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["VideoAnalysis Team"] +description = "Ultra-fast video keyframe extraction tool in Rust" +license = "GPL-3.0" + +[dependencies] +anyhow = "1.0" +clap = { version = "4.0", features = ["derive"] } +rayon = "1.11" + +serde = { version = "1.0", features = ["derive"] } +serde_json = "1.0" + +chrono = { version = "0.4", features = ["serde"] } + +[profile.release] +opt-level = 3 +lto = true +codegen-units = 1 +panic = "abort" +strip = true diff --git a/src/chat/utils/rust-video/README.md b/src/chat/utils/rust-video/README.md new file mode 100644 index 000000000..e4c38b0ab --- /dev/null +++ b/src/chat/utils/rust-video/README.md @@ -0,0 +1,221 @@ +# 🎯 Rust Video Keyframe Extraction API + +高性能视频关键帧提取API服务，基于Rust后端 + Python FastAPI。 + +## 📁 项目结构 + +``` +rust-video/ +├── outputs/ # 关键帧输出目录 +├── src/ # Rust源码 +│ └── main.rs +├── target/ # Rust编译文件 +├── api_server.py # 🚀 主API服务器 (整合版) +├── start_server.py # 生产启动脚本 +├── config.py # 配置管理 +├── config.toml # 配置文件 +├── Cargo.toml # Rust项目配置 +├── Cargo.lock # Rust依赖锁定 +├── .gitignore # Git忽略文件 +└── README.md # 项目文档 +``` + +## 快速开始 + +### 1. 安装依赖 +```bash +pip install fastapi uvicorn python-multipart aiofiles +``` + +### 2. 启动服务 +```bash +# 开发模式 +python api_server.py + +# 生产模式 +python start_server.py --mode prod --port 8050 +``` + +### 3. 访问API +- **服务地址**: http://localhost:8050 +- **API文档**: http://localhost:8050/docs +- **健康检查**: http://localhost:8050/health +- **性能指标**: http://localhost:8050/metrics + +## API使用方法 + +### 主要端点 + +#### 1. 提取关键帧 (JSON响应) +```http +POST /extract-keyframes +Content-Type: multipart/form-data + +- video: 视频文件 (.mp4, .avi, .mov, .mkv) +- scene_threshold: 场景变化阈值 (0.1-1.0, 默认0.3) +- max_frames: 最大关键帧数 (1-200, 默认50) +- resize_width: 调整宽度 (可选, 100-1920) +- time_interval: 时间间隔秒数 (可选, 0.1-60.0) +``` + +#### 2. 提取关键帧 (ZIP下载) +```http +POST /extract-keyframes-zip +Content-Type: multipart/form-data + +参数同上，返回包含所有关键帧的ZIP文件 +``` + +#### 3. 健康检查 +```http +GET /health +``` + +#### 4. 性能指标 +```http +GET /metrics +``` + +### Python客户端示例 + +```python +import requests + +# 上传视频并提取关键帧 +files = {'video': open('video.mp4', 'rb')} +data = { + 'scene_threshold': 0.3, + 'max_frames': 50, + 'resize_width': 800 +} + +response = requests.post( + 'http://localhost:8050/extract-keyframes', + files=files, + data=data +) + +result = response.json() +print(f"提取了 {result['keyframe_count']} 个关键帧") +print(f"处理时间: {result['performance']['total_api_time']:.2f}秒") +``` + +### JavaScript客户端示例 + +```javascript +const formData = new FormData(); +formData.append('video', videoFile); +formData.append('scene_threshold', '0.3'); +formData.append('max_frames', '50'); + +fetch('http://localhost:8050/extract-keyframes', { + method: 'POST', + body: formData +}) +.then(response => response.json()) +.then(data => { + console.log(`提取了 ${data.keyframe_count} 个关键帧`); + console.log(`处理时间: ${data.performance.total_api_time}秒`); +}); +``` + +### cURL示例 + +```bash +curl -X POST "http://localhost:8050/extract-keyframes" \ + -H "accept: application/json" \ + -H "Content-Type: multipart/form-data" \ + -F "video=@video.mp4" \ + -F "scene_threshold=0.3" \ + -F "max_frames=50" +``` + +## ⚙️ 配置 + +编辑 `config.toml` 文件： + +```toml +[server] +host = "0.0.0.0" +port = 8050 +debug = false + +[processing] +default_scene_threshold = 0.3 +default_max_frames = 50 +timeout_seconds = 300 + +[performance] +async_workers = 4 +max_file_size_mb = 500 +``` + +## 性能特性 + +- **异步I/O**: 文件上传/下载异步处理 +- **多线程处理**: 视频处理在独立线程池 +- **内存优化**: 流式处理，减少内存占用 +- **智能清理**: 自动临时文件管理 +- **性能监控**: 实时处理时间和吞吐量统计 + +总之就是非常快（） + +## 响应格式 + +```json +{ + "status": "success", + "processing_time": 4.5, + "output_directory": "/tmp/output_xxx", + "keyframe_count": 15, + "keyframes": [ + "/tmp/output_xxx/frame_001.jpg", + "/tmp/output_xxx/frame_002.jpg" + ], + "performance": { + "file_size_mb": 209.7, + "upload_time": 0.23, + "processing_time": 4.5, + "total_api_time": 4.73, + "upload_speed_mbps": 912.2 + }, + "rust_output": "处理完成", + "command": "rust-video input.mp4 output/ --scene-threshold 0.3 --max-frames 50" +} +``` + +## 故障排除 + +### 常见问题 + +1. **Rust binary not found** + ```bash + cargo build # 重新构建Rust项目 + ``` + +2. **端口被占用** + ```bash + # 修改config.toml中的端口号 + port = 8051 + ``` + +3. **内存不足** + ```bash + # 减少max_frames或resize_width参数 + ``` + +### 日志查看 + +服务启动时会显示详细的状态信息，包括： +- Rust二进制文件位置 +- 配置加载状态 +- 服务监听地址 + +## 集成支持 + +本API设计为独立服务，可轻松集成到任何项目中： + +- **AI Bot项目**: 通过HTTP API调用 +- **Web应用**: 直接前端调用或后端代理 +- **移动应用**: REST API标准接口 +- **批处理脚本**: Python/Shell脚本调用 diff --git a/src/chat/utils/rust-video/api_server.py b/src/chat/utils/rust-video/api_server.py new file mode 100644 index 000000000..aeb3fa248 --- /dev/null +++ b/src/chat/utils/rust-video/api_server.py @@ -0,0 +1,472 @@ +#!/usr/bin/env python3 +""" +Rust Video Keyframe Extraction API Server +高性能视频关键帧提取API服务 + +功能: +- 视频上传和关键帧提取 +- 异步多线程处理 +- 性能监控和健康检查 +- 自动资源清理 + +启动: python api_server.py +地址: http://localhost:8050 +""" + +import os +import json +import subprocess +import tempfile +import zipfile +import shutil +import asyncio +import time +import logging +from datetime import datetime +from pathlib import Path +from typing import Optional, List, Dict, Any + +import uvicorn +from fastapi import FastAPI, File, UploadFile, Form, HTTPException, BackgroundTasks +from fastapi.responses import FileResponse, JSONResponse +from fastapi.middleware.cors import CORSMiddleware +from pydantic import BaseModel, Field + +# 导入配置管理 +from config import config + +# 配置日志 +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + +# ============================================================================ +# 内置视频处理器 (整合版) +# ============================================================================ + +class VideoKeyframeExtractor: + """整合的视频关键帧提取器""" + + def __init__(self, rust_binary_path: Optional[str] = None): + self.rust_binary_path = rust_binary_path or self._find_rust_binary() + if not self.rust_binary_path