diff --git a/README.MD b/README.MD
index dfbee86..2f524da 100644
--- a/README.MD
+++ b/README.MD
@@ -64,7 +64,6 @@ Bubbles 是一个功能丰富的微信机器人框架，基于 [wcferry](https:/
 - 支持为不同的群聊和私聊设置不同的 AI 模型和 system prompt
   - OpenAI (ChatGPT)
   - DeepSeek
-  - Gemini
 
 #### 🛠️ 智能路由系统
 - 基于 AI 的意图识别，无需记住特定命令格式
diff --git a/ai_providers/ai_gemini.py b/ai_providers/ai_gemini.py
deleted file mode 100644
index 56e4850..0000000
--- a/ai_providers/ai_gemini.py
+++ /dev/null
@@ -1,411 +0,0 @@
-# ai_providers/ai_gemini.py
-#! /usr/bin/env python3
-# -*- coding: utf-8 -*-
-
-import logging
-import os
-import time
-import httpx
-import pathlib # 用于处理文件路径
-import mimetypes # 用于猜测图片类型
-import google.generativeai as genai
-from google.generativeai.types import generation_types, safety_types # 显式导入需要的类型
-from google.api_core.exceptions import GoogleAPICallError, ClientError
-
-# 引入 MessageSummary 类型提示
-try:
-    from function.func_summary import MessageSummary
-except ImportError:
-    MessageSummary = object # Fallback
-
-class Gemini:
-    DEFAULT_MODEL = "gemini-1.5-pro-latest"
-    DEFAULT_PROMPT = "You are a helpful assistant."
-    DEFAULT_MAX_HISTORY = 30
-    SAFETY_SETTINGS = { # 默认安全设置 - 可根据需要调整或从配置加载
-        safety_types.HarmCategory.HARM_CATEGORY_HARASSMENT: safety_types.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE,
-        safety_types.HarmCategory.HARM_CATEGORY_HATE_SPEECH: safety_types.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE,
-        safety_types.HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: safety_types.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE,
-        safety_types.HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: safety_types.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE,
-    }
-
-    def __init__(self, conf: dict, message_summary_instance: MessageSummary = None, bot_wxid: str = None) -> None:
-        self.LOG = logging.getLogger("Gemini")
-        self._api_key = conf.get("api_key")
-        self._model_name = conf.get("model_name", self.DEFAULT_MODEL)
-        # 存储原始配置的 prompt，用于初始化和可能的重载
-        self._base_prompt = conf.get("prompt", self.DEFAULT_PROMPT)
-        self._proxy = conf.get("proxy")
-        self.max_history_messages = conf.get("max_history_messages", self.DEFAULT_MAX_HISTORY)
-
-        self.message_summary = message_summary_instance
-        self.bot_wxid = bot_wxid
-        self._model = None
-        self.support_vision = False # 初始化时假设不支持，成功加载模型后再判断
-
-        if not self._api_key:
-            self.LOG.error("Gemini API Key 未在配置中提供！")
-            return # 没有 API Key 无法继续
-
-        if not self.message_summary:
-             self.LOG.warning("MessageSummary 实例未提供给 Gemini，上下文功能将不可用！")
-        if not self.bot_wxid:
-             self.LOG.warning("bot_wxid 未提供给 Gemini，可能无法正确识别机器人自身消息！")
-
-        try:
-            # 1. 配置代理 (如果提供)
-            transport = None
-            if self._proxy:
-                try:
-                    transport = httpx.HTTPTransport(proxy=self._proxy)
-                    self.LOG.info(f"Gemini 使用代理: {self._proxy}")
-                except Exception as proxy_err:
-                    self.LOG.error(f"配置 Gemini 代理失败: {proxy_err}", exc_info=True)
-                    # 代理配置失败，可以选择不使用代理继续或直接失败
-                    # 这里选择继续，不使用代理
-                    transport = None
-
-            # 2. 配置 Google AI Client
-            genai.configure(api_key=self._api_key, transport=transport)
-
-            # 3. 初始化模型
-            # 将基础 prompt 作为 system_instruction 传递
-            self._model = genai.GenerativeModel(
-                self._model_name,
-                system_instruction=self._base_prompt,
-                safety_settings=self.SAFETY_SETTINGS # 应用安全设置
-            )
-            self.LOG.info(f"已加载 Gemini 模型")
-
-            # 4. 检查视觉能力 (依赖模型名称的简单检查)
-            # 注意：更可靠的方式是调用 list_models 并检查支持的方法
-            if "vision" in self._model_name or "pro" in self._model_name or "gemini-1.5" in self._model_name or "flash" in self._model_name:
-                 self.support_vision = True
-                 self.LOG.info(f"模型 {self._model_name} 被认为支持视觉能力。")
-            else:
-                 self.LOG.info(f"模型 {self._model_name} 根据名称判断可能不支持视觉能力。")
-
-        except (GoogleAPICallError, ClientError) as api_error:
-            self.LOG.error(f"初始化 Gemini 时发生 API 错误: {api_error}", exc_info=True)
-            self._model = None
-        except Exception as e:
-            self.LOG.error(f"初始化 Gemini 时发生未知错误: {e}", exc_info=True)
-            self._model = None
-
-    def __repr__(self):
-        return f'Gemini(model={self._model_name}, initialized={self._model is not None})'
-
-    @staticmethod
-    def value_check(conf: dict) -> bool:
-        # 只需要 API Key 是必须的
-        return bool(conf and conf.get("api_key"))
-
-    def _format_history(self, history: list) -> list:
-        """将数据库历史消息转换为 Gemini API 的 contents 格式"""
-        contents = []
-        for msg in history:
-            role = "model" if msg.get("sender_wxid") == self.bot_wxid else "user"
-            content = msg.get('content', '')
-            sender_name = msg.get('sender', '未知用户') # 获取发送者名称
-
-            if content: # 避免添加空内容
-                # Gemini 推荐 user role 包含发言者信息，model role 不需要
-                if role == "user":
-                    formatted_content = f"[{sender_name}]: {content}" # 添加发送者标记
-                    contents.append({'role': role, 'parts': [{'text': formatted_content}]})
-                else: # role == "model"
-                    contents.append({'role': role, 'parts': [{'text': content}]})
-        return contents
-
-    def _generate_response(self, contents: list, generation_config_override: generation_types.GenerationConfig | None = None) -> str:
-        """内部方法，用于调用 Gemini API 并处理响应"""
-        if not self._model:
-            return "Gemini 模型未成功初始化，请检查配置和网络。"
-
-        # 配置生成参数 (可以从 config 中读取更多参数)
-        # 默认使用适中的温度，可以根据需要调整
-        default_config = generation_types.GenerationConfig(temperature=0.7)
-        config_to_use = generation_config_override if generation_config_override else default_config
-
-        self.LOG.debug(f"发送给 Gemini API 的内容条数: {len(contents)}")
-        # self.LOG.debug(f"使用的 GenerationConfig: {config_to_use}")
-        # self.LOG.debug(f"发送内容详情: {contents}") # DEBUG: 打印发送内容
-
-        rsp_text = ""
-        try:
-            # 调用 API
-            response = self._model.generate_content(
-                contents=contents,
-                generation_config=config_to_use,
-                # safety_settings=... # 如果需要覆盖初始化时的安全设置
-                stream=False # 非流式响应
-            )
-
-            # 1. 检查 Prompt 是否被阻止 (在获取 candidates 之前)
-            if response.prompt_feedback and response.prompt_feedback.block_reason:
-                reason = response.prompt_feedback.block_reason.name
-                self.LOG.warning(f"Gemini 提示被阻止，原因: {reason}")
-                return f"抱歉，您的请求因包含不适内容而被阻止 (原因: {reason})。"
-
-            # 2. 检查 Candidates 和 Finish Reason
-            # 尝试从 response 中安全地提取文本
-            try:
-                rsp_text = response.text # .text 是获取聚合文本的便捷方式
-            except ValueError:
-                # 如果 .text 不可用 (例如，因为 finish_reason 不是 STOP 或 MAX_TOKENS)
-                # 检查具体的 finish_reason
-                if response.candidates:
-                    candidate = response.candidates[0]
-                    finish_reason = candidate.finish_reason # 类型是 FinishReason 枚举
-                    finish_reason_name = finish_reason.name
-
-                    if finish_reason == generation_types.FinishReason.SAFETY:
-                        self.LOG.warning(f"Gemini 响应被安全策略阻止。")
-                        # 可以尝试查看 safety_ratings 获取更详细信息
-                        ratings_info = getattr(candidate, 'safety_ratings', [])
-                        self.LOG.debug(f"Safety Ratings: {ratings_info}")
-                        return "抱歉，生成的响应可能包含不安全内容，已被阻止。"
-                    elif finish_reason == generation_types.FinishReason.RECITATION:
-                        self.LOG.warning(f"Gemini 响应因引用保护被阻止。")
-                        return "抱歉，回答可能包含受版权保护的内容，已被部分阻止。"
-                    elif finish_reason == generation_types.FinishReason.OTHER:
-                         self.LOG.warning(f"Gemini 响应因未知原因停止 (FinishReason: OTHER)")
-                         return "抱歉，生成响应时遇到未知问题。"
-                    else:
-                        # 包括 MAX_TOKENS, STOP 等预期情况，但没有文本
-                        self.LOG.warning(f"Gemini 未返回文本内容，但完成原因可接受: {finish_reason_name}")
-                        return f"生成内容时遇到问题 (完成原因: {finish_reason_name})"
-                else:
-                    # 没有 candidates，也没有 prompt block，未知情况
-                    self.LOG.error("Gemini API 调用成功但未返回任何候选内容或提示反馈。")
-                    return "抱歉，Gemini未能生成响应。"
-
-        except (GoogleAPICallError, ClientError) as api_error:
-             self.LOG.error(f"Gemini API 调用错误：{api_error}", exc_info=True)
-             if "API key not valid" in str(api_error):
-                  return "Gemini API 密钥无效或已过期。"
-             elif "quota" in str(api_error).lower():
-                  return "Gemini API 调用已达配额限制。"
-             elif "Model not found" in str(api_error):
-                  return f"配置的 Gemini 模型 '{self._model_name}' 未找到或不可用。"
-             elif "Resource has been exhausted" in str(api_error):
-                 return "Gemini API 资源耗尽，请稍后再试或检查配额。"
-             else:
-                  return f"与 Gemini 通信时出错: {type(api_error).__name__}"
