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feat: improved docs

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2025-01-25 20:36:10 +00:00
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@@ -68,107 +68,46 @@ We're eager to provide personalized assistance when deploying your DocsGPT to a
> [!Note]
> Make sure you have [Docker](https://docs.docker.com/engine/install/) installed
1. Clone the repository and run the following command:
```bash
git clone https://github.com/arc53/DocsGPT.git
cd DocsGPT
```
On Mac OS or Linux, write:
`./setup.sh`
2. Run the following command:
```bash
./setup.sh
```
It will install all the dependencies and allow you to download the local model, use OpenAI or use our LLM API.
Otherwise, refer to this Guide for Windows:
1. Download and open this repository with `git clone https://github.com/arc53/DocsGPT.git`
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.
On windows:
2. Create a `.env` file in your root directory and set the env variables.
It should look like this inside:
```
LLM_NAME=[docsgpt or openai or others]
VITE_API_STREAMING=true
API_KEY=[if LLM_NAME is openai]
```
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.
See optional environment variables in the [/application/.env_sample](https://github.com/arc53/DocsGPT/blob/main/application/.env_sample) file.
3. Run [./run-with-docker-compose.sh](https://github.com/arc53/DocsGPT/blob/main/run-with-docker-compose.sh).
3. Run the following command:
```bash
docker-compose up
```
4. Navigate to http://localhost:5173/.
To stop, just run `Ctrl + C`.
## Development Environments
### Spin up Mongo and Redis
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).
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
> [!Note]
> Make sure you have Python 3.12 installed.
1. Export required environment variables or prepare a `.env` file in the project folder:
- Copy [.env-template](https://github.com/arc53/DocsGPT/blob/main/application/.env-template) and create `.env`.
(check out [`application/core/settings.py`](application/core/settings.py) if you want to see more config options.)
2. (optional) Create a Python virtual environment:
You can follow the [Python official documentation](https://docs.python.org/3/tutorial/venv.html) for virtual environments.
a) On Mac OS and Linux
```commandline
python -m venv venv
. venv/bin/activate
```
b) On Windows
```commandline
python -m venv venv
venv/Scripts/activate
```
3. Download embedding model and save it in the `model/` folder:
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.
```commandline
wget https://d3dg1063dc54p9.cloudfront.net/models/embeddings/mpnet-base-v2.zip
unzip mpnet-base-v2.zip -d model
rm mpnet-base-v2.zip
```
4. Install dependencies for the backend:
```commandline
pip install -r application/requirements.txt
```
5. Run the app using `flask --app application/app.py run --host=0.0.0.0 --port=7091`.
6. Start worker with `celery -A application.app.celery worker -l INFO`.
### Start Frontend
> [!Note]
> Make sure you have Node version 16 or higher.
1. Navigate to the [/frontend](https://github.com/arc53/DocsGPT/tree/main/frontend) folder.
2. Install the required packages `husky` and `vite` (ignore if already installed).
```commandline
npm install husky -g
npm install vite -g
```
3. Install dependencies by running `npm install --include=dev`.
4. Run the app using `npm run dev`.
## Contributing
Please refer to the [CONTRIBUTING.md](CONTRIBUTING.md) file for information about how to get involved. We welcome issues, questions, and pull requests.