chore: v3.4.18

perf: 安装和更新插件后全量重启避免奇奇怪怪的bug
feat: 支持 /tool off_all 停用所有函数工具

Dockerfile

@@ -12,6 +12,8 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
     && apt-get clean \
     && rm -rf /var/lib/apt/lists/*
 
+RUN ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime
+
 RUN python -m pip install -r requirements.txt
 
 EXPOSE 6185 

astrbot/core/config/default.py

@@ -2,7 +2,7 @@
 如需修改配置，请在 `data/cmd_config.json` 中修改或者在管理面板中可视化修改。
 """
 
-VERSION = "3.4.17"
+VERSION = "3.4.18"
 DB_PATH = "data/data_v3.db"
 
 # 默认配置
@@ -83,14 +83,7 @@ DEFAULT_CONFIG = {
     "pip_install_arg": "",
     "plugin_repo_mirror": "",
     "knowledge_db": {},
-    "persona": [
-        {
-            "name": "default",
-            "prompt": "",
-            "begin_dialogs": [],
-            "mood_imitation_dialogs": [],
-        }
-    ],
+    "persona": [],
 }
 
 
@@ -387,6 +380,16 @@ CONFIG_METADATA_2 = {
                             "model": "glm-4-flash",
                         },
                     },
+                    "硅基流动": {
+                        "id": "siliconflow",
+                        "type": "openai_chat_completion",
+                        "enable": True,
+                        "key": [],
+                        "api_base": "https://api.siliconflow.cn/v1",
+                        "model_config": {
+                            "model": "deepseek-ai/DeepSeek-V3",
+                        },
+                    },
                     "llmtuner": {
                         "id": "llmtuner_default",
                         "type": "llm_tuner",
@@ -616,14 +619,14 @@ CONFIG_METADATA_2 = {
                         "description": "预设对话",
                         "type": "list",
                         "items": {"type": "string"},
-                        "hint": "可选。在每个对话前会插入这些预设对话。对话需要成对(用户和助手)，输入完一个角色之后按回车",
+                        "hint": "可选。在每个对话前会插入这些预设对话。对话需要成对(用户和助手)，输入完一个角色的内容之后按【回车】。需要偶数个对话",
                         "obvious_hint": True,
                     },
                     "mood_imitation_dialogs": {
                         "description": "对话风格模仿",
                         "type": "list",
                         "items": {"type": "string"},
-                        "hint": "旨在让模型尽可能模仿学习到所填写的对话的语气风格。格式和 `预设对话` 一样。对话需要成对(用户和助手)，输入完一个角色之后按回车",
+                        "hint": "旨在让模型尽可能模仿学习到所填写的对话的语气风格。格式和 `预设对话` 一致。对话需要成对(用户和助手)，输入完一个角色的内容之后按【回车】。需要偶数个对话",
                         "obvious_hint": True,
                     },
                 },
@@ -696,7 +699,7 @@ CONFIG_METADATA_2 = {
                                 "description": "启用主动回复",
                                 "type": "bool",
                                 "obvious_hint": True,
-                                "hint": "启用后，会根据触发概率主动回复群聊内的对话。",
+                                "hint": "启用后，会根据触发概率主动回复群聊内的对话。QQ官方API(qq_official)不可用",
                             },
                             "method": {
                                 "description": "回复方法",

astrbot/core/core_lifecycle.py

@@ -25,9 +25,8 @@ class AstrBotCoreLifecycle:
         self.astrbot_config = astrbot_config
         self.db = db
         
-        if self.astrbot_config['http_proxy']:
-            os.environ['https_proxy'] = self.astrbot_config['http_proxy']
-            os.environ['http_proxy'] = self.astrbot_config['http_proxy']
+        os.environ['https_proxy'] = self.astrbot_config['http_proxy']
+        os.environ['http_proxy'] = self.astrbot_config['http_proxy']
     
     async def initialize(self):
         logger.info("AstrBot v"+ VERSION)

astrbot/core/pipeline/process_stage/method/llm_request.py

@@ -83,6 +83,8 @@ class LLMRequestSubStage(Stage):
                 # text completion
                 event.set_result(MessageEventResult().message(llm_response.completion_text)
                                  .set_result_content_type(ResultContentType.LLM_RESULT))
+            elif llm_response.role == 'err':
+                event.set_result(MessageEventResult().message(f"AstrBot 请求失败。\n错误信息: {llm_response.completion_text}"))
             elif llm_response.role == 'tool':
                 # function calling
                 function_calling_result = {}

astrbot/core/pipeline/result_decorate/stage.py

@@ -103,8 +103,12 @@ class ResultDecorateStage:
                     if url:
                         result.chain = [Image.fromURL(url)]
             
+            # at 回复
             if self.reply_with_mention and event.get_message_type() != MessageType.FRIEND_MESSAGE:
                 result.chain.insert(0, At(qq=event.get_sender_id(), name=event.get_sender_name()))
+                if len(result.chain) > 1 and isinstance(result.chain[1], Plain):
+                    result.chain[1].text = "\n" + result.chain[1].text
             
