Merge pull request #2596 from 6vision/master

feat: support claude-4-opus and claude-4-sonnet models

.gitignore

@@ -14,6 +14,9 @@ tmp
 plugins.json
 itchat.pkl
 *.log
+logs/
+workspace
+config.yaml
 user_datas.pkl
 chatgpt_tool_hub/
 plugins/**/
@@ -30,4 +33,5 @@ plugins/banwords/lib/__pycache__
 !plugins/role
 !plugins/keyword
 !plugins/linkai
+!plugins/agent
 client_config.json

README.md

@@ -1,11 +1,19 @@
-# 简介
+<p align="center"><img src= "https://github.com/user-attachments/assets/31fb4eab-3be4-477d-aa76-82cf62bfd12c" alt="Chatgpt-on-Wechat" width="600" /></p>
 
-> chatgpt-on-wechat（简称CoW）项目是基于大模型的智能对话机器人，支持微信公众号、企业微信应用、飞书、钉钉接入，可选择GPT3.5/GPT4.0/Claude/Gemini/LinkAI/ChatGLM/KIMI/文心一言/讯飞星火/通义千问/LinkAI，能处理文本、语音和图片，通过插件访问操作系统和互联网等外部资源，支持基于自有知识库定制企业AI应用。
+<p align="center">
+   <a href="https://github.com/zhayujie/chatgpt-on-wechat/releases/latest"><img src="https://img.shields.io/github/v/release/zhayujie/chatgpt-on-wechat" alt="Latest release"></a>
+  <a href="https://github.com/zhayujie/chatgpt-on-wechat/blob/master/LICENSE"><img src="https://img.shields.io/github/license/zhayujie/chatgpt-on-wechat" alt="License: MIT"></a>
+  <a href="https://github.com/zhayujie/chatgpt-on-wechat"><img src="https://img.shields.io/github/stars/zhayujie/chatgpt-on-wechat?style=flat-square" alt="Stars"></a> <br/>
+</p>
+
+chatgpt-on-wechat（简称CoW）项目是基于大模型的智能对话机器人，支持微信公众号、企业微信应用、飞书、钉钉接入，可选择GPT3.5/GPT4.0/Claude/Gemini/LinkAI/ChatGLM/KIMI/文心一言/讯飞星火/通义千问/LinkAI/ModelScope，能处理文本、语音和图片，通过插件访问操作系统和互联网等外部资源，支持基于自有知识库定制企业AI应用。
+
+# 简介
 
 最新版本支持的功能如下：
 
 -  ✅   **多端部署：** 有多种部署方式可选择且功能完备，目前已支持微信公众号、企业微信应用、飞书、钉钉等部署方式
--  ✅   **基础对话：** 私聊及群聊的消息智能回复，支持多轮会话上下文记忆，支持 GPT-3.5, GPT-4o-mini, GPT-4o,  GPT-4, Claude-3.5, Gemini, 文心一言, 讯飞星火, 通义千问，ChatGLM-4，Kimi(月之暗面), MiniMax
+-  ✅   **基础对话：** 私聊及群聊的消息智能回复，支持多轮会话上下文记忆，支持 GPT-4o系列, GPT-4.1系列, Claude, Gemini, 文心一言, 讯飞星火, 通义千问，ChatGLM-4，Kimi, MiniMax, GiteeAI, ModelScope
 -  ✅   **语音能力：** 可识别语音消息，通过文字或语音回复，支持 azure, baidu, google, openai(whisper/tts) 等多种语音模型
 -  ✅   **图像能力：** 支持图片生成、图片识别、图生图（如照片修复），可选择 Dall-E-3, stable diffusion, replicate, midjourney, CogView-3, vision模型
 -  ✅   **丰富插件：** 支持个性化插件扩展，已实现多角色切换、文字冒险、敏感词过滤、聊天记录总结、文档总结和对话、联网搜索等插件
@@ -45,6 +53,13 @@ DEMO视频：https://cdn.link-ai.tech/doc/cow_demo.mp4
 <br>
 
 # 🏷 更新日志
+
+>**2025.05.23：** [1.7.6版本](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/1.7.6) 优化web网页channel、新增[AgentMesh多智能体插件](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/plugins/agent/README.md)、百度语音合成优化、企微应用`access_token`获取优化、支持`claude-4-sonnet`和`claude-4-opus`模型
+
+>**2025.04.11：** [1.7.5版本](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/1.7.5) 新增支持 [wechatferry](https://github.com/zhayujie/chatgpt-on-wechat/pull/2562) 协议、新增 deepseek 模型、新增支持腾讯云语音能力、新增支持 ModelScope 和 Gitee-AI API接口
+
+>**2024.12.13：** [1.7.4版本](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/1.7.4) 新增 Gemini 2.0 模型、新增web channel、解决内存泄漏问题、解决 `#reloadp` 命令重载不生效问题
+
 >**2024.10.31：** [1.7.3版本](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/1.7.3) 程序稳定性提升、数据库功能、Claude模型优化、linkai插件优化、离线通知
 
 >**2024.09.26：** [1.7.2版本](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/1.7.2)  和 [1.7.1版本](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/1.7.1) 文心，讯飞等模型优化、o1 模型、快速安装和管理脚本
@@ -142,7 +157,7 @@ pip3 install -r requirements-optional.txt
 ```bash
 # config.json文件内容示例
 {
-  "model": "gpt-3.5-turbo",                                   # 模型名称, 支持 gpt-3.5-turbo, gpt-4, gpt-4-turbo, wenxin, xunfei, glm-4, claude-3-haiku, moonshot
+  "model": "gpt-4o-mini",                                     # 模型名称, 支持 gpt-4o-mini, gpt-4.1, gpt-4o, wenxin, xunfei, glm-4, claude-3-7-sonnet-latest, moonshot等
   "open_ai_api_key": "YOUR API KEY",                          # 如果使用openAI模型则填入上面创建的 OpenAI API KEY
   "open_ai_api_base": "https://api.openai.com/v1",            # OpenAI接口代理地址
   "proxy": "",                                                # 代理客户端的ip和端口，国内环境开启代理的需要填写该项，如 "127.0.0.1:7890"
@@ -186,7 +201,7 @@ pip3 install -r requirements-optional.txt
 
 **4.其他配置**
 
-+ `model`: 模型名称，目前支持 `gpt-3.5-turbo`, `gpt-4o-mini`, `gpt-4o`, `gpt-4`, `wenxin` , `claude` , `gemini`, `glm-4`,  `xunfei`, `moonshot`等，全部模型名称参考[common/const.py](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/common/const.py)文件
++ `model`: 模型名称，目前支持 `gpt-4o-mini`, `gpt-4.1`, `gpt-4o`, `gpt-3.5-turbo`, `wenxin` , `claude` , `gemini`, `glm-4`,  `xunfei`, `moonshot`等，全部模型名称参考[common/const.py](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/common/const.py)文件
 + `temperature`,`frequency_penalty`,`presence_penalty`: Chat API接口参数，详情参考[OpenAI官方文档。](https://platform.openai.com/docs/api-reference/chat)
 + `proxy`：由于目前 `openai` 接口国内无法访问，需配置代理客户端的地址，详情参考  [#351](https://github.com/zhayujie/chatgpt-on-wechat/issues/351)
 + 对于图像生成，在满足个人或群组触发条件外，还需要额外的关键词前缀来触发，对应配置 `image_create_prefix `

bot/bot_factory.py

@@ -68,5 +68,9 @@ def create_bot(bot_type):
         from bot.minimax.minimax_bot import MinimaxBot
         return MinimaxBot()
 
+    elif bot_type == const.MODELSCOPE:
+        from bot.modelscope.modelscope_bot import ModelScopeBot
+        return ModelScopeBot()
+
 
     raise RuntimeError

bot/chatgpt/chat_gpt_session.py

@@ -83,7 +83,7 @@ def num_tokens_from_messages(messages, model):
         tokens_per_message = 3
         tokens_per_name = 1
     else:
-        logger.warn(f"num_tokens_from_messages() is not implemented for model {model}. Returning num tokens assuming gpt-3.5-turbo.")
+        logger.debug(f"num_tokens_from_messages() is not implemented for model {model}. Returning num tokens assuming gpt-3.5-turbo.")
         return num_tokens_from_messages(messages, model="gpt-3.5-turbo")
     num_tokens = 0
     for message in messages:

bot/linkai/link_ai_bot.py

@@ -147,9 +147,9 @@ class LinkAIBot(Bot):
                 if response["choices"][0].get("img_urls"):
                     thread = threading.Thread(target=self._send_image, args=(context.get("channel"), context, response["choices"][0].get("img_urls")))
                     thread.start()
-                    if response["choices"][0].get("text_content"):
-                        reply_content = response["choices"][0].get("text_content")
-                reply_content = self._process_url(reply_content)
+                    reply_content = response["choices"][0].get("text_content")
+                if reply_content:
+                    reply_content = self._process_url(reply_content)
                 return Reply(ReplyType.TEXT, reply_content)
 
             else:

bot/modelscope/modelscope_bot.py

@@ -0,0 +1,277 @@
+# encoding:utf-8
+
+import time
+import json
+import openai
+import openai.error
+from bot.bot import Bot
+from bot.session_manager import SessionManager
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from config import conf, load_config
+from .modelscope_session import ModelScopeSession
+import requests
+
+
+# ModelScope对话模型API
+class ModelScopeBot(Bot):
+    def __init__(self):
+        super().__init__()
+        self.sessions = SessionManager(ModelScopeSession, model=conf().get("model") or "Qwen/Qwen2.5-7B-Instruct")
+        model = conf().get("model") or "Qwen/Qwen2.5-7B-Instruct"
+        if model == "modelscope":
+            model = "Qwen/Qwen2.5-7B-Instruct"
+        self.args = {
+            "model": model,  # 对话模型的名称
+            "temperature": conf().get("temperature", 0.3),  # 如果设置，值域须为 [0, 1] 我们推荐 0.3，以达到较合适的效果。
+            "top_p": conf().get("top_p", 1.0),  # 使用默认值
+        }
+        self.api_key = conf().get("modelscope_api_key")
+        self.base_url = conf().get("modelscope_base_url", "https://api-inference.modelscope.cn/v1/chat/completions")
+        """
+        需要获取ModelScope支持API-inference的模型名称列表，请到魔搭社区官网模型中心查看 https://modelscope.cn/models?filter=inference_type&page=1。
+        或者使用命令 curl https://api-inference.modelscope.cn/v1/models 对模型列表和ID进行获取。查看commend/const.py文件也可以获取模型列表。
+        获取ModelScope的免费API Key，请到魔搭社区官网用户中心查看获取方式 https://modelscope.cn/docs/model-service/API-Inference/intro。
+        """
+    def reply(self, query, context=None):
+        # acquire reply content
+        if context.type == ContextType.TEXT:
+            logger.info("[MODELSCOPE_AI] query={}".format(query))
+
+            session_id = context["session_id"]
+            reply = None
+            clear_memory_commands = conf().get("clear_memory_commands", ["#清除记忆"])
+            if query in clear_memory_commands:
+                self.sessions.clear_session(session_id)
+                reply = Reply(ReplyType.INFO, "记忆已清除")
+            elif query == "#清除所有":
+                self.sessions.clear_all_session()
+                reply = Reply(ReplyType.INFO, "所有人记忆已清除")
+            elif query == "#更新配置":
+                load_config()
+                reply = Reply(ReplyType.INFO, "配置已更新")
+            if reply:
+                return reply
+            session = self.sessions.session_query(query, session_id)
+            logger.debug("[MODELSCOPE_AI] session query={}".format(session.messages))
+
+            model = context.get("modelscope_model")
+            new_args = self.args.copy()
+            if model:
+                new_args["model"] = model
+
+            if new_args["model"] == "Qwen/QwQ-32B":
+                reply_content = self.reply_text_stream(session, args=new_args)
+            else:
+                reply_content = self.reply_text(session, args=new_args)
+
+            logger.debug(
+                "[MODELSCOPE_AI] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(
+                    session.messages,
+                    session_id,
+                    reply_content["content"],
+                    reply_content["completion_tokens"],
+                )
+            )
+            if reply_content["completion_tokens"] == 0 and len(reply_content["content"]) > 0:
+                # 只有当 content 为空且 completion_tokens 为 0 时才标记为错误
+                if len(reply_content["content"]) == 0:
+                    reply = Reply(ReplyType.ERROR, reply_content["content"])
+                else:
+                    reply = Reply(ReplyType.TEXT, reply_content["content"])
+            elif reply_content["completion_tokens"] > 0:
+                self.sessions.session_reply(reply_content["content"], session_id, reply_content["total_tokens"])
+                reply = Reply(ReplyType.TEXT, reply_content["content"])
+            else:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+                logger.debug("[MODELSCOPE_AI] reply {} used 0 tokens.".format(reply_content))
+            return reply
+        elif context.type == ContextType.IMAGE_CREATE:
+            ok, retstring = self.create_img(query, 0)
+            reply = None
+            if ok:
+                reply = Reply(ReplyType.IMAGE_URL, retstring)
+            else:
+                reply = Reply(ReplyType.ERROR, retstring)
+            return reply
+        else:
+            reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type))
+            return reply
+
+    def reply_text(self, session: ModelScopeSession, args=None, retry_count=0) -> dict:
+        """
+        call openai's ChatCompletion to get the answer
+        :param session: a conversation session
+        :param session_id: session id
+        :param retry_count: retry count
+        :return: {}
+        """
+        try:
+            headers = {
+                "Content-Type": "application/json",
+                "Authorization": "Bearer " + self.api_key
+            }
+            
+            body = args
+            body["messages"] = session.messages
+            res = requests.post(
+                self.base_url,
+                headers=headers,
+                data=json.dumps(body)
+            )
+
+            if res.status_code == 200:
+                response = res.json()
+                return {
+                    "total_tokens": response["usage"]["total_tokens"],
+                    "completion_tokens": response["usage"]["completion_tokens"],
+                    "content": response["choices"][0]["message"]["content"]
+                }
