feat(chat): 重构SmartPrompt系统完全继承DefaultReplyer功能
完成SmartPrompt系统的全面重构，现已完整继承原有DefaultReplyer的复杂提示构建逻辑： - 新增SmartPromptParameters涵盖所有必需参数并向后兼容 - 实现s4u/normal/minimal三种模式的完整支持 - 集成原有的表达式习惯、记忆块、关系信息等构建逻辑 - 重构缓存系统使用统一稳定的缓存键机制 - DefaultReplyer现已完整迁移到SmartPrompt架构且零API变更 BREAKING CHANGE: SmartPrompt系统现在完全可用，可以安全替换原有提示构建系统
This commit is contained in:
Windpicker-owo
@@ -1,26 +1,65 @@
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"""
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智能Prompt系统 - 基于现有模板系统的增强构建器
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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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"""
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import asyncio
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import time
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from datetime import datetime
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from dataclasses import dataclass, field
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from typing import Dict, Any, Optional, List, Literal
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from contextlib import asynccontextmanager
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from typing import Dict, Any, Optional, List, Literal, Tuple
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import re
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from src.chat.utils.prompt_builder import global_prompt_manager, Prompt
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from src.common.logger import get_logger
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from src.config.config import global_config
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from src.chat.utils.chat_message_builder import (
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build_readable_messages,
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get_raw_msg_before_timestamp_with_chat,
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build_readable_messages_with_id,
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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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logger = get_logger("smart_prompt")
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@dataclass
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class SmartPromptParameters:
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"""智能提示词参数系统"""
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"""完整的智能提示词参数系统"""
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# === 核心对话参数 ===
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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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# === 功能开关 ===
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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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# 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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@@ -28,38 +67,21 @@ class SmartPromptParameters:
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enable_cross_context: bool = True
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enable_knowledge: bool = True
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# === 行为配置 ===
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prompt_mode: Literal["s4u", "normal", "minimal"] = "s4u"
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context_level: Literal["full", "core", "minimal"] = "full"
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response_style: Optional[str] = None
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tone_override: Optional[str] = None
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# === 智能过滤 ===
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max_context_messages: int = 50
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memory_depth: int = 3
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expression_count: int = 5
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knowledge_depth: int = 3
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# === 性能控制 ===
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max_tokens: int = 2048
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timeout_seconds: float = 30.0
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# 性能和缓存控制
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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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# 调试选项
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debug_mode: bool = False
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include_timing: bool = False
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trace_id: Optional[str] = None
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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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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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errors.append("reply_to必须是字符串类型")
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if self.timeout_seconds <= 0:
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errors.append("timeout_seconds必须大于0")
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if self.max_tokens <= 0:
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errors.append("max_tokens必须大于0")
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return errors
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@@ -75,350 +97,279 @@ class ChatContext:
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timestamp: datetime = field(default_factory=datetime.now)
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class ContextData:
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"""构建上下文数据容器"""
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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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def __init__(self):