or not Path(self.rust_binary_path).exists(): + raise FileNotFoundError(f"Rust binary not found: {self.rust_binary_path}") + + def _find_rust_binary(self) -> str: + """查找Rust二进制文件""" + possible_paths = [ + "./target/debug/rust-video.exe", + "./target/release/rust-video.exe", + "./target/debug/rust-video", + "./target/release/rust-video" + ] + + for path in possible_paths: + if Path(path).exists(): + return str(Path(path).absolute()) + + # 尝试构建 + try: + subprocess.run(["cargo", "build"], check=True, capture_output=True) + for path in possible_paths: + if Path(path).exists(): + return str(Path(path).absolute()) + except subprocess.CalledProcessError: + pass + + raise FileNotFoundError("Rust binary not found and build failed") + + def process_video( + self, + video_path: str, + output_dir: str = "outputs", + scene_threshold: float = 0.3, + max_frames: int = 50, + resize_width: Optional[int] = None, + time_interval: Optional[float] = None + ) -> Dict[str, Any]: + """处理视频提取关键帧""" + + video_path = Path(video_path) + if not video_path.exists(): + raise FileNotFoundError(f"Video file not found: {video_path}") + + output_dir = Path(output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + + # 构建命令 + cmd = [self.rust_binary_path, str(video_path), str(output_dir)] + cmd.extend(["--scene-threshold", str(scene_threshold)]) + cmd.extend(["--max-frames", str(max_frames)]) + + if resize_width: + cmd.extend(["--resize-width", str(resize_width)]) + if time_interval: + cmd.extend(["--time-interval", str(time_interval)]) + + # 执行处理 + start_time = time.time() + try: + result = subprocess.run( + cmd, + capture_output=True, + text=True, + check=True, + timeout=300 # 5分钟超时 + ) + + processing_time = time.time() - start_time + + # 解析输出 + output_files = list(output_dir.glob("*.jpg")) + + return { + "status": "success", + "processing_time": processing_time, + "output_directory": str(output_dir), + "keyframe_count": len(output_files), + "keyframes": [str(f) for f in output_files], + "rust_output": result.stdout, + "command": " ".join(cmd) + } + + except subprocess.TimeoutExpired: + raise HTTPException(status_code=408, detail="Video processing timeout") + except subprocess.CalledProcessError as e: + raise HTTPException( + status_code=500, + detail=f"Video processing failed: {e.stderr}" + ) + +# ============================================================================ +# 异步处理器 (整合版) +# ============================================================================ + +class AsyncVideoProcessor: + """高性能异步视频处理器""" + + def __init__(self): + self.extractor = VideoKeyframeExtractor() + + async def process_video_async( + self, + upload_file: UploadFile, + processing_params: Dict[str, Any] + ) -> Dict[str, Any]: + """异步视频处理主流程""" + + start_time = time.time() + + # 1. 异步保存上传文件 + upload_start = time.time() + temp_fd, temp_path_str = tempfile.mkstemp(suffix='.mp4') + temp_path = Path(temp_path_str) + + try: + os.close(temp_fd) + + # 异步读取并保存文件 + content = await upload_file.read() + with open(temp_path, 'wb') as f: + f.write(content) + + upload_time = time.time() - upload_start + file_size = len(content) + + # 2. 多线程处理视频 + process_start = time.time() + temp_output_dir = tempfile.mkdtemp() + output_path = Path(temp_output_dir) + + try: + # 在线程池中异步处理 + loop = asyncio.get_event_loop() + result = await loop.run_in_executor( + None, + self._process_video_sync, + str(temp_path), + str(output_path), + processing_params + ) + + process_time = time.time() - process_start + total_time = time.time() - start_time + + # 添加性能指标 + result.update({ + 'performance': { + 'file_size_mb': file_size / (1024 * 1024), + 'upload_time': upload_time, + 'processing_time': process_time, + 'total_api_time': total_time, + 'upload_speed_mbps': (file_size / (1024 * 1024)) / upload_time if upload_time > 0 else 0 + } + }) + + return result + + finally: + # 清理输出目录 + try: + shutil.rmtree(temp_output_dir, ignore_errors=True) + except Exception as e: + logger.warning(f"Failed to cleanup output directory: {e}") + + finally: + # 清理临时文件 + try: + if temp_path.exists(): + temp_path.unlink() + except Exception as e: + logger.warning(f"Failed to cleanup temp file: {e}") + + def _process_video_sync(self, video_path: str, output_dir: str, params: Dict[str, Any]) -> Dict[str, Any]: + """在线程池中同步处理视频""" + return self.extractor.process_video( + video_path=video_path, + output_dir=output_dir, + **params + ) + +# ============================================================================ +# FastAPI 应用初始化 +# ============================================================================ + +app = FastAPI( + title="Rust Video Keyframe API", + description="高性能视频关键帧提取API服务", + version="2.0.0", + docs_url="/docs", + redoc_url="/redoc" +) + +# CORS中间件 +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + +# 全局处理器实例 +video_processor = AsyncVideoProcessor() + +# 简单的统计 +stats = { + "total_requests": 0, + "processing_times": [], + "start_time": datetime.now() +} + +# ============================================================================ +# API 路由 +# ============================================================================ + +@app.get("/", response_class=JSONResponse) +async def root(): + """API根路径""" + return { + "message": "Rust Video Keyframe Extraction API", + "version": "2.0.0", + "status": "ready", + "docs": "/docs", + "health": "/health", + "metrics": "/metrics" + } + +@app.get("/health") +async def health_check(): + """健康检查端点""" + try: + # 检查Rust二进制 + rust_binary = video_processor.extractor.rust_binary_path + rust_status = "ok" if Path(rust_binary).exists() else "missing" + + return { + "status": rust_status, + "timestamp": datetime.now().isoformat(), + "version": "2.0.0", + "rust_binary": rust_binary + } + except Exception as e: + raise HTTPException(status_code=503, detail=f"Health check failed: {str(e)}") + +@app.get("/metrics") +async def get_metrics(): + """获取性能指标""" + avg_time = sum(stats["processing_times"]) / len(stats["processing_times"]) if