Add FastAPI backend with agent system

backend/app/schemas/__init__.py

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+# Schemas package - import directly from submodules
+# e.g.: from app.schemas.auth import UserCreate

backend/app/schemas/agent.py

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+from pydantic import BaseModel
+
+
+class AgentCreate(BaseModel):
+    name: str
+    role: str
+    description: str | None = None
+    system_prompt: str
+
+
+class AgentOut(BaseModel):
+    id: str
+    name: str
+    role: str
+    description: str | None
+    is_active: bool
+    is_default: bool
+
+    model_config = {"from_attributes": True}
+
+
+class AgentMessageOut(BaseModel):
+    id: str
+    agent_id: str
+    conversation_id: str
+    role: str
+    content: str
+
+    model_config = {"from_attributes": True}
+
+
+class AgentStats(BaseModel):
+    agent_id: str
+    call_count: int
+    current_task: str | None
+    status: str  # active | idle | disabled
+
+
+class AgentConfigUpdate(BaseModel):
+    name: str | None = None
+    description: str | None = None
+    system_prompt: str | None = None
+    enabled: bool | None = None
+
+
+class AgentConfigOut(BaseModel):
+    id: str
+    name: str
+    role: str
+    description: str | None
+    system_prompt: str
+    enabled: bool
+    is_active: bool
+
+    model_config = {"from_attributes": True}

backend/app/schemas/auth.py

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+from pydantic import BaseModel, EmailStr
+
+
+class UserCreate(BaseModel):
+    email: EmailStr
+    password: str
+    full_name: str | None = None
+
+
+class UserOut(BaseModel):
+    id: str
+    email: str
+    full_name: str | None
+    is_active: bool
+    is_superuser: bool
+
+    model_config = {"from_attributes": True}
+
+
+class Token(BaseModel):
+    access_token: str
+    token_type: str = "bearer"
+
+
+class TokenPayload(BaseModel):
+    sub: str

backend/app/schemas/conversation.py

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+from pydantic import BaseModel
+from datetime import datetime
+
+
+class MessageCreate(BaseModel):
+    content: str
+
+
+class MessageOut(BaseModel):
+    id: str
+    role: str
+    content: str
+    model: str | None
+    tokens_used: int | None
+    created_at: datetime
+
+    model_config = {"from_attributes": True}
+
+
+class ConversationCreate(BaseModel):
+    title: str | None = None
+
+
+class ConversationOut(BaseModel):
+    id: str
+    title: str | None
+    message_count: int
+    created_at: datetime
+    updated_at: datetime
+
+    model_config = {"from_attributes": True}
+
+
+class ChatRequest(BaseModel):
+    message: str
+    conversation_id: str | None = None
+    agent_id: str | None = None
+    file_ids: list[str] = []  # 新增
+
+
+class ChatResponse(BaseModel):
+    conversation_id: str
+    message_id: str
+    content: str
+    agent_name: str

backend/app/schemas/document.py

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+from pydantic import BaseModel
+from datetime import datetime
+
+
+class DocumentOut(BaseModel):
+    id: str
+    title: str
+    filename: str
+    file_type: str
+    file_size: int
+    summary: str | None
+    chunk_count: int
+    is_indexed: bool
+    created_at: datetime
+
+    model_config = {"from_attributes": True}
+
+
+class DocumentChunkOut(BaseModel):
+    id: str
+    chunk_index: int
+    content: str
+    metadata_: str | None
+
+    model_config = {"from_attributes": True}
+
+
+class SearchRequest(BaseModel):
+    query: str
+    top_k: int = 5
+    user_id: str
+
+
+class SearchResult(BaseModel):
+    chunk_id: str
+    document_id: str
+    document_title: str
+    content: str
+    score: float
+    metadata_: str | None

backend/app/schemas/folder.py

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+from pydantic import BaseModel, Field, field_validator
+from typing import Optional, List
+from datetime import datetime
+
+class FolderCreate(BaseModel):
+    name: str = Field(..., min_length=1, max_length=255)
+    parent_id: Optional[str] = None
+
+    @field_validator('name')
+    @classmethod
+    def validate_name(cls, v):
+        forbidden = '/\\*?:'
+        for c in forbidden:
+            if c in v:
+                raise ValueError(f'Folder name cannot contain: {forbidden}')
+        return v
+
+class FolderUpdate(BaseModel):
+    name: str = Field(..., min_length=1, max_length=255)
+
+class FolderOut(BaseModel):
+    id: str
+    name: str
+    parent_id: Optional[str]
+    created_at: datetime
+    updated_at: datetime
+
+    model_config = {"from_attributes": True}
+
+class FolderTreeOut(BaseModel):
+    id: str
+    name: str
+    parent_id: Optional[str]
+    children: List["FolderTreeOut"] = []
+
+    model_config = {"from_attributes": True}
+
+# 递归模型需要 forward ref
+FolderTreeOut.model_rebuild()

