diff --git a/src/llm_models/model_client/aiohttp_gemini_client.py b/src/llm_models/model_client/aiohttp_gemini_client.py
new file mode 100644
index 000000000..95b5bb899
--- /dev/null
+++ b/src/llm_models/model_client/aiohttp_gemini_client.py
@@ -0,0 +1,555 @@
+import asyncio
+import json
+import io
+import base64
+from typing import Callable, Any, Coroutine, Optional, List, AsyncIterator
+import aiohttp
+from json_repair import repair_json
+
+from src.config.api_ada_configs import ModelInfo, APIProvider
+from src.common.logger import get_logger
+from .base_client import APIResponse, UsageRecord, BaseClient, client_registry
+from ..exceptions import (
+    RespParseException,
+    NetworkConnectionError,
+    RespNotOkException,
+    ReqAbortException,
+)
+from ..payload_content.message import Message, RoleType
+from ..payload_content.resp_format import RespFormat, RespFormatType
+from ..payload_content.tool_option import ToolOption, ToolParam, ToolCall
+
+logger = get_logger("AioHTTP-Gemini客户端")
+
+
+def _convert_messages(messages: list[Message]) -> tuple[list[dict], list[str] | None]:
+    """
+    转换消息格式 - 将消息转换为Gemini REST API所需的格式
+    :param messages: 消息列表
+    :return: (contents, system_instructions)
+    """
+    
+    def _convert_message_item(message: Message) -> dict:
+        """转换单个消息格式"""
+        # 转换角色名称
+        if message.role == RoleType.Assistant:
+            role = "model"
+        elif message.role == RoleType.User:
+            role = "user"
+        else:
+            raise ValueError(f"不支持的消息角色: {message.role}")
+        
+        # 转换内容
+        parts = []
+        if isinstance(message.content, str):
+            parts.append({"text": message.content})
+        elif isinstance(message.content, list):
+            for item in message.content:
+                if isinstance(item, tuple):  # (format, base64_data)
+                    parts.append({
+                        "inline_data": {
+                            "mime_type": f"image/{item[0].lower()}",
+                            "data": item[1]
+                        }
+                    })
+                elif isinstance(item, str):
+                    parts.append({"text": item})
+        else:
+            raise RuntimeError("无法触及的代码：请使用MessageBuilder类构建消息对象")
+        
+        return {
+            "role": role,
+            "parts": parts
+        }
+    
+    contents = []
+    system_instructions = []
+    
+    for message in messages:
+        if message.role == RoleType.System:
+            if isinstance(message.content, str):
+                system_instructions.append(message.content)
+            else:
+                raise ValueError("System消息不支持非文本内容")
+        elif message.role == RoleType.Tool:
+            # 工具调用结果处理
+            if not message.tool_call_id:
+                raise ValueError("工具调用消息缺少tool_call_id")
+            contents.append({
+                "role": "function",
+                "parts": [{"text": str(message.content)}]
+            })
+        else:
+            contents.append(_convert_message_item(message))
+    
+    return contents, system_instructions if system_instructions else None
+
+
+def _convert_tool_options(tool_options: list[ToolOption]) -> list[dict]:
+    """
+    转换工具选项格式 - 将工具选项转换为Gemini REST API所需的格式
+    """
+    
+    def _convert_tool_param(param: ToolParam) -> dict:
+        """转换工具参数"""
+        result = {
+            "type": param.param_type.value,
+            "description": param.description,
+        }
+        if param.enum_values:
+            result["enum"] = param.enum_values
+        return result
+    
+    def _convert_tool_option_item(tool_option: ToolOption) -> dict:
+        """转换单个工具选项"""
+        function_declaration = {
+            "name": tool_option.name,
+            "description": tool_option.description,
+        }
+        
+        if tool_option.params:
+            function_declaration["parameters"] = {
+                "type": "object",
+                "properties": {
+                    param.name: _convert_tool_param(param) 
+                    for param in tool_option.params
+                },
+                "required": [
+                    param.name 
+                    for param in tool_option.params 
+                    if param.required
+                ],
+            }
+        
+        return {
+            "function_declarations": [function_declaration]
+        }
+    
+    return [_convert_tool_option_item(tool_option) for tool_option in tool_options]
+
+
+def _build_generation_config(
+    max_tokens: int,
+    temperature: float,
+    response_format: RespFormat | None = None,
+    extra_params: dict | None = None
+) -> dict:
+    """构建生成配置"""
+    config = {
+        "maxOutputTokens": max_tokens,
+        "temperature": temperature,
+    }
+    
+    # 处理响应格式
+    if response_format:
+        if response_format.format_type == RespFormatType.JSON_OBJ:
