Multi-Agent质量工程：涌现测试与级联阻断实测全账

from maseval import MASEvalRunner, BenchmarkConfig

config = BenchmarkConfig(
    frameworks=["langgraph", "crewai", "ag2"],
    models=["gpt-4o", "claude-sonnet-4-20250514"],
    benchmarks=["alpaca_eval", "tool_usage", "reasoning"],
    metrics=["success_rate", "token_efficiency", "latency"]
)

runner = MASEvalRunner(config)
results = runner.run()  # 输出跨框架对比报告
# 关键发现：框架A在推理任务上+12%，框架B在工具任务上+8%

Agent A产生幻觉 → 幻觉输出作为Agent B的输入 → 
B基于错误前提推理 → B的输出放大了原始错误 →
C接收放大后的错误 → 级联完成

class ConfidenceGatedAgent:
    def __init__(self, threshold=0.75):
        self.threshold = threshold

    async def run(self, task):
        result = await self.llm.generate(task)
        confidence = await self.assess_confidence(result)

        if confidence < self.threshold:
            # 触发验证子流程而非直接传递
            verified = await self.verify_with_sources(result)
            if verified.confidence > self.threshold:
                return verified
            return VerificationNeeded(result, confidence)
        return result

async def cross_validated_decision(task, agent_a, agent_b, arbiter):
    result_a = await agent_a.run(task)
    result_b = await agent_b.run(task)

    if semantic_similarity(result_a, result_b) > 0.85:
        return merge_results(result_a, result_b)

    # 不一致时由仲裁Agent裁决
    return await arbiter.run(
        f"Agent A says: {result_a}\nAgent B says: {result_b}\nResolve."
    )

graph TB
    subgraph L1["第一层：基础设施故障"]
        A1[API超时] --> A2[速率限制触发]
        A3[网络分区] --> A4[存储不可用]
    end

    subgraph L2["第二层：模型层故障"]
        B1[幻觉输出] --> B2[格式违规]
        B3[上下文溢出] --> B4[安全越狱]
    end

    subgraph L3["第三层：编排层故障"]
        C1[Agent死锁] --> C2[无限循环]
        C3[消息丢失] --> C4[状态不一致]
    end

    subgraph L4["第四层：语义层故障"]
        D1[目标漂移] --> D2[协议误解]
        D3[权限泄漏] --> D4[涌现失控]
    end

    L1 --> L2 --> L3 --> L4

    style L1 fill:#f9d,stroke:#333
    style L2 fill:#9df,stroke:#333
    style L3 fill:#9f9,stroke:#333
    style L4 fill:#ff9,stroke:#333

class AgentChaosInjector:
    """多Agent混沌工程注入器"""

    def __init__(self, target_system):
        self.target = target_system
        self.fault_catalog = {
            "api_timeout": self._inject_api_timeout,
            "hallucination": self._inject_hallucination,
            "message_loss": self._inject_message_loss,
            "goal_drift": self._inject_goal_drift,
            "cascade_trigger": self._inject_cascade,
        }

    async def _inject_hallucination(self, agent, severity="medium"):
        """在Agent输出中注入受控幻觉"""
        if severity == "low":
            # 注入事实性小错误（日期、数字偏差）
            return perturb_facts(agent.output, delta=0.1)
        elif severity == "medium":
            # 注入逻辑谬误
            return inject_logical_fallacy(agent.output)
        else:
            # 注入完全虚构的"事实"
            return inject_fabrication(agent.output)

    async def _inject_cascade(self, origin_agent, propagation_depth=3):
        """从指定Agent触发级联故障"""
        tainted = await self._inject_hallucination(origin_agent, "medium")
        for i in range(propagation_depth):
            downstream = self.target.get_downstream(origin_agent, i)
            # 不注入新故障，观察原始故障是否自然级联
            result = await downstream.run(tainted)
            tainted = result
            yield {
                "depth": i + 1,
                "agent": downstream.name,
                "error_magnitude": measure_deviation(result),
                "confidence": await assess_confidence(result)
            }

    async def run_steady_state_hypothesis(self):
        """验证稳态假设：注入故障后系统是否能在SLA内恢复"""
        baseline = await self.target.run_baseline()

        results = {}
        for fault_name, injector in self.fault_catalog.items():
            injected = await injector(self.target.agents[0])
            recovery_time = await self.measure_recovery(injected)
            results[fault_name] = {
                "recovery_time_ms": recovery_time,
                "recovered": recovery_time < self.target.sla_threshold,
                "data_integrity": await self.verify_output_integrity(injected)
            }

        return results

graph LR
    subgraph Detection["检测层"]
        D1[置信度门控] --> D2[格式校验器]
        D2 --> D3[语义一致性检查]
        D3 --> D4[目标对齐验证]
    end

    subgraph Isolation["隔离层"]
        I1[Agent沙箱] --> I2[消息过滤器]
        I2 --> I3[权限边界]
        I3 --> I4[资源配额]
    end

    subgraph Recovery["恢复层"]
        R1[局部重试] --> R2[Agent替换]
        R2 --> R3[路径重规划]
        R3 --> R4[人工升级]
    end

    Detection --> Isolation --> Recovery

    style Detection fill:#e1f5fe,stroke:#0288d1
    style Isolation fill:#f3e5f5,stroke:#7b1fa2
    style Recovery fill:#e8f5e9,stroke:#388e3c

class CascadeRecoveryEngine:
    LEVELS = {
        1: {"action": "retry", "max_attempts": 2, "timeout": 5.0},
        2: {"action": "replace_agent", "fallback_model": "claude-haiku-4-5-20251001"},
        3: {"action": "replan", "strategy": "alternative_path"},
        4: {"action": "human_escalation", "sla_minutes": 15},
    }

    async def handle_failure(self, failure):
        level = self.classify_severity(failure)

        if level == 1:
            # 局部重试：同一Agent重新执行
            return await self.retry_with_backoff(failure.agent, failure.task)

        elif level == 2:
            # Agent替换：用备用模型接管失败Agent
            replacement = self.spawn_agent(
                model=self.LEVELS[2]["fallback_model"],
                capabilities=failure.agent.capabilities
            )
            return await replacement.run(failure.task)

        elif level == 3:
            # 路径重规划：寻找绕过失败节点的替代路径
            alt_path = self.find_alternative_path(
                self.topology, 
                failed_node=failure.agent.id
            )
            return await self.execute_path(alt_path, failure.original_task)

        else:
            # 人工升级
            await self.notify_human_operator(failure)
            return await self.wait_for_human_resolution(failure)

    def classify_severity(self, failure):
        if failure.type in ["api_timeout", "rate_limit"]:
            return 1
        if failure.type in ["format_error", "tool_error"]:
            return 2
        if failure.type in ["hallucination", "goal_drift"]:
            return 3
        return 4  # 未知故障直接升级