refactor: 重构Gemini和OpenAI聊天服务以支持工具和安全设置

- 将 `_build_payload`、`_build_tools`、`_get_safety_settings` 和 `_has_image_parts` 函数从 `OpenAIChatService` 和 `GeminiChatService` 类中提取为独立的函数。
- 将 `_handle_stream_response` 和 `_handle_normal_response` 函数从 `GeminiResponseHandler` 和 `OpenAIResponseHandler` 类中提取为独立的函数。
- 将 `_extract_text` 函数从 `OpenAIResponseHandler` 类中提取为独立的函数, 并在 `GeminiResponseHandler` 中复用。
- 将 `_convert_image` 函数从 `OpenAIMessageConverter` 类中提取为独立的函数。
- 优化 `OpenAIChatService` 和 `GeminiChatService` 中的代码结构, 使其更清晰。
- 优化 `app/api/openai_routes.py` 和 `app/api/gemini_routes.py` 中的路由函数, 移除不必要的参数。

app/api/gemini_routes.py

@@ -1,5 +1,4 @@
-from http.client import HTTPException
-from fastapi import APIRouter, Depends
+from fastapi import APIRouter, Depends, HTTPException
 from fastapi.responses import StreamingResponse
 
 from app.core.config import settings
@@ -10,6 +9,7 @@ from app.services.gemini_chat_service import GeminiChatService
 from app.services.key_manager import KeyManager
 from app.services.model_service import ModelService
 from app.services.chat.retry_handler import RetryHandler
+
 router = APIRouter(prefix="/gemini/v1beta")
 router_v1beta = APIRouter(prefix="/v1beta")
 logger = get_gemini_logger()
@@ -22,26 +22,29 @@ model_service = ModelService(settings.MODEL_SEARCH)
 
 @router.get("/models")
 @router_v1beta.get("/models")
-async def list_models(
-        key: str = None,
-        token: str = Depends(security_service.verify_key),
-):
+async def list_models(_=Depends(security_service.verify_key)):
     """获取可用的Gemini模型列表"""
     logger.info("-" * 50 + "list_gemini_models" + "-" * 50)
     logger.info("Handling Gemini models list request")
     api_key = await key_manager.get_next_working_key()
     logger.info(f"Using API key: {api_key}")
     models_json = model_service.get_gemini_models(api_key)
-    models_json["models"].append({"name": "models/gemini-2.0-flash-exp-search", "version": "2.0", "displayName": "Gemini 2.0 Flash Search Experimental", "description": "Gemini 2.0 Flash Search Experimental", "inputTokenLimit": 32767, "outputTokenLimit": 8192, "supportedGenerationMethods": ["generateContent", "countTokens"], "temperature": 1, "topP": 0.95, "topK": 64, "maxTemperature": 2})
+    models_json["models"].append({"name": "models/gemini-2.0-flash-exp-search", "version": "2.0",
+                                  "displayName": "Gemini 2.0 Flash Search Experimental",
+                                  "description": "Gemini 2.0 Flash Search Experimental", "inputTokenLimit": 32767,
+                                  "outputTokenLimit": 8192,
+                                  "supportedGenerationMethods": ["generateContent", "countTokens"], "temperature": 1,
+                                  "topP": 0.95, "topK": 64, "maxTemperature": 2})
     return models_json
 
+
 @router.post("/models/{model_name}:generateContent")
 @router_v1beta.post("/models/{model_name}:generateContent")
 @RetryHandler(max_retries=3, key_manager=key_manager, key_arg="api_key")
 async def generate_content(
         model_name: str,
         request: GeminiRequest,
-        x_goog_api_key: str = Depends(security_service.verify_goog_api_key),
+        _=Depends(security_service.verify_goog_api_key),
         api_key: str = Depends(key_manager.get_next_working_key),
 ):
     chat_service = GeminiChatService(settings.BASE_URL, key_manager)
@@ -70,7 +73,7 @@ async def generate_content(
 async def stream_generate_content(
         model_name: str,
         request: GeminiRequest,
-        x_goog_api_key: str = Depends(security_service.verify_goog_api_key),
+        _=Depends(security_service.verify_goog_api_key),
         api_key: str = Depends(key_manager.get_next_working_key),
 ):
     chat_service = GeminiChatService(settings.BASE_URL, key_manager)
@@ -81,7 +84,7 @@ async def stream_generate_content(
     logger.info(f"Using API key: {api_key}")
 
     try:
-        response_stream =chat_service.stream_generate_content(
+        response_stream = chat_service.stream_generate_content(
             model=model_name,
             request=request,
             api_key=api_key

app/api/openai_routes.py

@@ -1,16 +1,15 @@
-from http.client import HTTPException
-from fastapi import APIRouter, Depends, Header
+from fastapi import HTTPException, APIRouter, Depends
 from fastapi.responses import StreamingResponse
 
