feat: openvoice重构，添加语音克隆功能

app/controllers/chat_controller.py

@@ -4,12 +4,13 @@ from ..dependencies.summarizer import get_summarizer
 from ..dependencies.asr import get_asr
 from ..dependencies.tts import get_tts
 from .controller_enum import *
-from ..models import UserCharacter, Session, Character, User
+from ..models import UserCharacter, Session, Character, User, Audio
 from utils.audio_utils import VAD
 from fastapi import WebSocket, HTTPException, status
 from datetime import datetime
 from utils.xf_asr_utils import generate_xf_asr_url
 from config import get_config
+import numpy as np
 import uuid
 import json
 import asyncio
@@ -100,6 +101,19 @@ def update_session_activity(session_id,db):
     except Exception as e:
         db.roolback()
         raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=str(e))
+
+#获取target_se
+def get_emb(session_id,db):
+    try:
+        session_record = db.query(Session).filter(Session.id == session_id).first()
+        user_character_record = db.query(UserCharacter).filter(UserCharacter.id == session_record.user_character_id).first()
+        audio_record = db.query(Audio).filter(Audio.user_id == user_character_record.user_id).first()
+        emb_npy = np.frombuffer(audio_record.emb_data,dtype=np.int32)
+        emb_npy_3d = np.reshape(emb_npy,(1,256,1))
+        return emb_npy_3d
+    except Exception as e:
+        logger.error("未找到音频:"+str(e))
+        return np.array([])
 #--------------------------------------------------------
 
