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Intelligent PDF Q&A Chatbot using RAG, embeddings, and Gemini AI to extract precise answers from documents. Upload any PDF and ask questions to get context-aware responses with source references.

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🤖 PDF Q&A Chatbot with RAG & Generative AI

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.


🚀 Core Technologies

🔍 Retrieval-Augmented Generation (RAG)

Combines intelligent retrieval with generative response:

  • Semantic-based document chunk retrieval
  • Context-grounded answer generation
  • Maintains relevance and accuracy using actual document content

📐 Vector Embeddings (Google Embedding)

  • Text chunks are transformed into high-dimensional vector representations
  • Uses cosine similarity to find the most relevant sections
  • Enables semantic understanding beyond keyword matching

✨ Generative AI with Gemini 1.5 Pro

  • Synthesizes information from top-matching document chunks
  • Generates coherent and context-aware responses
  • Supports configurable parameters for response style and length

⚙️ Technical Workflow

  1. PDF Processing & Chunking – Handled via LangChain
  2. Embedding Generation – Using Google Generative AI Embedding API
  3. Similarity Matching – Semantic search using cosine similarity
  4. Response Generation – Gemini 1.5 Pro model responds using RAG

🖥️ Built With

  • Streamlit – Fast, interactive UI
  • LangChain – Document parsing & chunking
  • Google Generative AI SDK – Embedding & text generation
  • NumPy, Pandas – Vector math and data handling

🧠 Key Features

  • 📄 One-click PDF upload & processing
  • 💬 Clean, intuitive chat interface
  • 🔎 Transparent sourcing via expandable reference passages
  • 🔐 Secure API key management via Streamlit sidebar

💼 Business Value

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 Future of Document Interaction

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.


📌 Tags

#AI #GenerativeAI #RAG #DocumentIntelligence #EmbeddingModels #Streamlit


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Intelligent PDF Q&A Chatbot using RAG, embeddings, and Gemini AI to extract precise answers from documents. Upload any PDF and ask questions to get context-aware responses with source references.

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