+            else:
+                response = res.json()
+                if "errors" in response:
+                    error = response.get("errors")
+                elif "error" in response:
+                    error = response.get("error")
+                else:
+                    error = "Unknown error"
+                logger.error(f"[MODELSCOPE_AI] chat failed, status_code={res.status_code}, "
+                             f"msg={error.get('message')}, type={error.get('type')}")
+
+                result = {"completion_tokens": 0, "content": "提问太快啦，请休息一下再问我吧"}
+                need_retry = False
+                if res.status_code >= 500:
+                    # server error, need retry
+                    logger.warn(f"[MODELSCOPE_AI] do retry, times={retry_count}")
+                    need_retry = retry_count < 2
+                elif res.status_code == 401:
+                    result["content"] = "授权失败，请检查API Key是否正确"
+                elif res.status_code == 429:
+                    result["content"] = "请求过于频繁，请稍后再试"
+                    need_retry = retry_count < 2
+                else:
+                    need_retry = False
+
+                if need_retry:
+                    time.sleep(3)
+                    return self.reply_text(session, args, retry_count + 1)
+                else:
+                    return result
+        except Exception as e:
+            logger.exception(e)
+            need_retry = retry_count < 2
+            result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
+            if need_retry:
+                return self.reply_text(session, args, retry_count + 1)
+            else:
+                return result
+
+    def reply_text_stream(self, session: ModelScopeSession, args=None, retry_count=0) -> dict:
+        """
+        call ModelScope's ChatCompletion to get the answer with stream response
+        :param session: a conversation session
+        :param session_id: session id
+        :param retry_count: retry count
+        :return: {}
+        """
+        try:
+            headers = {
+                "Content-Type": "application/json",
+                "Authorization": "Bearer " + self.api_key
+            }
+            
+            body = args
+            body["messages"] = session.messages
+            body["stream"] = True  # 启用流式响应
+
+            res = requests.post(
+                self.base_url,
+                headers=headers,
+                data=json.dumps(body),
+                stream=True
+            )
+            if res.status_code == 200:
+                content = ""
+                for line in res.iter_lines():
+                    if line:
+                        decoded_line = line.decode('utf-8')
+                        if decoded_line.startswith("data: "):
+                            try:
+                                json_data = json.loads(decoded_line[6:])
+                                delta_content = json_data.get("choices", [{}])[0].get("delta", {}).get("content", "")
+                                if delta_content:
+                                    content += delta_content
+                            except json.JSONDecodeError as e:
+                                pass
+                return {
+                    "total_tokens": 1,  # 流式响应通常不返回token使用情况
+                    "completion_tokens": 1,
+                    "content": content
+                }
+            else:
+                response = res.json()
+                if "errors" in response:
+                    error = response.get("errors")
+                elif "error" in response:
+                    error = response.get("error")
+                else:
+                    error = "Unknown error"
+                logger.error(f"[MODELSCOPE_AI] chat failed, status_code={res.status_code}, "
+                             f"msg={error.get('message')}, type={error.get('type')}")
+
+                result = {"completion_tokens": 0, "content": "提问太快啦，请休息一下再问我吧"}
+                need_retry = False
+                if res.status_code >= 500:
+                    # server error, need retry
+                    logger.warn(f"[MODELSCOPE_AI] do retry, times={retry_count}")
+                    need_retry = retry_count < 2
+                elif res.status_code == 401:
+                    result["content"] = "授权失败，请检查API Key是否正确"
+                elif res.status_code == 429:
+                    result["content"] = "请求过于频繁，请稍后再试"
+                    need_retry = retry_count < 2
+                else:
+                    need_retry = False
+
+                if need_retry:
+                    time.sleep(3)
+                    return self.reply_text_stream(session, args, retry_count + 1)
+                else:
+                    return result
+        except Exception as e:
+            logger.exception(e)
+            need_retry = retry_count < 2
+            result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
+            if need_retry:
+                return self.reply_text_stream(session, args, retry_count + 1)
+            else:
+                return result
+    def create_img(self, query, retry_count=0):
+        try:
+            logger.info("[ModelScopeImage] image_query={}".format(query))
+            headers = {
+                "Content-Type": "application/json; charset=utf-8",  # 明确指定编码
+                "Authorization": f"Bearer {self.api_key}"
+            }
+            payload = {
+                "prompt": query,  # required
+                "n": 1,
+                "model": conf().get("text_to_image"),
+            }
+            url = "https://api-inference.modelscope.cn/v1/images/generations"
+            
+            # 手动序列化并保留中文（禁用 ASCII 转义）
+            json_payload = json.dumps(payload, ensure_ascii=False).encode('utf-8')
+            
+            # 使用 data 参数发送原始字符串（requests 会自动处理编码）
+            res = requests.post(url, headers=headers, data=json_payload)
+            
+            response_data = res.json()
+            image_url = response_data['images'][0]['url']
+            logger.info("[ModelScopeImage] image_url={}".format(image_url))
+            return True, image_url
+
+        except Exception as e:
+            logger.error(format(e))
+            return False, "画图出现问题，请休息一下再问我吧"

bot/modelscope/modelscope_session.py

@@ -0,0 +1,51 @@
+from bot.session_manager import Session
+from common.log import logger
+
+
+class ModelScopeSession(Session):
+    def __init__(self, session_id, system_prompt=None, model="Qwen/Qwen2.5-7B-Instruct"):
+        super().__init__(session_id, system_prompt)
+        self.model = model
+        self.reset()
+
+    def discard_exceeding(self, max_tokens, cur_tokens=None):
+        precise = True
+        try:
+            cur_tokens = self.calc_tokens()
+        except Exception as e:
+            precise = False
+            if cur_tokens is None:
+                raise e
+            logger.debug("Exception when counting tokens precisely for query: {}".format(e))
+        while cur_tokens > max_tokens:
+            if len(self.messages) > 2:
+                self.messages.pop(1)
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "assistant":
+                self.messages.pop(1)
+                if precise:
+                    cur_tokens = self.calc_tokens()
+                else:
+                    cur_tokens = cur_tokens - max_tokens
+                break
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "user":
+                logger.warn("user message exceed max_tokens. total_tokens={}".format(cur_tokens))
+                break
+            else:
+                logger.debug("max_tokens={}, total_tokens={}, len(messages)={}".format(max_tokens, cur_tokens,
+                                                                                       len(self.messages)))
+                break
+            if precise:
+                cur_tokens = self.calc_tokens()
+            else:
+                cur_tokens = cur_tokens - max_tokens
+        return cur_tokens
+
+    def calc_tokens(self):
+        return num_tokens_from_messages(self.messages, self.model)
+
+
+def num_tokens_from_messages(messages, model):
+    tokens = 0
+    for msg in messages:
+        tokens += len(msg["content"])
+    return tokens

bot/xunfei/xunfei_spark_bot.py

@@ -41,7 +41,7 @@ class XunFeiBot(Bot):
         self.api_key = conf().get("xunfei_api_key")
         self.api_secret = conf().get("xunfei_api_secret")
         # 默认使用v2.0版本: "generalv2"
-        # Spark Lite请求地址(spark_url): wss://spark-api.xf-yun.com/v1.1/chat, 对应的domain参数为: "general"
+        # Spark Lite请求地址(spark_url): wss://spark-api.xf-yun.com/v1.1/chat, 对应的domain参数为: "lite"
         # Spark V2.0请求地址(spark_url): wss://spark-api.xf-yun.com/v2.1/chat, 对应的domain参数为: "generalv2"
         # Spark Pro 请求地址(spark_url): wss://spark-api.xf-yun.com/v3.1/chat, 对应的domain参数为: "generalv3"
         # Spark Pro-128K请求地址(spark_url):  wss://spark-api.xf-yun.com/chat/pro-128k, 对应的domain参数为: "pro-128k"

bridge/bridge.py

@@ -40,7 +40,7 @@ class Bridge(object):
                 self.btype["chat"] = const.GEMINI
             if model_type and model_type.startswith("glm"):
                 self.btype["chat"] = const.ZHIPU_AI
-            if model_type and model_type.startswith("claude-3"):
+            if model_type and model_type.startswith("claude"):
                 self.btype["chat"] = const.CLAUDEAPI
 
             if model_type in ["claude"]:
@@ -49,6 +49,9 @@ class Bridge(object):
             if model_type in [const.MOONSHOT, "moonshot-v1-8k", "moonshot-v1-32k", "moonshot-v1-128k"]:
                 self.btype["chat"] = const.MOONSHOT
 
+            if model_type in [const.MODELSCOPE]:
+                self.btype["chat"] = const.MODELSCOPE
+            
             if model_type in ["abab6.5-chat"]:
                 self.btype["chat"] = const.MiniMax
 

channel/channel_factory.py

@@ -18,6 +18,9 @@ def create_channel(channel_type) -> Channel:
     elif channel_type == "wxy":
         from channel.wechat.wechaty_channel import WechatyChannel
         ch = WechatyChannel()
+    elif channel_type == "wcf":
+        from channel.wechat.wcf_channel import WechatfChannel
+        ch = WechatfChannel()
     elif channel_type == "terminal":
         from channel.terminal.terminal_channel import TerminalChannel
         ch = TerminalChannel()

channel/chat_channel.py

@@ -146,6 +146,7 @@ class ChatChannel(Channel):
                 elif context["origin_ctype"] == ContextType.VOICE:  # 如果源消息是私聊的语音消息，允许不匹配前缀，放宽条件
                     pass
                 else:
+                    logger.info("[chat_channel]receive single chat msg, but checkprefix didn't match")
                     return None
             content = content.strip()
             img_match_prefix = check_prefix(content, conf().get("image_create_prefix",[""]))

channel/web/README.md

@@ -1,7 +1,10 @@
-# Web channel
-使用SSE（Server-Sent Events，服务器推送事件）实现，提供了一个默认的网页。也可以自己实现加入api
+# Web Channel
 
-#使用方法
-- 在配置文件中channel_type填入web即可
-- 访问地址 http://localhost:9899
-- port可以在配置项 web_port中设置
+提供了一个默认的AI对话页面，可展示文本、图片等消息交互，支持markdown语法渲染，兼容插件执行。
+
+# 使用说明
+
+ - 在 `config.json` 配置文件中的 `channel_type` 字段填入 `web`
+ - 程序运行后将监听9899端口，浏览器访问 http://localhost:9899/chat 即可使用
+ - 监听端口可以在配置文件 `web_port` 中自定义
+ - 对于Docker运行方式，如果需要外部访问，需要在 `docker-compose.yml` 中通过 ports配置将端口监听映射到宿主机

channel/web/web_channel.py

@@ -2,7 +2,8 @@ import sys
 import time
 import web
 import json
-from queue import Queue
+import uuid
+from queue import Queue, Empty
 from bridge.context import *
 from bridge.reply import Reply, ReplyType
 from channel.chat_channel import ChatChannel, check_prefix
@@ -11,7 +12,9 @@ from common.log import logger
 from common.singleton import singleton
 from config import conf
 import os
-
+import mimetypes  # 添加这行来处理MIME类型
+import threading
+import logging
 
 class WebMessage(ChatMessage):
     def __init__(
@@ -43,131 +46,138 @@ class WebChannel(ChatChannel):
 
     def __init__(self):
         super().__init__()
-        self.message_queues = {}  # 为每个用户存储一个消息队列
