/_DocsGPT

GPT-powered chat for documentation, chat with your documents

Primary LanguagePythonMIT LicenseMIT

DocsGPT 🦖

Open-Source Documentation Assistant

DocsGPT is a cutting-edge open-source solution that streamlines the process of finding information in project documentation. With its integration of the powerful GPT models, developers can easily ask questions about a project and receive accurate answers.

Say goodbye to time-consuming manual searches, and let DocsGPT help you quickly find the information you need. Try it out and see how it revolutionizes your project documentation experience. Contribute to its development and be a part of the future of AI-powered assistance.

example1 example2 example3 example3

video-example-of-docs-gpt

Features

Group 9

Roadmap

You can find our Roadmap here, please don't hesitate contributing or creating issues, it helps us make DocsGPT better!

Live preview

Join Our Discord

Project structure

  • Application - flask app (main application)

  • Extensions - chrome extension

  • Scripts - script that creates similarity search index and store for other libraries.

  • frontend - frontend in vite and

QuickStart

Note: Make sure you have docker installed

  1. Open dowload this repository with git clone https://github.com/arc53/DocsGPT.git
  2. Create .env file in your root directory and set your OPENAI_API_KEY with your openai api key
  3. Run docker-compose build && docker-compose up
  4. Navigate to http://localhost:5173/

To stop just run Ctrl + C

Development environments

Spin up only 2 containers from docker-compose.yaml (by deleting all services except for redis and mongo)

Make sure you have python 3.10 or 3.11 installed

  1. Navigate to /application folder
  2. Run docker-compose -f docker-compose-dev.yaml build && docker-compose -f docker-compose-dev.yaml up -d
  3. Export required variables
    export CELERY_BROKER_URL=redis://localhost:6379/0
    export CELERY_RESULT_BACKEND=redis://localhost:6379/1 export MONGO_URI=mongodb://localhost:27017/docsgpt
  4. Install dependencies pip install -r requirements.txt
  5. Prepare .env file Copy .env_sample and create .env with your openai api token
  6. Run the app python wsgi.py
  7. Start worker with celery -A app.celery worker -l INFO

To start frontend

  1. Navigate to /frontend folder
  2. Install dependencies npm install
  3. Run the app
  4. npm run dev

How to install the Chrome extension

Guides

Interested in contributing?

How to use any other documentation

How to host it locally (so all data will stay on-premises)

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