From 0391111c82d3ba7cb8ade890af793128cb7c476f Mon Sep 17 00:00:00 2001 From: SengokuCola <1026294844@qq.com> Date: Tue, 27 May 2025 14:28:41 +0800 Subject: [PATCH] =?UTF-8?q?feat=EF=BC=9A=E6=8B=86=E5=88=86=E9=87=8D?= =?UTF-8?q?=E5=91=BD=E5=90=8D=E6=A8=A1=E5=9E=8B=E9=85=8D=E7=BD=AE=EF=BC=8C?= =?UTF-8?q?=E4=BF=AE=E5=A4=8D=E5=8A=A8=E4=BD=9C=E6=81=A2=E5=A4=8D=E9=97=AE?= =?UTF-8?q?=E9=A2=98?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../expressors/default_expressor.py | 6 +- .../info_processors/action_processor.py | 3 - .../info_processors/mind_processor.py | 6 +- .../info_processors/self_processor.py | 6 +- .../info_processors/tool_processor.py | 4 +- .../working_memory_processor.py | 6 +- src/chat/focus_chat/memory_activator.py | 2 +- .../focus_chat/planners/action_manager.py | 15 ++--- src/chat/focus_chat/planners/planner.py | 12 ++-- .../working_memory/memory_manager.py | 2 +- src/chat/heart_flow/background_tasks.py | 36 +++++------ .../observation/chatting_observation.py | 4 -- src/chat/memory_system/Hippocampus.py | 10 ++- src/chat/normal_chat/normal_chat_generator.py | 4 +- src/chat/utils/utils_image.py | 3 +- src/config/official_configs.py | 41 +++++++----- src/llm_models/utils_model.py | 5 +- src/tools/tool_use.py | 9 --- template/bot_config_template.toml | 63 +++++++++++-------- 19 files changed, 119 insertions(+), 118 deletions(-) diff --git a/src/chat/focus_chat/expressors/default_expressor.py b/src/chat/focus_chat/expressors/default_expressor.py index 2d0d1f35b..a9166f67a 100644 --- a/src/chat/focus_chat/expressors/default_expressor.py +++ b/src/chat/focus_chat/expressors/default_expressor.py @@ -78,10 +78,10 @@ class DefaultExpressor: self.log_prefix = "expressor" # TODO: API-Adapter修改标记 self.express_model = LLMRequest( - model=global_config.model.normal, - temperature=global_config.model.normal["temp"], + model=global_config.model.focus_expressor, + temperature=global_config.model.focus_expressor["temp"], max_tokens=256, - request_type="response_heartflow", + request_type="focus_expressor", ) self.heart_fc_sender = HeartFCSender() diff --git a/src/chat/focus_chat/info_processors/action_processor.py b/src/chat/focus_chat/info_processors/action_processor.py index c2fa6dbb8..1f05ac842 100644 --- a/src/chat/focus_chat/info_processors/action_processor.py +++ b/src/chat/focus_chat/info_processors/action_processor.py @@ -27,9 +27,6 @@ class ActionProcessor(BaseProcessor): """初始化观察处理器""" super().__init__() # TODO: API-Adapter修改标记 - self.model_summary = LLMRequest( - model=global_config.model.observation, temperature=0.7, max_tokens=300, request_type="chat_observation" - ) async def process_info( self, diff --git a/src/chat/focus_chat/info_processors/mind_processor.py b/src/chat/focus_chat/info_processors/mind_processor.py index 8e911acec..2a1642ade 100644 --- a/src/chat/focus_chat/info_processors/mind_processor.py +++ b/src/chat/focus_chat/info_processors/mind_processor.py @@ -71,10 +71,10 @@ class MindProcessor(BaseProcessor): self.subheartflow_id = subheartflow_id self.llm_model = LLMRequest( - model=global_config.model.sub_heartflow, - temperature=global_config.model.sub_heartflow["temp"], + model=global_config.model.focus_chat_mind, + temperature=global_config.model.focus_chat_mind["temp"], max_tokens=800, - request_type="sub_heart_flow", + request_type="focus_chat_mind", ) self.current_mind = "" diff --git a/src/chat/focus_chat/info_processors/self_processor.py b/src/chat/focus_chat/info_processors/self_processor.py index c4c4ead54..6589e2f7a 100644 --- a/src/chat/focus_chat/info_processors/self_processor.py +++ b/src/chat/focus_chat/info_processors/self_processor.py @@ -54,10 +54,10 @@ class SelfProcessor(BaseProcessor): self.subheartflow_id = subheartflow_id self.llm_model = LLMRequest( - model=global_config.model.sub_heartflow, - temperature=global_config.model.sub_heartflow["temp"], + model=global_config.model.focus_self_recognize, + temperature=global_config.model.focus_self_recognize["temp"], max_tokens=800, - request_type="self_identify", + request_type="focus_self_identify", ) name = chat_manager.get_stream_name(self.subheartflow_id) diff --git a/src/chat/focus_chat/info_processors/tool_processor.py b/src/chat/focus_chat/info_processors/tool_processor.py index 39ac8dc67..b1568cf33 100644 --- a/src/chat/focus_chat/info_processors/tool_processor.py +++ b/src/chat/focus_chat/info_processors/tool_processor.py @@ -49,9 +49,9 @@ class ToolProcessor(BaseProcessor): self.subheartflow_id = subheartflow_id self.log_prefix = f"[{subheartflow_id}:ToolExecutor] " self.llm_model = LLMRequest( - model=global_config.model.tool_use, + model=global_config.model.focus_tool_use, max_tokens=500, - request_type="tool_execution", + request_type="focus_tool", ) self.structured_info = [] diff --git a/src/chat/focus_chat/info_processors/working_memory_processor.py b/src/chat/focus_chat/info_processors/working_memory_processor.py index cceb16235..d7e3d83e7 100644 --- a/src/chat/focus_chat/info_processors/working_memory_processor.py +++ b/src/chat/focus_chat/info_processors/working_memory_processor.py @@ -61,10 +61,10 @@ class WorkingMemoryProcessor(BaseProcessor): self.subheartflow_id = subheartflow_id self.llm_model = LLMRequest( - model=global_config.model.sub_heartflow, - temperature=global_config.model.sub_heartflow["temp"], + model=global_config.model.focus_chat_mind, + temperature=global_config.model.focus_chat_mind["temp"], max_tokens=800, - request_type="working_memory", + request_type="focus_working_memory", ) name = chat_manager.get_stream_name(self.subheartflow_id) diff --git a/src/chat/focus_chat/memory_activator.py b/src/chat/focus_chat/memory_activator.py index 0d5d63229..0f75d09ed 100644 --- a/src/chat/focus_chat/memory_activator.py +++ b/src/chat/focus_chat/memory_activator.py @@ -36,7 +36,7 @@ class MemoryActivator: def __init__(self): # TODO: API-Adapter修改标记 self.summary_model = LLMRequest( - model=global_config.model.summary, temperature=0.7, max_tokens=50, request_type="chat_observation" + model=global_config.model.memory_summary, temperature=0.7, max_tokens=50, request_type="chat_observation" ) self.running_memory = [] diff --git a/src/chat/focus_chat/planners/action_manager.py b/src/chat/focus_chat/planners/action_manager.py index 6cf8de6d9..62db09a96 100644 --- a/src/chat/focus_chat/planners/action_manager.py +++ b/src/chat/focus_chat/planners/action_manager.py @@ -28,8 +28,7 @@ class ActionManager: self._registered_actions: Dict[str, ActionInfo] = {} # 当前正在使用的动作集合，默认加载默认动作 self._using_actions: Dict[str, ActionInfo] = {} - # 临时备份原始使用中的动作 - self._original_actions_backup: Optional[Dict[str, ActionInfo]] = None + # 默认动作集，仅作为快照，用于恢复默认 self._default_actions: Dict[str, ActionInfo] = {} @@ -278,22 +277,18 @@ class ActionManager: return True def temporarily_remove_actions(self, actions_to_remove: List[str]) -> None: - """临时移除使用集中的指定动作，备份原始使用集""" - if self._original_actions_backup is None: - self._original_actions_backup = self._using_actions.copy() + """临时移除使用集中的指定动作""" for name in actions_to_remove: self._using_actions.pop(name, None) def restore_actions(self) -> None: - """恢复之前备份的原始使用集""" - if self._original_actions_backup is not None: - self._using_actions = self._original_actions_backup.copy() - self._original_actions_backup = None + """恢复到默认动作集""" + logger.debug(f"恢复动作集: 从 {list(self._using_actions.keys())} 恢复到默认动作集 {list(self._default_actions.keys())}") + self._using_actions = self._default_actions.copy() def restore_default_actions(self) -> None: """恢复默认动作集到使用集""" self._using_actions = self._default_actions.copy() - self._original_actions_backup = None def get_action(self, action_name: str) -> Optional[Type[BaseAction]]: """ diff --git a/src/chat/focus_chat/planners/planner.py b/src/chat/focus_chat/planners/planner.py index 57c83cff6..576e89794 100644 --- a/src/chat/focus_chat/planners/planner.py +++ b/src/chat/focus_chat/planners/planner.py @@ -78,9 +78,9 @@ class ActionPlanner: self.log_prefix = log_prefix # LLM规划器配置 self.planner_llm = LLMRequest( - model=global_config.model.plan, + model=global_config.model.focus_planner, max_tokens=1000, - request_type="action_planning", # 用于动作规划 + request_type="focus_planner", # 用于动作规划 ) self.action_manager = action_manager @@ -161,6 +161,10 @@ class ActionPlanner: action = "no_reply" reasoning = "没有可用的动作" if not current_available_actions else "只有no_reply动作可用，跳过规划" logger.info(f"{self.log_prefix}{reasoning}") + self.action_manager.restore_actions() + logger.debug( + f"{self.log_prefix}恢复到默认动作集, 当前可用: {list(self.action_manager.get_using_actions().keys())}" + ) return { "action_result": {"action_type": action, "action_data": action_data, "reasoning": reasoning}, "current_mind": current_mind, @@ -241,10 +245,10 @@ class ActionPlanner: f"{self.log_prefix}规划器Prompt:\n{prompt}\n\n决策动作:{action},\n动作信息: '{action_data}'\n理由: {reasoning}" ) - # 恢复原始动作集 + # 恢复到默认动作集 self.action_manager.restore_actions() logger.debug( - f"{self.log_prefix}恢复了原始动作集, 当前可用: {list(self.action_manager.get_using_actions().keys())}" + f"{self.log_prefix}恢复到默认动作集, 当前可用: {list(self.action_manager.get_using_actions().keys())}" ) action_result = {"action_type": action, "action_data": action_data, "reasoning": reasoning} diff --git a/src/chat/focus_chat/working_memory/memory_manager.py b/src/chat/focus_chat/working_memory/memory_manager.py index 2ee8a36de..0157e4f8d 100644 --- a/src/chat/focus_chat/working_memory/memory_manager.py +++ b/src/chat/focus_chat/working_memory/memory_manager.py @@ -33,7 +33,7 @@ class MemoryManager: self._id_map: Dict[str, MemoryItem] = {} self.llm_summarizer = LLMRequest( - model=global_config.model.summary, temperature=0.3, max_tokens=512, request_type="memory_summarization" + model=global_config.model.focus_working_memory, temperature=0.3, max_tokens=512, request_type="memory_summarization" ) @property diff --git a/src/chat/heart_flow/background_tasks.py b/src/chat/heart_flow/background_tasks.py index 4d2438b6f..4e4d502bd 100644 --- a/src/chat/heart_flow/background_tasks.py +++ b/src/chat/heart_flow/background_tasks.py @@ -88,34 +88,34 @@ class BackgroundTaskManager: f"聊天状态更新任务已启动 间隔:{STATE_UPDATE_INTERVAL_SECONDS}s", "_state_update_task", ), - ( - self._run_cleanup_cycle, - "info", - f"清理任务已启动 间隔:{CLEANUP_INTERVAL_SECONDS}s", - "_cleanup_task", - ), - # 新增私聊激活任务配置 - ( - # Use lambda to pass the interval to the runner function - lambda: self._run_private_chat_activation_cycle(PRIVATE_CHAT_ACTIVATION_CHECK_INTERVAL_SECONDS), - "debug", - f"私聊激活检查任务已启动 间隔:{PRIVATE_CHAT_ACTIVATION_CHECK_INTERVAL_SECONDS}s", - "_private_chat_activation_task", - ), ] - # 根据 chat_mode 条件添加专注评估任务 + # 根据 chat_mode 条件添加其他任务 if not (global_config.chat.chat_mode == "normal"): - task_configs.append( + task_configs.extend([ + ( + self._run_cleanup_cycle, + "info", + f"清理任务已启动 间隔:{CLEANUP_INTERVAL_SECONDS}s", + "_cleanup_task", + ), + # 新增私聊激活任务配置 + ( + # Use lambda to pass the interval to the runner function + lambda: self._run_private_chat_activation_cycle(PRIVATE_CHAT_ACTIVATION_CHECK_INTERVAL_SECONDS), + "debug", + f"私聊激活检查任务已启动 间隔:{PRIVATE_CHAT_ACTIVATION_CHECK_INTERVAL_SECONDS}s", + "_private_chat_activation_task", + ), ( self._run_into_focus_cycle, "debug", # 设为debug，避免过多日志 f"专注评估任务已启动 间隔:{INTEREST_EVAL_INTERVAL_SECONDS}s", "_into_focus_task", ) - ) + ]) else: - logger.info("聊天模式为 normal，跳过启动专注评估任务") + logger.info("聊天模式为 normal，跳过启动清理任务、私聊激活任务和专注评估任务") # 统一启动所有任务 for task_func, log_level, log_msg, task_attr_name in task_configs: diff --git a/src/chat/heart_flow/observation/chatting_observation.py b/src/chat/heart_flow/observation/chatting_observation.py index b43074fa0..4264a76c0 100644 --- a/src/chat/heart_flow/observation/chatting_observation.py +++ b/src/chat/heart_flow/observation/chatting_observation.py @@ -66,10 +66,6 @@ class ChattingObservation(Observation): self.oldest_messages = [] self.oldest_messages_str = "" self.compressor_prompt = "" - # TODO: API-Adapter修改标记 - self.model_summary = LLMRequest( - model=global_config.model.observation, temperature=0.7, max_tokens=300, request_type="chat_observation" - ) async def initialize(self): self.is_group_chat, self.chat_target_info = await get_chat_type_and_target_info(self.chat_id) diff --git a/src/chat/memory_system/Hippocampus.py b/src/chat/memory_system/Hippocampus.py index d7a13bfe4..9424706e2 100644 --- a/src/chat/memory_system/Hippocampus.py +++ b/src/chat/memory_system/Hippocampus.py @@ -193,7 +193,6 @@ class MemoryGraph: class Hippocampus: def __init__(self): self.memory_graph = MemoryGraph() - self.llm_topic_judge = None self.model_summary = None self.entorhinal_cortex = None self.parahippocampal_gyrus = None @@ -205,8 +204,7 @@ class Hippocampus: # 从数据库加载记忆图 self.entorhinal_cortex.sync_memory_from_db() # TODO: API-Adapter修改标记 - self.llm_topic_judge = LLMRequest(global_config.model.topic_judge, request_type="memory") - self.model_summary = LLMRequest(global_config.model.summary, request_type="memory") + self.model_summary = LLMRequest(global_config.model.memory_summary, request_type="memory") def get_all_node_names(self) -> list: """获取记忆图中所有节点的名字列表""" @@ -344,7 +342,7 @@ class Hippocampus: # 使用LLM提取关键词 topic_num = min(5, max(1, int(len(text) * 0.1))) # 根据文本长度动态调整关键词数量 # logger.info(f"提取关键词数量: {topic_num}") - topics_response = await self.llm_topic_judge.generate_response(self.find_topic_llm(text, topic_num)) + topics_response = await self.model_summary.generate_response(self.find_topic_llm(text, topic_num)) # 提取关键词 keywords = re.findall(r"<([^>]+)>", topics_response[0]) @@ -699,7 +697,7 @@ class Hippocampus: # 使用LLM提取关键词 topic_num = min(5, max(1, int(len(text) * 0.1))) # 根据文本长度动态调整关键词数量 # logger.info(f"提取关键词数量: {topic_num}") - topics_response = await self.llm_topic_judge.generate_response(self.find_topic_llm(text, topic_num)) + topics_response = await self.model_summary.generate_response(self.find_topic_llm(text, topic_num)) # 提取关键词 keywords = re.findall(r"<([^>]+)>", topics_response[0]) @@ -1126,7 +1124,7 @@ class ParahippocampalGyrus: # 2. 使用LLM提取关键主题 topic_num = self.hippocampus.calculate_topic_num(input_text, compress_rate) - topics_response = await self.hippocampus.llm_topic_judge.generate_response( + topics_response = await self.hippocampus.model_summary.generate_response( self.hippocampus.find_topic_llm(input_text, topic_num) ) diff --git a/src/chat/normal_chat/normal_chat_generator.py b/src/chat/normal_chat/normal_chat_generator.py index 04be8b3a7..7fa6b0321 100644 --- a/src/chat/normal_chat/normal_chat_generator.py +++ b/src/chat/normal_chat/normal_chat_generator.py @@ -17,7 +17,7 @@ class NormalChatGenerator: def __init__(self): # TODO: API-Adapter修改标记 self.model_reasoning = LLMRequest( - model=global_config.model.reasoning, + model=global_config.model.normal_chat_1, temperature=0.7, max_tokens=3000, request_type="response_reasoning", @@ -30,7 +30,7 @@ class NormalChatGenerator: ) self.model_sum = LLMRequest( - model=global_config.model.summary, temperature=0.7, max_tokens=3000, request_type="relation" + model=global_config.model.memory_summary, temperature=0.7, max_tokens=3000, request_type="relation" ) self.current_model_type = "r1" # 默认使用 R1 self.current_model_name = "unknown model" diff --git a/src/chat/utils/utils_image.py b/src/chat/utils/utils_image.py index ea27ff1d9..abd99aa24 100644 --- a/src/chat/utils/utils_image.py +++ b/src/chat/utils/utils_image.py @@ -130,6 +130,7 @@ class ImageManager: # 根据配置决定是否保存图片 if global_config.emoji.save_emoji: # 生成文件名和路径 + logger.debug(f"保存表情包: {image_hash}") current_timestamp = time.time() filename = f"{int(current_timestamp)}_{image_hash[:8]}.