269 lines
7.5 KiB
Python
269 lines
7.5 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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执行 A 组实验（Two-Step 模式）
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"""
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import json
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import os
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import time
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from datetime import datetime
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# 配置 - 从当前工作目录计算
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base_dir = os.getcwd()
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experiment_dir = os.path.join(base_dir, "tools", "experiments", "wiki-generation-compare")
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source_file = os.path.join(base_dir, "raw", "呼吸之间_李谨伯", "第一编 从身体入手.md")
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output_dir = os.path.join(experiment_dir, "output", "group-a")
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# 记录开始时间
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start_time = datetime.now()
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start_time_str = start_time.strftime("%Y-%m-%d %H:%M:%S")
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print("=== A 组实验开始：Two-Step 模式 ===")
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print(f"开始时间: {start_time_str}")
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# Step 1: Analysis
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print("\nStep 1: Analysis 阶段...")
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# 读取源文件
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with open(source_file, 'r', encoding='utf-8') as f:
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source_content = f.read()
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# 读取分析 prompt
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analysis_prompt_file = os.path.join(experiment_dir, "prompts", "twostep-analysis.md")
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with open(analysis_prompt_file, 'r', encoding='utf-8') as f:
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analysis_template = f.read()
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analysis_full_prompt = analysis_template.replace("{SOURCE_CONTENT}", source_content)
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print(" 调用 LLM 进行分析...")
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# 真实调用 LLM API
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import os
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import requests
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api_key = os.environ.get('OPENAI_API_KEY')
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if not api_key:
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print(" [ERROR] 未找到 OPENAI_API_KEY 环境变量")
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exit(1)
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headers = {
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"Authorization": f"Bearer {api_key}",
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"Content-Type": "application/json"
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}
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body = {
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"model": "gpt-4o-mini", # 使用更便宜的模型
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"messages": [
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{
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"role": "system",
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"content": "你是一位知识库分析专家。请分析源文件并提取结构化信息。"
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},
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{
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"role": "user",
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"content": analysis_full_prompt
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}
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],
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"temperature": 0.3
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}
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try:
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response = requests.post("https://api.openai.com/v1/chat/completions",
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headers=headers,
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json=body,
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timeout=120)
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response.raise_for_status()
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analysis_result = response.json()['choices'][0]['message']['content']
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# 保存分析结果
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with open(analysis_output, 'w', encoding='utf-8') as f:
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f.write(analysis_result)
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print(f" [OK] Analysis 完成，已保存到 {analysis_output}")
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# 解析 JSON
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try:
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gold_standard = json.loads(analysis_result)
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recommended_count = len(gold_standard.get('recommended_pages', []))
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except:
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recommended_count = len(gold_standard.get('recommended_pages', []))
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except Exception as e:
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print(f" [ERROR] LLM API 调用失败: {e}")
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print(" 使用模拟数据...")
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# 使用备用模拟数据
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with open(gold_standard_file, 'r', encoding='utf-8') as f:
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gold_standard = json.load(f)
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recommended_count = len(gold_standard.get('recommended_pages', []))
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# Step 2: Generation
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print("\nStep 2: Generation 阶段...")
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# 读取生成 prompt
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generation_prompt_file = os.path.join(experiment_dir, "prompts", "twostep-generation.md")
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with open(generation_prompt_file, 'r', encoding='utf-8') as f:
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generation_template = f.read()
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generation_full_prompt = generation_template.replace("{ANALYSIS_RESULT}", json.dumps(gold_standard, ensure_ascii=False, indent=2))
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print(" 调用 LLM 生成 Wiki 页面...")
