113 lines
3.2 KiB
Python
113 lines
3.2 KiB
Python
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"""
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交互式 CLI —— 四层架构自适应分析
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用法: python3 cli.py [数据库路径]
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"""
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import os
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import sys
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sys.path.insert(0, os.path.dirname(__file__))
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from config import DB_PATH, LLM_CONFIG, MAX_EXPLORATION_ROUNDS
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from agent import DataAnalysisAgent
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def print_help():
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print("""
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可用命令:
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<问题> 分析一个问题
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rounds=<N> <问题> 设置探索轮数
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schema 查看数据库 Schema
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history 查看分析历史
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audit 查看 SQL 审计日志
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clear 清空分析历史
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help 显示帮助
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quit / q 退出
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""")
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def main():
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db_path = sys.argv[1] if len(sys.argv) > 1 else DB_PATH
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if not os.path.exists(db_path):
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print(f"❌ 数据库不存在: {db_path}")
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print(f" 请先运行 python3 demo.py 创建示例数据库，或指定已有数据库路径")
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sys.exit(1)
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if not LLM_CONFIG["api_key"]:
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print("⚠️ 未配置 LLM_API_KEY，请先设置环境变量：")
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print(" export LLM_API_KEY=sk-xxx")
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print(" export LLM_BASE_URL=https://api.openai.com/v1 # 或 Ollama 等")
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print(" export LLM_MODEL=gpt-4o")
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sys.exit(1)
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# 初始化 Agent
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agent = DataAnalysisAgent(db_path)
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print("=" * 60)
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print(" 🤖 数据分析 Agent —— 四层架构")
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print("=" * 60)
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print(f"\n🔗 LLM: {LLM_CONFIG['model']} @ {LLM_CONFIG['base_url']}")
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print(f"🔄 最大探索轮数: {MAX_EXPLORATION_ROUNDS}")
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print(f"💾 数据库: {db_path}")
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print(f"\n💬 输入分析问题（help 查看命令）\n")
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while True:
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try:
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user_input = input("📊 > ").strip()
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except (EOFError, KeyboardInterrupt):
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print("\n👋 再见！")
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break
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if not user_input:
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continue
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cmd = user_input.lower()
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if cmd in ("quit", "exit", "q"):
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print("👋 再见！")
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break
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elif cmd == "help":
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print_help()
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continue
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elif cmd == "schema":
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print(agent.get_schema())
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continue
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elif cmd == "history":
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print(agent.get_history())
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continue
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elif cmd == "audit":
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print(agent.get_audit())
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continue
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elif cmd == "clear":
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agent.clear_history()
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print("✅ 历史已清空")
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continue
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# 解析可选参数：rounds=3
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max_rounds = MAX_EXPLORATION_ROUNDS
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question = user_input
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if "rounds=" in question.lower():
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parts = question.split("rounds=")
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question = parts[0].strip()
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try:
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max_rounds = int(parts[1].strip().split()[0])
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except (ValueError, IndexError):
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pass
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try:
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report = agent.analyze(question, max_rounds=max_rounds)
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print("\n" + report)
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print("\n" + "~" * 60)
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except Exception as e:
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print(f"\n❌ 分析出错: {e}")
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import traceback
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traceback.print_exc()
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# 退出时显示审计
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print("\n📋 本次会话审计:")
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print(agent.get_audit())
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if __name__ == "__main__":
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main()
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