✨ A curated collection of Retrieval-Augmented Generation (RAG) tutorials and examples using Qdrant vector database and modern AI models. ✨
Projects | Use Cases | Articles | Contributing | Contact
| Folder | Description | Technologies / Models / Frameworks |
|---|---|---|
| AINS_qdrant_talk | Qdrant tutorial and hands-on notebooks for beginners and workshops. | Qdrant, langChain |
| Ask-your-websites | RAG pipeline for Qdrant docs Q&A from web links, with Colab support. | Qdrant, LangChain, OpenAI |
| Docling-Qdrant-RAG (Beginner-friendly implementation for quick starts) | RAG chatbot for PDF Q&A using Docling and Gemini AI. | Qdrant, Docling, Gemini AI, BGE Embeddings |
| Agentic-Qdrant-RAG | Advanced agentic RAG system for intelligent PDF analysis and retrieval. | Qdrant, LangGraph, OpenAI GPT-4o Vision, pypdfium2 |
| Bolt-RAG-with-Qroq-Qdrant | Lightning-fast PDF chat with multi-session support and modern UI. | Qdrant, Groq, Cohere, LangChain, Streamlit |
Enterprise Applications:
- Legal document review and analysis
- Technical documentation Q&A
- Research paper analysis
- Customer support knowledge bases
Educational & Research:
- Academic paper analysis
- Interactive learning materials
- Literature review automation
- Cross-document research
Personal Productivity:
- Document assistant and note-taking
- Reading companion for books/articles
- Meeting notes summarization
Will soon expand these tutorials to cover more advanced techniques and integrations, including:
- Advanced RAG strategies (e.g., re-ranking, query expansion)
- Integration with other vector databases
- Deployment strategies for RAG systems
- More advanced Chunking Techniques and frameworks like Chonkie.
Stay tuned for updates!
Contributions are welcome! Please see CONTRIBUTING.md for guidelines on how to contribute to this project.
For questions or support, connect with Mohamed Arbi Nsibi on LinkedIn.
Special thanks to the wonderful open source community and Qdrant for making these tutorials possible.