Live App: https://pdfanalyser-ai.streamlit.app/
In today's information-rich world, extracting meaningful insights from documents is more important than ever. This intelligent PDF Q&A chatbot leverages cutting-edge Retrieval-Augmented Generation (RAG) and Generative AI to transform how users interact with PDFs.
Combines intelligent retrieval with generative response:
- Semantic-based document chunk retrieval
- Context-grounded answer generation
- Maintains relevance and accuracy using actual document content
- Text chunks are transformed into high-dimensional vector representations
- Uses cosine similarity to find the most relevant sections
- Enables semantic understanding beyond keyword matching
- Synthesizes information from top-matching document chunks
- Generates coherent and context-aware responses
- Supports configurable parameters for response style and length
- PDF Processing & Chunking – Handled via
LangChain - Embedding Generation – Using
Google Generative AI Embedding API - Similarity Matching – Semantic search using cosine similarity
- Response Generation – Gemini 1.5 Pro model responds using RAG
Streamlit– Fast, interactive UILangChain– Document parsing & chunkingGoogle Generative AI SDK– Embedding & text generationNumPy,Pandas– Vector math and data handling
- 📄 One-click PDF upload & processing
- 💬 Clean, intuitive chat interface
- 🔎 Transparent sourcing via expandable reference passages
- 🔐 Secure API key management via Streamlit sidebar
This solution showcases how RAG architecture and embeddings elevate document intelligence workflows:
- ⏱️ Save time searching large documents
- ✅ Deliver accurate, context-aware answers
- 📚 Maintain source traceability for auditing or compliance
- 🏥📊 Scalable across industries like legal, healthcare, and enterprise knowledge management
The PDF Q&A Chatbot represents a new era of document engagement—where AI becomes an intelligent assistant to help you extract insights from your most valuable information assets.
#AI #GenerativeAI #RAG #DocumentIntelligence #EmbeddingModels #Streamlit