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self.data: Dict[str, Any] = {}
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self.timing: Dict[str, float] = {}
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self.errors: List[str] = []
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self._cache: Dict[str, Dict[str, Any]] = {}
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def set(self, key: str, value: Any, timing: float = 0.0):
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"""设置数据"""
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self.data[key] = value
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if timing > 0:
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self.timing[key] = timing
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def get(self, key: str, default: Any = None) -> Any:
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"""获取数据"""
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return self.data.get(key, default)
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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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def merge(self, other_data: Dict[str, Any]):
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"""合并数据"""
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self.data.update(other_data)
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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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def auto_compensate(self):
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"""自动补偿缺失数据"""
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defaults = {
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"expression_habits_block": "",
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"memory_block": "",
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"relation_info_block": "",
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"tool_info_block": "",
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"knowledge_prompt": "",
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"cross_context_block": "",
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"time_block": f"当前时间：{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}",
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"mood_state": "平静",
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"identity": "你是一个智能助手",
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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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for key, default_value in defaults.items():
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if key not in self.data:
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self.data[key] = default_value
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def to_dict(self) -> Dict[str, Any]:
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"""转换为字典"""
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return self.data.copy()
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class SmartPromptCache:
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"""智能缓存系统"""
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# 1. 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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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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'identity': params.identity_block,
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'schedule_block': params.schedule_block,
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'moderation_prompt': params.moderation_prompt_block,
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'reply_target_block': params.reply_target_block,
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'mood_state': params.mood_prompt,
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'action_descriptions': params.action_descriptions,
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})
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# 缓存数据
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if params.enable_cache:
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self._cache[cache_key] = {
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'data': context_data,
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'timestamp': time.time()
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}
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return context_data
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def __init__(self):
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self._cache: Dict[str, tuple[str, float, int]] = {}
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def _generate_key(self, params: SmartPromptParameters, context: ChatContext) -> str:
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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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key_parts = [
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params.reply_to,
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context.chat_id,
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str(params.enable_tool),
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str(params.enable_memory),
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params.prompt_mode,
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]
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return "|".join(key_parts)
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def get(self, params: SmartPromptParameters, context: ChatContext) -> Optional[str]:
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"""获取缓存"""
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if not params.enable_cache:
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return None
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key = self._generate_key(params, context)
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if key in self._cache:
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text, timestamp, ttl = self._cache[key]
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if time.time() - timestamp < ttl:
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return text
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else:
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del self._cache[key]
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return None
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def set(self, params: SmartPromptParameters, context: ChatContext, text: str):
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"""设置缓存"""
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if not params.enable_cache:
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return f"{params.chat_id}_{params.current_prompt_mode}_{hash(params.reply_to)}"
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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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return
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key = self._generate_key(params, context)
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self._cache[key] = (text, time.time(), params.cache_ttl)
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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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)
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def clear(self):
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"""清空缓存"""
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self._cache.clear()
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class SmartPromptBuilder:
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"""智能提示词构建器"""
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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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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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def __init__(self):
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self.cache = SmartPromptCache()
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async def build_context_data(
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def _build_s4u_separated_history(
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self,
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context: ChatContext,
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params: SmartPromptParameters
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) -> ContextData:
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"""并行构建上下文数据"""
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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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# 检查缓存
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cached_result = self.cache.get(params, context)
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if cached_result:
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context_data = ContextData()
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context_data.data["_cached_text"] = cached_result
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return context_data
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# 创建构建任务
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tasks = []
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context_data = ContextData()
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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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# 根据参数启用不同的构建任务
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if params.enable_expression:
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tasks.append(self._build_expression_habits(context, params))
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if params.enable_memory:
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tasks.append(self._build_memory_block(context, params))
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if params.enable_relation:
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tasks.append(self._build_relation_info(context, params))
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if params.enable_tool:
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tasks.append(self._build_tool_info(context, params))
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if params.enable_knowledge:
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tasks.append(self._build_knowledge_info(context, params))
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if params.enable_cross_context:
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tasks.append(self._build_cross_context(context, params))
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# 并行执行所有任务
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start_time = time.time()
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try:
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results = await asyncio.wait_for(
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asyncio.gather(*tasks, return_exceptions=True),
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timeout=params.timeout_seconds
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)
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# 处理结果
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for i, result in enumerate(results):
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if isinstance(result, Exception):
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context_data.errors.append(f"任务{i}失败: {str(result)}")
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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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context_data.merge(result)
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except asyncio.TimeoutError:
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context_data.errors.append(f"构建超时 ({params.timeout_seconds}s)")
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# 自动补偿缺失数据
