mirror of
https://github.com/arc53/DocsGPT.git
synced 2025-11-29 08:33:20 +00:00
feat: improved docs
This commit is contained in:
Alex
@@ -36,15 +36,14 @@ Tech Stack Overview:
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### 🌐 If you are looking to contribute to frontend (⚛️React, Vite):
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- 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.
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- Check out this [milestone](https://github.com/arc53/DocsGPT/milestone/1) and its issues.
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- The updated Figma design can be found [here](https://www.figma.com/file/OXLtrl1EAy885to6S69554/DocsGPT?node-id=0%3A1&t=hjWVuxRg9yi5YkJ9-1).
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Please try to follow the guidelines.
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### 🖥 If you are looking to contribute to Backend (🐍 Python):
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- 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).
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- Review our issues and contribute to [`/application`](https://github.com/arc53/DocsGPT/tree/main/application)
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- 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.
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- Before submitting your Pull Request, ensure it can be queried after ingesting some test data.
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103
README.md
103
README.md
@@ -68,107 +68,46 @@ We're eager to provide personalized assistance when deploying your DocsGPT to a
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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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1. Clone the repository and run the following command:
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```bash
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git clone https://github.com/arc53/DocsGPT.git
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cd DocsGPT
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```
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On Mac OS or Linux, write:
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`./setup.sh`
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2. Run the following command:
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```bash
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./setup.sh
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```
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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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On windows:
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2. Create a `.env` file in your root directory and set the env variables.
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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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See optional environment variables in the [/application/.env_sample](https://github.com/arc53/DocsGPT/blob/main/application/.env_sample) file.
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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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3. Run the following command:
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```bash
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docker-compose up
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```
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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 3.12 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-template](https://github.com/arc53/DocsGPT/blob/main/application/.env-template) 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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78
docs/pages/Deploying/Develepment-Environment.md
Normal file
78
docs/pages/Deploying/Develepment-Environment.md
Normal file
@@ -0,0 +1,78 @@
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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](https://github.com/arc53/DocsGPT/blob/main/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 3.12 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-template](https://github.com/arc53/DocsGPT/blob/main/application/.env-template) 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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> [!Note]
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> 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.
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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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@@ -15,11 +15,21 @@ If you prefer to follow manual steps, refer to this guide:
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1. Open and download this repository with
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```bash
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git clone https://github.com/arc53/DocsGPT.git
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cd DocsGPT
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```
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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)
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2. Create a `.env` file in your root directory and set the env variables.
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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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API_KEY=[if LLM_NAME is openai]
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```
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See optional environment variables in the [/application/.env_sample](https://github.com/arc53/DocsGPT/blob/main/application/.env_sample) file.
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3. Run the following commands:
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```bash
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docker-compose build && docker-compose up
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docker compose up
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```
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4. Navigate to http://localhost:5173/.
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@@ -27,43 +37,28 @@ To stop, simply press **Ctrl + C**.
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**For WINDOWS:**
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To run the setup on Windows, you have two options: using the Windows Subsystem for Linux (WSL) or using Git Bash or Command Prompt.
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**Option 1: Using Windows Subsystem for Linux (WSL):**
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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).
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2. After setting up WSL, open the WSL terminal.
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3. Clone the repository and create the `.env` file:
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1. Open and download this repository with
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```bash
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git clone https://github.com/arc53/DocsGPT.git
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cd DocsGPT
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echo "API_KEY=Yourkey" > .env
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echo "VITE_API_STREAMING=true" >> .env
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```
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4. Run the following command to start the setup with Docker Compose:
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```bash
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./run-with-docker-compose.sh
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```
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6. Open your web browser and navigate to http://localhost:5173/.
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7. To stop the setup, just press **Ctrl + C** in the WSL terminal
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**Option 2: Using Git Bash or Command Prompt (CMD):**
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2. Create a `.env` file in your root directory and set the env variables.
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It should look like this inside:
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1. Install Git for Windows if you haven't already. Download it from the official website: (https://gitforwindows.org/).
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2. Open Git Bash or Command Prompt.
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3. Clone the repository and create the `.env` file:
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```bash
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git clone https://github.com/arc53/DocsGPT.git
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cd DocsGPT
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echo "API_KEY=Yourkey" > .env
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echo "VITE_API_STREAMING=true" >> .env
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```
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4. Run the following command to start the setup with Docker Compose:
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```bash
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./run-with-docker-compose.sh
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LLM_NAME=[docsgpt or openai or others]
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API_KEY=[if LLM_NAME is openai]
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```
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5. Open your web browser and navigate to http://localhost:5173/.
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6. To stop the setup, just press **Ctrl + C** in the Git Bash or Command Prompt terminal.
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These steps should help you set up and run the project on Windows using either WSL or Git Bash/Command Prompt.
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See optional environment variables in the [/application/.env_sample](https://github.com/arc53/DocsGPT/blob/main/application/.env_sample) file.
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3. Run the following command:
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```bash
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docker-compose up
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```
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4. Navigate to http://localhost:5173/.
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5. To stop the setup, just press **Ctrl + C** in the WSL terminal
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**Important:** Ensure that Docker is installed and properly configured on your Windows system for these steps to work.
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@@ -7,6 +7,10 @@
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"title": "⚡️Quickstart",
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"href": "/Deploying/Quickstart"
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},
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"Development-Environment": {
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"title": "🛠️Development Environment",
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"href": "/Deploying/Development-Environment"
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},
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"Railway-Deploying": {
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"title": "🚂Deploying on Railway",
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"href": "/Deploying/Railway-Deploying"
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