azure/foundry-agent (Azure AI Foundry Agent)

This example demonstrates how to use the Azure Foundry Agent provider with promptfoo. This provider uses the @azure/ai-projects SDK and the v2 Responses agent runtime instead of the old threads/runs API.

You can run this example with:

npx promptfoo@latest init --example azure/foundry-agent
cd azure/foundry-agent

Setup

1. Install the required Azure SDK packages:

npm install @azure/ai-projects @azure/identity

2. Set up your Azure credentials. The provider uses DefaultAzureCredential, so you can authenticate via:

   • Azure CLI: az login
   • Environment variables
   • Managed Identity
   • Service Principal

3. Set your Azure AI Project URL:

export AZURE_AI_PROJECT_URL="https://your-project.services.ai.azure.com/api/projects/your-project-id"

Configuration

The provider uses the azure:foundry-agent:agent-name-or-id format. Agent names are preferred. Legacy agent IDs still work as a fallback lookup if the agent exists in the project.

providers:
  - id: azure:foundry-agent:my-foundry-agent
    config:
      projectUrl: 'https://your-project.services.ai.azure.com/api/projects/your-project-id'
      temperature: 0.7
      max_tokens: 150

tests:
  - vars:
      question: 'What is the capital of France?'
    assert:
      - type: contains
        value: 'Paris'

Configuration Options

These per-request settings are supported:

• instructions
• temperature
• top_p
• max_tokens / max_completion_tokens (mapped to max_output_tokens)
• response_format
• tools
• tool_choice
• functionToolCallbacks
• modelName
• reasoning_effort
• verbosity
• metadata
• passthrough
• maxPollTimeMs

These request-time settings are ignored by the v2 runtime and should be configured on the Foundry agent instead:

• tool_resources
• frequency_penalty
• presence_penalty
• seed
• stop
• timeoutMs
• retryOptions

Function Tool Callbacks

You can provide custom function callbacks just like with the regular Azure Assistant provider:

providers:
  - id: azure:foundry-agent:my-foundry-agent
    config:
      projectUrl: 'https://your-project.services.ai.azure.com/api/projects/your-project-id'
      functionToolCallbacks:
        getCurrentWeather: |
          (args) => {
            const { location } = JSON.parse(args);
            return `The weather in ${location} is sunny and 75°F`;
          }

Differences from Regular Azure Assistant Provider

The main differences are:

1. SDK Usage: Uses @azure/ai-projects SDK instead of direct HTTP calls
2. Authentication: Uses DefaultAzureCredential for Azure authentication
3. Project URL: Requires an Azure AI Project URL instead of Azure OpenAI endpoint
4. Provider Format: Uses azure:foundry-agent:agent-name-or-id instead of azure:assistant:assistant-id
5. Runtime: Uses responses.create(..., agent_reference) instead of threads/messages/runs

Environment Variables

• AZURE_AI_PROJECT_URL: Your Azure AI Project URL (can be overridden in config)
• Standard Azure credential environment variables (if not using other auth methods)

Error Handling

The provider includes the same comprehensive error handling as the regular Azure Assistant provider:

• Content filter detection and guardrails reporting
• Rate limit handling
• Service error detection
• Automatic retries for transient errors