RAG-chat-with-documents

Chainlit app for advanced RAG. Uses llamaparse, langchain, qdrant and models from groq.

Videos covering these topics

Llamaparse LlamaIndex

Llamaparse Qdrant Gorq

RAG With LlamaParse from LlamaIndex & LangChain 🚀

Links shown in video

• LlamaCloud
• Qdrant Cloud
• Groq Cloud

create virtualenv

python3 -m venv .venv && source .venv/bin/activate

Install packages

pip install -r requirements.txt

Environment variables

All env variables goes to .env ( cp example.env to .env and paste required env variables)

Run the python files (following the video to run step by step is recommended)

python3 ingest.py
chainlit run app.py

Additional helper documents

• LlamaIndex blogpost about Llamaparse
• Advanced demo with Reranker
• Parsing instructions Llamaparse