-        except generation_types.StopCandidateException as sce: # 明确捕获这个
-             self.LOG.error(f"Gemini API 响应被停止 (StopCandidateException): {sce}", exc_info=True)
-             # 通常在流式处理中遇到，但也可能在非流式中因某些原因触发
-             return "抱歉，Gemini 生成的响应被意外停止了。"
-        # BlockedPromptException 似乎不直接抛出，而是通过 prompt_feedback 反馈
-        # except generation_types.BlockedPromptException as bpe:
-        #      self.LOG.error(f"Gemini API 提示被阻止：{bpe}", exc_info=True)
-        #      return "抱歉，您的请求内容被 Gemini 阻止了。"
-        except Exception as e:
-             self.LOG.error(f"调用 Gemini 时发生未知错误: {e}", exc_info=True)
-             return f"处理您的请求时发生未知错误: {type(e).__name__}"
-
-        return rsp_text.strip()
-
-    def get_answer(
-        self,
-        question: str,
-        wxid: str,
-        system_prompt_override=None,
-        specific_max_history=None,
-        tools=None,
-        tool_handler=None,
-        tool_choice=None,
-        tool_max_iterations: int = 10
-    ) -> str:
-        if not self._model:
-            return "Gemini 模型未成功初始化，请检查配置和网络。"
-
-        if not question:
-            self.LOG.warning(f"尝试为 wxid={wxid} 获取答案，但问题为空。")
-            return "您没有提问哦。"
-
-        if tools:
-            self.LOG.debug("Gemini 提供的实现暂不支持工具调用，请忽略 tools 参数。")
-
-        # 1. 准备历史消息
-        contents = []
-        if self.message_summary and self.bot_wxid:
-            history = self.message_summary.get_messages(wxid)
-            limit = specific_max_history if specific_max_history is not None else self.max_history_messages
-            self.LOG.debug(f"获取 Gemini 历史 for {wxid}, 原始条数: {len(history)}, 使用限制: {limit}")
-
-            if limit > 0:
-                history = history[-limit:]
-            elif limit == 0:
-                history = [] # 明确清空历史
-
-            self.LOG.debug(f"应用限制后 Gemini 历史条数: {len(history)}")
-            contents.extend(self._format_history(history))
-        else:
-            self.LOG.warning(f"无法为 wxid={wxid} 获取 Gemini 历史记录。")
-
-        # 2. 添加当前用户问题
-        # 注意：格式化时已包含发送者信息
-        contents.append({'role': 'user', 'parts': [{'text': question}]})
-
-        # 3. 处理 System Prompt Override (如果提供)
-        # 注意：Gemini API 目前不直接支持在 generate_content 中覆盖 system_instruction
-        # 如果需要动态改变系统提示，通常需要重新初始化模型或在用户消息前插入一条 'user' role 的指令
-        # 这里我们暂时忽略 system_prompt_override，因为标准 API 调用不支持
-        if system_prompt_override:
-             self.LOG.warning("Gemini API 当前不支持单次请求覆盖系统提示，将使用初始化时的提示。")
-        # 可以考虑在这里将 override 的内容作为一条 user message 添加到 contents 开头
-        # 例如: contents.insert(0, {'role': 'user', 'parts': [{'text': f"[System Instruction Override]: {system_prompt_override}"}]})
-        # 但这会影响对话历史的结构，需要谨慎使用
-
-        # 4. 添加当前时间信息（可选，作为用户消息的一部分）
-        now_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
-        # 可以将时间信息添加到最近的用户消息中，或作为一条新的 user message
-        # 为了简单，暂不自动添加时间信息到内容中，如果需要，可以在 prompt 中说明
-
-        # 5. 调用内部生成方法
-        return self._generate_response(contents)
-
-    def get_image_description(self, image_path: str, prompt: str = "请详细描述这张图片中的内容") -> str:
-         if not self._model:
-             return "Gemini 模型未初始化。"
-         if not self.support_vision:
-             return f"当前 Gemini 模型 '{self._model_name}' 不支持图片理解。"
-
-         image_path_obj = pathlib.Path(image_path)
-         if not image_path_obj.is_file():
-             self.LOG.error(f"图片文件不存在或不是文件: {image_path}")
-             return "无法读取图片文件"
-
-         try:
-             # 猜测 MIME 类型
-             mime_type, _ = mimetypes.guess_type(image_path_obj)
-             if not mime_type or not mime_type.startswith("image/"):
-                 self.LOG.warning(f"无法确定图片 MIME 类型或类型不是 image/*: {image_path}, 猜测为 jpeg")
-                 mime_type = "image/jpeg" # 使用默认值
-
-             self.LOG.info(f"使用 Gemini 分析图片: {image_path} (MIME: {mime_type})")
-
-             # 使用 pathlib 生成 file URI
-             image_uri = image_path_obj.absolute().as_uri()
-
-             image_part = {'mime_type': mime_type, 'data': image_path_obj.read_bytes()}
-
-             # 构建包含文本提示和图片的消息
-             contents = [
-                 # Gemini 处理多模态输入时，推荐 prompt 和 image 都在 user role 的 parts 里
-                 {'role': 'user', 'parts': [
-                     {'text': prompt},
-                     image_part
-                     # 或者使用 from_uri (如果 API 支持且网络可访问该文件 URI):
-                     # genai.types.Part.from_uri(mime_type=mime_type, uri=image_uri)
-                     # 使用原始字节通常更可靠
-                 ]}
-             ]
-
-             # 可以为图片分析设置不同的生成参数，例如更低的温度以获得更客观的描述
-             image_gen_config = generation_types.GenerationConfig(temperature=0.4)
-
-             # 调用内部生成方法
-             return self._generate_response(contents, generation_config_override=image_gen_config)
-
-         except FileNotFoundError:
-             self.LOG.error(f"读取图片文件时发生 FileNotFoundError: {image_path}", exc_info=True)
-             return "读取图片文件时出错。"
-         except Exception as e:
-             self.LOG.error(f"使用 Gemini 分析图片时发生未知错误: {e}", exc_info=True)
-             return f"分析图片时发生未知错误: {type(e).__name__}"
-
-# --- Main 测试部分 ---
-if __name__ == "__main__":
-    print("--- 运行 Gemini 本地测试 ---")
-    # 配置日志记录
-    logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
-
-    # --- 配置加载 ---
-    # !!! 强烈建议从环境变量或安全的配置文件加载 API Key !!!
-    # 例如: api_key = os.environ.get("GEMINI_API_KEY")
-    # 不要将 API Key 硬编码在代码中提交
-    api_key_from_env = os.environ.get("GEMINI_API_KEY")
-    proxy_from_env = os.environ.get("HTTP_PROXY") # 支持 http/https 代理
-
-    if not api_key_from_env:
-         print("\n!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
-         print("!!! 警告：环境变量 GEMINI_API_KEY 未设置。请设置该变量。   !!!")
-         print("!!! 测试将无法连接到 Gemini API。                          !!!")
-         print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n")
-         # 可以选择退出或继续（如果只想测试初始化逻辑）
-         # exit(1)
-         api_key_to_use = "DUMMY_KEY_FOR_INIT_TEST" # 仅用于测试初始化日志，无法实际调用
-    else:
-        api_key_to_use = api_key_from_env
-
-    mock_config = {
-        "api_key": api_key_to_use,
-        "model_name": "gemini-1.5-flash-latest", # 使用较快的模型测试
-        "prompt": "你是一个风趣幽默的AI助手，擅长讲冷笑话。",
-        "proxy": proxy_from_env,
-        "max_history_messages": 3 # 测试时减少历史记录
-    }
-    print(f"测试配置: Model={mock_config['model_name']}, Proxy={'已设置' if mock_config['proxy'] else '未设置'}")
-
-    # --- 初始化 Gemini ---
-    # 在测试中不依赖 MessageSummary
-    print("\n--- 初始化 Gemini 实例 ---")
-    gemini_assistant = Gemini(mock_config, bot_wxid="test_bot_wxid") # 提供一个测试 bot_wxid
-
-    # --- 测试文本生成 ---
-    if gemini_assistant._model: # 检查模型是否成功初始化
-        print("\n--- 测试文本生成 (get_answer) ---")
-        test_question = "你好！今天天气怎么样？给我讲个关于程序员的冷笑话吧。"
-        print(f"提问: {test_question}")
-        start_time = time.time()
-        answer = gemini_assistant.get_answer(test_question, "test_user_wxid") # 提供测试 wxid
-        end_time = time.time()
-        print(f"\nGemini 回答 (耗时: {end_time - start_time:.2f}s):\n{answer}")
-
-        # 测试空问题
-        print("\n--- 测试空问题 ---")
-        empty_answer = gemini_assistant.get_answer("", "test_user_wxid")
-        print(f"空问题回答: {empty_answer}")
-
-        # 测试长对话历史（如果需要，可以手动构建一个 contents 列表来模拟）
-        # print("\n--- 模拟长对话测试 ---")
-        # mock_history = [
-        #     {'role': 'user', 'parts': [{'text': "[UserA]: 第一次提问"}]},
-        #     {'role': 'model', 'parts': [{'text': "第一次回答"}]},
-        #     {'role': 'user', 'parts': [{'text': "[UserB]: 第二次提问"}]},
-        #     {'role': 'model', 'parts': [{'text': "第二次回答"}]},
-        #     {'role': 'user', 'parts': [{'text': "[UserA]: 第三次提问，关于第一次提问的内容"}]},
-        # ]
-        # mock_history.append({'role': 'user', 'parts': [{'text': "当前的第四个问题"}]})
-        # long_hist_answer = gemini_assistant._generate_response(mock_history)
-        # print(f"长历史回答:\n{long_hist_answer}")
-
-    else:
-        print("\n--- Gemini 初始化失败，跳过文本生成测试 ---")
-
-    # --- 测试图片描述 (可选) ---
-    if gemini_assistant._model and gemini_assistant.support_vision:
-        print("\n--- 测试图片描述 (get_image_description) ---")
-        # 将 'path/to/your/test_image.jpg' 替换为实际的图片路径
-        image_test_path_str = "test_image.jpg" # 假设图片在脚本同目录下
-        image_test_path = pathlib.Path(image_test_path_str)
-
-        if image_test_path.exists():
-            desc_prompt = "详细描述这张图片里的所有元素和场景氛围。"
-            print(f"图片路径: {image_test_path.absolute()}")
-            print(f"描述提示: {desc_prompt}")
-            start_time = time.time()
-            description = gemini_assistant.get_image_description(str(image_test_path), desc_prompt)
-            end_time = time.time()
-            print(f"\n图片描述 (耗时: {end_time - start_time:.2f}s):\n{description}")
-        else:
-            print(f"\n跳过图片测试，测试图片文件未找到: {image_test_path.absolute()}")
-            print("请将一张名为 test_image.jpg 的图片放在脚本相同目录下进行测试。")
-    elif gemini_assistant._model:
-         print(f"\n--- 跳过图片测试，当前模型 {gemini_assistant._model_name} 不支持视觉 ---")
-    else:
-        print("\n--- Gemini 初始化失败，跳过图片描述测试 ---")
-
-    print("\n--- Gemini 本地测试结束 ---")
diff --git a/commands/handlers.py b/commands/handlers.py
index 30d8410..49058b1 100644
--- a/commands/handlers.py
+++ b/commands/handlers.py
@@ -440,9 +440,20 @@ def handle_chitchat(ctx: 'MessageContext', match: Optional[Match]) -> bool:
             tools = [history_lookup_tool]
             tool_handler = handle_tool_call
 
