"""知识节点相关 API"""

from fastapi import APIRouter, Depends, HTTPException
from sqlalchemy.ext.asyncio import AsyncSession
from sqlalchemy.future import select

from ..database import get_db
from ..dependencies.tenant import get_tenant_id
from ..models import ContextNode
from ..schemas import ContextNodeCreate
from ..services.llm import llm_service

router = APIRouter(prefix="/context_nodes", tags=["context"])


@router.get("/")
async def list_context_nodes(db: AsyncSession = Depends(get_db)):
    result = await db.execute(select(ContextNode))
    nodes = result.scalars().all()
    return [
        {
            "id": node.id,
            "content": node.content,
            "status": node.status,
            "version": node.version,
            "has_embedding": node.embedding is not None,
            "ai_insights": node.ai_insights,
        }
        for node in nodes
    ]


@router.post("/")
async def create_context_node(
    node: ContextNodeCreate,
    db: AsyncSession = Depends(get_db),
    tenant_id: int = Depends(get_tenant_id),
):
    try:
        embedding = await llm_service.get_embedding_async(
            node.content,
            db=db,
            tenant_id=tenant_id,
        )
        insights = await llm_service.extract_context_insights_async(
            node.content,
            db=db,
            tenant_id=tenant_id,
        )
    except RuntimeError:
        raise HTTPException(status_code=403, detail="预算超限，AI 调用被阻止（hard limit）")

    new_node = ContextNode(
        content=node.content,
        embedding=embedding if embedding else None,
        ai_insights=insights,
    )
    db.add(new_node)
    await db.commit()
    await db.refresh(new_node)

    return {
        "id": new_node.id,
        "content": new_node.content,
        "status": new_node.status,
        "version": new_node.version,
        "has_embedding": new_node.embedding is not None,
        "ai_insights": new_node.ai_insights,
    }