DEDUPED Hot AI repos, turned into use cases Get the Monday 5

PageIndex tutorial: RAG over a long PDF without a vector database

Submit a document, build a tree index, and chat with it using reasoning-based retrieval.

  • Top pick
  • Research
  • Intermediate
  • 30 minutes
  • From the README
  • Any agent

Credentials. Local mode sends document content to your LLM provider using your key.

Who it is forA financial analyst querying a 200-page annual report.

The problemChunked vector search breaks context in long documents.

The outcomeAnswers retrieved by navigating the document's structure.

What you need first

  • Python
  • An OpenAI API key (local mode) or a PageIndex API key (cloud mode)

Steps

  1. Install with pip install -U pageindex
  2. Set OPENAI_API_KEY
  3. Create a PageIndexClient and submit_document("report.pdf")
  4. Call client.chat with your question and the doc_id

Prompt for your agent

Using VectifyAI/PageIndex in local mode, submit <report.pdf> and ask <question>. Return the answer with the page or section it came from and verify it in the PDF.

Caveat. Index building runs an LLM over the document, so long files cost more to index.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for VectifyAI/PageIndex and "Ask questions of a long PDF without a vector database"

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

Cursor, ChatGPT, others

Share: X LinkedIn Hacker News Email Copy link

Third-party repos we don't own. AI-written use cases can be wrong. Disclaimer