"""AI auto-fix endpoint for tree validation errors.

POST /ai/fix-tree — accepts a tree with validation errors and returns
AI-generated fix proposals for each error.
"""

import logging
from typing import Annotated

from fastapi import APIRouter, Depends, HTTPException, Request, status
from sqlalchemy.ext.asyncio import AsyncSession

from app.api.deps import get_db, require_engineer_or_admin
from app.core.config import settings
from app.core.rate_limit import limiter
from app.core.ai_fix_service import generate_fixes
from app.models.user import User
from app.schemas.ai_fix import (
    AIFixTreeRequest,
    AIFixTreeResponse,
    AIFixProposal,
    AIFixTokenUsage,
)

logger = logging.getLogger(__name__)

router = APIRouter(prefix="/ai", tags=["ai-fix"])


def _require_ai_enabled() -> None:
    """Raise 503 if AI is not configured."""
    if not settings.ai_enabled:
        raise HTTPException(
            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
            detail="AI fix is not configured. Set GOOGLE_AI_API_KEY or ANTHROPIC_API_KEY.",
        )


@router.post("/fix-tree", response_model=AIFixTreeResponse)
@limiter.limit("10/minute")
async def fix_tree(
    request: Request,
    body: AIFixTreeRequest,
    user: Annotated[User, Depends(require_engineer_or_admin)],
    db: Annotated[AsyncSession, Depends(get_db)],
):
    """Generate AI-powered fixes for tree validation errors."""
    _require_ai_enabled()

    validation_errors = [
        {"node_id": e.node_id, "message": e.message}
        for e in body.validation_errors
    ]

    try:
        fixes, input_tokens, output_tokens = await generate_fixes(
            tree_structure=body.tree_structure,
            tree_name=body.tree_name,
            tree_type=body.tree_type,
            validation_errors=validation_errors,
        )
    except RuntimeError as exc:
        logger.error("AI provider not available: %s", exc)
        raise HTTPException(
            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
            detail=str(exc),
        )
    except Exception as exc:
        logger.exception("Unexpected error in AI fix service")
        raise HTTPException(
            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
            detail="An unexpected error occurred while generating fixes.",
        )

    return AIFixTreeResponse(
        fixes=[AIFixProposal(**f) for f in fixes],
        tokens_used=AIFixTokenUsage(input=input_tokens, output=output_tokens),
    )