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

conversation/conversational_agent.py

@@ -0,0 +1,218 @@
+"""
+对话式 Agent 核心模块
+融合对话能力的智能 Agent
+"""
+
+import logging
+from dataclasses import dataclass
+from typing import Dict, Any, Optional, List
+
+from .conversation_state import ConversationState
+from .intent_understanding import IntentUnderstanding, Intent
+from .response_generator import ResponseGenerator
+from ..agent_core import Agent, SkillResult
+
+
+@dataclass
+class ChatResponse:
+    """对话响应"""
+
+    message: str  # 响应消息
+    suggestions: Optional[List[str]] = None  # 建议的后续操作
+    status: str = "success"  # 状态：success, error, waiting_input
+    metadata: Optional[Dict[str, Any]] = None  # 元数据
+
+    def __post_init__(self) -> None:
+        """Validate response after initialization"""
+        if not self.message or not self.message.strip():
+            raise ValueError("message cannot be empty")
+        valid_statuses = ["success", "error", "waiting_input"]
+        if self.status not in valid_statuses:
+            raise ValueError(f"status must be one of {valid_statuses}")
+        if self.suggestions is not None and not isinstance(self.suggestions, list):
+            raise ValueError("suggestions must be a list or None")
+
+
+class ConversationalAgent:
+    """对话式 Agent，融合对话能力的智能 Agent"""
+
+    def __init__(
+        self, command_agent: Agent, config: Optional[Dict[str, Any]] = None
+    ) -> None:
+        """
+        初始化对话式 Agent
+
+        Args:
+            command_agent: 底层的 Command Agent
+            config: 配置字典
+        """
+        self.command_agent: Agent = command_agent
+        self.config: Dict[str, Any] = config or {}
+        self.logger: logging.Logger = logging.getLogger("ConversationalAgent")
+
+        # 初始化各个模块
+        self.intent_understanding: IntentUnderstanding = IntentUnderstanding(config)
+        self.conversation_state: ConversationState = ConversationState()
+        self.response_generator: ResponseGenerator = ResponseGenerator(config)
+
+    async def initialize(self) -> str:
+        """
+        初始化 Agent 并返回欢迎消息
+
+        Returns:
+            欢迎消息
+        """
+        welcome_msg = await self.response_generator.generate_welcome_message()
+        self.conversation_state.add_message("assistant", welcome_msg)
+        self.logger.info("对话式 Agent 已初始化")
+        return welcome_msg
+
+    async def chat(self, user_message: str) -> ChatResponse:
+        """
+        处理用户消息并返回响应
+
+        Args:
+            user_message: 用户的输入消息
+
+        Returns:
+            ChatResponse: 对话响应
+        """
+        self.logger.info(f"处理用户消息: {user_message}")
+
+        try:
+            # 1. 记录用户消息
+            self.conversation_state.add_message("user", user_message)
+
+            # 2. 理解用户意图
+            context: Dict[str, Any] = {
+                "conversation_history": self.conversation_state.get_conversation_history()
+            }
+            intent: Intent = await self.intent_understanding.understand(
+                user_message, context
+            )
+
+            self.logger.debug(f"识别的意图: {intent.command}")
+
+            # 3. 如果需要澄清，返回澄清问题
+            if intent.clarification_needed:
+                response: ChatResponse = ChatResponse(
+                    message=intent.clarification_question or "抱歉，我没有理解您的意思。能否请您重新表述？",
+                    status="waiting_input",
+                )
+                self.conversation_state.add_message("assistant", response.message)
+                return response
+
+            # 4. 映射意图到命令并执行
+            command_result: SkillResult = await self._execute_command(intent)
+
+            # 5. 生成响应
+            if command_result.success:
+                response_msg: str = (
+                    await self.response_generator.generate_success_response(
+                        intent.command, command_result.data, user_message
+                    )
+                )
+            else:
+                response_msg = await self.response_generator.generate_error_response(
+                    intent.command, command_result.error or "未知错误", user_message
+                )
+
+            # 6. 生成建议
+            suggestions: List[str] = await self.response_generator.generate_suggestions(
+                self.conversation_state.context
+            )
+
+            # 7. 构建响应
+            response = ChatResponse(
+                message=response_msg,
+                suggestions=suggestions,
+                status="success" if command_result.success else "error",
+                metadata={
+                    "command": intent.command,
+                    "confidence": intent.confidence,
+                    "reasoning": intent.raw_understanding,
+                },
+            )
+
+            # 8. 记录助手响应
+            self.conversation_state.add_message("assistant", response_msg)
+
+            self.logger.info(f"响应生成完成: {response_msg[:50]}...")
+
+            return response
+
+        except Exception as e:
+            self.logger.error(f"处理消息失败: {str(e)}", exc_info=True)
+
+            error_response: ChatResponse = ChatResponse(
+                message="抱歉，处理您的请求时出现了问题。请稍后重试。", status="error"
+            )
+
+            self.conversation_state.add_message("assistant", error_response.message)
+
+            return error_response
+
+    async def _execute_command(self, intent: Intent) -> SkillResult:
+        """
+        执行命令
+
+        Args:
+            intent: 识别的意图
+
+        Returns:
+            SkillResult: 命令执行结果
+        """
+        try:
+            # 开始任务
+            task = self.conversation_state.start_task(intent.command, intent.parameters)
+
+            # 执行命令
+            result: SkillResult = await self.command_agent.execute_command(
+                intent.command, intent.parameters
+            )
+
+            # 更新任务状态
+            if result.success:
+                self.conversation_state.complete_task(result.data)
+            else:
+                self.conversation_state.fail_task(result.error or "未知错误")
+
+            return result
+
+        except Exception as e:
+            self.logger.error(f"命令执行失败: {str(e)}")
+            self.conversation_state.fail_task(str(e))
+
+            return SkillResult(success=False, error=str(e), message="命令执行失败")
+
+    def get_conversation_history(self) -> List[Dict[str, str]]:
+        """
+        获取对话历史
+
+        Returns:
+            对话历史列表
+        """
+        return self.conversation_state.get_conversation_history()
+
+    def get_state_summary(self) -> Dict[str, Any]:
+        """
+        获取对话状态摘要
+
+        Returns:
+            状态摘要
+        """
+        return self.conversation_state.get_summary()
+
+    def clear_history(self) -> None:
+        """
+        清除对话历史
+        """
+        self.conversation_state.clear_history()
+        self.logger.info("对话历史已清除")
+
+    def reset(self) -> None:
+        """
+        重置对话状态
+        """
+        self.conversation_state.reset()
+        self.logger.info("对话状态已重置")