backend/app/schemas/forum.py

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+from pydantic import BaseModel
+
+
+class ForumPostCreate(BaseModel):
+    title: str
+    content: str
+    category: str | None = "discussion"
+
+
+class ForumPostOut(BaseModel):
+    id: str
+    user_id: str
+    title: str
+    content: str
+    category: str | None
+    is_executed: bool
+    execution_result: str | None
+    reply_count: int
+    created_at: str
+
+    model_config = {"from_attributes": True}
+
+
+class ForumReplyCreate(BaseModel):
+    content: str
+
+
+class ForumReplyOut(BaseModel):
+    id: str
+    post_id: str
+    user_id: str | None
+    agent_id: str | None
+    content: str
+    is_ai_reply: bool
+    created_at: str
+
+    model_config = {"from_attributes": True}

backend/app/schemas/graph.py

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+from pydantic import BaseModel, Field
+from typing import Literal
+
+
+class TagProperties(BaseModel):
+    tag_path: str = Field(..., description="完整标签路径，如 '编程语言/Python/异步'")
+    short_name: str = Field(..., description="显示名称，如 '异步'")
+    level: int = Field(..., ge=1, description="层级深度，1为顶级")
+    parent_path: str | None = Field(None, description="父路径，如 '编程语言/Python'")
+    description: str | None = Field(None, description="AI生成的标签描述")
+    color: str | None = Field(None, description="标签颜色，如 '#FF5733'")
+
+
+class KGNodeOut(BaseModel):
+    id: str
+    name: str
+    entity_type: str
+    description: str | None
+    properties_: dict | None
+    importance: float
+    created_at: str
+    # 新增：如果是 tag 节点，返回 tag 属性
+    tag_properties: TagProperties | None = None
+
+    model_config = {"from_attributes": True}
+
+    def model_post_init(self, __context):
+        if self.entity_type == "tag" and self.properties_:
+            self.tag_properties = TagProperties(**self.properties_)
+
+
+class KGEdgeOut(BaseModel):
+    id: str
+    source_id: str
+    target_id: str
+    relation_type: str
+    weight: float
+    properties_: dict | None
+
+    model_config = {"from_attributes": True}
+
+
+class GraphOut(BaseModel):
+    nodes: list[KGNodeOut]
+    edges: list[KGEdgeOut]
+
+
+class KGBuildRequest(BaseModel):
+    user_id: str
+    document_ids: list[str] | None = None  # None = 全量重建
+
+
+class TagExtractRequest(BaseModel):
+    content: str = Field(..., min_length=10)
+    user_id: str
+
+
+class TagExtractResponse(BaseModel):
+    tags: list[TagProperties]
+    tag_count: int
+
+
+class RelatedContentRequest(BaseModel):
+    tag_ids: list[str]
+    user_id: str
+    limit: int = 10

backend/app/schemas/settings.py

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+from pydantic import BaseModel, Field
+from typing import Optional, Literal, List
+from app.schemas.auth import UserOut
+
+# LLM Provider 类型
+LLMProviderType = Literal["openai", "claude", "ollama", "deepseek", "custom"]
+LLMType = Literal["chat", "vlm", "embedding", "rerank"]
+
+
+# 单个模型配置
+class LLMModelConfig(BaseModel):
+    name: str = ""  # 模型名称/别名，用于标识
+    provider: LLMProviderType = "openai"
+    model: str = ""
+    base_url: str = ""
+    api_key: str = ""
+    enabled: bool = True  # 是否启用
+
+
+# LLM 配置输入 - 每种类型支持多个模型
+class LLMConfigIn(BaseModel):
+    chat: Optional[List[LLMModelConfig]] = []
+    vlm: Optional[List[LLMModelConfig]] = []
+    embedding: Optional[List[LLMModelConfig]] = []
+    rerank: Optional[List[LLMModelConfig]] = []
+
+
+# 定时任务配置
+class SchedulerConfigIn(BaseModel):
+    daily_plan_time: Optional[str] = "08:00"
+    forum_scan_interval_minutes: Optional[int] = 30
+    todo_ai_generate_time: Optional[str] = "08:00"
+    enabled: Optional[bool] = True
+
+
+# 用户资料更新
+class ProfileUpdateIn(BaseModel):
+    full_name: Optional[str] = Field(None, min_length=2, max_length=50)
+    password: Optional[str] = Field(None, min_length=8)
+    current_password: Optional[str] = None
+
+
+# 完整设置输出
+class SettingsOut(BaseModel):
+    profile: UserOut
+    llm_config: Optional[dict] = None
+    scheduler_config: Optional[dict] = None
+
+    model_config = {"from_attributes": True}
+
+
+# 测试 LLM 连接请求
+class LLMTestIn(BaseModel):
+    type: LLMType
+    provider: LLMProviderType
+    model: str
+    base_url: str
+    api_key: str