+            # 引用回复
             if self.reply_with_quote:
                 result.chain.insert(0, Reply(id=event.message_obj.message_id))

astrbot/core/platform/sources/gewechat/client.py

@@ -95,6 +95,8 @@ class SimpleGewechatClient():
             if f'<atuserlist><![CDATA[,{abm.self_id}]]>' in msg_source \
                 or f'<atuserlist><![CDATA[{abm.self_id}]]>' in msg_source:
                 at_me = True
+            if '在群聊中@了你' in d.get('PushContent', ''):
+                at_me = True
         else:
             abm.type = MessageType.FRIEND_MESSAGE
             user_id = from_user_name

astrbot/core/provider/sources/gemini_source.py

@@ -190,7 +190,8 @@ class ProviderGoogleGenAI(Provider):
                 llm_response.role = "tool"
                 llm_response.tools_call_args.append(candidate['functionCall']['args'])
                 llm_response.tools_call_name.append(candidate['functionCall']['name'])
-            
+        
+        llm_response.completion_text = llm_response.completion_text.strip()
         return llm_response
 
 

astrbot/core/provider/sources/openai_source.py

@@ -1,6 +1,6 @@
 import base64
 import json
-import re
+import os
 
 from openai import AsyncOpenAI, NOT_GIVEN
 from openai.types.chat.chat_completion import ChatCompletion
@@ -94,26 +94,11 @@ class ProviderOpenAIOfficial(Provider):
             if tool_list:
                 payloads['tools'] = tool_list
         
-        completion = None
-        try:
-            completion = await self.client.chat.completions.create(
-                **payloads,
-                stream=False
-            )
-        except BaseException as e:
-            # 处理不支持 Function Calling 的模型
-            if 'does not support Function Calling' in str(e) \
-                or 'does not support tools' in str(e)  \
-                or 'Function call is not supported' in str(e): # siliconcloud
-                    del payloads['tools']
-                    logger.debug(f"模型 {self.model_name} 不支持 tools，已自动移除")
-                    completion = await self.client.chat.completions.create(
-                        **payloads,
-                        stream=False
-                    )
-            else:
-                raise e
-        
+        completion = await self.client.chat.completions.create(
+            **payloads,
+            stream=False
+        )
+
         assert isinstance(completion, ChatCompletion)
         logger.debug(f"completion: {completion}")
 
@@ -168,32 +153,86 @@ class ProviderOpenAIOfficial(Provider):
             "messages": context_query,
             **self.provider_config.get("model_config", {})
         }
-
+        llm_response = None
         try:
             llm_response = await self._query(payloads, func_tool)
-            if kwargs.get("persist", True):
-                await self.save_history(contexts, new_record, session_id, llm_response)
-            return llm_response
         except Exception as e:
             if "maximum context length" in str(e):
+                # 重试 10 次
                 retry_cnt = 10
                 while retry_cnt > 0:
                     logger.warning("上下文长度超过限制。尝试弹出最早的记录然后重试。")
                     try:
                         await self.pop_record(session_id)
                         llm_response = await self._query(payloads, func_tool)
-                        if kwargs.get("persist", True):
-                            await self.save_history(contexts, new_record, session_id, llm_response)
-                        return llm_response
+                        break
                     except Exception as e:
                         if "maximum context length" in str(e):
                             retry_cnt -= 1
                         else:
                             raise e
+                if retry_cnt == 0:
+                    llm_response = LLMResponse("err", "err: 请尝试 /reset 清除会话记录。")
+            elif "The model is not a VLM" in str(e): # siliconcloud
+                # 尝试删除所有 image
+                print(context_query)
+                new_contexts = await self._remove_image_from_context(context_query)
+                print(new_contexts)
+                payloads['messages'] = new_contexts
+                llm_response = await self._query(payloads, func_tool)
+
+            elif 'does not support Function Calling' in str(e) \
+                or 'does not support tools' in str(e)  \
+                or 'Function call is not supported' in str(e) \
+                or 'Tool calling is not supported' in str(e): # siliconcloud 
+                    logger.info(f"{self.get_model()} 不支持函数调用工具调用，已经自动去除")
+                    if 'tools' in payloads:
+                        del payloads['tools']
+                    llm_response = await self._query(payloads, None)
             else:
                 logger.error(f"发生了错误。Provider 配置如下: {self.provider_config}")
+                
+                if 'tool' in str(e).lower() and 'support' in str(e).lower():
+                    logger.error(f"疑似该模型不支持函数调用工具调用。请输入 /tool off_all")
+                
+                if 'Connection error.' in str(e):
+                    proxy = os.environ.get("http_proxy", None)
+                    if proxy:
+                        logger.error(f"可能为代理原因，请检查代理是否正常。当前代理: {proxy}")
+                
                 raise e
         
