from pydantic import BaseModel, Field


class LearningAssistantChatRequest(BaseModel):
    """学习助手请求：普通用户面向机构知识库提出医学学习问题。"""

    question: str = Field(..., min_length=2, max_length=1000, description="用户问题")
    top_k: int | None = Field(default=None, ge=1, le=10, description="最终返回给 LLM 的来源片段数")
    score_threshold: float | None = Field(default=None, ge=0, le=1, description="向量相似度过滤阈值")


class LearningAssistantSource(BaseModel):
    """学习助手来源：记录 PDF 文档、页码和引用片段。"""

    document_id: int
    document_title: str | None = None
    file_name: str
    page_start: int
    page_end: int
    chunk_uid: str
    score: float
    quote: str


class LearningAssistantChatResponse(BaseModel):
    """学习助手回答：返回答案、知识库命中状态、循证来源和耗时。"""

    answer: str
    retrieval_hit: bool
    sources: list[LearningAssistantSource] = Field(default_factory=list)
    retrieval_error: str | None = None
    model: str | None = None
    embedding_latency_ms: int | None = None
    search_latency_ms: int | None = None
    llm_latency_ms: int | None = None
    total_latency_ms: int | None = None