further development. Feedback and feature suggestions are always welcome!