feat: agent memory management — CRUD API + Android management screen

Backend:
- New /api/v1/agents/{id}/memory endpoints: CRUD for global_knowledge,
  knowledge_entities, learning_patterns, vector_memories + import/export
- Fix scope_id column overflow: 3 model columns expanded to hold compound
  keys (user_id:agent_id format, 73 chars vs old VARCHAR(36))
- Config: allow unknown env vars (extra="ignore") for optional overrides

Android:
- MemoryManageScreen: 4-tab UI (全局知识/知识实体/学习模式/对话记忆)
  with search, delete, and FAB to add new entries
- Import/export via ShareSheet and file picker
- AgentListScreen: long-press dropdown menu → 记忆管理 entry point
- NavGraph: memory_manage/{agentId}/{agentName} route with URL encoding

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backend/app/models/agent_vector_memory.py

@@ -21,7 +21,7 @@ class AgentVectorMemory(Base):
 
     id = Column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()))
     scope_kind = Column(String(16), nullable=False, index=True, comment="作用域类型: agent / bare")
-    scope_id = Column(String(36), nullable=False, index=True, comment="作用域 ID: agent_id / user_id")
+    scope_id = Column(String(255), nullable=False, index=True, comment="作用域 ID: agent_id / user_id")
     session_key = Column(String(128), nullable=False, default="", comment="会话标识")
     content_text = Column(Text, nullable=False, comment="原始对话文本")
     embedding = Column(Text, nullable=True, comment="JSON 序列化的 embedding 向量")