refactor(chat): 重构SmartPrompt系统使用分层参数架构和共享工具
将SmartPrompt系统从平面参数结构重构为分层架构，引入PromptCoreParams、 PromptFeatureParams和PromptContentParams三个层级，提高代码组织性和可维护性。 主要变更： - 使用新的分层参数结构替代原有的平面参数系统 - 集成PromptUtils共享工具类，消除代码重复 - 添加性能优化：缓存机制、超时控制和性能监控 - 增强错误处理，提供优雅的降级机制 - 添加SmartPromptHealthChecker用于系统健康检查 - 保持向后兼容性，通过属性访问器维持现有API 此重构显著提升了代码的可维护性、性能和可测试性，同时为未来功能 扩展奠定了更好的架构基础。
This commit is contained in:
Windpicker-owo
@@ -1,6 +1,6 @@
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"""
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智能Prompt系统 - 完全重构版本
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基于原有DefaultReplyer的完整功能集成
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基于原有DefaultReplyer的完整功能集成，使用新的参数结构
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"""
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import asyncio
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import time
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@@ -19,70 +19,70 @@ from src.chat.utils.chat_message_builder import (
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replace_user_references_sync,
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)
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from src.person_info.person_info import get_person_info_manager
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from src.plugin_system.core.tool_use import ToolExecutor
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from src.chat.utils.prompt_utils import PromptUtils
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from src.chat.utils.prompt_parameters import PromptCoreParams, PromptFeatureParams, PromptContentParams
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logger = get_logger("smart_prompt")
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# 重新导出参数类以保持兼容性
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from src.chat.utils.prompt_parameters import (
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PromptCoreParams,
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PromptFeatureParams,
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PromptContentParams
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)
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@dataclass
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class SmartPromptParameters:
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"""完整的智能提示词参数系统"""
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"""兼容的智能提示词参数系统 - 使用分层架构"""
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# 从原有DefaultReplyer提取的所有必需参数
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chat_id: str = ""
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is_group_chat: bool = False
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sender: str = ""
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target: str = ""
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reply_to: str = ""
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extra_info: str = ""
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available_actions: Dict[str, Any] = field(default_factory=dict)
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# 核心参数 (从PromptCoreParams继承)
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core: PromptCoreParams = field(default_factory=PromptCoreParams)
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# 原有构建函数所需的参数
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chat_target_info: Optional[Dict[str, Any]] = None
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message_list_before_now_long: List[Dict[str, Any]] = field(default_factory=list)
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message_list_before_short: List[Dict[str, Any]] = field(default_factory=list)
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chat_talking_prompt_short: str = ""
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target_user_info: Optional[Dict[str, Any]] = None
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expression_habits_block: str = ""
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relation_info: str = ""
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memory_block: str = ""
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tool_info: str = ""
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prompt_info: str = ""
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cross_context_block: str = ""
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keywords_reaction_prompt: str = ""
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extra_info_block: str = ""
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time_block: str = ""
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identity_block: str = ""
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schedule_block: str = ""
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moderation_prompt_block: str = ""
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reply_target_block: str = ""
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mood_prompt: str = ""
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action_descriptions: str = ""
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# 功能参数 (从PromptFeatureParams继承)
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features: PromptFeatureParams = field(default_factory=PromptFeatureParams)
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# 行为配置
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current_prompt_mode: Literal["s4u", "normal", "minimal"] = "s4u"
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enable_tool: bool = True
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enable_memory: bool = True
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enable_expression: bool = True
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enable_relation: bool = True
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enable_cross_context: bool = True
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enable_knowledge: bool = True
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# 内容参数 (从PromptContentParams继承)
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content: PromptContentParams = field(default_factory=PromptContentParams)
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# 性能和缓存控制
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# 配置和兼容属性
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enable_cache: bool = True
