#!/usr/bin/env python3
# -*- coding: utf-8 -*-

from openai import OpenAI
import os
import base64
import json
import time
from datetime import datetime

def encode_video(video_path):
    """编码视频文件为base64"""
    with open(video_path, "rb") as video_file:
        return base64.b64encode(video_file.read()).decode("utf-8")

def encode_audio(audio_path):
    """编码音频文件为base64"""
    with open(audio_path, "rb") as audio_file:
        return base64.b64encode(audio_file.read()).decode("utf-8")

def analyze_douyin_template(video_path, audio_path=None, output_file=None):
    """
    专门分析抖音热门视频模板的函数
    """
    
    STREAM_MODE = True
    
    # 编码视频文件
    print("正在编码视频文件...")
    base64_video = encode_video(video_path)
    
    # 编码音频文件（如果提供）
    content_list = [
        {
            "type": "video_url",
            "video_url": {"url": f"data:video/mp4;base64,{base64_video}"},
        }
    ]
    
    if audio_path and os.path.exists(audio_path):
        print("正在编码音频文件...")
        base64_audio = encode_audio(audio_path)
        content_list.append({
            "type": "audio_url",
            "audio_url": {"url": f"data:audio/wav;base64,{base64_audio}"},
        })
    
    # 专业的抖音模板分析提示词
    template_analysis_prompt = """🎯 **抖音热门视频模板分析专家**

请按照以下专业框架分析这个视频的热门模板和套路：

## 📱 一、Hook勾子分析（前3-5秒）

### 勾子类型识别：
1. **好奇类勾子**
   - "**是一种什么体验"
   - "如何不**也能**"  
   - "如果你**，你会怎么样"

2. **借势类勾子**
   - "曾经被某人**，如今却**"
   - "某**大火，我却关心**"
   - "某明星都在用的**"

3. **痛点式勾子**
   - "为什么**，却**"
   - "不知道**？一定要**"
   - "最新**，你不会不知道吧"

4. **极限式勾子**
   - "这是全网最**"
   - "**一定要**"
   - "99%的人都不知道的**"

5. **恐吓式勾子**
   - "**揭密，千万不要**"
   - "如果你再不**，就会**"
   - "**将迎来**，赶紧**"

## 🎵 二、BGM模板分析
- 是否使用热门音乐
- 音乐类型和情绪
- 与内容的匹配度

## 🎬 三、视频结构模板
- **知识类**: 问题→解决方案→效果→引导
- **剧情类**: 冲突→发展→反转→结局
- **测评类**: 展示→使用→对比→推荐
- **生活类**: 日常→亮点→感悟→互动

## 📝 四、文案套路
- 标题党元素
- 互动引导语
- 情绪触发词

## 🔥 五、爆款元素
- 反差萌
- 共鸣点  
- 争议性
- 实用性
- 娱乐性

请严格按照以下JSON格式输出分析结果，不要添加```json```标记：

{
  "hook_analysis": {
    "hook_type": "具体的勾子类型",
    "hook_formula": "使用的具体公式",
    "hook_content": "视频中实际的勾子内容",
    "hook_timing": "勾子出现的时间段",
    "effectiveness_score": 8
  },
  "bgm_analysis": {
    "has_bgm": true,
    "bgm_type": "热门音乐/原创/无音乐",
    "music_style": "音乐风格",
    "emotion_match": "与内容情绪匹配度",
    "trend_alignment": "是否符合当前热门趋势"
  },
  "video_structure": {
    "category": "知识类/剧情类/测评类/生活类",
    "structure_pattern": "具体的结构模板",
    "time_breakdown": {
      "0-3s": "开头内容",
      "3-10s": "主体内容", 
      "10-15s": "结尾内容"
    }
  },
  "copywriting_strategy": {
    "title_elements": ["标题中的关键元素"],
    "interaction_guides": ["互动引导语"],
    "emotional_triggers": ["情绪触发词"]
  },
  "viral_elements": {
    "key_factors": ["主要爆款因素"],
    "uniqueness": "独特性分析",
    "shareability": "分享传播价值"
  },
  "template_summary": {
    "main_template": "主要模板类型",
    "success_probability": "85%",
    "replication_difficulty": "复制难度评估",
    "optimization_suggestions": ["具体优化建议"]
  }
}

请开始分析："""

    content_list.append({
        "type": "text",
        "text": template_analysis_prompt
    })
    
    # 初始化客户端
    client = OpenAI(
        api_key="EMPTY",
        base_url="http://localhost:8000/v1",
    )
    
    print(f"\n开始分析抖音视频模板...")
    print(f"Content项目数量: {len(content_list)}")
    print("="*60)
    
    start_time = time.time()
    
    # 发送请求
    completion = client.chat.completions.create(
        model="/root/autodl-tmp/llm",
        messages=[
            {
                "role": "system",
                "content": [{"type":"text","text": "You are a professional Douyin/TikTok viral video template analyzer."}]
            },
            {
                "role": "user",
                "content": content_list
            }
        ],
        stream=STREAM_MODE,
        stream_options={"include_usage": True} if STREAM_MODE else None,
    )
    
    # 处理流式响应
    if STREAM_MODE:
        full_response = ""
        usage_info = None
        
        print("🎯 抖音模板分析结果:")
        print("-" * 40)
        
        for chunk in completion:
            if chunk.choices:
                delta = chunk.choices[0].delta
                if delta.content:
                    full_response += delta.content
                    print(delta.content, end='', flush=True)
            else:
                usage_info = chunk.usage
        
        end_time = time.time()
        
        print("\n" + "="*60)
        print("✅ 分析完成!")
        print(f"⏱️ 耗时: {end_time - start_time:.2f} 秒")
        
        if usage_info:
            print(f"📊 Token使用: {usage_info}")
        
        # 保存结果
        if output_file:
            result_data = {
                "timestamp": datetime.now().isoformat(),
                "video_path": video_path,
                "analysis_result": full_response,
                "usage": str(usage_info) if usage_info else None,
                "processing_time": end_time - start_time
            }
            
            with open(output_file, 'w', encoding='utf-8') as f:
                json.dump(result_data, f, ensure_ascii=False, indent=2)
            
            print(f"💾 结果已保存到: {output_file}")
        
        return full_response
    
    else:
        result = completion.choices[0].message.content
        print("🎯 抖音模板分析结果:")
        print("="*50)
        print(result)
        return result

def main():
    """主函数"""
    
    # 配置文件路径
    video_path = "/root/autodl-tmp/hot_video_analyse/source/sample_demo_2.mp4"
    audio_path = "/root/autodl-tmp/hot_video_analyse/source/transcription/sample_demo_1_audio.wav"
    
    # 输出文件
    output_file = f"douyin_template_analysis_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json"
    
    # 执行分析
    result = analyze_douyin_template(
        video_path=video_path,
        audio_path=audio_path,
        output_file=output_file
    )
    
    print(f"\n{'='*60}")
    print("🎉 抖音热门视频模板分析完成!")

if __name__ == "__main__":
    main()