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[Feature] Server-side multi-provider/model support (#583)

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* [Feature] Server side multi-pvorider/model support

* copilot suggesition implemented

* feat: improve model selector UI and auto-select default server model

- Replace emoji headers with Lucide icons (Monitor, User)
- Fix transition-all to explicit properties per web guidelines
- Use CSS padding instead of hardcoded space indentation
- Add ModelSelectorSectionHeader component for section headers
- Replace Star icon with "default" text label
- Style Configure button with muted text color
- Auto-select default server model when page loads
- Support AI_MODELS_CONFIG env var for cloud deployments
- Support custom apiKeyEnv/baseUrlEnv per provider config

* docs: update server-side multi-model configuration documentation

- Add AI_MODELS_CONFIG env var option for cloud deployments
- Document apiKeyEnv and baseUrlEnv fields for custom env var names
- Document default field for auto-selecting default model
- Remove deprecated version field from examples
- Add field reference table for clarity

---------

Co-authored-by: dayuan.jiang <jdy.toh@gmail.com>
This commit is contained in:
Biki Kalita
2026-01-15 21:28:22 +05:30
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parent b128c57e94
commit b23b9179a0
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docs/en/docker.md
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@@ -22,6 +22,27 @@ cp env.example .env
docker run -d -p 3000:3000 --env-file .env ghcr.io/dayuanjiang/next-ai-draw-io:latest
```
### Using server-side model configuration
You can mount an `ai-models.json` file into the container to provide multiple server-side models without exposing user API keys:
```bash
docker run -d -p 3000:3000 \
-e OPENAI_API_KEY=your_api_key \
-v $(pwd)/ai-models.json:/app/ai-models.json:ro \
ghcr.io/dayuanjiang/next-ai-draw-io:latest
```
If you prefer to keep the config in a different path inside the container, set `AI_MODELS_CONFIG_PATH`:
```bash
docker run -d -p 3000:3000 \
-e OPENAI_API_KEY=your_api_key \
-e AI_MODELS_CONFIG_PATH=/config/ai-models.json \
-v $(pwd)/ai-models.json:/config/ai-models.json:ro \
ghcr.io/dayuanjiang/next-ai-draw-io:latest
```
Open [http://localhost:3000](http://localhost:3000) in your browser.
Replace the environment variables with your preferred AI provider configuration. See [AI Providers](./ai-providers.md) for available options.