+        system_prompt_override = None
+        persona_text = getattr(ctx, 'persona', None)
+        if persona_text and getattr(ctx, 'robot', None):
+            try:
+                system_prompt_override = ctx.robot._build_system_prompt(chat_model, persona_text)
+            except Exception as persona_exc:
+                if ctx.logger:
+                    ctx.logger.error(f"构建人设系统提示失败: {persona_exc}", exc_info=True)
+                system_prompt_override = None
+
         rsp = chat_model.get_answer(
             question=latest_message_prompt, 
             wxid=ctx.get_receiver(),
+            system_prompt_override=system_prompt_override,
             specific_max_history=specific_max_history,
             tools=tools,
             tool_handler=tool_handler,
@@ -562,10 +573,20 @@ def handle_perplexity_ask(ctx: 'MessageContext', match: Optional[Match]) -> bool
                 # 需要调整 get_answer 方法以支持 system_prompt_override 参数
                 # 这里我们假设已对各AI模型实现了这个参数
                 specific_max_history = getattr(ctx, 'specific_max_history', None)
+                override_prompt = fallback_prompt
+                persona_text = getattr(ctx, 'persona', None)
+                if persona_text and getattr(ctx, 'robot', None):
+                    try:
+                        override_prompt = ctx.robot._build_system_prompt(chat_model, persona_text, override_prompt=fallback_prompt)
+                    except Exception as persona_exc:
+                        if ctx.logger:
+                            ctx.logger.error(f"构建人设系统提示失败: {persona_exc}", exc_info=True)
+                        override_prompt = fallback_prompt
+
                 rsp = chat_model.get_answer(
                     question=latest_message_prompt, 
                     wxid=ctx.get_receiver(), 
-                    system_prompt_override=fallback_prompt,
+                    system_prompt_override=override_prompt,
                     specific_max_history=specific_max_history
                 )
                 
