feat: 增加xinference语音模型

apps/setting/models_provider/impl/xinference_model_provider/credential/stt.py

@@ -0,0 +1,42 @@
+# coding=utf-8
+from typing import Dict
+
+from common import forms
+from common.exception.app_exception import AppApiException
+from common.forms import BaseForm
+from setting.models_provider.base_model_provider import BaseModelCredential, ValidCode
+
+
+class XInferenceSTTModelCredential(BaseForm, BaseModelCredential):
+    api_base = forms.TextInputField('API 域名', required=True)
+    api_key = forms.PasswordInputField('API Key', required=True)
+
+    def is_valid(self, model_type: str, model_name, model_credential: Dict[str, object], provider,
+                 raise_exception=False):
+        model_type_list = provider.get_model_type_list()
+        if not any(list(filter(lambda mt: mt.get('value') == model_type, model_type_list))):
+            raise AppApiException(ValidCode.valid_error.value, f'{model_type} 模型类型不支持')
+
+        for key in ['api_base', 'api_key']:
+            if key not in model_credential:
+                if raise_exception:
+                    raise AppApiException(ValidCode.valid_error.value, f'{key} 字段为必填字段')
+                else:
+                    return False
+        try:
+            model = provider.get_model(model_type, model_name, model_credential)
+            model.check_auth()
+        except Exception as e:
+            if isinstance(e, AppApiException):
+                raise e
+            if raise_exception:
+                raise AppApiException(ValidCode.valid_error.value, f'校验失败,请检查参数是否正确: {str(e)}')
+            else:
+                return False
+        return True
+
+    def encryption_dict(self, model: Dict[str, object]):
+        return {**model, 'api_key': super().encryption(model.get('api_key', ''))}
+
+    def get_model_params_setting_form(self, model_name):
+        pass

apps/setting/models_provider/impl/xinference_model_provider/model/stt.py

@@ -0,0 +1,59 @@
+import asyncio
+import io
+from typing import Dict
+
+from openai import OpenAI
+
+from common.config.tokenizer_manage_config import TokenizerManage
+from setting.models_provider.base_model_provider import MaxKBBaseModel
+from setting.models_provider.impl.base_stt import BaseSpeechToText
+
+
+def custom_get_token_ids(text: str):
+    tokenizer = TokenizerManage.get_tokenizer()
+    return tokenizer.encode(text)
+
+
+class XInferenceSpeechToText(MaxKBBaseModel, BaseSpeechToText):
+    api_base: str
+    api_key: str
+    model: str
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self.api_key = kwargs.get('api_key')
+        self.api_base = kwargs.get('api_base')
+
+    @staticmethod
+    def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
+        optional_params = {}
+        if 'max_tokens' in model_kwargs and model_kwargs['max_tokens'] is not None:
+            optional_params['max_tokens'] = model_kwargs['max_tokens']
+        if 'temperature' in model_kwargs and model_kwargs['temperature'] is not None:
+            optional_params['temperature'] = model_kwargs['temperature']
+        return XInferenceSpeechToText(
+            model=model_name,
+            api_base=model_credential.get('api_base'),
+            api_key=model_credential.get('api_key'),
+            **optional_params,
+        )
+
+    def check_auth(self):
+        client = OpenAI(
+            base_url=self.api_base,
+            api_key=self.api_key
+        )
+        response_list = client.models.with_raw_response.list()
+        # print(response_list)
+
+    def speech_to_text(self, audio_file):
+        client = OpenAI(
+            base_url=self.api_base,
+            api_key=self.api_key
+        )
+        audio_data = audio_file.read()
+        buffer = io.BytesIO(audio_data)
+        buffer.name = "file.mp3"  # this is the important line
+        res = client.audio.transcriptions.create(model=self.model, language="zh", file=buffer)
+        return res.text
+

