Enterprise DNA
O Open Source Orchestration medium

ChatPDF

by Community

Chat and Ask on your own data. Accelerator to quickly upload your own enterprise data and use OpenAI services to chat to that uploaded data and ask questions

C

OSS

ChatPDF

Added 1 June 2026

#azure #azure-functions #azure-openai #azure-webapp #azureopenai #chatgpt #cognitive-search #gpt-3

Overview

ChatPDF is an open-source accelerator that lets you upload enterprise data and query it using OpenAI's chat services. Built in TypeScript, it provides a quick starting point for building a chat-over-documents application.

Best for

Best for
Developers who want a quick, open-source starting point to experiment with chat over their own documents using OpenAI.

Use cases

  • Upload PDFs and ask questions about their content
  • Prototype a document Q&A system for internal knowledge bases
  • Experiment with OpenAI chat on custom enterprise data

Notes

ChatPDF is an open-source accelerator that lets you upload enterprise data and query it using OpenAI’s chat services. Built in TypeScript, it provides a quick starting point for building a chat-over-documents application.

865 stars on GitHub. Last updated 2025-01-02. Licensed MIT.

Use cases

  • Upload PDFs and ask questions about their content
  • Prototype a document Q&A system for internal knowledge bases
  • Experiment with OpenAI chat on custom enterprise data

Pros

  • Simple setup for rapid prototyping with your own data
  • Open-source with 865 stars, indicating community interest
  • Written in TypeScript for type safety and maintainability

Cons

  • Requires an OpenAI API key, incurring usage costs
  • Community project with limited support and documentation
  • Not a production-ready solution; lacks advanced features like access control or scaling

Indexed from awesome-langchain and enriched against its public facts.

Pros

  • Simple setup for rapid prototyping with your own data
  • Open-source with 865 stars, indicating community interest
  • Written in TypeScript for type safety and maintainability

Cons

  • Requires an OpenAI API key, incurring usage costs
  • Community project with limited support and documentation
  • Not a production-ready solution; lacks advanced features like access control or scaling