docs: Add comprehensive Azure OpenAI configuration documentation (#837)
* docs: Add comprehensive Azure OpenAI configuration documentation - Add detailed Azure OpenAI configuration section with prerequisites, authentication, and setup options - Include both global and per-model baseURL configuration examples - Add comprehensive troubleshooting guide for common Azure OpenAI issues - Update environment variables section with Azure OpenAI examples - Add Azure OpenAI models to all model tables (Main, Research, Fallback) - Include prominent Azure configuration example in main documentation - Fix azureBaseURL format to use correct Azure OpenAI endpoint structure Addresses common Azure OpenAI setup challenges and provides clear guidance for new users. * refactor: Move Azure models from docs/models.md to scripts/modules/supported-models.json - Remove Azure model entries from documentation tables - Add Azure provider section to supported-models.json with gpt-4o, gpt-4o-mini, and gpt-4-1 - Maintain consistency with existing model configuration structure
This commit is contained in:
Jitesh Thakur
@@ -41,13 +41,14 @@ Taskmaster uses two primary methods for configuration:
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"defaultTag": "master",
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"projectName": "Your Project Name",
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"ollamaBaseURL": "http://localhost:11434/api",
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"azureBaseURL": "https://your-endpoint.azure.com/",
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"azureBaseURL": "https://your-endpoint.azure.com/openai/deployments",
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"vertexProjectId": "your-gcp-project-id",
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"vertexLocation": "us-central1"
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}
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}
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```
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2. **Legacy `.taskmasterconfig` File (Backward Compatibility)**
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- For projects that haven't migrated to the new structure yet.
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@@ -129,13 +130,15 @@ ANTHROPIC_API_KEY=sk-ant-api03-your-key-here
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PERPLEXITY_API_KEY=pplx-your-key-here
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# OPENAI_API_KEY=sk-your-key-here
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# GOOGLE_API_KEY=AIzaSy...
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# AZURE_OPENAI_API_KEY=your-azure-openai-api-key-here
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# etc.
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# Optional Endpoint Overrides
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# Use a specific provider's base URL, e.g., for an OpenAI-compatible API
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# OPENAI_BASE_URL=https://api.third-party.com/v1
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#
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# AZURE_OPENAI_ENDPOINT=https://your-azure-endpoint.openai.azure.com/
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# Azure OpenAI Configuration
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# AZURE_OPENAI_ENDPOINT=https://your-resource-name.openai.azure.com/ or https://your-endpoint-name.cognitiveservices.azure.com/openai/deployments
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# OLLAMA_BASE_URL=http://custom-ollama-host:11434/api
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# Google Vertex AI Configuration (Required if using 'vertex' provider)
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@@ -207,3 +210,104 @@ Google Vertex AI is Google Cloud's enterprise AI platform and requires specific
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"vertexLocation": "us-central1"
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}
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```
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### Azure OpenAI Configuration
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Azure OpenAI provides enterprise-grade OpenAI models through Microsoft's Azure cloud platform and requires specific configuration:
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1. **Prerequisites**:
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- An Azure account with an active subscription
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- Azure OpenAI service resource created in the Azure portal
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- Azure OpenAI API key and endpoint URL
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- Deployed models (e.g., gpt-4o, gpt-4o-mini, gpt-4.1, etc) in your Azure OpenAI resource
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2. **Authentication**:
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- Set the `AZURE_OPENAI_API_KEY` environment variable with your Azure OpenAI API key
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- Configure the endpoint URL using one of the methods below
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3. **Configuration Options**:
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**Option 1: Using Global Azure Base URL (affects all Azure models)**
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```json
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// In .taskmaster/config.json
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{
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"models": {
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"main": {
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"provider": "azure",
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"modelId": "gpt-4o",
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"maxTokens": 16000,
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"temperature": 0.7
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},
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"fallback": {
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"provider": "azure",
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"modelId": "gpt-4o-mini",
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"maxTokens": 10000,
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"temperature": 0.7
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}
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},
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"global": {
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"azureBaseURL": "https://your-resource-name.azure.com/openai/deployments"
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}
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}
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```
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**Option 2: Using Per-Model Base URLs (recommended for flexibility)**
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```json
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// In .taskmaster/config.json
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{
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"models": {
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"main": {
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"provider": "azure",
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"modelId": "gpt-4o",
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"maxTokens": 16000,
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"temperature": 0.7,
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"baseURL": "https://your-resource-name.azure.com/openai/deployments"
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},
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"research": {
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"provider": "perplexity",
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"modelId": "sonar-pro",
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"maxTokens": 8700,
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"temperature": 0.1
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},
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"fallback": {
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"provider": "azure",
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"modelId": "gpt-4o-mini",
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"maxTokens": 10000,
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"temperature": 0.7,
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"baseURL": "https://your-resource-name.azure.com/openai/deployments"
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}
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}
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}
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```
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4. **Environment Variables**:
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```bash
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# In .env file
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AZURE_OPENAI_API_KEY=your-azure-openai-api-key-here
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# Optional: Override endpoint for all Azure models
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AZURE_OPENAI_ENDPOINT=https://your-resource-name.azure.com/openai/deployments
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```
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5. **Important Notes**:
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- **Model Deployment Names**: The `modelId` in your configuration should match the **deployment name** you created in Azure OpenAI Studio, not the underlying model name
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- **Base URL Priority**: Per-model `baseURL` settings override the global `azureBaseURL` setting
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- **Endpoint Format**: When using per-model `baseURL`, use the full path including `/openai/deployments`
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6. **Troubleshooting**:
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**"Resource not found" errors:**
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- Ensure your `baseURL` includes the full path: `https://your-resource-name.openai.azure.com/openai/deployments`
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- Verify that your deployment name in `modelId` exactly matches what's configured in Azure OpenAI Studio
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- Check that your Azure OpenAI resource is in the correct region and properly deployed
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**Authentication errors:**
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- Verify your `AZURE_OPENAI_API_KEY` is correct and has not expired
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- Ensure your Azure OpenAI resource has the necessary permissions
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- Check that your subscription has not been suspended or reached quota limits
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**Model availability errors:**
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- Confirm the model is deployed in your Azure OpenAI resource
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- Verify the deployment name matches your configuration exactly (case-sensitive)
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- Ensure the model deployment is in a "Succeeded" state in Azure OpenAI Studio
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- Ensure youre not getting rate limited by `maxTokens` maintain appropriate Tokens per Minute Rate Limit (TPM) in your deployment.
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