#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
真实 B 组实验（Single-Step 模式）- 使用 openai 库
"""

import json
import os
import re
from datetime import datetime
import openai

# 配置
base_dir = os.getcwd()
experiment_dir = os.path.join(base_dir, "tools", "experiments", "wiki-generation-compare")
source_file = os.path.join(base_dir, "raw", "呼吸之间_李谨伯", "第一编 从身体入手.md")
output_dir = os.path.join(experiment_dir, "output", "group-b-real")

# 创建输出目录
os.makedirs(output_dir, exist_ok=True)
os.makedirs(os.path.join(output_dir, "wiki", "concepts"), exist_ok=True)
os.makedirs(os.path.join(output_dir, "wiki", "methods"), exist_ok=True)
os.makedirs(os.path.join(output_dir, "wiki", "entities"), exist_ok=True)

# 记录开始时间
start_time = datetime.now()
start_time_str = start_time.strftime("%Y-%m-%d %H:%M:%S")

print("=== B 组真实实验开始：Single-Step 模式 ===")
print(f"开始时间: {start_time_str}")

# 检查 API Key
api_key = os.environ.get('OPENAI_API_KEY')
if not api_key:
    print("[ERROR] 未找到 OPENAI_API_KEY 环境变量")
    exit(1)

print(f"API Key 长度: {len(api_key)}")

# 初始化 openai 客户端
client = openai.OpenAI(api_key=api_key, timeout=300)

# 直接生成
print("\n生成阶段...")

# 读取源文件
with open(source_file, 'r', encoding='utf-8') as f:
    source_content = f.read()

# 读取单步 prompt
singlestep_prompt_file = os.path.join(experiment_dir, "prompts", "singlestep.md")
with open(singlestep_prompt_file, 'r', encoding='utf-8') as f:
    template = f.read()

full_prompt = template.replace("{SOURCE_CONTENT}", source_content)

print(f"  Prompt 长度: {len(full_prompt)} 字符")
print("  调用 OpenAI API 生成 Wiki 页面...")

try:
    response = client.chat.completions.create(
        model="reasoning",
        messages=[
            {
                "role": "system",
                "content": "你是一位知识库构建专家。请直接从源文件中提取关键术语并生成 Wiki 页面。"
            },
            {
                "role": "user",
                "content": full_prompt
            }
        ],
        temperature=0.5,
        max_tokens=16000
    )

    generation_result = response.choices[0].message.content
    print("  [OK] LLM 生成完成")
    print(f"  生成内容长度: {len(generation_result)} 字符")

    # 保存原始生成结果
    raw_output_file = os.path.join(output_dir, "raw_generation.md")
    with open(raw_output_file, 'w', encoding='utf-8') as f:
        f.write(generation_result)
    print(f"  [OK] 原始生成结果已保存到 {raw_output_file}")

except Exception as e:
    print(f"  [ERROR] LLM API 调用失败: {type(e).__name__}: {e}")
    exit(1)

# 解析生成结果
sample_pages = []

# 解析 ---FILE: ... ---END FILE--- 块
file_blocks = re.findall(r'---FILE: (.*?)---(.*?)---END FILE---', generation_result, re.DOTALL)

if not file_blocks:
    print("  [WARNING] 未找到标准文件块格式，尝试宽松匹配...")
    # 尝试宽松匹配
    file_blocks = re.findall(r'FILE: (.*?)\n(.*?)(?=(?:FILE:|$))', generation_result, re.DOTALL)

print(f"\n  解析到 {len(file_blocks)} 个文件块")

for i, block in enumerate(file_blocks):
    if isinstance(block, tuple):
        file_path = block[0].strip()
        file_content = block[1].strip()
    else:
        # 如果没有匹配，尝试直接提取整个内容
        continue

    # 创建目录（如果需要）
    full_path = os.path.join(output_dir, file_path)
    file_dir = os.path.dirname(full_path)
    os.makedirs(file_dir, exist_ok=True)

    # 写入文件
    with open(full_path, 'w', encoding='utf-8') as f:
        f.write(file_content)
    sample_pages.append(full_path)
    print(f"  [OK] 生成 [{i+1}/{len(file_blocks)}]: {file_path}")

# 记录结束时间
end_time = datetime.now()
end_time_str = end_time.strftime("%Y-%m-%d %H:%M:%S")
duration = (end_time - start_time).total_seconds() / 60

print(f"\n=== B 组实验完成 ===")
print(f"结束时间: {end_time_str}")
print(f"总耗时: {round(duration, 2)} 分钟")
print(f"生成文件数: {len(sample_pages)}")

# 保存元数据
metadata = {
    "group": "B-real",
    "mode": "Single-Step (Real API)",
    "sourceFile": "raw/呼吸之间_李谨伯/第一编 从身体入手.md",
    "startTime": start_time_str,
    "endTime": end_time_str,
    "durationMinutes": round(duration, 2),
    "pagesGenerated": len(sample_pages),
    "apiModel": "reasoning",
    "rawContentLength": len(generation_result),
    "status": "success"
}

metadata_file = os.path.join(output_dir, "metadata.json")
with open(metadata_file, 'w', encoding='utf-8') as f:
    json.dump(metadata, f, ensure_ascii=False, indent=2)

print(f"[OK] 元数据已保存到 {metadata_file}")
print(f"\n文件输出位置:")
print(f"  原始生成: {raw_output_file}")
print(f"  Wiki 页面: {output_dir}/wiki/")
print(f"  元数据: {metadata_file}")