Insurance Policy Analysis Application

Analyzing Insurance Policies, Emails, etc. using Large Language Models and creating a Query-Answer Interface

Github

Demo

A powerful document analysis application that leverages Large Language Models (LLMs) to provide intelligent question-answering capabilities for insurance policies and other documents. The application uses RAG (Retrieval-Augmented Generation) to provide accurate, context-aware responses based on uploaded documents.

Features

  • Multi-LLM Support: Choose between OpenAI, Azure OpenAI, and Google Gemini models
  • Document Upload: Support for PDF and DOCX files
  • Vector Search: FAISS-based vector database for efficient document retrieval
  • Interactive Chat: Streamlit-powered web interface with chat history
  • RAG Implementation: Combines document retrieval with LLM generation for accurate responses
  • Persistent Storage: Embeddings are stored and can be reused across sessions

Technology Stack

  • Frontend: Streamlit
  • LLMs: OpenAI GPT-4o, Azure OpenAI, Google Gemini
  • Vector Database: FAISS
  • Document Processing: LangChain, PyPDF, Unstructured
  • Embeddings: OpenAI text-embedding-3-large, Azure OpenAI, Google Generative AI

How It Works

  1. Document Processing: Uploaded documents are processed using LangChain loaders (PyPDF for PDFs, Unstructured for DOCX)
  2. Embedding Generation: Text chunks are converted to vector embeddings using the selected embedding model
  3. Vector Storage: Embeddings are stored in a FAISS vector database for efficient similarity search
  4. Query Processing: User questions are embedded and used to retrieve relevant document chunks
  5. Response Generation: Retrieved context is combined with the user question and sent to the LLM for answer generation

Use Cases

  • Insurance Policy Analysis: Analyze complex insurance documents and get quick answers
  • Contract Review: Upload contracts and ask specific questions about terms and conditions
  • Document Q&A: General purpose document question-answering for various file types
  • Research Assistant: Extract specific information from large documents efficiently