{image_format}" emoji_dir = os.path.join(self.IMAGE_DIR, "emoji") @@ -156,7 +157,7 @@ class ImageManager: description=description, timestamp=current_timestamp, ) - logger.trace(f"保存表情包元数据: {file_path}") + # logger.debug(f"保存表情包元数据: {file_path}") except Exception as e: logger.error(f"保存表情包文件或元数据失败: {str(e)}") diff --git a/src/config/official_configs.py b/src/config/official_configs.py index 778c34aef..a35026e53 100644 --- a/src/config/official_configs.py +++ b/src/config/official_configs.py @@ -178,10 +178,10 @@ class EmojiConfig(ConfigBase): check_interval: int = 120 """表情包检查间隔（分钟）""" - save_pic: bool = False + save_pic: bool = True """是否保存图片""" - save_emoji: bool = False + save_emoji: bool = True """是否保存表情包""" cache_emoji: bool = True @@ -384,27 +384,33 @@ class ModelConfig(ConfigBase): normal: dict[str, Any] = field(default_factory=lambda: {}) """普通模型配置""" - topic_judge: dict[str, Any] = field(default_factory=lambda: {}) - """主题判断模型配置""" - - summary: dict[str, Any] = field(default_factory=lambda: {}) - """摘要模型配置""" + memory_summary: dict[str, Any] = field(default_factory=lambda: {}) + """记忆的概括模型配置""" vlm: dict[str, Any] = field(default_factory=lambda: {}) """视觉语言模型配置""" - heartflow: dict[str, Any] = field(default_factory=lambda: {}) - """心流模型配置""" - observation: dict[str, Any] = field(default_factory=lambda: {}) """观察模型配置""" - sub_heartflow: dict[str, Any] = field(default_factory=lambda: {}) - """子心流模型配置""" - - plan: dict[str, Any] = field(default_factory=lambda: {}) - """计划模型配置""" + focus_working_memory: dict[str, Any] = field(default_factory=lambda: {}) + """专注工作记忆模型配置""" + + focus_chat_mind: dict[str, Any] = field(default_factory=lambda: {}) + """专注聊天规划模型配置""" + + focus_self_recognize: dict[str, Any] = field(default_factory=lambda: {}) + """专注自我识别模型配置""" + + focus_tool_use: dict[str, Any] = field(default_factory=lambda: {}) + """专注工具使用模型配置""" + focus_planner: dict[str, Any] = field(default_factory=lambda: {}) + """专注规划模型配置""" + + focus_expressor: dict[str, Any] = field(default_factory=lambda: {}) + """专注表达器模型配置""" + embedding: dict[str, Any] = field(default_factory=lambda: {}) """嵌入模型配置""" @@ -417,5 +423,6 @@ class ModelConfig(ConfigBase): pfc_reply_checker: dict[str, Any] = field(default_factory=lambda: {}) """PFC回复检查模型配置""" - tool_use: dict[str, Any] = field(default_factory=lambda: {}) - """工具使用模型配置""" + + + diff --git a/src/llm_models/utils_model.py b/src/llm_models/utils_model.py index 2c45e5233..2a45c5c94 100644 --- a/src/llm_models/utils_model.py +++ b/src/llm_models/utils_model.py @@ -459,6 +459,7 @@ class LLMRequest: logger.error( f"模型 {self.model_name} 错误码: {response.status} - {error_code_mapping.get(response.status)}" ) + print(request_content) print(response) # 尝试获取并记录服务器返回的详细错误信息 try: @@ -499,8 +500,8 @@ class LLMRequest: if global_config.model.normal.get("name") == old_model_name: global_config.model.normal["name"] = self.model_name logger.warning(f"将全局配置中的 llm_normal 模型临时降级至{self.model_name}") - if global_config.model.reasoning.get("name") == old_model_name: - global_config.model.reasoning["name"] = self.model_name + if global_config.model.normal_chat_1.get("name") == old_model_name: + global_config.model.normal_chat_1["name"] = self.model_name logger.warning(f"将全局配置中的 llm_reasoning 模型临时降级至{self.model_name}") if payload and "model" in payload: diff --git a/src/tools/tool_use.py b/src/tools/tool_use.py index 8ddc747da..caca2cb6f 100644 --- a/src/tools/tool_use.py +++ b/src/tools/tool_use.py @@ -1,18 +1,9 @@ -from src.llm_models.utils_model import LLMRequest -from src.config.config import global_config import json