# bhaskatripathi/pdfGPT

PDF GPT allows you to chat with the contents of your PDF file by using GPT capabilities. The most effective open source solution to turn your pdf files in a chatbot!

Repository: https://github.com/bhaskatripathi/pdfGPT
Canonical: https://ross.abutalabs.com/products/pdfgpt
Homepage: https://huggingface.co/spaces/bhaskartripathi/pdfChatter
Language: Python
License: MIT
License Family: permissive
Topics: pdfgpt, chatpdf, chatwithpdf
Last push: 2026-03-06T20:50:46+00:00

## Health v2 (maintenance only)
Score: 62/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 70, release rhythm 35, longevity 91
- inputs: {"age_days": 1275, "days_push": 180, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 7167, forks 833 (observed 2026-08-28T04:09:56.356416+00:00)

## What it is
pdfGPT is an open-source Python application that lets users chat with the contents of PDF files using GPT capabilities. It implements a simple RAG-style architecture using Universal Sentence Encoder embeddings without a vector database or third-party frameworks like LangChain, and is deployed as a web app (e.g., on Hugging Face Spaces).

## Use cases
- chat with a pdf document
- ask questions about a pdf file
- turn a pdf into a chatbot
- summarize and query long pdf documents
- avoid token limit issues when feeding pdfs to GPT
- get accurate answers from pdf content without hallucinations

## When to choose
- you want a simple, dependency-light chat-with-PDF tool without LangChain or a vector DB
- you need accurate, precise answers from a single PDF
- you want a self-hostable open-source alternative to chatpdf.com
- you want a quick Hugging Face Spaces demo of PDF Q&A

## When to avoid
- you need multi-PDF or OCR support (still on the roadmap)
- you need a production-grade RAG pipeline with modern vector stores and indexing
- you want a polished UI or actively updated documentation
- you need fully local/offline models without OpenAI API keys

## Facets
- artifact type: application
- maturity: maintenance
- function: rag, nlp, llm-inference, pdf, chatbot, search-engine
- domain: pdf, large-language-models, artificial-intelligence, developer-tools
- platform: python, self-hosted, cross-platform
- tags: chat-with-pdf, openai, embeddings, universal-sentence-encoder, gradio, question-answering, document-chat, natural-language-processing, retrieval-augmented-generation, web-server

## Member repositories
- bhaskatripathi/pdfGPT (main) score 62

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:56.356416+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:39:57.737332+00:00, confidence not recorded.
  - readme: https://github.com/bhaskatripathi/pdfGPT (fetched 2026-08-28T04:09:56.356416+00:00, sha b0f26d8c4ae3)
  - homepage: https://huggingface.co/spaces/bhaskartripathi/pdfChatter (fetched 2026-08-29T08:35:12.754122+00:00, sha ba985b68d9c6)
- Data as of 2026-08-30T08:39:29.467469+00:00.