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docs/docs/get-started/docker.mdx
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@ -1,40 +1,88 @@
--- ---
title: Docker Deployment title: Docker deployment
slug: /get-started/docker slug: /get-started/docker
--- ---
# Docker Deployment There are two different Docker Compose files.
They deploy the same applications and containers, but to different environments.
## Standard Deployment - [`docker-compose.yml`](https://github.com/langflow-ai/openrag/blob/main/docker-compose.yml) is an OpenRAG deployment with GPU support for accelerated AI processing.
```bash - [`docker-compose-cpu.yml`](https://github.com/langflow-ai/openrag/blob/main/docker-compose-cpu.yml) is a CPU-only version of OpenRAG for systems without GPU support. Use this Docker compose file for environments where GPU drivers aren't available.
# Build and start all services
docker compose build
docker compose up -d
```
## CPU-Only Deployment To install OpenRAG with Docker Compose:
For environments without GPU support: 1. Clone the OpenRAG repository.
```bash
git clone https://github.com/langflow-ai/openrag.git
cd openrag
```
```bash 2. Copy the example `.env` file that is included in the repository root.
docker compose -f docker-compose-cpu.yml up -d The example file includes all environment variables with comments to guide you in finding and setting their values.
``` ```bash
cp .env.example .env
```
## Force Rebuild Alternatively, create a new `.env` file in the repository root.
```
touch .env
```
If you need to reset state or rebuild everything: 3. Set environment variables. The Docker Compose files are populated with values from your `.env`, so the following values are **required** to be set:
```bash
OPENSEARCH_PASSWORD=your_secure_password
OPENAI_API_KEY=your_openai_api_key
LANGFLOW_SUPERUSER=admin
LANGFLOW_SUPERUSER_PASSWORD=your_langflow_password
LANGFLOW_SECRET_KEY=your_secret_key
```
For more information on configuring OpenRAG with environment variables, see [Environment variables](/configure/configuration).
For additional configuration values, including `config.yaml`, see [Configuration](/configure/configuration).
4. Deploy OpenRAG with Docker Compose based on your deployment type.
For GPU-enabled systems, run the following command:
```bash
docker compose up -d
```
For CPU-only systems, run the following command:
```bash
docker compose -f docker-compose-cpu.yml up -d
```
The OpenRAG Docker Compose file starts five containers:
| Container Name | Default Address | Purpose |
|---|---|---|
| OpenRAG Backend | http://localhost:8000 | FastAPI server and core functionality. |
| OpenRAG Frontend | http://localhost:3000 | React web interface for users. |
| Langflow | http://localhost:7860 | AI workflow engine and flow management. |
| OpenSearch | http://localhost:9200 | Vector database for document storage. |
| OpenSearch Dashboards | http://localhost:5601 | Database administration interface. |
5. Verify installation by confirming all services are running.
```bash
docker compose ps
```
You can now access the application at:
- **Frontend**: http://localhost:3000
- **Backend API**: http://localhost:8000
- **Langflow**: http://localhost:7860
Continue with the [Quickstart](/quickstart).
## Rebuild all Docker containers
If you need to reset state and rebuild all of your containers, run the following command.
Your OpenSearch and Langflow databases will be lost.
Documents stored in the `./documents` directory will persist, since the directory is mounted as a volume in the OpenRAG backend container.
```bash ```bash
docker compose up --build --force-recreate --remove-orphans docker compose up --build --force-recreate --remove-orphans
``` ```
## Service URLs
After deployment, services are available at:
- Frontend: http://localhost:3000
- Backend API: http://localhost:8000
- Langflow: http://localhost:7860
- OpenSearch: http://localhost:9200
- OpenSearch Dashboards: http://localhost:5601

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@ -10,7 +10,7 @@ OpenRAG can be installed in multiple ways:
* [**Python wheel**](#install-python-wheel): Install the OpenRAG Python wheel and use the [OpenRAG Terminal User Interface (TUI)](/get-started/tui) to install, run, and configure your OpenRAG deployment without running Docker commands. * [**Python wheel**](#install-python-wheel): Install the OpenRAG Python wheel and use the [OpenRAG Terminal User Interface (TUI)](/get-started/tui) to install, run, and configure your OpenRAG deployment without running Docker commands.