+from app.core.config import settings
+from app.core.logger import get_openai_logger
 from app.core.security import SecurityService
+from app.schemas.openai_models import ChatRequest, EmbeddingRequest
 from app.services.chat.retry_handler import RetryHandler
+from app.services.embedding_service import EmbeddingService
 from app.services.key_manager import KeyManager
 from app.services.model_service import ModelService
 from app.services.openai_chat_service import OpenAIChatService
-from app.services.embedding_service import EmbeddingService
-from app.schemas.openai_models import ChatRequest, EmbeddingRequest
-from app.core.config import settings
-from app.core.logger import get_openai_logger
 
 router = APIRouter()
 logger = get_openai_logger()
@@ -24,10 +23,7 @@ embedding_service = EmbeddingService(settings.BASE_URL)
 
 @router.get("/v1/models")
 @router.get("/hf/v1/models")
-async def list_models(
-    authorization: str = Header(None),
-    token: str = Depends(security_service.verify_authorization),
-):
+async def list_models(_=Depends(security_service.verify_authorization)):
     logger.info("-" * 50 + "list_models" + "-" * 50)
     logger.info("Handling models list request")
     api_key = await key_manager.get_next_working_key()
@@ -43,10 +39,9 @@ async def list_models(
 @router.post("/hf/v1/chat/completions")
 @RetryHandler(max_retries=3, key_manager=key_manager, key_arg="api_key")
 async def chat_completion(
-    request: ChatRequest,
-    authorization: str = Header(None),
-    token: str = Depends(security_service.verify_authorization),
-    api_key: str = Depends(key_manager.get_next_working_key),
+        request: ChatRequest,
+        _=Depends(security_service.verify_authorization),
+        api_key: str = Depends(key_manager.get_next_working_key),
 ):
     chat_service = OpenAIChatService(settings.BASE_URL, key_manager)
     logger.info("-" * 50 + "chat_completion" + "-" * 50)
@@ -69,13 +64,11 @@ async def chat_completion(
         raise HTTPException(status_code=500, detail="Chat completion failed") from e
 
 
-
 @router.post("/v1/embeddings")
 @router.post("/hf/v1/embeddings")
 async def embedding(
-    request: EmbeddingRequest,
-    authorization: str = Header(None),
-    token: str = Depends(security_service.verify_authorization),
+        request: EmbeddingRequest,
+        _=Depends(security_service.verify_authorization),
 ):
     logger.info("-" * 50 + "embedding" + "-" * 50)
     logger.info(f"Handling embedding request for model: {request.model}")
@@ -95,8 +88,7 @@ async def embedding(
 @router.get("/v1/keys/list")
 @router.get("/hf/v1/keys/list")
 async def get_keys_list(
-    authorization: str = Header(None),
-    token: str = Depends(security_service.verify_auth_token),
+        _=Depends(security_service.verify_auth_token),
 ):
     """获取有效和无效的API key列表"""
     logger.info("-" * 50 + "get_keys_list" + "-" * 50)

app/core/security.py

@@ -17,7 +17,7 @@ class SecurityService:
         return key
 
     async def verify_authorization(
-        self, authorization: Optional[str] = Header(None)
+            self, authorization: Optional[str] = Header(None)
     ) -> str:
         if not authorization:
             logger.error("Missing Authorization header")

app/schemas/gemini_models.py

@@ -3,10 +3,8 @@ from pydantic import BaseModel
 
 
 class SafetySetting(BaseModel):
-    category: Optional[Literal[
-        "HARM_CATEGORY_HATE_SPEECH", "HARM_CATEGORY_DANGEROUS_CONTENT", "HARM_CATEGORY_HARASSMENT", "HARM_CATEGORY_SEXUALLY_EXPLICIT", "HARM_CATEGORY_CIVIC_INTEGRITY"]] = None
-    threshold: Optional[Literal[
-        "HARM_BLOCK_THRESHOLD_UNSPECIFIED", "BLOCK_LOW_AND_ABOVE", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_ONLY_HIGH", "BLOCK_NONE", "OFF"]] = None
+    category: Optional[Literal["HARM_CATEGORY_HATE_SPEECH", "HARM_CATEGORY_DANGEROUS_CONTENT", "HARM_CATEGORY_HARASSMENT", "HARM_CATEGORY_SEXUALLY_EXPLICIT", "HARM_CATEGORY_CIVIC_INTEGRITY"]] = None
+    threshold: Optional[Literal["HARM_BLOCK_THRESHOLD_UNSPECIFIED", "BLOCK_LOW_AND_ABOVE", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_ONLY_HIGH", "BLOCK_NONE", "OFF"]] = None
 
 
 class GenerationConfig(BaseModel):

app/services/chat/api_client.py

@@ -4,6 +4,7 @@ from typing import Dict, Any, AsyncGenerator
 import httpx
 from abc import ABC, abstractmethod
 
+
 class ApiClient(ABC):
     """API客户端基类"""
 
@@ -15,6 +16,7 @@ class ApiClient(ABC):
     async def stream_generate_content(self, payload: Dict[str, Any], model: str, api_key: str) -> AsyncGenerator[str, None]:
         pass
 
+
 class GeminiApiClient(ApiClient):
     """Gemini API客户端"""
 