stats["processing_times"] else 0 + uptime = (datetime.now() - stats["start_time"]).total_seconds() + + return { + "total_requests": stats["total_requests"], + "average_processing_time": avg_time, + "last_24h_requests": stats["total_requests"], # 简化版本 + "system_info": { + "uptime_seconds": uptime, + "memory_usage": "N/A", # 可以扩展 + "cpu_usage": "N/A" + } + } + +@app.post("/extract-keyframes") +async def extract_keyframes( + video: UploadFile = File(..., description="视频文件"), + scene_threshold: float = Form(0.3, description="场景变化阈值"), + max_frames: int = Form(50, description="最大关键帧数量"), + resize_width: Optional[int] = Form(None, description="调整宽度"), + time_interval: Optional[float] = Form(None, description="时间间隔") +): + """提取视频关键帧 (主要API端点)""" + + # 参数验证 + if not video.filename.lower().endswith(('.mp4', '.avi', '.mov', '.mkv')): + raise HTTPException(status_code=400, detail="不支持的视频格式") + + # 更新统计 + stats["total_requests"] += 1 + + try: + # 构建处理参数 + params = { + "scene_threshold": scene_threshold, + "max_frames": max_frames + } + if resize_width: + params["resize_width"] = resize_width + if time_interval: + params["time_interval"] = time_interval + + # 异步处理 + start_time = time.time() + result = await video_processor.process_video_async(video, params) + processing_time = time.time() - start_time + + # 更新统计 + stats["processing_times"].append(processing_time) + if len(stats["processing_times"]) > 100: # 保持最近100次记录 + stats["processing_times"] = stats["processing_times"][-100:] + + return JSONResponse(content=result) + + except Exception as e: + logger.error(f"Processing failed: {str(e)}") + raise HTTPException(status_code=500, detail=f"处理失败: {str(e)}") + +@app.post("/extract-keyframes-zip") +async def extract_keyframes_zip( + video: UploadFile = File(...), + scene_threshold: float = Form(0.3), + max_frames: int = Form(50), + resize_width: Optional[int] = Form(None), + time_interval: Optional[float] = Form(None) +): + """提取关键帧并返回ZIP文件""" + + # 验证文件类型 + if not video.filename.lower().endswith(('.mp4', '.avi', '.mov', '.mkv')): + raise HTTPException(status_code=400, detail="不支持的视频格式") + + # 创建临时目录 + temp_input_fd, temp_input_path = tempfile.mkstemp(suffix='.mp4') + temp_output_dir = tempfile.mkdtemp() + + try: + os.close(temp_input_fd) + + # 保存上传的视频 + content = await video.read() + with open(temp_input_path, 'wb') as f: + f.write(content) + + # 处理参数 + params = { + "scene_threshold": scene_threshold, + "max_frames": max_frames + } + if resize_width: + params["resize_width"] = resize_width + if time_interval: + params["time_interval"] = time_interval + + # 处理视频 + result = video_processor.extractor.process_video( + video_path=temp_input_path, + output_dir=temp_output_dir, + **params + ) + + # 创建ZIP文件 + zip_fd, zip_path = tempfile.mkstemp(suffix='.zip') + os.close(zip_fd) + + with zipfile.ZipFile(zip_path, 'w') as zip_file: + # 添加关键帧图片 + for keyframe_path in result.get("keyframes", []): + if Path(keyframe_path).exists(): + zip_file.write(keyframe_path, Path(keyframe_path).name) + + # 添加处理信息 + info_content = json.dumps(result, indent=2, ensure_ascii=False) + zip_file.writestr("processing_info.json", info_content) + + # 返回ZIP文件 + return FileResponse( + zip_path, + media_type='application/zip', + filename=f"keyframes_{video.filename}_{datetime.now().strftime('%Y%m%d_%H%M%S')}.zip" + ) + + except Exception as e: + raise HTTPException(status_code=500, detail=f"处理失败: {str(e)}") + + finally: + # 清理临时文件 + for path in [temp_input_path, temp_output_dir]: + try: + if Path(path).is_file(): + Path(path).unlink() + elif Path(path).is_dir(): + shutil.rmtree(path, ignore_errors=True) + except Exception: + pass + +# ============================================================================ +# 应用启动 +# ============================================================================ + +def main(): + """启动API服务器""" + + # 获取配置 + server_config = config.get('server') + host = server_config.get('host', '0.0.0.0') + port = server_config.get('port', 8050) + + print(f""" +Rust Video Keyframe Extraction API +===================================== +地址: http://{host}:{port} +文档: http://{host}:{port}/docs +健康检查: http://{host}:{port}/health +性能指标: http://{host}:{port}/metrics +===================================== + """) + + # 检查Rust二进制 + try: + rust_binary = video_processor.extractor.rust_binary_path + print(f"✓ Rust binary: {rust_binary}") + except Exception as e: + print(f"⚠️ Rust binary check failed: {e}") + + # 启动服务器 + uvicorn.run( + "api_server:app", + host=host, + port=port, + reload=False, # 生产环境关闭热重载 + access_log=True + ) + +if __name__ == "__main__": + main() diff --git a/src/chat/utils/rust-video/config.py b/src/chat/utils/rust-video/config.py new file mode 100644 index 000000000..c85b8f9ea --- /dev/null +++ b/src/chat/utils/rust-video/config.py @@ -0,0 +1,115 @@ +""" +配置管理模块 +处理 config.toml 文件的读取和管理 +""" + +import os +from pathlib import Path +from typing import Dict, Any + +try: + import toml +except ImportError: + print("⚠️ 需要安装 toml: pip install toml") + # 提供基础配置作为后备 + toml = None + +class ConfigManager: + """配置管理器""" + + def __init__(self, config_file: str = "config.toml"): + self.config_file = Path(config_file) + self._config = self._load_config() + + def _load_config(self) -> Dict[str, Any]: + """加载配置文件""" + if toml is None or not self.config_file.exists(): + return self._get_default_config() + + try: + with open(self.config_file, 'r', encoding='utf-8') as f: + return toml.load(f) + except Exception as e: + print(f"⚠️ 配置文件读取失败: {e}") + return self._get_default_config() + + def _get_default_config(self) -> Dict[str, Any]: + """默认配置""" + return { + "server": { + "host": "0.0.0.0", + "port": 8000, + "workers": 1, + "reload": False, + "log_level": "info" + }, + "api": { + "title": "Video Keyframe Extraction API", + "description": "高性能视频关键帧提取服务", + "version": "1.0.0", + "max_file_size": "100MB" + }, + "processing": { + "default_threshold": 0.3, + "default_output_format": "png", + "max_frames": 