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.
 ## Roadmap You can find our [Roadmap](https://github.com/orgs/arc53/projects/2) here, please don't hesitate contributing or creating issues, it helps us make DocsGPT better! ## Our open source models optimised for DocsGPT: | Name | Base Model | Requirements (or similar) | |-------------------|------------|----------------------------------------------------------| | [Docsgpt-7b-falcon](https://huggingface.co/Arc53/docsgpt-7b-falcon) | Falcon-7b | 1xA10G gpu | | [Docsgpt-14b](https://huggingface.co/Arc53/docsgpt-14b) | llama-2-14b | 2xA10 gpu's | | [Docsgpt-40b-falcon](https://huggingface.co/Arc53/docsgpt-40b-falcon) | falcon-40b | 8xA10G gpu's | If you don't have enough resources to run it you can use bitsnbytes to quantize ## Features  ## Useful links [Live preview](https://docsgpt.arc53.com/) [Join Our Discord](https://discord.gg/n5BX8dh8rU) [Guides](https://github.com/arc53/docsgpt/wiki) [Interested in contributing?](https://github.com/arc53/DocsGPT/blob/main/CONTRIBUTING.md) [How to use any other documentation](https://github.com/arc53/docsgpt/wiki/How-to-train-on-other-documentation) [How to host it locally (so all data will stay on-premises)](https://github.com/arc53/DocsGPT/wiki/How-to-use-different-LLM's#hosting-everything-locally) ## Project structure - Application - Flask app (main application) - Extensions - Chrome extension - Scripts - Script that creates similarity search index and store for other libraries. - Frontend - Frontend uses Vite and React ## QuickStart Note: Make sure you have docker installed 1. Dowload and open this repository with `git clone https://github.com/arc53/DocsGPT.git` 2. Create an .env file in your root directory and set the env variable OPENAI_API_KEY with your openai api key and VITE_API_STREAMING to true or false, depending on if you want streaming answers or not It should look like this inside: ``` OPENAI_API_KEY=Yourkey VITE_API_STREAMING=true ``` 3. Run `./run-with-docker-compose.sh` 4. Navigate to http://localhost:5173/ To stop just run Ctrl + C ## Development environments ### Spin up mongo and redis For development only 2 containers are used from docker-compose.yaml (by deleting all services except for redis and mongo). See file [docker-compose-dev.yaml](./docker-compose-dev.yaml). Run ``` docker compose -f docker-compose-dev.yaml build docker compose -f docker-compose-dev.yaml up -d ``` ### Run the backend Make sure you have Python 3.10 or 3.11 installed. 1. Export required environment variables ```commandline export CELERY_BROKER_URL=redis://localhost:6379/0 export CELERY_RESULT_BACKEND=redis://localhost:6379/1 export MONGO_URI=mongodb://localhost:27017/docsgpt ``` 2. Prepare .env file Copy `.env_sample` and create `.env` with your OpenAI API token 3. (optional) Create a python virtual environment ```commandline python -m venv venv . venv/bin/activate ``` 4. Change to `application/` subdir and install dependencies for the backend ```commandline cd application/ pip install -r requirements.txt ``` 5. Run the app `python wsgi.py` 6. Start worker with `celery -A app.celery worker -l INFO` ### Start frontend Make sure you have Node version 16 or higher. 1. Navigate to `/frontend` folder 2. Install dependencies `npm install` 3. Run the app `npm run dev` Built with [🦜️🔗 LangChain](https://github.com/hwchase17/langchain)