perf: siliconcloud 不支持 tool 的模型

feat: 支持取消人格

astrbot/api/event/filter/__init__.py

@@ -6,6 +6,7 @@ from astrbot.core.star.register import (
     register_platform_adapter_type as platform_adapter_type,
     register_permission_type as permission_type,
     register_on_llm_request as on_llm_request,
+    register_on_llm_response as on_llm_response,
     register_llm_tool as llm_tool,
     register_on_decorating_result as on_decorating_result,
     register_after_message_sent as after_message_sent
@@ -31,5 +32,6 @@ __all__ = [
     'on_llm_request',
     'llm_tool',
     'on_decorating_result',
-    'after_message_sent'
+    'after_message_sent',
+    'on_llm_response'
 ]

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 = "3.4.16"
+VERSION = "3.4.17"
 DB_PATH = "data/data_v3.db"
 
 # 默认配置
@@ -37,6 +37,7 @@ DEFAULT_CONFIG = {
         "enable": True,
         "wake_prefix": "",
         "web_search": False,
+        "web_search_link": False,
         "identifier": False,
         "datetime_system_prompt": True,
         "default_personality": "default",
@@ -55,6 +56,13 @@ DEFAULT_CONFIG = {
         "group_message_max_cnt": 300,
         "image_caption": False,
         "image_caption_prompt": "Please describe the image using Chinese.",
+        "active_reply": {
+            "enable": False,
+            "method": "possibility_reply",
+            "possibility_reply": 0.1,
+            "prompt": "",
+        },
+        "put_history_to_prompt": True,
     },
     "content_safety": {
         "internal_keywords": {"enable": True, "extra_keywords": []},
@@ -78,7 +86,7 @@ DEFAULT_CONFIG = {
     "persona": [
         {
             "name": "default",
-            "prompt": "如果用户寻求帮助或者打招呼，请告诉他可以用 /help 查看 AstrBot 帮助。",
+            "prompt": "",
             "begin_dialogs": [],
             "mood_imitation_dialogs": [],
         }
@@ -111,14 +119,13 @@ CONFIG_METADATA_2 = {
                         "ws_reverse_host": "",
                         "ws_reverse_port": 6199,
                     },
-                    "vchat(微信)": {"id": "default", "type": "vchat", "enable": False},
                     "gewechat(微信)": {
                         "id": "gwchat",
                         "type": "gewechat",
                         "enable": False,
                         "base_url": "http://localhost:2531",
                         "nickname": "soulter",
-                        "host": "localhost",
+                        "host": "这里填写你的局域网IP或者公网服务器IP",
                         "port": 11451,
                     },
                 },
@@ -237,7 +244,8 @@ CONFIG_METADATA_2 = {
                         "description": "ID 白名单",
                         "type": "list",
                         "items": {"type": "string"},
-                        "hint": "AstrBot 只处理所填写的 ID 发来的消息事件。为空时不启用白名单过滤。可以使用 /myid 指令获取在某个平台上的会话 ID。也可在 AstrBot 日志内获取会话 ID，当一条消息没通过白名单时，会输出 INFO 级别的日志。会话 ID 类似 aiocqhttp:GroupMessage:547540978",
+                        "obvious_hint": True,
+                        "hint": "AstrBot 只处理所填写的 ID 发来的消息事件。为空时不启用白名单过滤。可以使用 /sid 指令获取在某个平台上的会话 ID。也可在 AstrBot 日志内获取会话 ID，当一条消息没通过白名单时，会输出 INFO 级别的日志。会话 ID 类似 aiocqhttp:GroupMessage:547540978",
                     },
                     "id_whitelist_log": {
                         "description": "打印白名单日志",
@@ -324,7 +332,7 @@ CONFIG_METADATA_2 = {
                         "type": "openai_chat_completion",
                         "enable": True,
                         "key": [],
-                        "api_base": "",
+                        "api_base": "https://api.openai.com/v1",
                         "model_config": {
                             "model": "gpt-4o-mini",
                         },
@@ -420,9 +428,17 @@ CONFIG_METADATA_2 = {
                         "api_key": "",
                         "api_base": "",
                         "model": "tts-1",
+                        "openai-tts-voice": "alloy",
+                        "timeout": "20",
                     },
                 },
                 "items": {
+                    "openai-tts-voice": {
+                        "description": "voice",
+                        "type": "string",
+                        "obvious_hint": True,
+                        "hint": "OpenAI TTS 的声音。OpenAI 默认支持：'alloy', 'echo', 'fable', 'onyx', 'nova', 'shimmer'",
+                    },
                     "whisper_hint": {
                         "description": "本地部署 Whisper 模型须知",
                         "type": "string",
@@ -453,7 +469,7 @@ CONFIG_METADATA_2 = {
                     "api_base": {
                         "description": "API Base URL",
                         "type": "string",
-                        "hint": "API Base URL 请在在模型提供商处获得。如使用时出现了 404 报错，可以尝试在地址末尾加上 `/v1`。",
+                        "hint": "API Base URL 请在在模型提供商处获得。如出现 404 报错，尝试在地址末尾加上 /v1",
                         "obvious_hint": True,
                     },
                     "base_model_path": {
@@ -539,16 +555,25 @@ CONFIG_METADATA_2 = {
                     "web_search": {
