83 lines
2.5 KiB
Python
83 lines
2.5 KiB
Python
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#!/usr/bin/env python3
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"""
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完全自主分析示例
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这个示例展示了如何让 AI 完全自主地分析数据，无需指定任何需求或模板。
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AI 会自动识别数据类型、推断分析目标、生成分析计划并执行分析。
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使用方法：
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python examples/autonomous_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 --output output/autonomous
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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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"""运行完全自主分析"""
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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("完全自主分析示例")
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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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output_dir = "output/autonomous"
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logger.info(f"数据文件: {data_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: 完全自主")
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logger.info("AI 将自动：")
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logger.info(" 1. 识别数据类型（工单、销售、用户等）")
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logger.info(" 2. 推断数据的业务含义")
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logger.info(" 3. 自主决定分析维度和方法")
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logger.info(" 4. 生成动态分析计划")
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logger.info(" 5. 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（不指定需求和模板）
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report_path = run_analysis(
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data_file=data_file,
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user_requirement=None, # 无需求，完全自主
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template_file=None, # 无模板
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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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if __name__ == "__main__":
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main()
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