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feat: refactor API key configuration and enhance application initialization

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- 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.
This commit is contained in:
Mimikko-zeus
2026-02-27 14:32:30 +08:00
parent ab5bbff6f7
commit 8a538bb950
58 changed files with 13457 additions and 350 deletions
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examples/demo_data_governance.py Normal file
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"""
数据治理功能演示脚本
展示如何使用数据治理功能
"""
from pathlib import Path
from history.manager import get_history_manager
from history.data_sanitizer import get_sanitizer
def demo_basic_usage():
"""演示基础使用"""
print("=" * 60)
print("演示 1: 基础使用 - 自动治理")
print("=" * 60)
# 获取历史管理器（自动启用治理）
manager = get_history_manager(Path("./workspace"))
# 添加一条包含敏感信息的记录
record = manager.add_record(
task_id='demo-001',
user_input='读取配置文件 C:\\Users\\admin\\config.json，邮箱: admin@company.com',
intent_label='file_operation',
intent_confidence=0.95,
execution_plan='读取并解析配置文件',
code='with open("C:\\\\Users\\\\admin\\\\config.json") as f:\n config = json.load(f)',
success=True,
duration_ms=150,
stdout='配置加载成功',
stderr='',
log_path='./logs/demo-001.log',
task_summary='读取配置文件'
)
print(f"\n[OK] 已添加记录: {record.task_id}")
# 检查治理元数据
if record._governance:
print(f" - 数据级别: {record._governance['level']}")
print(f" - 敏感度评分: {record._governance['sensitivity_score']:.2f}")
print(f" - 保留期: {record._governance['retention_days']} 天")
print(f" - 敏感字段: {', '.join(record._governance['sensitive_fields'])}")
print("\n")
def demo_sanitizer():
"""演示脱敏功能"""
print("=" * 60)
print("演示 2: 数据脱敏")
print("=" * 60)
sanitizer = get_sanitizer()
# 测试文本
test_text = """
用户信息：
- 邮箱: zhang.san@company.com
- 手机: 13812345678
- 配置文件: C:\\Users\\zhangsan\\Documents\\config.json
- API密钥: sk-1234567890abcdefghijklmnopqrstuvwxyz123456789012
- 服务器IP: 192.168.1.100
"""
print("\n原始文本:")
print(test_text)
# 执行脱敏
sanitized_text, matches = sanitizer.sanitize(test_text)
print("\n脱敏后文本:")
print(sanitized_text)
print(f"\n检测到 {len(matches)} 处敏感信息:")
for match in matches:
print(f" - {match.type.value}: {match.value[:20]}... → {match.masked_value}")
# 敏感度评分
score = sanitizer.get_sensitivity_score(test_text)
print(f"\n敏感度评分: {score:.2f}")
print("\n")
def demo_governance_metrics():
"""演示治理指标"""
print("=" * 60)
print("演示 3: 治理指标")
print("=" * 60)
manager = get_history_manager(Path("./workspace"))
# 添加几条不同敏感度的记录
test_records = [
{
'task_id': 'demo-low',
'user_input': '计算 1 + 1',
'code': 'print(1 + 1)',
'stdout': '2',
'summary': '简单计算'
},
{
'task_id': 'demo-medium',
'user_input': '列出文件 C:\\Users\\test\\documents',
'code': 'os.listdir("C:\\\\Users\\\\test\\\\documents")',
'stdout': '["file1.txt", "file2.txt"]',
'summary': '列出文件'
},
{
'task_id': 'demo-high',
'user_input': '连接数据库',
'code': 'conn = psycopg2.connect("postgresql://user:pass123@192.168.1.100/db")',
'stdout': 'Connected',
'summary': '数据库连接'
}
]
for rec in test_records:
manager.add_record(
task_id=rec['task_id'],
user_input=rec['user_input'],
intent_label='test',
intent_confidence=0.9,
execution_plan='测试',
code=rec['code'],
success=True,
duration_ms=100,
stdout=rec['stdout'],
stderr='',
log_path='',
task_summary=rec['summary']
)
# 获取治理指标
metrics = manager.get_governance_metrics()
if metrics:
print(f"\n[治理指标统计]:")
print(f" - 总记录数: {metrics.total_records}")
print(f" - 完整保存: {metrics.full_records}")
print(f" - 脱敏保存: {metrics.sanitized_records}")
print(f" - 最小化保存: {metrics.minimal_records}")
print(f" - 存储占用: {metrics.total_size_bytes / 1024:.2f} KB")
if metrics.sensitive_field_hits:
print(f"\n 敏感字段命中:")
for field, count in metrics.sensitive_field_hits.items():
print(f" * {field}: {count} 次")
print("\n")
def demo_cleanup():
"""演示数据清理"""
print("=" * 60)
print("演示 4: 数据清理")
print("=" * 60)
manager = get_history_manager(Path("./workspace"))
print(f"\n清理前记录数: {len(manager.get_all())}")
# 执行清理
stats = manager.manual_cleanup()
print(f"\n清理统计:")
print(f" - 归档: {stats['archived']} 条")
print(f" - 删除: {stats['deleted']} 条")
print(f" - 保留: {stats['remaining']} 条")
print("\n")
def demo_export():
"""演示导出脱敏数据"""
print("=" * 60)
print("演示 5: 导出脱敏数据")
print("=" * 60)
manager = get_history_manager(Path("./workspace"))
export_path = Path("./workspace/history_sanitized_export.json")
count = manager.export_sanitized(export_path)
print(f"\n[OK] 已导出 {count} 条脱敏记录")
print(f" 文件位置: {export_path.absolute()}")
print("\n")
if __name__ == '__main__':
print("\n")
print("=" * 60)
print(" " * 15 + "数据治理功能演示")
print("=" * 60)
print("\n")
try:
# 运行所有演示
demo_basic_usage()
demo_sanitizer()
demo_governance_metrics()
demo_cleanup()
demo_export()
print("=" * 60)
print("[OK] 所有演示完成")
print("=" * 60)
print("\n提示: 可以在 ./workspace 目录查看生成的文件")
print(" - history.json: 治理后的历史记录")
print(" - governance_metrics.json: 治理指标")
print(" - archive/: 归档目录")
print(" - history_sanitized_export.json: 导出的脱敏数据")
print("\n")
except Exception as e:
print(f"\n[ERROR] 演示过程中出错: {e}")
import traceback
traceback.print_exc()