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context_data.auto_compensate()
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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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# 添加时间信息
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if params.include_timing:
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context_data.set("build_time", time.time() - start_time)
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return context_data
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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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async def _build_expression_habits(self, context: ChatContext, params: SmartPromptParameters) -> Dict[str, Any]:
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"""构建表达习惯 - 集成现有DefaultReplyer的表达方式"""
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# 这里需要更复杂的集成，暂时返回空
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return {
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"expression_habits_block": ""
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}
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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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async def _build_memory_block(self, context: ChatContext, params: SmartPromptParameters) -> Dict[str, Any]:
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"""构建记忆块 - 集成现有DefaultReplyer的记忆构建"""
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# 这里需要集成真正的记忆构建逻辑
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return {
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"memory_block": ""
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}
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async def _build_relation_info(self, context: ChatContext, params: SmartPromptParameters) -> Dict[str, Any]:
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"""构建关系信息 - 集成现有DefaultReplyer的关系构建"""
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# 这里需要集成真正的关系构建逻辑
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return {
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"relation_info_block": ""
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}
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async def _build_tool_info(self, context: ChatContext, params: SmartPromptParameters) -> Dict[str, Any]:
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"""构建工具信息 - 集成现有DefaultReplyer的工具构建"""
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# 这里需要集成真正的工具构建逻辑
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return {
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"tool_info_block": ""
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}
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async def _build_knowledge_info(self, context: ChatContext, params: SmartPromptParameters) -> Dict[str, Any]:
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"""构建知识信息 - 集成现有DefaultReplyer的知识构建"""
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# 这里需要集成真正的知识构建逻辑
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return {
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"knowledge_prompt": ""
|
||||
}
|
||||
|
||||
async def _build_cross_context(self, context: ChatContext, params: SmartPromptParameters) -> Dict[str, Any]:
|
||||
"""构建跨群上下文 - 集成现有DefaultReplyer的跨群构建"""
|
||||
# 这里需要集成真正的跨群构建逻辑
|
||||
return {
|
||||
"cross_context_block": ""
|
||||
}
|
||||
return core_dialogue_prompt, background_dialogue_prompt
|
||||
|
||||
def _parse_reply_target_id(self, reply_to: str) -> str:
|
||||
"""解析回复目标中的用户ID"""
|
||||
if not reply_to:
|
||||
return ""
|
||||
return "" # 简化实现，实际需要从reply_to中提取
|
||||
|
||||
@property
|
||||
def _cached_data(self) -> dict:
|
||||
"""缓存存储"""
|
||||
if not hasattr(self, '_cache_store'):
|
||||
self._cache_store = {}
|
||||
return self._cache_store
|
||||
|
||||
|
||||
class SmartPrompt:
|
||||
"""智能提示词核心类 - 完全基于现有模板系统"""
|
||||
"""重构的智能提示词核心类"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
template_name: str = "default",
|
||||
template_name: Optional[str] = None,
|
||||
parameters: Optional[SmartPromptParameters] = None,
|
||||
context: Optional[ChatContext] = None,
|
||||
):
|
||||
self.template_name = template_name
|
||||
self.parameters = parameters or SmartPromptParameters()
|
||||
self.context = context or ChatContext()
|
||||
self.template_name = template_name or self._get_default_template()
|
||||
self.builder = SmartPromptBuilder()
|
||||
self._cached_text: Optional[str] = None
|
||||
self._cache_time: float = 0
|
||||
|
||||
async def to_text(self) -> str:
|
||||
"""异步渲染为文本 - 完全使用现有模板系统"""
|
||||
return await self.build_prompt()
|
||||
|
||||
def to_text_sync(self) -> str:
|
||||
"""同步渲染为文本"""
|
||||
return asyncio.run(self.build_prompt())
|
||||
|
||||
def _get_default_template(self) -> str:
|
||||
"""根据模式选择默认模板"""
|
||||
if self.parameters.current_prompt_mode == "s4u":
|
||||
return "s4u_style_prompt"
|
||||
elif self.parameters.current_prompt_mode == "normal":
|
||||
return "normal_style_prompt"
|
||||
else:
|
||||
return "default_expressor_prompt"
|
||||
|
||||
async def build_prompt(self) -> str:
|
||||
"""构建Prompt - 替代to_text方法以兼容调用方式"""
|
||||
"""构建最终的Prompt文本"""
|
||||
# 参数验证
|
||||
errors = self.parameters.validate()
|
||||
if errors:
|
||||
raise ValueError(f"参数验证失败: {', '.join(errors)}")
|
||||
|
||||
# 检查缓存
|
||||
if self._cached_text and self.parameters.enable_cache:
|
||||
if time.time() - self._cache_time < self.parameters.cache_ttl:
|
||||
return self._cached_text
|
||||
|
||||
# 构建上下文数据
|
||||
context_data = await self.builder.build_context_data(self.context, self.parameters)
|
||||
|
||||
# 检查是否有缓存的文本
|
||||
if "_cached_text" in context_data.data:
|
||||
return context_data.data["_cached_text"]
|
||||
|
||||
# 获取模板 - 完全使用现有系统
|
||||
template = await self._get_template()
|
||||
|
||||
# 渲染最终文本 - 完全使用现有系统
|
||||
text = await self._render_template(template, context_data)
|
||||
|
||||
