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layout default
title Chapter 7: Benchmarking, Evaluation, and Quality Gates
nav_order 7
parent AutoAgent Tutorial

Chapter 7: Benchmarking, Evaluation, and Quality Gates

Welcome to Chapter 7: Benchmarking, Evaluation, and Quality Gates. In this part of AutoAgent Tutorial: Zero-Code Agent Creation and Automated Workflow Orchestration, you will build an intuitive mental model first, then move into concrete implementation details and practical production tradeoffs.

This chapter focuses on evaluation rigor for AutoAgent outputs.

Learning Goals

  • align evaluation goals with benchmark constraints
  • interpret benchmark claims and reproduction boundaries
  • define pass/fail criteria for internal tasks
  • prevent quality regressions over iterative updates

Evaluation Guidance

  • benchmark on representative scenarios, not only demos
  • include cost/latency/accuracy tradeoff reporting
  • gate production rollouts on repeatable evaluation passes

Source References

Summary

You now have an evaluation loop for safer AutoAgent evolution.

Next: Chapter 8: Contribution Workflow and Production Governance

Depth Expansion Playbook

Source Code Walkthrough

autoagent/server.py

The AgentResponse class in autoagent/server.py handles a key part of this chapter's functionality:

    content: str

class AgentResponse(BaseModel):
    result: str
    messages: List
    agent_name: str
# 为所有注册的tools创建endpoints
@app.on_event("startup")
def create_tool_endpoints():
    for tool_name, tool_func in registry.tools.items():
        # 创建动态的POST endpoint
        async def create_tool_endpoint(request: ToolRequest, func=tool_func):
            try:
                # 检查必需参数
                sig = inspect.signature(func)
                required_params = {
                    name for name, param in sig.parameters.items()
                    if param.default == inspect.Parameter.empty
                }
                
                # 验证是否提供了所有必需参数
                if not all(param in request.args for param in required_params):
                    missing = required_params - request.args.keys()
                    raise HTTPException(
                        status_code=400,
                        detail=f"Missing required parameters: {missing}"
                    )
                
                result = func(**request.args)
                return {"status": "success", "result": result}
            except Exception as e:
                raise HTTPException(status_code=400, detail=str(e))

This class is important because it defines how AutoAgent Tutorial: Zero-Code Agent Creation and Automated Workflow Orchestration implements the patterns covered in this chapter.

autoagent/server.py

The lifespan function in autoagent/server.py handles a key part of this chapter's functionality:

import inspect

# 定义lifespan上下文管理器
@asynccontextmanager
async def lifespan(app: FastAPI):
    # 启动时执行
    await create_agent_endpoints(app)
    yield
    # 关闭时执行
    # 清理代码（如果需要）

app = FastAPI(title="MetaChain API", lifespan=lifespan)

class ToolRequest(BaseModel):
    args: Dict[str, Any]

class AgentRequest(BaseModel):
    model: str
    query: str
    context_variables: Optional[Dict[str, Any]] = {}

class Message(BaseModel):
    role: str
    content: str

class AgentResponse(BaseModel):
    result: str
    messages: List
    agent_name: str
# 为所有注册的tools创建endpoints
@app.on_event("startup")
def create_tool_endpoints():

This function is important because it defines how AutoAgent Tutorial: Zero-Code Agent Creation and Automated Workflow Orchestration implements the patterns covered in this chapter.

autoagent/server.py

The create_tool_endpoints function in autoagent/server.py handles a key part of this chapter's functionality:

# 为所有注册的tools创建endpoints
@app.on_event("startup")
def create_tool_endpoints():
    for tool_name, tool_func in registry.tools.items():
        # 创建动态的POST endpoint
        async def create_tool_endpoint(request: ToolRequest, func=tool_func):
            try:
                # 检查必需参数
                sig = inspect.signature(func)
                required_params = {
                    name for name, param in sig.parameters.items()
                    if param.default == inspect.Parameter.empty
                }
                
                # 验证是否提供了所有必需参数
                if not all(param in request.args for param in required_params):
                    missing = required_params - request.args.keys()
                    raise HTTPException(
                        status_code=400,
                        detail=f"Missing required parameters: {missing}"
                    )
                
                result = func(**request.args)
                return {"status": "success", "result": result}
            except Exception as e:
                raise HTTPException(status_code=400, detail=str(e))
        
        # 添加endpoint到FastAPI应用
        endpoint = create_tool_endpoint
        endpoint.__name__ = f"tool_{tool_name}"
        app.post(f"/tools/{tool_name}")(endpoint)
# 重写agent endpoints创建逻辑

This function is important because it defines how AutoAgent Tutorial: Zero-Code Agent Creation and Automated Workflow Orchestration implements the patterns covered in this chapter.

autoagent/server.py

The create_agent_endpoints function in autoagent/server.py handles a key part of this chapter's functionality:

async def lifespan(app: FastAPI):
    # 启动时执行
    await create_agent_endpoints(app)
    yield
    # 关闭时执行
    # 清理代码（如果需要）

app = FastAPI(title="MetaChain API", lifespan=lifespan)

class ToolRequest(BaseModel):
    args: Dict[str, Any]

class AgentRequest(BaseModel):
    model: str
    query: str
    context_variables: Optional[Dict[str, Any]] = {}

class Message(BaseModel):
    role: str
    content: str

class AgentResponse(BaseModel):
    result: str
    messages: List
    agent_name: str
# 为所有注册的tools创建endpoints
@app.on_event("startup")
def create_tool_endpoints():
    for tool_name, tool_func in registry.tools.items():
        # 创建动态的POST endpoint
        async def create_tool_endpoint(request: ToolRequest, func=tool_func):
            try:

This function is important because it defines how AutoAgent Tutorial: Zero-Code Agent Creation and Automated Workflow Orchestration implements the patterns covered in this chapter.

How These Components Connect

flowchart TD
    A[AgentResponse]
    B[lifespan]
    C[create_tool_endpoints]
    D[create_agent_endpoints]
    E[list_agents]
    A --> B
    B --> C
    C --> D
    D --> E
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