                         "description": "启用网页搜索",
                         "type": "bool",
-                        "hint": "能访问 Google 时效果最佳。如果 Google 访问失败，程序会依次访问 Bing, Sogo 搜索引擎。",
+                        "obvious_hint": True,
+                        "hint": "能访问 Google 时效果最佳（国内需要在 `其他配置` 开启 HTTP 代理）。如果 Google 访问失败，程序会依次访问 Bing, Sogo 搜索引擎。",
+                    },
+                    "web_search_link": {
+                        "description": "网页搜索引用链接",
+                        "type": "bool",
+                        "obvious_hint": True,
+                        "hint": "开启后，将会传入网页搜索结果的链接给模型，并引导模型输出引用链接。",
                     },
                     "identifier": {
                         "description": "启动识别群员",
                         "type": "bool",
+                        "obvious_hint": True,
                         "hint": "在 Prompt 前加上群成员的名字以让模型更好地了解群聊状态。启用将略微增加 token 开销。",
                     },
                     "datetime_system_prompt": {
                         "description": "启用日期时间系统提示",
                         "type": "bool",
+                        "obvious_hint": True,
                         "hint": "启用后，会在系统提示词中加上当前机器的日期时间。",
                     },
                     "default_personality": {
@@ -591,14 +616,14 @@ 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。格式要求：第一句为用户，第二句为助手，以此类推。",
+                        "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",
                         "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。",
+                        "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",
                         "obvious_hint": True,
                     },
                 },
@@ -644,25 +669,61 @@ CONFIG_METADATA_2 = {
                     "group_icl_enable": {
                         "description": "群聊内记录各群员对话",
                         "type": "bool",
-                        "obvious-hint": True,
+                        "obvious_hint": True,
                         "hint": "启用后，会记录群聊内各群员的对话。使用 /reset 命令清除记录。推荐使用 gpt-4o-mini 模型。",
                     },
                     "group_message_max_cnt": {
                         "description": "群聊消息最大数量",
                         "type": "int",
-                        "obvious-hint": True,
+                        "obvious_hint": True,
                         "hint": "群聊消息最大数量。超过此数量后，会自动清除旧消息。",
                     },
                     "image_caption": {
                         "description": "启用图像转述(需要模型支持)",
                         "type": "bool",
-                        "obvious-hint": True,
+                        "obvious_hint": True,
                         "hint": "启用后，当接收到图片消息时，会使用模型先将图片转述为文字再进行后续处理。推荐使用 gpt-4o-mini 模型。",
                     },
                     "image_caption_prompt": {
                         "description": "图像转述提示词",
                         "type": "string"
                     },
+                    "active_reply": {
+                        "description": "主动回复",
+                        "type": "object",
+                        "items": {
+                            "enable": {
+                                "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。",
+                            },
+                            "method": {
+                                "description": "回复方法",
+                                "type": "string",
+                                "options": ["possibility_reply"],
+                                "hint": "回复方法。possibility_reply 为根据概率回复",
+                            },
+                            "possibility_reply": {
+                                "description": "回复概率",
+                                "type": "float",
+                                "obvious_hint": True,
+                                "hint": "回复概率。当回复方法为 possibility_reply 时有效。当概率 >= 1 时，每条消息都会回复。",
+                            },
+                            "prompt": {
+                                "description": "提示词",
+                                "type": "string",
+                                "obvious_hint": True,
+                                "hint": "提示词。当提示词为空时，如果触发回复，prompt是触发的消息的内容；否则是提示词。此项可以和定时回复（暂未实现）配合使用。",
+                            },
+                        },
+                    },
+                    "put_history_to_prompt": {
+                        "description": "将群聊历史记录作为 prompt",
+                        "type": "bool",
+                        "obvious_hint": True,
+                        "hint": "需要先启用 group_icl_enable。此功能会将群聊历史记录放到 prompt 再请求。如果关闭，则是放在 system_prompt。如果开启了主动回复，建议启用，模型能够更好地完成回复任务。",
+                    }
                 },
             },
         },

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

@@ -21,6 +21,10 @@ class DifyRequestSubStage(Stage):
         req: ProviderRequest = None
         
         provider = self.ctx.plugin_manager.context.get_using_provider()
+        
+        if not provider:
+            return
+        
         if provider.meta().type != "dify":
             return
         