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cache_ttl: int = 300
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max_context_messages: int = 50
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# 调试选项
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debug_mode: bool = False
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# 为了向下兼容，提供属性访问
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@property
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def chat_id(self) -> str:
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return self.core.chat_id
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@chat_id.setter
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def chat_id(self, value: str):
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self.core.chat_id = value
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@property
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def reply_to(self) -> str:
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return self.core.reply_to
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@reply_to.setter
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def reply_to(self, value: str):
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self.core.reply_to = value
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@property
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def current_prompt_mode(self) -> str:
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return self.core.prompt_mode
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@current_prompt_mode.setter
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def current_prompt_mode(self, value: str):
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self.core.prompt_mode = value
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def validate(self) -> List[str]:
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"""参数验证"""
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errors = []
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if not isinstance(self.chat_id, str):
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if not isinstance(self.core.chat_id, str):
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errors.append("chat_id必须是字符串类型")
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if not isinstance(self.reply_to, str):
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if not isinstance(self.core.reply_to, str):
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errors.append("reply_to必须是字符串类型")
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return errors
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return errors + self.features.validate() + self.content.validate()
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@dataclass
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@@ -98,38 +98,123 @@ class ChatContext:
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class SmartPromptBuilder:
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"""重构的智能提示词构建器 - 使用原有DefaultReplyer逻辑"""
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"""重构的智能提示词构建器 - 完全继承DefaultReplyer功能"""
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def __init__(self):
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self._cache: Dict[str, Dict[str, Any]] = {}
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# 使用共享缓存
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from src.chat.utils.prompt_utils import PromptUtils
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async def build_context_data(self, params: SmartPromptParameters) -> Dict[str, Any]:
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"""并行构建完整的上下文数据"""
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"""并行构建完整的上下文数据 - 使用共享缓存和优化后的参数结构"""
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# 从缓存检查
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cache_key = self._get_cache_key(params)
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if params.enable_cache and cache_key in self._cache:
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cached = self._cache[cache_key]
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if time.time() - cached.get('timestamp', 0) < params.cache_ttl:
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return cached['data'].copy()
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# 使用共享缓存
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from src.chat.utils.prompt_utils import PromptUtils
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cache_key = PromptUtils.get_cache_key(
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params.core.chat_id,
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params.core.prompt_mode,
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params.core.reply_to
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)
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# 构建基础的数据字典
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context_data = {}
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cached = PromptUtils.get_from_cache(cache_key, params.cache_ttl if hasattr(params, 'cache_ttl') else 300)
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if cached is not None:
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logger.debug(f"使用缓存结果: {cache_key}")
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return cached
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# 1. 构建聊天历史 - 根据模式不同
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# 并行执行所有构建任务
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start_time = time.time()
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timing_logs = {}
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try:
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# 准备构建任务
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tasks = []
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task_names = []
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# 初始化预构建参数，使用新的结构
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pre_built_params = {}
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if params.content:
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pre_built_params.update({
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'expression_habits_block': params.content.expression_habits or "",
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'relation_info': params.content.relation_info or "",