* [**Docker Compose**](#install-and-run-docker): Clone the OpenRAG repository and deploy OpenRAG with Docker Compose, including all services and dependencies. * [**Docker Compose**](get-started/docker): Clone the OpenRAG repository and deploy OpenRAG with Docker Compose, including all services and dependencies.
## Prerequisites ## Prerequisites
@ -138,80 +138,4 @@ The `LANGFLOW_PUBLIC_URL` controls where the Langflow web interface can be acces
The `WEBHOOK_BASE_URL` controls where the endpoint for `/connectors/CONNECTOR_TYPE/webhook` will be available. The `WEBHOOK_BASE_URL` controls where the endpoint for `/connectors/CONNECTOR_TYPE/webhook` will be available.
This connection enables real-time document synchronization with external services. This connection enables real-time document synchronization with external services.
For example, for Google Drive file synchronization the webhook URL is `/connectors/google_drive/webhook`. For example, for Google Drive file synchronization the webhook URL is `/connectors/google_drive/webhook`.
## Docker {#install-and-run-docker}
There are two different Docker Compose files.
They deploy the same applications and containers, but to different environments.
- [`docker-compose.yml`](https://github.com/langflow-ai/openrag/blob/main/docker-compose.yml) is an OpenRAG deployment with GPU support for accelerated AI processing.
- [`docker-compose-cpu.yml`](https://github.com/langflow-ai/openrag/blob/main/docker-compose-cpu.yml) is a CPU-only version of OpenRAG for systems without GPU support. Use this Docker compose file for environments where GPU drivers aren't available.
To install OpenRAG with Docker Compose:
1. Clone the OpenRAG repository.
```bash
git clone https://github.com/langflow-ai/openrag.git
cd openrag
```
2. Copy the example `.env` file that is included in the repository root.
The example file includes all environment variables with comments to guide you in finding and setting their values.
```bash
cp .env.example .env
```
Alternatively, create a new `.env` file in the repository root.
```
touch .env
```
3. Set environment variables. The Docker Compose files are populated with values from your `.env`, so the following values are **required** to be set:
```bash
OPENSEARCH_PASSWORD=your_secure_password
OPENAI_API_KEY=your_openai_api_key
LANGFLOW_SUPERUSER=admin
LANGFLOW_SUPERUSER_PASSWORD=your_langflow_password
LANGFLOW_SECRET_KEY=your_secret_key
```
For more information on configuring OpenRAG with environment variables, see [Environment variables](/configure/configuration).
For additional configuration values, including `config.yaml`, see [Configuration](/configure/configuration).
4. Deploy OpenRAG with Docker Compose based on your deployment type.
For GPU-enabled systems, run the following command:
```bash
docker compose up -d
```
For CPU-only systems, run the following command:
```bash
docker compose -f docker-compose-cpu.yml up -d
```
The OpenRAG Docker Compose file starts five containers:
| Container Name | Default Address | Purpose |
|---|---|---|
| OpenRAG Backend | http://localhost:8000 | FastAPI server and core functionality. |
| OpenRAG Frontend | http://localhost:3000 | React web interface for users. |
| Langflow | http://localhost:7860 | AI workflow engine and flow management. |
| OpenSearch | http://localhost:9200 | Vector database for document storage. |
| OpenSearch Dashboards | http://localhost:5601 | Database administration interface. |
5. Verify installation by confirming all services are running.
```bash
docker compose ps
```
You can now access the application at:
- **Frontend**: http://localhost:3000
- **Backend API**: http://localhost:8000
- **Langflow**: http://localhost:7860
Continue with the Quickstart.