 # 创建新聊天
@@ -283,6 +297,7 @@ async def sct_llm_handler(ws,session_id,response_type,llm_info,tts_info,db,redis
             'Authorization': f"Bearer {Config.MINIMAX_LLM.API_KEY}",
             'Content-Type': 'application/json'
         }
+        target_se = get_emb(session_id,db)
     except Exception as e:
         logger.error(f"编辑http请求时发生错误: {str(e)}")
     try:
@@ -299,7 +314,17 @@ async def sct_llm_handler(ws,session_id,response_type,llm_info,tts_info,db,redis
                             response_message = {"type": "text", "code":200, "msg": sentence}
                             await ws.send_text(json.dumps(response_message, ensure_ascii=False)) #返回文本信息
                         elif response_type == RESPONSE_AUDIO:
-                            sr,audio = tts.synthesize(sentence, tts_info["speaker_id"], tts_info["language"], tts_info["noise_scale"], tts_info["noise_scale_w"], tts_info["length_scale"],return_bytes=True)
+                            if target_se.size == 0:
+                                audio,sr = tts._base_tts(text=sentence,
+                                                        noise_scale=tts_info["noise_scale"],
+                                                        noise_scale_w=tts_info["noise_scale_w"],
+                                                        speed=tts_info["length_scale"])
+                            else:
+                                audio,sr = tts.synthesize(text=sentence,
+                                                        noise_scale=tts_info["noise_scale"],
+                                                        noise_scale_w=tts_info["noise_scale_w"],
+                                                        speed=tts_info["length_scale"],
+                                                        target_se=target_se)
                             response_message = {"type": "text", "code":200, "msg": sentence}
                             await ws.send_bytes(audio)  #返回音频数据
                             await ws.send_text(json.dumps(response_message, ensure_ascii=False))    #返回文本信息
@@ -455,6 +480,7 @@ async def scl_llm_handler(ws,session_id,response_type,llm_info,tts_info,db,redis
                 'Authorization': f"Bearer {Config.MINIMAX_LLM.API_KEY}",
                 'Content-Type': 'application/json'
             }
+            target_se = get_emb(session_id,db)
             async with aiohttp.ClientSession() as client:
                 async with client.post(Config.MINIMAX_LLM.URL, headers=headers, data=payload) as response:  #发送大模型请求
                     async for chunk in response.content.iter_any():
@@ -469,7 +495,17 @@ async def scl_llm_handler(ws,session_id,response_type,llm_info,tts_info,db,redis
                                 response_message = {"type": "text", "code":200, "msg": sentence}
                                 await ws.send_text(json.dumps(response_message, ensure_ascii=False))
                             elif response_type == RESPONSE_AUDIO:
-                                sr,audio = tts.synthesize(sentence, tts_info["speaker_id"], tts_info["language"], tts_info["noise_scale"], tts_info["noise_scale_w"], tts_info["length_scale"],return_bytes=True)
+                                if target_se.size == 0:
+                                    audio,sr = tts._base_tts(text=sentence,
+                                                            noise_scale=tts_info["noise_scale"],
+                                                            noise_scale_w=tts_info["noise_scale_w"],
+                                                            speed=tts_info["length_scale"])
+                                else:
+                                    audio,sr = tts.synthesize(text=sentence,
+                                                            noise_scale=tts_info["noise_scale"],
+                                                            noise_scale_w=tts_info["noise_scale_w"],
+                                                            speed=tts_info["length_scale"],
+                                                            target_se=target_se)
                                 response_message = {"type": "text", "code":200, "msg": sentence}
                                 await ws.send_bytes(audio)
                                 await ws.send_text(json.dumps(response_message, ensure_ascii=False))
@@ -629,11 +665,11 @@ async def voice_call_llm_handler(ws,session_id,llm_info,tts_info,db,redis,asr_re
                 "temperature": llm_info["temperature"],
                 "top_p": llm_info["top_p"]
             })
-            
             headers = {
                 'Authorization': f"Bearer {Config.MINIMAX_LLM.API_KEY}",
                 'Content-Type': 'application/json'
             }
+            target_se = get_emb(session_id,db)
             async with aiohttp.ClientSession() as client:
                 async with client.post(Config.MINIMAX_LLM.URL, headers=headers, data=payload) as response:  #发送大模型请求
                     async for chunk in response.content.iter_any():
@@ -643,7 +679,17 @@ async def voice_call_llm_handler(ws,session_id,llm_info,tts_info,db,redis,asr_re
                             llm_response += chunk_data
                         sentences,current_sentence,is_first = split_string_with_punctuation(current_sentence,chunk_data,is_first,is_end)
                         for sentence in sentences:
-                            sr,audio = tts.synthesize(sentence, tts_info["language"], tts_info["speaker_id"], tts_info["noise_scale"], tts_info["noise_scale_w"], tts_info["length_scale"], return_bytes=True)
+                            if target_se.size == 0:
+                                audio,sr = tts._base_tts(text=sentence,
+                                                        noise_scale=tts_info["noise_scale"],
+                                                        noise_scale_w=tts_info["noise_scale_w"],
+                                                        speed=tts_info["length_scale"])
+                            else:
+                                audio,sr = tts.synthesize(text=sentence,
+                                                        noise_scale=tts_info["noise_scale"],
+                                                        noise_scale_w=tts_info["noise_scale_w"],
+                                                        speed=tts_info["length_scale"],
+                                                        target_se=target_se)
                             text_response = {"type": "llm_text", "code": 200, "msg": sentence}
                             await ws.send_bytes(audio) #返回音频二进制流数据
                             await ws.send_text(json.dumps(text_response, ensure_ascii=False)) #返回文本数据
@@ -673,23 +719,6 @@ async def voice_call_llm_handler(ws,session_id,llm_info,tts_info,db,redis,asr_re
             break
     voice_call_end_event.set()
 
-        
-#语音合成及返回函数
-async def voice_call_tts_handler(ws,tts_info,split_result_q,split_finished_event,voice_call_end_event):
-    logger.debug("语音合成及返回函数启动")
-    while not (split_finished_event.is_set() and split_result_q.empty()):
-        try:
-            sentence = await asyncio.wait_for(split_result_q.get(),timeout=3)
-            sr,audio = tts.synthesize(sentence, tts_info["language"], tts_info["speaker_id"], tts_info["noise_scale"], tts_info["noise_scale_w"], tts_info["length_scale"], return_bytes=True)
-            text_response = {"type": "llm_text", "code": 200, "msg": sentence}
-            await ws.send_bytes(audio) #返回音频二进制流数据
-            await ws.send_text(json.dumps(text_response, ensure_ascii=False)) #返回文本数据
-            logger.debug(f"websocket返回:{sentence}")
-        except asyncio.TimeoutError:
-            continue
-    voice_call_end_event.set()
-
-
 async def voice_call_handler(ws, db, redis):
     logger.debug("voice_call websocket 连接建立")
     audio_q = asyncio.Queue()	#音频队列

