LLama3.3-RAG application

This project leverages a locally Llama 3.3 to build a RAG application to chat with your docs and Streamlit to build the UI.

Demo

Watch the demo video:

Installation and setup

Setup Ollama:

# setup ollama on linux 
curl -fsSL https://ollama.com/install.sh | sh
# pull llama 3.3:70B
ollama pull llama3.3 

Setup Qdrant VectorDB

docker run -p 6333:6333 -p 6334:6334 \
-v $(pwd)/qdrant_storage:/qdrant/storage:z \
qdrant/qdrant

Install Dependencies: Ensure you have Python 3.11 or later installed.

pip install streamlit ollama llama-index-vector-stores-qdrant

---

📬 Stay Updated with Our Newsletter!

Get a FREE Data Science eBook 📖 with 150+ essential lessons in Data Science when you subscribe to our newsletter! Stay in the loop with the latest tutorials, insights, and exclusive resources. Subscribe now!

---

Contribution

Contributions are welcome! Please fork the repository and submit a pull request with your improvements.