         self.msg_id_counter = 0  # 添加消息ID计数器
+        self.session_queues = {}  # 存储session_id到队列的映射
+        self.request_to_session = {}  # 存储request_id到session_id的映射
 
     def _generate_msg_id(self):
         """生成唯一的消息ID"""
         self.msg_id_counter += 1
         return str(int(time.time())) + str(self.msg_id_counter)
 
+    def _generate_request_id(self):
+        """生成唯一的请求ID"""
+        return str(uuid.uuid4())
+
     def send(self, reply: Reply, context: Context):
         try:
-            if reply.type == ReplyType.IMAGE:
-                from PIL import Image
+            if reply.type in self.NOT_SUPPORT_REPLYTYPE:
+                logger.warning(f"Web channel doesn't support {reply.type} yet")
+                return
 
-                image_storage = reply.content
-                image_storage.seek(0)
-                img = Image.open(image_storage)
-                print("<IMAGE>")
-                img.show()
-            elif reply.type == ReplyType.IMAGE_URL:
-                import io
+            if reply.type == ReplyType.IMAGE_URL:
+                time.sleep(0.5)
 
-                import requests
-                from PIL import Image
-
-                img_url = reply.content
-                pic_res = requests.get(img_url, stream=True)
-                image_storage = io.BytesIO()
-                for block in pic_res.iter_content(1024):
-                    image_storage.write(block)
-                image_storage.seek(0)
-                img = Image.open(image_storage)
-                print(img_url)
-                img.show()
-            else:
-                print(reply.content)
-
-            # 获取用户ID，如果没有则使用默认值
-            # user_id = getattr(context.get("session", None), "session_id", "default_user")
-            user_id = context["receiver"]
-            # 确保用户有对应的消息队列
-            if user_id not in self.message_queues:
-                self.message_queues[user_id] = Queue()
+            # 获取请求ID和会话ID
+            request_id = context.get("request_id", None)
+            
+            if not request_id:
+                logger.error("No request_id found in context, cannot send message")
+                return
                 
-            # 将消息放入对应用户的队列
-            message_data = {
-                "type": str(reply.type),
-                "content": reply.content,
-                "timestamp": time.time()
-            }
-            self.message_queues[user_id].put(message_data)
-            logger.debug(f"Message queued for user {user_id}")
+            # 通过request_id获取session_id
+            session_id = self.request_to_session.get(request_id)
+            if not session_id:
+                logger.error(f"No session_id found for request {request_id}")
+                return
+            
+            # 检查是否有会话队列
+            if session_id in self.session_queues:
+                # 创建响应数据，包含请求ID以区分不同请求的响应
+                response_data = {
+                    "type": str(reply.type),
+                    "content": reply.content,
+                    "timestamp": time.time(),
+                    "request_id": request_id
+                }
+                self.session_queues[session_id].put(response_data)
+                logger.debug(f"Response sent to queue for session {session_id}, request {request_id}")
+            else:
+                logger.warning(f"No response queue found for session {session_id}, response dropped")
             
         except Exception as e:
             logger.error(f"Error in send method: {e}")
-            raise
-
-    def sse_handler(self, user_id):
-        """
-        Handle Server-Sent Events (SSE) for real-time communication.
-        """
-        web.header('Content-Type', 'text/event-stream')
-        web.header('Cache-Control', 'no-cache')
-        web.header('Connection', 'keep-alive')
-        
-        # 确保用户有消息队列
-        if user_id not in self.message_queues:
-            self.message_queues[user_id] = Queue()
-        
-        try:    
-            while True:
-                try:
-                    # 发送心跳
-                    yield f": heartbeat\n\n"
-                    
-                    # 非阻塞方式获取消息
-                    if not self.message_queues[user_id].empty():
-                        message = self.message_queues[user_id].get_nowait()
-                        yield f"data: {json.dumps(message)}\n\n"
-                    time.sleep(0.5)
-                except Exception as e:
-                    logger.error(f"SSE Error: {e}")
-                    break
-        finally:
-            # 清理资源
-            if user_id in self.message_queues:
-                # 只有当队列为空时才删除
-                if self.message_queues[user_id].empty():
-                    del self.message_queues[user_id]
 
     def post_message(self):
         """
         Handle incoming messages from users via POST request.
+        Returns a request_id for tracking this specific request.
         """
         try:
             data = web.data()  # 获取原始POST数据
             json_data = json.loads(data)
-            user_id = json_data.get('user_id', 'default_user')
+            session_id = json_data.get('session_id', f'session_{int(time.time())}')
             prompt = json_data.get('message', '')
-        except json.JSONDecodeError:
-            return json.dumps({"status": "error", "message": "Invalid JSON"})
-        except Exception as e:
-            return json.dumps({"status": "error", "message": str(e)})
-        
-        if not prompt:
-            return json.dumps({"status": "error", "message": "No message provided"})
             
-        try:
-            msg_id = self._generate_msg_id()
-            context = self._compose_context(ContextType.TEXT, prompt, msg=WebMessage(msg_id, 
-                                                                                     prompt,
-                                                                                     from_user_id=user_id,
-                                                                                     other_user_id = user_id
-                                                                                     ))
-            context["isgroup"] = False
-            # context["session"] = web.storage(session_id=user_id)
+            # 生成请求ID
+            request_id = self._generate_request_id()
             
-            if not context:
-                return json.dumps({"status": "error", "message": "Failed to process message"})
-                
-            self.produce(context)
-            return json.dumps({"status": "success", "message": "Message received"})
+            # 将请求ID与会话ID关联
+            self.request_to_session[request_id] = session_id
+            
+            # 确保会话队列存在
+            if session_id not in self.session_queues:
+                self.session_queues[session_id] = Queue()
+            
+            # 创建消息对象
+            msg = WebMessage(self._generate_msg_id(), prompt)
+            msg.from_user_id = session_id  # 使用会话ID作为用户ID
+            
+            # 创建上下文
+            context = self._compose_context(ContextType.TEXT, prompt, msg=msg)
+            
+            # 添加必要的字段
+            context["session_id"] = session_id
+            context["request_id"] = request_id
+            context["isgroup"] = False  # 添加 isgroup 字段
+            context["receiver"] = session_id  # 添加 receiver 字段
+            
+            # 异步处理消息 - 只传递上下文
+            threading.Thread(target=self.produce, args=(context,)).start()
+            
+            # 返回请求ID
+            return json.dumps({"status": "success", "request_id": request_id})
             
         except Exception as e:
             logger.error(f"Error processing message: {e}")
-            return json.dumps({"status": "error", "message": "Internal server error"})
+            return json.dumps({"status": "error", "message": str(e)})
+
+    def poll_response(self):
+        """
+        Poll for responses using the session_id.
+        """
+        try:
+            # 不记录轮询请求的日志
+            web.ctx.log_request = False
+            
+            data = web.data()
+            json_data = json.loads(data)
+            session_id = json_data.get('session_id')
+            
+            if not session_id or session_id not in self.session_queues:
+                return json.dumps({"status": "error", "message": "Invalid session ID"})
+            
+            # 尝试从队列获取响应，不等待
+            try:
+                # 使用peek而不是get，这样如果前端没有成功处理，下次还能获取到
+                response = self.session_queues[session_id].get(block=False)
+                
+                # 返回响应，包含请求ID以区分不同请求
+                return json.dumps({
+                    "status": "success", 
+                    "has_content": True,
+                    "content": response["content"],
+                    "request_id": response["request_id"],
+                    "timestamp": response["timestamp"]
+                })
+                
+            except Empty:
+                # 没有新响应
+                return json.dumps({"status": "success", "has_content": False})
+                
+        except Exception as e:
+            logger.error(f"Error polling response: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
 
     def chat_page(self):
         """Serve the chat HTML page."""
@@ -176,22 +186,51 @@ class WebChannel(ChatChannel):
             return f.read()
 
     def startup(self):
-        logger.setLevel("WARN")
-        print("\nWeb Channel is running. Send POST requests to /message to send messages.")
+        logger.info("""[WebChannel] 当前channel为web，可修改 config.json 配置文件中的 channel_type 字段进行切换。全部可用类型为：
+        1. web: 网页
+        2. terminal: 终端
+        3. wechatmp: 个人公众号
+        4. wechatmp_service: 企业公众号
+        5. wechatcom_app: 企微自建应用
+        6. dingtalk: 钉钉
+        7. feishu: 飞书""")
+        logger.info("Web对话网页已运行, 请使用浏览器访问 http://localhost:9899/chat")
+        
+        # 确保静态文件目录存在
+        static_dir = os.path.join(os.path.dirname(__file__), 'static')
+        if not os.path.exists(static_dir):
+            os.makedirs(static_dir)
+            logger.info(f"Created static directory: {static_dir}")
         
         urls = (
-            '/sse/(.+)', 'SSEHandler',  # 修改路由以接收用户ID
+            '/', 'RootHandler',  # 添加根路径处理器
             '/message', 'MessageHandler',
-            '/chat', 'ChatHandler', 
+            '/poll', 'PollHandler',  # 添加轮询处理器
+            '/chat', 'ChatHandler',
+            '/assets/(.*)', 'AssetsHandler',  # 匹配 /assets/任何路径
         )
         port = conf().get("web_port", 9899)
         app = web.application(urls, globals(), autoreload=False)
-        web.httpserver.runsimple(app.wsgifunc(), ("0.0.0.0", port))
+        
+        # 禁用web.py的默认日志输出
+        import io
+        from contextlib import redirect_stdout
+        
+        # 配置web.py的日志级别为ERROR，只显示错误
+        logging.getLogger("web").setLevel(logging.ERROR)
+        
+        # 禁用web.httpserver的日志
+        logging.getLogger("web.httpserver").setLevel(logging.ERROR)
+        
+        # 临时重定向标准输出，捕获web.py的启动消息
+        with redirect_stdout(io.StringIO()):
+            web.httpserver.runsimple(app.wsgifunc(), ("0.0.0.0", port))
 
 
-class SSEHandler:
-    def GET(self, user_id):
-        return WebChannel().sse_handler(user_id)
+class RootHandler:
+    def GET(self):
+        # 重定向到/chat
+        raise web.seeother('/chat')
 
 
 class MessageHandler:
@@ -199,6 +238,54 @@ class MessageHandler:
         return WebChannel().post_message()
 
 
+class PollHandler:
+    def POST(self):
+        return WebChannel().poll_response()
+
+
 class ChatHandler:
     def GET(self):
-        return WebChannel().chat_page()
+        # 正常返回聊天页面
+        file_path = os.path.join(os.path.dirname(__file__), 'chat.html')
+        with open(file_path, 'r', encoding='utf-8') as f:
+            return f.read()
+
+
+class AssetsHandler:
+    def GET(self, file_path):  # 修改默认参数
+        try:
+            # 如果请求是/static/，需要处理
+            if file_path == '':
+                # 返回目录列表...