diff --git a/config.yaml.template b/config.yaml.template
index e53665b..83c0952 100644
--- a/config.yaml.template
+++ b/config.yaml.template
@@ -108,14 +108,6 @@ deepseek:  # -----deepseek配置这行不填-----
   show_reasoning: false  # 是否在回复中显示思维过程，仅在启用思维链功能时有效
   max_history_messages: 10 # <--- 添加这一行，设置 DeepSeek 最多回顾 10 条历史消息
 
-gemini:  # -----gemini配置-----
-  api_key: "YOUR_GOOGLE_API_KEY"  # 必须
-  model_flash: "gemini-1.5-pro-latest"  # 快速回复模型（可选）
-  model_reasoning: "gemini-1.5-pro-latest"  # 深度思考模型（可选）
-  prompt: "你是一个AI助手，请用通俗易懂的语言回答用户的问题。" # 可选
-  proxy: "http://127.0.0.1:7890" # 可选, 代理地址
-  max_history_messages: 20 # 可选, 对话历史长度
-
 aliyun_image:  # -----如果要使用阿里云文生图，取消下面的注释并填写相关内容，模型到阿里云百炼找通义万相-文生图2.1-Turbo-----
   enable: true  # 是否启用阿里文生图功能，false为关闭，默认开启，如果未配置，则会将消息发送给聊天大模型
   api_key: sk-xxxxxxxxxxxxxxxxxxxxxxxx  # 替换为你的DashScope API密钥
@@ -126,15 +118,6 @@ aliyun_image:  # -----如果要使用阿里云文生图，取消下面的注释
   trigger_keyword: 牛阿里  # 触发词，默认为"牛阿里"
   fallback_to_chat: true  # 当服务不可用时是否转发给聊天模型处理
 
