Add provider model docs

docs/concepts/managed-llms/managed-language-models.md

@@ -1,5 +1,5 @@
 ---
-title: Leveraging Managed Language Models with Defang
+title: Using Managed LLMs
 description: Defang makes it easy to leverage cloud-native managed language models.
 sidebar_position: 3000
 ---
@@ -32,7 +32,7 @@ If you already have an OpenAI-compatible application, Defang makes it easy to de
 
 | Provider | Managed Language Models |
 | --- | --- |
-| [Playground](/docs/providers/playground#managed-large-language-models) | ❌ |
+| [Playground](/docs/providers/playground#managed-large-language-models) | ✅ |
 | [AWS Bedrock](/docs/providers/aws#managed-large-language-models) | ✅ |
 | [DigitalOcean GenAI](/docs/providers/digitalocean#future-improvements) | ❌ |
 | [GCP Vertex AI](/docs/providers/gcp#managed-large-language-models) | ✅ |

docs/concepts/managed-llms/openai-access-gateway.md

@@ -1,20 +1,44 @@
 ---
-title: Deploying OpenAI-compatible apps with Defang
+title: OpenAI Access Gateway
 description: Defang makes it easy to leverage cloud-native managed language models for your OpenAI-compatible application.
 sidebar_position: 3000
 ---
 
-# Deploying OpenAI-compatible applications to cloud-native managed language models with Defang
+# OpenAI Access Gateway
 
-Defang makes it easy to deploy on your favourite cloud's managed LLM service with our [OpenAI Access Gateway](https://github.com/DefangLabs/openai-access-gateway). This service sits between your application and the cloud service and acts as a compatibility layer. It handles incoming OpenAI requests, translates those requests to the appropriate cloud-native API, handles the native response, and re-constructs an OpenAI-compatible response.
+Defang makes it easy to deploy on your favourite cloud's managed LLM service with our [OpenAI Access Gateway](https://github.com/DefangLabs/openai-access-gateway). This service sits between your application and the cloud service and acts as a compatibility layer.
+It handles incoming OpenAI requests, translates those requests to the appropriate cloud-native API, handles the native response, and re-constructs an OpenAI-compatible response.
 
 See [our tutorial](/docs/tutorials/deploying-openai-apps-aws-bedrock-gcp-vertex/) which describes how to configure the OpenAI Access Gateway for your application
 
+## Docker Provider Services
+
+As of Docker Compose v2.35 and Docker Desktop v4.41, Compose introduces a new service type called `provider` that allows you to declare platform capabilities required by your application.
+For AI models, you use the `model` type to declare model dependencies. This will expose an OpenAI compatible API for your service. Check the [Docker Model Runner documentation](https://docs.docker.com/compose/how-tos/model-runner/) for more details.
+
+```yaml
+services:
+  chat:
+    build: .
+    depends_on:
+      - ai_runner
+
+  ai_runner:
+    provider:
+      type: model
+      options:
+        model: ai/mistral
+    x-defang-llm: true
+```
+
+Under the hood, when you use the `model` provider, Defang will deploy the **OpenAI Access Gateway** in a private network. This allows you to use the same code for both local development and cloud deployment.
+The `x-defang-llm` extension is used to configure the appropriate roles and permissions for your service. See the [Managed Language Models](/docs/concepts/managed-llms/managed-language-models/) page for more details.
+
 ## Current Support
 
 | Provider | Managed Language Models |
 | --- | --- |
-| [Playground](/docs/providers/playground#managed-services) | ❌ |
+| [Playground](/docs/providers/playground#managed-services) | ✅ |
 | [AWS Bedrock](/docs/providers/aws#managed-llms) | ✅ |
 | [DigitalOcean GenAI](/docs/providers/digitalocean#future-improvements) | ❌ |
 | [GCP Vertex AI](/docs/providers/gcp#managed-llms) | ✅ |