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201 lines
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201 lines
8.2 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><a href="https://docsgpt.arc53.com/">DocsGPT</a></strong> is a cutting-edge open-source solution that streamlines the process of finding information in the 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><a href="https://docsgpt.arc53.com/">DocsGPT</a></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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<a href="https://twitter.com/docsgptai"></a>
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</div>
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### Production Support / Help for Companies:
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We're eager to provide personalized assistance when deploying your DocsGPT to a live environment.
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- [Book Demo :wave:](https://airtable.com/appdeaL0F1qV8Bl2C/shrrJF1Ll7btCJRbP)
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- [Send Email :email:](mailto:contact@arc53.com?subject=DocsGPT%20support%2Fsolutions)
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## Roadmap
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You can find our roadmap [here](https://github.com/orgs/arc53/projects/2). Please don't hesitate to contribute or create issues, it helps us improve DocsGPT!
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## Our Open-Source Models Optimized for DocsGPT:
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| Name | Base Model | Requirements (or similar) |
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| --------------------------------------------------------------------- | ----------- | ------------------------- |
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| [Docsgpt-7b-mistral](https://huggingface.co/Arc53/docsgpt-7b-mistral) | Mistral-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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- :mag: :fire: [Cloud Version](https://docsgpt.arc53.com/)
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- :speech_balloon: :tada: [Join our Discord](https://discord.gg/n5BX8dh8rU)
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- :books: :sunglasses: [Guides](https://docs.docsgpt.cloud/)
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- :couple: [Interested in contributing?](https://github.com/arc53/DocsGPT/blob/main/CONTRIBUTING.md)
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- :file_folder: :rocket: [How to use any other documentation](https://docs.docsgpt.cloud/Guides/How-to-train-on-other-documentation)
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- :house: :closed_lock_with_key: [How to host it locally (so all data will stay on-premises)](https://docs.docsgpt.cloud/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 for other libraries.
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- Frontend - Frontend uses <a href="https://vitejs.dev/">Vite</a> and <a href="https://react.dev/">React</a>.
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## QuickStart
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> [!Note]
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> Make sure you have [Docker](https://docs.docker.com/engine/install/) installed
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On Mac OS or Linux, write:
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`./setup.sh`
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It will install all the dependencies and allow you to download the local model, use OpenAI or use our LLM API.
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Otherwise, refer to this Guide for Windows:
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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 variables and `VITE_API_STREAMING` to true or false, depending on whether you want streaming answers or not.
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It should look like this inside:
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```
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LLM_NAME=[docsgpt or openai or others]
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VITE_API_STREAMING=true
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API_KEY=[if LLM_NAME is openai]
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```
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See optional environment variables in the [/.env-template](https://github.com/arc53/DocsGPT/blob/main/.env-template) and [/application/.env_sample](https://github.com/arc53/DocsGPT/blob/main/application/.env_sample) files.
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3. Run [./run-with-docker-compose.sh](https://github.com/arc53/DocsGPT/blob/main/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 two containers are used from [docker-compose.yaml](https://github.com/arc53/DocsGPT/blob/main/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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> [!Note]
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> Make sure you have Python 3.10 or 3.11 installed.
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1. Export required environment variables or prepare a `.env` file in the project folder:
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- Copy [.env_sample](https://github.com/arc53/DocsGPT/blob/main/application/.env_sample) and create `.env`.
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(check out [`application/core/settings.py`](application/core/settings.py) if you want to see more config options.)
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2. (optional) Create a Python virtual environment:
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You can follow the [Python official documentation](https://docs.python.org/3/tutorial/venv.html) for virtual environments.
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a) On Mac OS and Linux
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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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b) On Windows
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```commandline
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python -m venv venv
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venv/Scripts/activate
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```
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3. Download embedding model and save it in the `model/` folder:
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You can use the script below, or download it manually from [here](https://d3dg1063dc54p9.cloudfront.net/models/embeddings/mpnet-base-v2.zip), unzip it and save it in the `model/` folder.
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```commandline
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wget https://d3dg1063dc54p9.cloudfront.net/models/embeddings/mpnet-base-v2.zip
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unzip mpnet-base-v2.zip -d model
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rm mpnet-base-v2.zip
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```
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4. 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 using `flask --app application/app.py 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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> [!Note]
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> Make sure you have Node version 16 or higher.
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1. Navigate to the [/frontend](https://github.com/arc53/DocsGPT/tree/main/frontend) folder.
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2. Install the required packages `husky` and `vite` (ignore if already installed).
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```commandline
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npm install husky -g
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npm install vite -g
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```
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3. Install dependencies by running `npm install --include=dev`.
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4. Run the app using `npm run dev`.
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## Contributing
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Please refer to the [CONTRIBUTING.md](CONTRIBUTING.md) file for information about how to get involved. We welcome issues, questions, and pull requests.
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## Code Of Conduct
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We as members, contributors, and leaders, pledge to make participation in our community a harassment-free experience for everyone, regardless of age, body size, visible or invisible disability, ethnicity, sex characteristics, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, religion, or sexual identity and orientation. Please refer to the [CODE_OF_CONDUCT.md](CODE_OF_CONDUCT.md) file for more information about contributing.
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## Many Thanks To Our Contributors⚡
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<a href="https://github.com/arc53/DocsGPT/graphs/contributors" alt="View Contributors">
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<img src="https://contrib.rocks/image?repo=arc53/DocsGPT" alt="Contributors" />
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</a>
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## License
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The source code license is [MIT](https://opensource.org/license/mit/), as described in the [LICENSE](LICENSE) file.
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Built with [:bird: :link: LangChain](https://github.com/hwchase17/langchain)
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