docker-page
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Mendon Kissling
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2 changed files with 26 additions and 20 deletions
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@ -7,6 +7,8 @@ The first time you start OpenRAG, whether using the TUI or a `.env` file, you mu
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Values from onboarding can be changed later in the OpenRAG **Settings** page.
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Choose one LLM provider and complete only those steps:
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<Tabs groupId="Provider">
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<TabItem value="OpenAI" label="OpenAI" default>
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1. Enable **Get API key from environment variable** to automatically enter your key from the TUI-generated `.env` file.
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@ -3,25 +3,24 @@ title: Install with Docker
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slug: /get-started/docker
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---
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import Tabs from '@theme/Tabs';
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import TabItem from '@theme/TabItem';
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import PartialOnboarding from '@site/docs/_partial-onboarding.mdx';
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There are two different Docker Compose files.
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They deploy the same applications and containers locally, but to different environments.
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OpenRAG has two Docker Compose files. Both files deploy the same applications and containers locally, but they are for 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.yml`](https://github.com/langflow-ai/openrag/blob/main/docker-compose.yml) is an OpenRAG deployment with GPU support for accelerated AI processing. This Docker Compose file requires an NVIDIA GPU with [CUDA](https://docs.nvidia.com/cuda/) support.
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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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Both Docker deployments depend on `docling serve` to be running on port `5001` on the host machine. This enables [Mac MLX](https://opensource.apple.com/projects/mlx/) support for document processing. Installing OpenRAG with the TUI starts `docling serve` automatically, but for a Docker deployment you must manually start the `docling serve` process.
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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 NVIDIA GPU support. Use this Docker Compose file for environments where GPU drivers aren't available.
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## Prerequisites
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- [Python Version 3.10 to 3.13](https://www.python.org/downloads/release/python-3100/)
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- [uv](https://docs.astral.sh/uv/getting-started/installation/)
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- [Podman](https://podman.io/docs/installation) (recommended) or [Docker](https://docs.docker.com/get-docker/) installed
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- [Docker Compose](https://docs.docker.com/compose/install/) installed. If you're using Podman, use [podman-compose](https://docs.podman.io/en/latest/markdown/podman-compose.1.html) or alias Docker compose commands to Podman commands.
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- Install [Python Version 3.10 to 3.13](https://www.python.org/downloads/release/python-3100/)
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- Install [uv](https://docs.astral.sh/uv/getting-started/installation/)
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- Install [Podman](https://podman.io/docs/installation) (recommended) or [Docker](https://docs.docker.com/get-docker/)
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- Install [Docker Compose](https://docs.docker.com/compose/install/). If using Podman, use [podman-compose](https://docs.podman.io/en/latest/markdown/podman-compose.1.html) or alias Docker compose commands to Podman commands.
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- Create an [OpenAI API key](https://platform.openai.com/api-keys). This key is **required** to start OpenRAG, but you can choose a different model provider during [Application Onboarding](#application-onboarding).
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- Optional: GPU support requires an NVIDIA GPU with CUDA support and compatible NVIDIA drivers installed on the OpenRAG host machine. If you don't have GPU capabilities, OpenRAG provides an alternate CPU-only deployment.
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- Optional: Install GPU support with an NVIDIA GPU, [CUDA](https://docs.nvidia.com/cuda/) support, and compatible NVIDIA drivers on the OpenRAG host machine. If you don't have GPU capabilities, OpenRAG provides an alternate CPU-only deployment.
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## Install OpenRAG with Docker Compose
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@ -49,8 +48,7 @@ To install OpenRAG with Docker Compose, do the following:
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touch .env
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```
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4. Set environment variables. The Docker Compose files will be populated with values from your `.env`.
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The following values are **required** to be set:
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4. The Docker Compose files are populated with the values from your .env. The following values must be set:
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```bash
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OPENSEARCH_PASSWORD=your_secure_password
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@ -63,7 +61,8 @@ The following values are **required** to be set:
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For more information on configuring OpenRAG with environment variables, see [Environment variables](/reference/configuration).
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5. Start `docling serve` on the host machine.
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Both Docker deployments depend on `docling serve` to be running on port `5001` on the host machine. This enables [Mac MLX](https://opensource.apple.com/projects/mlx/) support for document processing.
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OpenRAG Docker installations require that `docling serve` is running on port 5001 on the host machine.
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This enables [Mac MLX](https://opensource.apple.com/projects/mlx/) support for document processing.
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```bash
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uv run python scripts/docling_ctl.py start --port 5001
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@ -74,7 +73,7 @@ The following values are **required** to be set:
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uv run python scripts/docling_ctl.py status
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```
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Successful result:
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Make sure the response shows that `docling serve` is running, for example:
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```bash
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Status: running
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Endpoint: http://127.0.0.1:5001
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@ -84,16 +83,21 @@ The following values are **required** to be set:
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7. Deploy OpenRAG locally with Docker Compose based on your deployment type.
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For GPU-enabled systems, run the following commands:
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<Tabs groupId="Compose file">
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<TabItem value="docker-compose.yml" label="docker-compose.yml" default>
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```bash
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docker compose build
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docker compose up -d
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```
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For environments without GPU support, run:
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```
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</TabItem>
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<TabItem value="docker-compose-cpu.yml" label="docker-compose-cpu.yml">
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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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</TabItem>
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</Tabs>
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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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@ -110,7 +114,7 @@ The following values are **required** to be set:
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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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You can now access OpenRAG at the following endpoints:
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- **Frontend**: http://localhost:3000
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- **Backend API**: http://localhost:8000
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