+        if kwargs.get("persist", True) and llm_response:
+            await self.save_history(contexts, new_record, session_id, llm_response)
+        
+        return llm_response
+    
+    async def _remove_image_from_context(self, contexts: List):
+        '''
+        从上下文中删除所有带有 image 的记录
+        '''
+        new_contexts = []
+        
+        flag = False
+        for context in contexts:
+            if flag:
+                flag = False # 删除 image 后，下一条（LLM 响应）也要删除
+                continue
+            if isinstance(context['content'], list):
+                flag = True
+                # continue
+                new_content = []
+                for item in context['content']:
+                    if isinstance(item, dict) and 'image_url' in item:
+                        continue
+                    new_content.append(item)
+                if not new_content:
+                    # 用户只发了图片
+                    new_content = [{"type": "text", "text": "[图片]"}]
+                context['content'] = new_content
+            new_contexts.append(context)
+        return new_contexts
+
     
     async def save_history(self, contexts: List, new_record: dict, session_id: str, llm_response: LLMResponse):
         if llm_response.role == "assistant" and session_id:

astrbot/dashboard/routes/plugin.py

@@ -56,6 +56,7 @@ class PluginRoute(Route):
         try:
             logger.info(f"正在安装插件 {repo_url}")
             await self.plugin_manager.install_plugin(repo_url)
+            self.core_lifecycle.restart()
             logger.info(f"安装插件 {repo_url} 成功。")
             return Response().ok(None, "安装成功。").__dict__
         except Exception as e:
@@ -70,6 +71,7 @@ class PluginRoute(Route):
             file_path = f"data/temp/{file.filename}"
             await file.save(file_path)
             await self.plugin_manager.install_plugin_from_file(file_path)
+            self.core_lifecycle.restart()
             logger.info(f"安装插件 {file.filename} 成功")
             return Response().ok(None, "安装成功。").__dict__
         except Exception as e:
@@ -94,6 +96,7 @@ class PluginRoute(Route):
         try:
             logger.info(f"正在更新插件 {plugin_name}")
             await self.plugin_manager.update_plugin(plugin_name)
+            self.core_lifecycle.restart()
             logger.info(f"更新插件 {plugin_name} 成功。")
             return Response().ok(None, "更新成功。").__dict__
         except Exception as e:

changelogs/v3.4.18.md

@@ -0,0 +1,12 @@
+# What's Changed
+
+- fix: 修复主动概率回复关闭后仍然回复的问题 #317
+- fix: 尝试修复 gewechat 群聊收不到 at 的回复 #294
+- perf: 移除了默认人格
+- fix: 修复HTTP代理删除后不生效 #319
+- fix: 调用Gemini API输出多余空行问题 #318
+- feat: 添加硅基流动模版
+- fix: 硅基流动 not a vlm 和 tool calling not supported 报错 #305 #291
+- perf: 回复时艾特发送者之后添加空格或换行 #312
+- fix: docker容器内时区不对导致 reminder 时间错误
+- perf: siliconcloud 不支持 tool 的模型

packages/astrbot/long_term_memory.py

@@ -27,6 +27,7 @@ class LongTermMemory:
         self.image_caption_prompt = self.config["image_caption_prompt"]
         
         self.active_reply = self.config["active_reply"]
+        self.enable_active_reply = self.active_reply.get("enable", False)
         self.ar_method = self.active_reply["method"]
         self.ar_possibility = self.active_reply["possibility_reply"]
         self.ar_prompt = self.active_reply.get("prompt", "")
@@ -51,7 +52,7 @@ class LongTermMemory:
         return response.completion_text
     
     async def need_active_reply(self, event: AstrMessageEvent) -> bool:
-        if not self.active_reply:
+        if not self.enable_active_reply:
             return False
         if event.get_message_type() != MessageType.GROUP_MESSAGE:
             return False

packages/astrbot/main.py

@@ -91,7 +91,7 @@ class Main(star.Star):
             active = " (启用)" if tool.active else "(停用)"
             msg += f"- {tool.name}: {tool.description} {active}\n"
             
-        msg += "\n使用 /tool on/off <工具名> 激活或者停用工具。"
+        msg += "\n使用 /tool on/off <工具名> 激活或者停用函数工具。/tool off_all 停用所有函数工具。"
         event.set_result(MessageEventResult().message(msg).use_t2i(False))
         
     @tool.command("on")
@@ -107,6 +107,13 @@ class Main(star.Star):
             event.set_result(MessageEventResult().message(f"停用工具 {tool_name} 成功。"))
         else:
             event.set_result(MessageEventResult().message(f"停用工具 {tool_name} 失败，未找到此工具。"))
+            
+    @tool.command("off_all")
+    async def tool_all_off(self, event: AstrMessageEvent):
+        tm = self.context.get_llm_tool_manager()
+        for tool in tm.func_list:
+            self.context.deactivate_llm_tool(tool.name)
+        event.set_result(MessageEventResult().message(f"停用所有工具成功。"))
 
     @filter.command("plugin")
     async def plugin(self, event: AstrMessageEvent, oper1: str = None, oper2: str = None):