"""AI Chat Builder endpoints.

Conversational flow builder:
  POST /ai/chat/sessions              — Start session, get AI greeting
  POST /ai/chat/sessions/{id}/messages — Send message, get AI response
  GET  /ai/chat/sessions/{id}         — Get session state (for resume)
  POST /ai/chat/sessions/{id}/generate — Generate final TreeStructure
  POST /ai/chat/sessions/{id}/import   — Create Tree from generated structure
  DELETE /ai/chat/sessions/{id}        — Abandon session
"""
import logging
from typing import Annotated
from uuid import UUID

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

from app.core.rate_limit import limiter
from app.api.deps import get_current_active_user, get_db, require_engineer_or_admin
from app.core.config import settings
from app.core.ai_chat_service import (
    start_chat_session,
    send_message,
    generate_final_tree,
    get_chat_session,
    MAX_MESSAGES_FREE,
    MAX_MESSAGES_PAID,
)
from app.core.ai_quota_service import check_ai_quota, record_ai_usage, get_user_plan
from app.models.user import User
from app.models.tree import Tree
from app.schemas.ai_chat import (
    AIChatStartRequest,
    AIChatStartResponse,
    AIChatMessageRequest,
    AIChatMessageResponse,
    AIChatSessionResponse,
    AIChatGenerateResponse,
    AIChatImportRequest,
    AIChatImportResponse,
)

logger = logging.getLogger(__name__)

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


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


@router.post("/sessions", response_model=AIChatStartResponse, status_code=201)
@limiter.limit("10/minute")
async def create_session(
    request: Request,
    data: AIChatStartRequest,
    current_user: Annotated[User, Depends(get_current_active_user)],
    db: Annotated[AsyncSession, Depends(get_db)],
    _: None = Depends(require_engineer_or_admin),
):
    """Start a new AI chat builder session."""
    _require_ai_enabled()

    allowed, quota_status = await check_ai_quota(
        user_id=current_user.id,
        account_id=current_user.account_id,
        db=db,
        billing_anchor=current_user.ai_billing_cycle_anchor_at,
        is_super_admin=current_user.is_super_admin,
    )
    if not allowed:
        reset_key = (
            "daily_reset_at"
            if quota_status.get("deny_reason") == "daily"
            else "monthly_reset_at"
        )
        raise HTTPException(
            status_code=status.HTTP_429_TOO_MANY_REQUESTS,
            detail={
                "message": f"AI build limit exceeded ({quota_status['deny_reason']})",
                "reset_at": quota_status.get(reset_key),
                "quota": quota_status,
            },
        )

    plan = await get_user_plan(current_user.account_id, db)

    try:
        session, greeting = await start_chat_session(
            flow_type=data.flow_type,
            user_id=current_user.id,
            account_id=current_user.account_id,
            db=db,
            tree_id=data.tree_id,
        )
    except Exception as e:
        logger.exception("AI chat session start failed: %s", e)
        raise HTTPException(
            status_code=status.HTTP_502_BAD_GATEWAY,
            detail=f"AI provider error ({type(e).__name__}). Please try again.",
        )

    await record_ai_usage(
        user_id=current_user.id,
        account_id=current_user.account_id,
        conversation_id=None,
        generation_type="chat_message",
        tier=plan,
        input_tokens=session.total_input_tokens,
        output_tokens=session.total_output_tokens,
        estimated_cost=(
            session.total_input_tokens * 1.0 / 1_000_000
            + session.total_output_tokens * 5.0 / 1_000_000
        ),
        succeeded=True,
        counts_toward_quota=False,
        error_code=None,
        extra_data={"phase": "scoping", "chat_session_id": str(session.id)},
        db=db,
    )

    await db.commit()

    return AIChatStartResponse(
        session_id=session.id,
        greeting=greeting,
        current_phase=session.current_phase,
    )