+            config["responseMimeType"] = "application/json"
+        elif response_format.format_type == RespFormatType.JSON_SCHEMA:
+            config["responseMimeType"] = "application/json"
+            config["responseSchema"] = response_format.to_dict()
+    
+    # 合并额外参数
+    if extra_params:
+        config.update(extra_params)
+    
+    return config
+
+
+class AiohttpGeminiStreamParser:
+    """流式响应解析器"""
+    
+    def __init__(self):
+        self.content_buffer = io.StringIO()
+        self.reasoning_buffer = io.StringIO()
+        self.tool_calls_buffer = []
+        self.usage_record = None
+    
+    def parse_chunk(self, chunk_text: str):
+        """解析单个流式数据块"""
+        try:
+            if not chunk_text.strip():
+                return
+            
+            # 移除data:前缀
+            if chunk_text.startswith("data: "):
+                chunk_text = chunk_text[6:].strip()
+            
+            if chunk_text == "[DONE]":
+                return
+            
+            chunk_data = json.loads(chunk_text)
+            
+            # 解析候选项
+            if "candidates" in chunk_data and chunk_data["candidates"]:
+                candidate = chunk_data["candidates"][0]
+                
+                # 解析内容
+                if "content" in candidate and "parts" in candidate["content"]:
+                    for part in candidate["content"]["parts"]:
+                        if "text" in part:
+                            self.content_buffer.write(part["text"])
+                
+                # 解析工具调用
+                if "functionCall" in candidate:
+                    func_call = candidate["functionCall"]
+                    call_id = f"gemini_call_{len(self.tool_calls_buffer)}"
+                    self.tool_calls_buffer.append({
+                        "id": call_id,
+                        "name": func_call.get("name", ""),
+                        "args": func_call.get("args", {})
+                    })
+            
+            # 解析使用统计
+            if "usageMetadata" in chunk_data:
+                usage = chunk_data["usageMetadata"]
+                self.usage_record = (
+                    usage.get("promptTokenCount", 0),
+                    usage.get("candidatesTokenCount", 0),
+                    usage.get("totalTokenCount", 0)
+                )
+        
+        except json.JSONDecodeError as e:
+            logger.warning(f"解析流式数据块失败: {e}, 数据: {chunk_text}")
+        except Exception as e:
+            logger.error(f"处理流式数据块时出错: {e}")
+    
+    def get_response(self) -> APIResponse:
+        """获取最终响应"""
+        response = APIResponse()
+        
+        if self.content_buffer.tell() > 0:
+            response.content = self.content_buffer.getvalue()
+        
+        if self.reasoning_buffer.tell() > 0:
+            response.reasoning_content = self.reasoning_buffer.getvalue()
+        
+        if self.tool_calls_buffer:
+            response.tool_calls = []
+            for call_data in self.tool_calls_buffer:
+                response.tool_calls.append(ToolCall(
+                    call_data["id"],
+                    call_data["name"],
+                    call_data["args"]
+                ))
+        
+        # 清理缓冲区
+        self.content_buffer.close()
+        self.reasoning_buffer.close()
+        
+        return response
+
+
+async def _default_stream_response_handler(
+    response: aiohttp.ClientResponse,
+    interrupt_flag: asyncio.Event | None,
+) -> tuple[APIResponse, Optional[tuple[int, int, int]]]:
+    """默认流式响应处理器"""
+    parser = AiohttpGeminiStreamParser()
+    
+    try:
+        async for line in response.content:
+            if interrupt_flag and interrupt_flag.is_set():
+                raise ReqAbortException("请求被外部信号中断")
+            
+            line_text = line.decode('utf-8').strip()
+            if line_text:
+                parser.parse_chunk(line_text)
+        
+        api_response = parser.get_response()
+        return api_response, parser.usage_record
+        
+    except Exception as e:
+        if not isinstance(e, ReqAbortException):
+            raise RespParseException(None, f"流式响应解析失败: {e}") from e
+        raise
+
+
+def _default_normal_response_parser(
+    response_data: dict,
+) -> tuple[APIResponse, Optional[tuple[int, int, int]]]:
+    """默认普通响应解析器"""
+    api_response = APIResponse()
+    
+    try:
+        # 解析候选项
+        if "candidates" in response_data and response_data["candidates"]:
+            candidate = response_data["candidates"][0]
+            
+            # 解析文本内容
+            if "content" in candidate and "parts" in candidate["content"]:
+                content_parts = []
+                for part in candidate["content"]["parts"]:
+                    if "text" in part:
+                        content_parts.append(part["text"])
+                
+                if content_parts:
+                    api_response.content = "".join(content_parts)
+            
+            # 解析工具调用
+            if "functionCall" in candidate:
+                func_call = candidate["functionCall"]
+                api_response.tool_calls = [ToolCall(
+                    f"gemini_call_0",
+                    func_call.get("name", ""),
+                    func_call.get("args", {})
+                )]
+        
+        # 解析使用统计
+        usage_record = None
+        if "usageMetadata" in response_data:
+            usage = response_data["usageMetadata"]
+            usage_record = (
+                usage.get("promptTokenCount", 0),
+                usage.get("candidatesTokenCount", 0),
+                usage.get("totalTokenCount", 0)
+            )
+        
+        api_response.raw_data = response_data
+        return api_response, usage_record
+        
+    except Exception as e:
+        raise RespParseException(response_data, f"响应解析失败: {e}") from e
+
+
+@client_registry.register_client_class("aiohttp_gemini")
+class AiohttpGeminiClient(BaseClient):
+    """使用aiohttp的Gemini客户端"""
+    
+    def __init__(self, api_provider: APIProvider):
+        super().__init__(api_provider)
+        self.base_url = "https://generativelanguage.googleapis.com/v1beta"
+        self.session: aiohttp.ClientSession | None = None
+        self.api_key = api_provider.api_key
+        
+        # 如果提供了自定义base_url，使用它
+        if api_provider.base_url:
+            self.base_url = api_provider.base_url.rstrip('/')
+    
+    async def _get_session(self) -> aiohttp.ClientSession:
+        """获取或创建aiohttp会话"""
+        if self.session is None or self.session.closed:
+            timeout = aiohttp.ClientTimeout(total=300)  # 5分钟超时
+            self.session = aiohttp.ClientSession(
+                timeout=timeout,
+                headers={
+                    "Content-Type": "application/json",
+                    "User-Agent": "MMC-AioHTTP-Gemini-Client/1.0"
+                }
+            )
+        return self.session
+    
+    async def _make_request(
+        self,
+        method: str,
+        endpoint: str,
+        data: dict | None = None,
+        stream: bool = False
+    ) -> aiohttp.ClientResponse:
+        """发起HTTP请求"""
+        session = await self._get_session()
+        url = f"{self.base_url}/{endpoint}?key={self.api_key}"
+        
+        try:
+            if method.upper() == "POST":
+                response = await session.post(
+                    url,
+                    json=data,
+                    headers={"Accept": "text/event-stream" if stream else "application/json"}
+                )
+            else:
+                response = await session.get(url)
+            
+            # 检查HTTP状态码
+            if response.status >= 400:
+                error_text = await response.text()
+                raise RespNotOkException(response.status, error_text)
+            
+            return response
+            
+        except aiohttp.ClientError as e:
+            raise NetworkConnectionError() from e
+    
+    async def get_response(
+        self,
+        model_info: ModelInfo,
+        message_list: list[Message],
+        tool_options: list[ToolOption] | None = None,
+        max_tokens: int = 1024,
+        temperature: float = 0.7,
+        response_format: RespFormat | None = None,
+        stream_response_handler: Optional[
+            Callable[
+                [aiohttp.ClientResponse, asyncio.Event | None],
+                Coroutine[Any, Any, tuple[APIResponse, Optional[tuple[int, int, int]]]],
+            ]
+        ] = None,
+        async_response_parser: Optional[
+            Callable[[dict], tuple[APIResponse, Optional[tuple[int, int, int]]]]
+        ] = None,
+        interrupt_flag: asyncio.Event | None = None,
+        extra_params: dict[str, Any] | None = None,
+    ) -> APIResponse:
+        """
+        获取对话响应
+        """
+        if stream_response_handler is None:
+            stream_response_handler = _default_stream_response_handler
+        
+        if async_response_parser is None:
+            async_response_parser = _default_normal_response_parser
+        
+        # 转换消息格式
+        contents, system_instructions = _convert_messages(message_list)
+        
+        # 构建请求体
+        request_data = {
+            "contents": contents,
+            "generationConfig": _build_generation_config(
+                max_tokens, temperature, response_format, extra_params
+            )
+        }
+        
+        # 添加系统指令
+        if system_instructions:
+            request_data["systemInstruction"] = {
+                "parts": [{"text": instr} for instr in system_instructions]
+            }
+        
+        # 添加工具定义
+        if tool_options:
+            request_data["tools"] = _convert_tool_options(tool_options)
+        
+        try:
+            if model_info.force_stream_mode:
+                # 流式请求
+                endpoint = f"models/{model_info.model_identifier}:streamGenerateContent"
+                req_task = asyncio.create_task(
+                    self._make_request("POST", endpoint, request_data, stream=True)
+                )
+                
+                while not req_task.done():
+                    if interrupt_flag and interrupt_flag.is_set():
+                        req_task.cancel()
+                        raise ReqAbortException("请求被外部信号中断")
+                    await asyncio.sleep(0.1)
+                
+                response = req_task.result()
+                api_response, usage_record = await stream_response_handler(response, interrupt_flag)
+                
+            else:
+                # 普通请求
+                endpoint = f"models/{model_info.model_identifier}:generateContent"
+                req_task = asyncio.create_task(
+                    self._make_request("POST", endpoint, request_data)
+                )
+                
+                while not req_task.done():
+                    if interrupt_flag and interrupt_flag.is_set():
+                        req_task.cancel()
+                        raise ReqAbortException("请求被外部信号中断")
+                    await asyncio.sleep(0.1)
+                
+                response = req_task.result()
+                response_data = await response.json()
+                api_response, usage_record = async_response_parser(response_data)
+        
+        except (ReqAbortException, NetworkConnectionError, RespNotOkException, RespParseException):
+            # 直接重抛项目定义的异常
+            raise
+        except Exception as e:
+            # 其他异常转换为网络连接错误
+            raise NetworkConnectionError() from e
+        
+        # 设置使用统计
+        if usage_record:
+            api_response.usage = UsageRecord(
+                model_name=model_info.name,
+                provider_name=model_info.api_provider,
+                prompt_tokens=usage_record[0],
+                completion_tokens=usage_record[1],
+                total_tokens=usage_record[2],
+            )
+        
+        return api_response
+    
+    async def get_embedding(
+        self,
+        model_info: ModelInfo,
+        embedding_input: str,
+        extra_params: dict[str, Any] | None = None,
+    ) -> APIResponse:
+        """
+        获取文本嵌入 - 此客户端不支持嵌入功能
+        """
+        raise NotImplementedError("AioHTTP Gemini客户端不支持文本嵌入功能")
+    
+    async def get_audio_transcriptions(
+        self,
+        model_info: ModelInfo,
+        audio_base64: str,
+        extra_params: dict[str, Any] | None = None,
+    ) -> APIResponse:
+        """
+        获取音频转录
+        """
+        # 构建包含音频的内容
+        contents = [{
+            "role": "user",
+            "parts": [
+                {"text": "Generate a transcript of the speech. The language of the transcript should match the language of the speech."},
+                {
+                    "inline_data": {
+                        "mime_type": "audio/wav",
+                        "data": audio_base64
+                    }
+                }
+            ]
+        }]
+        
+        request_data = {
+            "contents": contents,
+            "generationConfig": _build_generation_config(2048, 0.1, None, extra_params)
+        }
+        
+        try:
+            endpoint = f"models/{model_info.model_identifier}:generateContent"
+            response = await self._make_request("POST", endpoint, request_data)
+            response_data = await response.json()
+            
+            api_response, usage_record = _default_normal_response_parser(response_data)
+            
+            if usage_record:
+                api_response.usage = UsageRecord(
+                    model_name=model_info.name,
+                    provider_name=model_info.api_provider,
+                    prompt_tokens=usage_record[0],
+                    completion_tokens=usage_record[1],
+                    total_tokens=usage_record[2],
+                )
+            
+            return api_response
+            
+        except (NetworkConnectionError, RespNotOkException, RespParseException):
+            raise
+        except Exception as e:
+            raise NetworkConnectionError() from e
+    
+    def get_support_image_formats(self) -> list[str]:
+        """
+        获取支持的图片格式
+        """
+        return ["png", "jpg", "jpeg", "webp", "heic", "heif"]
+    
+    async def __aenter__(self):
+        """异步上下文管理器入口"""
+        return self
+    
+    async def __aexit__(self, exc_type, exc_val, exc_tb):
+        """异步上下文管理器出口"""
+        if self.session and not self.session.closed:
+            await self.session.close()
+    
+    def __del__(self):
+        """析构函数，确保会话被正确关闭"""
+        if hasattr(self, 'session') and self.session and not self.session.closed:
+            asyncio.create_task(self.session.close())