feat: 语音转文本

apps/setting/models_provider/base_model_provider.py

@@ -139,6 +139,8 @@ def encryption(message: str):
 class ModelTypeConst(Enum):
     LLM = {'code': 'LLM', 'message': '大语言模型'}
     EMBEDDING = {'code': 'EMBEDDING', 'message': '向量模型'}
+    STT = {'code': 'STT', 'message': '语音识别'}
+    TTS = {'code': 'TTS', 'message': '语音合成'}
 
 
 class ModelInfo:

apps/setting/models_provider/impl/base_stt.py

@@ -0,0 +1,14 @@
+# coding=utf-8
+from abc import abstractmethod
+
+from pydantic import BaseModel
+
+
+class BaseSpeechToText(BaseModel):
+    @abstractmethod
+    def check_auth(self):
+        pass
+
+    @abstractmethod
+    def speech_to_text(self, audio_file):
+        pass

apps/setting/models_provider/impl/base_tts.py

@@ -0,0 +1,14 @@
+# coding=utf-8
+from abc import abstractmethod
+
+from pydantic import BaseModel
+
+
+class BaseTextToSpeech(BaseModel):
+    @abstractmethod
+    def check_auth(self):
+        pass
+
+    @abstractmethod
+    def text_to_speech(self, text):
+        pass

apps/setting/models_provider/impl/openai_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 OpenAISTTModelCredential(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/openai_model_provider/model/stt.py

@@ -0,0 +1,54 @@
+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 OpenAISpeechToText(MaxKBBaseModel, BaseSpeechToText):
+    openai_api_base: str
+    openai_api_key: str
+
+    def __init__(self, api_base, api_key, **kwargs):
+        super().__init__(**kwargs)
+        self.openai_api_key = api_key
+        self.openai_api_base = 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 OpenAISpeechToText(
+            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.openai_api_base,
+            api_key=self.openai_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.openai_api_base,
+            api_key=self.openai_api_key
+        )
+        return client.audio.transcriptions.create(
+            model=self.model_name,
+            language="zh",
+            file=audio_file
+        )

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

@@ -0,0 +1,56 @@
+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 OpenAITextToSpeech(MaxKBBaseModel, BaseTextToSpeech):
+    openai_api_base: str
+    openai_api_key: str
+
+    def __init__(self, api_base, api_key, **kwargs):
+        super().__init__(**kwargs)
+        self.openai_api_key = api_key
+        self.openai_api_base = 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 OpenAITextToSpeech(
+            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.openai_api_base,
+            api_key=self.openai_api_key
+        )
+        response_list = client.models.with_raw_response.list()
+        # print(response_list)
+
+    def text_to_speech(self, text):
+        client = OpenAI(
+            base_url=self.openai_api_base,
+            api_key=self.openai_api_key
+        )
+        with client.audio.speech.with_streaming_response.create(
+                model=self.model_name,
+                voice="alloy",
+                input="建国是个大聪明",
+        ) as response:
+            # response.content
+            pass

apps/setting/models_provider/impl/openai_model_provider/openai_model_provider.py

@@ -13,11 +13,15 @@
     ModelTypeConst, ModelInfoManage
 from setting.models_provider.impl.openai_model_provider.credential.embedding import OpenAIEmbeddingCredential
 from setting.models_provider.impl.openai_model_provider.credential.llm import OpenAILLMModelCredential
+from setting.models_provider.impl.openai_model_provider.credential.stt import OpenAISTTModelCredential
 from setting.models_provider.impl.openai_model_provider.model.embedding import OpenAIEmbeddingModel
 from setting.models_provider.impl.openai_model_provider.model.llm import OpenAIChatModel
+from setting.models_provider.impl.openai_model_provider.model.stt import OpenAISpeechToText
+from setting.models_provider.impl.openai_model_provider.model.tts import OpenAITextToSpeech
 from smartdoc.conf import PROJECT_DIR
 
 openai_llm_model_credential = OpenAILLMModelCredential()
+openai_stt_model_credential = OpenAISTTModelCredential()
 model_info_list = [
     ModelInfo('gpt-3.5-turbo', '最新的gpt-3.5-turbo，随OpenAI调整而更新', ModelTypeConst.LLM,
               openai_llm_model_credential, OpenAIChatModel
@@ -58,7 +62,13 @@
               OpenAIChatModel),
     ModelInfo('gpt-4-1106-preview', '2023年11月6日的gpt-4-turbo快照，支持上下文长度128,000 tokens',
               ModelTypeConst.LLM, openai_llm_model_credential,
-              OpenAIChatModel)
+              OpenAIChatModel),
+    ModelInfo('whisper-1', '',
+              ModelTypeConst.STT, openai_stt_model_credential,
+              OpenAISpeechToText),
+    ModelInfo('tts-1', '',
+              ModelTypeConst.TTS, openai_stt_model_credential,
+              OpenAITextToSpeech)
 ]
 open_ai_embedding_credential = OpenAIEmbeddingCredential()
 model_info_embedding_list = [

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

@@ -0,0 +1,45 @@
+# 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 VolcanicEngineSTTModelCredential(BaseForm, BaseModelCredential):
+    volcanic_api_url = forms.TextInputField('API 域名', required=True)
+    volcanic_app_id = forms.TextInputField('App ID', required=True)
+    volcanic_token = forms.PasswordInputField('Token', required=True)
+    volcanic_cluster = forms.TextInputField('Cluster', 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 ['volcanic_api_url', 'volcanic_app_id', 'volcanic_token', 'volcanic_cluster']:
+            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, 'volcanic_token': super().encryption(model.get('volcanic_token', ''))}
+
+    def get_model_params_setting_form(self, model_name):
+        pass