@router.post("/sessions/{session_id}/messages", response_model=AIChatMessageResponse)
@limiter.limit("10/minute")
async def post_message(
    request: Request,
    session_id: UUID,
    data: AIChatMessageRequest,
    current_user: Annotated[User, Depends(get_current_active_user)],
    db: Annotated[AsyncSession, Depends(get_db)],
    _: None = Depends(require_engineer_or_admin),
):
    """Send a user message and get AI response."""
    _require_ai_enabled()

    session = await get_chat_session(session_id, current_user.id, db)

    if session.status != "active":
        raise HTTPException(
            status_code=status.HTTP_400_BAD_REQUEST,
            detail=f"Session is {session.status}, cannot send messages",
        )

    plan = await get_user_plan(current_user.account_id, db)
    max_messages = MAX_MESSAGES_PAID if plan != "free" else MAX_MESSAGES_FREE
    if current_user.is_super_admin:
        max_messages = 999

    if session.message_count >= max_messages:
        raise HTTPException(
            status_code=status.HTTP_429_TOO_MANY_REQUESTS,
            detail=f"Maximum messages per session reached ({max_messages}). Generate your tree or start a new session.",
        )

    prev_input = session.total_input_tokens
    prev_output = session.total_output_tokens

    try:
        ai_content, tree_update, new_phase, metadata = await send_message(
            session, data.content, db,
            action_type=data.action_type or "open_chat",
            focal_node_id=data.focal_node_id,
            flow_context=data.flow_context,
        )
    except Exception as e:
        logger.exception("AI chat message failed: %s", e)
        await record_ai_usage(
            user_id=current_user.id,
            account_id=current_user.account_id,
            conversation_id=None,
            generation_type="chat_message",
            tier=plan,
            input_tokens=0,
            output_tokens=0,
            estimated_cost=0,
            succeeded=False,
            counts_toward_quota=False,
            error_code=type(e).__name__,
            extra_data={"chat_session_id": str(session.id)},
            db=db,
        )
        await db.commit()
        raise HTTPException(
            status_code=status.HTTP_502_BAD_GATEWAY,
            detail=f"AI provider error ({type(e).__name__}). Please try again.",
        )

    input_delta = session.total_input_tokens - prev_input
    output_delta = session.total_output_tokens - prev_output
    await record_ai_usage(
        user_id=current_user.id,
        account_id=current_user.account_id,
        conversation_id=None,
        generation_type="chat_message",
        tier=plan,
        input_tokens=input_delta,
        output_tokens=output_delta,
        estimated_cost=(
            input_delta * 1.0 / 1_000_000
            + output_delta * 5.0 / 1_000_000
        ),
        succeeded=True,
        counts_toward_quota=False,
        error_code=None,
        extra_data={"phase": session.current_phase, "chat_session_id": str(session.id)},
        db=db,
    )

    await db.commit()

    return AIChatMessageResponse(
        content=ai_content,
        current_phase=session.current_phase,
        working_tree=session.working_tree,
        tree_metadata=session.tree_metadata if session.tree_metadata else None,
    )


@router.get("/sessions/{session_id}", response_model=AIChatSessionResponse)
async def get_session(
    session_id: UUID,
    current_user: Annotated[User, Depends(get_current_active_user)],
    db: Annotated[AsyncSession, Depends(get_db)],
):
    """Get full session state for resume after page reload."""
    session = await get_chat_session(session_id, current_user.id, db)

    visible_history = [
        msg for msg in session.conversation_history
        if not msg.get("hidden")
    ]

    return AIChatSessionResponse(
        session_id=session.id,
        status=session.status,
        current_phase=session.current_phase,
        flow_type=session.flow_type,
        conversation_history=visible_history,
        working_tree=session.working_tree,
        tree_metadata=session.tree_metadata if session.tree_metadata else None,
        message_count=session.message_count,
        generated_tree=session.working_tree if session.status == "completed" else None,
    )


@router.post("/sessions/{session_id}/generate", response_model=AIChatGenerateResponse)
@limiter.limit("10/minute")
async def generate_tree(
    request: Request,
    session_id: UUID,
    current_user: Annotated[User, Depends(get_current_active_user)],
    db: Annotated[AsyncSession, Depends(get_db)],
    _: None = Depends(require_engineer_or_admin),
):
    """Generate final TreeStructure JSON from conversation."""
    _require_ai_enabled()

    session = await get_chat_session(session_id, current_user.id, db)

    if session.status == "completed" and session.working_tree:
        return AIChatGenerateResponse(
            tree_structure=session.working_tree,
            tree_metadata=session.tree_metadata,
            status="completed",
        )

    if session.status != "active":
        raise HTTPException(
            status_code=status.HTTP_400_BAD_REQUEST,
            detail=f"Session is {session.status}, cannot generate",
        )

    plan = await get_user_plan(current_user.account_id, db)
    prev_input = session.total_input_tokens
    prev_output = session.total_output_tokens

