fix: 修正Dockerfile中TOOLS_CODE_EXECUTION_ENABLED环境变量的拼写错误

将TOOLS_CODE_EXECUTION_ENABLED环境变量的值从"fasle"更正为"false"，修复了拼写错误。

.env.example

@@ -2,7 +2,8 @@ API_KEYS=["AIzaSyxxxxxxxxxxxxxxxxxxx","AIzaSyxxxxxxxxxxxxxxxxxxx"]
 ALLOWED_TOKENS=["sk-123456"]
 # AUTH_TOKEN=sk-123456
 MODEL_SEARCH=["gemini-2.0-flash-exp","gemini-2.0-pro-exp"]
-TOOLS_CODE_EXECUTION_ENABLED=true
+MODEL_IMAGE=["gemini-2.0-flash-exp"]
+TOOLS_CODE_EXECUTION_ENABLED=false
 SHOW_SEARCH_LINK=true
 SHOW_THINKING_PROCESS=true
 BASE_URL=https://generativelanguage.googleapis.com/v1beta
@@ -12,4 +13,12 @@ PAID_KEY=AIzaSyxxxxxxxxxxxxxxxxxxx
 CREATE_IMAGE_MODEL=imagen-3.0-generate-002
 UPLOAD_PROVIDER=smms
 SMMS_SECRET_TOKEN=XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
+PICGO_API_KEY=xxxx
+##########################################################################
+#########################stream_optimizer 相关配置########################
+STREAM_MIN_DELAY=0.016
+STREAM_MAX_DELAY=0.024
+STREAM_SHORT_TEXT_THRESHOLD=10
+STREAM_LONG_TEXT_THRESHOLD=50
+STREAM_CHUNK_SIZE=5
 ##########################################################################

Dockerfile

@@ -10,7 +10,7 @@ COPY ./app /app/app
 ENV API_KEYS='["your_api_key_1"]'
 ENV ALLOWED_TOKENS='["your_token_1"]'
 ENV BASE_URL=https://generativelanguage.googleapis.com/v1beta
-ENV TOOLS_CODE_EXECUTION_ENABLED=true
+ENV TOOLS_CODE_EXECUTION_ENABLED=false
 ENV MODEL_SEARCH='["gemini-2.0-flash-exp"]'
 
 # Expose port

README.md

@@ -76,6 +76,13 @@
     # 图片上传配置
     UPLOAD_PROVIDER="smms"  # 图片上传提供商，目前支持smms
     SMMS_SECRET_TOKEN="your-smms-token"  # SM.MS图床的API Token
+
+    # stream_optimizer 相关配置
+    STREAM_MIN_DELAY=0.016
+    STREAM_MAX_DELAY=0.024
+    STREAM_SHORT_TEXT_THRESHOLD=10
+    STREAM_LONG_TEXT_THRESHOLD=50
+    STREAM_CHUNK_SIZE=5
     ```
 
    ### 配置说明
@@ -136,6 +143,24 @@
       - 用途: 用于图片上传到 SM.MS 图床
       - 获取方式: 需要在 SM.MS 官网注册并获取
 
+   #### 流式输出优化配置
+
+    - `STREAM_MIN_DELAY`: 最小延迟时间
+      - 默认值: `0.016`（秒）
+      - 说明: 长文本输出时使用的最小延迟时间，值越小输出速度越快
+    - `STREAM_MAX_DELAY`: 最大延迟时间
+      - 默认值: `0.024`（秒）
+      - 说明: 短文本输出时使用的最大延迟时间，值越大输出速度越慢
+    - `STREAM_SHORT_TEXT_THRESHOLD`: 短文本阈值
+      - 默认值: `10`（字符）
+      - 说明: 小于此长度的文本被视为短文本，将使用最大延迟输出
+    - `STREAM_LONG_TEXT_THRESHOLD`: 长文本阈值
+      - 默认值: `50`（字符）
+      - 说明: 大于此长度的文本被视为长文本，将使用最小延迟并分块输出
+    - `STREAM_CHUNK_SIZE`: 长文本分块大小
+      - 默认值: `5`（字符）
+      - 说明: 长文本分块输出时，每个块的大小
+
 ### ▶️ 运行
 