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

@@ -68,6 +68,15 @@ class LLMRequestSubStage(Stage):
             if _nested:
                 req.func_tool = None # 暂时不支持递归工具调用
             llm_response = await provider.text_chat(**req.__dict__) # 请求 LLM
+            
+            # 执行 LLM 响应后的事件。
+            handlers = star_handlers_registry.get_handlers_by_event_type(EventType.OnLLMResponseEvent)
+            for handler in handlers:
+                try:
+                    await handler.handler(event, llm_response)
+                except BaseException:
+                    logger.error(traceback.format_exc())
+            
             await Metric.upload(llm_tick=1, model_name=provider.get_model(), provider_type=provider.meta().type)
 
             if llm_response.role == 'assistant':

astrbot/core/pipeline/process_stage/stage.py

@@ -37,7 +37,11 @@ class ProcessStage(Stage):
                     # Handler 的 LLM 请求
                     logger.debug(f"llm request -> {resp.prompt}")
                     event.set_extra("provider_request", resp)
+                    _t = False
                     async for _ in self.llm_request_sub_stage.process(event):
+                        _t = True
+                        yield
+                    if not _t:
                         yield
                 else:
                     yield
@@ -49,6 +53,11 @@ class ProcessStage(Stage):
         if not event._has_send_oper and event.is_at_or_wake_command:
             if (event.get_result() and not event.get_result().is_stopped()) or not event.get_result():
                 provider = self.ctx.plugin_manager.context.get_using_provider()
+                
+                if not provider:
+                    logger.info("未找到可用的 LLM 提供商，请先前往配置服务提供商。")
+                    return
+                
                 match provider.meta().type:
                     case "dify":
                         async for _ in self.dify_request_sub_stage.process(event):

astrbot/core/platform/astr_message_event.py

@@ -296,6 +296,7 @@ class AstrMessageEvent(abc.ABC):
     def request_llm(
         self,
         prompt: str,
+        func_tool_manager = None,
         session_id: str = None,
         image_urls: List[str] = None,
         contexts: List = None,
@@ -311,11 +312,13 @@ class AstrMessageEvent(abc.ABC):
         
         image_urls: 可以是 base64:// 或者 http:// 开头的图片链接，也可以是本地图片路径。
         contexts: 当指定 contexts 时，将会**只**使用 contexts 作为上下文。
+        func_tool_manager: 函数工具管理器，用于调用函数工具。用 self.context.get_llm_tool_manager() 获取。
         '''
         return ProviderRequest(
             prompt = prompt,
             session_id = session_id,
             image_urls = image_urls,
+            func_tool = func_tool_manager,
             contexts = contexts,
             system_prompt = system_prompt
         )

astrbot/core/platform/manager.py

@@ -24,7 +24,10 @@ class PlatformManager():
                 case "qq_official":
                     from .sources.qqofficial.qqofficial_platform_adapter import QQOfficialPlatformAdapter # noqa: F401
                 case "vchat":
-                    from .sources.vchat.vchat_platform_adapter import VChatPlatformAdapter # noqa: F401
+                    try:
+                        from .sources.vchat.vchat_platform_adapter import VChatPlatformAdapter # noqa: F401
+                    except BaseException:
+                        logger.warning("当前 astrbot 已不维护 vchat 的接入，如有需要请 pip 安装 vchat 然后重启")
                 case "gewechat":
                     from .sources.gewechat.gewechat_platform_adapter import GewechatPlatformAdapter # noqa: F401
         

astrbot/core/provider/entites.py

@@ -2,6 +2,7 @@ import enum
 from dataclasses import dataclass, field
 from typing import List, Dict, Type
 from .func_tool_manager import FuncCall
+from openai.types.chat.chat_completion import ChatCompletion
 
 
 class ProviderType(enum.Enum):
@@ -51,4 +52,7 @@ class LLMResponse:
     tools_call_args: List[Dict[str, any]] = field(default_factory=list)
     '''工具调用参数'''
     tools_call_name: List[str] = field(default_factory=list)
-    '''工具调用名称'''
+    '''工具调用名称'''
+    
+    raw_completion: ChatCompletion = None
+    _new_record: Dict[str, any] = None

astrbot/core/provider/func_tool_manager.py

@@ -108,13 +108,19 @@ class FuncCall:
         for f in self.func_list:
             if not f.active:
                 continue
-            tools.append(
-                {
-                    "name": f.name,
-                    "parameters": f.parameters,
-                    "description": f.description,
-                }
-            )
+
+            func_declaration = {
+                "name": f.name,
+                "description": f.description
+            }
+
+            # 检查并添加非空的properties参数
+            params = f.parameters if isinstance(f.parameters, dict) else {}
+            if params.get("properties", {}):
+                func_declaration["parameters"] = params
+
+            tools.append(func_declaration)
+
         declarations["function_declarations"] = tools
         return declarations
         

astrbot/core/provider/manager.py

@@ -17,6 +17,8 @@ class ProviderManager():
         self.provider_tts_settings: dict = config.get('provider_tts_settings', {})
         self.persona_configs: list = config.get('persona', [])
         
