(100% Free, Private (No Internet), and Local PC Installation)
🔥 DeepSeek + NOMIC + FAISS + Neural Reranking + HyDE + GraphRAG + Chat Memory = The Ultimate RAG Stack!
This chatbot enables fast, accurate, and explainable retrieval of information from PDFs, DOCX, and TXT files using DeepSeek-7B, BM25, FAISS, Neural Reranking (Cross-Encoder), GraphRAG, and Chat History Integration.
✅ GraphRAG Integration: Enhances retrieval by constructing a Knowledge Graph from your documents, allowing for more contextual and relational understanding.
✅ Chat Memory History Awareness: Maintains context by utilizing chat history, enabling more coherent and contextually relevant responses.
✅ Improved Error Handling: Resolved issues related to chat history clearing and other minor bugs for a smoother user experience.
git clone https://github.com/SaiAkhil066/DeepSeek-RAG-Chatbot.git
cd DeepSeek-RAG-Chatbot
python -m venv venv
venv/Scripts/activate
pip install -r requirements.txtOllama is required to run DeepSeek-7B and Nomic Embeddings locally.
🔗 Download Ollama → https://ollama.com/
Then, pull the required models:
ollama pull deepseek-r1:7b
ollama pull nomic-embed-textstreamlit run app.py- Upload Documents: Add your PDFs, DOCX, or TXT files.
- Hybrid Retrieval: Combines BM25 and FAISS to fetch the most relevant text.
- GraphRAG Processing: Builds a Knowledge Graph from documents to understand relationships and context.
- Neural Reranking: Utilizes Cross-Encoder to refine search results for higher accuracy.
- Query Expansion (HyDE): Enhances recall by generating expanded queries.
- Chat Memory History Integration: Maintains context by referencing previous interactions.
- DeepSeek-7B Generation: Produces answers based on the best-matched document chunks.
| Feature | Previous Version | New Version |
|---|---|---|
| Retrieval Method | Hybrid (BM25 + FAISS) | Hybrid + GraphRAG |
| Contextual Understanding | Limited | Enhanced with Knowledge Graphs |
| User Interface | Standard | Dark Theme with Customizable Sidebar |
| Chat History | Not Utilized | Integrated for Contextual Responses |
| Error Handling | Basic | Improved with Bug Fixes |
💡 Issue: Error when clearing chat history.
✅ Fix: Ensure you're using the latest version of Streamlit, as st.experimental_rerun() has been updated.
pip install --upgrade streamlit🚀 Want to improve this chatbot? Feel free to fork this repo, submit pull requests, or report issues!
Got feedback or suggestions? Let’s discuss on Reddit! 🚀💡