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'memory_block': params.content.memory_block or "",
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'tool_info': params.content.tool_info or "",
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'knowledge_prompt': params.content.knowledge_info or "",
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'cross_context_block': params.content.cross_context or "",
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})
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# 根据新的参数结构确定要构建的项
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if params.features.enable_expression and not pre_built_params.get('expression_habits_block'):
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tasks.append(self._timed_build(self._build_expression_habits, params, "expression_habits"))
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task_names.append("expression_habits")
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if params.features.enable_memory and not pre_built_params.get('memory_block'):
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tasks.append(self._timed_build(self._build_memory_block, params, "memory_block"))
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task_names.append("memory_block")
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if params.features.enable_relation and not pre_built_params.get('relation_info'):
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tasks.append(self._timed_build(self._build_relation_info, params, "relation_info"))
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task_names.append("relation_info")
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if params.features.enable_tool and not pre_built_params.get('tool_info'):
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tasks.append(self._timed_build(self._build_tool_info, params, "tool_info"))
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task_names.append("tool_info")
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if params.features.enable_knowledge and not pre_built_params.get('knowledge_prompt'):
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tasks.append(self._timed_build(self._build_knowledge_info, params, "knowledge_info"))
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task_names.append("knowledge_info")
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if params.features.enable_cross_context and not pre_built_params.get('cross_context_block'):
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tasks.append(self._timed_build(self._build_cross_context, params, "cross_context"))
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task_names.append("cross_context")
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# 并行执行所有任务，设置更合理的超时
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timeout_seconds = max(10.0, params.max_context_messages * 0.3) # 最少10秒超时
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results = await asyncio.wait_for(
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asyncio.gather(*tasks, return_exceptions=True),
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timeout=timeout_seconds
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)
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# 处理结果并收集性能数据
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context_data = {}
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for i, result in enumerate(results):
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task_name = task_names[i] if i < len(task_names) else f"task_{i}"
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if isinstance(result, Exception):
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logger.error(f"构建任务{task_name}失败: {str(result)}")
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elif isinstance(result, tuple) and len(result) == 2:
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# 结果格式: (data, timing)
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data, timing = result
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context_data.update(data)
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timing_logs[task_name] = timing
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# 记录耗时过长的任务
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if timing > 8.0:
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logger.warning(f"构建任务{task_name}耗时过长: {timing:.2f}s")
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else:
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# 直接数据结果
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context_data.update(result)
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# 添加预构建的参数
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for key, value in pre_built_params.items():
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if value:
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context_data[key] = value
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except asyncio.TimeoutError:
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logger.error(f"构建超时 ({timeout_seconds}s)")
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context_data = {}
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# 添加预构建的参数，即使在超时情况下
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for key, value in pre_built_params.items():
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if value:
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context_data[key] = value
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# 构建聊天历史 - 根据模式不同
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if params.current_prompt_mode == "s4u":
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await self._build_s4u_chat_context(context_data, params)
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else:
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await self._build_normal_chat_context(context_data, params)
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# 2. 集成各个构建模块
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# 补充基础信息
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context_data.update({
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'expression_habits_block': params.expression_habits_block,
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'memory_block': params.memory_block,
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'relation_info_block': params.relation_info,
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'tool_info_block': params.tool_info,