+        # 人格情景管理
+        # 目前没有拆成独立的模块
         self.default_persona_name = self.provider_settings.get('default_personality', 'default')
         self.personas: List[Personality] = []
         self.selected_default_persona = None
@@ -28,7 +30,7 @@ class ProviderManager():
             if begin_dialogs:
                 if len(begin_dialogs) % 2 != 0:
                     logger.error(f"{persona['name']} 人格情景预设对话格式不对，条数应该为偶数。")
-                    continue
+                    begin_dialogs = []
                 user_turn = True
                 for dialog in begin_dialogs:
                     bd_processed.append({
@@ -40,9 +42,9 @@ class ProviderManager():
             if mood_imitation_dialogs:
                 if len(mood_imitation_dialogs) % 2 != 0:
                     logger.error(f"{persona['name']} 对话风格对话格式不对，条数应该为偶数。")
-                    continue
+                    mood_imitation_dialogs = []
                 user_turn = True
-                for dialog in begin_dialogs:
+                for dialog in mood_imitation_dialogs:
                     role = "A" if user_turn else "B"
                     mid_processed += f"{role}: {dialog}\n"
                     if not user_turn:
@@ -61,6 +63,10 @@ class ProviderManager():
             except Exception as e:
                 logger.error(f"解析 Persona 配置失败：{e}")
         
+        if not self.selected_default_persona and len(self.personas) > 0:
+            # 默认选择第一个
+            self.selected_default_persona = self.personas[0]
+        
         
         self.provider_insts: List[Provider] = []
         '''加载的 Provider 的实例'''

astrbot/core/provider/provider.py

@@ -74,7 +74,7 @@ class Provider(AbstractProvider):
         if persistant_history:
             # 读取历史记录
             try:
-                for history in db_helper.get_llm_history(provider_type=provider_config['type']):
+                for history in db_helper.get_llm_history(provider_type=provider_config['id']):
                     self.session_memory[history.session_id] = json.loads(history.content)
             except BaseException as e:
                 logger.warning(f"读取 LLM 对话历史记录 失败：{e}。仍可正常使用。")

astrbot/core/provider/sources/gemini_source.py

@@ -260,10 +260,11 @@ class ProviderGoogleGenAI(Provider):
                     "role": "assistant",
                     "content": llm_response.completion_text
                 }]
-            self.db_helper.update_llm_history(session_id, json.dumps(self.session_memory[session_id]), self.provider_config['type'])
+            self.db_helper.update_llm_history(session_id, json.dumps(self.session_memory[session_id]), self.provider_config['id'])
         
     async def forget(self, session_id: str) -> bool:
         self.session_memory[session_id] = []
+        self.db_helper.update_llm_history(session_id, json.dumps(self.session_memory[session_id]), self.provider_config['id'])
         return True
 
     def get_current_key(self) -> str:

astrbot/core/provider/sources/llmtuner_source.py

@@ -118,10 +118,11 @@ class LLMTunerModelLoader(Provider):
                     "role": "assistant",
                     "content": llm_response.completion_text
                 }]
-            self.db_helper.update_llm_history(session_id, json.dumps(self.session_memory[session_id]), self.provider_config['type'])
+            self.db_helper.update_llm_history(session_id, json.dumps(self.session_memory[session_id]), self.provider_config['id'])
         
     async def forget(self, session_id):
         self.session_memory[session_id] = []
+        self.db_helper.update_llm_history(session_id, json.dumps(self.session_memory[session_id]), self.provider_config['id'])
         return True
 
     async def get_current_key(self):

astrbot/core/provider/sources/openai_source.py

@@ -72,31 +72,21 @@ class ProviderOpenAIOfficial(Provider):
         except NotFoundError as e:
             raise Exception(f"获取模型列表失败：{e}")
     
-    async def pop_record(self, session_id: str, pop_system_prompt: bool = False):
+    async def pop_record(self, session_id: str):
         '''
-        弹出第一条记录
+        弹出最早的一个对话
         '''
         if session_id not in self.session_memory:
             raise Exception("会话 ID 不存在")
 
-        if len(self.session_memory[session_id]) == 0:
-            return None
-
-        for i in range(len(self.session_memory[session_id])):
-            # 检查是否是 system prompt
-            if not pop_system_prompt and self.session_memory[session_id][i]['user']['role'] == "system":
-                # 如果只有一个 system prompt，才不删掉
-                f = False
-                for j in range(i+1, len(self.session_memory[session_id])):
-                    if self.session_memory[session_id][j]['user']['role'] == "system":
-                        f = True
-                        break
-                if not f:
-                    continue
-            record = self.session_memory[session_id].pop(i)
-            break
-
-        return record
+        if len(self.session_memory[session_id]) < 2:
+            return
+        
+        try:
+            self.session_memory[session_id].pop(0)
+            self.session_memory[session_id].pop(0)
+        except IndexError:
+            pass
     
     async def _query(self, payloads: dict, tools: FuncCall) -> LLMResponse:
         if tools:
@@ -104,20 +94,25 @@ 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:
-            if 'does not support Function Calling' \
-                or 'does not support tools' in e: # ollama 
+            # 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
         