+                pass
+
+            # 获取当前文件的绝对路径
+            current_dir = os.path.dirname(os.path.abspath(__file__))
+            static_dir = os.path.join(current_dir, 'static')
+
+            full_path = os.path.normpath(os.path.join(static_dir, file_path))
+
+            # 安全检查：确保请求的文件在static目录内
+            if not os.path.abspath(full_path).startswith(os.path.abspath(static_dir)):
+                logger.error(f"Security check failed for path: {full_path}")
+                raise web.notfound()
+
+            if not os.path.exists(full_path) or not os.path.isfile(full_path):
+                logger.error(f"File not found: {full_path}")
+                raise web.notfound()
+
+            # 设置正确的Content-Type
+            content_type = mimetypes.guess_type(full_path)[0]
+            if content_type:
+                web.header('Content-Type', content_type)
+            else:
+                # 默认为二进制流
+                web.header('Content-Type', 'application/octet-stream')
+
+            # 读取并返回文件内容
+            with open(full_path, 'rb') as f:
+                return f.read()
+
+        except Exception as e:
+            logger.error(f"Error serving static file: {e}", exc_info=True)  # 添加更详细的错误信息
+            raise web.notfound()

channel/wechat/wcf_channel.py

@@ -0,0 +1,179 @@
+# encoding:utf-8
+
+"""
+wechat channel
+"""
+
+import io
+import json
+import os
+import threading
+import time
+from queue import Empty
+from typing import Any
+
+from bridge.context import *
+from bridge.reply import *
+from channel.chat_channel import ChatChannel
+from channel.wechat.wcf_message import WechatfMessage
+from common.log import logger
+from common.singleton import singleton
+from common.utils import *
+from config import conf, get_appdata_dir
+from wcferry import Wcf, WxMsg
+
+
+@singleton
+class WechatfChannel(ChatChannel):
+    NOT_SUPPORT_REPLYTYPE = []
+
+    def __init__(self):
+        super().__init__()
+        self.NOT_SUPPORT_REPLYTYPE = []
+        # 使用字典存储最近消息，用于去重
+        self.received_msgs = {}
+        # 初始化wcferry客户端
+        self.wcf = Wcf()
+        self.wxid = None  # 登录后会被设置为当前登录用户的wxid
+
+    def startup(self):
+        """
+        启动通道
+        """
+        try:
+            # wcferry会自动唤起微信并登录
+            self.wxid = self.wcf.get_self_wxid()
+            self.name = self.wcf.get_user_info().get("name")
+            logger.info(f"微信登录成功，当前用户ID: {self.wxid}, 用户名：{self.name}")
+            self.contact_cache = ContactCache(self.wcf)
+            self.contact_cache.update()
+            # 启动消息接收
+            self.wcf.enable_receiving_msg()
+            # 创建消息处理线程
+            t = threading.Thread(target=self._process_messages, name="WeChatThread", daemon=True)
+            t.start()
+
+
+        except Exception as e:
+            logger.error(f"微信通道启动失败: {e}")
+            raise e
+
+    def _process_messages(self):
+        """
+        处理消息队列
+        """
+        while True:
+            try:
+                msg = self.wcf.get_msg()
+                if msg:
+                    self._handle_message(msg)
+            except Empty:
+                continue
+            except Exception as e:
+                logger.error(f"处理消息失败: {e}")
+                continue
+
+    def _handle_message(self, msg: WxMsg):
+        """
+        处理单条消息
+        """
+        try:
+            # 构造消息对象
+            cmsg = WechatfMessage(self, msg)
+            # 消息去重
+            if cmsg.msg_id in self.received_msgs:
+                return
+            self.received_msgs[cmsg.msg_id] = time.time()
+            # 清理过期消息ID
+            self._clean_expired_msgs()
+
+            logger.debug(f"收到消息: {msg}")
+            context = self._compose_context(cmsg.ctype, cmsg.content,
+                                            isgroup=cmsg.is_group,
+                                            msg=cmsg)
+            if context:
+                self.produce(context)
+        except Exception as e:
+            logger.error(f"处理消息失败: {e}")
+
+    def _clean_expired_msgs(self, expire_time: float = 60):
+        """
+        清理过期的消息ID
+        """
+        now = time.time()
+        for msg_id in list(self.received_msgs.keys()):
+            if now - self.received_msgs[msg_id] > expire_time:
+                del self.received_msgs[msg_id]
+
+    def send(self, reply: Reply, context: Context):
+        """
+        发送消息
+        """
+        receiver = context["receiver"]
+        if not receiver:
+            logger.error("receiver is empty")
+            return
+
+        try:
+            if reply.type == ReplyType.TEXT:
+                # 处理@信息
+                at_list = []
+                if context.get("isgroup"):
+                    if context["msg"].actual_user_id:
+                        at_list = [context["msg"].actual_user_id]
+                at_str = ",".join(at_list) if at_list else ""
+                self.wcf.send_text(reply.content, receiver, at_str)
+
+            elif reply.type == ReplyType.ERROR or reply.type == ReplyType.INFO:
+                self.wcf.send_text(reply.content, receiver)
+            else:
+                logger.error(f"暂不支持的消息类型: {reply.type}")
+
+        except Exception as e:
+            logger.error(f"发送消息失败: {e}")
+
+    def close(self):
+        """
+        关闭通道
+        """
+        try:
+            self.wcf.cleanup()
+        except Exception as e:
+            logger.error(f"关闭通道失败: {e}")
+
+
+class ContactCache:
+    def __init__(self, wcf):
+        """
+        wcf: 一个 wcfferry.client.Wcf 实例
+        """
+        self.wcf = wcf
+        self._contact_map = {}  # 形如 {wxid: {完整联系人信息}}
+
+    def update(self):
+        """
+        更新缓存：调用 get_contacts()，
+        再把 wcf.contacts 构建成 {wxid: {完整信息}} 的字典
+        """
+        self.wcf.get_contacts()
+        self._contact_map.clear()
+        for item in self.wcf.contacts:
+            wxid = item.get('wxid')
+            if wxid:  # 确保有 wxid 字段
+                self._contact_map[wxid] = item
+
+    def get_contact(self, wxid: str) -> dict:
+        """
+        返回该 wxid 对应的完整联系人 dict，
+        如果没找到就返回 None
+        """
+        return self._contact_map.get(wxid)
+
+    def get_name_by_wxid(self, wxid: str) -> str:
+        """
+        通过wxid，获取成员/群名称
+        """
+        contact = self.get_contact(wxid)
+        if contact:
+            return contact.get('name', '')
+        return ''

channel/wechat/wcf_message.py

@@ -0,0 +1,58 @@
+# encoding:utf-8
+
+"""
+wechat channel message
+"""
+
+from bridge.context import ContextType
+from channel.chat_message import ChatMessage
+from common.log import logger
+from wcferry import WxMsg
+
+
+class WechatfMessage(ChatMessage):
+    """
+    微信消息封装类
+    """
+
+    def __init__(self, channel, wcf_msg: WxMsg, is_group=False):
+        """
+        初始化消息对象
+        :param wcf_msg: wcferry消息对象
+        :param is_group: 是否是群消息
+        """
+        super().__init__(wcf_msg)
+        self.msg_id = wcf_msg.id
+        self.create_time = wcf_msg.ts  # 使用消息时间戳
+        self.is_group = is_group or wcf_msg._is_group
+        self.wxid = channel.wxid
+        self.name = channel.name
+
+        # 解析消息类型
+        if wcf_msg.is_text():
+            self.ctype = ContextType.TEXT
+            self.content = wcf_msg.content
+        else:
+            raise NotImplementedError(f"Unsupported message type: {wcf_msg.type}")
+
+        # 设置发送者和接收者信息
+        self.from_user_id = self.wxid if wcf_msg.sender == self.wxid else wcf_msg.sender
+        self.from_user_nickname = self.name if wcf_msg.sender == self.wxid else channel.contact_cache.get_name_by_wxid(wcf_msg.sender)
+        self.to_user_id = self.wxid
+        self.to_user_nickname = self.name
+        self.other_user_id = wcf_msg.sender
+        self.other_user_nickname = channel.contact_cache.get_name_by_wxid(wcf_msg.sender)
+
+        # 群消息特殊处理
+        if self.is_group:
+            self.other_user_id = wcf_msg.roomid
+            self.other_user_nickname = channel.contact_cache.get_name_by_wxid(wcf_msg.roomid)
+            self.actual_user_id = wcf_msg.sender
+            self.actual_user_nickname = channel.wcf.get_alias_in_chatroom(wcf_msg.sender, wcf_msg.roomid)
+            if not self.actual_user_nickname:  # 群聊获取不到企微号成员昵称，这里尝试从联系人缓存去获取
+                self.actual_user_nickname = channel.contact_cache.get_name_by_wxid(wcf_msg.sender)
+            self.room_id = wcf_msg.roomid
+            self.is_at = wcf_msg.is_at(self.wxid)  # 是否被@当前登录用户
+
+        # 判断是否是自己发送的消息
+        self.my_msg = wcf_msg.from_self()

channel/wechat/wechat_channel.py

@@ -117,23 +117,35 @@ class WechatChannel(ChatChannel):
 
     def startup(self):
         try:
-            itchat.instance.receivingRetryCount = 600  # 修改断线超时时间
-            # login by scan QRCode
-            hotReload = conf().get("hot_reload", False)
-            status_path = os.path.join(get_appdata_dir(), "itchat.pkl")
-            itchat.auto_login(
-                enableCmdQR=2,
-                hotReload=hotReload,
-                statusStorageDir=status_path,
-                qrCallback=qrCallback,
-                exitCallback=self.exitCallback,
-                loginCallback=self.loginCallback
-            )
-            self.user_id = itchat.instance.storageClass.userName
-            self.name = itchat.instance.storageClass.nickName
-            logger.info("Wechat login success, user_id: {}, nickname: {}".format(self.user_id, self.name))
-            # start message listener
-            itchat.run()
+            time.sleep(3)
+            logger.error("""[WechatChannel] 当前channel暂不可用，目前支持的channel有:
+                1. terminal: 终端
+                2. wechatmp: 个人公众号
+                3. wechatmp_service: 企业公众号
+                4. wechatcom_app: 企微自建应用
+                5. dingtalk: 钉钉
+                6. feishu: 飞书
+                7. web: 网页
+                8. wcf: wechat (需Windows环境，参考 https://github.com/zhayujie/chatgpt-on-wechat/pull/2562 )
+            可修改 config.json 配置文件的 channel_type 字段进行切换""")
+
+            # itchat.instance.receivingRetryCount = 600  # 修改断线超时时间
+            # # login by scan QRCode
+            # hotReload = conf().get("hot_reload", False)
+            # status_path = os.path.join(get_appdata_dir(), "itchat.pkl")
+            # itchat.auto_login(
+            #     enableCmdQR=2,
+            #     hotReload=hotReload,
+            #     statusStorageDir=status_path,
+            #     qrCallback=qrCallback,