 #### 使用 Docker (推荐)

app/api/gemini_routes.py

@@ -1,6 +1,6 @@
 from fastapi import APIRouter, Depends, HTTPException
 from fastapi.responses import StreamingResponse, JSONResponse
-
+from copy import deepcopy
 from app.core.config import settings
 from app.core.logger import get_gemini_logger
 from app.core.security import SecurityService
@@ -23,7 +23,7 @@ async def get_key_manager():
 async def get_next_working_key_wrapper(key_manager: KeyManager = Depends(get_key_manager)):
     return await key_manager.get_next_working_key()
 
-model_service = ModelService(settings.MODEL_SEARCH)
+model_service = ModelService(settings.MODEL_SEARCH,settings.MODEL_IMAGE)
 
 
 @router.get("/models")
@@ -36,12 +36,40 @@ async def list_models(_=Depends(security_service.verify_key),
     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",
+    # 模型名称以及对应的详细信息
-                                  "description": "Gemini 2.0 Flash Search Experimental", "inputTokenLimit": 32767,
+    model_mapping = {x.get("name", "").split("/", maxsplit=1)[1]: x for x in models_json["models"]}
-                                  "outputTokenLimit": 8192,
+
-                                  "supportedGenerationMethods": ["generateContent", "countTokens"], "temperature": 1,
+    # 添加搜索模型
-                                  "topP": 0.95, "topK": 64, "maxTemperature": 2})
+    if settings.MODEL_SEARCH:
+        for name in settings.MODEL_SEARCH:
+            model = model_mapping.get(name, None)
+            if not model:
+                continue
+
+            item = deepcopy(model)
+            item["name"] = f"models/{name}-search"
+            display_name = f'{item.get("displayName")} For Search'
+            item["displayName"] = display_name
+            item["description"] = display_name
+
+            models_json["models"].append(item)
+
+    # 添加图像生成模型
+    if settings.MODEL_IMAGE:
+        for name in settings.MODEL_IMAGE:
+            model = model_mapping.get(name, None)
+            if not model:
+                continue
+
+            item = deepcopy(model)
+            item["name"] = f"models/{name}-image"
+            display_name = f'{item.get("displayName")} For Image'
+            item["displayName"] = display_name
+            item["description"] = display_name
+
+            models_json["models"].append(item)
+            
     return models_json
 
 
@@ -62,6 +90,9 @@ async def generate_content(
     logger.info(f"Request: \n{request.model_dump_json(indent=2)}")
     logger.info(f"Using API key: {api_key}")
 
+    if not model_service.check_model_support(model_name):
+        raise HTTPException(status_code=400, detail=f"Model {model_name} is not supported")
+
     try:
         response = await chat_service.generate_content(
             model=model_name,
@@ -92,6 +123,9 @@ async def stream_generate_content(
     logger.info(f"Request: \n{request.model_dump_json(indent=2)}")
     logger.info(f"Using API key: {api_key}")
 
+    if not model_service.check_model_support(model_name):
+        raise HTTPException(status_code=400, detail=f"Model {model_name} is not supported")
+
     try:
         response_stream = chat_service.stream_generate_content(
             model=model_name,

app/api/openai_routes.py

@@ -17,7 +17,7 @@ logger = get_openai_logger()
 
 # 初始化服务
 security_service = SecurityService(settings.ALLOWED_TOKENS, settings.AUTH_TOKEN)
-model_service = ModelService(settings.MODEL_SEARCH)
+model_service = ModelService(settings.MODEL_SEARCH,settings.MODEL_IMAGE)
 embedding_service = EmbeddingService(settings.BASE_URL)
 image_create_service = ImageCreateService()
 
