{"record":{"id":"1df189b7a4882c40","repo":"ScrapeGraphAI/Scrapegraph-ai","slug":"validation-analysis-failed-str-e","errorCode":null,"errorMessage":"Validation analysis failed: {str(e)}","messagePattern":"Validation analysis failed: (.+?)","errorType":"error_code","errorClass":"AnalysisError","httpStatus":null,"severity":"error","filePath":"scrapegraphai/utils/code_error_analysis.py","lineNumber":272,"sourceCode":"                \"execution_result\",\n            ],\n        )\n        chain = prompt | llm_model | StrOutputParser()\n\n        # Execute chain with validated state\n        return chain.invoke(\n            {\n                \"generated_code\": validated_state.generated_code,\n                \"errors\": validated_state.errors[\"validation\"],\n                \"json_schema\": validated_state.json_schema,\n                \"execution_result\": validated_state.execution_result,\n            }\n        )\n\n    except KeyError as e:\n        raise InvalidStateError(f\"Missing required key in state dictionary: {e}\")\n    except Exception as e:\n        raise AnalysisError(f\"Validation analysis failed: {str(e)}\")\n\n\ndef semantic_focused_analysis(\n    state: Dict[str, Any], comparison_result: Dict[str, Any], llm_model\n) -> str:\n    \"\"\"\n    Analyzes the semantic differences in the generated code based on a comparison result.\n\n    Args:\n        state (dict): Contains the 'generated_code'.\n        comparison_result (Dict[str, Any]): Contains\n        'differences' and 'explanation' of the comparison.\n        llm_model: The language model used for generating the analysis.\n\n    Returns:\n        str: The result of the semantic error analysis.\n\n    Raises:","sourceCodeStart":254,"sourceCodeEnd":290,"githubUrl":"https://github.com/ScrapeGraphAI/Scrapegraph-ai/blob/532dfffbf6ee823a6c9cf8cfedc24a93bf026780/scrapegraphai/utils/code_error_analysis.py#L254-L290","documentation":"Generic failure of the validation-focused LLM analysis chain; the underlying exception message is appended. Distinguished from InvalidStateError: this is the prompt/LLM leg failing, not the input state.","triggerScenarios":"validation_focused_analysis / validation_reasoning_loop invoked with a broken llm_model (auth, base_url, rate limit) or when the 'validation' prompt template cannot render because a variable's value is of an unexpected type.","commonSituations":"Bad or missing provider API key, unreachable OpenAI/local endpoint, non-serializable json_schema object passed in state.","solutions":["Inspect str(e) in the message for the root cause","Validate json_schema is a plain dict (JSON-serializable) before passing state","Confirm llm_model works with a standalone invoke call","Retry with backoff for rate-limit/network errors"],"exampleFix":null,"handlingStrategy":"retry","validationCode":"import json\njson.dumps(state.get(\"json_schema\", {}))  # must be serializable\nllm_model.invoke(\"ping\")  # model reachable","typeGuard":null,"tryCatchPattern":"from scrapegraphai.utils.code_error_analysis import AnalysisError\ntry:\n    validation_focused_analysis(state, llm_model)\nexcept AnalysisError as e:\n    logger.error(\"validation analysis failed: %s\", e)\n    raise","preventionTips":["Keep json_schema as a plain dict","Check provider quota/keys before long runs","Retry transient provider errors with backoff"],"tags":["llm","validation-analysis","chain-invocation"],"backgroundTag":"llm-chain-invocation-failed","analyzedSha":"532dfffbf6ee823a6c9cf8cfedc24a93bf026780","analyzedAt":"2026-08-28T15:19:38.821Z","schemaVersion":2},"datasetVersion":"2026-08-28T16:17:29.566Z"}