mirror of
https://github.com/Soul-AILab/SoulX-Podcast.git
synced 2026-06-03 23:21:04 +08:00
Major updates: - Add vLLM engine support with automatic fallback to HuggingFace - Complete REST API implementation with sync/async modes - Add comprehensive API documentation - Organize scripts into dedicated directory API Features: - Support both HuggingFace and vLLM inference engines - Sync and async generation endpoints - Task queue management with concurrency control - Health check with engine information - Automatic file cleanup Configuration: - Environment variable based configuration - Engine validation and auto-fallback - Configurable concurrency limits Documentation: - README_API.md: Complete API usage guide - CHANGELOG_API.md: API version history - VLLM_UPGRADE_SUMMARY.md: Detailed upgrade guide - scripts/README.md: Scripts documentation Scripts Organization: - Move all test and utility scripts to scripts/ - Add configuration test script - Add singleton pattern test Performance: - vLLM engine provides 2-3x speedup - Better GPU memory utilization - Support for prefix caching 🤖 Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
203 lines
5.8 KiB
Python
203 lines
5.8 KiB
Python
"""
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Utility Functions for API
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"""
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import os
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import re
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import uuid
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import shutil
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from pathlib import Path
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from datetime import datetime, timedelta
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from typing import List, Tuple
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from fastapi import UploadFile, HTTPException
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import logging
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from api.config import config
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logger = logging.getLogger(__name__)
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def generate_task_id() -> str:
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"""生成唯一的任务ID"""
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return str(uuid.uuid4())
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def save_upload_file(upload_file: UploadFile, task_id: str, index: int) -> Path:
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"""
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保存上传的文件到临时目录
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Args:
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upload_file: FastAPI上传文件对象
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task_id: 任务ID
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index: 文件索引
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Returns:
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Path: 保存的文件路径
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"""
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try:
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# 获取文件扩展名
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file_extension = Path(upload_file.filename).suffix or ".wav"
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# 构建保存路径
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filename = f"{task_id}_prompt_{index}{file_extension}"
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file_path = config.temp_dir / filename
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# 保存文件
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with open(file_path, "wb") as buffer:
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shutil.copyfileobj(upload_file.file, buffer)
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logger.info(f"Saved upload file to {file_path}")
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return file_path
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except Exception as e:
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logger.error(f"Failed to save upload file: {e}")
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raise HTTPException(status_code=500, detail=f"文件保存失败: {str(e)}")
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finally:
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upload_file.file.close()
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def validate_audio_files(files: List[UploadFile]) -> None:
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"""
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验证音频文件
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Args:
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files: 上传的文件列表
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Raises:
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HTTPException: 如果验证失败
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"""
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if not files or len(files) == 0:
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raise HTTPException(status_code=400, detail="至少需要上传1个参考音频文件")
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if len(files) > 4:
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raise HTTPException(status_code=400, detail="最多支持4个说话人(4个音频文件)")
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# 验证文件类型和大小
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allowed_extensions = {".wav", ".mp3", ".flac", ".m4a"}
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for i, file in enumerate(files):
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# 检查文件扩展名
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file_ext = Path(file.filename).suffix.lower()
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if file_ext not in allowed_extensions:
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raise HTTPException(
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status_code=400,
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detail=f"文件 {file.filename} 格式不支持。支持的格式: {', '.join(allowed_extensions)}"
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)
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# 检查文件大小(通过content-length header,可能不准确)
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if hasattr(file, 'size') and file.size and file.size > config.max_upload_size:
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raise HTTPException(
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status_code=400,
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detail=f"文件 {file.filename} 超过最大大小限制 ({config.max_upload_size / 1024 / 1024}MB)"
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)
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def validate_dialogue_format(dialogue_text: str, num_speakers: int) -> Tuple[bool, str]:
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"""
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验证对话文本格式
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Args:
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dialogue_text: 对话文本
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num_speakers: 说话人数量
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Returns:
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Tuple[bool, str]: (是否有效, 错误信息)
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"""
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dialogue_text = dialogue_text.strip()
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# 单说话人模式:不需要特殊格式
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if num_speakers == 1:
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if len(dialogue_text) == 0:
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return False, "对话文本不能为空"
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# 单说话人可以不使用[S1]标记
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return True, ""
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# 多说话人模式:需要[S1][S2]等标记
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# 提取所有说话人标记
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speaker_pattern = r'\[S[1-4]\]'
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matches = re.findall(speaker_pattern, dialogue_text)
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if not matches:
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return False, f"多说话人模式需要使用说话人标记,如: [S1]你好[S2]你好"
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# 检查使用的说话人ID是否在有效范围内
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used_speakers = set()
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for match in matches:
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speaker_id = int(match[2]) # 提取[S1]中的1
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used_speakers.add(speaker_id)
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if speaker_id > num_speakers:
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return False, f"文本中使用了说话人[S{speaker_id}],但只提供了{num_speakers}个参考音频"
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return True, ""
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def cleanup_old_files(directory: Path, minutes: int = 30) -> int:
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"""
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清理过期的文件
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Args:
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directory: 要清理的目录
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minutes: 文件保留时间(分钟)
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Returns:
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int: 清理的文件数量
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"""
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if not directory.exists():
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return 0
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cutoff_time = datetime.now() - timedelta(minutes=minutes)
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cleaned_count = 0
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try:
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for file_path in directory.glob("*"):
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if file_path.is_file():
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# 获取文件修改时间
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file_mtime = datetime.fromtimestamp(file_path.stat().st_mtime)
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if file_mtime < cutoff_time:
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try:
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file_path.unlink()
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cleaned_count += 1
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logger.info(f"Cleaned up old file: {file_path}")
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except Exception as e:
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logger.warning(f"Failed to delete {file_path}: {e}")
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except Exception as e:
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logger.error(f"Error during cleanup: {e}")
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return cleaned_count
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def format_audio_duration(seconds: float) -> str:
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"""格式化音频时长"""
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minutes = int(seconds // 60)
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secs = int(seconds % 60)
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return f"{minutes:02d}:{secs:02d}"
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def parse_dialogue_text(dialogue_text: str, num_speakers: int) -> List[str]:
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"""
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解析对话文本为列表格式
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Args:
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dialogue_text: 原始对话文本
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num_speakers: 说话人数量
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Returns:
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List[str]: 分段的对话列表,每段包含说话人标记
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"""
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# 单说话人:直接添加[S1]标记
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if num_speakers == 1:
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if not dialogue_text.startswith("[S1]"):
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return [f"[S1]{dialogue_text}"]
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else:
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return [dialogue_text]
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# 多说话人:按[S1][S2]分割
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pattern = r'(\[S[1-4]\][^\[\]]*)'
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segments = re.findall(pattern, dialogue_text)
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# 过滤空段落
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segments = [seg.strip() for seg in segments if seg.strip()]
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return segments
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