This project is a secure, agentic LLM-based assistant that helps insurance analysts extract clauses, assess policy compliance, and summarize documents using local LLMs. Built for privacy-conscious enterprises like USAA.
- Local LLM support (Mistral 7B, LLaMA3 via Ollama or LM Studio)
- Fine-tuning on insurance-specific clause and QA datasets (with QLoRA)
- Agentic document workflow with LangGraph
- Clause retrieval with Chroma vector DB
- Streamlit front-end for simple document upload and review
backend/
– Core logic (parsing, LLM inference, retrieval, agent orchestration)fine_tuning/
– Dataset prep and fine-tuning scriptsfrontend/
– Streamlit app UImodels/
– (Optional) local fine-tuned model foldersdata/
– PDFs and generated Chroma index
# Create environment
python -m venv venv
source venv/bin/activate
# Install dependencies
pip install -r requirements.txt
# Run Streamlit frontend
streamlit run frontend/app.py