         assert isinstance(completion, ChatCompletion)
         logger.debug(f"completion: {completion}")
@@ -129,14 +124,8 @@ class ProviderOpenAIOfficial(Provider):
         if choice.message.content:
             # text completion
             completion_text = str(choice.message.content).strip()
-            
-            # 适配 deepseek-r1 模型
-            if r'<think>' in completion_text:
-                completion_text = re.sub(r'<think>.*?</think>', '', completion_text, flags=re.DOTALL).strip()
-                # 可能有单标签情况
-                completion_text = completion_text.replace(r'<think>', '').replace(r'</think>', '').strip()
-            
-            return LLMResponse("assistant", completion_text)
+
+            return LLMResponse("assistant", completion_text, raw_completion=completion)
         elif choice.message.tool_calls:
             # tools call (function calling)
             args_ls = []
@@ -147,8 +136,9 @@ class ProviderOpenAIOfficial(Provider):
                         args = json.loads(tool_call.function.arguments)
                         args_ls.append(args)
                         func_name_ls.append(tool_call.function.name)
-            return LLMResponse(role="tool", tools_call_args=args_ls, tools_call_name=func_name_ls)
+            return LLMResponse(role="tool", tools_call_args=args_ls, tools_call_name=func_name_ls, raw_completion=completion)
         else:
+            logger.error(f"API 返回的 completion 无法解析：{completion}。")
             raise Exception("Internal Error")
 
     async def text_chat(
@@ -188,19 +178,22 @@ class ProviderOpenAIOfficial(Provider):
             if "maximum context length" in str(e):
                 retry_cnt = 10
                 while retry_cnt > 0:
-                    logger.warning(f"请求失败：{e}。上下文长度超过限制。尝试弹出最早的记录然后重试。")
+                    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:
-                        self.pop_record(session_id)
+                        await self.pop_record(session_id)
                         llm_response = await self._query(payloads, func_tool)
-                        break
+                        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):
                             retry_cnt -= 1
                         else:
                             raise e
             else:
+                logger.error(f"发生了错误。Provider 配置如下: {self.provider_config}")
                 raise e
-
+        
     
     async def save_history(self, contexts: List, new_record: dict, session_id: str, llm_response: LLMResponse):
         if llm_response.role == "assistant" and session_id:
@@ -219,10 +212,11 @@ class ProviderOpenAIOfficial(Provider):
                     "role": "assistant",
                     "content": llm_response.completion_text
                 }]
-            self.db_helper.update_llm_history(session_id, json.dumps(self.session_memory[session_id]), self.provider_config['type'])
+            self.db_helper.update_llm_history(session_id, json.dumps(self.session_memory[session_id]), self.provider_config['id'])
         
     async def forget(self, session_id: str) -> bool:
         self.session_memory[session_id] = []
+        self.db_helper.update_llm_history(session_id, json.dumps(self.session_memory[session_id]), self.provider_config['id'])
         return True
 
     def get_current_key(self) -> str:

astrbot/core/provider/sources/openai_tts_api_source.py

@@ -15,7 +15,7 @@ class ProviderOpenAITTSAPI(TTSProvider):
     ) -> None:
         super().__init__(provider_config, provider_settings)
         self.chosen_api_key = provider_config.get("api_key", "")
-        self.voice = provider_config.get("voice", "alloy")
+        self.voice = provider_config.get("openai-tts-voice", "alloy")
 
         self.client = AsyncOpenAI(
             api_key=self.chosen_api_key,

astrbot/core/star/register/__init__.py

@@ -7,6 +7,7 @@ from .star_handler import (
     register_regex,
     register_permission_type,
     register_on_llm_request,
+    register_on_llm_response,
     register_llm_tool,
     register_on_decorating_result,
     register_after_message_sent
@@ -21,6 +22,7 @@ __all__ = [
     'register_regex',
     'register_permission_type',
     'register_on_llm_request',
+    'register_on_llm_response',
     'register_llm_tool',
     'register_on_decorating_result',
     'register_after_message_sent'

astrbot/core/star/register/star_handler.py

@@ -139,6 +139,8 @@ def register_on_llm_request():
     
     Examples:
     ```py
+    from astrbot.api.provider import ProviderRequest
+    
     @on_llm_request()
     async def test(self, event: AstrMessageEvent, request: ProviderRequest) -> None:
         request.system_prompt += "你是一个猫娘..."
@@ -152,6 +154,27 @@ def register_on_llm_request():
     
     return decorator
 
+def register_on_llm_response():
+    '''当有 LLM 请求后的事件
+    
+    Examples:
+    ```py
+    from astrbot.api.provider import LLMResponse
+    
+    @on_llm_response()
+    async def test(self, event: AstrMessageEvent, response: LLMResponse) -> None:
+        ...
+    ```
+    
+    请务必接收两个参数：event, request
+    '''
+    def decorator(awaitable):
+        _ = get_handler_or_create(awaitable, EventType.OnLLMResponseEvent)
+        return awaitable
+    
+    return decorator
+
+
 def register_llm_tool(name: str = None):
     '''为函数调用（function-calling / tools-use）添加工具。
     