@@ -40,7 +42,7 @@ class GeminiApiClient(ApiClient):
             model = model[:-7]
         async with httpx.AsyncClient(timeout=timeout) as client:
             url = f"{self.base_url}/models/{model}:streamGenerateContent?alt=sse&key={api_key}"
-            async with client.stream("POST", url, json=payload) as response:
+            async with client.stream(method="POST", url=url, json=payload) as response:
                 if response.status_code != 200:
                     error_content = await response.aread()
                     error_msg = error_content.decode("utf-8")

app/services/chat/message_converter.py

@@ -3,6 +3,7 @@
 from abc import ABC, abstractmethod
 from typing import List, Dict, Any
 
+
 class MessageConverter(ABC):
     """消息转换器基类"""
 
@@ -10,6 +11,22 @@ class MessageConverter(ABC):
     def convert(self, messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
         pass
 
+
+def _convert_image(image_url: str) -> Dict[str, Any]:
+    if image_url.startswith("data:image"):
+        return {
+            "inline_data": {
+                "mime_type": "image/jpeg",
+                "data": image_url.split(",")[1]
+            }
+        }
+    return {
+        "image_url": {
+            "url": image_url
+        }
+    }
+
+
 class OpenAIMessageConverter(MessageConverter):
     """OpenAI消息格式转换器"""
 
@@ -29,22 +46,8 @@ class OpenAIMessageConverter(MessageConverter):
                         if content["type"] == "text":
                             parts.append({"text": content["text"]})
                         elif content["type"] == "image_url":
-                            parts.append(self._convert_image(content["image_url"]["url"]))
+                            parts.append(_convert_image(content["image_url"]["url"]))
 
             converted_messages.append({"role": role, "parts": parts})
 
         return converted_messages
-        
-    def _convert_image(self, image_url: str) -> Dict[str, Any]:
-        if image_url.startswith("data:image"):
-            return {
-                "inline_data": {
-                    "mime_type": "image/jpeg",
-                    "data": image_url.split(",")[1]
-                }
-            }
-        return {
-            "image_url": {
-                "url": image_url
-            }
-        }

app/services/chat/response_handler.py

@@ -6,6 +6,7 @@ import time
 import uuid
 from app.core.config import settings
 
+
 class ResponseHandler(ABC):
     """响应处理器基类"""
 
@@ -13,6 +14,7 @@ class ResponseHandler(ABC):
     def handle_response(self, response: Dict[str, Any], model: str, stream: bool = False) -> Dict[str, Any]:
         pass
 
+
 class GeminiResponseHandler(ResponseHandler):
     """Gemini响应处理器"""
 
@@ -22,132 +24,46 @@ class GeminiResponseHandler(ResponseHandler):
 
     def handle_response(self, response: Dict[str, Any], model: str, stream: bool = False) -> Dict[str, Any]:
         if stream:
-            return self._handle_stream_response(response, model, stream)
-        return self._handle_normal_response(response, model, stream)
+            return _handle_gemini_stream_response(response, model, stream)
+        return _handle_gemini_normal_response(response, model, stream)
 
-    def _handle_stream_response(self, response: Dict[str, Any], model: str, stream: bool) -> Dict[str, Any]:
-        text = self._extract_text(response, model, stream=stream)
-        content = {"parts": [{"text": text}],"role": "model"}
-        response["candidates"][0]["content"] = content
-        return response
 
-    def _handle_normal_response(self, response: Dict[str, Any], model: str, stream: bool) -> Dict[str, Any]:
-        text = self._extract_text(response, model, stream=stream)
-        content = {"parts": [{"text": text}],"role": "model"}
-        response["candidates"][0]["content"] = content
-        return response
+def _handle_openai_stream_response(response: Dict[str, Any], model: str, finish_reason: str) -> Dict[str, Any]:
+    text = _extract_text(response, model, stream=True)
+    return {
+        "id": f"chatcmpl-{uuid.uuid4()}",
+        "object": "chat.completion.chunk",
+        "created": int(time.time()),
+        "model": model,
+        "choices": [{
+            "index": 0,
+            "delta": {"content": text} if text else {},
+            "finish_reason": finish_reason
+        }]
+    }
 
