添加proxy代理功能

config-template.py

@@ -20,6 +20,7 @@ mirai_http_api_config = {
 
 # [必需] OpenAI的配置
 # api_key: OpenAI的API Key
+# http_proxy: 请求OpenAI时使用的代理，None为不使用，https和socks5暂不能使用
 # 若只有一个api-key，请直接修改以下内容中的"openai_api_key"为你的api-key
 #
 # 如准备了多个api-key，可以以字典的形式填写，程序会自动选择可用的api-key
@@ -30,11 +31,13 @@ mirai_http_api_config = {
 #         "key1": "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
 #         "key2": "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
 #     },
+#     "http_proxy": "http://127.0.0.1:12345"
 # }
 openai_config = {
     "api_key": {
         "default": "openai_api_key"
     },
+    "http_proxy": None
 }
 
 # [必需] 管理员QQ号，用于接收报错等通知及执行管理员级别指令

pkg/openai/manager.py

@@ -36,7 +36,11 @@ class OpenAIInteract:
         config = pkg.utils.context.get_config()
 
         # 根据模型选择使用的接口
-        ai: ModelRequest = create_openai_model_request(config.completion_api_params['model'], 'user')
+        ai: ModelRequest = create_openai_model_request(
+            config.completion_api_params['model'], 
+            'user', 
+            config.openai_config["http_proxy"]
+        )
         ai.request(
             prompts,
             **config.completion_api_params

pkg/openai/modelmgr.py

@@ -1,5 +1,5 @@
 # 提供与模型交互的抽象接口
-import openai, logging
+import openai, logging, threading, asyncio
 
 COMPLETION_MODELS = {
     'text-davinci-003',
@@ -26,48 +26,74 @@ IMAGE_MODELS = {
 
 
 class ModelRequest():
-    """模型请求抽象类"""
+    """GPT父类"""
     can_chat = False
+    runtime:threading.Thread = None
+    ret = ""
+    proxy:str = None
 
-    def __init__(self, model_name, user_name, request_fun):
+    def __init__(self, model_name, user_name, request_fun, http_proxy:str = None):
         self.model_name = model_name
         self.user_name = user_name
         self.request_fun = request_fun
+        if http_proxy != None:
+            self.proxy = http_proxy
+            openai.proxy = self.proxy
+
+    async def __a_request__(self, **kwargs):
+        self.ret = await self.request_fun(**kwargs)
 
     def request(self, **kwargs):
-        ret = self.request_fun(**kwargs)
-        self.ret = self.ret_handle(ret)
-        self.message = self.ret["choices"][0]["message"]
+        if self.proxy != None: #异步请求
+            self.runtime = threading.Thread(
+                target=asyncio.run,
+                args=(self.__a_request__(**kwargs),)
+            )
+            self.runtime.start()
+        else: #同步请求
+            self.ret = self.request_fun(**kwargs)
 
     def __msg_handle__(self, msg):
         """将prompt dict转换成接口需要的格式"""
         return msg
     
     def ret_handle(self):
+        '''
+        API消息返回处理函数
+        若重写该方法，应检查异步线程状态，或在需要检查处super该方法
+        '''
+        if self.runtime != None and isinstance(self.runtime, threading.Thread):
+            self.runtime.join()
         return
-    
+
     def get_total_tokens(self):
-        return self.ret['usage']['total_tokens']
-    
+        try:
+            return self.ret['usage']['total_tokens']
+        except Exception:
+            return 0
+
     def get_message(self):
         return self.message
-    
+
     def get_response(self):
         return self.ret
-    
 
 class ChatCompletionModel(ModelRequest):
-    """ChatCompletion接口实现"""
+    """ChatCompletion类模型"""
     Chat_role = ['system', 'user', 'assistant']
-    def __init__(self, model_name, user_name):
-        request_fun = openai.ChatCompletion.create
+    def __init__(self, model_name, user_name, http_proxy:str = None, **kwargs):
+        if http_proxy == None:
+            request_fun = openai.ChatCompletion.create
+        else:
+            request_fun = openai.ChatCompletion.acreate
         self.can_chat = True
-        super().__init__(model_name, user_name, request_fun)
+        super().__init__(model_name, user_name, request_fun, http_proxy, **kwargs)
 
     def request(self, prompts, **kwargs):
-        self.ret = self.request_fun(messages = self.__msg_handle__(prompts), **kwargs, user=self.user_name)
+        prompts = self.__msg_handle__(prompts)
+        kwargs['messages'] = prompts
+        super().request(**kwargs)
         self.ret_handle()
-        self.message = self.ret["choices"][0]["message"]['content']
 
     def __msg_handle__(self, msgs):
         temp_msgs = []
@@ -76,20 +102,24 @@ class ChatCompletionModel(ModelRequest):
             temp_msgs.append(msg.copy())
         return temp_msgs
 
-    def get_content(self):
-        return self.message
-    
+    def get_message(self):
+        return self.ret["choices"][0]["message"]['content'] #需要时直接加载加快请求速度，降低内存消耗
+
 
 class CompletionModel(ModelRequest):
-    """Completion接口实现"""
-    def __init__(self, model_name, user_name):
-        request_fun = openai.Completion.create
-        super().__init__(model_name, user_name, request_fun)
+    """Completion类模型"""
+    def __init__(self, model_name, user_name, http_proxy:str = None, **kwargs):
+        if http_proxy == None:
+            request_fun = openai.Completion.create
+        else:
+            request_fun = openai.Completion.acreate
+        super().__init__(model_name, user_name, request_fun, http_proxy, **kwargs)
 
     def request(self, prompts, **kwargs):
-        self.ret = self.request_fun(prompt = self.__msg_handle__(prompts), **kwargs)
+        prompts = self.__msg_handle__(prompts)
+        kwargs['prompt'] = prompts
+        super().request(**kwargs)
         self.ret_handle()
-        self.message = self.ret["choices"][0]["text"]
 
     def __msg_handle__(self, msgs):
         prompt = ''
@@ -102,17 +132,17 @@ class CompletionModel(ModelRequest):
         #         prompt = prompt + "{}:{}\n".format(msg['role'] , msg['content'])
         prompt = prompt + "assistant: "
         return prompt
-    
-    def get_text(self):
-        return self.message
-    
 
-def create_openai_model_request(model_name: str, user_name: str = 'user') -> ModelRequest:
+    def get_message(self):
+        return self.ret["choices"][0]["text"]
+
+
+def create_openai_model_request(model_name: str, user_name: str = 'user', http_proxy:str = None) -> ModelRequest:
     """使用给定的模型名称创建模型请求对象"""
     if model_name in CHAT_COMPLETION_MODELS:
-        model = ChatCompletionModel(model_name, user_name)
+        model = ChatCompletionModel(model_name, user_name, http_proxy)
     elif model_name in COMPLETION_MODELS:
-        model = CompletionModel(model_name, user_name)
+        model = CompletionModel(model_name, user_name, http_proxy)
     else :
         log = "找不到模型[{}]，请检查配置文件".format(model_name)
         logging.error(log)