@@ -61,6 +61,10 @@ async def chat_completion(
     logger.info(f"Handling chat completion request for model: {request.model}")
     logger.info(f"Request: \n{request.model_dump_json(indent=2)}")
     logger.info(f"Using API key: {api_key}")
+
+    if not model_service.check_model_support(request.model):
+        raise HTTPException(status_code=400, detail=f"Model {request.model} is not supported")
+       
     try:
         # 如果model是imagen3,使用paid_key
         if request.model == f"{settings.CREATE_IMAGE_MODEL}-chat":

app/core/config.py

@@ -7,6 +7,7 @@ class Settings(BaseSettings):
     ALLOWED_TOKENS: List[str]
     BASE_URL: str = "https://generativelanguage.googleapis.com/v1beta"
     MODEL_SEARCH: List[str] = ["gemini-2.0-flash-exp"]
+    MODEL_IMAGE: List[str] = ["gemini-2.0-flash-exp"]
     TOOLS_CODE_EXECUTION_ENABLED: bool = False
     SHOW_SEARCH_LINK: bool = True
     SHOW_THINKING_PROCESS: bool = True
@@ -16,7 +17,15 @@ class Settings(BaseSettings):
     CREATE_IMAGE_MODEL: str = "imagen-3.0-generate-002"
     UPLOAD_PROVIDER: str = "smms"
     SMMS_SECRET_TOKEN: str = ""
+    PICGO_API_KEY: str = ""
     TEST_MODEL: str = "gemini-1.5-flash"
+    
+    # 流式输出优化器配置
+    STREAM_MIN_DELAY: float = 0.016
+    STREAM_MAX_DELAY: float = 0.024
+    STREAM_SHORT_TEXT_THRESHOLD: int = 10
+    STREAM_LONG_TEXT_THRESHOLD: int = 50
+    STREAM_CHUNK_SIZE: int = 5
 
     def __init__(self):
         super().__init__()

app/core/uploader.py

@@ -149,6 +149,116 @@ class QiniuUploader(ImageUploader):
         pass
     
     
+class PicGoUploader(ImageUploader):
+    """Chevereto API 图片上传器"""
+    
+    def __init__(self, api_key: str, api_url: str = "https://www.picgo.net/api/1/upload"):
+        """
+        初始化 Chevereto 上传器
+        
+        Args:
+            api_key: Chevereto API 密钥
+            api_url: Chevereto API 上传地址
+        """
+        self.api_key = api_key
+        self.api_url = api_url
+        
+    def upload(self, file: bytes, filename: str) -> UploadResponse:
+        """
+        上传图片到 Chevereto 服务
+        
+        Args:
+            file: 图片文件二进制数据
+            filename: 文件名
+            
+        Returns:
+            UploadResponse: 上传响应对象
+            
+        Raises:
+            UploadError: 上传失败时抛出异常
+        """
+        try:
+            # 准备请求头
+            headers = {
+                "X-API-Key": self.api_key
+            }
+            
+            # 准备文件数据
+            files = {
+                "source": (filename, file)
+            }
+            
+            # 发送请求
+            response = requests.post(
+                self.api_url,
+                headers=headers,
+                files=files
+            )
+            
+            # 检查响应状态
+            response.raise_for_status()
+            
+            # 解析响应
+            result = response.json()
+            
+            # 验证上传是否成功
+            if result.get("status_code") != 200:
+                error_message = "Upload failed"
+                if "error" in result:
+                    error_message = result["error"].get("message", error_message)
+                raise UploadError(
+                    message=error_message,
+                    error_type=UploadErrorType.SERVER_ERROR,
+                    status_code=result.get("status_code"),
+                    details=result.get("error")
+                )
+                
+            # 从响应中提取图片信息
+            image_data = result.get("image", {})
+            
+            # 构建图片元数据
+            image_metadata = ImageMetadata(
+                width=image_data.get("width", 0),
+                height=image_data.get("height", 0),
+                filename=image_data.get("filename", filename),
+                size=image_data.get("size", 0),
+                url=image_data.get("url", ""),
+                delete_url=image_data.get("delete_url", None)
+            )
+            
+            return UploadResponse(
+                success=True,
+                code="success",
+                message=result.get("success", {}).get("message", "Upload success"),
+                data=image_metadata
+            )
+            
+        except requests.RequestException as e:
+            # 处理网络请求相关错误
+            raise UploadError(
+                message=f"Upload request failed: {str(e)}",
+                error_type=UploadErrorType.NETWORK_ERROR,
+                original_error=e
+            )
+        except (KeyError, ValueError, TypeError) as e:
+            # 处理响应解析错误
+            raise UploadError(
+                message=f"Invalid response format: {str(e)}",
+                error_type=UploadErrorType.PARSE_ERROR,
+                original_error=e
+            )
+        except UploadError:
+            # 重新抛出已经是 UploadError 类型的异常
+            raise
+        except Exception as e:
+            # 处理其他未预期的错误
+            raise UploadError(
+                message=f"Upload failed: {str(e)}",
+                error_type=UploadErrorType.UNKNOWN,
+                original_error=e
+            )
+
+    
 class ImageUploaderFactory:
     @staticmethod
     def create(provider: str, **credentials) -> ImageUploader:
@@ -159,5 +269,7 @@ class ImageUploaderFactory:
                 credentials["access_key"], 
                 credentials["secret_key"]
             )
+        elif provider == "picgo":
+            api_url = credentials.get("api_url", "https://www.picgo.net/api/1/upload")
+            return PicGoUploader(credentials["api_key"], api_url)
         raise ValueError(f"Unknown provider: {provider}")
-    