+            #     exitCallback=self.exitCallback,
+            #     loginCallback=self.loginCallback
+            # )
+            # self.user_id = itchat.instance.storageClass.userName
+            # self.name = itchat.instance.storageClass.nickName
+            # logger.info("Wechat login success, user_id: {}, nickname: {}".format(self.user_id, self.name))
+            # # start message listener
+            # itchat.run()
         except Exception as e:
             logger.exception(e)
 

channel/wechatcom/wechatcomapp_client.py

@@ -1,21 +1,43 @@
+# wechatcomapp_client.py
 import threading
 import time
-
 from wechatpy.enterprise import WeChatClient
 
-
 class WechatComAppClient(WeChatClient):
     def __init__(self, corp_id, secret, access_token=None, session=None, timeout=None, auto_retry=True):
         super(WechatComAppClient, self).__init__(corp_id, secret, access_token, session, timeout, auto_retry)
         self.fetch_access_token_lock = threading.Lock()
+        self._active_refresh()
+        
+    def _active_refresh(self):
+        """启动主动刷新的后台线程"""
+        def refresh_loop():
+            while True:
+                now = time.time()
+                expires_at = self.session.get(f"{self.corp_id}_expires_at", 0)
+                
+                # 提前10分钟刷新(600秒)
+                if expires_at - now < 600:
+                    with self.fetch_access_token_lock:
+                        # 双重检查避免重复刷新
+                        if self.session.get(f"{self.corp_id}_expires_at", 0) - time.time() < 600:
+                            super(WechatComAppClient, self).fetch_access_token()
+                # 每次检查间隔60秒
+                time.sleep(60)
+                
+        # 启动守护线程
+        refresh_thread = threading.Thread(
+            target=refresh_loop,
+            daemon=True,
+            name="wechatcom_token_refresh_thread"
+        )
+        refresh_thread.start()
 
-    def fetch_access_token(self):  # 重载父类方法，加锁避免多线程重复获取access_token
+    def fetch_access_token(self):
         with self.fetch_access_token_lock:
             access_token = self.session.get(self.access_token_key)
-            if access_token:
-                if not self.expires_at:
-                    return access_token
-                timestamp = time.time()
-                if self.expires_at - timestamp > 60:
-                    return access_token
-            return super().fetch_access_token()
+            expires_at = self.session.get(f"{self.corp_id}_expires_at", 0)
+            
+            if access_token and expires_at > time.time() + 60:
+                return access_token
+            return super().fetch_access_token()

common/const.py

@@ -15,7 +15,7 @@ GEMINI = "gemini"  # gemini-1.0-pro
 ZHIPU_AI = "glm-4"
 MOONSHOT = "moonshot"
 MiniMax = "minimax"
-
+MODELSCOPE = "modelscope"
 
 # model
 CLAUDE3 = "claude-3-opus-20240229"
@@ -37,6 +37,9 @@ GPT_4o_MINI = "gpt-4o-mini"
 GPT4_32k = "gpt-4-32k"
 GPT4_06_13 = "gpt-4-0613"
 GPT4_32k_06_13 = "gpt-4-32k-0613"
+GPT_41 = "gpt-4.1"
+GPT_41_MINI = "gpt-4.1-mini"
+GPT_41_NANO = "gpt-4.1-nano"
 
 O1 = "o1-preview"
 O1_MINI = "o1-mini"
@@ -74,28 +77,42 @@ GLM_4_AIRX = "glm-4-airx"
 
 CLAUDE_3_OPUS = "claude-3-opus-latest"
 CLAUDE_3_OPUS_0229 = "claude-3-opus-20240229"
-
 CLAUDE_35_SONNET = "claude-3-5-sonnet-latest"  # 带 latest 标签的模型名称，会不断更新指向最新发布的模型
 CLAUDE_35_SONNET_1022 = "claude-3-5-sonnet-20241022"  # 带具体日期的模型名称，会固定为该日期发布的模型
 CLAUDE_35_SONNET_0620 = "claude-3-5-sonnet-20240620"
 CLAUDE_3_SONNET = "claude-3-sonnet-20240229"
-
 CLAUDE_3_HAIKU = "claude-3-haiku-20240307"
+CLAUDE_4_SONNET = "claude-sonnet-4-0"
+CLAUDE_4_OPUS = "claude-opus-4-0"
+
+DEEPSEEK_CHAT = "deepseek-chat"  # DeepSeek-V3对话模型
+DEEPSEEK_REASONER = "deepseek-reasoner"  # DeepSeek-R1模型
+
+GITEE_AI_MODEL_LIST = ["Yi-34B-Chat", "InternVL2-8B", "deepseek-coder-33B-instruct", "InternVL2.5-26B", "Qwen2-VL-72B", "Qwen2.5-32B-Instruct", "glm-4-9b-chat", "codegeex4-all-9b", "Qwen2.5-Coder-32B-Instruct", "Qwen2.5-72B-Instruct", "Qwen2.5-7B-Instruct", "Qwen2-72B-Instruct", "Qwen2-7B-Instruct", "code-raccoon-v1", "Qwen2.5-14B-Instruct"]
+
+MODELSCOPE_MODEL_LIST = ["LLM-Research/c4ai-command-r-plus-08-2024","mistralai/Mistral-Small-Instruct-2409","mistralai/Ministral-8B-Instruct-2410","mistralai/Mistral-Large-Instruct-2407",
+                          "Qwen/Qwen2.5-Coder-32B-Instruct","Qwen/Qwen2.5-Coder-14B-Instruct","Qwen/Qwen2.5-Coder-7B-Instruct","Qwen/Qwen2.5-72B-Instruct","Qwen/Qwen2.5-32B-Instruct","Qwen/Qwen2.5-14B-Instruct","Qwen/Qwen2.5-7B-Instruct","Qwen/QwQ-32B-Preview",
+                          "LLM-Research/Llama-3.3-70B-Instruct","opencompass/CompassJudger-1-32B-Instruct","Qwen/QVQ-72B-Preview","LLM-Research/Meta-Llama-3.1-405B-Instruct","LLM-Research/Meta-Llama-3.1-8B-Instruct","Qwen/Qwen2-VL-7B-Instruct","LLM-Research/Meta-Llama-3.1-70B-Instruct",
+                          "Qwen/Qwen2.5-14B-Instruct-1M","Qwen/Qwen2.5-7B-Instruct-1M","Qwen/Qwen2.5-VL-3B-Instruct","Qwen/Qwen2.5-VL-7B-Instruct","Qwen/Qwen2.5-VL-72B-Instruct","deepseek-ai/DeepSeek-R1-Distill-Llama-70B","deepseek-ai/DeepSeek-R1-Distill-Llama-8B","deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
+                          "deepseek-ai/DeepSeek-R1-Distill-Qwen-14B","deepseek-ai/DeepSeek-R1-Distill-Qwen-7B","deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B","deepseek-ai/DeepSeek-R1","deepseek-ai/DeepSeek-V3","Qwen/QwQ-32B"]
 
 MODEL_LIST = [
               GPT35, GPT35_0125, GPT35_1106, "gpt-3.5-turbo-16k",
-              O1, O1_MINI, GPT_4o, GPT_4O_0806, GPT_4o_MINI, GPT4_TURBO, GPT4_TURBO_PREVIEW, GPT4_TURBO_01_25, GPT4_TURBO_11_06, GPT4, GPT4_32k, GPT4_06_13, GPT4_32k_06_13,
+              GPT_41, GPT_41_MINI, GPT_41_NANO, O1, O1_MINI, GPT_4o, GPT_4O_0806, GPT_4o_MINI, GPT4_TURBO, GPT4_TURBO_PREVIEW, GPT4_TURBO_01_25, GPT4_TURBO_11_06, GPT4, GPT4_32k, GPT4_06_13, GPT4_32k_06_13,
               WEN_XIN, WEN_XIN_4,
               XUNFEI,
               ZHIPU_AI, GLM_4, GLM_4_PLUS, GLM_4_flash, GLM_4_LONG, GLM_4_ALLTOOLS, GLM_4_0520, GLM_4_AIR, GLM_4_AIRX,
               MOONSHOT, MiniMax,
               GEMINI, GEMINI_PRO, GEMINI_15_flash, GEMINI_15_PRO,GEMINI_20_flash_exp,
-              CLAUDE_3_OPUS, CLAUDE_3_OPUS_0229, CLAUDE_35_SONNET, CLAUDE_35_SONNET_1022, CLAUDE_35_SONNET_0620, CLAUDE_3_SONNET, CLAUDE_3_HAIKU, "claude", "claude-3-haiku", "claude-3-sonnet", "claude-3-opus", "claude-3.5-sonnet",
+              CLAUDE_4_OPUS, CLAUDE_4_SONNET, CLAUDE_3_OPUS, CLAUDE_3_OPUS_0229, CLAUDE_35_SONNET, CLAUDE_35_SONNET_1022, CLAUDE_35_SONNET_0620, CLAUDE_3_SONNET, CLAUDE_3_HAIKU, "claude", "claude-3-haiku", "claude-3-sonnet", "claude-3-opus", "claude-3.5-sonnet",
               "moonshot-v1-8k", "moonshot-v1-32k", "moonshot-v1-128k",
               QWEN, QWEN_TURBO, QWEN_PLUS, QWEN_MAX,
-              LINKAI_35, LINKAI_4_TURBO, LINKAI_4o
+              LINKAI_35, LINKAI_4_TURBO, LINKAI_4o,
+              DEEPSEEK_CHAT, DEEPSEEK_REASONER,
+              MODELSCOPE
             ]
 
+MODEL_LIST = MODEL_LIST + GITEE_AI_MODEL_LIST + MODELSCOPE_MODEL_LIST
 # channel
 FEISHU = "feishu"
 DINGTALK = "dingtalk"

config-template.json

@@ -1,5 +1,5 @@
 {
-  "channel_type": "wx",
+  "channel_type": "web",
   "model": "",
   "open_ai_api_key": "YOUR API KEY",
   "claude_api_key": "YOUR API KEY",

config.py

@@ -171,6 +171,9 @@ available_setting = {
     "zhipu_ai_api_base": "https://open.bigmodel.cn/api/paas/v4",
     "moonshot_api_key": "",
     "moonshot_base_url": "https://api.moonshot.cn/v1/chat/completions",
+    #魔搭社区 平台配置
+    "modelscope_api_key": "",
+    "modelscope_base_url": "https://api-inference.modelscope.cn/v1/chat/completions",
     # LinkAI平台配置
     "use_linkai": False,
     "linkai_api_key": "",

plugins/agent/README.md

@@ -0,0 +1,66 @@
+# Agent插件
+
+## 插件说明
+
+基于 [AgentMesh](https://github.com/MinimalFuture/AgentMesh) 多智能体框架实现的Agent插件，可以让机器人快速获得Agent能力，通过自然语言对话来访问 **终端、浏览器、文件系统、搜索引擎** 等各类工具。
+同时还支持通过 **多智能体协作** 来完成复杂任务，例如多智能体任务分发、多智能体问题讨论、协同处理等。
+
+AgentMesh项目地址：https://github.com/MinimalFuture/AgentMesh
+
+## 安装
+
+1. 确保已安装依赖：
+
+```bash
+pip install agentmesh-sdk>=0.1.2
+```
+
+2. 如需使用浏览器工具，还需安装：
+
+```bash
+pip install browser-use>=0.1.40
+playwright install
+```
+
+## 配置
+
+插件配置文件是 `plugins/agent`目录下的 `config.yaml`，包含智能体团队的配置以及工具的配置，可以从模板文件 `config-template.yaml`中复制：
+
+```bash
+cp config-template.yaml config.yaml
+```
+
+说明：
+
+ - `team`配置是默认选中的 agent team
+ - `teams` 下是Agent团队配置，团队的model默认为`gpt-4.1-mini`，可根据需要进行修改，模型对应的 `api_key` 需要在项目根目录的 `config.json` 全局配置中进行配置。例如openai模型需要配置 `open_ai_api_key`
+ - 支持为 `agents` 下面的每个agent添加model字段来设置不同的模型
+
+
+## 使用方法
+
+在对机器人发送的消息中使用 `$agent` 前缀来触发插件，支持以下命令：
+
+- `$agent [task]`: 使用默认团队执行任务 (默认团队可通 config.yaml 中的team配置修改)
+- `$agent teams`: 列出可用的团队
+- `$agent use [team_name] [task]`: 使用指定的团队执行任务
+
+
+### 示例
+
+```bash
+$agent 帮我查看当前目录下有哪些文件夹
+$agent teams
+$agent use software_team 帮我写一个产品预约体验的表单页面
+```
+
+## 工具支持
+
+目前支持多种内置工具，包括但不限于：
+
+- `calculator`: 数学计算工具
+- `current_time`: 获取当前时间
+- `browser`: 浏览器操作工具，注意需安装`browser-use`依赖
+- `google_search`: 搜索引擎，注意需在`config.yaml`中配置 `api_key`
+- `file_save`: 文件保存工具，开启后智能体输出的内容将保存在 `workspace` 目录下
+- `terminal`: 终端命令执行工具

plugins/agent/__init__.py

@@ -0,0 +1,3 @@
+from .agent import AgentPlugin
+
+__all__ = ["AgentPlugin"]

plugins/agent/agent.py

@@ -0,0 +1,282 @@
+import os
+import yaml
+from typing import Dict, List, Optional
+
+from agentmesh import AgentTeam, Agent, LLMModel
+from agentmesh.models import ClaudeModel
+from agentmesh.tools import ToolManager
+from config import conf
+
+import plugins
+from plugins import Plugin, Event, EventContext, EventAction
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+
+
+@plugins.register(
+    name="agent",
+    desc="Use AgentMesh framework to process tasks with multi-agent teams",
+    version="0.1.0",
+    author="Saboteur7",
+    desire_priority=1,
+)
+class AgentPlugin(Plugin):
+    """Plugin for integrating AgentMesh framework."""
+    
+    def __init__(self):
+        super().__init__()
+        self.handlers[Event.ON_HANDLE_CONTEXT] = self.on_handle_context
+        self.name = "agent"
+        self.description = "Use AgentMesh framework to process tasks with multi-agent teams"
+        self.config = self._load_config()
+        self.tool_manager = ToolManager()
+        self.tool_manager.load_tools(config_dict=self.config.get("tools"))
+        logger.info("[agent] inited")
+    
+    def _load_config(self) -> Dict:
+        """Load configuration from config.yaml file."""
