Merge remote-tracking branch 'origin/main'

apps/setting/models_provider/impl/azure_model_provider/azure_model_provider.py

@@ -10,7 +10,7 @@
 from typing import Dict
 
 from langchain.schema import HumanMessage
-from langchain_community.chat_models import AzureChatOpenAI
+from langchain_community.chat_models.azure_openai import AzureChatOpenAI
 
 from common import froms
 from common.exception.app_exception import AppApiException
@@ -29,9 +29,6 @@ def is_valid(self, model_type: str, model_name, model_credential: Dict[str, obje
         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')
 
-        if model_name not in model_dict:
-            raise AppApiException(ValidCode.valid_error.value, f'{model_name} 模型名称不支持')
-
         for key in ['api_base', 'api_key', 'deployment_name']:
             if key not in model_credential:
                 if raise_exception:
@@ -40,7 +37,43 @@ def is_valid(self, model_type: str, model_name, model_credential: Dict[str, obje
                     return False
         try:
             model = AzureModelProvider().get_model(model_type, model_name, model_credential)
-            model.invoke([HumanMessage(content='valid')])
+            model.invoke([HumanMessage(content='你好')])
+        except Exception as e:
+            if isinstance(e, AppApiException):
+                raise e
+            if raise_exception:
+                raise AppApiException(ValidCode.valid_error.value, '校验失败,请检查参数是否正确')
+            else:
+                return False
+
+        return True
+
+    def encryption_dict(self, model: Dict[str, object]):
+        return {**model, 'api_key': super().encryption(model.get('api_key', ''))}
+
+    api_base = froms.TextInputField('API 域名', required=True)
+
+    api_key = froms.PasswordInputField("API Key", required=True)
+
+    deployment_name = froms.TextInputField("部署名", required=True)
+
+
+class DefaultAzureLLMModelCredential(BaseForm, BaseModelCredential):
+
+    def is_valid(self, model_type: str, model_name, model_credential: Dict[str, object], raise_exception=False):
+        model_type_list = AzureModelProvider().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', 'deployment_name', 'api_version']:
+            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 = AzureModelProvider().get_model(model_type, model_name, model_credential)
+            model.invoke([HumanMessage(content='你好')])
         except Exception as e:
             if isinstance(e, AppApiException):
                 raise e
@@ -54,6 +87,8 @@ def is_valid(self, model_type: str, model_name, model_credential: Dict[str, obje
     def encryption_dict(self, model: Dict[str, object]):
         return {**model, 'api_key': super().encryption(model.get('api_key', ''))}
 
+    api_version = froms.TextInputField("api_version", required=True)
+
     api_base = froms.TextInputField('API 域名', required=True)
 
     api_key = froms.PasswordInputField("API Key", required=True)
@@ -63,6 +98,8 @@ def encryption_dict(self, model: Dict[str, object]):
 
 azure_llm_model_credential = AzureLLMModelCredential()
 
+base_azure_llm_model_credential = DefaultAzureLLMModelCredential()
+
 model_dict = {
     'gpt-3.5-turbo-0613': ModelInfo('gpt-3.5-turbo-0613', '', ModelTypeConst.LLM, azure_llm_model_credential,
                                     api_version='2023-07-01-preview'),
@@ -84,18 +121,18 @@ def get_model(self, model_type, model_name, model_credential: Dict[str, object],
         model_info: ModelInfo = model_dict.get(model_name)
         azure_chat_open_ai = AzureChatOpenAI(
             openai_api_base=model_credential.get('api_base'),
-            openai_api_version=model_info.api_version,
+            openai_api_version=model_credential.get(
+                'api_version') if 'api_version' in model_credential else model_info.api_version,
             deployment_name=model_credential.get('deployment_name'),
             openai_api_key=model_credential.get('api_key'),
-            openai_api_type="azure",
-            tiktoken_model_name=model_name
+            openai_api_type="azure"
         )
         return azure_chat_open_ai
 
     def get_model_credential(self, model_type, model_name):
         if model_name in model_dict:
             return model_dict.get(model_name).model_credential
-        raise AppApiException(500, f'不支持的模型:{model_name}')
+        return base_azure_llm_model_credential
 
     def get_model_provide_info(self):
         return ModelProvideInfo(provider='model_azure_provider', name='Azure OpenAI', icon=get_file_content(

apps/setting/models_provider/impl/wenxin_model_provider/wenxin_model_provider.py

@@ -9,8 +9,9 @@
 import os
 from typing import Dict
 
-from langchain_community.chat_models import QianfanChatEndpoint
 from langchain.schema import HumanMessage
+from langchain_community.chat_models import QianfanChatEndpoint
+from qianfan import ChatCompletion
 
 from common import froms
 from common.exception.app_exception import AppApiException
@@ -27,10 +28,9 @@ def is_valid(self, model_type: str, model_name, model_credential: Dict[str, obje
         model_type_list = WenxinModelProvider().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')
-
-        if model_name not in model_dict:
-            raise AppApiException(ValidCode.valid_error.value, f'{model_name} 模型名称不支持')
-
+        model_info = [model.lower() for model in ChatCompletion.models()]
+        if not model_info.__contains__(model_name.lower()):
+            raise AppApiException(ValidCode.valid_error.value, f'{model_name} 模型不支持')
         for key in ['api_key', 'secret_key']:
             if key not in model_credential:
                 if raise_exception:
@@ -39,10 +39,9 @@ def is_valid(self, model_type: str, model_name, model_credential: Dict[str, obje
                     return False
         try:
             WenxinModelProvider().get_model(model_type, model_name, model_credential).invoke(
-                [HumanMessage(content='valid')])
+                [HumanMessage(content='你好')])
         except Exception as e:
-            if raise_exception:
-                raise AppApiException(ValidCode.valid_error.value, "校验失败,请检查 api_key secret_key 是否正确")
+            raise e
         return True
 
     def encryption_dict(self, model_info: Dict[str, object]):
@@ -121,7 +120,7 @@ def get_model_list(self, model_type):
     def get_model_credential(self, model_type, model_name):
         if model_name in model_dict:
             return model_dict.get(model_name).model_credential
-        raise AppApiException(500, f'不支持的模型:{model_name}')
+        return win_xin_llm_model_credential
 
     def get_model_provide_info(self):
         return ModelProvideInfo(provider='model_wenxin_provider', name='千帆大模型', icon=get_file_content(

pyproject.toml

@@ -23,7 +23,7 @@ sentence-transformers = "^2.2.2"
 blinker = "^1.6.3"
 openai = "^1.13.3"
 tiktoken = "^0.5.1"
-qianfan = "^0.1.1"
+qianfan = "^0.3.6.1"
 pycryptodome = "^3.19.0"
 beautifulsoup4 = "^4.12.2"
 html2text = "^2024.2.26"