app/schemas/gemini_models.py

@@ -33,8 +33,8 @@ class GeminiContent(BaseModel):
 
 
 class GeminiRequest(BaseModel):
-    contents: List[GeminiContent]
+    contents: List[GeminiContent] = []
     tools: Optional[List[Dict[str, Any]]] = []
     safetySettings: Optional[List[SafetySetting]] = None
-    generationConfig: Optional[GenerationConfig] = None
+    generationConfig: Optional[GenerationConfig] = {}
     systemInstruction: Optional[SystemInstruction] = None

app/services/chat/api_client.py

@@ -24,10 +24,18 @@ class GeminiApiClient(ApiClient):
         self.base_url = base_url
         self.timeout = timeout
 
-    async def generate_content(self, payload: Dict[str, Any], model: str, api_key: str) -> Dict[str, Any]:
+    def _get_real_model(self, model: str) -> str:
-        timeout = httpx.Timeout(self.timeout, read=self.timeout)
         if model.endswith("-search"):
             model = model[:-7]
+        if model.endswith("-image"):
+            model = model[:-6]
+
+        return model
+
+    async def generate_content(self, payload: Dict[str, Any], model: str, api_key: str) -> Dict[str, Any]:
+        timeout = httpx.Timeout(self.timeout, read=self.timeout)
+        model = self._get_real_model(model)
+
         async with httpx.AsyncClient(timeout=timeout) as client:
             url = f"{self.base_url}/models/{model}:generateContent?key={api_key}"
             response = await client.post(url, json=payload)
@@ -38,8 +46,8 @@ class GeminiApiClient(ApiClient):
 
     async def stream_generate_content(self, payload: Dict[str, Any], model: str, api_key: str) -> AsyncGenerator[str, None]:
         timeout = httpx.Timeout(self.timeout, read=self.timeout)
-        if model.endswith("-search"):
+        model = self._get_real_model(model)
-            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(method="POST", url=url, json=payload) as response:

app/services/chat/message_converter.py

@@ -34,7 +34,7 @@ class OpenAIMessageConverter(MessageConverter):
 
     def convert(self, messages: List[Dict[str, Any]]) -> tuple[List[Dict[str, Any]], Optional[Dict[str, Any]]]:
         converted_messages = []
-        system_instruction = None
+        system_instruction_parts = []
 
         for idx, msg in enumerate(messages):
             role = msg.get("role", "")
@@ -64,8 +64,16 @@ class OpenAIMessageConverter(MessageConverter):
 
             if parts:
                 if role == "system":
-                    system_instruction = {"role": "system", "parts": parts}
+                    system_instruction_parts.extend(parts)
                 else:
                     converted_messages.append({"role": role, "parts": parts})
 