astrbot/core/star/star_handler.py

@@ -47,6 +47,7 @@ class EventType(enum.Enum):
     '''
     AdapterMessageEvent = enum.auto() # 收到适配器发来的消息
     OnLLMRequestEvent = enum.auto() # 收到 LLM 请求（可以是用户也可以是插件）
+    OnLLMResponseEvent = enum.auto() # LLM 响应后
     OnDecoratingResultEvent = enum.auto() # 发送消息前
     OnCallingFuncToolEvent = enum.auto() # 调用函数工具
     OnAfterMessageSentEvent = enum.auto() # 发送消息后

astrbot/core/utils/io.py

@@ -109,7 +109,7 @@ async def download_file(url: str, path: str, show_progress: bool = False):
     '''
     try:
         async with aiohttp.ClientSession(trust_env=True) as session:
-            async with session.get(url, timeout=120) as resp:
+            async with session.get(url, timeout=1800) as resp:
                 if resp.status != 200:
                     raise Exception(f"下载文件失败: {resp.status}")
                 total_size = int(resp.headers.get('content-length', 0))

astrbot/dashboard/routes/static_file.py

@@ -6,6 +6,10 @@ class StaticFileRoute(Route):
         index_ = ['/', '/auth/login', '/config', '/logs', '/extension', '/dashboard/default', '/project-atri', '/console', '/chat']
         for i in index_:
             self.app.add_url_rule(i, view_func=self.index)
+            
+        @self.app.errorhandler(404)
+        async def page_not_found(e):
+            return "404 Not found。如果你初次使用打开面板发现 404，请参考文档: https://astrbot.app/deploy/dashboard-404.html"
     
     async def index(self):
         return await self.app.send_static_file('index.html')

changelogs/v3.4.17.md

@@ -0,0 +1,11 @@
+# What's Changed
+
+- [beta] 支持群聊内基于概率的主动回复
+- openai tts 更换模型 #300
+- 增加模型响应后的插件钩子
+- 修复 相同type的provider共享了记忆
+- 优化 人格情景在发现格式不对时仍然加载而不是跳过 #282
+- 修复 Gemini函数调用时，parameters为空对象导致的错误 by @Camreishi
+- 修复 弹出记录报错的问题 #272
+- 优化 移除默认人格
+- 优化 未启用模型提供商时的异常处理

compose.yml

@@ -4,6 +4,8 @@ services:
   astrbot:
     image: soulter/astrbot:latest
     container_name: astrbot
-    network_mode: "host"
+    ports: 
+      - "6180-6200:6180-6200"
+      - "11451:11451"
     volumes:
-      - ./data:/AstrBot/data
+      - ./data:/AstrBot/data

packages/astrbot/long_term_memory.py

@@ -1,5 +1,6 @@
 import datetime
 import uuid
+import random
 import astrbot.api.star as star
 from astrbot.api.event import AstrMessageEvent
 from astrbot.api.platform import MessageType
@@ -8,7 +9,9 @@ from astrbot.api.message_components import Plain, Image
 from astrbot import logger
 from collections import defaultdict
 
-
+'''
+聊天记忆增强
+'''
 class LongTermMemory:
     def __init__(self, config: dict, context: star.Context):
         self.config = config
@@ -23,6 +26,13 @@ class LongTermMemory:
         self.image_caption = self.config["image_caption"]
         self.image_caption_prompt = self.config["image_caption_prompt"]
         
+        self.active_reply = self.config["active_reply"]
+        self.ar_method = self.active_reply["method"]
+        self.ar_possibility = self.active_reply["possibility_reply"]
+        self.ar_prompt = self.active_reply.get("prompt", "")
+        
+        self.put_history_to_prompt = self.config["put_history_to_prompt"]
+        
     async def remove_session(self, event: AstrMessageEvent) -> int:
         cnt = 0
         if event.unified_msg_origin in self.session_chats:
@@ -39,8 +49,27 @@ class LongTermMemory:
             persist=False,
         )
         return response.completion_text
+    
+    async def need_active_reply(self, event: AstrMessageEvent) -> bool:
+        if not self.active_reply:
+            return False
+        if event.get_message_type() != MessageType.GROUP_MESSAGE:
+            return False
+        
+        if event.is_at_or_wake_command:
+            # if the message is a command, let it pass
+            return False
+
+        match self.ar_method:
+            case "possibility_reply":
+                trig = random.random() < self.ar_possibility
+                return trig
+            
+        return False
+
 
     async def handle_message(self, event: AstrMessageEvent):
+        '''仅支持群聊'''
         if event.get_message_type() == MessageType.GROUP_MESSAGE:
             datetime_str = datetime.datetime.now().strftime("%H:%M:%S")
 
