{"record":{"id":"c43be3955a7bea16","repo":"datawhalechina/hello-agents","slug":"riskassessmentagent-str-e","errorCode":null,"errorMessage":"RiskAssessmentAgent 执行失败: {str(e)}","messagePattern":"RiskAssessmentAgent 执行失败: (.+?)","errorType":"exception","errorClass":"AgentException","httpStatus":null,"severity":"error","filePath":"Co-creation-projects/Shawnxyxy-HealthRecordAgent/backend/agents/risk_assess.py","lineNumber":26,"sourceCode":"\nclass RiskAssessmentAgent(BaseAgent):\n    def __init__(self, task_id=None, llm=None):\n        super().__init__(name=\"RiskAssessment\", task_id=task_id, llm=llm)\n\n    async def run(self, input_data: Dict[str, Any]) -> Dict[str, Any]:\n        try:\n            indicator_results = input_data[\"indicator_results\"]\n            if not indicator_results:\n                raise AgentException(\"缺少健康指标分析结果\")\n            self.set_state(\"running\")\n\n            result = await self._assess_risk(indicator_results)\n\n            self.set_state(\"completed\")\n            return result\n        except Exception as e:\n            self.set_state(\"error\")\n            raise AgentException(f\"RiskAssessmentAgent 执行失败: {str(e)}\")\n\n    async def _assess_risk(self, indicator_results: Dict[str, Any]) -> Dict[str, Any]:\n        risk_prompt = f\"\"\"\n你是一名专业的健康风险评估专家。\n\n以下是某用户的健康指标分析结果（已由其他智能体完成分析）：\n{indicator_results}\n\n请你完成以下任务：\n1. 综合判断用户的整体健康风险等级（low / medium / high）\n2. 列出主要风险因素（不超过 5 条）\n3. 推测可能存在的潜在健康风险或疾病方向\n4. 给出你评估的置信度（0~1 之间的小数）\n\n请以 JSON 格式返回，例如：\n{{\n  \"overall_risk_level\": \"medium\",\n  \"risk_factors\": [\"高胆固醇\", \"睡眠不足\"],","sourceCodeStart":8,"sourceCodeEnd":44,"githubUrl":"https://github.com/datawhalechina/hello-agents/blob/606a07d341a47be773fab7f4b71177f53f96b2c3/Co-creation-projects/Shawnxyxy-HealthRecordAgent/backend/agents/risk_assess.py#L8-L44","documentation":"This is the catch-all wrapper thrown by RiskAssessmentAgent.run's except block. Any exception inside run() — including the empty-indicator AgentException, LLM failures inside _assess_risk, or prompt formatting errors — is caught, agent state is set to 'error', and a new AgentException is raised with the prefixed message. The original exception text is embedded via str(e) but the traceback chain is lost because it is re-raised as a new exception without 'from e'.","triggerScenarios":"Any failure inside run(): empty indicator_results (error 140), exceptions from self._assess_risk (LLM timeout, API auth failure, malformed JSON in the model response), or AttributeError from unexpected input shapes.","commonSituations":"LLM API key/quota problems surfacing through the agent; upstream output shape drift; retry loops that see only the wrapper message and can't classify the root cause.","solutions":["Read the suffix of the message after 'RiskAssessmentAgent 执行失败: ' — that is str(e) of the original exception and identifies the real failure.","If it is '缺少健康指标分析结果', fix the upstream input (see the empty-indicator error).","If it mentions network/timeout/auth, fix the LLM configuration (api_key, base_url, model name in config).","Improve the code: use 'raise AgentException(...) from e' and catch AgentException separately so precondition errors are not double-wrapped."],"exampleFix":"# before\nexcept Exception as e:\n    self.set_state(\"error\")\n    raise AgentException(f\"RiskAssessmentAgent 执行失败: {str(e)}\")\n\n# after\nexcept AgentException:\n    self.set_state(\"error\")\n    raise\nexcept Exception as e:\n    self.set_state(\"error\")\n    raise AgentException(f\"RiskAssessmentAgent 执行失败: {str(e)}\") from e","handlingStrategy":"try-catch","validationCode":null,"typeGuard":null,"tryCatchPattern":"try:\n    result = await risk_agent.run(input_data)\nexcept AgentException as e:\n    msg = str(e).removeprefix(\"RiskAssessmentAgent 执行失败: \")\n    log.error(\"risk agent failed: %s\", msg, exc_info=True)\n    # classify by inner message; do not blind-retry LLM/auth failures\n    raise","preventionTips":["Always read the inner message after the wrapper prefix — it carries the root cause.","Patch the agent to re-raise with 'from e' so tracebacks stay intact.","Log agent state transitions (running/error) to correlate with pipeline monitoring."],"tags":["agent-pipeline","exception-wrapping","python","error-handling"],"backgroundTag":null,"analyzedSha":"606a07d341a47be773fab7f4b71177f53f96b2c3","analyzedAt":"2026-08-14T22:57:27.446Z","schemaVersion":2},"datasetVersion":"2026-08-15T22:17:37.221Z"}