213 lines
6.7 KiB
Python
213 lines
6.7 KiB
Python
#!/usr/bin/env python3
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"""
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基于模板分析示例
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这个示例展示了如何使用分析模板作为参考框架。
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AI 会理解模板的结构和要求，并根据数据特征灵活调整分析内容。
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使用方法：
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python examples/template_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 --template templates/ticket_analysis.md --output output/template
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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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"""运行基于模板的分析"""
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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("基于模板分析示例")
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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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template_file = "templates/ticket_analysis.md"
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output_dir = "output/template"
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logger.info(f"数据文件: {data_file}")
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logger.info(f"分析模板: {template_file}")
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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: 基于模板")
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logger.info("AI 将：")
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logger.info(" 1. 解析模板结构和要求")
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logger.info(" 2. 检查数据是否满足模板要求")
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logger.info(" 3. 根据数据特征灵活调整分析内容")
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logger.info(" 4. 按模板结构组织报告")
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logger.info(" 5. 说明哪些分析被跳过及原因")
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logger.info("")
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logger.info("注意：如果数据缺少某些字段，AI 会智能跳过相关分析")
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logger.info("")
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try:
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# 运行分析（使用模板）
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report_path = run_analysis(
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data_file=data_file,
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user_requirement=None,
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template_file=template_file,
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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_problem_analysis():
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"""问题分析模板示例"""
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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("问题分析模板示例")
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logger.info("=" * 80)
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data_file = "test_data/anomaly_sample.csv"
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template_file = "templates/problem_analysis.md"
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output_dir = "output/problem_analysis"
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logger.info(f"数据文件: {data_file}")
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logger.info(f"分析模板: {template_file}")
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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("这个示例使用包含异常的数据集，AI 将：")
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logger.info(" 1. 识别数据中的异常模式")
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logger.info(" 2. 分析异常的分布和影响")
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logger.info(" 3. 推断可能的根本原因")
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logger.info(" 4. 提供解决方案建议")
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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=None,
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template_file=template_file,
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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_data_analysis():
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"""通用数据分析模板示例"""
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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("通用数据分析模板示例")
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logger.info("=" * 80)
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data_file = "test_data/sales_sample.csv"
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template_file = "templates/data_analysis.md"
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output_dir = "output/data_analysis"
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logger.info(f"数据文件: {data_file}")
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logger.info(f"分析模板: {template_file}")
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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("这个示例使用通用数据分析模板，适用于各种数据类型")
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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=None,
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template_file=template_file,
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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_combined_analysis():
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"""组合模式：模板 + 需求"""
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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("组合模式示例：模板 + 需求")
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logger.info("=" * 80)
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data_file = "test_data/ticket_sample.csv"
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template_file = "templates/ticket_analysis.md"
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user_requirement = "重点关注车门模块的远程控制问题，进行深入的根因分析"
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output_dir = "output/combined_analysis"
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logger.info(f"数据文件: {data_file}")
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logger.info(f"分析模板: {template_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("这个示例同时使用模板和需求：")
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logger.info(" - 模板提供报告结构框架")
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logger.info(" - 需求指定分析重点和深度")
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logger.info(" - AI 会在模板框架下进行针对性深入分析")
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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=template_file,
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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_problem_analysis()
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# example_data_analysis()
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# example_combined_analysis()
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