-gemini_image:  # -----谷歌AI画图配置这行不填-----
-  enable: true  # 是否启用谷歌AI画图功能
-  api_key:  # 谷歌Gemini API密钥，必填
-  model: gemini-2.0-flash-exp-image-generation  # 模型名称，建议保持默认，只有这一个模型可以进行绘画
-  temp_dir: ./geminiimg  # 图片保存目录，可选
-  trigger_keyword: 牛谷歌  # 触发词，默认为"牛谷歌"
-  fallback_to_chat: false  # 未启用时是否回退到聊天模式
-  proxy: http://127.0.0.1:7890  # 使用Clash代理，格式为：http://域名或者IP地址:端口号
-
 perplexity:  # -----perplexity配置这行不填-----
   key:  # 填写你的Perplexity API Key
   api: https://api.perplexity.ai  # API地址
diff --git a/configuration.py b/configuration.py
index ca242df..71c4624 100644
--- a/configuration.py
+++ b/configuration.py
@@ -89,8 +89,6 @@ class Config(object):
         self.DEEPSEEK = yconfig.get("deepseek", {})
         self.PERPLEXITY = yconfig.get("perplexity", {})
         self.ALIYUN_IMAGE = yconfig.get("aliyun_image", {})
-        self.GEMINI_IMAGE = yconfig.get("gemini_image", {})
-        self.GEMINI = yconfig.get("gemini", {})
         self.AI_ROUTER = yconfig.get("ai_router", {"enable": True, "allowed_groups": []})
         self.AUTO_ACCEPT_FRIEND_REQUEST = yconfig.get("auto_accept_friend_request", False)
         self.MAX_HISTORY = yconfig.get("MAX_HISTORY", 300)
diff --git a/constants.py b/constants.py
index f34e8aa..10f7b3c 100644
--- a/constants.py
+++ b/constants.py
@@ -6,15 +6,13 @@ class ChatType(IntEnum):
     # UnKnown = 0  # 未知, 即未设置
     CHATGPT = 1  # ChatGPT
     DEEPSEEK = 2  # DeepSeek
-    GEMINI = 3  # Gemini
     PERPLEXITY = 4  # Perplexity
 
     @staticmethod
     def is_in_chat_types(chat_type: int) -> bool:
         if chat_type in [ChatType.CHATGPT.value,
                         ChatType.DEEPSEEK.value,
-                        ChatType.PERPLEXITY.value,
-                        ChatType.GEMINI.value]:
+                        ChatType.PERPLEXITY.value]:
             return True
         return False
 
diff --git a/function/func_persona.py b/function/func_persona.py
new file mode 100644
index 0000000..0a04b3a
--- /dev/null
+++ b/function/func_persona.py
@@ -0,0 +1,115 @@
+import logging
+import os
+import sqlite3
+from datetime import datetime
+from typing import Optional
+
+
+class PersonaManager:
+    """Manage persona profiles per chat session."""
+
+    def __init__(self, db_path: str = "data/message_history.db") -> None:
+        self.LOG = logging.getLogger("PersonaManager")
+        self.db_path = db_path
+        self.conn: Optional[sqlite3.Connection] = None
+        self.cursor: Optional[sqlite3.Cursor] = None
+        self._connect()
+        self._prepare_table()
+
+    def _connect(self) -> None:
+        try:
+            db_dir = os.path.dirname(self.db_path)
+            if db_dir and not os.path.exists(db_dir):
+                os.makedirs(db_dir, exist_ok=True)
+                self.LOG.info(f"Created persona database directory: {db_dir}")
+
+            self.conn = sqlite3.connect(self.db_path, check_same_thread=False)
+            self.cursor = self.conn.cursor()
+            self.LOG.info(f"PersonaManager connected to database: {self.db_path}")
+        except sqlite3.Error as exc:
+            self.LOG.error(f"Failed to connect persona database: {exc}")
+            raise
+
+    def _prepare_table(self) -> None:
+        assert self.cursor is not None
+        try:
+            self.cursor.execute(
+                """
+                CREATE TABLE IF NOT EXISTS personas (
+                    chat_id TEXT PRIMARY KEY,
+                    persona TEXT NOT NULL,
+                    setter_wxid TEXT,
+                    updated_at TEXT NOT NULL
+                )
+                """
+            )
+            self.conn.commit()
+        except sqlite3.Error as exc:
+            self.LOG.error(f"Failed to ensure personas table exists: {exc}")
+            raise
+
+    def set_persona(self, chat_id: str, persona: str, setter_wxid: Optional[str] = None) -> None:
+        if not chat_id:
+            raise ValueError("chat_id must not be empty when setting persona")
+        if persona is None:
+            raise ValueError("persona must not be None when setting persona")
+
+        persona = persona.strip()
+        assert self.cursor is not None
+
+        timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+        try:
+            self.cursor.execute(
+                """
+                INSERT INTO personas (chat_id, persona, setter_wxid, updated_at)
+                VALUES (?, ?, ?, ?)
+                ON CONFLICT(chat_id) DO UPDATE SET
+                    persona=excluded.persona,
+                    setter_wxid=excluded.setter_wxid,
+                    updated_at=excluded.updated_at
+                """,
+                (chat_id, persona, setter_wxid, timestamp),
+            )
+            self.conn.commit()
+            self.LOG.info(f"Persona updated for chat_id={chat_id}")
+        except sqlite3.Error as exc:
+            self.conn.rollback()
+            self.LOG.error(f"Failed to set persona for {chat_id}: {exc}")
+            raise
+
+    def clear_persona(self, chat_id: str) -> bool:
+        if not chat_id:
+            return False
+        assert self.cursor is not None
+        try:
+            self.cursor.execute("DELETE FROM personas WHERE chat_id = ?", (chat_id,))
+            deleted = self.cursor.rowcount
+            self.conn.commit()
+            if deleted:
+                self.LOG.info(f"Persona cleared for chat_id={chat_id}")
+            return bool(deleted)
+        except sqlite3.Error as exc:
+            self.conn.rollback()
+            self.LOG.error(f"Failed to clear persona for {chat_id}: {exc}")
+            return False
+
+    def get_persona(self, chat_id: str) -> Optional[str]:
+        if not chat_id:
+            return None
+        assert self.cursor is not None
+        try:
+            self.cursor.execute("SELECT persona FROM personas WHERE chat_id = ?", (chat_id,))
+            row = self.cursor.fetchone()
+            return row[0] if row else None
+        except sqlite3.Error as exc:
+            self.LOG.error(f"Failed to fetch persona for {chat_id}: {exc}")
+            return None
+
+    def close(self) -> None:
+        if self.conn:
+            try:
+                self.conn.commit()
+                self.conn.close()
+                self.LOG.info("PersonaManager database connection closed")
+            except sqlite3.Error as exc:
+                self.LOG.error(f"Failed to close persona database connection: {exc}")
diff --git a/image/__init__.py b/image/__init__.py
index 185416e..87f3422 100644
--- a/image/__init__.py
+++ b/image/__init__.py
@@ -2,10 +2,8 @@
 
 包含以下功能：
 - AliyunImage: 阿里云文生图
-- GeminiImage: 谷歌Gemini文生图
 """
 
 from .img_aliyun_image import AliyunImage
-from .img_gemini_image import GeminiImage
 