-    def _extract_text(self, response: Dict[str, Any], model: str, stream: bool = False) -> str:
-        text = ""
-        if stream:
-            if response.get("candidates"):
-                candidate = response["candidates"][0]
-                content = candidate.get("content", {})
-                parts = content.get("parts", [])
-                # if "thinking" in model:
-                #     if settings.SHOW_THINKING_PROCESS:  
-                #         if len(parts) == 1:
-                #             if self.thinking_first:
-                #                 self.thinking_first = False
-                #                 self.thinking_status = True
-                #                 text = "> thinking\n\n" + parts[0].get("text")
-                #             else:
-                #                 text = parts[0].get("text")
-
-                #         if len(parts) == 2:
-                #             self.thinking_status = False
-                #             if self.thinking_first:
-                #                 self.thinking_first = False
-                #                 text = (
-                #                     "> thinking\n\n"
-                #                     + parts[0].get("text")
-                #                     + "\n\n---\n> output\n\n"
-                #                     + parts[1].get("text")
-                #                 )
-                #             else:
-                #                 text = (
-                #                     parts[0].get("text")
-                #                     + "\n\n---\n> output\n\n"
-                #                     + parts[1].get("text")
-                #                 )
-                #     else:
-                #         if len(parts) == 1:
-                #             if self.thinking_first:
-                #                 self.thinking_first = False
-                #                 self.thinking_status = True
-                #                 text = ""
-                #             elif self.thinking_status:
-                #                 text = ""
-                #             else:
-                #                 text = parts[0].get("text")
-
-                #         if len(parts) == 2:
-                #             self.thinking_status = False
-                #             if self.thinking_first:
-                #                 self.thinking_first = False
-                #                 text = parts[1].get("text")
-                #             else:
-                #                 text = parts[1].get("text")
-                # else:
-                #     if "text" in parts[0]:
-                #         text = parts[0].get("text")
-                #     elif "executableCode" in parts[0]:
-                #         text = _format_code_block(parts[0]["executableCode"])
-                #     elif "codeExecution" in parts[0]:
-                #         text = _format_code_block(parts[0]["codeExecution"])
-                #     elif "executableCodeResult" in parts[0]:
-                #         text = _format_execution_result(
-                #             parts[0]["executableCodeResult"]
-                #         )
-                #     elif "codeExecutionResult" in parts[0]:
-                #         text = _format_execution_result(
-                #             parts[0]["codeExecutionResult"]
-                #         )
-                #     else:
-                #         text = ""
-                if "text" in parts[0]:
-                    text = parts[0].get("text")
-                elif "executableCode" in parts[0]:
-                    text = _format_code_block(parts[0]["executableCode"])
-                elif "codeExecution" in parts[0]:
-                    text = _format_code_block(parts[0]["codeExecution"])
-                elif "executableCodeResult" in parts[0]:
-                    text = _format_execution_result(
-                        parts[0]["executableCodeResult"]
-                    )
-                elif "codeExecutionResult" in parts[0]:
-                    text = _format_execution_result(
-                        parts[0]["codeExecutionResult"]
-                    )
-                else:
-                    text = ""
-                text = _add_search_link_text(model, candidate, text)
-        else:
-            if response.get("candidates"):
-                candidate = response["candidates"][0]
-                if "thinking" in model:
-                    if settings.SHOW_THINKING_PROCESS:
-                        if len(candidate["content"]["parts"]) == 2:
-                            text = (
-                                "> thinking\n\n"
-                                + candidate["content"]["parts"][0]["text"]
-                                + "\n\n---\n> output\n\n"
-                                + candidate["content"]["parts"][1]["text"]
-                            )
-                        else:
-                            text = candidate["content"]["parts"][0]["text"]
-                    else:
-                        if len(candidate["content"]["parts"]) == 2:
-                            text = candidate["content"]["parts"][1]["text"] 
-                        else:
-                            text = candidate["content"]["parts"][0]["text"]
-                else:
-                    text = candidate["content"]["parts"][0]["text"]
-                text = _add_search_link_text(model, candidate, text)
-            else:
-                text = "暂无返回"
-        return text
 
+def _handle_openai_normal_response(response: Dict[str, Any], model: str, finish_reason: str) -> Dict[str, Any]:
+    text = _extract_text(response, model, stream=False)
+    return {
+        "id": f"chatcmpl-{uuid.uuid4()}",
+        "object": "chat.completion",
+        "created": int(time.time()),
+        "model": model,
+        "choices": [{
+            "index": 0,
+            "message": {
+                "role": "assistant",
+                "content": text
+            },
+            "finish_reason": finish_reason
+        }],
+        "usage": {
+            "prompt_tokens": 0,
+            "completion_tokens": 0,
+            "total_tokens": 0
+        }
+    }
 
 
 class OpenAIResponseHandler(ResponseHandler):
@@ -159,163 +75,141 @@ class OpenAIResponseHandler(ResponseHandler):
         self.thinking_status = False
 
     def handle_response(
-        self, 
-        response: Dict[str, Any], 
-        model: str,
-        stream: bool = False,
-        finish_reason: str = None
+            self,
+            response: Dict[str, Any],
+            model: str,
+            stream: bool = False,
+            finish_reason: str = None
     ) -> Optional[Dict[str, Any]]:
         if stream:
-            return self._handle_stream_response(response, model, finish_reason)
-        return self._handle_normal_response(response, model, finish_reason)
+            return _handle_openai_stream_response(response, model, finish_reason)
+        return _handle_openai_normal_response(response, model, finish_reason)
 
-    def _handle_stream_response(self, response: Dict[str, Any], model: str, finish_reason: str) -> Dict[str, Any]:
-        text = self._extract_text(response, model, stream=True)
-        return {
-            "id": f"chatcmpl-{uuid.uuid4()}",
-            "object": "chat.completion.chunk",
-            "created": int(time.time()),
-            "model": model,
-            "choices": [{
-                "index": 0,
-                "delta": {"content": text} if text else {},
-                "finish_reason": finish_reason
-            }]
-        }
 
