chore: import upstream snapshot with attribution
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# azure/openai (Azure OpenAI)
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This example demonstrates how to use Azure OpenAI with promptfoo, including text generation and vision capabilities.
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You can run this example with:
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```bash
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npx promptfoo@latest init --example azure/openai
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cd azure/openai
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```
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## Environment Variables
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This example requires the following environment variables:
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- `AZURE_API_KEY` - Your Azure OpenAI API key
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- `AZURE_OPENAI_API_KEY` - Alternative environment variable for your Azure OpenAI API key
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You can set these in a `.env` file or directly in your environment.
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## Prerequisites
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1. An Azure account with access to Azure OpenAI Service
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2. Deployments for one or more Azure OpenAI models:
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- Text models: gpt-5.1, gpt-4o
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- Vision models: gpt-4o (or other vision-capable models)
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3. Your Azure OpenAI endpoint URL
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## Setup Instructions
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1. Update the `apiHost` in the configuration files to your Azure OpenAI endpoint
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2. Set `AZURE_API_KEY` in your environment
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3. Update the deployment names to match your actual deployments
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## Available Examples
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### Basic Text Generation
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```bash
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npx promptfoo@latest eval
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# or
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npx promptfoo@latest eval -c promptfooconfig.yaml
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```
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### Vision Models
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```bash
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npx promptfoo@latest eval -c promptfooconfig.vision.yaml
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```
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Demonstrates three ways to provide images to vision models:
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- **URL**: Direct link to an image on the web
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- **Local file**: Using `file://` paths (automatically converted to base64)
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- **Base64**: Pre-encoded image data URI
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## Troubleshooting
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If you get a 401 error:
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- Ensure your `AZURE_API_KEY` is set correctly
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- Verify your endpoint URL is correct (no https://)
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- Check that your deployment supports the requested capabilities
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## Additional Resources
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- [Azure OpenAI Provider Documentation](https://promptfoo.dev/docs/providers/azure/)
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- [Azure OpenAI Service Documentation](https://learn.microsoft.com/en-us/azure/ai-services/openai/)
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- [Azure OpenAI Vision Documentation](https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/gpt-with-vision)
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[
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{
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"role": "user",
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"content": [
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{
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"type": "text",
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"text": "{{question}}"
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},
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{
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"type": "image_url",
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"image_url": {
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"url": "{{image_url}}"
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}
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}
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]
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}
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]
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# yaml-language-server: $schema=https://promptfoo.dev/config-schema.json
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description: Azure OpenAI vision model evaluation
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prompts:
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# Vision models require a specific message format with content arrays
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- file://prompt.vision.json
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providers:
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# Update with your Azure OpenAI deployment details
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- id: azure:chat:gpt-5
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config:
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apiHost: promptfoo.openai.azure.com
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apiVersion: 2024-02-15-preview
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temperature: 0.1
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max_tokens: 500
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tests:
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# Test 2: Load image from local file (automatically converted to base64 with data URL)
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- vars:
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question: What color is the planet in this image?
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image_url: file://assets/earth.jpg
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assert:
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- type: contains-any
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value: [blue, green]
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# Note: If you see 401 errors, ensure:
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# 1. Your AZURE_API_KEY environment variable is set correctly
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# 2. The apiHost matches your Azure OpenAI resource name
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# 3. Your deployment supports vision (GPT-5.1, GPT-4o, GPT-4.1)
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# yaml-language-server: $schema=https://promptfoo.dev/config-schema.json
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description: Azure OpenAI chat and embeddings with fact generation
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prompts:
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- 'Generate one very interesting fact about {{topic}}'
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providers:
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# GPT-5.1 - Latest flagship model
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- id: azure:chat:gpt-5.1
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config:
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apiHost: 'your-org.openai.azure.com'
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defaultTest:
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assert:
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- type: latency
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threshold: 3000
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tests:
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- vars:
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topic: monkeys
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- vars:
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topic: bananas
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assert:
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- type: similar
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value: Bananas are naturally radioactive.
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provider:
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id: azure:embeddings:text-embedding-3-large
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config:
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apiHost: 'your-org.openai.azure.com'
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