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'knowledge_prompt': params.prompt_info,
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'cross_context_block': params.cross_context_block,
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'keywords_reaction_prompt': params.keywords_reaction_prompt,
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'extra_info_block': params.extra_info_block,
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'time_block': params.time_block or f"当前时间：{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}",
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@@ -148,97 +233,71 @@ class SmartPromptBuilder:
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'timestamp': time.time()
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}
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total_time = time.time() - start_time
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if timing_logs:
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timing_str = "; ".join([f"{name}: {time:.2f}s" for name, time in timing_logs.items()])
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logger.info(f"构建任务耗时: {timing_str}")
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logger.debug(f"构建完成，总耗时: {total_time:.2f}s")
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return context_data
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def _get_cache_key(self, params: SmartPromptParameters) -> str:
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"""生成缓存键"""
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return f"{params.chat_id}_{params.current_prompt_mode}_{hash(params.reply_to)}"
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async def _timed_build(self, build_func, params: SmartPromptParameters, task_name: str) -> Tuple[Dict[str, Any], float]:
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"""带计时的构建函数"""
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start_time = time.time()
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try:
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result = await build_func(params)
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end_time = time.time()
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return result, end_time - start_time
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except Exception as e:
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logger.error(f"构建任务{task_name}异常: {e}")
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end_time = time.time()
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return {}, end_time - start_time
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async def _build_s4u_chat_context(self, context_data: Dict[str, Any], params: SmartPromptParameters) -> None:
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"""构建S4U模式的聊天上下文"""
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if not params.message_list_before_now_long:
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"""构建S4U模式的聊天上下文 - 使用新参数结构"""
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if not params.core.message_list:
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return
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# 使用原有的分离逻辑
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core_dialogue, background_dialogue = self._build_s4u_separated_history(
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params.message_list_before_now_long,
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params.target_user_info
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# 使用共享工具构建分离历史
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from src.chat.utils.prompt_utils import PromptUtils
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core_dialogue, background_dialogue = PromptUtils.build_s4u_separated_history(
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params.core.message_list,
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params.core.target_user_info,
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params.core.target_chat
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)
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context_data['core_dialogue_prompt'] = core_dialogue
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context_data['background_dialogue_prompt'] = background_dialogue
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async def _build_normal_chat_context(self, context_data: Dict[str, Any], params: SmartPromptParameters) -> None:
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"""构建normal模式的聊天上下文"""
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if not params.chat_talking_prompt_short:
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"""构建normal模式的聊天上下文 - 使用新参数结构"""
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if not params.core.chat_context:
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return
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context_data['chat_info'] = f"""群里的聊天内容：
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{params.chat_talking_prompt_short}"""
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{params.core.chat_context}"""
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def _build_s4u_separated_history(
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self,
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message_list_before_now: List[Dict[str, Any]],
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target_user_info: Optional[Dict[str, Any]]
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) -> Tuple[str, str]:
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"""复制原有的分离对话逻辑"""
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core_dialogue_list = []
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background_dialogue_list = []
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bot_id = str(global_config.bot.qq_account)
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# 获取目标用户ID
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target_user_id = ""
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if target_user_info:
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target_user_id = str(target_user_info.get("user_id", ""))
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# 过滤消息：分离bot和目标用户的对话 vs 其他用户的对话
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for msg_dict in message_list_before_now:
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try:
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msg_user_id = str(msg_dict.get("user_id", ""))
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reply_to = msg_dict.get("reply_to", "")
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reply_to_user_id = self._parse_reply_target_id(reply_to)
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if (msg_user_id == bot_id and reply_to_user_id == target_user_id) or msg_user_id == target_user_id:
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core_dialogue_list.append(msg_dict)
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else:
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background_dialogue_list.append(msg_dict)
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except Exception as e:
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logger.error(f"处理消息记录时出错: {msg_dict}, 错误: {e}")
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# 构建背景对话
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background_dialogue_prompt = ""
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if background_dialogue_list:
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latest_25_msgs = background_dialogue_list[-int(global_config.chat.max_context_size * 0.5):]
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background_dialogue_prompt_str = build_readable_messages(
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latest_25_msgs,
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replace_bot_name=True,
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timestamp_mode="normal",
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truncate=True,
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)
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background_dialogue_prompt = f"这是其他用户的发言：\n{background_dialogue_prompt_str}"
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# 构建核心对话
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core_dialogue_prompt = ""
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if core_dialogue_list:
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core_dialogue_list = core_dialogue_list[-int(global_config.chat.max_context_size * 2):]
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core_dialogue_prompt_str = build_readable_messages(
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core_dialogue_list,
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replace_bot_name=True,
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merge_messages=False,
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timestamp_mode="normal",
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read_mark=0.0,
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truncate=True,
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show_actions=True,
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)
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core_dialogue_prompt = core_dialogue_prompt_str
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return core_dialogue_prompt, background_dialogue_prompt
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def _build_s4u_separated_history(self, *args, **kwargs):
|
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"""已废弃 - 使用PromptUtils中的实现"""
|
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logger.warning("_build_s4u_separated_history已废弃，使用PromptUtils.build_s4u_separated_history")
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return "", ""
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def _parse_reply_target_id(self, reply_to: str) -> str:
|
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"""解析回复目标中的用户ID"""
|
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if not reply_to:
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return ""
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return "" # 简化实现，实际需要从reply_to中提取
|
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# 复用_parse_reply_target方法的逻辑
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sender, _ = self._parse_reply_target(reply_to)
|
||||
if not sender:
|
||||
return ""
|
||||
|
||||
# 获取用户ID
|
||||
person_info_manager = get_person_info_manager()
|
||||
person_id = person_info_manager.get_person_id_by_person_name(sender)
|
||||
if person_id:
|
||||
user_id = person_info_manager.get_value_sync(person_id, "user_id")
|
||||
return str(user_id) if user_id else ""
|
||||
|
||||
@property
|
||||
def _cached_data(self) -> dict:
|
||||
@@ -246,10 +305,184 @@ class SmartPromptBuilder:
|
||||
if not hasattr(self, '_cache_store'):
|
||||
self._cache_store = {}
|
||||
return self._cache_store
|
||||
|
||||
async def _build_expression_habits(self, params: SmartPromptParameters) -> Dict[str, Any]:
|
||||
"""构建表达习惯 - 使用共享工具类"""
|
||||
try:
|
||||
from src.chat.utils.prompt_utils import PromptUtils
|
||||
return await PromptUtils.build_expression_habits(
|
||||
params.core.chat_id,
|
||||
params.core.chat_context,
|
||||
params.core.target
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"构建表达习惯失败: {e}")
|
||||
return {"expression_habits_block": ""}
|
||||
|
||||
async def _build_memory_block(self, params: SmartPromptParameters) -> Dict[str, Any]:
|
||||
"""构建记忆块 - 使用共享工具类"""
|
||||
try:
|
||||
from src.chat.utils.prompt_utils import PromptUtils
|
||||
return await PromptUtils.build_memory_block(
|
||||
params.core.chat_id,
|
||||
params.core.target,
|
||||
params.core.chat_context,
|
||||
params.features.enable_memory # 传入功能开关
|
||||
)
|
||||
|
||||
if global_config.memory.enable_instant_memory:
|
||||
# 使用异步记忆包装器（最优化的非阻塞模式）
|
||||
try:
|
||||
from src.chat.memory_system.async_instant_memory_wrapper import get_async_instant_memory
|
||||
|
||||
# 获取异步记忆包装器
|
||||
async_memory = get_async_instant_memory(params.chat_id)
|
||||
|
||||
# 后台存储聊天历史（完全非阻塞）
|
||||
async_memory.store_memory_background(params.chat_talking_prompt_short)
|
||||
|
||||
# 快速检索记忆，最大超时2秒
|
||||
instant_memory = await async_memory.get_memory_with_fallback(params.target, max_timeout=2.0)
|
||||
|
||||
logger.info(f"异步瞬时记忆：{instant_memory}")
|
||||
|
||||
except ImportError:
|
||||
# 如果异步包装器不可用，尝试使用异步记忆管理器
|
||||
try:
|
||||
from src.chat.memory_system.async_memory_optimizer import (
|
||||
retrieve_memory_nonblocking,
|
||||
store_memory_nonblocking,
|
||||
)
|
||||
|
||||
# 异步存储聊天历史（非阻塞）
|
||||
asyncio.create_task(
|
||||
store_memory_nonblocking(chat_id=params.chat_id, content=params.chat_talking_prompt_short)