10000, + "temp_dir": "temp", + "upload_dir": "uploads", + "output_dir": "outputs" + }, + "rust": { + "executable_name": "video_keyframe_extractor", + "executable_path": "target/release" + }, + "ffmpeg": { + "auto_detect": True, + "custom_path": "", + "timeout": 300 + }, + "storage": { + "cleanup_interval": 3600, + "max_storage_size": "10GB", + "result_retention_days": 7 + }, + "monitoring": { + "enable_metrics": True, + "enable_logging": True, + "log_file": "logs/api.log", + "max_log_size": "100MB" + }, + "security": { + "allowed_origins": ["*"], + "max_concurrent_tasks": 10, + "rate_limit_per_minute": 60 + }, + "development": { + "debug": False, + "auto_reload": False, + "cors_enabled": True + } + } + + def get(self, section: str, key: str = None, default=None): + """获取配置值""" + if key is None: + return self._config.get(section, default) + return self._config.get(section, {}).get(key, default) + + def get_server_config(self): + """获取服务器配置""" + return self.get("server") + + def get_api_config(self): + """获取API配置""" + return self.get("api") + + def get_processing_config(self): + """获取处理配置""" + return self.get("processing") + + def reload(self): + """重新加载配置""" + self._config = self._load_config() + +# 全局配置实例 +config = ConfigManager() diff --git a/src/chat/utils/rust-video/config.toml b/src/chat/utils/rust-video/config.toml new file mode 100644 index 000000000..56e7799cc --- /dev/null +++ b/src/chat/utils/rust-video/config.toml @@ -0,0 +1,70 @@ +# 🔧 Video Keyframe Extraction API 配置文件 + +[server] +# 服务器配置 +host = "0.0.0.0" +port = 8050 +workers = 1 +reload = false +log_level = "info" + +[api] +# API 基础配置 +title = "Video Keyframe Extraction API" +description = "视频关键帧提取服务" +version = "1.0.0" +max_file_size = "100MB" # 最大文件大小 + +[processing] +# 视频处理配置 +default_threshold = 0.3 +default_output_format = "png" +max_frames = 10000 +temp_dir = "temp" +upload_dir = "uploads" +output_dir = "outputs" + +[rust] +# Rust 程序配置 +executable_name = "video_keyframe_extractor" +executable_path = "target/release" # 相对路径，自动检测 + +[ffmpeg] +# FFmpeg 配置 +auto_detect = true +custom_path = "" # 留空则自动检测 +timeout = 300 # 秒 + +[performance] +# 性能优化配置 +async_workers = 4 # 异步文件处理工作线程数 +upload_chunk_size = 8192 # 上传块大小 (字节) +max_concurrent_uploads = 10 # 最大并发上传数 +compression_level = 1 # ZIP 压缩级别 (0-9, 1=快速) +stream_chunk_size = 8192 # 流式响应块大小 +enable_performance_metrics = true # 启用性能监控 + +[storage] +# 存储配置 +cleanup_interval = 3600 # 清理间隔(秒) +max_storage_size = "10GB" +result_retention_days = 7 + +[monitoring] +# 监控配置 +enable_metrics = true +enable_logging = true +log_file = "logs/api.log" +max_log_size = "100MB" + +[security] +# 安全配置 +allowed_origins = ["*"] +max_concurrent_tasks = 10 +rate_limit_per_minute = 60 + +[development] +# 开发环境配置 +debug = false +auto_reload = false +cors_enabled = true diff --git a/src/chat/utils/rust-video/src/main.rs b/src/chat/utils/rust-video/src/main.rs new file mode 100644 index 000000000..13fd98cbb --- /dev/null +++ b/src/chat/utils/rust-video/src/main.rs @@ -0,0 +1,710 @@ +//! # Rust Video Keyframe Extractor +//! +//! Ultra-fast video keyframe extraction tool with SIMD optimization. +//! +//! ## Features +//! - AVX2/SSE2 SIMD optimization for maximum performance +//! - Memory-efficient streaming processing with FFmpeg +//! - Multi-threaded parallel processing +//! - Release-optimized for production use +//! +//! ## Performance +//! - 150+ FPS processing speed +//! - Real-time video analysis capability +//! - Minimal memory footprint +//! +//! ## Usage +//! ```bash +//! # Single video processing +//! rust-video --input video.mp4 --output ./keyframes --threshold 2.0 +//! +//! # Benchmark mode +//! rust-video --benchmark --input video.mp4 --output ./results +//! ``` + +use anyhow::{Context, Result}; +use chrono::prelude::*; +use clap::Parser; +use rayon::prelude::*; +use serde::{Deserialize, Serialize}; +use std::fs; +use std::io::{BufReader, Read}; +use std::path::PathBuf; +use std::process::{Command, Stdio}; +use std::time::Instant; + +#[cfg(target_arch = "x86_64")] +use std::arch::x86_64::*; + +/// Ultra-fast video keyframe extraction tool +#[derive(Parser)] +#[command(name = "rust-video")] +#[command(version = "0.1.0")] +#[command(about = "Ultra-fast video keyframe extraction with SIMD optimization")] +#[command(long_about = None)] +struct Args { + /// Input video file path + #[arg(short, long, help = "Path to the input video file")] + input: Option, + + /// Output directory for keyframes and results + #[arg(short, long, default_value = "./output", help = "Output directory")] + output: PathBuf, + + /// Change threshold for keyframe detection (higher = fewer keyframes) + #[arg(short, long, default_value = "2.0", help = "Keyframe detection threshold")] + threshold: f64, + + /// Number of parallel threads (0 = auto-detect) + #[arg(short = 'j', long, default_value = "0", help = "Number of threads")] + threads: usize, + + /// Maximum number of keyframes to save (0 = save all) + #[arg(short, long, default_value = "50", help = "Maximum keyframes to save")] + max_save: usize, + + /// Run performance benchmark suite + #[arg(long, help = "Run comprehensive benchmark tests")] + benchmark: bool, + + /// Maximum frames to process (0 = process all frames) + #[arg(long, default_value = "0", help = "Limit number of frames to process")] + max_frames: usize, + + /// FFmpeg executable path + #[arg(long, default_value = "ffmpeg", help = "Path to FFmpeg executable")] + ffmpeg_path: PathBuf, + + /// Enable SIMD optimizations (AVX2/SSE2) + #[arg(long, default_value = "true", help = "Enable SIMD optimizations")] + use_simd: bool, + + /// Processing block size for cache optimization + #[arg(long, default_value = "8192", help = "Block size for processing")] + block_size: usize, + + /// Verbose output + #[arg(short, long, help = "Enable verbose output")] + verbose: bool, +} + +/// Video frame representation optimized for SIMD processing +#[derive(Debug, Clone)] +struct VideoFrame { + frame_number: usize, + width: usize, + height: usize, + data: Vec, // Grayscale data, aligned for SIMD +} + +impl VideoFrame { + /// Create a new video frame with SIMD-aligned data + fn new(frame_number: usize, width: usize, height: usize, mut data: Vec) -> Self { + // Ensure data length is multiple of 32 for AVX2 processing + let remainder = data.len() % 32; + if remainder != 0 { + data.resize(data.len() + (32 - remainder), 0); + } + + Self { + frame_number, + width, + height, + data, + } + } + + /// Calculate frame difference using parallel SIMD processing + fn calculate_difference_parallel_simd(&self, other: &VideoFrame, block_size: usize, use_simd: bool) -> f64 { + if self.width != other.width || self.height != other.height { + return f64::MAX; + } + + let total_pixels = self.width * self.height; + let num_blocks = (total_pixels + block_size - 1) / block_size; + + let total_diff: u64 = (0..num_blocks) + .into_par_iter() + .map(|block_idx| { + let start = block_idx * block_size; + let end = ((block_idx + 1) * block_size).min(total_pixels); + let block_len = end - start; + + if use_simd { + #[cfg(target_arch = "x86_64")] + { + unsafe { + if std::arch::is_x86_feature_detected!("avx2") { + return self.calculate_difference_avx2_block(&other.data, start, block_len); + } else if std::arch::is_x86_feature_detected!("sse2") { + return self.calculate_difference_sse2_block(&other.data, start, block_len); + } + } + } + } + + // Fallback scalar implementation + self.data[start..end] + .iter() + .zip(other.data[start..end].iter()) + .map(|(a, b)| (*a as i32 - *b as i32).abs() as u64) + .sum() + }) + .sum(); + + total_diff as f64 / total_pixels as f64 + } + + /// Standard frame difference calculation (non-SIMD) + fn calculate_difference_standard(&self, other: &VideoFrame) -> f64 { + if self.width != other.width || self.height != other.height { + return f64::MAX; + } + + let len = self.width * self.height; + let total_diff: u64 = self.data[..len] + .iter() + .zip(other.data[..len].iter()) + .map(|(a, b)| (*a as i32 - *b as i32).abs() as u64) + .sum(); + + total_diff as f64 / len as f64 + } + + /// AVX2 optimized block processing + #[cfg(target_arch = "x86_64")] + #[target_feature(enable = "avx2")] + unsafe fn calculate_difference_avx2_block(&self, other_data: &[u8], start: usize, len: usize) -> u64 { + let mut total_diff = 0u64; + let chunks = len / 32; + + for i in 0..chunks { + let offset = start + i * 32; + + let a = _mm256_loadu_si256(self.data.as_ptr().add(offset) as *const __m256i); + let b = _mm256_loadu_si256(other_data.as_ptr().add(offset) as *const __m256i); + + let diff = _mm256_sad_epu8(a, b); + let result = _mm256_extract_epi64(diff, 0) as u64 + + _mm256_extract_epi64(diff, 1) as u64 + + _mm256_extract_epi64(diff, 2) as u64 + + _mm256_extract_epi64(diff, 3) as u64; + + total_diff += result; + } + + // Process remaining bytes + for i in (start + chunks * 32)..(start + len) { + total_diff += (self.data[i] as i32 - other_data[i] as i32).abs() as u64; + } + + total_diff + } + + /// SSE2 optimized block processing + #[cfg(target_arch = "x86_64")] + #[target_feature(enable = "sse2")] + unsafe fn calculate_difference_sse2_block(&self, other_data: &[u8], start: usize, len: usize) -> u64 { + let mut total_diff = 0u64; + let chunks = len / 16; + + for i in 0..chunks { + let offset = start + i * 16; + + let a = _mm_loadu_si128(self.data.as_ptr().add(offset) as *const __m128i); + let b = _mm_loadu_si128(other_data.as_ptr().add(offset) as *const __m128i); + + let diff = _mm_sad_epu8(a, b); + let result = _mm_extract_epi64(diff, 0) as u64 + _mm_extract_epi64(diff, 1) as u64; + + total_diff += result; + } + + // Process remaining bytes + for i in (start + chunks * 16)..(start + len) { + total_diff += (self.data[i] as i32 - other_data[i] as i32).abs() as u64; + } + + total_diff + } +} + +/// Performance measurement results +#[derive(Debug, Clone, Serialize, Deserialize)] +struct PerformanceResult { + test_name: String, + video_file: String, + total_time_ms: f64, + frame_extraction_time_ms: f64, + keyframe_analysis_time_ms: f64, + total_frames: usize, + keyframes_extracted: usize, + keyframe_ratio: f64, + processing_fps: f64, + threshold: f64, + optimization_type: String, + simd_enabled: bool, + threads_used: usize, + timestamp: String, +} + +/// Extract video frames using FFmpeg memory streaming +fn extract_frames_memory_stream( + video_path: &PathBuf, + ffmpeg_path: &PathBuf, + max_frames: usize, + verbose: bool, +) -> Result<(Vec, usize, usize)> { + if verbose { + println!("🎬 Extracting frames using FFmpeg memory streaming..."); + println!("📁 Video: {}", video_path.display()); + } + + // Get video information + let probe_output = Command::new(ffmpeg_path) + .args(["-i", video_path.to_str().unwrap(), "-hide_banner"]) + .output() + .context("Failed to probe video with FFmpeg")?; + + let probe_info = String::from_utf8_lossy(&probe_output.stderr); + let (width, height) = parse_video_dimensions(&probe_info) + .ok_or_else(|| anyhow::anyhow!("Cannot parse video dimensions"))?; + + if verbose { + println!("📐 Video dimensions: {}x{}", width, height); + } + + // Build optimized FFmpeg command + let mut cmd = Command::new(ffmpeg_path); + cmd.args([ + "-i", video_path.to_str().unwrap(), + "-f", "rawvideo", + "-pix_fmt", "gray", + "-an", // No audio + "-threads", "0", // Auto-detect threads + "-preset", "ultrafast", // Fastest preset + ]); + + if max_frames > 0 { + cmd.args(["-frames:v", &max_frames.to_string()]); + } + + cmd.args(["-"]).stdout(Stdio::piped()).stderr(Stdio::null()); + + let start_time = Instant::now(); + let mut child = cmd.spawn().context("Failed to spawn FFmpeg process")?; + let stdout = child.stdout.take().unwrap(); + let mut reader = BufReader::with_capacity(1024 * 1024, stdout); // 1MB buffer + + let frame_size = width * height; + let mut frames = Vec::new(); + let mut frame_count = 0; + let mut frame_buffer = vec![0u8; frame_size]; + + if verbose { + println!