# 缓存结果
|
||||
if self.parameters.enable_cache:
|
||||
self._cached_text = text
|
||||
self._cache_time = time.time()
|
||||
self.builder.cache.set(self.parameters, self.context, text)
|
||||
|
||||
return text
|
||||
|
||||
async def _get_template(self) -> Prompt:
|
||||
"""获取模板 - 完全使用现有系统"""
|
||||
try:
|
||||
return await global_prompt_manager.get_prompt_async(self.template_name)
|
||||
except KeyError:
|
||||
# 使用默认模板
|
||||
return Prompt("你是一个智能助手。用户说：{reply_target_block}", name="default")
|
||||
# 构建基础上下文的完整映射
|
||||
context_data = await self.builder.build_context_data(self.parameters)
|
||||
|
||||
async def _render_template(self, template: Prompt, context_data: ContextData) -> str:
|
||||
"""渲染模板 - 完全使用现有系统"""
|
||||
# 准备渲染参数
|
||||
render_params = {
|
||||
**context_data.to_dict(),
|
||||
"reply_target_block": self._build_reply_target_block(),
|
||||
"extra_info_block": self.parameters.extra_info,
|
||||
"action_descriptions": self._build_action_descriptions(),
|
||||
}
|
||||
|
||||
# 根据模式选择不同的渲染策略
|
||||
if self.parameters.prompt_mode == "minimal":
|
||||
# 最小化模式，只包含核心信息
|
||||
minimal_params = {
|
||||
"reply_target_block": render_params["reply_target_block"],
|
||||
"identity": render_params.get("identity", ""),
|
||||
"time_block": render_params.get("time_block", ""),
|
||||
}
|
||||
# 使用现有模板的format方法
|
||||
return template.format(**minimal_params)
|
||||
else:
|
||||
# 完整模式 - 使用现有系统的格式化方法
|
||||
return template.format(**render_params)
|
||||
# 获取模板
|
||||
template = await global_prompt_manager.get_prompt_async(self.template_name)
|
||||
|
||||
def _build_reply_target_block(self) -> str:
|
||||
"""构建回复目标块"""
|
||||
if not self.parameters.reply_to:
|
||||
return "现在，请进行回复。"
|
||||
|
||||
sender, content = self._parse_reply_to(self.parameters.reply_to)
|
||||
if sender and content:
|
||||
return f"现在{sender}说：{content}。请对此进行回复。"
|
||||
else:
|
||||
return f"现在有消息：{self.parameters.reply_to}。请对此进行回复。"
|
||||
|
||||
def _build_action_descriptions(self) -> str:
|
||||
"""构建动作描述"""
|
||||
if not self.parameters.available_actions:
|
||||
return ""
|
||||
|
||||
descriptions = []
|
||||
for action_name, action_info in self.parameters.available_actions.items():
|
||||
if isinstance(action_info, dict) and "description" in action_info:
|
||||
descriptions.append(f"- {action_name}: {action_info['description']}")
|
||||
# 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)
|
||||
else:
|
||||
descriptions.append(f"- {action_name}")
|
||||
return await self._build_default_prompt(template, context_data)
|
||||
|
||||
if descriptions:
|
||||
return "你有以下动作能力：\n" + "\n".join(descriptions) + "\n"
|
||||
return ""
|
||||
|
||||
def _parse_reply_to(self, reply_to: str) -> tuple[str, str]:
|
||||
"""解析回复目标"""
|
||||
if ":" in reply_to or "：" in reply_to:
|
||||
import re
|
||||
parts = re.split(r"[:：]", reply_to, maxsplit=1)
|
||||
if len(parts) == 2:
|
||||
return parts[0].strip(), parts[1].strip()
|
||||
return "", reply_to.strip()
|
||||
|
||||
def __str__(self) -> str:
|
||||
"""字符串表示"""
|
||||
return f"SmartPrompt(template={self.template_name}, mode={self.parameters.prompt_mode})"
|
||||
|
||||
def __repr__(self) -> str:
|
||||
"""详细表示"""
|
||||
return f"SmartPrompt(template='{self.template_name}', parameters={self.parameters}, context={self.context})"
|
||||
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。"
|
||||
|
||||
async def _build_s4u_prompt(self, template: Prompt, context_data: Dict[str, Any]) -> str:
|
||||
"""构建S4U模式的完整Prompt"""
|
||||
params = {
|
||||
**context_data,
|
||||
'expression_habits_block': context_data.get('expression_habits_block', ''),
|
||||
'tool_info_block': context_data.get('tool_info_block', ''),
|
||||
'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', ''),
|
||||
'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', ''),
|
||||
'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', ''),
|
||||
}
|
||||
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"""
|
||||
params = {
|
||||
**context_data,
|
||||
'expression_habits_block': context_data.get('expression_habits_block', ''),
|
||||
'tool_info_block': context_data.get('tool_info_block', ''),
|
||||
'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', ''),
|
||||
'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', ''),
|
||||
'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', ''),
|
||||
}
|
||||
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"""
|
||||
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', ''),
|
||||
'chat_target_2': "",
|
||||
'reply_target_block': context_data.get('reply_target_block', ''),
|
||||
'raw_reply': self.parameters.target,
|
||||
'reason': "",
|
||||
'mood_state': 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', ''),
|
||||
}
|
||||
return await global_prompt_manager.format_prompt(self.template_name, **params)
|
||||
|
||||
|
||||
# 工厂函数
|
||||
# 工厂函数 - 简化创建
|
||||
def create_smart_prompt(
|
||||
template_name: str = "default",
|
||||
reply_to: str = "",
|
||||
extra_info: str = "",
|
||||
enable_tool: bool = True,
|
||||
prompt_mode: str = "s4u",
|
||||
chat_id: str = "",
|
||||
**kwargs
|
||||
) -> SmartPrompt:
|
||||
"""快速创建智能Prompt实例的工厂函数"""
|
||||
@@ -426,27 +377,7 @@ def create_smart_prompt(
|
||||
parameters = SmartPromptParameters(
|
||||
reply_to=reply_to,
|
||||
extra_info=extra_info,
|
||||
enable_tool=enable_tool,
|
||||
prompt_mode=prompt_mode,
|
||||
**kwargs
|
||||
)
|
||||
|
||||
context = ChatContext(chat_id=chat_id)
|
||||
|
||||
return SmartPrompt(
|
||||
template_name=template_name,
|
||||
parameters=parameters,
|
||||
context=context
|
||||
)
|
||||
|
||||
|
||||
# 便捷装饰器
|
||||
def prompt_template(name: str):
|
||||
"""模板注册装饰器 - 与现有系统保持一致"""
|
||||
def decorator(func):
|
||||
def wrapper(*args, **kwargs):
|
||||
template_content = func(*args, **kwargs)
|
||||
Prompt(template_content, name=name)
|
||||
return template_content
|
||||
return wrapper
|
||||
return decorator
|
||||
return SmartPrompt(parameters=parameters)
|
||||
Reference in New Issue
Block a user