refactor(router): Use dependency injection for chat services

Refactor GeminiChatService and OpenAIChatService instantiation
in gemini_routes.py and openai_routes.py respectively.

Utilize FastAPI's dependency injection (`Depends`) to manage
chat service instances per request, ensuring consistency and
adhering to FastAPI best practices. This removes manual
service creation within the route handlers.

app/router/gemini_routes.py

@@ -31,6 +31,11 @@ async def get_next_working_key(key_manager: KeyManager = Depends(get_key_manager
     return await key_manager.get_next_working_key()
 
 
+async def get_chat_service(key_manager: KeyManager = Depends(get_key_manager)):
+    """获取Gemini聊天服务实例"""
+    return GeminiChatService(settings.BASE_URL, key_manager)
+
+
 @router.get("/models")
 @router_v1beta.get("/models")
 async def list_models(
@@ -88,7 +93,7 @@ async def generate_content(
     request: GeminiRequest,
     _=Depends(security_service.verify_key_or_goog_api_key),
     api_key: str = Depends(get_next_working_key),
-    key_manager: KeyManager = Depends(get_key_manager)
+    chat_service: GeminiChatService = Depends(get_chat_service)
 ):
     """非流式生成内容"""
     logger.info("-" * 50 + "gemini_generate_content" + "-" * 50)
@@ -100,7 +105,6 @@ async def generate_content(
         raise HTTPException(status_code=400, detail=f"Model {model_name} is not supported")
     
     try:
-        chat_service = GeminiChatService(settings.BASE_URL, key_manager)
         response = await chat_service.generate_content(
             model=model_name,
             request=request,
@@ -120,7 +124,7 @@ async def stream_generate_content(
     request: GeminiRequest,
     _=Depends(security_service.verify_key_or_goog_api_key),
     api_key: str = Depends(get_next_working_key),
-    key_manager: KeyManager = Depends(get_key_manager)
+    chat_service: GeminiChatService = Depends(get_chat_service)
 ):
     """流式生成内容"""
     logger.info("-" * 50 + "gemini_stream_generate_content" + "-" * 50)
@@ -132,7 +136,6 @@ async def stream_generate_content(
         raise HTTPException(status_code=400, detail=f"Model {model_name} is not supported")
     
     try:
-        chat_service = GeminiChatService(settings.BASE_URL, key_manager)
         response_stream = chat_service.stream_generate_content(
             model=model_name,
             request=request,
@@ -145,14 +148,12 @@ async def stream_generate_content(
 
 
 @router.post("/verify-key/{api_key}")
-async def verify_key(api_key: str):
+async def verify_key(api_key: str, chat_service: GeminiChatService = Depends(get_chat_service)):
     """验证Gemini API密钥的有效性"""
     logger.info("-" * 50 + "verify_gemini_key" + "-" * 50)
     logger.info("Verifying API key validity")
     
     try:
-        key_manager = await get_key_manager()
-        chat_service = GeminiChatService(settings.BASE_URL, key_manager)
         
         # 使用generate_content接口测试key的有效性
         gemini_request = GeminiRequest(

app/router/openai_routes.py

@@ -36,6 +36,11 @@ async def get_next_working_key_wrapper(
     return await key_manager.get_next_working_key()
 
 
+async def get_openai_chat_service(key_manager: KeyManager = Depends(get_key_manager)):
+    """获取OpenAI聊天服务实例"""
+    return OpenAIChatService(settings.BASE_URL, key_manager)
+
+
 @router.get("/v1/models")
 @router.get("/hf/v1/models")
 async def list_models(
@@ -62,12 +67,12 @@ async def chat_completion(
     request: ChatRequest,
     _=Depends(security_service.verify_authorization),
     api_key: str = Depends(get_next_working_key_wrapper),
-    key_manager: KeyManager = Depends(get_key_manager),
+    key_manager: KeyManager = Depends(get_key_manager), # 保留 key_manager 用于获取 paid_key
+    chat_service: OpenAIChatService = Depends(get_openai_chat_service),
 ):
     # 如果model是imagen3,使用paid_key
     if request.model == f"{settings.CREATE_IMAGE_MODEL}-chat":
         api_key = await key_manager.get_paid_key()
-    chat_service = OpenAIChatService(settings.BASE_URL, key_manager)
     logger.info("-" * 50 + "chat_completion" + "-" * 50)
     logger.info(f"Handling chat completion request for model: {request.model}")
     logger.info(f"Request: \n{request.model_dump_json(indent=2)}")