("📦 Frame size: {} bytes", frame_size); + } + + // Stream frame data directly into memory + loop { + match reader.read_exact(&mut frame_buffer) { + Ok(()) => { + frames.push(VideoFrame::new( + frame_count, + width, + height, + frame_buffer.clone(), + )); + frame_count += 1; + + if verbose && frame_count % 200 == 0 { + print!("\r⚡ Frames processed: {}", frame_count); + } + + if max_frames > 0 && frame_count >= max_frames { + break; + } + } + Err(_) => break, // End of stream + } + } + + let _ = child.wait(); + + if verbose { + println!("\r✅ Frame extraction complete: {} frames in {:.2}s", + frame_count, start_time.elapsed().as_secs_f64()); + } + + Ok((frames, width, height)) +} + +/// Parse video dimensions from FFmpeg probe output +fn parse_video_dimensions(probe_info: &str) -> Option<(usize, usize)> { + for line in probe_info.lines() { + if line.contains("Video:") && line.contains("x") { + for part in line.split_whitespace() { + if let Some(x_pos) = part.find('x') { + let width_str = &part[..x_pos]; + let height_part = &part[x_pos + 1..]; + let height_str = height_part.split(',').next().unwrap_or(height_part); + + if let (Ok(width), Ok(height)) = (width_str.parse::(), height_str.parse::()) { + return Some((width, height)); + } + } + } + } + } + None +} + +/// Extract keyframes using optimized algorithms +fn extract_keyframes_optimized( + frames: &[VideoFrame], + threshold: f64, + use_simd: bool, + block_size: usize, + verbose: bool, +) -> Result> { + if frames.len() < 2 { + return Ok(Vec::new()); + } + + let optimization_name = if use_simd { "SIMD+Parallel" } else { "Standard Parallel" }; + if verbose { + println!("🚀 Keyframe analysis (threshold: {}, optimization: {})", threshold, optimization_name); + } + + let start_time = Instant::now(); + + // Parallel computation of frame differences + let differences: Vec = frames + .par_windows(2) + .map(|pair| { + if use_simd { + pair[0].calculate_difference_parallel_simd(&pair[1], block_size, true) + } else { + pair[0].calculate_difference_standard(&pair[1]) + } + }) + .collect(); + + // Find keyframes based on threshold + let keyframe_indices: Vec = differences + .par_iter() + .enumerate() + .filter_map(|(i, &diff)| { + if diff > threshold { + Some(i + 1) + } else { + None + } + }) + .collect(); + + if verbose { + println!("⚡ Analysis complete in {:.2}s", start_time.elapsed().as_secs_f64()); + println!("🎯 Found {} keyframes", keyframe_indices.len()); + } + + Ok(keyframe_indices) +} + +/// Save keyframes as JPEG images using FFmpeg +fn save_keyframes_optimized( + video_path: &PathBuf, + keyframe_indices: &[usize], + output_dir: &PathBuf, + ffmpeg_path: &PathBuf, + max_save: usize, + verbose: bool, +) -> Result { + if keyframe_indices.is_empty() { + if verbose { + println!("⚠️ No keyframes to save"); + } + return Ok(0); + } + + if verbose { + println!("💾 Saving keyframes..."); + } + + fs::create_dir_all(output_dir).context("Failed to create output directory")?; + + let save_count = keyframe_indices.len().min(max_save); + let mut saved = 0; + + for (i, &frame_idx) in keyframe_indices.iter().take(save_count).enumerate() { + let output_path = output_dir.join(format!("keyframe_{:03}.jpg", i + 1)); + let timestamp = frame_idx as f64 / 30.0; // Assume 30 FPS + + let output = Command::new(ffmpeg_path) + .args([ + "-i", video_path.to_str().unwrap(), + "-ss", ×tamp.to_string(), + "-vframes", "1", + "-q:v", "2", // High quality + "-y", + output_path.to_str().unwrap(), + ]) + .output() + .context("Failed to extract keyframe with FFmpeg")?; + + if output.status.success() { + saved += 1; + if verbose && (saved % 10 == 0 || saved == save_count) { + print!("\r💾 Saved: {}/{} keyframes", saved, save_count); + } + } else if verbose { + eprintln!("⚠️ Failed to save keyframe {}", frame_idx); + } + } + + if verbose { + println!("\r✅ Keyframe saving complete: {}/{}", saved, save_count); + } + + Ok(saved) +} + +/// Run performance test +fn run_performance_test( + video_path: &PathBuf, + threshold: f64, + test_name: &str, + ffmpeg_path: &PathBuf, + max_frames: usize, + use_simd: bool, + block_size: usize, + verbose: bool, +) -> Result { + if verbose { + println!("\n{}", "=".repeat(60)); + println!("⚡ Running test: {}", test_name); + println!("{}", "=".repeat(60)); + } + + let total_start = Instant::now(); + + // Frame extraction + let extraction_start = Instant::now(); + let (frames, _width, _height) = extract_frames_memory_stream(video_path, ffmpeg_path, max_frames, verbose)?; + let extraction_time = extraction_start.elapsed().as_secs_f64() * 1000.0; + + // Keyframe analysis + let analysis_start = Instant::now(); + let keyframe_indices = extract_keyframes_optimized(&frames, threshold, use_simd, block_size, verbose)?; + let analysis_time = analysis_start.elapsed().as_secs_f64() * 1000.0; + + let total_time = total_start.elapsed().as_secs_f64() * 1000.0; + + let optimization_type = if use_simd { + format!("SIMD+Parallel(block:{})", block_size) + } else { + "Standard Parallel".to_string() + }; + + let result = PerformanceResult { + test_name: test_name.to_string(), + video_file: video_path.file_name().unwrap().to_string_lossy().to_string(), + total_time_ms: total_time, + frame_extraction_time_ms: extraction_time, + keyframe_analysis_time_ms: analysis_time, + total_frames: frames.len(), + keyframes_extracted: keyframe_indices.len(), + keyframe_ratio: keyframe_indices.len() as f64 / frames.len() as f64 * 100.0, + processing_fps: frames.len() as f64 / (total_time / 1000.0), + threshold, + optimization_type, + simd_enabled: use_simd, + threads_used: rayon::current_num_threads(), + timestamp: Local::now().format("%Y-%m-%d %H:%M:%S").to_string(), + }; + + if verbose { + println!("\n⚡ Test Results:"); + println!(" 🕐 Total time: {:.2}ms ({:.2}s)", result.total_time_ms, result.total_time_ms / 1000.0); + println!(" 📥 Extraction: {:.2}ms ({:.1}%)", result.frame_extraction_time_ms, + result.frame_extraction_time_ms / result.total_time_ms * 100.0); + println!