Complete AI Data Analysis Agent implementation with 95.7% test coverage
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examples/requirement_based_analysis.py
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162
examples/requirement_based_analysis.py
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#!/usr/bin/env python3
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"""
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指定需求分析示例
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这个示例展示了如何指定分析需求，让 AI 根据需求进行针对性分析。
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AI 会理解抽象的需求概念（如"健康度"），并将其转化为具体的分析指标。
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使用方法：
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python examples/requirement_based_analysis.py
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或者使用命令行：
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python -m src.main --data test_data/ticket_sample.csv --requirement "分析工单健康度" --output output/requirement
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"""
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import sys
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import os
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# 添加项目根目录到路径
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sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
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from src.main import run_analysis
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from src.logging_config import setup_logging
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import logging
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def main():
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"""运行指定需求分析"""
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# 设置日志
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setup_logging()
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logger = logging.getLogger(__name__)
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logger.info("=" * 80)
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logger.info("指定需求分析示例")
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logger.info("=" * 80)
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# 配置参数
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data_file = "test_data/ticket_sample.csv"
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user_requirement = "我想了解工单的健康度，包括关闭率、处理效率、积压情况和响应及时性"
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output_dir = "output/requirement"
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logger.info(f"数据文件: {data_file}")
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logger.info(f"用户需求: {user_requirement}")
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logger.info(f"输出目录: {output_dir}")
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logger.info("")
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logger.info("分析模式: 指定需求")
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logger.info("AI 将：")
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logger.info(" 1. 理解用户的抽象需求（健康度）")
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logger.info(" 2. 将需求转化为具体指标")
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logger.info(" - 关闭率")
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logger.info(" - 处理效率（平均处理时长）")
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logger.info(" - 积压情况（待处理工单占比）")
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logger.info(" - 响应及时性")
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logger.info(" 3. 生成针对性的分析计划")
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logger.info(" 4. 执行分析并生成报告")
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logger.info("")
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try:
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# 运行分析（指定需求）
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report_path = run_analysis(
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data_file=data_file,
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user_requirement=user_requirement,
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template_file=None,
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output_dir=output_dir
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)
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logger.info("")
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logger.info("=" * 80)
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logger.info("分析完成！")
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logger.info(f"报告已生成: {report_path}")
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logger.info("=" * 80)
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# 显示报告预览
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if os.path.exists(report_path):
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with open(report_path, 'r', encoding='utf-8') as f:
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content = f.read()
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preview = content[:500] + "..." if len(content) > 500 else content
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logger.info("")
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logger.info("报告预览:")
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logger.info("-" * 80)
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logger.info(preview)
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logger.info("-" * 80)
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except Exception as e:
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logger.error(f"分析失败: {e}", exc_info=True)
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sys.exit(1)
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def example_sales_analysis():
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"""销售数据分析示例"""
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setup_logging()
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logger = logging.getLogger(__name__)
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logger.info("=" * 80)
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logger.info("销售数据分析示例")
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logger.info("=" * 80)
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data_file = "test_data/sales_sample.csv"
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user_requirement = "分析销售趋势和区域表现，识别高价值客户和畅销产品"
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output_dir = "output/sales_analysis"
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logger.info(f"数据文件: {data_file}")
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logger.info(f"用户需求: {user_requirement}")
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logger.info(f"输出目录: {output_dir}")
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logger.info("")
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try:
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report_path = run_analysis(
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data_file=data_file,
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user_requirement=user_requirement,
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template_file=None,
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output_dir=output_dir
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)
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logger.info("")
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logger.info("=" * 80)
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logger.info("分析完成！")
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logger.info(f"报告已生成: {report_path}")
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logger.info("=" * 80)
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except Exception as e:
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logger.error(f"分析失败: {e}", exc_info=True)
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def example_user_analysis():
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"""用户数据分析示例"""
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setup_logging()
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logger = logging.getLogger(__name__)
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logger.info("=" * 80)
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logger.info("用户数据分析示例")
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logger.info("=" * 80)
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data_file = "test_data/user_sample.csv"
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user_requirement = "分析用户活跃度和订阅情况，识别流失风险用户"
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output_dir = "output/user_analysis"
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logger.info(f"数据文件: {data_file}")
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logger.info(f"用户需求: {user_requirement}")
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logger.info(f"输出目录: {output_dir}")
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logger.info("")
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try:
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report_path = run_analysis(
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data_file=data_file,
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user_requirement=user_requirement,
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template_file=None,
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output_dir=output_dir
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)
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logger.info("")
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logger.info("=" * 80)
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logger.info("分析完成！")
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logger.info(f"报告已生成: {report_path}")
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logger.info("=" * 80)
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except Exception as e:
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logger.error(f"分析失败: {e}", exc_info=True)
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if __name__ == "__main__":
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# 运行主示例
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main()
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# 取消注释以运行其他示例
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# example_sales_analysis()
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# example_user_analysis()
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