Chat with PDF
Ask questions about any PDF document and get answers cited by page number. A complete MERN and Python RAG system ready for your final year project submission.
Screenshots
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Watch the demo
What it does
A retrieval-augmented chat system: upload a PDF, ask questions in plain English, and get answers grounded in the actual document, with every answer citing the exact page it came from. Built with hybrid retrieval (exact-match + semantic search) so it handles both specific lookups and broad summary questions correctly.
Features
- ✓Upload any PDF and start asking questions immediately
- ✓Answers cited by exact page number
- ✓Hybrid retrieval — correctly handles specific numeric/identifier questions, not just fuzzy topic matches
- ✓Handles both narrow lookups and whole-document summary questions
What's included
- ✓Full working Streamlit application
- ✓8-chapter Word report (architecture, requirements, testing, references)
- ✓13-14 slide presentation deck
- ✓Viva question bank with cheat sheet and pitch script
- ✓Architecture diagrams
Pricing
Same pricing tiers across every project kit.
A freelancer would charge ₹10,000–₹20,000 for the same project. Our kits start at ₹1,499 and are delivered in hours — not weeks.
Starter
The working application, ready to run and demonstrate.
- ✓Full source code
- ✓Setup & run instructions
- ✓requirements.txt / package.json
- ✓Runs on your machine in under 10 min
Standard
Submit-ready — full academic report and presentation included.
- ✓Everything in Starter
- ✓8-chapter Word report
- ✓14-slide presentation deck
- ✓Architecture & flow diagrams
Complete
Everything to submit AND confidently defend your project.
- ✓Everything in Standard
- ✓Viva Q&A bank + cheat sheet
- ✓Customized to your name & college
- ✓WhatsApp support until submission
Satisfaction guarantee
Not happy with what you receive? Message us within 24 hours and we'll either fix it or refund you — no questions asked.
Questions about this project
Does it work with scanned PDFs?+
It works best with text-based PDFs. Scanned/image-only PDFs need OCR, which isn't included by default but can be added.
How long does setup take?+
Under 10 minutes with the included instructions — it's a standard Python + pip install.
Guides for this kit
Viva prep and architecture notes that match this project.
- Viva Prep
Defending a Chat with PDF project in viva — questions and model answers
Panel-ready answers for PDF parsing, chunking, hybrid retrieval, page citations, hallucination control, and failure demos in document Q&A projects.
- Guides
Top 10 Streamlit AI demo projects students actually finish
Ten Streamlit AI project ideas for Indian final year students that are small enough to finish, with problem, stack, demo plan, and examiner questions.
- Architecture
How RAG (Retrieval-Augmented Generation) actually works
A plain-English breakdown of chunking, embeddings, and vector search — and exactly why it stops generative AI from making things up in your project.