+        system_instruction = (
+            None
+            if not system_instruction_parts
+            else {
+                "role": "system",
+                "parts": system_instruction_parts,
+            }
+        )
         return converted_messages, system_instruction

app/services/chat/response_handler.py

@@ -1,5 +1,6 @@
 # app/services/chat/response_handler.py
 
+import base64
 import json
 import random
 import string
@@ -8,6 +9,7 @@ from typing import Dict, Any, List, Optional
 import time
 import uuid
 from app.core.config import settings
+from app.core.uploader import ImageUploaderFactory
 
 
 class ResponseHandler(ABC):
@@ -135,67 +137,8 @@ def _extract_result(response: Dict[str, Any], model: str, stream: bool = False,
             candidate = response["candidates"][0]
             content = candidate.get("content", {})
             parts = content.get("parts", [])
-            # if "thinking" in model:
+            if not parts:
-            #     if settings.SHOW_THINKING_PROCESS:
+                return "", []
-            #         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]:
@@ -210,6 +153,8 @@ def _extract_result(response: Dict[str, Any], model: str, stream: bool = False,
                 text = _format_execution_result(
                     parts[0]["codeExecutionResult"]
                 )
+            elif "inlineData" in parts[0]:
+                text = _extract_image_data(parts[0])
             else:
                 text = ""
             text = _add_search_link_text(model, candidate, text)
@@ -235,14 +180,38 @@ def _extract_result(response: Dict[str, Any], model: str, stream: bool = False,
                         text = candidate["content"]["parts"][0]["text"]
             else:
                 text = ""
-                for part in candidate["content"]["parts"]:
+                if "parts" in candidate["content"]:
-                    text += part.get("text", "")
+                    for part in candidate["content"]["parts"]:
+                        if "text" in part:
+                            text += part["text"]
+                        elif "inlineData" in part:
+                            text += _extract_image_data(part)
+
+
             text = _add_search_link_text(model, candidate, text)
             tool_calls = _extract_tool_calls(candidate["content"]["parts"], gemini_format)
         else:
             text = "暂无返回"
     return text, tool_calls
 
+def _extract_image_data(part: dict) -> str:
+    image_uploader = None
+    if settings.UPLOAD_PROVIDER == "smms":
+        image_uploader = ImageUploaderFactory.create(provider=settings.UPLOAD_PROVIDER,api_key=settings.SMMS_SECRET_TOKEN)
+    elif settings.UPLOAD_PROVIDER == "picgo":
+        image_uploader = ImageUploaderFactory.create(provider=settings.UPLOAD_PROVIDER,api_key=settings.PICGO_API_KEY)
+    current_date = time.strftime("%Y/%m/%d")
+    filename = f"{current_date}/{uuid.uuid4().hex[:8]}.png"
+    base64_data = part["inlineData"]["data"]
+                #将base64_data转成bytes数组
+    bytes_data = base64.b64decode(base64_data)
+    upload_response = image_uploader.upload(bytes_data,filename)
+    if upload_response.success:
+        text = f"\n![image]({upload_response.data.url})\n"
+    else:
+        text = ""
+    return text
+    
 def _extract_tool_calls(parts: List[Dict[str, Any]], gemini_format: bool) -> List[Dict[str, Any]]:
     """提取工具调用信息"""
     if not parts or not isinstance(parts, list):

app/services/chat/stream_optimizer.py

@@ -4,6 +4,7 @@ import asyncio
 import math
 from typing import Any, List, AsyncGenerator, Callable
 from app.core.logger import get_openai_logger, get_gemini_logger
+from app.core.config import settings
 
 logger_openai = get_openai_logger()
 logger_gemini = get_gemini_logger()
@@ -20,8 +21,8 @@ class StreamOptimizer:
                  min_delay: float = 0.016, 
                  max_delay: float = 0.024,
                  short_text_threshold: int = 10,
-                 long_text_threshold: int = 100,
+                 long_text_threshold: int = 50,
-                 chunk_size: int = 10):
+                 chunk_size: int = 5):
         """初始化流式输出优化器
         
         参数:
@@ -112,5 +113,20 @@ class StreamOptimizer:
 