backend/app/schemas/stats.py

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+from pydantic import BaseModel
+from typing import Optional
+
+
+# ===== System Health =====
+class SystemHealth(BaseModel):
+    uptime_seconds: int
+    cpu_percent: float
+    memory_used_mb: float
+    memory_total_mb: float
+    memory_percent: float
+    disk_used_gb: float
+    disk_total_gb: float
+    disk_percent: float
+    active_users_24h: int
+
+
+# ===== Daily Stats Base =====
+class DailyStatItem(BaseModel):
+    date: str
+    count: int
+
+
+class DailyTokenStatItem(BaseModel):
+    date: str
+    input_tokens: int
+    output_tokens: int
+
+
+# ===== Conversation Stats =====
+class ConversationStats(BaseModel):
+    daily_conversations: list[DailyStatItem]
+    daily_messages: list[DailyStatItem]
+    daily_input_tokens: list[DailyTokenStatItem]
+    daily_output_tokens: list[DailyTokenStatItem]
+    totals: dict
+
+
+# ===== Knowledge Stats =====
+class KnowledgeStats(BaseModel):
+    daily_new_tags: list[DailyStatItem]
+    daily_documents: list[DailyStatItem]
+    daily_knowledge_queries: list[DailyStatItem]
+    daily_tag_relations: list[DailyStatItem]
+    totals: dict
+
+
+# ===== Kanban Stats =====
+class KanbanStats(BaseModel):
+    daily_new_tasks: list[DailyStatItem]
+    daily_completed_tasks: list[DailyStatItem]
+    daily_completion_rate: list[DailyStatItem]
+    current_pending_tasks: int
+    totals: dict
+
+
+# ===== Community Stats =====
+class CommunityStats(BaseModel):
+    daily_posts: list[DailyStatItem]
+    daily_replies: list[DailyStatItem]
+    daily_ai_executions: list[DailyStatItem]
+    daily_agent_calls: list[DailyStatItem]
+    totals: dict
+
+
+# ===== Personal Insights =====
+class HourlyActivity(BaseModel):
+    hour: int
+    count: int
+
+
+class TagUsage(BaseModel):
+    tag_path: str
+    usage_count: int
+
+
+class PersonalInsights(BaseModel):
+    hourly_activity: list[HourlyActivity]
+    top_tags: list[TagUsage]
+    token_trend_percent: float
+    this_month_tokens: int
+    last_month_tokens: int

backend/app/schemas/task.py

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+from pydantic import BaseModel
+from datetime import datetime
+from app.models.task import TaskStatus, TaskPriority
+
+
+class TaskCreate(BaseModel):
+    title: str
+    description: str | None = None
+    priority: TaskPriority = TaskPriority.MEDIUM
+    due_date: datetime | None = None
+    tags: list[str] | None = None
+
+
+class TaskUpdate(BaseModel):
+    title: str | None = None
+    description: str | None = None
+    status: TaskStatus | None = None
+    priority: TaskPriority | None = None
+    due_date: datetime | None = None
+    tags: list[str] | None = None
+
+
+class TaskOut(BaseModel):
+    id: str
+    title: str
+    description: str | None
+    status: TaskStatus
+    priority: TaskPriority
+    due_date: datetime | None
+    completed_at: datetime | None
+    tags: str | None
+    created_at: datetime
+    updated_at: datetime
+
+    model_config = {"from_attributes": True}
+
+
+class DailyPlanRequest(BaseModel):
+    user_id: str

backend/app/schemas/todo.py

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+from pydantic import BaseModel
+from datetime import datetime
+from app.models.todo import TodoSource
+
+
+class TodoCreate(BaseModel):
+    title: str
+
+
+class TodoUpdate(BaseModel):
+    title: str | None = None
+    is_completed: bool | None = None
+
+
+class TodoOut(BaseModel):
+    id: str
+    title: str
+    is_completed: bool
+    source: TodoSource
+    source_detail: str | None
+    todo_date: str
+    completed_at: datetime | None
+    created_at: datetime
+    updated_at: datetime
+
+    model_config = {"from_attributes": True}
+
+
+class TodoListOut(BaseModel):
+    items: list[TodoOut]
+    total: int
+    page: int
+    page_size: int
+
+
+class TodoSummaryOut(BaseModel):
+    date: str
+    total: int
+    completed: int
+    pending: int