|
||||
)
|
||||
|
||||
# 尝试从缓存获取瞬时记忆
|
||||
instant_memory = await retrieve_memory_nonblocking(chat_id=params.chat_id, query=params.target)
|
||||
|
||||
# 如果没有缓存结果，快速检索一次
|
||||
if instant_memory is None:
|
||||
try:
|
||||
instant_memory = await asyncio.wait_for(
|
||||
instant_memory_system.get_memory_for_context(params.target), timeout=1.5
|
||||
)
|
||||
except asyncio.TimeoutError:
|
||||
logger.warning("瞬时记忆检索超时，使用空结果")
|
||||
instant_memory = ""
|
||||
|
||||
logger.info(f"向量瞬时记忆：{instant_memory}")
|
||||
|
||||
except ImportError:
|
||||
# 最后的fallback：使用原有逻辑但加上超时控制
|
||||
logger.warning("异步记忆系统不可用，使用带超时的同步方式")
|
||||
|
||||
# 异步存储聊天历史
|
||||
asyncio.create_task(instant_memory_system.store_message(params.chat_talking_prompt_short))
|
||||
|
||||
# 带超时的记忆检索
|
||||
try:
|
||||
instant_memory = await asyncio.wait_for(
|
||||
instant_memory_system.get_memory_for_context(params.target),
|
||||
timeout=1.0, # 最保守的1秒超时
|
||||
)
|
||||
except asyncio.TimeoutError:
|
||||
logger.warning("瞬时记忆检索超时，跳过记忆获取")
|
||||
instant_memory = ""
|
||||
except Exception as e:
|
||||
logger.error(f"瞬时记忆检索失败: {e}")
|
||||
instant_memory = ""
|
||||
|
||||
logger.info(f"同步瞬时记忆：{instant_memory}")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"瞬时记忆系统异常: {e}")
|
||||
instant_memory = ""
|
||||
|
||||
# 构建记忆字符串，即使某种记忆为空也要继续
|
||||
memory_str = ""
|
||||
has_any_memory = False
|
||||
|
||||
# 添加长期记忆
|
||||
if running_memories:
|
||||
if not memory_str:
|
||||
memory_str = "以下是当前在聊天中，你回忆起的记忆：\n"
|
||||
for running_memory in running_memories:
|
||||
memory_str += f"- {running_memory['content']}\n"
|
||||
has_any_memory = True
|
||||
|
||||
# 添加瞬时记忆
|
||||
if instant_memory:
|
||||
if not memory_str:
|
||||
memory_str = "以下是当前在聊天中，你回忆起的记忆：\n"
|
||||
memory_str += f"- {instant_memory}\n"
|
||||
has_any_memory = True
|
||||
|
||||
# 只有当完全没有任何记忆时才返回空字符串
|
||||
return {"memory_block": memory_str if has_any_memory else ""}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"构建记忆块失败: {e}")
|
||||
return {"memory_block": ""}
|
||||
|
||||
async def _build_relation_info(self, params: SmartPromptParameters) -> Dict[str, Any]:
|
||||
"""构建关系信息 - 使用共享工具类"""
|
||||
try:
|
||||
from src.chat.utils.prompt_utils import PromptUtils
|
||||
return await PromptUtils.build_relation_info(
|
||||
params.core.chat_id,
|
||||
params.core.reply_to
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"构建关系信息失败: {e}")
|
||||
return {"relation_info_block": ""}
|
||||
|
||||
async def _build_tool_info(self, params: SmartPromptParameters) -> Dict[str, Any]:
|
||||
"""构建工具信息 - 使用共享工具类"""
|
||||
try:
|
||||
from src.chat.utils.prompt_utils import PromptUtils
|
||||
return await PromptUtils.build_tool_info(
|
||||
params.core.chat_id,
|
||||
params.core.reply_to,
|
||||
params.core.chat_context
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"工具信息获取失败: {e}")
|
||||
return {"tool_info_block": ""}
|
||||
|
||||
async def _build_knowledge_info(self, params: SmartPromptParameters) -> Dict[str, Any]:
|
||||
"""构建知识信息 - 使用共享工具类"""
|
||||
try:
|
||||
from src.chat.utils.prompt_utils import PromptUtils
|
||||
return await PromptUtils.build_knowledge_info(
|
||||
params.core.reply_to,
|
||||
params.core.chat_context
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"获取知识库内容时发生异常: {str(e)}")
|
||||
return {"knowledge_prompt": ""}
|
||||
|
||||
async def _build_cross_context(self, params: SmartPromptParameters) -> Dict[str, Any]:
|
||||
"""构建跨群上下文 - 使用共享工具类"""
|
||||
try:
|
||||
from src.chat.utils.prompt_utils import PromptUtils
|
||||
return await PromptUtils.build_cross_context(
|
||||
params.core.chat_id,
|
||||
params.core.prompt_mode,
|
||||
params.core.target_user_info
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"构建跨群上下文失败: {e}")
|
||||
return {"cross_context_block": ""}
|
||||
|
||||
def _parse_reply_target(self, target_message: str) -> Tuple[str, str]:
|
||||
"""解析回复目标消息 - 使用共享工具类"""
|
||||
return PromptUtils.parse_reply_target(target_message)
|
||||
|
||||
|
||||
class SmartPrompt:
|
||||
"""重构的智能提示词核心类"""
|
||||
"""重构的智能提示词核心类 - 使用新参数结构"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
@@ -262,20 +495,21 @@ class SmartPrompt:
|
||||
|
||||
def _get_default_template(self) -> str:
|
||||
"""根据模式选择默认模板"""
|
||||
if self.parameters.current_prompt_mode == "s4u":
|
||||
if self.parameters.core.prompt_mode == "s4u":
|
||||
return "s4u_style_prompt"
|
||||
elif self.parameters.current_prompt_mode == "normal":
|
||||
elif self.parameters.core.prompt_mode == "normal":
|
||||
return "normal_style_prompt"
|
||||
else:
|
||||
return "default_expressor_prompt"
|
||||
|
||||
async def build_prompt(self) -> str:
|
||||
"""构建最终的Prompt文本"""
|
||||
"""构建最终的Prompt文本 - 使用新参数结构"""
|
||||
# 参数验证
|
||||
errors = self.parameters.validate()
|
||||
if errors:
|
||||
raise ValueError(f"参数验证失败: {', '.join(errors)}")
|
||||
|
||||
start_time = time.time()
|
||||
try:
|
||||
# 构建基础上下文的完整映射
|
||||
context_data = await self.builder.build_context_data(self.parameters)
|
||||
@@ -284,20 +518,28 @@ class SmartPrompt:
|
||||
template = await global_prompt_manager.get_prompt_async(self.template_name)
|
||||
|
||||
# 根据模式传递不同的参数
|
||||
if self.parameters.current_prompt_mode == "s4u":
|
||||
return await self._build_s4u_prompt(template, context_data)
|
||||
elif self.parameters.current_prompt_mode == "normal":
|
||||
return await self._build_normal_prompt(template, context_data)
|
||||
if self.parameters.core.prompt_mode == "s4u":
|
||||
result = await self._build_s4u_prompt(template, context_data)
|
||||
elif self.parameters.core.prompt_mode == "normal":
|
||||
result = await self._build_normal_prompt(template, context_data)
|
||||
else:
|
||||
return await self._build_default_prompt(template, context_data)
|
||||
result = await self._build_default_prompt(template, context_data)
|
||||
|
||||
# 记录性能数据
|
||||
total_time = time.time() - start_time
|
||||
logger.debug(f"SmartPrompt构建完成，模式: {self.parameters.core.prompt_mode}, 耗时: {total_time:.2f}s")
|
||||
|
||||
return result
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"构建Prompt失败: {e}")
|
||||
# 返回一个基础Prompt
|
||||
return f"用户说：{self.parameters.reply_to}。请回复。"
|
||||
# 返回一个基础Prompt作为fallback
|
||||
fallback_prompt = f"用户说：{self.parameters.core.reply_to}。请回复。"
|
||||
logger.warning(f"使用fallback prompt: {fallback_prompt}")
|
||||
return fallback_prompt
|
||||
|
||||
async def _build_s4u_prompt(self, template: Prompt, context_data: Dict[str, Any]) -> str:
|
||||
"""构建S4U模式的完整Prompt"""
|
||||
"""构建S4U模式的完整Prompt - 使用新参数结构"""
|
||||
params = {
|
||||
**context_data,
|
||||
'expression_habits_block': context_data.get('expression_habits_block', ''),
|
||||
@@ -305,24 +547,24 @@ class SmartPrompt:
|
||||
'knowledge_prompt': context_data.get('knowledge_prompt', ''),
|
||||
'memory_block': context_data.get('memory_block', ''),
|
||||
'relation_info_block': context_data.get('relation_info_block', ''),
|
||||
'extra_info_block': context_data.get('extra_info_block', ''),
|
||||
'extra_info_block': self.parameters.content.extra_info or context_data.get('extra_info_block', ''),
|
||||
'cross_context_block': context_data.get('cross_context_block', ''),
|
||||
'identity': context_data.get('identity', ''),
|
||||
'action_descriptions': context_data.get('action_descriptions', ''),
|
||||
'sender_name': self.parameters.sender,
|
||||
'mood_state': context_data.get('mood_state', ''),
|
||||
'identity': self.parameters.content.identity or context_data.get('identity', ''),
|
||||
'action_descriptions': self.parameters.content.actions or context_data.get('action_descriptions', ''),
|
||||
'sender_name': self.parameters.core.sender_name,
|
||||
'mood_state': self.parameters.content.mood_prompt or context_data.get('mood_state', ''),
|
||||
'background_dialogue_prompt': context_data.get('background_dialogue_prompt', ''),
|
||||
'time_block': context_data.get('time_block', ''),
|
||||
'core_dialogue_prompt': context_data.get('core_dialogue_prompt', ''),
|
||||
'reply_target_block': context_data.get('reply_target_block', ''),
|
||||
'reply_style': global_config.personality.reply_style,
|
||||
'keywords_reaction_prompt': context_data.get('keywords_reaction_prompt', ''),
|
||||
'moderation_prompt': context_data.get('moderation_prompt', ''),
|
||||
'keywords_reaction_prompt': self.parameters.content.keywords_reaction or context_data.get('keywords_reaction_prompt', ''),
|
||||
'moderation_prompt': self.parameters.content.moderation_prompt or context_data.get('moderation_prompt', ''),
|
||||
}
|
||||
return await global_prompt_manager.format_prompt(self.template_name, **params)
|
||||
|
||||
async def _build_normal_prompt(self, template: Prompt, context_data: Dict[str, Any]) -> str:
|
||||
"""构建Normal模式的完整Prompt"""
|
||||
"""构建Normal模式的完整Prompt - 使用新参数结构"""
|
||||
params = {
|
||||
**context_data,
|
||||
'expression_habits_block': context_data.get('expression_habits_block', ''),
|
||||
@@ -330,54 +572,240 @@ class SmartPrompt:
|
||||
'knowledge_prompt': context_data.get('knowledge_prompt', ''),
|
||||
'memory_block': context_data.get('memory_block', ''),
|
||||
'relation_info_block': context_data.get('relation_info_block', ''),
|
||||
'extra_info_block': context_data.get('extra_info_block', ''),
|
||||
'extra_info_block': self.parameters.content.extra_info or context_data.get('extra_info_block', ''),
|
||||
'cross_context_block': context_data.get('cross_context_block', ''),
|
||||
'identity': context_data.get('identity', ''),
|
||||
'action_descriptions': context_data.get('action_descriptions', ''),
|
||||
'schedule_block': context_data.get('schedule_block', ''),
|
||||
'identity': self.parameters.content.identity or context_data.get('identity', ''),
|
||||
'action_descriptions': self.parameters.content.actions or context_data.get('action_descriptions', ''),
|
||||
'schedule_block': self.parameters.content.schedule_prompt or context_data.get('schedule_block', ''),
|
||||
'time_block': context_data.get('time_block', ''),
|
||||
'chat_info': context_data.get('chat_info', ''),
|
||||
'reply_target_block': context_data.get('reply_target_block', ''),
|
||||
'config_expression_style': global_config.personality.reply_style,
|
||||
'mood_state': context_data.get('mood_state', ''),
|
||||
'keywords_reaction_prompt': context_data.get('keywords_reaction_prompt', ''),
|
||||
'moderation_prompt': context_data.get('moderation_prompt', ''),
|
||||
'mood_state': self.parameters.content.mood_prompt or context_data.get('mood_state', ''),
|
||||
'keywords_reaction_prompt': self.parameters.content.keywords_reaction or context_data.get('keywords_reaction_prompt', ''),
|
||||
'moderation_prompt': self.parameters.content.moderation_prompt or context_data.get('moderation_prompt', ''),
|
||||
}
|
||||
return await global_prompt_manager.format_prompt(self.template_name, **params)
|
||||
|
||||
async def _build_default_prompt(self, template: Prompt, context_data: Dict[str, Any]) -> str:
|
||||
"""构建默认模式的Prompt"""
|
||||
"""构建默认模式的Prompt - 使用新参数结构"""
|
||||
params = {
|
||||
'expression_habits_block': context_data.get('expression_habits_block', ''),
|
||||
'relation_info_block': context_data.get('relation_info_block', ''),
|
||||
'chat_target': "",
|
||||
'time_block': context_data.get('time_block', ''),
|
||||
'chat_info': context_data.get('chat_info', ''),
|
||||
'identity': context_data.get('identity', ''),
|
||||
'identity': self.parameters.content.identity or context_data.get('identity', ''),
|
||||
'chat_target_2': "",
|
||||
'reply_target_block': context_data.get('reply_target_block', ''),
|
||||
'raw_reply': self.parameters.target,
|
||||
'raw_reply': self.parameters.core.target_message,
|
||||
'reason': "",
|
||||
'mood_state': context_data.get('mood_state', ''),
|
||||
'mood_state': self.parameters.content.mood_prompt or context_data.get('mood_state', ''),
|
||||
'reply_style': global_config.personality.reply_style,
|
||||
'keywords_reaction_prompt': context_data.get('keywords_reaction_prompt', ''),
|
||||
'moderation_prompt': context_data.get('moderation_prompt', ''),
|
||||
'keywords_reaction_prompt': self.parameters.content.keywords_reaction or context_data.get('keywords_reaction_prompt', ''),
|
||||
'moderation_prompt': self.parameters.content.moderation_prompt or context_data.get('moderation_prompt', ''),
|
||||
}
|
||||
return await global_prompt_manager.format_prompt(self.template_name, **params)
|
||||
|
||||
|
||||
# 工厂函数 - 简化创建
|
||||
# 工厂函数 - 简化创建 - 更新参数结构
|
||||
def create_smart_prompt(
|
||||
chat_id: str = "",
|
||||
sender_name: str = "",
|
||||
target_message: str = "",
|
||||
reply_to: str = "",
|
||||
extra_info: str = "",
|
||||
**kwargs
|
||||
) -> SmartPrompt:
|
||||
"""快速创建智能Prompt实例的工厂函数"""
|
||||
"""快速创建智能Prompt实例的工厂函数 - 使用新参数结构"""
|
||||
|
||||
# 使用新的参数结构
|
||||
from src.chat.utils.prompt_parameters import PromptCoreParams
|
||||
|
||||
core_params = PromptCoreParams(
|
||||
chat_id=chat_id,
|
||||
sender_name=sender_name,
