feat(memory-graph): Phase 1 基础架构实现

- 定义核心数据模型 (MemoryNode, MemoryEdge, Memory)
- 实现配置管理系统 (MemoryGraphConfig)
- 实现向量存储层 (VectorStore with ChromaDB)
- 实现图存储层 (GraphStore with NetworkX)
- 创建设计文档大纲
- 添加基础测试并验证通过

待完成:
- 持久化管理
- 节点去重逻辑
- 记忆构建器
- 记忆检索器

src/memory_graph/config.py

@@ -0,0 +1,145 @@
+"""
+记忆图系统配置管理
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from pathlib import Path
+from typing import Dict, Optional
+
+
+@dataclass
+class ConsolidationConfig:
+    """记忆整理配置"""
+
+    interval_hours: int = 6  # 整理间隔（小时）
+    batch_size: int = 100  # 每次处理记忆数量
+    enable_auto_discovery: bool = True  # 是否启用自动关联发现
+    enable_conflict_detection: bool = True  # 是否启用冲突检测
+
+
+@dataclass
+class RetrievalConfig:
+    """记忆检索配置"""
+
+    default_mode: str = "auto"  # auto/fast/deep
+    max_expand_depth: int = 2  # 最大图扩展深度
+    vector_weight: float = 0.4  # 向量相似度权重
+    graph_distance_weight: float = 0.2  # 图距离权重
+    importance_weight: float = 0.2  # 重要性权重
+    recency_weight: float = 0.2  # 时效性权重
+
+    def __post_init__(self):
+        """验证权重总和"""
+        total = self.vector_weight + self.graph_distance_weight + self.importance_weight + self.recency_weight
+        if abs(total - 1.0) > 0.01:
+            raise ValueError(f"权重总和必须为1.0，当前为 {total}")
+
+
+@dataclass
+class NodeMergerConfig:
+    """节点去重配置"""
+
+    similarity_threshold: float = 0.85  # 相似度阈值
+    context_match_required: bool = True  # 是否要求上下文匹配
+    merge_batch_size: int = 50  # 批量处理大小
+
+    def __post_init__(self):
+        """验证阈值范围"""
+        if not 0.0 <= self.similarity_threshold <= 1.0:
+            raise ValueError(f"相似度阈值必须在 [0, 1] 范围内，当前为 {self.similarity_threshold}")
+
+
+@dataclass
+class StorageConfig:
+    """存储配置"""
+
+    data_dir: Path = field(default_factory=lambda: Path("data/memory_graph"))
+    vector_collection_name: str = "memory_nodes"
+    graph_file_name: str = "memory_graph.json"
+    enable_persistence: bool = True  # 是否启用持久化
+    auto_save_interval: int = 300  # 自动保存间隔（秒）
+
+
+@dataclass
+class MemoryGraphConfig:
+    """记忆图系统总配置"""
+
+    consolidation: ConsolidationConfig = field(default_factory=ConsolidationConfig)
+    retrieval: RetrievalConfig = field(default_factory=RetrievalConfig)
+    node_merger: NodeMergerConfig = field(default_factory=NodeMergerConfig)
+    storage: StorageConfig = field(default_factory=StorageConfig)
+
+    # 时间衰减配置
+    decay_rates: Dict[str, float] = field(
+        default_factory=lambda: {
+            "EVENT": 0.05,  # 事件衰减较快
+            "FACT": 0.01,  # 事实衰减慢
+            "RELATION": 0.005,  # 关系衰减很慢
+            "OPINION": 0.03,  # 观点中等衰减
+        }
+    )
+
+    # 嵌入模型配置
+    embedding_model: Optional[str] = None  # 如果为None，则使用系统默认
+    embedding_dimension: int = 384  # 默认使用 sentence-transformers 的维度
+
+    # 调试和日志
+    enable_debug_logging: bool = False
+    enable_visualization: bool = False  # 是否启用记忆可视化
+
+    @classmethod
+    def from_dict(cls, config_dict: Dict) -> MemoryGraphConfig:
+        """从字典创建配置"""
+        return cls(
+            consolidation=ConsolidationConfig(**config_dict.get("consolidation", {})),
+            retrieval=RetrievalConfig(**config_dict.get("retrieval", {})),
+            node_merger=NodeMergerConfig(**config_dict.get("node_merger", {})),
+            storage=StorageConfig(**config_dict.get("storage", {})),
+            decay_rates=config_dict.get("decay_rates", cls().decay_rates),
+            embedding_model=config_dict.get("embedding_model"),
+            embedding_dimension=config_dict.get("embedding_dimension", 384),
+            enable_debug_logging=config_dict.get("enable_debug_logging", False),
+            enable_visualization=config_dict.get("enable_visualization", False),
+        )
+
+    def to_dict(self) -> Dict:
+        """转换为字典"""
+        return {
+            "consolidation": {
+                "interval_hours": self.consolidation.interval_hours,
+                "batch_size": self.consolidation.batch_size,
+                "enable_auto_discovery": self.consolidation.enable_auto_discovery,
+                "enable_conflict_detection": self.consolidation.enable_conflict_detection,
+            },
+            "retrieval": {
+                "default_mode": self.retrieval.default_mode,
+                "max_expand_depth": self.retrieval.max_expand_depth,
+                "vector_weight": self.retrieval.vector_weight,
+                "graph_distance_weight": self.retrieval.graph_distance_weight,
+                "importance_weight": self.retrieval.importance_weight,
+                "recency_weight": self.retrieval.recency_weight,
+            },
+            "node_merger": {
+                "similarity_threshold": self.node_merger.similarity_threshold,
+                "context_match_required": self.node_merger.context_match_required,
+                "merge_batch_size": self.node_merger.merge_batch_size,
+            },
+            "storage": {
+                "data_dir": str(self.storage.data_dir),
+                "vector_collection_name": self.storage.vector_collection_name,
+                "graph_file_name": self.storage.graph_file_name,
+                "enable_persistence": self.storage.enable_persistence,
+                "auto_save_interval": self.storage.auto_save_interval,
+            },
+            "decay_rates": self.decay_rates,
+            "embedding_model": self.embedding_model,
+            "embedding_dimension": self.embedding_dimension,
+            "enable_debug_logging": self.enable_debug_logging,
+            "enable_visualization": self.enable_visualization,
+        }
+
+
+# 默认配置实例
+DEFAULT_CONFIG = MemoryGraphConfig()