mirror of
https://github.com/arc53/DocsGPT
synced 2024-11-17 21:26:26 +00:00
156 lines
5.5 KiB
Markdown
156 lines
5.5 KiB
Markdown
<h1 align="center">
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DocsGPT 🦖
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</h1>
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<p align="center">
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<strong>Open-Source Documentation Assistant</strong>
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</p>
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<p align="left">
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<strong>DocsGPT</strong> is a cutting-edge open-source solution that streamlines the process of finding information in project documentation. With its integration of the powerful <strong>GPT</strong> models, developers can easily ask questions about a project and receive accurate answers.
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Say goodbye to time-consuming manual searches, and let <strong>DocsGPT</strong> 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.
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</p>
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<div align="center">
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<a href="https://github.com/arc53/DocsGPT"></a>
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<a href="https://github.com/arc53/DocsGPT"></a>
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<a href="https://github.com/arc53/DocsGPT/blob/main/LICENSE"></a>
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<a href="https://discord.gg/n5BX8dh8rU"></a>
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</div>
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### Enterprise Solutions:
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When deploying your DocsGPT to a live environment, we're eager to provide personalized assistance. Fill out this [form](https://airtable.com/appdeaL0F1qV8Bl2C/shrrJF1Ll7btCJRbP) to discuss your project further, and our team will connect with you shortly.
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### [🎉 Join the Hacktoberfest with DocsGPT and Earn a Free T-shirt! 🎉](https://github.com/arc53/DocsGPT/blob/main/HACKTOBERFEST.md)
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## Roadmap
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You can find our [Roadmap](https://github.com/orgs/arc53/projects/2) here. Please don't hesitate to contribute or create issues, it helps us make DocsGPT better!
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## Our open source models optimised for DocsGPT:
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| Name | Base Model | Requirements (or similar) |
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|-------------------|------------|----------------------------------------------------------|
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| [Docsgpt-7b-falcon](https://huggingface.co/Arc53/docsgpt-7b-falcon) | Falcon-7b | 1xA10G gpu |
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| [Docsgpt-14b](https://huggingface.co/Arc53/docsgpt-14b) | llama-2-14b | 2xA10 gpu's |
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| [Docsgpt-40b-falcon](https://huggingface.co/Arc53/docsgpt-40b-falcon) | falcon-40b | 8xA10G gpu's |
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If you don't have enough resources to run it you can use bitsnbytes to quantize
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## Features
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## Useful links
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[Live preview](https://docsgpt.arc53.com/)
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[Join Our Discord](https://discord.gg/n5BX8dh8rU)
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[Guides](https://docs.docsgpt.co.uk/)
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[Interested in contributing?](https://github.com/arc53/DocsGPT/blob/main/CONTRIBUTING.md)
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[How to use any other documentation](https://docs.docsgpt.co.uk/Guides/How-to-train-on-other-documentation)
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[How to host it locally (so all data will stay on-premises)](https://docs.docsgpt.co.uk/Guides/How-to-use-different-LLM)
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## Project structure
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- Application - Flask app (main application)
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- Extensions - Chrome extension
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- Scripts - Script that creates similarity search index and store for other libraries.
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- Frontend - Frontend uses Vite and React
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## QuickStart
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Note: Make sure you have Docker installed
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On Mac OS or Linux just write:
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`./setup.sh`
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It will install all the dependencies and give you an option to download local model or use OpenAI
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Otherwise refer to this Guide:
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1. Download and open this repository with `git clone https://github.com/arc53/DocsGPT.git`
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2. Create a .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
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It should look like this inside:
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```
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API_KEY=Yourkey
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VITE_API_STREAMING=true
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```
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See optional environment variables in the `/.env-template` and `/application/.env_sample` files.
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3. Run `./run-with-docker-compose.sh`
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4. Navigate to http://localhost:5173/
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To stop just run Ctrl + C
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## Development environments
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### Spin up mongo and redis
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For development only 2 containers are used from docker-compose.yaml (by deleting all services except for Redis and Mongo).
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See file [docker-compose-dev.yaml](./docker-compose-dev.yaml).
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Run
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```
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docker compose -f docker-compose-dev.yaml build
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docker compose -f docker-compose-dev.yaml up -d
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```
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### Run the backend
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Make sure you have Python 3.10 or 3.11 installed.
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1. Export required environment variables
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```commandline
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export CELERY_BROKER_URL=redis://localhost:6379/0
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export CELERY_RESULT_BACKEND=redis://localhost:6379/1
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export MONGO_URI=mongodb://localhost:27017/docsgpt
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export FLASK_APP=application/app.py
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export FLASK_DEBUG=true
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```
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2. Prepare .env file
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Copy `.env_sample` and create `.env` with your OpenAI API token
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3. (optional) Create a Python virtual environment
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```commandline
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python -m venv venv
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. venv/bin/activate
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```
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4. Change to `application/` subdir and install dependencies for the backend
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```commandline
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pip install -r application/requirements.txt
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```
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5. Run the app `flask run --host=0.0.0.0 --port=7091`
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6. Start worker with `celery -A application.app.celery worker -l INFO`
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### Start frontend
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Make sure you have Node version 16 or higher.
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1. Navigate to `/frontend` folder
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2. Install dependencies
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`npm install`
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3. Run the app
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`npm run dev`
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Built with [🦜️🔗 LangChain](https://github.com/hwchase17/langchain)
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