Initial project setup: Obsidian intelligent journal organizer
- Add core agent architecture with Command + Skill pattern - Implement Claude API integration for content analysis - Add Obsidian REST API integration for vault operations - Create conversational interface (v2.0) with natural language processing - Add comprehensive configuration management and validation - Include project documentation and developer guides - Set up testing framework with unit, integration, and property tests - Add Kiro specs for Claude API configuration and code quality improvements - Configure project steering files for development guidelines
This commit is contained in:
windyboy
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"""
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意图理解模块
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使用 Claude 理解用户的自然语言输入，提取意图和参数
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"""
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import json
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import logging
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import re
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from dataclasses import dataclass, field
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from datetime import datetime, timedelta
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from typing import Dict, Any, Optional, List
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from ..dependency_manager import get_dependency_manager, graceful_import
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# Try to import anthropic with graceful degradation
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dependency_manager = get_dependency_manager()
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Anthropic = dependency_manager.get_class_from_module('anthropic', 'Anthropic')
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@dataclass
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class Intent:
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"""用户意图"""
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command: str # 对应的命令名称
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parameters: Dict[str, Any] = field(default_factory=dict)
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confidence: float = 1.0
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clarification_needed: bool = False
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clarification_question: Optional[str] = None
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raw_understanding: str = "" # Claude 的原始理解
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def __post_init__(self) -> None:
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"""Validate intent after initialization"""
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if not self.command or not self.command.strip():
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raise ValueError("command cannot be empty")
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if not 0.0 <= self.confidence <= 1.0:
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raise ValueError("confidence must be between 0.0 and 1.0")
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if not isinstance(self.parameters, dict):
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raise ValueError("parameters must be a dictionary")
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class IntentUnderstanding:
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"""意图理解器，使用 Claude 理解用户意图"""
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def __init__(self, config: Optional[Dict[str, Any]] = None) -> None:
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"""
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初始化意图理解器
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Args:
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config: 配置字典
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"""
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self.config: Dict[str, Any] = config or {}
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self.logger: logging.Logger = logging.getLogger("IntentUnderstanding")
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# Initialize Anthropic client with dependency checking
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if Anthropic is not None:
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try:
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self.client: Optional[Anthropic] = Anthropic()
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except Exception as e:
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self.logger.error(f"Failed to initialize Anthropic client: {e}")
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self.client = None
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else:
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self.client = None
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self.logger.warning("Anthropic library not available - Claude-based understanding disabled")
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# 定义支持的命令和它们的关键词
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self.command_keywords: Dict[str, List[str]] = {
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"organize": [
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"整理",
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"组织",
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"分类",
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"归纳",
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"整理日记",
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"organize",
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"arrange",
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"categorize",
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],
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"analyze": [
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"分析",
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"总结",
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"统计",
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"分类",
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"分析日记",
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"analyze",
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"summarize",
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"statistics",
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],
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"export": [
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"导出",
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"保存",
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"生成",
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"输出",
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"导出为",
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"export",
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"save",
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"generate",
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"output",
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],
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"review": [
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"回顾",
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"查看",
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"查询",
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"搜索",
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"浏览",
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"review",
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"view",
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"search",
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"browse",
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],
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}
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# 定义参数提取规则
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self.parameter_patterns: Dict[str, List[str]] = {
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"date": [
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r"(\d{4}[-/]\d{1,2}[-/]\d{1,2})", # YYYY-MM-DD 或 YYYY/M/D
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r"(今天|明天|昨天|前天)", # 相对日期
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r"(这周|本周|上周|下周)", # 周
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r"(这个月|本月|上个月|下个月)", # 月
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],
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"category": [
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r"(经验|教训|待办|问题|成就|改进)",
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r"(experience|lesson|task|problem|achievement|improvement)",
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],
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"format": [r"(PDF|Excel|Word|Markdown|JSON)", r"(pdf|xlsx|docx|md|json)"],