+        config_path = os.path.join(self.path, "config.yaml")
+        if not os.path.exists(config_path):
+            logger.warning(f"Config file not found at {config_path}")
+            return {}
+            
+        with open(config_path, 'r', encoding='utf-8') as f:
+            return yaml.safe_load(f)
+    
+    def get_help_text(self, verbose=False, **kwargs):
+        """Return help message for the agent plugin."""
+        help_text = "通过AgentMesh实现对终端、浏览器、文件系统、搜索引擎等工具的执行，并支持多智能体协作。"
+        trigger_prefix = conf().get("plugin_trigger_prefix", "$")
+        
+        if not verbose:
+            return help_text
+            
+        teams = self.get_available_teams()
+        teams_str = ", ".join(teams) if teams else "未配置任何团队"
+        
+        help_text += "\n\n使用说明：\n"
+        help_text += f"{trigger_prefix}agent [task] - 使用默认团队执行任务\n"
+        help_text += f"{trigger_prefix}agent teams - 列出可用的团队\n"
+        help_text += f"{trigger_prefix}agent use [team_name] [task] - 使用特定团队执行任务\n\n"
+        help_text += f"可用团队: \n{teams_str}\n\n"
+        help_text += f"示例:\n"
+        help_text += f"{trigger_prefix}agent 帮我查看当前文件夹路径\n"
+        help_text += f"{trigger_prefix}agent use software_team 帮我写一个产品预约体验的表单页面"
+        return help_text
+    
+    def get_available_teams(self) -> List[str]:
+        """Get list of available teams from configuration."""
+        teams_config = self.config.get("teams", {})
+        return list(teams_config.keys())
+
+
+    def create_team_from_config(self, team_name: str) -> Optional[AgentTeam]:
+        """Create a team from configuration."""
+        # Get teams configuration
+        teams_config = self.config.get("teams", {})
+
+        # Check if the specified team exists
+        if team_name not in teams_config:
+            logger.error(f"Team '{team_name}' not found in configuration.")
+            available_teams = list(teams_config.keys())
+            logger.info(f"Available teams: {', '.join(available_teams)}")
+            return None
+
+        # Get team configuration
+        team_config = teams_config[team_name]
+
+        # Get team's model
+        team_model_name = team_config.get("model", "gpt-4.1-mini")
+        team_model = self.create_llm_model(team_model_name)
+
+        # Get team's max_steps (default to 20 if not specified)
+        team_max_steps = team_config.get("max_steps", 20)
+
+        # Create team with the model
+        team = AgentTeam(
+            name=team_name,
+            description=team_config.get("description", ""),
+            rule=team_config.get("rule", ""),
+            model=team_model,
+            max_steps=team_max_steps
+        )
+
+        # Create and add agents to the team
+        agents_config = team_config.get("agents", [])
+        for agent_config in agents_config:
+            # Check if agent has a specific model
+            if agent_config.get("model"):
+                agent_model = self.create_llm_model(agent_config.get("model"))
+            else:
+                agent_model = team_model
+
+            # Get agent's max_steps
+            agent_max_steps = agent_config.get("max_steps")
+
+            agent = Agent(
+                name=agent_config.get("name", ""),
+                system_prompt=agent_config.get("system_prompt", ""),
+                model=agent_model,  # Use agent's model if specified, otherwise will use team's model
+                description=agent_config.get("description", ""),
+                max_steps=agent_max_steps
+            )
+
+            # Add tools to the agent if specified
+            tool_names = agent_config.get("tools", [])
+            for tool_name in tool_names:
+                tool = self.tool_manager.create_tool(tool_name)
+                if tool:
+                    agent.add_tool(tool)
+                else:
+                    if tool_name == "browser":
+                        logger.warning(
+                            "Tool 'Browser' loaded failed, "
+                            "please install the required dependency with: \n"
+                            "'pip install browser-use>=0.1.40' or 'pip install agentmesh-sdk[full]'\n"
+                        )
+                    else:
+                        logger.warning(f"Tool '{tool_name}' not found for agent '{agent.name}'\n")
+
+            # Add agent to team
+            team.add(agent)
+
+        return team
+    
+    def on_handle_context(self, e_context: EventContext):
+        """Handle the message context."""
+        if e_context['context'].type != ContextType.TEXT:
+            return
+        content = e_context['context'].content
+        trigger_prefix = conf().get("plugin_trigger_prefix", "$")
+        
+        if not content.startswith(f"{trigger_prefix}agent "):
+            e_context.action = EventAction.CONTINUE
+            return
+
+        if not self.config:
+            reply = Reply()
+            reply.type = ReplyType.ERROR
+            reply.content = "未找到插件配置，请在 plugins/agent 目录下创建 config.yaml 配置文件，可根据 config-template.yml 模板文件复制"
+            e_context['reply'] = reply
+            e_context.action = EventAction.BREAK_PASS
+            return
+
+        # Extract the actual task
+        task = content[len(f"{trigger_prefix}agent "):].strip()
+        
+        # If task is empty, return help message
+        if not task:
+            reply = Reply()
+            reply.type = ReplyType.TEXT
+            reply.content = self.get_help_text(verbose=True)
+            e_context['reply'] = reply
+            e_context.action = EventAction.BREAK_PASS
+            return
+            
+        # Check if task is asking for available teams
+        if task.lower() in ["teams", "list teams", "show teams"]:
+            teams = self.get_available_teams()
+            reply = Reply()
+            reply.type = ReplyType.TEXT
+            
+            if not teams:
+                reply.content = "未配置任何团队。请检查 config.yaml 文件。"
+            else:
+                reply.content = f"可用团队: {', '.join(teams)}"
+                
+            e_context['reply'] = reply
+            e_context.action = EventAction.BREAK_PASS
+            return
+        
+        # Check if task specifies a team
+        team_name = None
+        if task.startswith("use "):
+            parts = task[4:].split(" ", 1)
+            if len(parts) > 0:
+                team_name = parts[0]
+                if len(parts) > 1:
+                    task = parts[1].strip()
+                else:
+                    reply = Reply()
+                    reply.type = ReplyType.TEXT
+                    reply.content = f"已选择团队 '{team_name}'。请输入您想执行的任务。"
+                    e_context['reply'] = reply
+                    e_context.action = EventAction.BREAK_PASS
+                    return
+        if not team_name:
+            team_name = self.config.get("team")
+
+        # If no team specified, use default or first available
+        if not team_name:
+            teams = self.configself.get_available_teams()
+            if not teams:
+                reply = Reply()
+                reply.type = ReplyType.TEXT
+                reply.content = "未配置任何团队。请检查 config.yaml 文件。"
+                e_context['reply'] = reply
+                e_context.action = EventAction.BREAK_PASS
+                return
+            team_name = teams[0]
+            
+        # Create team
+        team = self.create_team_from_config(team_name)
+        if not team:
+            reply = Reply()
+            reply.type = ReplyType.TEXT
+            reply.content = f"创建团队 '{team_name}' 失败。请检查配置。"
+            e_context['reply'] = reply
+            e_context.action = EventAction.BREAK_PASS
+            return
+        
+        # Run the task
+        try:
+            logger.info(f"[agent] Running task '{task}' with team '{team_name}', team_model={team.model.model}")
+            result = team.run_async(task=task)
+            for agent_result in result:
+                res_text = f"🤖 {agent_result.get('agent_name')}\n\n{agent_result.get('final_answer')}"
+                _send_text(e_context, content=res_text)
+            
+            reply = Reply()
+            reply.type = ReplyType.TEXT
+            reply.content = ""
+            e_context['reply'] = reply
+            e_context.action = EventAction.BREAK_PASS
+            
+        except Exception as e:
+            logger.exception(f"Error running task with team '{team_name}'")
+            
+            reply = Reply()
+            reply.type = ReplyType.ERROR
+            reply.content = f"执行任务时出错: {str(e)}"
+            e_context['reply'] = reply
+            e_context.action = EventAction.BREAK_PASS
+        return
+
+    def create_llm_model(self, model_name) -> LLMModel:
+        if conf().get("use_linkai"):
+            api_base = "https://api.link-ai.tech/v1"
+            api_key = conf().get("linkai_api_key")
+        elif model_name.startswith(("gpt", "text-davinci", "o1", "o3")):
+            api_base = conf().get("open_ai_api_base") or "https://api.openai.com/v1"
+            api_key = conf().get("open_ai_api_key")
+        elif model_name.startswith("claude"):
+            return ClaudeModel(model=model_name, api_key=conf().get("claude_api_key"))
+        elif model_name.startswith("moonshot"):
+            api_base = "https://api.moonshot.cn/v1"
+            api_key = conf().get("moonshot_api_key")
+        elif model_name.startswith("qwen"):
+            api_base = "https://dashscope.aliyuncs.com/compatible-mode/v1"
+            api_key = conf().get("dashscope_api_key")
+        else:
+            api_base = conf().get("open_ai_api_base") or "https://api.openai.com/v1"
+            api_key = conf().get("open_ai_api_key")
+
+        llm_model = LLMModel(model=model_name, api_key=api_key, api_base=api_base)
+        return llm_model
+
+
+def _send_text(e_context: EventContext, content: str):
+    reply = Reply(ReplyType.TEXT, content)
+    channel = e_context["channel"]
+    channel.send(reply, e_context["context"])

plugins/agent/config-template.yaml

@@ -0,0 +1,52 @@
+# 默认选中的Agent Team名称
+team: general_team
+
+tools:
+  google_search:
+    # get your apikey from https://serper.dev/
+    api_key: "YOUR API KEY"
+
+# Agent Team 配置
+teams:
+  # 通用智能体团队
+  general_team:
+    model: "gpt-4.1-mini"        # 团队使用的模型
+    description: "A versatile research and information agent team"
+    max_steps: 5
+    agents:
+      - name: "通用智能助手"
+        description: "Universal assistant specializing in research, information synthesis, and task execution"
+        system_prompt: "You are a versatile assistant who answers questions and completes tasks using available tools. Reply in a clearly structured, attractive and easy to read format."
+        # Agent 支持使用的工具
+        tools:
+          - time
+          - calculator
+          - google_search
+          - browser
+          - terminal
+
+  # 软件开发智能体团队
+  software_team:
+    model: "gpt-4.1-mini"
+    description: "A software development team with product manager, developer and tester."
+    rule: "A normal R&D process should be that Product Manager writes PRD, Developer writes code based on PRD, and Finally, Tester performs testing."
+    max_steps: 10
+    agents:
+      - name: "Product-Manager"
+        description: "Responsible for product requirements and documentation"
+        system_prompt: "You are an experienced product manager who creates concise PRDs, focusing on user needs and feature specifications. You always format your responses in Markdown."
+        tools:
+          - time
+          - file_save
+      - name: "Developer"
+        description: "Implements code based on PRD"
+        system_prompt: "You are a skilled developer. When developing web application, you creates single-page website based on user needs, you deliver HTML files with embedded JavaScript and CSS that are visually appealing, responsive, and user-friendly, featuring a grand layout and beautiful background. The HTML, CSS, and JavaScript code should be well-structured and effectively organized."
+        tools:
+          - file_save
+      - name: "Tester"
+        description: "Tests code and verifies functionality"
+        system_prompt: "You are a tester who validates code against requirements. For HTML applications, use browser tools to test functionality. For Python or other client-side applications, use the terminal tool to run and test. You only need to test a few core cases."
