雅荷心语博客我的第一个 hello world
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from fastapi.responses import Response from io import BytesIO from GPT_SoVITS.TTS_infer_pack.TTS import TTS, TTS_Config import numpy as np import soundfile as sf from flask import Flask, jsonify app = Flask(__name__) tts_config_cache = {} # 缓存 TTS_Config 对象 def pack_wav(io_buffer: BytesIO, data: np.ndarray, rate: int): io_buffer = BytesIO() sf.write(io_buffer, data, rate, format='wav') return io_buffer def pack_audio(data: np.ndarray, rate: int, media_type: str): io_buffer = BytesIO() io_buffer = pack_wav(io_buffer, data, rate) io_buffer.seek(0) return io_buffer def get_tts_config(tts_infer_yaml_path): if tts_infer_yaml_path not in tts_config_cache: tts_config_cache[tts_infer_yaml_path] = TTS_Config(tts_infer_yaml_path) return tts_config_cache[tts_infer_yaml_path] def tts_handle(req: dict): # 打印传入的配置信息 print(f"传入的配置是: {req}") # 从传入的配置中获取是否启用流式模式的参数，若未提供则默认为False streaming_mode = req.get("streaming_mode", False) # 从传入的配置中获取所需的媒体类型，若未提供则默认为wav格式 media_type = req.get("media_type", "wav") # 从传入的配置中获取TTS推理配置文件的路径，若未提供则默认为"GPT_SoVITS/configs/tts_infer.yaml" tts_infer_yaml_path = req.get("tts_infer_yaml_path", "GPT_SoVITS/configs/tts_infer.yaml") # 根据提供的配置文件路径创建TTS配置对象 tts_config = get_tts_config(tts_infer_yaml_path) try: # 使用创建的TTS配置对象初始化TTS类的实例 tts_instance = TTS(tts_config) # 使用初始化的TTS实例处理输入请求，生成音频数据 tts_generator = tts_instance.run(req) # 获取生成的音频数据和采样率 sr, audio_data = next(tts_generator) # 将生成的音频数据打包成指定媒体类型的二进制数据 audio_data = pack_audio(audio_data, sr, media_type).getvalue() # 构建并返回包含音频数据和媒体类型的响应对象 return Response(audio_data, media_type=f"audio/{media_type}") except Exception as e: # 如果在处理请求过程中发生异常，打印错误信息并返回一个空响应对象 print(f"生成失败: {str(e)}") return Response("", media_type=f"audio/{media_type}") @app.route('/hello', methods=['GET']) def hello(): audio = tts_handle({ "text": "你好", "text_lang": "zh", "ref_audio_path": "666.mp3", "prompt_text": "", "prompt_lang": "zh", "top_k": 5, "top_p": 1, "temperature": 1, "text_split_method": "cut0", "batch_size": 1, "batch_threshold": 1, "speed_factor": 1.0, "split_bucket": True, "fragment_interval": 0.3, "seed": -1, "media_type": "wav", "streaming_mode": False, "parallel_infer": True, "repetition_penalty": 1.35, "tts_infer_yaml_path": "GPT_SoVITS/configs/tts_infer.yaml" }) print(f"生成结果: {audio}") return jsonify(message="Hello, World!") if __name__ == '__main__': app.run(debug=True, port=5001) |