app/controllers/user_controller.py

@@ -1,14 +1,20 @@
 from ..schemas.user_schema import *
 from ..dependencies.logger import get_logger
+from ..dependencies.tts import get_tts
 from ..models import User, Hardware, Audio
 from datetime import datetime
 from sqlalchemy.orm import Session
 from fastapi import HTTPException, status
+from pydub import AudioSegment
+import numpy as np
+import io
 
 
 #依赖注入获取logger
 logger = get_logger()
 
+#依赖注入获取tts
+tts = get_tts()
 
 #创建用户
 async def create_user_handler(user:UserCrateRequest, db: Session):
@@ -156,13 +162,17 @@ async def get_hardware_handler(hardware_id, db):
 #用户上传音频
 async def upload_audio_handler(user_id, audio, db):
     try:
-        audio_data = audio.file.read()
+        audio_data = await audio.read()
-        new_audio = Audio(user_id=user_id, audio_data=audio_data)
+        raw_data = AudioSegment.from_file(io.BytesIO(audio_data), format="mp3").raw_data
+        numpy_data = np.frombuffer(raw_data, dtype=np.int32)
+        emb_data = tts.audio2emb(numpy_data,rate=44100,vad=True).tobytes()
+        new_audio = Audio(user_id=user_id, audio_data=audio_data,emb_data=emb_data)
         db.add(new_audio)
         db.commit()
         db.refresh(new_audio)
     except Exception as e:
         db.rollback()
+        print(str(e))
         raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=str(e))
     audio_upload_data = AudioUploadData(audio_id=new_audio.id, uploadedAt=datetime.now().isoformat())
     return AudioUploadResponse(status="success", message="用户上传音频成功", data=audio_upload_data)
@@ -174,8 +184,11 @@ async def update_audio_handler(audio_id, audio_file, db):
         existing_audio = db.query(Audio).filter(Audio.id == audio_id).first()
         if existing_audio is None:
             raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="音频不存在")
-        audio_data = audio_file.file.read()
+        audio_data = await audio_file.read()
+        raw_data = AudioSegment.from_file(io.BytesIO(audio_data), format="mp3").raw_data
+        emb_data = tts.audio2emb(np.frombuffer(raw_data, dtype=np.int32),rate=44100,vad=True).tobytes()
         existing_audio.audio_data = audio_data
+        existing_audio.emb_data = emb_data
         db.commit()
     except Exception as e:
         db.rollback()

tests/unit_test/chat_test.py

@@ -30,6 +30,7 @@ class ChatServiceTest:
         }
         response = requests.request("POST", url, headers=headers, data=payload)
         if response.status_code == 200:
+            print("用户创建成功")
             self.user_id = response.json()['data']['user_id']
         else:
             raise Exception("创建聊天时，用户创建失败")
@@ -57,6 +58,21 @@ class ChatServiceTest:
         else:
             raise Exception("创建聊天时，角色创建失败")
         
