FoundryEvals将 Agent Framework 评估 API 连接到 Microsoft Foundry 的托管评估服务。 它提供质量、安全、工具使用、代理行为和标准评估程序，以及 Foundry 门户中提供的存储报表。
有关 EvalItem本地检查、自定义计算器和聊天拆分策略，请参阅 代理评估。
先决条件
- Microsoft Foundry 项目和模型部署。
- 项目范围的 Foundry 终结点。
- 提交评估和读取报表的权限。
评估响应或测试查询
配置 FoundryEvals，然后评估已生成的响应，或让 EvaluateAsync 为每个查询运行代理。
string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-4o-mini";
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
AIProjectClient projectClient = new(new Uri(endpoint), new DefaultAzureCredential());
AIAgent agent = projectClient.AsAIAgent(
model: deploymentName,
instructions: "You are a helpful assistant that provides clear, accurate answers.",
name: "QualityTestAgent");
// Configure Foundry evaluators.
FoundryEvals foundryEvals = new(projectClient, deploymentName, FoundryEvals.Relevance, FoundryEvals.Coherence);
// --- Pattern 1: Run agent, then evaluate pre-existing responses ---
string[] queries = ["What is photosynthesis?", "Explain gravity in simple terms."];
AgentResponse[] responses = new AgentResponse[queries.Length];
for (int i = 0; i < queries.Length; i++)
{
responses[i] = await agent.RunAsync(queries[i]);
}
AgentEvaluationResults results1 = await agent.EvaluateAsync(responses, queries, foundryEvals);
Console.WriteLine("=== Pattern 1: Evaluate pre-existing responses ===");
PrintResults(results1, queries);
// --- Pattern 2: Run + evaluate in one call ---
string[] queries2 = ["What causes rain?", "Why is the sky blue?"];
AgentEvaluationResults results2 = await agent.EvaluateAsync(queries2, foundryEvals);
Console.WriteLine("=== Pattern 2: Run + evaluate in one call ===");
PrintResults(results2, queries2);
.NET示例还演示了 Foundry 标准评估器和每维度质量门。
评估代理
将现有响应或测试查询传递给 evaluate_agent()。 结果包括传递/失败计数和 Foundry 报告 URL。
async def main() -> None:
# 1. Set up the FoundryChatClient
chat_client = FoundryChatClient(
project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
model=os.environ.get("FOUNDRY_MODEL", "gpt-4o"),
credential=AzureCliCredential(),
)
# 2. Create an agent with tools
agent = Agent(
client=chat_client,
name="travel-assistant",
instructions=(
"You are a helpful travel assistant. Use your tools to answer questions about weather and flights."
),
tools=[get_weather, get_flight_price],
)
# 3. Create the evaluator — provider config goes here, once
evals = FoundryEvals(client=chat_client)
# =========================================================================
# Pattern 1: evaluate_agent(responses=...) — evaluate a response you already have
# =========================================================================
print("=" * 60)
print("Pattern 1: evaluate_agent(responses=...) — evaluate existing response")
print("=" * 60)
query = "How much does a flight from Seattle to Paris cost?"
response = await agent.run(query)
print(f"Agent said: {response.text[:100]}...")
# Pass agent= so tool definitions are extracted, queries= for the eval item context
results = await evaluate_agent(
agent=agent,
responses=response,
queries=[query],
evaluators=FoundryEvals(
client=chat_client,
evaluators=[FoundryEvals.RELEVANCE, FoundryEvals.TOOL_CALL_ACCURACY],
),
)
for r in results:
print(f"Status: {r.status}")
print(f"Results: {r.passed}/{r.total} passed")
print(f"Portal: {r.report_url}")
if r.all_passed:
print("[PASS] All passed")
else:
print(f"[FAIL] {r.failed} failed")
其他示例包括跟踪评估、工具调用评估、多轮评估、工作流评估、混合提供程序和自定义 Foundry 标准。
注释
Microsoft Foundry 评估集成目前不适用于 Agent Framework Go。 有关最新状态，请参阅 Agent Framework Go 存储库 。
质量控制点
当结果必须在运行中可比较时，固定数据集、模型部署、计算器版本和量规版本。 当所需的指标回归时，使用结果断言帮助程序来失败 CI。