Merge pull request #139 from langflow-ai/docs-move-docker-page
docs: move docker deployment to its own page
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Nate McCall
GitHub
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c247f7764a
2 changed files with 75 additions and 103 deletions
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---
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title: Docker Deployment
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title: Docker deployment
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slug: /get-started/docker
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---
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# Docker Deployment
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There are two different Docker Compose files.
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They deploy the same applications and containers, but to different environments.
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## Standard Deployment
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- [`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.
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```bash
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# Build and start all services
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docker compose build
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docker compose up -d
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```
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- [`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.
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## CPU-Only Deployment
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To install OpenRAG with Docker Compose:
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For environments without GPU support:
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1. Clone the OpenRAG repository.
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```bash
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git clone https://github.com/langflow-ai/openrag.git
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cd openrag
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```
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```bash
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docker compose -f docker-compose-cpu.yml up -d
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```
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2. Copy the example `.env` file that is included in the repository root.
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The example file includes all environment variables with comments to guide you in finding and setting their values.
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```bash
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cp .env.example .env
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```
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## Force Rebuild
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Alternatively, create a new `.env` file in the repository root.
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```
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touch .env
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```
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If you need to reset state or rebuild everything:
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3. Set environment variables. The Docker Compose files are populated with values from your `.env`, so the following values are **required** to be set:
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```bash
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OPENSEARCH_PASSWORD=your_secure_password
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OPENAI_API_KEY=your_openai_api_key
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LANGFLOW_SUPERUSER=admin
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LANGFLOW_SUPERUSER_PASSWORD=your_langflow_password
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LANGFLOW_SECRET_KEY=your_secret_key
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```
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For more information on configuring OpenRAG with environment variables, see [Environment variables](/configure/configuration).
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For additional configuration values, including `config.yaml`, see [Configuration](/configure/configuration).
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4. Deploy OpenRAG with Docker Compose based on your deployment type.
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For GPU-enabled systems, run the following command:
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```bash
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docker compose up -d
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```
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For CPU-only systems, run the following command:
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```bash
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docker compose -f docker-compose-cpu.yml up -d
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```
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The OpenRAG Docker Compose file starts five containers:
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| Container Name | Default Address | Purpose |
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|---|---|---|
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| OpenRAG Backend | http://localhost:8000 | FastAPI server and core functionality. |
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| OpenRAG Frontend | http://localhost:3000 | React web interface for users. |
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| Langflow | http://localhost:7860 | AI workflow engine and flow management. |
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| OpenSearch | http://localhost:9200 | Vector database for document storage. |
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| OpenSearch Dashboards | http://localhost:5601 | Database administration interface. |
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5. Verify installation by confirming all services are running.
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```bash
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docker compose ps
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```
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You can now access the application at:
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- **Frontend**: http://localhost:3000
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- **Backend API**: http://localhost:8000
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- **Langflow**: http://localhost:7860
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Continue with the [Quickstart](/quickstart).
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## Rebuild all Docker containers
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If you need to reset state and rebuild all of your containers, run the following command.
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Your OpenSearch and Langflow databases will be lost.
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Documents stored in the `./documents` directory will persist, since the directory is mounted as a volume in the OpenRAG backend container.
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```bash
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docker compose up --build --force-recreate --remove-orphans
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```
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## Service URLs
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After deployment, services are available at:
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- Frontend: http://localhost:3000
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- Backend API: http://localhost:8000
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- Langflow: http://localhost:7860
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- OpenSearch: http://localhost:9200
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- OpenSearch Dashboards: http://localhost:5601
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@ -10,7 +10,7 @@ OpenRAG can be installed in multiple ways:
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* [**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.
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* [**Docker Compose**](#install-and-run-docker): Clone the OpenRAG repository and deploy OpenRAG with Docker Compose, including all services and dependencies.
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* [**Docker Compose**](get-started/docker): Clone the OpenRAG repository and deploy OpenRAG with Docker Compose, including all services and dependencies.
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## Prerequisites
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@ -138,80 +138,4 @@ The `LANGFLOW_PUBLIC_URL` controls where the Langflow web interface can be acces
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The `WEBHOOK_BASE_URL` controls where the endpoint for `/connectors/CONNECTOR_TYPE/webhook` will be available.
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This connection enables real-time document synchronization with external services.
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For example, for Google Drive file synchronization the webhook URL is `/connectors/google_drive/webhook`.
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## Docker {#install-and-run-docker}
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There are two different Docker Compose files.
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They deploy the same applications and containers, but to different environments.
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- [`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.
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- [`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.
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To install OpenRAG with Docker Compose:
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1. Clone the OpenRAG repository.
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```bash
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git clone https://github.com/langflow-ai/openrag.git
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cd openrag
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```
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2. Copy the example `.env` file that is included in the repository root.
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The example file includes all environment variables with comments to guide you in finding and setting their values.
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```bash
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cp .env.example .env
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```
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Alternatively, create a new `.env` file in the repository root.
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```
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touch .env
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```
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3. Set environment variables. The Docker Compose files are populated with values from your `.env`, so the following values are **required** to be set:
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```bash
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OPENSEARCH_PASSWORD=your_secure_password
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OPENAI_API_KEY=your_openai_api_key
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LANGFLOW_SUPERUSER=admin
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LANGFLOW_SUPERUSER_PASSWORD=your_langflow_password
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LANGFLOW_SECRET_KEY=your_secret_key
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```
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For more information on configuring OpenRAG with environment variables, see [Environment variables](/configure/configuration).
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For additional configuration values, including `config.yaml`, see [Configuration](/configure/configuration).
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4. Deploy OpenRAG with Docker Compose based on your deployment type.
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For GPU-enabled systems, run the following command:
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```bash
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docker compose up -d
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```
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For CPU-only systems, run the following command:
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```bash
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docker compose -f docker-compose-cpu.yml up -d
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```
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The OpenRAG Docker Compose file starts five containers:
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| Container Name | Default Address | Purpose |
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|---|---|---|
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| OpenRAG Backend | http://localhost:8000 | FastAPI server and core functionality. |
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| OpenRAG Frontend | http://localhost:3000 | React web interface for users. |
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| Langflow | http://localhost:7860 | AI workflow engine and flow management. |
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| OpenSearch | http://localhost:9200 | Vector database for document storage. |
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| OpenSearch Dashboards | http://localhost:5601 | Database administration interface. |
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5. Verify installation by confirming all services are running.
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```bash
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docker compose ps
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```
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You can now access the application at:
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- **Frontend**: http://localhost:3000
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- **Backend API**: http://localhost:8000
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- **Langflow**: http://localhost:7860
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Continue with the Quickstart.
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For example, for Google Drive file synchronization the webhook URL is `/connectors/google_drive/webhook`.
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