Show HN: PDF Knowledge Base Search:Quick search for your personal PDF library | Hacker News Reader

Show HN: PDF Knowledge Base Search:Quick search for your personal PDF library

github.com

2 pointsmixtape2025-12 comments

First, apologies because I used ChatGPT to draft this text. First time poster here.

I’ve developed a lightweight Python-based solution that lets you turn your personal PDF library into a searchable knowledge base—no complex setup, no bloated dependencies.

What It Does: 1. Extracts text from PDFs and saves it as JSON files, chunked by pages. 2. Optionally generates text embeddings (using `fastembed`) for semantic search. 3. Provides a user-friendly GUI for searching, navigating results, and previewing matching content.

The search interface supports: - BM25 Algorithm: Great for keyword-based search. - Simple Text Search: For exact phrase matching. - Embedding-Based Search (optional): If you want semantic search capabilities, embeddings are supported but not required.

Why This Project? I wanted something simple, portable, and fast for managing my own PDF archives—something that doesn’t require setting up a database or maintaining a server. The focus is on the search interface simplicity and usefulness.

With this tool: - Your knowledge base is stored as portable JSON and EMB files. You can easily move it across devices. - The GUI allows for intuitive searches and even opens matching pages in your default PDF viewer (Okular by default, but configurable).

Key Features: - Minimal Dependencies: Works out of the box with BM25 and a small set of Python libraries. - Optional Semantic Search: Add `fastembed` for enhanced search capabilities. - Customizable Workflow: JSON-only mode for simplicity or JSON+EMB for full functionality. - Cross-Platform Support: As long as Python and your chosen PDF viewer are installed.

Use Cases: - Researchers managing collections of academic papers. - Anyone needing quick access to information buried in PDFs.

How to Get Started: 1. Install Python and the required libraries. 2. Process your PDFs into JSON files with a single script. 3. (Optional) Generate embeddings for richer search results. 4. Use the search interface to start finding what you need!

Check out the code and detailed instructions here: https://github.com/Topping1/BM25-PDF-Search

I hope this is useful for the community.

This sounds like an interesting project. Can it extract text from scanned books? In those types of pdfs, each page is stored as an image file. If you could pair this project with that capability, I could see this being insanely useful to many organizations.

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