-__all__ = ['AliyunImage', 'GeminiImage']
\ No newline at end of file
+__all__ = ['AliyunImage']
diff --git a/image/img_gemini_image.py b/image/img_gemini_image.py
deleted file mode 100644
index 708a2bd..0000000
--- a/image/img_gemini_image.py
+++ /dev/null
@@ -1,113 +0,0 @@
-#! /usr/bin/env python3
-# -*- coding: utf-8 -*-
-
-import logging
-import os
-import mimetypes
-import time
-import random
-from google import genai
-from google.genai import types
-
-class GeminiImage:
-    """谷歌AI画图API调用
-    """
-
-    def __init__(self, config={}) -> None:
-        self.LOG = logging.getLogger("GeminiImage")
-        
-        self.enable = config.get("enable", True)
-        self.api_key = config.get("api_key", "") or os.environ.get("GEMINI_API_KEY", "")
-        self.model = config.get("model", "gemini-2.0-flash-exp-image-generation")
-        self.proxy = config.get("proxy", "")
-        
-        project_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
-        self.temp_dir = config.get("temp_dir", os.path.join(project_dir, "geminiimg"))
-        
-        if not os.path.exists(self.temp_dir):
-            os.makedirs(self.temp_dir)
-        
-        if not self.api_key:
-            self.enable = False
-            return
-            
-        try:
-            # 设置代理
-            if self.proxy:
-                os.environ["HTTP_PROXY"] = self.proxy
-                os.environ["HTTPS_PROXY"] = self.proxy
-            
-            # 初始化客户端
-            self.client = genai.Client(api_key=self.api_key)
-        except Exception:
-            self.enable = False
-    
-    def generate_image(self, prompt: str) -> str:
-        """生成图像并返回图像文件路径
-        """
-        try:
-            # 设置代理
-            if self.proxy:
-                os.environ["HTTP_PROXY"] = self.proxy
-                os.environ["HTTPS_PROXY"] = self.proxy
-            
-            image_prompt = f"生成一张高质量的图片: {prompt}。请直接提供图像，不需要描述。"
-            
-            # 发送请求
-            response = self.client.models.generate_content(
-                model=self.model,
-                contents=image_prompt,
-                config=types.GenerateContentConfig(
-                    response_modalities=['Text', 'Image']
-                )
-            )
-            
-            # 处理响应
-            if hasattr(response, 'candidates') and response.candidates:
-                for candidate in response.candidates:
-                    if hasattr(candidate, 'content') and candidate.content:
-                        for part in candidate.content.parts:
-                            if hasattr(part, 'inline_data') and part.inline_data:
-                                # 保存图像
-                                file_name = f"gemini_image_{int(time.time())}_{random.randint(1000, 9999)}"
-                                file_extension = mimetypes.guess_extension(part.inline_data.mime_type) or ".png"
-                                file_path = os.path.join(self.temp_dir, f"{file_name}{file_extension}")
-                                
-                                with open(file_path, "wb") as f:
-                                    f.write(part.inline_data.data)
-                                
-                                return file_path
-            
-            # 如果没有找到图像，尝试获取文本响应
-            try:
-                text_content = response.text
-                if text_content:
-                    return f"模型未能生成图像: {text_content[:100]}..."
-            except (AttributeError, TypeError):
-                pass
-                
-            return "图像生成失败，可能需要更新模型或调整提示词"
-        
-        except Exception as e:
-            error_str = str(e)
-            self.LOG.error(f"图像生成出错: {error_str}")
-            
-            # 处理500错误
-            if "500 INTERNAL" in error_str:
-                self.LOG.error("遇到谷歌服务器内部错误")
-                return "谷歌AI服务器临时故障，请稍后再试。这是谷歌服务器的问题，不是你的请求有误。"
-            
-            if "timeout" in error_str.lower():
-                return "图像生成超时，请检查网络或代理设置"
-                
-            if "violated" in error_str.lower() or "policy" in error_str.lower():
-                return "请求包含违规内容，无法生成图像"
-            
-            # 其他常见错误类型处理
-            if "quota" in error_str.lower() or "rate" in error_str.lower():
-                return "API使用配额已用尽或请求频率过高，请稍后再试"
-                
-            if "authentication" in error_str.lower() or "auth" in error_str.lower():
-                return "API密钥验证失败，请联系管理员检查配置"
-                
-            return f"图像生成失败，错误原因: {error_str.split('.')[-1] if '.' in error_str else error_str}"
\ No newline at end of file
diff --git a/image/img_manager.py b/image/img_manager.py
index b6a45af..fa8d527 100644
--- a/image/img_manager.py
+++ b/image/img_manager.py
@@ -5,7 +5,7 @@ import shutil
 import time
 from wcferry import Wcf
 from configuration import Config
-from image import AliyunImage, GeminiImage
+from image import AliyunImage
 
 
 class ImageGenerationManager:
@@ -30,22 +30,9 @@ class ImageGenerationManager:
         
         # 初始化图像生成服务
         self.aliyun_image = None
-        self.gemini_image = None
         
         self.LOG.info("开始初始化图像生成服务...")
         
-        # 初始化Gemini图像生成服务
-        try:
-            if hasattr(self.config, 'GEMINI_IMAGE'):
-                self.gemini_image = GeminiImage(self.config.GEMINI_IMAGE)
-            else:
-                self.gemini_image = GeminiImage({})
-            
-            if getattr(self.gemini_image, 'enable', False):
-                self.LOG.info("谷歌Gemini图像生成功能已启用")
-        except Exception as e:
-            self.LOG.error(f"初始化谷歌Gemini图像生成服务失败: {e}")
-                       
         # 初始化AliyunImage服务
         if hasattr(self.config, 'ALIYUN_IMAGE') and self.config.ALIYUN_IMAGE.get('enable', False):
             try:
@@ -56,7 +43,7 @@ class ImageGenerationManager:
     
     def handle_image_generation(self, service_type, prompt, receiver, at_user=None):
         """处理图像生成请求的通用函数
-        :param service_type: 服务类型，'aliyun'/'gemini'
+        :param service_type: 服务类型，目前仅支持 'aliyun'
         :param prompt: 图像生成提示词
         :param receiver: 接收者ID
         :param at_user: 被@的用户ID，用于群聊
@@ -78,13 +65,6 @@ class ImageGenerationManager:
                 wait_message = "当前模型为阿里V1模型，生成速度非常慢，可能需要等待较长时间，请耐心等候..."
             else:
                 wait_message = "正在生成图像，请稍等..."
-        elif service_type == 'gemini':
-            if not self.gemini_image or not getattr(self.gemini_image, 'enable', False):
-                self.send_text("谷歌文生图服务未启用", receiver, at_user)
-                return True
-                
-            service = self.gemini_image
-            wait_message = "正在通过谷歌AI生成图像，请稍等..."
         else:
             self.LOG.error(f"未知的图像生成服务类型: {service_type}")
             return False
@@ -98,7 +78,7 @@ class ImageGenerationManager:
             try:
                 self.LOG.info(f"开始处理图片: {image_url}")
                 # 谷歌API直接返回本地文件路径，无需下载
-                image_path = image_url if service_type == 'gemini' else service.download_image(image_url)
+                image_path = service.download_image(image_url)
                 
                 if image_path:
                     # 创建一个临时副本，避免文件占用问题
@@ -167,4 +147,4 @@ class ImageGenerationManager:
                 else:
                     self.LOG.error(f"无法删除文件 {file_path} 经过 {max_retries} 次尝试: {str(e)}")
         
