diff --git a/src/chat/heart_flow/heartflow_message_processor.py b/src/chat/heart_flow/heartflow_message_processor.py index bd9f0f81..1d90e468 100644 --- a/src/chat/heart_flow/heartflow_message_processor.py +++ b/src/chat/heart_flow/heartflow_message_processor.py @@ -72,16 +72,15 @@ class HeartFCMessageReceiver: chat = message.chat_stream # 2. 兴趣度计算与更新 - interested_rate, keywords = await _calculate_interest(message) + _, keywords = await _calculate_interest(message) await self.storage.store_message(message, chat) heartflow_chat: HeartFChatting = await heartflow.get_or_create_heartflow_chat(chat.stream_id) # type: ignore - # subheartflow.add_message_to_normal_chat_cache(message, interested_rate, is_mentioned) if global_config.mood.enable_mood: chat_mood = mood_manager.get_mood_by_chat_id(heartflow_chat.stream_id) - asyncio.create_task(chat_mood.update_mood_by_message(message, interested_rate)) + asyncio.create_task(chat_mood.update_mood_by_message(message)) # 3. 日志记录 mes_name = chat.group_info.group_name if chat.group_info else "私聊" @@ -109,7 +108,7 @@ class HeartFCMessageReceiver: replace_bot_name=True, ) - logger.info(f"[{mes_name}]{userinfo.user_nickname}:{processed_plain_text}[{interested_rate:.2f}]") # type: ignore + logger.info(f"[{mes_name}]{userinfo.user_nickname}:{processed_plain_text}") # type: ignore _ = Person.register_person( platform=message.message_info.platform, # type: ignore diff --git a/src/config/api_ada_configs.py b/src/config/api_ada_configs.py index bd881bfd..3fc9c878 100644 --- a/src/config/api_ada_configs.py +++ b/src/config/api_ada_configs.py @@ -102,9 +102,6 @@ class ModelTaskConfig(ConfigBase): replyer: TaskConfig """normal_chat首要回复模型模型配置""" - emotion: TaskConfig - """情绪模型配置""" - vlm: TaskConfig """视觉语言模型配置""" diff --git a/src/mood/mood_manager.py b/src/mood/mood_manager.py index 16784230..ed4b5f56 100644 --- a/src/mood/mood_manager.py +++ b/src/mood/mood_manager.py @@ -62,11 +62,11 @@ class ChatMood: self.regression_count: int = 0 - self.mood_model = LLMRequest(model_set=model_config.model_task_config.emotion, request_type="mood") + self.mood_model = LLMRequest(model_set=model_config.model_task_config.utils, request_type="mood") self.last_change_time: float = 0 - async def update_mood_by_message(self, message: MessageRecv, interested_rate: float): + async def update_mood_by_message(self, message: MessageRecv): self.regression_count = 0 during_last_time = message.message_info.time - self.last_change_time # type: ignore @@ -74,10 +74,9 @@ class ChatMood: base_probability = 0.05 time_multiplier = 4 * (1 - math.exp(-0.01 * during_last_time)) - if interested_rate <= 0: - interest_multiplier = 0 - else: - interest_multiplier = 2 * math.pow(interested_rate, 0.25) + # 基于消息长度计算基础兴趣度 + message_length = len(message.message_content.content or "") + interest_multiplier = min(2.0, 1.0 + message_length / 100) logger.debug( f"base_probability: {base_probability}, time_multiplier: {time_multiplier}, interest_multiplier: {interest_multiplier}" @@ -90,7 +89,7 @@ class ChatMood: return logger.debug( - f"{self.log_prefix} 更新情绪状态，感兴趣度: {interested_rate:.2f}, 更新概率: {update_probability:.2f}" + f"{self.log_prefix} 更新情绪状态，更新概率: {update_probability:.2f}" ) message_time: float = message.message_info.time # type: ignore diff --git a/template/model_config_template.toml b/template/model_config_template.toml index 76f09955..f7be4325 100644 --- a/template/model_config_template.toml +++ b/template/model_config_template.toml @@ -1,5 +1,5 @@ [inner] -version = "1.6.0" +version = "1.7.0" # 配置文件版本号迭代规则同bot_config.toml @@ -12,14 +12,14 @@ max_retry = 2 # 最大重试次数（单个模型API timeout = 30 # API请求超时时间（单位：秒） retry_interval = 10 # 重试间隔时间（单位：秒） -[[api_providers]] # SiliconFlow的API服务商配置 -name = "SiliconFlow" -base_url = "https://api.siliconflow.cn/v1" -api_key = "your-siliconflow-api-key" +[[api_providers]] # 阿里 百炼 API服务商配置 +name = "BaiLian" +base_url = "https://dashscope.aliyuncs.com/compatible-mode/v1" +api_key = "your-bailian-key" client_type = "openai" max_retry = 2 -timeout = 30 -retry_interval = 10 +timeout = 15 +retry_interval = 5 [[api_providers]] # 特殊：Google的Gimini使用特殊API，与OpenAI格式不兼容，需要配置client为"gemini" name = "Google" @@ -30,14 +30,14 @@ max_retry = 2 timeout = 30 retry_interval = 10 -[[api_providers]] # 阿里 百炼 API服务商配置 -name = "BaiLian" -base_url = "https://dashscope.aliyuncs.com/compatible-mode/v1" -api_key = "your-bailian-key" +[[api_providers]] # SiliconFlow的API服务商配置 +name = "SiliconFlow" +base_url = "https://api.siliconflow.cn/v1" +api_key = "your-siliconflow-api-key" client_type = "openai" max_retry = 2 -timeout = 15 -retry_interval = 5 +timeout = 60 +retry_interval = 10 [[models]] # 模型（可以配置多个） @@ -93,8 +93,8 @@ price_in = 0 price_out = 0 -[model_task_config.utils] # 在麦麦的一些组件中使用的模型，例如表情包模块，取名模块，关系模块，是麦麦必须的模型 -model_list = ["siliconflow-deepseek-v3"] # 使用的模型列表，每个子项对应上面的模型名称(name) +[model_task_config.utils] # 在麦麦的一些组件中使用的模型，例如表情包模块，取名模块，关系模块，麦麦的情绪变化等，是麦麦必须的模型 +model_list = ["siliconflow-deepseek-v3","qwen3-30b"] # 使用的模型列表，每个子项对应上面的模型名称(name) temperature = 0.2 # 模型温度，新V3建议0.1-0.3 max_tokens = 800 # 最大输出token数 @@ -103,6 +103,11 @@ model_list = ["qwen3-8b","qwen3-30b"] temperature = 0.7 max_tokens = 800 +[model_task_config.tool_use] #工具调用模型，需要使用支持工具调用的模型 +model_list = ["qwen3-30b"] +temperature = 0.7 +max_tokens = 800 + [model_task_config.replyer] # 首要回复模型，还用于表达器和表达方式学习 model_list = ["siliconflow-deepseek-v3"] temperature = 0.3 # 模型温度，新V3建议0.1-0.3 @@ -113,11 +118,6 @@ model_list = ["siliconflow-deepseek-v3"] temperature = 0.3 max_tokens = 800 -[model_task_config.emotion] #负责麦麦的情绪变化 -model_list = ["qwen3-30b"] -temperature = 0.7 -max_tokens = 800 - [model_task_config.vlm] # 图像识别模型 model_list = ["qwen2.5-vl-72b"] max_tokens = 800 @@ -125,11 +125,6 @@ max_tokens = 800 [model_task_config.voice] # 语音识别模型 model_list = ["sensevoice-small"] -[model_task_config.tool_use] #工具调用模型，需要使用支持工具调用的模型 -model_list = ["qwen3-30b"] -temperature = 0.7 -max_tokens = 800 - #嵌入模型 [model_task_config.embedding] model_list = ["bge-m3"]