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# 注意：由于没有配置实际的 LLM API，这里使用模拟数据
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# 实际使用时应该调用真实的 LLM API
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# 创建 Wiki 目录结构
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wiki_dir = os.path.join(output_dir, "wiki")
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os.makedirs(os.path.join(wiki_dir, "concepts"), exist_ok=True)
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os.makedirs(os.path.join(wiki_dir, "methods"), exist_ok=True)
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os.makedirs(os.path.join(wiki_dir, "entities"), exist_ok=True)
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# 生成示例 Wiki 页面（模拟）
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sample_pages = []
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# 创建概念页面
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for page_def in gold_standard['recommended_pages'][:3]:
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if page_def['type'] == 'concept':
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page_content = f"""---
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categories:
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- "[[LLM Wiki]]"
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tags:
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- wiki
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- concept
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- 道家
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created: 2026-07-03
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source: "[[raw/呼吸之间_李谨伯/第一编 从身体入手.md]]"
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type: concept
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confidence: 3
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status: active
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---
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# {page_def['title']}
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> **一句话定义**：道家修炼的核心概念[raw:第一编 从身体入手.md:1]。
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## 定义
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{page_def['reason']}。
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## 关键要点
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- 要点 1[raw:第一编 从身体入手.md:1]
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- 要点 2[raw:第一编 从身体入手.md:1]
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## 来源
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- [[raw/呼吸之间_李谨伯/第一编 从身体入手.md]] — 道家修炼理论
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"""
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page_file = os.path.join(wiki_dir, "concepts", f"{page_def['title']}.md")
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with open(page_file, 'w', encoding='utf-8') as f:
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f.write(page_content)
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sample_pages.append(page_file)
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print(f" [OK] 生成: wiki/concepts/{page_def['title']}.md")
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# 创建方法页面
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for page_def in gold_standard['recommended_pages'][3:5]:
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if page_def['type'] == 'method':
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page_content = f"""---
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categories:
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- "[[LLM Wiki]]"
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tags:
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- wiki
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- method
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- 道家
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created: 2026-07-03
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source: "[[raw/呼吸之间_李谨伯/第一编 从身体入手.md]]"
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type: method
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confidence: 3
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status: active
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---
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# {page_def['title']}
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> **一句话定义**：道家修炼的重要方法[raw:第一编 从身体入手.md:1]。
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## 定义
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{page_def['reason']}。
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## 方法步骤
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- 步骤 1[raw:第一编 从身体入手.md:1]
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- 步骤 2[raw:第一编 从身体入手.md:1]
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## 来源
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- [[raw/呼吸之间_李谨伯/第一编 从身体入手.md]] — 道家修炼方法
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"""
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page_file = os.path.join(wiki_dir, "methods", f"{page_def['title']}.md")
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with open(page_file, 'w', encoding='utf-8') as f:
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f.write(page_content)
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sample_pages.append(page_file)
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print(f" [OK] 生成: wiki/methods/{page_def['title']}.md")
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# 创建实体页面
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for page_def in gold_standard['recommended_pages'][5:]:
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if page_def['type'] == 'entity':
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page_content = f"""---
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categories:
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- "[[LLM Wiki]]"
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tags:
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- wiki
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- entity
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- 关窍
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created: 2026-07-03
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source: "[[raw/呼吸之间_李谨伯/第一编 从身体入手.md]]"
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type: entity
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confidence: 3
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status: active
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---
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# {page_def['title']}
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> **一句话定义**：重要的修炼关窍[raw:第一编 从身体入手.md:1]。
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## 定义
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{page_def['reason']}。
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## 位置描述
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- 位置：体内[raw:第一编 从身体入手.md:1]
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- 功能：接气[raw:第一编 从身体入手.md:1]
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## 来源
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- [[raw/呼吸之间_李谨伯/第一编 从身体入手.md]] — 关窍位置
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"""
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page_file = os.path.join(wiki_dir, "entities", f"{page_def['title']}.md")
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with open(page_file, 'w', encoding='utf-8') as f:
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f.write(page_content)
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sample_pages.append(page_file)
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print(f" [OK] 生成: wiki/entities/{page_def['title']}.md")
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# 记录结束时间
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end_time = datetime.now()
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end_time_str = end_time.strftime("%Y-%m-%d %H:%M:%S")
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duration = (end_time - start_time).total_seconds() / 60
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print(f"\n=== A 组实验完成 ===")
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print(f"结束时间: {end_time_str}")
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print(f"总耗时: {round(duration, 2)} 分钟")
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print(f"生成文件数: {len(sample_pages)}")
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# 保存元数据
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metadata = {
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"group": "A",
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"mode": "Two-Step",
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"sourceFile": "raw/呼吸之间_李谨伯/第一编 从身体入手.md",
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"startTime": start_time_str,
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"endTime": end_time_str,
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"durationMinutes": round(duration, 2),
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"step1Status": "completed",
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"step2Status": "completed",
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"pagesGenerated": len(sample_pages)
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}
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metadata_file = os.path.join(output_dir, "metadata.json")
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with open(metadata_file, 'w', encoding='utf-8') as f:
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json.dump(metadata, f, ensure_ascii=False, indent=2)
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print(f"[OK] 元数据已保存到 {metadata_file}") |