apps/setting/models_provider/impl/xinference_model_provider/model/tts.py

@@ -0,0 +1,60 @@
+from typing import Dict
+
+from openai import OpenAI
+
+from common.config.tokenizer_manage_config import TokenizerManage
+from setting.models_provider.base_model_provider import MaxKBBaseModel
+from setting.models_provider.impl.base_tts import BaseTextToSpeech
+
+
+def custom_get_token_ids(text: str):
+    tokenizer = TokenizerManage.get_tokenizer()
+    return tokenizer.encode(text)
+
+
+class XInferenceTextToSpeech(MaxKBBaseModel, BaseTextToSpeech):
+    api_base: str
+    api_key: str
+    model: str
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self.api_key = kwargs.get('api_key')
+        self.api_base = kwargs.get('api_base')
+        self.model = kwargs.get('model')
+
+    @staticmethod
+    def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
+        optional_params = {}
+        if 'max_tokens' in model_kwargs and model_kwargs['max_tokens'] is not None:
+            optional_params['max_tokens'] = model_kwargs['max_tokens']
+        if 'temperature' in model_kwargs and model_kwargs['temperature'] is not None:
+            optional_params['temperature'] = model_kwargs['temperature']
+        return XInferenceTextToSpeech(
+            model=model_name,
+            api_base=model_credential.get('api_base'),
+            api_key=model_credential.get('api_key'),
+            **optional_params,
+        )
+
+    def check_auth(self):
+        client = OpenAI(
+            base_url=self.api_base,
+            api_key=self.api_key
+        )
+        response_list = client.models.with_raw_response.list()
+        # print(response_list)
+
+    def text_to_speech(self, text):
+        client = OpenAI(
+            base_url=self.api_base,
+            api_key=self.api_key
+        )
+        # ['中文女', '中文男', '日语男', '粤语女', '英文女', '英文男', '韩语女']
+
+        with client.audio.speech.with_streaming_response.create(
+                model=self.model,
+                voice="中文女",
+                input=text,
+        ) as response:
+            return response.read()

apps/setting/models_provider/impl/xinference_model_provider/xinference_model_provider.py

@@ -11,12 +11,17 @@ from setting.models_provider.impl.xinference_model_provider.credential.embedding
     XinferenceEmbeddingModelCredential
 from setting.models_provider.impl.xinference_model_provider.credential.llm import XinferenceLLMModelCredential
 from setting.models_provider.impl.xinference_model_provider.credential.reranker import XInferenceRerankerModelCredential
+from setting.models_provider.impl.xinference_model_provider.credential.stt import XInferenceSTTModelCredential
 from setting.models_provider.impl.xinference_model_provider.model.embedding import XinferenceEmbedding
 from setting.models_provider.impl.xinference_model_provider.model.llm import XinferenceChatModel
 from setting.models_provider.impl.xinference_model_provider.model.reranker import XInferenceReranker
+from setting.models_provider.impl.xinference_model_provider.model.stt import XInferenceSpeechToText
+from setting.models_provider.impl.xinference_model_provider.model.tts import XInferenceTextToSpeech
 from smartdoc.conf import PROJECT_DIR
 
 xinference_llm_model_credential = XinferenceLLMModelCredential()
+xinference_stt_model_credential = XInferenceSTTModelCredential()
+
 model_info_list = [
     ModelInfo(
         'code-llama',
@@ -270,6 +275,20 @@ model_info_list = [
         xinference_llm_model_credential,
         XinferenceChatModel
     ),
+    ModelInfo(
+        'CosyVoice-300M-SFT',
+        'CosyVoice-300M-SFT是一个小型的语音合成模型。',
+        ModelTypeConst.TTS,
+        xinference_stt_model_credential,
+        XInferenceTextToSpeech
+    ),
+    ModelInfo(
+        'Belle-whisper-large-v3-zh',
+        'Belle Whisper Large V3 是一个中文大型语音识别模型。',
+        ModelTypeConst.STT,
+        xinference_stt_model_credential,
+        XInferenceSpeechToText
+    ),
 ]
 
 xinference_embedding_model_credential = XinferenceEmbeddingModelCredential()