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feat: improved docs

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2025-01-25 20:36:10 +00:00
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5
CONTRIBUTING.md
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@@ -36,15 +36,14 @@ Tech Stack Overview:
### 🌐 If you are looking to contribute to frontend (⚛️React, Vite): ### 🌐 If you are looking to contribute to frontend (⚛️React, Vite):
- The current frontend is being migrated from [`/application`](https://github.com/arc53/DocsGPT/tree/main/application) to [`/frontend`](https://github.com/arc53/DocsGPT/tree/main/frontend) with a new design, so please contribute to the new one.
- Check out this [milestone](https://github.com/arc53/DocsGPT/milestone/1) and its issues.
- The updated Figma design can be found [here](https://www.figma.com/file/OXLtrl1EAy885to6S69554/DocsGPT?node-id=0%3A1&t=hjWVuxRg9yi5YkJ9-1). - The updated Figma design can be found [here](https://www.figma.com/file/OXLtrl1EAy885to6S69554/DocsGPT?node-id=0%3A1&t=hjWVuxRg9yi5YkJ9-1).
Please try to follow the guidelines. Please try to follow the guidelines.
### 🖥 If you are looking to contribute to Backend (🐍 Python): ### 🖥 If you are looking to contribute to Backend (🐍 Python):
- Review our issues and contribute to [`/application`](https://github.com/arc53/DocsGPT/tree/main/application) or [`/scripts`](https://github.com/arc53/DocsGPT/tree/main/scripts) (please disregard old [`ingest_rst.py`](https://github.com/arc53/DocsGPT/blob/main/scripts/old/ingest_rst.py) [`ingest_rst_sphinx.py`](https://github.com/arc53/DocsGPT/blob/main/scripts/old/ingest_rst_sphinx.py) files; these will be deprecated soon). - Review our issues and contribute to [`/application`](https://github.com/arc53/DocsGPT/tree/main/application)
- All new code should be covered with unit tests ([pytest](https://github.com/pytest-dev/pytest)). Please find tests under [`/tests`](https://github.com/arc53/DocsGPT/tree/main/tests) folder. - All new code should be covered with unit tests ([pytest](https://github.com/pytest-dev/pytest)). Please find tests under [`/tests`](https://github.com/arc53/DocsGPT/tree/main/tests) folder.
- Before submitting your Pull Request, ensure it can be queried after ingesting some test data. - Before submitting your Pull Request, ensure it can be queried after ingesting some test data.