@@ -59,23 +88,33 @@ class LongTermMemory:
                             final_message += f" [Image: {caption}]"
                         except Exception as e:
                             logger.error(f"获取图片描述失败: {e}")
+                    else:
+                        final_message += " [Image]"
             logger.debug(f"ltm | {event.unified_msg_origin} | {final_message}")
             self.session_chats[event.unified_msg_origin].append(final_message)
             if len(self.session_chats[event.unified_msg_origin]) > self.max_cnt:
                 self.session_chats[event.unified_msg_origin].pop(0)
 
     async def on_req_llm(self, event: AstrMessageEvent, req: ProviderRequest):
+        '''当触发 LLM 请求前，调用此方法修改 req'''
         if event.unified_msg_origin not in self.session_chats:
             return
         
         chats_str = '\n---\n'.join(self.session_chats[event.unified_msg_origin])
-        req.system_prompt += "You are now in a chatroom. The chat history is as follows: \n"
-        req.system_prompt += chats_str
-        if self.image_caption:
-            req.system_prompt += (
-                "The images sent by the members are displayed in text form above."
-            )
-
+        
+        if self.put_history_to_prompt:
+            prompt = req.prompt
+            req.prompt = f"You are now in a chatroom. The chat history is as follows:\n{chats_str}"
+            req.prompt += f"\nNow, a new message is coming: `{prompt}`. Please react to it. Only output your response and do not output any other information."
+            req.contexts = [] # 清空上下文，当使用了群聊增强，所有聊天记录都在一个prompt中。
+        else:
+            req.system_prompt += "You are now in a chatroom. The chat history is as follows: \n"
+            req.system_prompt += chats_str
+            if self.image_caption:
+                req.system_prompt += (
+                    "The images sent by the members are displayed in text form above."
+                )
+            
     async def after_req_llm(self, event: AstrMessageEvent):
         if event.unified_msg_origin not in self.session_chats:
             return

packages/astrbot/main.py

@@ -5,7 +5,7 @@ import astrbot.api.star as star
 import astrbot.api.event.filter as filter
 from astrbot.api.event import AstrMessageEvent, MessageEventResult
 from astrbot.api import sp
-from astrbot.api.provider import Personality, ProviderRequest
+from astrbot.api.provider import Personality, ProviderRequest, LLMResponse
 from astrbot.api.platform import MessageType
 from astrbot.core.utils.io import download_dashboard, get_dashboard_version
 from astrbot.core.config.default import VERSION
@@ -25,7 +25,7 @@ class Main(star.Star):
         self.enable_datetime = cfg['provider_settings']["datetime_system_prompt"]
         
         self.ltm = None
-        if self.context.get_config()['provider_ltm_settings']['group_icl_enable']:
+        if self.context.get_config()['provider_ltm_settings']['group_icl_enable'] or self.context.get_config()['provider_ltm_settings']['active_reply']['enable']:
             try:
                 self.ltm = LongTermMemory(self.context.get_config()['provider_ltm_settings'], self.context)
             except BaseException as e:
@@ -203,6 +203,10 @@ UID: {user_id} 此 ID 可用于设置管理员。/op <UID> 授权管理员, /deo
     async def provider(self, event: AstrMessageEvent, idx: int = None):
         '''查看或者切换 LLM Provider'''
         
+        if not self.context.get_using_provider():
+            event.set_result(MessageEventResult().message("未找到任何 LLM 提供商。请先配置。"))
+            return
+        
         if idx is None:
             ret = "## 当前载入的 LLM 提供商\n"
             for idx, llm in enumerate(self.context.get_all_providers()):
@@ -227,6 +231,11 @@ UID: {user_id} 此 ID 可用于设置管理员。/op <UID> 授权管理员, /deo
 
     @filter.command("reset")
     async def reset(self, message: AstrMessageEvent):
+        
+        if not self.context.get_using_provider():
+            message.set_result(MessageEventResult().message("未找到任何 LLM 提供商。请先配置。"))
+            return
+        
         await self.context.get_using_provider().forget(message.session_id)
         ret = "清除会话 LLM 聊天历史成功。"
         if self.ltm:
@@ -237,6 +246,12 @@ UID: {user_id} 此 ID 可用于设置管理员。/op <UID> 授权管理员, /deo
 
     @filter.command("model")
     async def model_ls(self, message: AstrMessageEvent, idx_or_name: Union[int, str] = None):
+                
+        if not self.context.get_using_provider():
+            message.set_result(MessageEventResult().message("未找到任何 LLM 提供商。请先配置。"))
+            return
+        
+        
         if idx_or_name is None:
             models = []
             try:
@@ -277,6 +292,12 @@ UID: {user_id} 此 ID 可用于设置管理员。/op <UID> 授权管理员, /deo
 
     @filter.command("history")
     async def his(self, message: AstrMessageEvent, page: int = 1):
+        
+                
+        if not self.context.get_using_provider():
+            message.set_result(MessageEventResult().message("未找到任何 LLM 提供商。请先配置。"))
+            return
+        
         size_per_page = 3
         contexts, total_pages = await self.context.get_using_provider().get_human_readable_context(message.session_id, page, size_per_page)
 