-    def _handle_normal_response(self, response: Dict[str, Any], model: str, finish_reason: str) -> Dict[str, Any]:
-        text = self._extract_text(response, model, stream=False)
-        return {
-            "id": f"chatcmpl-{uuid.uuid4()}",
-            "object": "chat.completion",
-            "created": int(time.time()),
-            "model": model,
-            "choices": [{
-                "index": 0,
-                "message": {
-                    "role": "assistant",
-                    "content": text
-                },
-                "finish_reason": finish_reason
-            }],
-            "usage": {
-                "prompt_tokens": 0,
-                "completion_tokens": 0,
-                "total_tokens": 0
-            }
-        }
+def _extract_text(response: Dict[str, Any], model: str, stream: bool = False) -> str:
+    text = ""
+    if stream:
+        if response.get("candidates"):
+            candidate = response["candidates"][0]
+            content = candidate.get("content", {})
+            parts = content.get("parts", [])
+            # if "thinking" in model:
+            #     if settings.SHOW_THINKING_PROCESS:
+            #         if len(parts) == 1:
+            #             if self.thinking_first:
+            #                 self.thinking_first = False
+            #                 self.thinking_status = True
+            #                 text = "> thinking\n\n" + parts[0].get("text")
+            #             else:
+            #                 text = parts[0].get("text")
 
-    def _extract_text(self, response: Dict[str, Any], model: str, stream: bool = False) -> str:
-        text = ""
-        if stream:
-            if response.get("candidates"):
-                candidate = response["candidates"][0]
-                content = candidate.get("content", {})
-                parts = content.get("parts", [])
-                # if "thinking" in model:
-                #     if settings.SHOW_THINKING_PROCESS:  
-                #         if len(parts) == 1:
-                #             if self.thinking_first:
-                #                 self.thinking_first = False
-                #                 self.thinking_status = True
-                #                 text = "> thinking\n\n" + parts[0].get("text")
-                #             else:
-                #                 text = parts[0].get("text")
+            #         if len(parts) == 2:
+            #             self.thinking_status = False
+            #             if self.thinking_first:
+            #                 self.thinking_first = False
+            #                 text = (
+            #                     "> thinking\n\n"
+            #                     + parts[0].get("text")
+            #                     + "\n\n---\n> output\n\n"
+            #                     + parts[1].get("text")
+            #                 )
+            #             else:
+            #                 text = (
+            #                     parts[0].get("text")
+            #                     + "\n\n---\n> output\n\n"
+            #                     + parts[1].get("text")
+            #                 )
+            #     else:
+            #         if len(parts) == 1:
+            #             if self.thinking_first:
+            #                 self.thinking_first = False
+            #                 self.thinking_status = True
+            #                 text = ""
+            #             elif self.thinking_status:
+            #                 text = ""
+            #             else:
+            #                 text = parts[0].get("text")
 