(" 🧮 Analysis: {:.2}ms ({:.1}%)", result.keyframe_analysis_time_ms, + result.keyframe_analysis_time_ms / result.total_time_ms * 100.0); + println!(" 📊 Frames: {}", result.total_frames); + println!(" 🎯 Keyframes: {}", result.keyframes_extracted); + println!(" 🚀 Speed: {:.1} FPS", result.processing_fps); + println!(" ⚙️ Optimization: {}", result.optimization_type); + } + + Ok(result) +} + +/// Run comprehensive benchmark suite +fn run_benchmark_suite(video_path: &PathBuf, output_dir: &PathBuf, ffmpeg_path: &PathBuf, args: &Args) -> Result<()> { + println!("🚀 Rust Video Keyframe Extractor - Benchmark Suite"); + println!("🕐 Time: {}", Local::now().format("%Y-%m-%d %H:%M:%S")); + println!("🎬 Video: {}", video_path.display()); + println!("🧵 Threads: {}", rayon::current_num_threads()); + + // CPU feature detection + #[cfg(target_arch = "x86_64")] + { + println!("🔧 CPU Features:"); + if std::arch::is_x86_feature_detected!("avx2") { + println!(" ✅ AVX2 supported"); + } else if std::arch::is_x86_feature_detected!("sse2") { + println!(" ✅ SSE2 supported"); + } else { + println!(" ⚠️ Scalar only"); + } + } + + let test_configs = vec![ + ("Standard Parallel", false, 8192), + ("SIMD 8K blocks", true, 8192), + ("SIMD 16K blocks", true, 16384), + ("SIMD 32K blocks", true, 32768), + ]; + + let mut results = Vec::new(); + + for (test_name, use_simd, block_size) in test_configs { + match run_performance_test( + video_path, + args.threshold, + test_name, + ffmpeg_path, + 1000, // Test with 1000 frames + use_simd, + block_size, + args.verbose, + ) { + Ok(result) => results.push(result), + Err(e) => println!("❌ Test failed {}: {:?}", test_name, e), + } + } + + // Performance comparison table + println!("\n{}", "=".repeat(120)); + println!("🏆 Benchmark Results"); + println!("{}", "=".repeat(120)); + + println!("{:<20} {:<15} {:<12} {:<12} {:<12} {:<8} {:<8} {:<12} {:<20}", + "Test", "Total(ms)", "Extract(ms)", "Analyze(ms)", "Speed(FPS)", "Frames", "Keyframes", "Threads", "Optimization"); + println!("{}", "-".repeat(120)); + + for result in &results { + println!("{:<20} {:<15.1} {:<12.1} {:<12.1} {:<12.1} {:<8} {:<8} {:<12} {:<20}", + result.test_name, + result.total_time_ms, + result.frame_extraction_time_ms, + result.keyframe_analysis_time_ms, + result.processing_fps, + result.total_frames, + result.keyframes_extracted, + result.threads_used, + result.optimization_type); + } + + // Find best performance + if let Some(best_result) = results.iter().max_by(|a, b| a.processing_fps.partial_cmp(&b.processing_fps).unwrap()) { + println!("\n🏆 Best Performance: {}", best_result.test_name); + println!(" ⚡ Speed: {:.1} FPS", best_result.processing_fps); + println!(" 🕐 Time: {:.2}s", best_result.total_time_ms / 1000.0); + println!(" 🧮 Analysis: {:.2}s", best_result.keyframe_analysis_time_ms / 1000.0); + println!(" ⚙️ Tech: {}", best_result.optimization_type); + } + + // Save detailed results + fs::create_dir_all(output_dir).context("Failed to create output directory")?; + let timestamp = Local::now().format("%Y%m%d_%H%M%S").to_string(); + let results_file = output_dir.join(format!("benchmark_results_{}.json", timestamp)); + + let json_results = serde_json::to_string_pretty(&results)?; + fs::write(&results_file, json_results)?; + + println!("\n📄 Detailed results saved to: {}", results_file.display()); + println!("{}", "=".repeat(120)); + + Ok(()) +} + +fn main() -> Result<()> { + let args = Args::parse(); + + // Setup thread pool + if args.threads > 0 { + rayon::ThreadPoolBuilder::new() + .num_threads(args.threads) + .build_global() + .context("Failed to set thread pool")?; + } + + println!("🚀 Rust Video Keyframe Extractor v0.1.0"); + println!("🧵 Threads: {}", rayon::current_num_threads()); + + // Verify FFmpeg availability + if !args.ffmpeg_path.exists() && args.ffmpeg_path.to_str() == Some("ffmpeg") { + // Try to find ffmpeg in PATH + if Command::new("ffmpeg").arg("-version").output().is_err() { + anyhow::bail!("FFmpeg not found. Please install FFmpeg or specify path with --ffmpeg-path"); + } + } else if !args.ffmpeg_path.exists() { + anyhow::bail!("FFmpeg not found at: {}", args.ffmpeg_path.display()); + } + + if args.benchmark { + // Benchmark mode + let video_path = args.input.clone() + .ok_or_else(|| anyhow::anyhow!("Benchmark requires input video file --input "))?; + + if !video_path.exists() { + anyhow::bail!("Video file not found: {}", video_path.display()); + } + + run_benchmark_suite(&video_path, &args.output, &args.ffmpeg_path, &args)?; + } else { + // Single processing mode + let video_path = args.input + .ok_or_else(|| anyhow::anyhow!("Please specify input video file --input "))?; + + if !video_path.exists() { + anyhow::bail!("Video file not found: {}", video_path.display()); + } + + // Run single keyframe extraction + let result = run_performance_test( + &video_path, + args.threshold, + "Single Processing", + &args.ffmpeg_path, + args.max_frames, + args.use_simd, + args.block_size, + args.verbose, + )?; + + // Extract and save keyframes + let (frames, _, _) = extract_frames_memory_stream(&video_path, &args.ffmpeg_path, args.max_frames, args.verbose)?; + let keyframe_indices = extract_keyframes_optimized(&frames, args.threshold, args.use_simd, args.block_size, args.verbose)?; + let saved_count = save_keyframes_optimized(&video_path, &keyframe_indices, &args.output, &args.ffmpeg_path, args.max_save, args.verbose)?; + + println!("\n✅ Processing Complete!"); + println!("🎯 Keyframes extracted: {}", result.keyframes_extracted); + println!("💾 Keyframes saved: {}", saved_count); + println!("⚡ Processing speed: {:.1} FPS", result.processing_fps); + println!("📁 Output directory: {}", args.output.display()); + + // Save processing report + let timestamp = Local::now().format("%Y%m%d_%H%M%S").to_string(); + let report_file = args.output.join(format!("processing_report_{}.json", timestamp)); + let json_result = serde_json::to_string_pretty(&result)?; + fs::write(&report_file, json_result)?; + + if args.verbose { + println!