164 lines
4.8 KiB
Python
164 lines
4.8 KiB
Python
"""
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端到端测试诊断脚本
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用于快速检查测试环境和依赖
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"""
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import sys
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import os
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from pathlib import Path
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project_root = Path(__file__).parent.parent.parent.absolute()
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os.chdir(project_root)
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print("=" * 60)
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print("端到端测试环境诊断")
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print("=" * 60)
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# 1. 检查 Python 版本
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print(f"\n[OK] Python 版本：{sys.version}")
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print(f" 路径：{sys.executable}")
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# 2. 检查测试配置文件
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print("\n" + "-" * 60)
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print("测试配置文件检查")
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print("-" * 60)
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config_file = Path(__file__).parent / "test_config.yaml"
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if config_file.exists():
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print(f"[OK] 配置文件存在：{config_file}")
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import yaml
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with open(config_file, 'r', encoding='utf-8') as f:
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config = yaml.safe_load(f)
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print(f"[OK] 主测试视频：{config['test_files']['primary_video']}")
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print(f"[OK] 备用视频：{len(config['test_files']['backup_videos'])} 个")
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print(f"[OK] 音频文件：{len(config['test_files']['audio_files'])} 个")
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# 检查文件是否存在
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for key, files in [('视频', config['test_files']['backup_videos']),
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('音频', config['test_files']['audio_files'])]:
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for file_path in files:
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full_path = project_root / file_path
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exists = "[OK]" if full_path.exists() else "[X]"
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print(f" {exists} {file_path}")
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else:
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print(f"[X] 配置文件不存在：{config_file}")
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# 3. 检查测试文件
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print("\n" + "-" * 60)
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print("测试文件检查")
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print("-" * 60)
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test_files_dir = Path(__file__).parent
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print(f"测试目录：{test_files_dir}")
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# 4. 检查依赖
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print("\n" + "-" * 60)
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print("依赖检查")
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print("-" * 60)
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dependencies = {
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'pytest': 'pytest',
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'yaml': 'pyyaml',
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'flask': 'flask',
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'torch': 'pytorch',
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'librosa': 'librosa',
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}
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for module, package in dependencies.items():
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try:
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__import__(module)
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print(f"[OK] {package}")
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except ImportError:
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print(f"[X] {package} (需要安装：pip install {package})")
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# 5. 检查实际测试文件
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print("\n" + "-" * 60)
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print("实际测试文件检查")
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print("-" * 60)
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input_dir = project_root / "input"
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if input_dir.exists():
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print(f"输入目录：{input_dir}")
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video_files = list(input_dir.glob("*.AVI")) + list(input_dir.glob("*.avi")) + \
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list(input_dir.glob("*.mp4")) + list(input_dir.glob("*.MP4"))
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audio_files = list(input_dir.glob("*.wav")) + list(input_dir.glob("*.WAV"))
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print(f" 视频文件：{len(video_files)} 个")
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for f in video_files[:5]:
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size_mb = f.stat().st_size / 1024 / 1024
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print(f" - {f.name} ({size_mb:.2f} MB)")
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print(f" 音频文件：{len(audio_files)} 个")
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for f in audio_files[:5]:
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size_mb = f.stat().st_size / 1024 / 1024
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print(f" - {f.name} ({size_mb:.2f} MB)")
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else:
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print(f"[X] 输入目录不存在：{input_dir}")
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# 6. 检查 ASR 模型
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print("\n" + "-" * 60)
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print("ASR 模型检查")
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print("-" * 60)
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try:
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from app.asr.asr_service import ASRService
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print("[OK] ASR 服务模块可导入")
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# 检查模型缓存目录
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import os
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model_cache = os.environ.get("MODELSCOPE_CACHE", "未设置")
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print(f" 模型缓存目录：{model_cache}")
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cache_path = Path(model_cache) if model_cache != "未设置" else None
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if cache_path and cache_path.exists():
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model_files = list(cache_path.glob("*"))
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print(f" 缓存的模型文件：{len(model_files)} 个")
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else:
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print(f" [!] 模型缓存目录不存在（首次运行会下载模型）")
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except Exception as e:
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print(f"[X] ASR 服务导入失败：{e}")
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# 7. 检查 ffmpeg
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print("\n" + "-" * 60)
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print("FFmpeg 检查")
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print("-" * 60)
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ffmpeg_path = project_root / "lib" / "ffmpeg.exe"
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if ffmpeg_path.exists():
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print(f"[OK] ffmpeg 存在：{ffmpeg_path}")
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else:
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print(f"[X] ffmpeg 不存在：{ffmpeg_path}")
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print(" 请确保 ffmpeg 在 lib 目录下")
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# 8. 运行建议
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print("\n" + "=" * 60)
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print("运行建议")
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print("=" * 60)
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print("""
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运行端到端测试：
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pytest test/real/ -v
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只运行快速验证测试（不测试 ASR）：
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pytest test/real/test_real_e2e.py::TestVideoFileValidation -v
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pytest test/real/test_real_e2e.py::TestAudioFileValidation -v
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pytest test/real/test_real_e2e.py::TestErrorHandling -v
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运行单个 ASR 测试（带详细输出）：
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pytest test/real/test_real_e2e.py::TestASRRecognition::test_recognize_audio_file -v -s
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如果测试卡住，按 Ctrl+C 查看堆栈跟踪
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注意事项：
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1. 首次运行会下载 ASR 模型（可能很大，需要时间）
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2. CPU 运行 ASR 推理较慢（1 分钟音频可能需要 2-5 分钟）
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3. 确保有足够的磁盘空间（临时文件 + 模型缓存）
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4. 如果内存不足，建议使用较小的测试文件
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""")
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print("=" * 60)
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print("诊断完成")
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print("=" * 60)
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