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}
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async def understand(
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self, user_message: str, context: Optional[Dict[str, Any]] = None
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) -> Intent:
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"""
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理解用户的自然语言输入
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Args:
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user_message: 用户的输入消息
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context: 上下文信息（如对话历史）
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Returns:
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Intent: 提取的意图
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"""
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self.logger.debug(f"理解用户消息: {user_message}")
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try:
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# 首先尝试本地模式匹配（快速路径）
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intent = self._match_intent_locally(user_message)
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if intent and intent.confidence > 0.8:
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self.logger.debug(f"本地匹配成功: {intent.command}")
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return intent
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# 使用 Claude 进行更深入的理解
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intent = await self._understand_with_claude(user_message, context)
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return intent
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except Exception as e:
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self.logger.error(f"意图理解失败: {str(e)}")
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return Intent(
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command="unknown",
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clarification_needed=True,
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clarification_question="抱歉，我没有理解您的意思。能否请您重新表述？",
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)
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def _match_intent_locally(self, user_message: str) -> Optional[Intent]:
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"""
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本地模式匹配，快速识别常见意图
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Args:
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user_message: 用户消息
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Returns:
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Intent 或 None
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"""
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message_lower: str = user_message.lower()
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# 逐个检查命令关键词
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for command, keywords in self.command_keywords.items():
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for keyword in keywords:
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if keyword in message_lower:
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# 提取参数
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parameters: Dict[str, Any] = self._extract_parameters_locally(
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user_message
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)
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return Intent(
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command=command, parameters=parameters, confidence=0.9
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)
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return None
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def _extract_parameters_locally(self, user_message: str) -> Dict[str, Any]:
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"""
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本地提取参数
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Args:
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user_message: 用户消息
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Returns:
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提取的参数字典
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"""
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parameters: Dict[str, Any] = {}
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# 提取日期
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for pattern in self.parameter_patterns["date"]:
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match: Optional[re.Match[str]] = re.search(pattern, user_message)
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if match:
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date_str: str = match.group(1)
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parameters["date"] = self._normalize_date(date_str)
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break
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# 提取分类
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for pattern in self.parameter_patterns["category"]:
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match = re.search(pattern, user_message)
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if match:
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parameters["category"] = match.group(1)
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break
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# 提取格式
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for pattern in self.parameter_patterns["format"]:
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match = re.search(pattern, user_message)
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if match:
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parameters["format"] = match.group(1).lower()
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break
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return parameters
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def _normalize_date(self, date_str: str) -> str:
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"""
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规范化日期字符串为 YYYY-MM-DD 格式
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Args:
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date_str: 日期字符串
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Returns:
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规范化的日期字符串
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"""
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today: datetime = datetime.now()
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# 处理相对日期
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if date_str == "今天":
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return today.strftime("%Y-%m-%d")
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elif date_str == "明天":
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return (today + timedelta(days=1)).strftime("%Y-%m-%d")
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elif date_str == "昨天":
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return (today - timedelta(days=1)).strftime("%Y-%m-%d")
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elif date_str == "前天":
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return (today - timedelta(days=2)).strftime("%Y-%m-%d")
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# 处理标准日期格式
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try:
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# 尝试 YYYY-MM-DD 或 YYYY/M/D 格式
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for fmt in ["%Y-%m-%d", "%Y/%m/%d", "%Y-%m-%d"]:
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try:
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parsed: datetime = datetime.strptime(
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date_str.replace("/", "-"), fmt
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)
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return parsed.strftime("%Y-%m-%d")
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except ValueError:
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continue
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except:
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pass
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return date_str
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async def _understand_with_claude(
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self, user_message: str, context: Optional[Dict[str, Any]] = None
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) -> Intent:
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"""
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使用 Claude 理解用户意图