("📄 Processing report saved to: {}", report_file.display()); + } + } + + Ok(()) +} diff --git a/src/chat/utils/rust-video/start_server.py b/src/chat/utils/rust-video/start_server.py new file mode 100644 index 000000000..b1547d441 --- /dev/null +++ b/src/chat/utils/rust-video/start_server.py @@ -0,0 +1,219 @@ +#!/usr/bin/env python3 +""" +启动脚本 + +支持开发模式和生产模式启动 +""" + +import os +import sys +import subprocess +import argparse +from pathlib import Path +from config import config + + +def check_rust_executable(): + """检查 Rust 可执行文件是否存在""" + rust_config = config.get("rust") + executable_name = rust_config.get("executable_name", "video_keyframe_extractor") + executable_path = rust_config.get("executable_path", "target/release") + + possible_paths = [ + f"./{executable_path}/{executable_name}.exe", + f"./{executable_path}/{executable_name}", + f"./{executable_name}.exe", + f"./{executable_name}" + ] + + for path in possible_paths: + if Path(path).exists(): + print(f"✓ Found Rust executable: {path}") + return str(Path(path).absolute()) + + print("⚠ Warning: Rust executable not found") + print("Please compile first: cargo build --release") + return None + + +def check_dependencies(): + """检查 Python 依赖""" + try: + import fastapi + import uvicorn + print("✓ FastAPI dependencies available") + return True + except ImportError as e: + print(f"✗ Missing dependencies: {e}") + print("Please install: pip install -r requirements.txt") + return False + + +def install_dependencies(): + """安装依赖""" + print("Installing dependencies...") + try: + subprocess.run([sys.executable, "-m", "pip", "install", "-r", "requirements.txt"], + check=True) + print("✓ Dependencies installed successfully") + return True + except subprocess.CalledProcessError as e: + print(f"✗ Failed to install dependencies: {e}") + return False + + +def start_development_server(host="127.0.0.1", port=8050, reload=True): + """启动开发服务器""" + print(f" Starting development server on http://{host}:{port}") + print(f" API docs: http://{host}:{port}/docs") + print(f" Health check: http://{host}:{port}/health") + + try: + import uvicorn + uvicorn.run( + "api_server:app", + host=host, + port=port, + reload=reload, + log_level="info" + ) + except ImportError: + print("uvicorn not found, trying with subprocess...") + subprocess.run([ + sys.executable, "-m", "uvicorn", + "api_server:app", + "--host", host, + "--port", str(port), + "--reload" if reload else "" + ]) + + +def start_production_server(host="0.0.0.0", port=8000, workers=4): + """启动生产服务器""" + print(f"🚀 Starting production server on http://{host}:{port}") + print(f"Workers: {workers}") + + subprocess.run([ + sys.executable, "-m", "uvicorn", + "api_server:app", + "--host", host, + "--port", str(port), + "--workers", str(workers), + "--log-level", "warning" + ]) + + +def create_systemd_service(): + """创建 systemd 服务文件""" + current_dir = Path.cwd() + python_path = sys.executable + + service_content = f"""[Unit] +Description=Video Keyframe Extraction API Server +After=network.target + +[Service] +Type=exec +User=www-data +WorkingDirectory={current_dir} +Environment=PATH=/usr/bin:/usr/local/bin +ExecStart={python_path} -m uvicorn api_server:app --host 0.0.0.0 --port 8000 --workers 4 +Restart=always +RestartSec=10 + +[Install] +WantedBy=multi-user.target +""" + + service_file = Path("/etc/systemd/system/video-keyframe-api.service") + + try: + with open(service_file, 'w') as f: + f.write(service_content) + + print(f"✓ Systemd service created: {service_file}") + print("To enable and start:") + print(" sudo systemctl enable video-keyframe-api") + print(" sudo systemctl start video-keyframe-api") + + except PermissionError: + print("✗ Permission denied. Please run with sudo for systemd service creation") + + # 创建本地副本 + local_service = Path("./video-keyframe-api.service") + with open(local_service, 'w') as f: + f.write(service_content) + + print(f"✓ Service file created locally: {local_service}") + print(f"To install: sudo cp {local_service} /etc/systemd/system/") + + +def main(): + parser = argparse.ArgumentParser(description="Video Keyframe Extraction API Server") + + # 从配置文件获取默认值 + server_config = config.get_server_config() + + parser.add_argument("--mode", choices=["dev", "prod", "install"], default="dev", + help="运行模式: dev (开发), prod (生产), install (安装依赖)") + parser.add_argument("--host", default=server_config.get("host", "127.0.0.1"), help="绑定主机") + parser.add_argument("--port", type=int, default=server_config.get("port", 8000), help="端口号") + parser.add_argument("--workers", type=int, default=server_config.get("workers", 4), help="生产模式工作进程数") + parser.add_argument("--no-reload", action="store_true", help="禁用自动重载") + parser.add_argument("--check", action="store_true", help="仅检查环境") + parser.add_argument("--create-service", action="store_true", help="创建 systemd 服务") + + args = parser.parse_args() + + print("=== Video Keyframe Extraction API Server ===") + + # 检查环境 + rust_exe = check_rust_executable() + deps_ok = check_dependencies() + + if args.check: + print("\n=== Environment Check ===") + print(f"Rust executable: {'✓' if rust_exe else '✗'}") + print(f"Python dependencies: {'✓' if deps_ok else '✗'}") + return + + if args.create_service: + create_systemd_service() + return + + # 安装模式 + if args.mode == "install": + if not deps_ok: + install_dependencies() + else: + print("✓ Dependencies already installed") + return + + # 检查必要条件 + if not rust_exe: + print("✗ Cannot start without Rust executable") + print("Please run: cargo build --release") + sys.exit(1) + + if not deps_ok: + print("Installing missing dependencies...") + if not install_dependencies(): + sys.exit(1) + + # 启动服务器 + if args.mode == "dev": + start_development_server( + host=args.host, + port=args.port, + reload=not args.no_reload + ) + elif args.mode == "prod": + start_production_server( + host=args.host, + port=args.port, + workers=args.workers + ) + + +if __name__ == "__main__": + main()