-        return False 
\ No newline at end of file
+        return False 
diff --git a/image/文生图功能的使用说明.MD b/image/文生图功能的使用说明.MD
index 3ef30cf..8f28e14 100644
--- a/image/文生图功能的使用说明.MD
+++ b/image/文生图功能的使用说明.MD
@@ -7,8 +7,6 @@
 
 阿里云AI绘画：[JiQingzhe2004 (JiQingzhe)](https://github.com/JiQingzhe2004)
 
-谷歌AI绘画：[JiQingzhe2004 (JiQingzhe)](https://github.com/JiQingzhe2004)
-
 ------
 
 在`config.yaml`中进行以下配置才可以调用：
@@ -25,23 +23,8 @@ aliyun_image:  # -----如果要使用阿里云文生图，取消下面的注释
   trigger_keyword: 牛阿里  # 触发词，默认为"牛阿里"
   fallback_to_chat: true  # 当未启用绘画功能时：true=将请求发给聊天模型处理，false=回复固定的未启用提示信息
 
-gemini_image:  # -----谷歌AI画图配置这行不填-----
-  enable: true  # 是否启用谷歌AI画图功能
-  api_key: your-api-key-here  # 谷歌Gemini API密钥，必填
-  model: gemini-2.0-flash-exp-image-generation  # 模型名称，建议保持默认，只有这一个模型可以进行绘画
-  temp_dir: ./geminiimg  # 图片保存目录，可选
-  trigger_keyword: 牛谷歌  # 触发词，默认为"牛谷歌"
-  fallback_to_chat: false  # 当未启用绘画功能时：true=将请求发给聊天模型处理，false=回复固定的未启用提示信息
 ```
 
-## 如何获取API密钥
-
-1. 访问 [Google AI Studio](https://aistudio.google.com/)
-2. 创建一个账号或登录
-3. 访问 [API Keys](https://aistudio.google.com/app/apikeys) 页面
-4. 创建一个新的API密钥
-5. 复制API密钥并填入配置文件
-
 ## 使用方法
 
 直接发送消息或在群聊中@机器人，使用触发词加提示词，例如：
@@ -50,7 +33,6 @@ gemini_image:  # -----谷歌AI画图配置这行不填-----
 ```
 牛智谱 一只可爱的猫咪在阳光下玩耍
 牛阿里 一只可爱的猫咪在阳光下玩耍
-牛谷歌 一只可爱的猫咪在阳光下玩耍
 ```
 ## 群组的使用方法
 ```
diff --git a/robot.py b/robot.py
index 3f84e9c..a3927ac 100644
--- a/robot.py
+++ b/robot.py
@@ -10,19 +10,18 @@ import os
 import random
 import shutil
 import copy
-from image import AliyunImage, GeminiImage
 from image.img_manager import ImageGenerationManager
 
 from wcferry import Wcf, WxMsg
 
 from ai_providers.ai_chatgpt import ChatGPT
 from ai_providers.ai_deepseek import DeepSeek
-from ai_providers.ai_gemini import Gemini
 from ai_providers.ai_perplexity import Perplexity
 from function.func_weather import Weather
 from function.func_news import News
 from function.func_summary import MessageSummary  # 导入新的MessageSummary类
 from function.func_reminder import ReminderManager  # 导入ReminderManager类
+from function.func_persona import PersonaManager  # 导入PersonaManager用于人设存储
 from configuration import Config
 from constants import ChatType
 from job_mgmt import Job
@@ -155,31 +154,6 @@ class Robot(Job):
             except Exception as e:
                 self.LOG.error(f"初始化 DeepSeek 模型时出错: {str(e)}")
         
-        # 初始化Gemini
-        if Gemini.value_check(self.config.GEMINI):
-            try:
-                gemini_flash_conf = copy.deepcopy(self.config.GEMINI)
-                flash_model_name = gemini_flash_conf.get("model_flash", Gemini.DEFAULT_MODEL)
-                gemini_flash_conf["model_name"] = flash_model_name
-                self.chat_models[ChatType.GEMINI.value] = Gemini(
-                    gemini_flash_conf,
-                    message_summary_instance=self.message_summary,
-                    bot_wxid=self.wxid
-                )
-                self.LOG.info(f"已加载 Gemini 模型: {flash_model_name}")
-
-                reasoning_model_name = self.config.GEMINI.get("model_reasoning")
-                if reasoning_model_name and reasoning_model_name != flash_model_name:
-                    gemini_reason_conf = copy.deepcopy(self.config.GEMINI)
-                    gemini_reason_conf["model_name"] = reasoning_model_name
-                    self.reasoning_chat_models[ChatType.GEMINI.value] = Gemini(
-                        gemini_reason_conf,
-                        message_summary_instance=self.message_summary,
-                        bot_wxid=self.wxid
-                    )
-                    self.LOG.info(f"已加载 Gemini 推理模型: {reasoning_model_name}")
-            except Exception as e:
-                self.LOG.error(f"初始化 Gemini 模型时出错: {str(e)}")
             
         # 初始化Perplexity
         if Perplexity.value_check(self.config.PERPLEXITY):
@@ -266,6 +240,15 @@ class Robot(Job):
         except Exception as e:
             self.LOG.error(f"初始化提醒管理器失败: {e}", exc_info=True)
         
+        # 初始化人设管理器
+        persona_db_path = getattr(self.message_summary, 'db_path', "data/message_history.db") if getattr(self, 'message_summary', None) else "data/message_history.db"
+        try:
+            self.persona_manager = PersonaManager(persona_db_path)
+            self.LOG.info("人设管理器已初始化。")
+        except Exception as e:
+            self.LOG.error(f"初始化人设管理器失败: {e}", exc_info=True)
+            self.persona_manager = None
+        
     @staticmethod
     def value_check(args: dict) -> bool:
         if args:
@@ -293,12 +276,23 @@ class Robot(Job):
             # 确保context能访问到当前选定的chat模型及特定历史限制
             setattr(ctx, 'chat', self.chat)
             setattr(ctx, 'specific_max_history', specific_limit)
+            persona_text = None
+            if getattr(self, 'persona_manager', None):
+                try:
+                    persona_text = self.persona_manager.get_persona(ctx.get_receiver())
+                except Exception as persona_error:
+                    self.LOG.error(f"获取会话人设失败: {persona_error}", exc_info=True)
+                    persona_text = None
+            setattr(ctx, 'persona', persona_text)
             ctx.reasoning_requested = bool(
                 ctx.text
                 and "想想" in ctx.text
                 and (not ctx.is_group or ctx.is_at_bot)
             )
 