-                #         if len(parts) == 2:
-                #             self.thinking_status = False
-                #             if self.thinking_first:
-                #                 self.thinking_first = False
-                #                 text = (
-                #                     "> thinking\n\n"
-                #                     + parts[0].get("text")
-                #                     + "\n\n---\n> output\n\n"
-                #                     + parts[1].get("text")
-                #                 )
-                #             else:
-                #                 text = (
-                #                     parts[0].get("text")
-                #                     + "\n\n---\n> output\n\n"
-                #                     + parts[1].get("text")
-                #                 )
-                #     else:
-                #         if len(parts) == 1:
-                #             if self.thinking_first:
-                #                 self.thinking_first = False
-                #                 self.thinking_status = True
-                #                 text = ""
-                #             elif self.thinking_status:
-                #                 text = ""
-                #             else:
-                #                 text = parts[0].get("text")
-
-                #         if len(parts) == 2:
-                #             self.thinking_status = False
-                #             if self.thinking_first:
-                #                 self.thinking_first = False
-                #                 text = parts[1].get("text")
-                #             else:
-                #                 text = parts[1].get("text")
-                # else:
-                #     if "text" in parts[0]:
-                #         text = parts[0].get("text")
-                #     elif "executableCode" in parts[0]:
-                #         text = _format_code_block(parts[0]["executableCode"])
-                #     elif "codeExecution" in parts[0]:
-                #         text = _format_code_block(parts[0]["codeExecution"])
-                #     elif "executableCodeResult" in parts[0]:
-                #         text = _format_execution_result(
-                #             parts[0]["executableCodeResult"]
-                #         )
-                #     elif "codeExecutionResult" in parts[0]:
-                #         text = _format_execution_result(
-                #             parts[0]["codeExecutionResult"]
-                #         )
-                #     else:
-                #         text = ""
-                # text = _add_search_link_text(model, candidate, text)
-                if "text" in parts[0]:
-                    text = parts[0].get("text")
-                elif "executableCode" in parts[0]:
-                    text = _format_code_block(parts[0]["executableCode"])
-                elif "codeExecution" in parts[0]:
-                    text = _format_code_block(parts[0]["codeExecution"])
-                elif "executableCodeResult" in parts[0]:
-                    text = _format_execution_result(
-                        parts[0]["executableCodeResult"]
-                    )
-                elif "codeExecutionResult" in parts[0]:
-                    text = _format_execution_result(
-                        parts[0]["codeExecutionResult"]
-                    )
-                else:
-                    text = ""
-                text = _add_search_link_text(model, candidate, text)
-        else:
-            if response.get("candidates"):
-                candidate = response["candidates"][0]
-                if "thinking" in model:
-                    if settings.SHOW_THINKING_PROCESS:
-                        if len(candidate["content"]["parts"]) == 2:
-                            text = (
+            #         if len(parts) == 2:
+            #             self.thinking_status = False
+            #             if self.thinking_first:
+            #                 self.thinking_first = False
+            #                 text = parts[1].get("text")
+            #             else:
+            #                 text = parts[1].get("text")
+            # else:
+            #     if "text" in parts[0]:
+            #         text = parts[0].get("text")
+            #     elif "executableCode" in parts[0]:
+            #         text = _format_code_block(parts[0]["executableCode"])
+            #     elif "codeExecution" in parts[0]:
+            #         text = _format_code_block(parts[0]["codeExecution"])
+            #     elif "executableCodeResult" in parts[0]:
+            #         text = _format_execution_result(
+            #             parts[0]["executableCodeResult"]
+            #         )
+            #     elif "codeExecutionResult" in parts[0]:
+            #         text = _format_execution_result(
+            #             parts[0]["codeExecutionResult"]
+            #         )
+            #     else:
+            #         text = ""
+            if "text" in parts[0]:
+                text = parts[0].get("text")
+            elif "executableCode" in parts[0]:
+                text = _format_code_block(parts[0]["executableCode"])
+            elif "codeExecution" in parts[0]:
+                text = _format_code_block(parts[0]["codeExecution"])
+            elif "executableCodeResult" in parts[0]:
+                text = _format_execution_result(
+                    parts[0]["executableCodeResult"]
+                )
+            elif "codeExecutionResult" in parts[0]:
+                text = _format_execution_result(
+                    parts[0]["codeExecutionResult"]
+                )
+            else:
+                text = ""
+            text = _add_search_link_text(model, candidate, text)
+    else:
+        if response.get("candidates"):
+            candidate = response["candidates"][0]
+            if "thinking" in model:
+                if settings.SHOW_THINKING_PROCESS:
+                    if len(candidate["content"]["parts"]) == 2:
+                        text = (
                                 "> thinking\n\n"
                                 + candidate["content"]["parts"][0]["text"]
                                 + "\n\n---\n> output\n\n"
                                 + candidate["content"]["parts"][1]["text"]
-                            )
-                        else:
-                            text = candidate["content"]["parts"][0]["text"]
+                        )
                     else:
-                        if len(candidate["content"]["parts"]) == 2:
-                            text = candidate["content"]["parts"][1]["text"] 
-                        else:
-                            text = candidate["content"]["parts"][0]["text"]
+                        text = candidate["content"]["parts"][0]["text"]
                 else:
-                    text = candidate["content"]["parts"][0]["text"]
-                text = _add_search_link_text(model, candidate, text)
+                    if len(candidate["content"]["parts"]) == 2:
+                        text = candidate["content"]["parts"][1]["text"]
+                    else:
+                        text = candidate["content"]["parts"][0]["text"]
             else:
-                text = "暂无返回"
-        return text
+                text = candidate["content"]["parts"][0]["text"]
+            text = _add_search_link_text(model, candidate, text)
+        else:
+            text = "暂无返回"
+    return text
+
+
+def _handle_gemini_stream_response(response: Dict[str, Any], model: str, stream: bool) -> Dict[str, Any]:
+    text = _extract_text(response, model, stream=stream)
+    content = {"parts": [{"text": text}], "role": "model"}
+    response["candidates"][0]["content"] = content
+    return response
+
+
+def _handle_gemini_normal_response(response: Dict[str, Any], model: str, stream: bool) -> Dict[str, Any]:
+    text = _extract_text(response, model, stream=stream)
+    content = {"parts": [{"text": text}], "role": "model"}
+    response["candidates"][0]["content"] = content
+    return response
 
 
 def _format_code_block(code_data: dict) -> str:
@@ -325,12 +219,12 @@ def _format_code_block(code_data: dict) -> str:
     return f"""\n\n---\n\n【代码执行】\n```{language}\n{code}\n```\n"""
 
 
-def _add_search_link_text(model:str, candidate:dict, text:str) -> str:
+def _add_search_link_text(model: str, candidate: dict, text: str) -> str:
     if (
-        settings.SHOW_SEARCH_LINK
-        and model.endswith("-search")
-        and "groundingMetadata" in candidate
-        and "groundingChunks" in candidate["groundingMetadata"]
+            settings.SHOW_SEARCH_LINK
+            and model.endswith("-search")
+            and "groundingMetadata" in candidate
+            and "groundingChunks" in candidate["groundingMetadata"]
     ):
         grounding_chunks = candidate["groundingMetadata"]["groundingChunks"]
         text += "\n\n---\n\n"

app/services/chat/retry_handler.py

@@ -8,6 +8,7 @@ from app.services.key_manager import KeyManager
 T = TypeVar('T')
 logger = get_retry_logger()
 
