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| 1 | +--- |
| 2 | +title: Use Docker Model |
| 3 | +description: Learn how to integrate Docker Model Runner with Docker Compose to build AI-powered applications |
| 4 | +keywords: compose, docker compose, model runner, ai, llm, artificial intelligence, machine learning |
| 5 | +weight: 111 |
| 6 | +params: |
| 7 | + sidebar: |
| 8 | + badge: |
| 9 | + color: green |
| 10 | + text: New |
| 11 | +--- |
| 12 | + |
| 13 | +{{< summary-bar feature_name="Compose model runner" >}} |
| 14 | + |
| 15 | +Docker Model Runner can be integrated with Docker Compose to run AI models as part of your multi-container applications. |
| 16 | +This allows you to define and run AI-powered applications alongside your other services. |
| 17 | + |
| 18 | +## Prerequisites |
| 19 | + |
| 20 | +- Docker Compose v2.35 or later |
| 21 | +- Docker Desktop 4.41 or later |
| 22 | +- Docker Model Runner enabled in Docker Desktop |
| 23 | +- Apple Silicon Mac (currently Model Runner is only available for Mac with Apple Silicon) |
| 24 | + |
| 25 | +## Enabling Docker Model Runner |
| 26 | + |
| 27 | +Before you can use Docker Model Runner with Compose, you need to enable it in Docker Desktop, as described in the [Docker Model Runner documentation](/desktop/features/model-runner/). |
| 28 | + |
| 29 | +## Provider services |
| 30 | + |
| 31 | +Compose introduces a new service type called `provider` that allows you to declare platform capabilities required by your application. For AI models, you can use the `model` type to declare model dependencies. |
| 32 | + |
| 33 | +Here's an example of how to define a model provider: |
| 34 | + |
| 35 | +```yaml |
| 36 | +services: |
| 37 | + chat: |
| 38 | + image: my-chat-app |
| 39 | + depends_on: |
| 40 | + - ai-runner |
| 41 | + |
| 42 | + ai-runner: |
| 43 | + provider: |
| 44 | + type: model |
| 45 | + options: |
| 46 | + model: ai/smollm2 |
| 47 | +``` |
| 48 | +
|
| 49 | +You should notice the dedicated `provider` attribute in the `ai-runner` service. |
| 50 | +This attribute specifies that the service is a model provider and let you define options such as the name of the model to be used. |
| 51 | + |
| 52 | +There is also a `depends_on` attribute in the `chat` service. |
| 53 | +This attribute specifies that the `chat` service depends on the `ai-runner` service. |
| 54 | +This means that the `ai-runner` service will be started before the `chat` service to allow injection of model information to the `chat` service. |
| 55 | + |
| 56 | +## How it works |
| 57 | + |
| 58 | +During the `docker compose up` process, Docker Model Runner will automatically pull and run the specified model. |
| 59 | +It will also send to Compose the model tag name and the URL to access the model runner. |
| 60 | + |
| 61 | +Those information will be then pass to services which declare a dependency on the model provider. |
| 62 | +In the example above, the `chat` service will receive 2 env variables prefixed by the service name: |
| 63 | + - `AI-RUNNER_URL` with the URL to access the model runner |
| 64 | + - `AI-RUNNER_MODEL` with the model name which could be passed with the URL to request the model. |
| 65 | + |
| 66 | +This allows the `chat` service to interact with the model and use it for its own purposes. |
| 67 | + |
| 68 | + |
| 69 | +## Reference |
| 70 | + |
| 71 | +- [Docker Model Runner documentation](desktop/features/model-runner/) |
| 72 | + |
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