from src.common.logger_manager import get_logger from src.tools.tool_can_use import get_all_tool_definitions, get_tool_instance logger = get_logger("tool_use") - - class ToolUser: - def __init__(self): - self.llm_model_tool = LLMRequest( - model=global_config.model.tool_use, temperature=0.2, max_tokens=1000, request_type="tool_use" - ) - @staticmethod def _define_tools(): """获取所有已注册工具的定义 diff --git a/template/bot_config_template.toml b/template/bot_config_template.toml index bc546b6a2..0156cf36d 100644 --- a/template/bot_config_template.toml +++ b/template/bot_config_template.toml @@ -196,7 +196,7 @@ pfc_chatting = false # 是否启用PFC聊天，该功能仅作用于私聊，与 model_max_output_length = 800 # 模型单次返回的最大token数 #这个模型必须是推理模型 -[model.reasoning] # 一般聊天模式的推理回复模型 +[model.normal_chat_1] # 一般聊天模式的首要回复模型，推荐使用 推理模型 name = "Pro/deepseek-ai/DeepSeek-R1" provider = "SILICONFLOW" pri_in = 1.0 #模型的输入价格（非必填，可以记录消耗） @@ -210,13 +210,7 @@ pri_out = 8 #模型的输出价格（非必填，可以记录消耗） #默认temp 0.2 如果你使用的是老V3或者其他模型，请自己修改temp参数 temp = 0.2 #模型的温度，新V3建议0.1-0.3 -[model.topic_judge] #主题判断模型：建议使用qwen2.5 7b -name = "Pro/Qwen/Qwen2.5-7B-Instruct" -provider = "SILICONFLOW" -pri_in = 0.35 -pri_out = 0.35 - -[model.summary] #概括模型，建议使用qwen2.5 32b 及以上 +[model.memory_summary] # 记忆的概括模型，建议使用qwen2.5 32b 及以上 name = "Qwen/Qwen2.5-32B-Instruct" provider = "SILICONFLOW" pri_in = 1.26 @@ -228,12 +222,6 @@ provider = "SILICONFLOW" pri_in = 0.35 pri_out = 0.35 -[model.heartflow] # 用于控制麦麦是否参与聊天的模型 -name = "Qwen/Qwen2.5-32B-Instruct" -provider = "SILICONFLOW" -pri_in = 1.26 -pri_out = 1.26 - [model.observation] #观察模型，压缩聊天内容，建议用免费的 # name = "Pro/Qwen/Qwen2.5-7B-Instruct" name = "Qwen/Qwen2.5-7B-Instruct" @@ -241,19 +229,48 @@ provider = "SILICONFLOW" pri_in = 0 pri_out = 0 -[model.sub_heartflow] #心流：认真聊天时,生成麦麦的内心想法，必须使用具有工具调用能力的模型 +[model.focus_working_memory] #工作记忆模型，建议使用qwen2.5 32b +# name = "Pro/Qwen/Qwen2.5-7B-Instruct" +name = "Qwen/Qwen2.5-32B-Instruct" +provider = "SILICONFLOW" +pri_in = 1.26 +pri_out = 1.26 + +[model.focus_chat_mind] #聊天规划：认真聊天时,生成麦麦对聊天的规划想法 name = "Pro/deepseek-ai/DeepSeek-V3" provider = "SILICONFLOW" pri_in = 2 pri_out = 8 temp = 0.3 #模型的温度，新V3建议0.1-0.3 -[model.plan] #决策：认真聊天时,负责决定麦麦该做什么 +[model.focus_tool_use] #工具调用模型，需要使用支持工具调用的模型，建议使用qwen2.5 32b +name = "Qwen/Qwen2.5-32B-Instruct" +provider = "SILICONFLOW" +pri_in = 1.26 +pri_out = 1.26 + +[model.focus_planner] #决策：认真聊天时,负责决定麦麦该做什么 name = "Pro/deepseek-ai/DeepSeek-V3" provider = "SILICONFLOW" pri_in = 2 pri_out = 8 +#表达器模型，用于生成表达方式 +[model.focus_expressor] +name = "Pro/deepseek-ai/DeepSeek-V3" +provider = "SILICONFLOW" +pri_in = 2 +pri_out = 8 +temp = 0.3 + +#自我识别模型，用于自我认知和身份识别 +[model.focus_self_recognize] +name = "Pro/deepseek-ai/DeepSeek-V3" +provider = "SILICONFLOW" +pri_in = 2 +pri_out = 8 +temp = 0.3 + #嵌入模型 [model.embedding] #嵌入 @@ -263,6 +280,9 @@ pri_in = 0 pri_out = 0 + + + #私聊PFC：需要开启PFC功能，默认三个模型均为硅基流动v3，如果需要支持多人同时私聊或频繁调用，建议把其中的一个或两个换成官方v3或其它模型，以免撞到429 #PFC决策模型 @@ -289,15 +309,6 @@ pri_in = 2 pri_out = 8 -#以下模型暂时没有使用！！ -#以下模型暂时没有使用！！ -#以下模型暂时没有使用！！ -#以下模型暂时没有使用！！ -#以下模型暂时没有使用！！ -[model.tool_use] #工具调用模型，需要使用支持工具调用的模型，建议使用qwen2.5 32b -name = "Qwen/Qwen2.5-32B-Instruct" -provider = "SILICONFLOW" -pri_in = 1.26 -pri_out = 1.26 +