+
 class RetryHandler:
     """重试处理装饰器"""
 

app/services/gemini_chat_service.py

@@ -10,6 +10,61 @@ from app.services.chat.response_handler import GeminiResponseHandler
 from app.services.key_manager import KeyManager
 
 logger = get_gemini_logger()
+
+
+def _has_image_parts(contents: List[Dict[str, Any]]) -> bool:
+    """判断消息是否包含图片部分"""
+    for content in contents:
+        if "parts" in content:
+            for part in content["parts"]:
+                if "image_url" in part or "inline_data" in part:
+                    return True
+    return False
+
+
+def _build_tools(model: str, payload: Dict[str, Any]) -> List[Dict[str, Any]]:
+    """构建工具"""
+    tools = []
+    if settings.TOOLS_CODE_EXECUTION_ENABLED and not (
+            model.endswith("-search") or "-thinking" in model
+    ) and not _has_image_parts(payload.get("contents", [])):
+        tools.append({"code_execution": {}})
+    if model.endswith("-search"):
+        tools.append({"googleSearch": {}})
+    return tools
+
+
+def _get_safety_settings(model: str) -> List[Dict[str, str]]:
+    """获取安全设置"""
+    if model == "gemini-2.0-flash-exp":
+        return [
+            {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "OFF"},
+            {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "OFF"},
+            {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "OFF"},
+            {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "OFF"},
+            {"category": "HARM_CATEGORY_CIVIC_INTEGRITY", "threshold": "OFF"}
+        ]
+    return [
+        {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_NONE"},
+        {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_NONE"},
+        {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_NONE"},
+        {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_NONE"},
+        {"category": "HARM_CATEGORY_CIVIC_INTEGRITY", "threshold": "BLOCK_NONE"}
+    ]
+
+
+def _build_payload(model: str, request: GeminiRequest) -> Dict[str, Any]:
+    """构建请求payload"""
+    payload = request.model_dump()
+    return {
+        "contents": payload.get("contents", []),
+        "tools": _build_tools(model, payload),
+        "safetySettings": _get_safety_settings(model),
+        "generationConfig": payload.get("generationConfig", {}),
+        "systemInstruction": payload.get("systemInstruction", [])
+    }
+
+
 class GeminiChatService:
     """聊天服务"""
 
@@ -20,7 +75,7 @@ class GeminiChatService:
 
     def generate_content(self, model: str, request: GeminiRequest, api_key: str) -> Dict[str, Any]:
         """生成内容"""
-        payload = self._build_payload(model, request)
+        payload = _build_payload(model, request)
         response = self.api_client.generate_content(payload, model, api_key)
         return self.response_handler.handle_response(response, model, stream=False)
 
@@ -28,7 +83,7 @@ class GeminiChatService:
         """流式生成内容"""
         retries = 0
         max_retries = 3
-        payload = self._build_payload(model, request)
+        payload = _build_payload(model, request)
         while retries < max_retries:
             try:
                 async for line in self.api_client.stream_generate_content(payload, model, api_key):
@@ -47,52 +102,3 @@ class GeminiChatService:
                 if retries >= max_retries:
                     logger.error(f"Max retries ({max_retries}) reached for streaming. Raising error")
                     break
-            
-    def _build_payload(self,model: str, request: GeminiRequest) -> Dict[str, Any]:
-        """构建请求payload"""
-        payload = request.model_dump()
-        return {
-            "contents": payload.get("contents", []),
-            "tools": self._build_tools(model, payload),
-            "safetySettings": self._get_safety_settings(model),
-            "generationConfig": payload.get("generationConfig", {}),
-            "systemInstruction": payload.get("systemInstruction", [])
-        }
-        
-    def _build_tools(self, model: str, payload: Dict[str, Any]) -> List[Dict[str, Any]]:
-        """构建工具"""
-        tools = []
-        if settings.TOOLS_CODE_EXECUTION_ENABLED and not (
-            model.endswith("-search") or "-thinking" in model
-        ) and not self._has_image_parts(payload.get("contents", [])):
-            tools.append({"code_execution": {}})
-        if model.endswith("-search"):
-            tools.append({"googleSearch": {}})
-        return tools
-    
-    def _has_image_parts(self, contents: List[Dict[str, Any]]) -> bool:
-        """判断消息是否包含图片部分"""
-        for content in contents:
-            if "parts" in content:
-                for part in content["parts"]:
-                    if "image_url" in part or "inline_data" in part:
-                        return True
-        return False
-        
-    def _get_safety_settings(self, model: str) -> List[Dict[str, str]]:
-        """获取安全设置"""
-        if model == "gemini-2.0-flash-exp":
-            return [
-                {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "OFF"},
-                {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "OFF"},
-                {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "OFF"},
-                {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "OFF"},
-                {"category": "HARM_CATEGORY_CIVIC_INTEGRITY", "threshold": "OFF"}
-            ]
-        return [
-            {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_NONE"},
-            {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_NONE"},
-            {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_NONE"},
-            {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_NONE"},
-            {"category": "HARM_CATEGORY_CIVIC_INTEGRITY", "threshold": "BLOCK_NONE"}
-        ]

app/services/model_service.py

@@ -36,9 +36,9 @@ class ModelService:
             return None
 
     def convert_to_openai_models_format(
-        self, gemini_models: Dict[str, Any]
+            self, gemini_models: Dict[str, Any]
     ) -> Dict[str, Any]:
-        openai_format = {"object": "list", "data": [],"success": True}
+        openai_format = {"object": "list", "data": [], "success": True}
 
         for model in gemini_models.get("models", []):
             model_id = model["name"].split("/")[-1]

app/services/openai_chat_service.py

@@ -13,6 +13,76 @@ from app.services.key_manager import KeyManager
 logger = get_openai_logger()
 
