feat: refactor API key configuration and enhance application initialization

- 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.

app/exceptions.py

@@ -0,0 +1,106 @@
+"""
+需求分析异常分级系统
+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
+"""
+
+
+class RequirementAnalysisException(Exception):
+    """需求分析异常基类"""
+    
+    def __init__(self, message: str, severity: str = "medium"):
+        """
+        Args:
+            message: 异常描述
+            severity: 严重程度 (critical/high/medium/low)
+        """
+        super().__init__(message)
+        self.severity = severity
+
+
+class CriticalInfoMissingException(RequirementAnalysisException):
+    """关键信息缺失异常 - 必须澄清才能继续"""
+    
+    def __init__(self, message: str, missing_fields: list = None):
+        super().__init__(message, severity="critical")
+        self.missing_fields = missing_fields or []
+
+
+class AmbiguousRequirementException(RequirementAnalysisException):
+    """需求歧义异常 - 建议澄清"""
+    
+    def __init__(self, message: str, ambiguous_parts: list = None):
+        super().__init__(message, severity="high")
+        self.ambiguous_parts = ambiguous_parts or []
+
+
+class LowConfidenceException(RequirementAnalysisException):
+    """低置信度异常 - 可以继续但建议澄清"""
+    
+    def __init__(self, message: str, confidence: float = 0.0):
+        super().__init__(message, severity="medium")
+        self.confidence = confidence
+
+
+class CheckerFailureException(RequirementAnalysisException):
+    """检查器本身失败异常 - 可以降级处理"""
+    
+    def __init__(self, message: str, original_error: Exception = None):
+        super().__init__(message, severity="low")
+        self.original_error = original_error
+
+
+def classify_requirement_error(result: dict = None, error: Exception = None) -> RequirementAnalysisException:
+    """
+    根据检查结果或错误对象，分类异常类型
+    
+    Args:
+        result: 需求完整性检查结果
+        error: 原始异常对象
+        
+    Returns:
+        分类后的异常对象
+    """
+    # 如果是检查器本身失败
+    if error is not None:
+        return CheckerFailureException(
+            f"需求完整性检查器失败: {str(error)}",
+            original_error=error
+        )
+    
+    # 如果没有结果，视为检查器失败
+    if result is None:
+        return CheckerFailureException("需求完整性检查返回空结果")
+    
+    is_complete = result.get('is_complete', True)
+    confidence = result.get('confidence', 1.0)
+    reason = result.get('reason', '未知原因')
+    
+    # 明确标记为不完整
+    if not is_complete:
+        # 检查是否有关键信息缺失标记
+        missing_info = result.get('missing_info', [])
+        critical_fields = result.get('critical_fields', [])
+        
+        if critical_fields or len(missing_info) > 2:
+            # 关键信息缺失
+            return CriticalInfoMissingException(
+                f"关键信息缺失: {reason}",
+                missing_fields=critical_fields or missing_info
+            )
+        else:
+            # 一般歧义
+            return AmbiguousRequirementException(
+                f"需求存在歧义: {reason}",
+                ambiguous_parts=missing_info
+            )
+    
+    # 标记为完整但置信度低
+    if is_complete and confidence < 0.7:
+        return LowConfidenceException(
+            f"需求置信度较低 ({confidence:.1%}): {reason}",
+            confidence=confidence
+        )
+    
+    # 其他情况视为检查器问题
+    return CheckerFailureException(f"需求检查结果异常: {reason}")
+