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Args:
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user_message: 用户消息
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context: 上下文信息
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Returns:
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Intent: 提取的意图
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"""
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# Check if Claude is available
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if self.client is None:
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self.logger.warning("Claude client not available, falling back to local matching")
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return Intent(
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command="unknown",
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clarification_needed=True,
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clarification_question="抱歉，AI 理解功能暂时不可用。请使用更具体的命令，如 '整理今天的日记' 或 '分析本周内容'。",
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)
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# Construct prompt
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prompt = self._build_understanding_prompt(user_message, context)
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try:
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# Call Claude
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response = self.client.messages.create(
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model="claude-3-5-sonnet-20241022",
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max_tokens=500,
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messages=[{"role": "user", "content": prompt}],
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)
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# Parse response
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response_text = response.content[0].text
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self.logger.debug(f"Claude 响应: {response_text}")
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return self._parse_claude_response(response_text, user_message)
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except Exception as e:
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self.logger.error(f"Claude API call failed: {str(e)}")
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# Fall back to local matching
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local_intent = self._match_intent_locally(user_message)
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if local_intent:
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return local_intent
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return Intent(
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command="unknown",
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clarification_needed=True,
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clarification_question="抱歉，我在理解您的意图时遇到了问题。请尝试使用更具体的命令。",
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)
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def _build_understanding_prompt(
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self, user_message: str, context: Optional[Dict[str, Any]] = None
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) -> str:
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"""
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构建用于 Claude 的提示
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Args:
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user_message: 用户消息
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context: 上下文信息
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Returns:
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提示文本
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"""
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available_commands: str = ", ".join(self.command_keywords.keys())
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prompt: str = f"""你是一个 Obsidian 日记整理助手的意图识别器。
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用户消息: "{user_message}"
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可用的命令有: {available_commands}
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请分析用户的意图，并返回一个 JSON 对象，包含以下字段:
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{{
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"command": "识别出的命令名称（必须是可用命令之一）",
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"parameters": {{
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"date": "如果用户指定了日期，转换为 YYYY-MM-DD 格式；否则为 null",
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"category": "如果用户指定了分类，提取分类名称；否则为 null",
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"format": "如果用户指定了导出格式，提取格式；否则为 null",
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"other_params": "其他相关参数"
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}},
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"confidence": 0.0 到 1.0 之间的置信度,
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"clarification_needed": 是否需要澄清（布尔值）,
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"clarification_question": "如果需要澄清，提出的问题；否则为 null",
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"reasoning": "简短的推理说明"
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}}
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请确保返回有效的 JSON 格式。"""
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if context and "conversation_history" in context:
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prompt += f"\n\n对话历史（最近的消息）:\n"
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for msg in context["conversation_history"][-3:]:
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prompt += f"- {msg['role']}: {msg['content']}\n"
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return prompt
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def _parse_claude_response(self, response_text: str, user_message: str) -> Intent:
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"""
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解析 Claude 的响应
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Args:
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response_text: Claude 的响应文本
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user_message: 原始用户消息
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Returns:
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Intent: 提取的意图
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"""
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try:
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# 尝试从响应中提取 JSON
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json_match: Optional[re.Match[str]] = re.search(
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r"\{.*\}", response_text, re.DOTALL
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)
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if not json_match:
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raise ValueError("未找到 JSON 响应")
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json_str: str = json_match.group(0)
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data: Dict[str, Any] = json.loads(json_str)
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# 构建 Intent 对象
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intent: Intent = Intent(
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command=data.get("command", "unknown"),
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parameters={
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k: v for k, v in data.get("parameters", {}).items() if v is not None
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},
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confidence=data.get("confidence", 0.7),
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clarification_needed=data.get("clarification_needed", False),
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clarification_question=data.get("clarification_question"),
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raw_understanding=data.get("reasoning", ""),
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)
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return intent
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except Exception as e:
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self.logger.error(f"解析 Claude 响应失败: {str(e)}")
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return Intent(
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command="unknown",
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clarification_needed=True,
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clarification_question="抱歉，我在处理您的请求时遇到了问题。能否请您重新表述？",
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)
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