+            if self._handle_persona_command(ctx):
+                return
+
             if ctx.reasoning_requested:
                 self.LOG.info("检测到推理模式触发词，跳过AI路由，直接进入闲聊推理模式。")
                 self._handle_chitchat(ctx, None)
@@ -581,6 +575,12 @@ class Robot(Job):
         if hasattr(self, 'message_summary') and self.message_summary:
             self.LOG.info("正在关闭消息历史数据库...")
             self.message_summary.close_db()
+        if hasattr(self, 'persona_manager') and self.persona_manager:
+            self.LOG.info("正在关闭人设数据库连接...")
+            try:
+                self.persona_manager.close()
+            except Exception as e:
+                self.LOG.error(f"关闭人设数据库时出错: {e}")
         
         self.LOG.info("机器人资源清理完成")
                 
@@ -609,6 +609,126 @@ class Robot(Job):
             
         return None
     
+    def _handle_persona_command(self, ctx: MessageContext) -> bool:
+        """处理 /set 人设命令"""
+        text = (ctx.text or "").strip()
+        if not text or not text.startswith("/"):
+            return False
+
+        parts = text.split(None, 1)
+        command = parts[0].lower()
+        payload = parts[1] if len(parts) > 1 else ""
+
+        at_list = ctx.msg.sender if ctx.is_group else ""
+        scope_label = "本群" if ctx.is_group else "当前会话"
+
+        if command == "/persona":
+            if not getattr(self, "persona_manager", None):
+                ctx.send_text("❌ 人设功能暂不可用。", at_list)
+                return True
+
+            persona_text = getattr(ctx, "persona", None)
+            if persona_text is None:
+                try:
+                    persona_text = self.persona_manager.get_persona(ctx.get_receiver())
+                    setattr(ctx, "persona", persona_text)
+                except Exception as exc:
+                    self.LOG.error(f"查询人设失败: {exc}", exc_info=True)
+                    persona_text = None
+
+            if persona_text:
+                ctx.send_text(f"{scope_label}当前的人设是：\n## 角色\n{persona_text}", at_list)
+            else:
+                ctx.send_text(f"{scope_label}当前没有设置人设，可发送“/set 你的人设描述”来设定。", at_list)
+            return True
+
+        if command != "/set":
+            return False
+
+        if not getattr(self, "persona_manager", None):
+            ctx.send_text("❌ 人设功能暂不可用。", at_list)
+            return True
+
+        persona_body = payload.strip()
+        chat_id = ctx.get_receiver()
+
+        if not persona_body:
+            current = getattr(ctx, "persona", None)
+            if current:
+                ctx.send_text(
+                    f"{scope_label}当前的人设是：\n{current}\n发送“/set clear”可以清空，或重新发送“/set + 新人设”进行更新。\n也可以使用“/persona”随时查看当前人设。",
+                    at_list
+                )
+            else:
+                ctx.send_text("请在 /set 后输入人设描述，例如：/set 你是一个幽默的机器人助手。", at_list)
+            return True
+
+        if persona_body.lower() in {"clear", "reset"}:
+            cleared = self.persona_manager.clear_persona(chat_id)
+            setattr(ctx, "persona", None)
+            if cleared:
+                ctx.send_text(f"✅ 已清空{scope_label}的人设。", at_list)
+            else:
+                ctx.send_text(f"{scope_label}当前没有设置人设。", at_list)
+            return True
+
+        try:
+            self.persona_manager.set_persona(chat_id, persona_body, setter_wxid=ctx.msg.sender)
+            setattr(ctx, "persona", persona_body)
+            preview = persona_body if len(persona_body) <= 120 else persona_body[:120] + "..."
+            ctx.send_text(
+                f"✅ {scope_label}人设设定成功：\n## 角色\n{preview}"
+                f"{'' if len(preview) == len(persona_body) else '...'}\n如需查看完整内容，可发送“/persona”。",
+                at_list
+            )
+        except Exception as exc:
+            self.LOG.error(f"设置人设失败: {exc}", exc_info=True)
+            ctx.send_text("❌ 设置人设时遇到问题，请稍后再试。", at_list)
+        return True
+
+    @staticmethod
+    def _get_model_base_prompt(chat_model):
+        """获取模型默认的系统提示"""
+        if not chat_model:
+            return None
+
+        system_msg = getattr(chat_model, "system_content_msg", None)
+        if isinstance(system_msg, dict):
+            prompt = system_msg.get("content")
+            if prompt:
+                return prompt
+
+        if hasattr(chat_model, "_base_prompt"):
+            prompt = getattr(chat_model, "_base_prompt")
+            if prompt:
+                return prompt
+
+        if hasattr(chat_model, "prompt"):
+            prompt = getattr(chat_model, "prompt")
+            if prompt:
+                return prompt
+
+        return None
+
+    @staticmethod
+    def _merge_prompt_with_persona(prompt, persona):
+        """将人设信息附加到系统提示后"""
+        persona = (persona or "").strip()
+        prompt = (prompt or "").strip() if prompt else ""
+
+        if persona:
+            persona_section = f"## 角色\n{persona}"
+            if prompt:
+                return f"{persona_section}\n\n{prompt}"
+            return persona_section
+
+        return prompt or None
+
+    def _build_system_prompt(self, chat_model, persona=None, override_prompt=None):
+        """生成包含人设的系统提示"""
+        base_prompt = override_prompt if override_prompt is not None else self._get_model_base_prompt(chat_model)
+        return self._merge_prompt_with_persona(base_prompt, persona)
+
     def _get_reasoning_chat_model(self):
         """获取当前聊天模型对应的推理模型实例"""
         model_id = getattr(self, 'current_model_id', None)
@@ -668,7 +788,6 @@ class Robot(Job):
         mapping = {
             ChatType.CHATGPT.value: getattr(self.config, 'CHATGPT', None),
             ChatType.DEEPSEEK.value: getattr(self.config, 'DEEPSEEK', None),
-            ChatType.GEMINI.value: getattr(self.config, 'GEMINI', None),
             ChatType.PERPLEXITY.value: getattr(self.config, 'PERPLEXITY', None),
         }
         return mapping.get(model_id)