+        tools:
+          - file_save
+          - browser
+          - terminal

plugins/godcmd/godcmd.py

@@ -155,7 +155,7 @@ def get_help_text(isadmin, isgroup):
     for plugin in plugins:
         if plugins[plugin].enabled and not plugins[plugin].hidden:
             namecn = plugins[plugin].namecn
-            help_text += "\n%s:" % namecn
+            help_text += "\n%s: " % namecn
             help_text += PluginManager().instances[plugin].get_help_text(verbose=False).strip()
 
     if ADMIN_COMMANDS and isadmin:
@@ -339,7 +339,8 @@ class Godcmd(Plugin):
                             ok, result = True, "配置已重载"
                         elif cmd == "resetall":
                             if bottype in [const.OPEN_AI, const.CHATGPT, const.CHATGPTONAZURE, const.LINKAI,
-                                           const.BAIDU, const.XUNFEI, const.QWEN, const.GEMINI, const.ZHIPU_AI, const.MOONSHOT]:
+                                           const.BAIDU, const.XUNFEI, const.QWEN, const.GEMINI, const.ZHIPU_AI, const.MOONSHOT,
+                                           const.MODELSCOPE]:
                                 channel.cancel_all_session()
                                 bot.sessions.clear_all_session()
                                 ok, result = True, "重置所有会话成功"

plugins/role/role.py

@@ -99,7 +99,7 @@ class Role(Plugin):
         if e_context["context"].type != ContextType.TEXT:
             return
         btype = Bridge().get_bot_type("chat")
-        if btype not in [const.OPEN_AI, const.CHATGPT, const.CHATGPTONAZURE, const.QWEN_DASHSCOPE, const.XUNFEI, const.BAIDU, const.ZHIPU_AI, const.MOONSHOT, const.MiniMax, const.LINKAI]:
+        if btype not in [const.OPEN_AI, const.CHATGPT, const.CHATGPTONAZURE, const.QWEN_DASHSCOPE, const.XUNFEI, const.BAIDU, const.ZHIPU_AI, const.MOONSHOT, const.MiniMax, const.LINKAI,const.MODELSCOPE]:
             logger.debug(f'不支持的bot: {btype}')
             return
         bot = Bridge().get_bot("chat")

requirements-optional.txt

@@ -44,3 +44,6 @@ zhipuai>=2.0.1
 
 # tongyi qwen new sdk
 dashscope
+
+# tencentcloud sdk
+tencentcloud-sdk-python>=3.0.0

requirements.txt

@@ -8,3 +8,4 @@ Pillow
 pre-commit
 web.py
 linkai>=0.0.6.0
+agentmesh-sdk>=0.1.3

simple_login_form_test.html

@@ -0,0 +1,278 @@
+<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+<meta charset="UTF-8" />
+<meta name="viewport" content="width=device-width, initial-scale=1" />
+<title>登录</title>
+<style>
+  /* Reset and base */
+  * {
+    box-sizing: border-box;
+  }
+  body, html {
+    margin: 0; padding: 0; height: 100%;
+    font-family: "Segoe UI", Tahoma, Geneva, Verdana, sans-serif;
+    background: linear-gradient(135deg, #667eea, #764ba2);
+    display: flex;
+    justify-content: center;
+    align-items: center;
+  }
+  .login-container {
+    background: rgba(255, 255, 255, 0.95);
+    padding: 2.5rem 3rem;
+    border-radius: 12px;
+    box-shadow: 0 8px 24px rgba(0,0,0,0.15);
+    width: 100%;
+    max-width: 400px;
+  }
+  h2 {
+    margin-bottom: 1.5rem;
+    color: #333;
+    text-align: center;
+  }
+  form {
+    display: flex;
+    flex-direction: column;
+  }
+  label {
+    font-weight: 600;
+    margin-bottom: 0.4rem;
+    color: #444;
+  }
+  input[type="text"],
+  input[type="email"],
+  input[type="password"] {
+    padding: 0.6rem 0.8rem;
+    font-size: 1rem;
+    border: 1.8px solid #ccc;
+    border-radius: 6px;
+    transition: border-color 0.3s ease;
+    outline-offset: 2px;
+  }
+  input[type="text"]:focus,
+  input[type="email"]:focus,
+  input[type="password"]:focus {
+    border-color: #667eea;
+  }
+  .password-wrapper {
+    position: relative;
+    display: flex;
+    align-items: center;
+  }
+  .toggle-password {
+    position: absolute;
+    right: 0.8rem;
+    background: none;
+    border: none;
+    cursor: pointer;
+    font-size: 1rem;
+    color: #667eea;
+    user-select: none;
+  }
+  .login-button {
+    margin-top: 1.5rem;
+    padding: 0.75rem;
+    font-size: 1.1rem;
+    font-weight: 700;
+    background-color: #667eea;
+    color: white;
+    border: none;
+    border-radius: 8px;
+    cursor: pointer;
+    transition: background-color 0.3s ease;
+  }
+  .login-button:disabled {
+    background-color: #a3a9f7;
+    cursor: not-allowed;
+  }
+  .forgot-password {
+    margin-top: 1rem;
+    text-align: right;
+  }
+  .forgot-password a {
+    color: #667eea;
+    text-decoration: none;
+    font-size: 0.9rem;
+  }
+  .forgot-password a:hover {
+    text-decoration: underline;
+  }
+  .error-message {
+    margin-top: 1rem;
+    color: #d93025;
+    font-weight: 600;
+    text-align: center;
+  }
+  .loading-spinner {
+    border: 3px solid #f3f3f3;
+    border-top: 3px solid #667eea;
+    border-radius: 50%;
+    width: 20px;
+    height: 20px;
+    animation: spin 1s linear infinite;
+    display: inline-block;
+    vertical-align: middle;
+    margin-left: 8px;
+  }
+  @keyframes spin {
+    0% { transform: rotate(0deg);}
+    100% { transform: rotate(360deg);}
+  }
+  /* Responsive */
+  @media (max-width: 480px) {
+    .login-container {
+      margin: 1rem;
+      padding: 2rem 1.5rem;
+    }
+  }
+</style>
+</head>
+<body>
+  <div class="login-container" role="main" aria-label="登录表单">
+    <h2>用户登录</h2>
+    <form id="loginForm" novalidate>
+      <label for="usernameEmail">用户名或邮箱</label>
+      <input type="text" id="usernameEmail" name="usernameEmail" autocomplete="username" placeholder="请输入用户名或邮箱" required aria-describedby="usernameEmailError" />
+      <div id="usernameEmailError" class="error-message" aria-live="polite"></div>
+
+      <label for="password" style="margin-top:1rem;">密码</label>
+      <div class="password-wrapper">
+        <input type="password" id="password" name="password" autocomplete="current-password" placeholder="请输入密码" required minlength="6" aria-describedby="passwordError" />
+        <button type="button" class="toggle-password" aria-label="切换密码可见性" title="切换密码可见性">👁️</button>
+      </div>
+      <div id="passwordError" class="error-message" aria-live="polite"></div>
+
+      <button type="submit" id="loginButton" class="login-button" disabled>登录</button>
+      <div class="forgot-password">
+        <a href="/forgot-password.html" target="_blank" rel="noopener noreferrer">忘记密码？</a>
+      </div>
+      <div id="submitError" class="error-message" aria-live="polite"></div>
+    </form>
+  </div>
+
+<script>
+  (function(){
+    const usernameEmailInput = document.getElementById('usernameEmail');
+    const passwordInput = document.getElementById('password');
+    const loginButton = document.getElementById('loginButton');
+    const usernameEmailError = document.getElementById('usernameEmailError');
+    const passwordError = document.getElementById('passwordError');
+    const submitError = document.getElementById('submitError');
+    const togglePasswordBtn = document.querySelector('.toggle-password');
+    const form = document.getElementById('loginForm');
+
+    // 校验用户名或邮箱格式
+    function validateUsernameEmail(value) {
+      if (!value.trim()) {
+        return "用户名或邮箱不能为空";
+      }
+      // 简单邮箱正则
+      const emailRegex = /^[^\s@]+@[^\s@]+\.[^\s@]+$/;
+      // 用户名规则：允许字母数字下划线，长度3-20
+      const usernameRegex = /^[a-zA-Z0-9_]{3,20}$/;
+      if (emailRegex.test(value)) {
+        return "";
+      } else if (usernameRegex.test(value)) {
+        return "";
+      } else {
+        return "请输入有效的用户名或邮箱格式";
+      }
+    }
+
+    // 校验密码格式
+    function validatePassword(value) {
+      if (!value) {
+        return "密码不能为空";
+      }
+      if (value.length < 6) {
+        return "密码长度不能少于6位";
+      }
+      return "";
+    }
+
+    // 实时校验并更新错误提示和按钮状态
+    function validateForm() {
+      const usernameEmailVal = usernameEmailInput.value;
+      const passwordVal = passwordInput.value;
+
+      const usernameEmailErrMsg = validateUsernameEmail(usernameEmailVal);
+      const passwordErrMsg = validatePassword(passwordVal);
+
+      usernameEmailError.textContent = usernameEmailErrMsg;
+      passwordError.textContent = passwordErrMsg;
+      submitError.textContent = "";
+
+      const isValid = !usernameEmailErrMsg && !passwordErrMsg;
+      loginButton.disabled = !isValid;
+      return isValid;
+    }
+
+    // 密码可见切换
+    togglePasswordBtn.addEventListener('click', () => {
+      if (passwordInput.type === 'password') {
+        passwordInput.type = 'text';
+        togglePasswordBtn.textContent = '🙈';
+        togglePasswordBtn.setAttribute('aria-label', '隐藏密码');
+        togglePasswordBtn.setAttribute('title', '隐藏密码');
+      } else {
+        passwordInput.type = 'password';
+        togglePasswordBtn.textContent = '👁️';
+        togglePasswordBtn.setAttribute('aria-label', '显示密码');
+        togglePasswordBtn.setAttribute('title', '显示密码');
+      }
+    });
+
+    // 监听输入事件实时校验
+    usernameEmailInput.addEventListener('input', validateForm);
+    passwordInput.addEventListener('input', validateForm);
+
+    // 模拟登录请求
+    function fakeLoginRequest(data) {
+      return new Promise((resolve, reject) => {
+        setTimeout(() => {
+          // 模拟用户名/邮箱为 "user" 或 "user@example.com" 且密码为 "password123" 才成功
+          const validUsers = ["user", "user@example.com"];
+          if (validUsers.includes(data.usernameEmail.toLowerCase()) && data.password === "password123") {
+            resolve();
+          } else {
+            reject(new Error("用户名或密码错误"));
+          }
+        }, 1500);
+      });
+    }
+
+    // 表单提交处理
+    form.addEventListener('submit', async (e) => {
+      e.preventDefault();
+      if (!validateForm()) return;
+
+      loginButton.disabled = true;
+      const originalText = loginButton.textContent;
+      loginButton.textContent = "登录中";
+      const spinner = document.createElement('span');
+      spinner.className = 'loading-spinner';
+      loginButton.appendChild(spinner);
+      submitError.textContent = "";
+
+      try {
+        await fakeLoginRequest({
+          usernameEmail: usernameEmailInput.value.trim(),
+          password: passwordInput.value
+        });
+        // 登录成功跳转（此处用alert模拟）
+        alert("登录成功，跳转到用户主页");
+        // window.location.href = "/user-home.html"; // 实际跳转
+      } catch (err) {
+        submitError.textContent = err.message;
+      } finally {
+        loginButton.disabled = false;
+        loginButton.textContent = originalText;
+      }
+    });
+
+    // 页面加载时校验一次，防止缓存值导致按钮状态异常
+    validateForm();
+  })();
+<\/script>
+<\/body>
+<\/html>

voice/baidu/baidu_voice.py

@@ -1,9 +1,11 @@
 """
-baidu voice service
+baidu voice service with thread-safe token caching
 """
 import json
 import os
 import time
+import threading
+import requests
 
 from aip import AipSpeech
 
@@ -14,28 +16,13 @@ from config import conf
 from voice.audio_convert import get_pcm_from_wav
 from voice.voice import Voice
 
-"""
-    百度的语音识别API.
