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PDF RAG / Chat Tool

Get local retrieval-based Q&A from PDFs; speed up research and document review with source-aware answers, grounded citations, and privacy-first processing.

Tool Interface
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How It Works (Step by Step)

  • PDF text is extracted per page and split into small chunks.
  • A hybrid BM25 + embedding relevance score is computed for your question.
  • Extractive mode returns concise summaries from the most relevant sources.
  • In WebLLM mode (if enabled), answers are generated locally from sources.
  • Click a source to jump to the page and highlight question terms.

WebLLM is off by default. Manual confirmation is required for the initial model download.

Chat history is stored locally in your browser. WebLLM downloads the model on first run.

Chat

Answers will appear here after you ask a question.

What is this tool?

An academic helper that processes PDFs client-side and speeds up Q&A with RAG.

The tool is designed to simplify technical workflows for end users. It follows an offline, privacy-first, in-browser flow without server-side uploads.

How to use

  1. Upload your PDF and start text extraction.
  2. Ask questions about the document in the chat box.
  3. Verify answers by checking the cited source pages.

Privacy promise

Your PDF and questions are processed in-browser. No data is sent, stored, or shared.

This approach is especially useful for users who need low-latency processing and tighter data control.

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Related tools

Use these links to continue into tools that are commonly used in the same workflow. Each one points to a related step or a similar problem space.

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A strong complement when you work with academic PDFs and citation images together.

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Use cases and comparison

This section helps you quickly decide when to use this tool and how it differs from nearby alternatives.

Best-fit scenarios

  • Technical workflows that require rapid iteration
  • Cases where you need processing without sending data to external services
  • Repeatable operations that can be standardized across teams

How it differs

AI Prompt Optimizer: Useful for refining the questions you ask your PDFs so they are clearer and more targeted.

Visual BibTeX Parser: A strong complement when you work with academic PDFs and citation images together.

FAQ