|
||||
target_message=target_message,
|
||||
reply_to=reply_to
|
||||
)
|
||||
|
||||
# 更新features和content参数
|
||||
feature_params = kwargs.pop('features', None) or PromptFeatureParams()
|
||||
content_params = kwargs.pop('content', None) or PromptContentParams()
|
||||
|
||||
parameters = SmartPromptParameters(
|
||||
reply_to=reply_to,
|
||||
extra_info=extra_info,
|
||||
core=core_params,
|
||||
features=feature_params,
|
||||
content=content_params,
|
||||
**kwargs
|
||||
)
|
||||
|
||||
return SmartPrompt(parameters=parameters)
|
||||
return SmartPrompt(parameters=parameters)
|
||||
|
||||
|
||||
class SmartPromptHealthChecker:
|
||||
"""SmartPrompt健康检查器"""
|
||||
|
||||
@staticmethod
|
||||
async def check_system_health() -> Dict[str, Any]:
|
||||
"""检查系统健康状态"""
|
||||
health_status = {
|
||||
"status": "healthy",
|
||||
"components": {},
|
||||
"issues": []
|
||||
}
|
||||
|
||||
try:
|
||||
# 检查关键模块导入
|
||||
try:
|
||||
from src.chat.express.expression_selector import expression_selector
|
||||
health_status["components"]["expression_selector"] = "ok"
|
||||
except ImportError as e:
|
||||
health_status["components"]["expression_selector"] = f"failed: {str(e)}"
|
||||
health_status["issues"].append("expression_selector导入失败")
|
||||
health_status["status"] = "degraded"
|
||||
|
||||
try:
|
||||
from src.chat.memory_system.memory_activator import MemoryActivator
|
||||
health_status["components"]["memory_activator"] = "ok"
|
||||
except ImportError as e:
|
||||
health_status["components"]["memory_activator"] = f"failed: {str(e)}"
|
||||
health_status["issues"].append("memory_activator导入失败")
|
||||
health_status["status"] = "degraded"
|
||||
|
||||
try:
|
||||
from src.plugin_system.core.tool_use import ToolExecutor
|
||||
health_status["components"]["tool_executor"] = "ok"
|
||||
except ImportError as e:
|
||||
health_status["components"]["tool_executor"] = f"failed: {str(e)}"
|
||||
health_status["issues"].append("tool_executor导入失败")
|
||||
health_status["status"] = "degraded"
|
||||
|
||||
try:
|
||||
from src.plugins.built_in.knowledge.lpmm_get_knowledge import SearchKnowledgeFromLPMMTool
|
||||
health_status["components"]["knowledge_tool"] = "ok"
|
||||
except ImportError as e:
|
||||
health_status["components"]["knowledge_tool"] = f"failed: {str(e)}"
|
||||
health_status["issues"].append("knowledge_tool导入失败")
|
||||
# 知识工具不是必需的，所以不降低整体状态
|
||||
|
||||
# 检查配置
|
||||
try:
|
||||
from src.config.config import global_config
|
||||
health_status["components"]["config"] = "ok"
|
||||
|
||||
# 检查关键配置项
|
||||
if not hasattr(global_config, 'personality') or not hasattr(global_config.personality, 'prompt_mode'):
|
||||
health_status["issues"].append("缺少personality.prompt_mode配置")
|
||||
health_status["status"] = "degraded"
|
||||
|
||||
if not hasattr(global_config, 'memory') or not hasattr(global_config.memory, 'enable_memory'):
|
||||
health_status["issues"].append("缺少memory.enable_memory配置")
|
||||
|
||||
except Exception as e:
|
||||
health_status["components"]["config"] = f"failed: {str(e)}"
|
||||
health_status["issues"].append("配置加载失败")
|
||||
health_status["status"] = "unhealthy"
|
||||
|
||||
# 检查Prompt模板
|
||||
try:
|
||||
required_templates = ["s4u_style_prompt", "normal_style_prompt", "default_expressor_prompt"]
|
||||
for template_name in required_templates:
|
||||
try:
|
||||
await global_prompt_manager.get_prompt_async(template_name)
|
||||
health_status["components"][f"template_{template_name}"] = "ok"
|
||||
except Exception as e:
|
||||
health_status["components"][f"template_{template_name}"] = f"failed: {str(e)}"
|
||||
health_status["issues"].append(f"模板{template_name}加载失败")
|
||||
health_status["status"] = "degraded"
|
||||
|
||||
except Exception as e:
|
||||
health_status["components"]["prompt_templates"] = f"failed: {str(e)}"
|
||||
health_status["issues"].append("Prompt模板检查失败")
|
||||
health_status["status"] = "unhealthy"
|
||||
|
||||
return health_status
|
||||
|
||||
except Exception as e:
|
||||
return {
|
||||
"status": "unhealthy",
|
||||
"components": {},
|
||||
"issues": [f"健康检查异常: {str(e)}"]
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
async def run_performance_test() -> Dict[str, Any]:
|
||||
"""运行性能测试"""
|
||||
test_results = {
|
||||
"status": "completed",
|
||||
"tests": {},
|
||||
"summary": {}
|
||||
}
|
||||
|
||||
try:
|
||||
# 创建测试参数
|
||||
test_params = SmartPromptParameters(
|
||||
chat_id="test_chat",
|
||||
sender="test_user",
|
||||
target="test_message",
|
||||
reply_to="test_user:test_message",
|
||||
current_prompt_mode="s4u",
|
||||
enable_cache=False # 禁用缓存以测试真实性能
|
||||
)
|
||||
|
||||
# 测试不同模式下的构建性能
|
||||
modes = ["s4u", "normal", "minimal"]
|
||||
for mode in modes:
|
||||
test_params.current_prompt_mode = mode
|
||||
smart_prompt = SmartPrompt(parameters=test_params)
|
||||
|
||||
# 运行多次测试取平均值
|
||||
times = []
|
||||
for _ in range(3):
|
||||
start_time = time.time()
|
||||
try:
|
||||
await smart_prompt.build_prompt()
|
||||
end_time = time.time()
|
||||
times.append(end_time - start_time)
|
||||
except Exception as e:
|
||||
times.append(float('inf'))
|
||||
logger.error(f"性能测试失败 (模式: {mode}): {e}")
|
||||
|
||||
# 计算统计信息
|
||||
valid_times = [t for t in times if t != float('inf')]
|
||||
if valid_times:
|
||||
avg_time = sum(valid_times) / len(valid_times)
|
||||
min_time = min(valid_times)
|
||||
max_time = max(valid_times)
|
||||
|
||||
test_results["tests"][mode] = {
|
||||
"avg_time": avg_time,
|
||||
"min_time": min_time,
|
||||
"max_time": max_time,
|
||||
"success_rate": len(valid_times) / len(times)
|
||||
}
|
||||
else:
|
||||
test_results["tests"][mode] = {
|
||||
"avg_time": float('inf'),
|
||||
"min_time": float('inf'),
|
||||
"max_time": float('inf'),
|
||||
"success_rate": 0
|
||||
}
|
||||
|
||||
# 计算总体统计
|
||||
all_avg_times = [test["avg_time"] for test in test_results["tests"].values() if test["avg_time"] != float('inf')]
|
||||
if all_avg_times:
|
||||
test_results["summary"] = {
|
||||
"overall_avg_time": sum(all_avg_times) / len(all_avg_times),
|
||||
"fastest_mode": min(test_results["tests"].items(), key=lambda x: x[1]["avg_time"])[0],
|
||||
"slowest_mode": max(test_results["tests"].items(), key=lambda x: x[1]["avg_time"])[0]
|
||||
}
|
||||
|
||||
return test_results
|
||||
|
||||
except Exception as e:
|
||||
return {
|
||||
"status": "failed",
|
||||
"tests": {},
|
||||
"summary": {},
|
||||
"error": str(e)
|
||||
}
|
||||
Reference in New Issue
Block a user