-    dev_pid:
-        - 1936: 普通话远场
-        - 1536：普通话(支持简单的英文识别)
-        - 1537：普通话(纯中文识别)
-        - 1737：英语
-        - 1637：粤语
-        - 1837：四川话
-    要使用本模块, 首先到 yuyin.baidu.com 注册一个开发者账号,
-    之后创建一个新应用, 然后在应用管理的"查看key"中获得 API Key 和 Secret Key
-    然后在 config.json 中填入这两个值, 以及 app_id, dev_pid
-    """
-
-
 class BaiduVoice(Voice):
     def __init__(self):
         try:
+            # 读取本地 TTS 参数配置
             curdir = os.path.dirname(__file__)
             config_path = os.path.join(curdir, "config.json")
-            bconf = None
-            if not os.path.exists(config_path):  # 如果没有配置文件，创建本地配置文件
+            if not os.path.exists(config_path):
                 bconf = {"lang": "zh", "ctp": 1, "spd": 5, "pit": 5, "vol": 5, "per": 0}
                 with open(config_path, "w") as fw:
                     json.dump(bconf, fw, indent=4)
@@ -47,48 +34,139 @@ class BaiduVoice(Voice):
             self.api_key = str(conf().get("baidu_api_key"))
             self.secret_key = str(conf().get("baidu_secret_key"))
             self.dev_id = conf().get("baidu_dev_pid")
-            self.lang = bconf["lang"]
-            self.ctp = bconf["ctp"]
-            self.spd = bconf["spd"]
-            self.pit = bconf["pit"]
-            self.vol = bconf["vol"]
-            self.per = bconf["per"]
 
+            self.lang = bconf["lang"]
+            self.ctp  = bconf["ctp"]
+            self.spd  = bconf["spd"]
+            self.pit  = bconf["pit"]
+            self.vol  = bconf["vol"]
+            self.per  = bconf["per"]
+
+            # 百度 SDK 客户端（短文本合成 & 语音识别）
             self.client = AipSpeech(self.app_id, self.api_key, self.secret_key)
+
+            # access_token 缓存与锁
+            self._access_token    = None
+            self._token_expire_ts = 0
+            self._token_lock      = threading.Lock()
         except Exception as e:
-            logger.warn("BaiduVoice init failed: %s, ignore " % e)
+            logger.warn("BaiduVoice init failed: %s, ignore" % e)
+
+    def _get_access_token(self):
+        # 多线程安全获取 token
+        with self._token_lock:
+            now = time.time()
+            if self._access_token and now < self._token_expire_ts:
+                return self._access_token
+            url = "https://aip.baidubce.com/oauth/2.0/token"
+            params = {
+                "grant_type":    "client_credentials",
+                "client_id":     self.api_key,
+                "client_secret": self.secret_key,
+            }
+            resp = requests.post(url, params=params).json()
+            token = resp.get("access_token")
+            expires_in = resp.get("expires_in", 2592000)
+            if token:
+                self._access_token    = token
+                self._token_expire_ts = now + expires_in - 60  # 提前 1 分钟过期
+                return token
+            else:
+                logger.error("BaiduVoice _get_access_token failed: %s", resp)
+                return None
 
     def voiceToText(self, voice_file):
-        # 识别本地文件
-        logger.debug("[Baidu] voice file name={}".format(voice_file))
+        logger.debug("[Baidu] recognize voice file=%s", voice_file)
         pcm = get_pcm_from_wav(voice_file)
         res = self.client.asr(pcm, "pcm", 16000, {"dev_pid": self.dev_id})
-        if res["err_no"] == 0:
-            logger.info("百度语音识别到了：{}".format(res["result"]))
+        if res.get("err_no") == 0:
             text = "".join(res["result"])
-            reply = Reply(ReplyType.TEXT, text)
+            logger.info("[Baidu] ASR result: %s", text)
+            return Reply(ReplyType.TEXT, text)
         else:
-            logger.info("百度语音识别出错了: {}".format(res["err_msg"]))
-            if res["err_msg"] == "request pv too much":
-                logger.info("  出现这个原因很可能是你的百度语音服务调用量超出限制，或未开通付费")
-            reply = Reply(ReplyType.ERROR, "百度语音识别出错了；{0}".format(res["err_msg"]))
-        return reply
+            err = res.get("err_msg", "")
+            logger.error("[Baidu] ASR error: %s", err)
+            return Reply(ReplyType.ERROR, f"语音识别失败：{err}")
+
+    def _long_text_synthesis(self, text):
+        token = self._get_access_token()
+        if not token:
+            return Reply(ReplyType.ERROR, "获取百度 access_token 失败")
+
+        # 创建合成任务
+        create_url = f"https://aip.baidubce.com/rpc/2.0/tts/v1/create?access_token={token}"
+        payload = {
+            "text":            text,
+            "format":          "mp3-16k",
+            "voice":           0,
+            "lang":            self.lang,
+            "speed":           self.spd,
+            "pitch":           self.pit,
+            "volume":          self.vol,
+            "enable_subtitle": 0,
+        }
+        headers = {"Content-Type": "application/json"}
+        create_resp = requests.post(create_url, headers=headers, json=payload).json()
+        task_id = create_resp.get("task_id")
+        if not task_id:
+            logger.error("[Baidu] 长文本合成创建任务失败: %s", create_resp)
+            return Reply(ReplyType.ERROR, "长文本合成任务提交失败")
+        logger.info("[Baidu] 长文本合成任务已提交 task_id=%s", task_id)
+
+        # 轮询查询任务状态
+        query_url = f"https://aip.baidubce.com/rpc/2.0/tts/v1/query?access_token={token}"
+        for _ in range(100):
+            time.sleep(3)
+            resp = requests.post(query_url, headers=headers, json={"task_ids":[task_id]})
+            result = resp.json()
+            infos = result.get("tasks_info") or result.get("tasks") or []
+            if not infos:
+                continue
+            info = infos[0]
+            status = info.get("task_status")
+            if status == "Success":
+                task_res = info.get("task_result", {})
+                audio_url = task_res.get("audio_address") or task_res.get("speech_url")
+                break
+            elif status == "Running":
+                continue
+            else:
+                logger.error("[Baidu] 长文本合成失败: %s", info)
+                return Reply(ReplyType.ERROR, "长文本合成执行失败")
+        else:
+            return Reply(ReplyType.ERROR, "长文本合成超时，请稍后重试")
+
+        # 下载并保存音频
+        audio_data = requests.get(audio_url).content
+        fn = TmpDir().path() + f"reply-long-{int(time.time())}-{hash(text)&0x7FFFFFFF}.mp3"
+        with open(fn, "wb") as f:
+            f.write(audio_data)
+        logger.info("[Baidu] 长文本合成 success: %s", fn)
+        return Reply(ReplyType.VOICE, fn)
 
     def textToVoice(self, text):
-        result = self.client.synthesis(
-            text,
-            self.lang,
-            self.ctp,
-            {"spd": self.spd, "pit": self.pit, "vol": self.vol, "per": self.per},
-        )
-        if not isinstance(result, dict):
-            # Avoid the same filename under multithreading
-            fileName = TmpDir().path() + "reply-" + str(int(time.time())) + "-" + str(hash(text) & 0x7FFFFFFF) + ".mp3"
-            with open(fileName, "wb") as f:
-                f.write(result)
-            logger.info("[Baidu] textToVoice text={} voice file name={}".format(text, fileName))
-            reply = Reply(ReplyType.VOICE, fileName)
-        else:
-            logger.error("[Baidu] textToVoice error={}".format(result))
-            reply = Reply(ReplyType.ERROR, "抱歉，语音合成失败")
-        return reply
+        try:
+            # GBK 编码字节长度
+            gbk_len = len(text.encode("gbk", errors="ignore"))
+            if gbk_len <= 1024:
+                # 短文本走 SDK 合成
+                result = self.client.synthesis(
+                    text, self.lang, self.ctp,
+                    {"spd":self.spd, "pit":self.pit, "vol":self.vol, "per":self.per}
+                )
+                if not isinstance(result, dict):
+                    fn = TmpDir().path() + f"reply-{int(time.time())}-{hash(text)&0x7FFFFFFF}.mp3"
+                    with open(fn, "wb") as f:
+                        f.write(result)
+                    logger.info("[Baidu] 短文本合成 success: %s", fn)
+                    return Reply(ReplyType.VOICE, fn)
+                else:
+                    logger.error("[Baidu] 短文本合成 error: %s", result)
+                    return Reply(ReplyType.ERROR, "短文本语音合成失败")
+            else:
+                # 长文本
+                return self._long_text_synthesis(text)
+        except Exception as e:
+            logger.error("BaiduVoice textToVoice exception: %s", e)
+            return Reply(ReplyType.ERROR, f"合成异常：{e}")
+

voice/factory.py

@@ -50,4 +50,8 @@ def create_voice(voice_type):
         from voice.xunfei.xunfei_voice import XunfeiVoice
 
         return XunfeiVoice()
+    elif voice_type == "tencent":
+        from voice.tencent.tencent_voice import TencentVoice
+
+        return TencentVoice()
     raise RuntimeError

voice/tencent/config.json.template

@@ -0,0 +1,5 @@
+{
+    "voice_type": 1003,
+    "secret_id": "YOUR_SECRET_ID",
+    "secret_key": "YOUR_SECRET_KEY"
+}

voice/tencent/tencent_voice.py

@@ -0,0 +1,119 @@
+import json
+import base64
+import os
+import time
+from voice.voice import Voice
+from common.log import logger
+from tencentcloud.common import credential
+from tencentcloud.asr.v20190614 import asr_client, models as asr_models
+from tencentcloud.tts.v20190823 import tts_client, models as tts_models
+from bridge.reply import Reply, ReplyType
+from common.tmp_dir import TmpDir
+
+class TencentVoice(Voice):
+    def __init__(self):
+        super().__init__()
+        self.secret_id = None
+        self.secret_key = None
+        self.voice_type = 1003
+        self._load_config()
+        
+    def _load_config(self):
+        """
+        从本地配置文件加载配置
+        """
+        try:
+            config_path = os.path.join(os.path.dirname(__file__), 'config.json')
+            with open(config_path, 'r') as f:
+                config = json.load(f)
+            self.secret_id = config.get('secret_id')
+            self.secret_key = config.get('secret_key')
+            self.voice_type = config.get('voice_type', self.voice_type)
+            if not self.secret_id or not self.secret_key:
+                logger.error("[Tencent] Missing credentials in config.json")
+        except Exception as e:
+            logger.error(f"[Tencent] Failed to load config: {e}")
+    
+    def setup(self, config):
+        """
+        设置配置信息（保留此方法用于向后兼容）
+        """
+        pass
+        
+    def voiceToText(self, voice_file):
+        """
+        将语音文件转换为文本
+        """
+        try:
+            # 实例化认证对象
+            cred = credential.Credential(self.secret_id, self.secret_key)
+            
+            # 实例化客户端
+            client = asr_client.AsrClient(cred, "ap-guangzhou")
+            
+            # 读取音频文件
+            with open(voice_file, 'rb') as f:
+                audio_data = f.read()
+            
+            # 进行base64编码
+            base64_audio = base64.b64encode(audio_data).decode('utf-8')
+            
+            # 构造请求对象
+            req = asr_models.SentenceRecognitionRequest()
+            req.ProjectId = 0
+            req.SubServiceType = 2
+            req.EngSerViceType = "16k_zh"
+            req.SourceType = 1
+            req.VoiceFormat = "wav"
+            req.UsrAudioKey = "voice_recognition"
+            req.Data = base64_audio
+            
+            # 发起请求
+            resp = client.SentenceRecognition(req)
+            
+            # 解析结果
+            if resp.Result:
+                logger.info("[Tencent] Voice to text success: {}".format(resp.Result))
+                return Reply(ReplyType.TEXT, resp.Result)
+            else:
+                logger.warning("[Tencent] Voice to text failed")
+                return Reply(ReplyType.ERROR, "腾讯语音识别失败")
+            
+        except Exception as e:
+            logger.error("[Tencent] Voice to text error: {}".format(e))
+            return Reply(ReplyType.ERROR, "腾讯语音识别出错：{}".format(str(e)))
+
+    def textToVoice(self, text):
+        """
+        将文本转换为语音
+        """
+        try:
+            cred = credential.Credential(self.secret_id, self.secret_key)
+            client = tts_client.TtsClient(cred, "ap-guangzhou")
+
+            req = tts_models.TextToVoiceRequest()
+            req.Text = text
+            req.SessionId = str(int(time.time()))
+            req.Volume = 5
+            req.Speed = 0
+            req.ProjectId = 0
+            req.ModelType = 1
+            req.PrimaryLanguage = 1
+            req.SampleRate = 16000
+            req.VoiceType = self.voice_type  # 客服女声
+
+            response = client.TextToVoice(req)
+            
+            if response.Audio:
+                fileName = TmpDir().path() + "reply-" + str(int(time.time())) + "-" + str(hash(text) & 0x7FFFFFFF) + ".mp3"
+                with open(fileName, "wb") as f:
+                    f.write(base64.b64decode(response.Audio))
+                logger.info("[Tencent] textToVoice text={} voice file name={}".format(text, fileName))
+                return Reply(ReplyType.VOICE, fileName)
+            else:
+                logger.error("[Tencent] textToVoice failed")
+                return Reply(ReplyType.ERROR, "腾讯语音合成失败")
+
+        except Exception as e:
+            logger.error("[Tencent] Text to voice error: {}".format(e))
+            return Reply(ReplyType.ERROR, "腾讯语音合成出错：{}".format(str(e)))