+        #上传音频用于音频克隆
+        url = f"{self.socket}/users/audio?user_id={self.user_id}"
+        current_file_path = os.path.abspath(__file__)
+        current_file_path = os.path.dirname(current_file_path)
+        tests_dir = os.path.dirname(current_file_path)
+        mp3_file_path = os.path.join(tests_dir, 'assets', 'demo_speaker0.mp3')
+        with open(mp3_file_path, 'rb') as audio_file:
+            files = {'audio_file':(mp3_file_path, audio_file, 'audio/mpeg')}
+            response = requests.post(url,files=files)
+            if response.status_code == 200:
+                self.audio_id = response.json()['data']['audio_id']
+                print("音频上传成功")
+            else:
+                raise Exception("音频上传失败")
+        
         #创建一个对话
         url = f"{self.socket}/chats"
         payload = json.dumps({
@@ -66,6 +82,7 @@ class ChatServiceTest:
         headers = {
             'Content-Type': 'application/json'
         }
+        
         response = requests.request("POST", url, headers=headers, data=payload)
         if response.status_code == 200:
             print("对话创建成功")
@@ -302,6 +319,11 @@ class ChatServiceTest:
         else:
             raise Exception("聊天删除测试失败")
         
+        url = f"{self.socket}/users/audio/{self.audio_id}"
+        response = requests.request("DELETE", url)
+        if response.status_code != 200:
+            raise Exception("音频删除测试失败")
+        
         url = f"{self.socket}/users/{self.user_id}"
         response = requests.request("DELETE", url)
         if response.status_code != 200:
@@ -312,7 +334,6 @@ class ChatServiceTest:
         if response.status_code != 200:
             raise Exception("角色删除测试失败")
 
-
 def chat_test():
     chat_service_test = ChatServiceTest()
     chat_service_test.test_create_chat()

tests/unit_test/user_test.py

@@ -5,7 +5,7 @@ import os
 
 
 class UserServiceTest:
-    def __init__(self,socket="http://127.0.0.1:8001"):
+    def __init__(self,socket="http://127.0.0.1:7878"):
         self.socket = socket
 
     def test_user_create(self):
@@ -132,7 +132,7 @@ class UserServiceTest:
         current_file_path = os.path.abspath(__file__)
         current_dir = os.path.dirname(current_file_path)
         tests_dir = os.path.dirname(current_dir)
-        wav_file_path = os.path.join(tests_dir, 'assets', 'iat_mp3_8k.mp3')
+        wav_file_path = os.path.join(tests_dir, 'assets', 'demo_speaker0.mp3')
         with open(wav_file_path, 'rb') as audio_file:
             files = {'audio_file':(wav_file_path,audio_file,'audio/mpeg')}
             response = requests.post(url, files=files)
@@ -141,15 +141,15 @@ class UserServiceTest:
                 print("音频上传测试成功")
             else:
                 raise Exception("音频上传测试失败")
-    
+
     def test_update_audio(self):
         url = f"{self.socket}/users/audio/{self.audio_id}"
         current_file_path = os.path.abspath(__file__)
         current_dir = os.path.dirname(current_file_path)
         tests_dir = os.path.dirname(current_dir)
-        wav_file_path = os.path.join(tests_dir, 'assets', 'iat_mp3_8k.mp3')
+        wav_file_path = os.path.join(tests_dir, 'assets', 'demo_speaker0.mp3')
         with open(wav_file_path, 'rb') as audio_file:
-            files = {'audio_file':(wav_file_path,audio_file,'audio/mpeg')}
+            files = {'audio_file':(wav_file_path,audio_file,'audio/wav')}
             response = requests.put(url, files=files)
             if response.status_code == 200:
                 print("音频上传测试成功")

utils/tts/openvoice_utils.py

@@ -260,6 +260,11 @@ class TextToSpeech:
             audio: tensor
             sr: 生成音频的采样速率
         """
+        if source_se is not None:
+            source_se = torch.tensor(source_se.astype(np.float32)).to(self.device)
+        if target_se is not None:
+            target_se = torch.tensor(target_se.astype(np.float32)).to(self.device)
+            
         if source_se is None:
             source_se = self.source_se
         if target_se is None:
@@ -319,7 +324,6 @@ class TextToSpeech:
             tts_sr = self.base_tts_model.hps.data.sampling_rate
             converter_sr = self.tone_color_converter.hps.data.sampling_rate
             audio = F.resample(audio, tts_sr, converter_sr)
-            print(audio.dtype)
             audio, sr = self._convert_tone(audio,
                                            source_se=source_se,
                                            target_se=target_se,