 
 # 创建默认的优化器实例，可以直接导入使用
-openai_optimizer = StreamOptimizer(logger=logger_openai)
+openai_optimizer = StreamOptimizer(
-gemini_optimizer = StreamOptimizer(logger=logger_gemini)
+    logger=logger_openai,
+    min_delay=settings.STREAM_MIN_DELAY,
+    max_delay=settings.STREAM_MAX_DELAY,
+    short_text_threshold=settings.STREAM_SHORT_TEXT_THRESHOLD,
+    long_text_threshold=settings.STREAM_LONG_TEXT_THRESHOLD,
+    chunk_size=settings.STREAM_CHUNK_SIZE
+)
+
+gemini_optimizer = StreamOptimizer(
+    logger=logger_gemini,
+    min_delay=settings.STREAM_MIN_DELAY,
+    max_delay=settings.STREAM_MAX_DELAY,
+    short_text_threshold=settings.STREAM_SHORT_TEXT_THRESHOLD,
+    long_text_threshold=settings.STREAM_LONG_TEXT_THRESHOLD,
+    chunk_size=settings.STREAM_CHUNK_SIZE
+)

app/services/gemini_chat_service.py

@@ -62,14 +62,19 @@ def _get_safety_settings(model: str) -> List[Dict[str, str]]:
 
 def _build_payload(model: str, request: GeminiRequest) -> Dict[str, Any]:
     """构建请求payload"""
-    payload = request.model_dump()
+    request_dict = request.model_dump()
-    return {
+    payload = {
-        "contents": payload.get("contents", []),
+        "contents": request_dict.get("contents", []),
-        "tools": _build_tools(model, payload),
+        "tools": _build_tools(model, request_dict),
         "safetySettings": _get_safety_settings(model),
-        "generationConfig": payload.get("generationConfig", {}),
+        "generationConfig": request_dict.get("generationConfig", {}),
-        "systemInstruction": payload.get("systemInstruction", [])
+        "systemInstruction": request_dict.get("systemInstruction", "")
     }
+    
+    if model.endswith("-image"):
+        payload.pop("systemInstruction")
+        payload["generationConfig"]["responseModalities"] = ["Text","Image"]
+    return payload
 
 
 class GeminiChatService:

app/services/model_service.py

@@ -7,8 +7,9 @@ from app.core.config import settings
 logger = get_model_logger()
 
 class ModelService:
-    def __init__(self, model_search: list):
+    def __init__(self, model_search: list, model_image: list):
         self.model_search = model_search
+        self.model_image = model_image
         self.base_url = "https://generativelanguage.googleapis.com/v1beta"
 
     def get_gemini_models(self, api_key: str) -> Optional[Dict[str, Any]]:
@@ -57,9 +58,27 @@ class ModelService:
                 search_model = openai_model.copy()
                 search_model["id"] = f"{model_id}-search"
                 openai_format["data"].append(search_model)
+            if model_id in self.model_image:
+                image_model = openai_model.copy()
+                image_model["id"] = f"{model_id}-image"
+                openai_format["data"].append(image_model)
 
         if settings.CREATE_IMAGE_MODEL:
             image_model = openai_model.copy()
             image_model["id"] = f"{settings.CREATE_IMAGE_MODEL}-chat"
             openai_format["data"].append(image_model)
         return openai_format
+
+    def check_model_support(self, model: str) -> bool:
+        if not model or not isinstance(model, str):
+            return False
+
+        model = model.strip()
+        if model.endswith("-search"):
+            model = model[:-7]
+            return model in settings.MODEL_SEARCH
+        if model.endswith("-image"):
+            model = model[:-6]
+            return model in settings.MODEL_IMAGE
+
+        return True

app/services/openai_chat_service.py

@@ -35,7 +35,7 @@ def _build_tools(
 
     if (
             settings.TOOLS_CODE_EXECUTION_ENABLED
-            and not (model.endswith("-search") or "-thinking" in model)
+            and not (model.endswith("-search") or "-thinking" in model or model.endswith("-image"))
             and not _has_image_parts(messages)
     ):
         tools.append({"code_execution": {}})
@@ -110,12 +110,15 @@ def _build_payload(
         "tools": _build_tools(request, messages),
         "safetySettings": _get_safety_settings(request.model),
     }
-
+    if request.model.endswith("-image"):
+        payload["generationConfig"]["responseModalities"] = ["Text","Image"]
+        
     if (
         instruction
         and isinstance(instruction, dict)
         and instruction.get("role") == "system"
         and instruction.get("parts")
+        and not request.model.endswith("-image")
     ):
         payload["systemInstruction"] = instruction