8a538bb950
- Renamed `check_environment` to `check_api_key_configured` for clarity, simplifying the API key validation logic. - Removed the blocking behavior of the API key check during application startup, allowing the app to run while providing a prompt for configuration. - Updated `LocalAgentApp` to accept an `api_configured` parameter, enabling conditional messaging for API key setup. - Enhanced the `SandboxRunner` to support backup management and improved execution result handling with detailed metrics. - Integrated data governance strategies into the `HistoryManager`, ensuring compliance and improved data management. - Added privacy settings and metrics tracking across various components to enhance user experience and application safety.
107 lines
3.5 KiB
Python
107 lines
3.5 KiB
Python
"""
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需求分析异常分级系统
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用于区分不同类型的需求分析失败，并采取相应的处理策略
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"""
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class RequirementAnalysisException(Exception):
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"""需求分析异常基类"""
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def __init__(self, message: str, severity: str = "medium"):
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"""
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Args:
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message: 异常描述
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severity: 严重程度 (critical/high/medium/low)
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"""
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super().__init__(message)
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self.severity = severity
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class CriticalInfoMissingException(RequirementAnalysisException):
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"""关键信息缺失异常 - 必须澄清才能继续"""
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def __init__(self, message: str, missing_fields: list = None):
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super().__init__(message, severity="critical")
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self.missing_fields = missing_fields or []
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class AmbiguousRequirementException(RequirementAnalysisException):
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"""需求歧义异常 - 建议澄清"""
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def __init__(self, message: str, ambiguous_parts: list = None):
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super().__init__(message, severity="high")
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self.ambiguous_parts = ambiguous_parts or []
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class LowConfidenceException(RequirementAnalysisException):
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"""低置信度异常 - 可以继续但建议澄清"""
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def __init__(self, message: str, confidence: float = 0.0):
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super().__init__(message, severity="medium")
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self.confidence = confidence
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class CheckerFailureException(RequirementAnalysisException):
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"""检查器本身失败异常 - 可以降级处理"""
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def __init__(self, message: str, original_error: Exception = None):
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super().__init__(message, severity="low")
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self.original_error = original_error
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def classify_requirement_error(result: dict = None, error: Exception = None) -> RequirementAnalysisException:
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"""
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根据检查结果或错误对象，分类异常类型
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Args:
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result: 需求完整性检查结果
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error: 原始异常对象
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Returns:
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分类后的异常对象
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"""
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# 如果是检查器本身失败
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if error is not None:
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return CheckerFailureException(
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f"需求完整性检查器失败: {str(error)}",
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original_error=error
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)
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# 如果没有结果，视为检查器失败
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if result is None:
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return CheckerFailureException("需求完整性检查返回空结果")
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is_complete = result.get('is_complete', True)
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confidence = result.get('confidence', 1.0)
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reason = result.get('reason', '未知原因')
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# 明确标记为不完整
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if not is_complete:
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# 检查是否有关键信息缺失标记
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missing_info = result.get('missing_info', [])
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critical_fields = result.get('critical_fields', [])
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if critical_fields or len(missing_info) > 2:
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# 关键信息缺失
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return CriticalInfoMissingException(
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f"关键信息缺失: {reason}",
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missing_fields=critical_fields or missing_info
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)
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else:
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# 一般歧义
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return AmbiguousRequirementException(
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f"需求存在歧义: {reason}",
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ambiguous_parts=missing_info
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)
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# 标记为完整但置信度低
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if is_complete and confidence < 0.7:
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return LowConfidenceException(
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f"需求置信度较低 ({confidence:.1%}): {reason}",
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confidence=confidence
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)
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# 其他情况视为检查器问题
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return CheckerFailureException(f"需求检查结果异常: {reason}")
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