103
README.md
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@@ -68,107 +68,46 @@ We're eager to provide personalized assistance when deploying your DocsGPT to a
> [!Note] > [!Note]
> Make sure you have [Docker](https://docs.docker.com/engine/install/) installed > 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: 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. 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: Otherwise, refer to this Guide for Windows:
1. Download and open this repository with `git clone https://github.com/arc53/DocsGPT.git` On windows:
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.
2. Create a `.env` file in your root directory and set the env variables.
It should look like this inside: It should look like this inside:
``` ```
LLM_NAME=[docsgpt or openai or others] LLM_NAME=[docsgpt or openai or others]
VITE_API_STREAMING=true
API_KEY=[if LLM_NAME is openai] 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/. 4. Navigate to http://localhost:5173/.
To stop, just run `Ctrl + C`. 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 ## Contributing
Please refer to the [CONTRIBUTING.md](CONTRIBUTING.md) file for information about how to get involved. We welcome issues, questions, and pull requests. 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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docs/pages/Deploying/Develepment-Environment.md Normal file
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@@ -0,0 +1,78 @@
## 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](https://github.com/arc53/DocsGPT/blob/main/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`.
> [!Note]
> You can also launch the in a debugger mode in vscode by accessing SHIFT + CMD + D or SHIFT + Windows + D on windows and selecting Flask or Celery.
### 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`.

59
docs/pages/Deploying/Quickstart.md
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@@ -15,11 +15,21 @@ If you prefer to follow manual steps, refer to this guide:
1. Open and download this repository with 1. Open and download this repository with
```bash ```bash
git clone https://github.com/arc53/DocsGPT.git git clone https://github.com/arc53/DocsGPT.git
cd DocsGPT
``` ```
2. Create a `.env` file in your root directory and set your `API_KEY` with your [OpenAI API key](https://platform.openai.com/account/api-keys). (optional in case you want to use OpenAI) 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]
API_KEY=[if LLM_NAME is openai]
```
See optional environment variables in the [/application/.env_sample](https://github.com/arc53/DocsGPT/blob/main/application/.env_sample) file.
3. Run the following commands: 3. Run the following commands:
```bash ```bash
docker-compose build && docker-compose up docker compose up
``` ```
4. Navigate to http://localhost:5173/. 4. Navigate to http://localhost:5173/.
@@ -27,43 +37,28 @@ To stop, simply press **Ctrl + C**.
**For WINDOWS:** **For WINDOWS:**
To run the setup on Windows, you have two options: using the Windows Subsystem for Linux (WSL) or using Git Bash or Command Prompt. 1. Open and download this repository with
**Option 1: Using Windows Subsystem for Linux (WSL):**
1. Install WSL if you haven't already. You can follow the official Microsoft documentation for installation: (https://learn.microsoft.com/en-us/windows/wsl/install).
2. After setting up WSL, open the WSL terminal.
3. Clone the repository and create the `.env` file:
```bash ```bash
git clone https://github.com/arc53/DocsGPT.git git clone https://github.com/arc53/DocsGPT.git
cd DocsGPT cd DocsGPT
echo "API_KEY=Yourkey" > .env
echo "VITE_API_STREAMING=true" >> .env
``` ```
4. Run the following command to start the setup with Docker Compose:
```bash
./run-with-docker-compose.sh
```
6. Open your web browser and navigate to http://localhost:5173/.
7. To stop the setup, just press **Ctrl + C** in the WSL terminal
**Option 2: Using Git Bash or Command Prompt (CMD):** 2. Create a `.env` file in your root directory and set the env variables.
It should look like this inside:
1. Install Git for Windows if you haven't already. Download it from the official website: (https://gitforwindows.org/).
2. Open Git Bash or Command Prompt.
3. Clone the repository and create the `.env` file:
```bash
git clone https://github.com/arc53/DocsGPT.git
cd DocsGPT
echo "API_KEY=Yourkey" > .env
echo "VITE_API_STREAMING=true" >> .env
``` ```
4. Run the following command to start the setup with Docker Compose: LLM_NAME=[docsgpt or openai or others]
```bash API_KEY=[if LLM_NAME is openai]
./run-with-docker-compose.sh
``` ```
5. Open your web browser and navigate to http://localhost:5173/.
6. To stop the setup, just press **Ctrl + C** in the Git Bash or Command Prompt terminal.
These steps should help you set up and run the project on Windows using either WSL or Git Bash/Command Prompt. See optional environment variables in the [/application/.env_sample](https://github.com/arc53/DocsGPT/blob/main/application/.env_sample) file.
3. Run the following command:
```bash
docker-compose up
```
4. Navigate to http://localhost:5173/.
5. To stop the setup, just press **Ctrl + C** in the WSL terminal
**Important:** Ensure that Docker is installed and properly configured on your Windows system for these steps to work. **Important:** Ensure that Docker is installed and properly configured on your Windows system for these steps to work.

4
docs/pages/Deploying/_meta.json
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@@ -7,6 +7,10 @@
"title": "⚡️Quickstart", "title": "⚡️Quickstart",
"href": "/Deploying/Quickstart" "href": "/Deploying/Quickstart"
}, },
"Development-Environment": {
"title": "🛠️Development Environment",
"href": "/Deploying/Development-Environment"
},
"Railway-Deploying": { "Railway-Deploying": {
"title": "🚂Deploying on Railway", "title": "🚂Deploying on Railway",
"href": "/Deploying/Railway-Deploying" "href": "/Deploying/Railway-Deploying"