@@ -296,6 +317,10 @@ UID: {user_id} 此 ID 可用于设置管理员。/op <UID> 授权管理员, /deo
     @filter.permission_type(filter.PermissionType.ADMIN)
     @filter.command("key")
     async def key(self, message: AstrMessageEvent, index: int=None):
+                
+        if not self.context.get_using_provider():
+            message.set_result(MessageEventResult().message("未找到任何 LLM 提供商。请先配置。"))
+            return
         
         if index is None:
             keys_data = self.context.get_using_provider().get_keys()
@@ -324,6 +349,12 @@ UID: {user_id} 此 ID 可用于设置管理员。/op <UID> 授权管理员, /deo
 
     @filter.command("persona")
     async def persona(self, message: AstrMessageEvent):
+                
+        if not self.context.get_using_provider():
+            message.set_result(MessageEventResult().message("未找到任何 LLM 提供商。请先配置。"))
+            return
+        
+        
         l = message.message_str.split(" ")
         
         curr_persona_name = "无"
@@ -337,6 +368,7 @@ UID: {user_id} 此 ID 可用于设置管理员。/op <UID> 授权管理员, /deo
 - 设置人格情景: `/persona 人格名`, 如 /persona 编剧
 - 人格情景列表: `/persona list`
 - 人格情景详细信息: `/persona view 人格名`
+- 取消人格: `/persona unset`
 
 当前人格情景: {curr_persona_name}
 
@@ -362,6 +394,9 @@ UID: {user_id} 此 ID 可用于设置管理员。/op <UID> 授权管理员, /deo
             else:
                 msg = f"人格{ps}不存在"
             message.set_result(MessageEventResult().message(msg))
+        elif l[1] == "unset":
+            self.context.get_using_provider().curr_personality = None
+            message.set_result(MessageEventResult().message("取消人格成功。"))
         else:
             ps = "".join(l[1:]).strip()
             if persona := next(builtins.filter(
@@ -421,12 +456,39 @@ UID: {user_id} 此 ID 可用于设置管理员。/op <UID> 授权管理员, /deo
             
     @filter.platform_adapter_type(filter.PlatformAdapterType.ALL)
     async def on_message(self, event: AstrMessageEvent):
-        '''长期记忆'''
+        '''群聊记忆增强'''
         if self.ltm:
-            try:
-                await self.ltm.handle_message(event)
-            except BaseException as e:
-                logger.error(e)
+            need_active = await self.ltm.need_active_reply(event)
+                        
+            group_icl_enable = self.context.get_config()['provider_ltm_settings']['group_icl_enable']
+            if group_icl_enable:
+                '''记录对话'''
+                try:
+                    await self.ltm.handle_message(event)
+                except BaseException as e:
+                    logger.error(e)
+                
+            if need_active:
+                '''主动回复'''
+                provider = self.context.get_using_provider()
+                if not provider:
+                    logger.error("未找到任何 LLM 提供商。请先配置。无法主动回复")
+                    return
+                try:
+                    session_provider_context = provider.session_memory.get(event.session_id)
+                    
+                    prompt = self.ltm.ar_prompt
+                    if not prompt:
+                        prompt = event.message_str
+                    
+                    yield event.request_llm(
+                        prompt=prompt,
+                        func_tool_manager=self.context.get_llm_tool_manager(),
+                        session_id=event.session_id,
+                        contexts=session_provider_context if session_provider_context else []
+                    )
+                except BaseException as e:
+                    logger.error(f"主动回复失败: {e}")
     
     
     @filter.on_llm_request()

packages/web_searcher/engines/google.py

@@ -8,7 +8,8 @@ from typing import List
 class Google(SearchEngine):
     def __init__(self) -> None:
         super().__init__()
-        self.proxy = os.environ.get("HTTPS_PROXY")
+        self.proxy = os.environ.get("https_proxy")
+        print(f"Google Search using proxy: {self.proxy}")
     
     async def search(self, query: str, num_results: int) -> List[SearchResult]:
         results = []

packages/web_searcher/main.py

@@ -22,6 +22,8 @@ class Main(star.Star):
         self.sogo_search = Sogo()
         self.google = Google()
         
+        self.websearch_link = self.context.get_config()['provider_settings'].get('web_search_link', False)
+        
     async def initialize(self):
         websearch = self.context.get_config()['provider_settings']['web_search']
         if websearch:
@@ -109,8 +111,17 @@ class Main(star.Star):
             except BaseException:
                 site_result = ""
             site_result = site_result[:700] + "..." if len(site_result) > 700 else site_result
-            ret += f"{idx}. {i.title} \n{i.snippet}\n{site_result}\n\n"
+            
+            header = f"{idx}. {i.title} "
+            
+            if self.websearch_link and i.url:
+                header += i.url
+            
+            ret += f"{header}\n{i.snippet}\n{site_result}\n\n"
             idx += 1
+            
+        if self.websearch_link:
+            ret += "针对问题，请根据上面的结果分点总结，并且在结尾处附上对应内容的参考链接（如有）。"
         
         return ret