 
+def _has_image_parts(contents: List[Dict[str, Any]]) -> bool:
+    """判断消息是否包含图片部分"""
+    for content in contents:
+        if "parts" in content:
+            for part in content["parts"]:
+                if "image_url" in part or "inline_data" in part:
+                    return True
+    return False
+
+
+def _build_tools(
+        request: ChatRequest, messages: List[Dict[str, Any]]
+) -> List[Dict[str, Any]]:
+    """构建工具"""
+    tools = []
+    model = request.model
+
+    if (
+        settings.TOOLS_CODE_EXECUTION_ENABLED
+        and not (model.endswith("-search") or "-thinking" in model)
+        and not _has_image_parts(messages)
+    ):
+        tools.append({"code_execution": {}})
+    if model.endswith("-search"):
+        tools.append({"googleSearch": {}})
+    return tools
+
+
+def _get_safety_settings(model: str) -> List[Dict[str, str]]:
+    """获取安全设置"""
+    # if (
+    #     "2.0" in model
+    #     and "gemini-2.0-flash-thinking-exp" not in model
+    #     and "gemini-2.0-pro-exp" not in model
+    # ):
+    if model == "gemini-2.0-flash-exp":
+        return [
+            {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "OFF"},
+            {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "OFF"},
+            {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "OFF"},
+            {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "OFF"},
+            {"category": "HARM_CATEGORY_CIVIC_INTEGRITY", "threshold": "OFF"},
+        ]
+    return [
+        {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_NONE"},
+        {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_NONE"},
+        {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_NONE"},
+        {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_NONE"},
+        {"category": "HARM_CATEGORY_CIVIC_INTEGRITY", "threshold": "BLOCK_NONE"},
+    ]
+
+
+def _build_payload(
+        request: ChatRequest, messages: List[Dict[str, Any]]
+) -> Dict[str, Any]:
+    """构建请求payload"""
+    return {
+        "contents": messages,
+        "generationConfig": {
+            "temperature": request.temperature,
+            "maxOutputTokens": request.max_tokens,
+            "stopSequences": request.stop,
+            "topP": request.top_p,
+            "topK": request.top_k,
+        },
+        "tools": _build_tools(request, messages),
+        "safetySettings": _get_safety_settings(request.model),
+    }
+
+
 class OpenAIChatService:
     """聊天服务"""
 
@@ -32,7 +102,7 @@ class OpenAIChatService:
         messages = self.message_converter.convert(request.messages)
 
         # 构建请求payload
-        payload = self._build_payload(request, messages)
+        payload = _build_payload(request, messages)
 
         if request.stream:
             return self._handle_stream_completion(request.model, payload, api_key)
@@ -84,69 +154,3 @@ class OpenAIChatService:
                     yield f"data: {json.dumps({'error': 'Streaming failed after retries'})}\n\n"
                     yield "data: [DONE]\n\n"
                     break
-
-    def _build_payload(
-        self, request: ChatRequest, messages: List[Dict[str, Any]]
-    ) -> Dict[str, Any]:
-        """构建请求payload"""
-        return {
-            "contents": messages,
-            "generationConfig": {
-                "temperature": request.temperature,
-                "maxOutputTokens": request.max_tokens,
-                "stopSequences": request.stop,
-                "topP": request.top_p,
-                "topK": request.top_k,
-            },
-            "tools": self._build_tools(request, messages),
-            "safetySettings": self._get_safety_settings(request.model),
-        }
-
-    def _build_tools(
-        self, request: ChatRequest, messages: List[Dict[str, Any]]
-    ) -> List[Dict[str, Any]]:
-        """构建工具"""
-        tools = []
-        model = request.model
-
-        if (
-            settings.TOOLS_CODE_EXECUTION_ENABLED
-            and not (model.endswith("-search") or "-thinking" in model)
-            and not self._has_image_parts(messages)
-        ):
-            tools.append({"code_execution": {}})
-        if model.endswith("-search"):
-            tools.append({"googleSearch": {}})
-        return tools
-
-    def _has_image_parts(self, contents: List[Dict[str, Any]]) -> bool:
-        """判断消息是否包含图片部分"""
-        for content in contents:
-            if "parts" in content:
-                for part in content["parts"]:
-                    if "image_url" in part or "inline_data" in part:
-                        return True
-        return False
-
-    def _get_safety_settings(self, model: str) -> List[Dict[str, str]]:
-        """获取安全设置"""
-        # if (
-        #     "2.0" in model
-        #     and "gemini-2.0-flash-thinking-exp" not in model
-        #     and "gemini-2.0-pro-exp" not in model
-        # ):
-        if model == "gemini-2.0-flash-exp":
-            return [
-                {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "OFF"},
-                {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "OFF"},
-                {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "OFF"},
-                {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "OFF"},
-                {"category": "HARM_CATEGORY_CIVIC_INTEGRITY", "threshold": "OFF"},
-            ]
-        return [
-            {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_NONE"},
-            {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_NONE"},
-            {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_NONE"},
-            {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_NONE"},
-            {"category": "HARM_CATEGORY_CIVIC_INTEGRITY", "threshold": "BLOCK_NONE"},
-        ]