    try:
        tree_structure, metadata = await generate_final_tree(session, db)
    except ValueError as e:
        await record_ai_usage(
            user_id=current_user.id,
            account_id=current_user.account_id,
            conversation_id=None,
            generation_type="chat_generate",
            tier=plan,
            input_tokens=session.total_input_tokens - prev_input,
            output_tokens=session.total_output_tokens - prev_output,
            estimated_cost=0,
            succeeded=False,
            counts_toward_quota=False,
            error_code="invalid_output",
            extra_data={"error": str(e), "chat_session_id": str(session.id)},
            db=db,
        )
        await db.commit()
        raise HTTPException(
            status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
            detail=f"Tree generation failed: {e}",
        )
    except Exception as e:
        logger.exception("AI chat generate failed: %s", e)
        input_delta = session.total_input_tokens - prev_input
        output_delta = session.total_output_tokens - prev_output
        await record_ai_usage(
            user_id=current_user.id,
            account_id=current_user.account_id,
            conversation_id=None,
            generation_type="chat_generate",
            tier=plan,
            input_tokens=input_delta,
            output_tokens=output_delta,
            estimated_cost=0,
            succeeded=False,
            counts_toward_quota=False,
            error_code=type(e).__name__,
            extra_data={"error": str(e), "chat_session_id": str(session.id)},
            db=db,
        )
        await db.commit()

        error_name = type(e).__name__
        if "timeout" in error_name.lower() or "Timeout" in str(e):
            raise HTTPException(
                status_code=status.HTTP_504_GATEWAY_TIMEOUT,
                detail="Tree generation timed out. Please try again.",
            )
        raise HTTPException(
            status_code=status.HTTP_502_BAD_GATEWAY,
            detail=f"AI provider error ({error_name}). Please try again.",
        )

    input_delta = session.total_input_tokens - prev_input
    output_delta = session.total_output_tokens - prev_output
    await record_ai_usage(
        user_id=current_user.id,
        account_id=current_user.account_id,
        conversation_id=None,
        generation_type="chat_generate",
        tier=plan,
        input_tokens=input_delta,
        output_tokens=output_delta,
        estimated_cost=(
            input_delta * 1.0 / 1_000_000
            + output_delta * 5.0 / 1_000_000
        ),
        succeeded=True,
        counts_toward_quota=True,
        error_code=None,
        extra_data={"chat_session_id": str(session.id)},
        db=db,
    )

    session.status = "completed"
    await db.commit()

    return AIChatGenerateResponse(
        tree_structure=tree_structure,
        tree_metadata=metadata,
        status="completed",
    )


@router.post("/sessions/{session_id}/import", response_model=AIChatImportResponse)
@limiter.limit("10/minute")
async def import_tree(
    request: Request,
    session_id: UUID,
    data: AIChatImportRequest,
    current_user: Annotated[User, Depends(get_current_active_user)],
    db: Annotated[AsyncSession, Depends(get_db)],
    _: None = Depends(require_engineer_or_admin),
):
    """Create a Tree record from the generated tree structure."""
    session = await get_chat_session(session_id, current_user.id, db)

    if session.status != "completed" or not session.working_tree:
        raise HTTPException(
            status_code=status.HTTP_400_BAD_REQUEST,
            detail="Session must be completed with a generated tree before importing",
        )

    # Always create a new Tree record (no duplicate check — user may
    # want multiple copies or re-import after edits)
    metadata = session.tree_metadata or {}

    # Extract intake form from metadata if present (procedural flows)
    intake_form = None
    if isinstance(metadata.get("intake_form"), list):
        intake_form = metadata.pop("intake_form")

    tree = Tree(
        name=data.name or metadata.get("name", "AI-Generated Flow"),
        description=data.description or metadata.get("description", ""),
        tree_type=session.flow_type,
        tree_structure=session.working_tree,
        intake_form=intake_form,
        author_id=current_user.id,
        account_id=current_user.account_id,
        category_id=data.category_id,
        is_public=False,
    )
    db.add(tree)
    await db.flush()

    session.generated_tree_id = tree.id
    await db.commit()

    return AIChatImportResponse(
        tree_id=tree.id,
        tree_type=session.flow_type,
    )


@router.delete("/sessions/{session_id}", status_code=204)
@limiter.limit("10/minute")
async def abandon_session(
    request: Request,
    session_id: UUID,
    current_user: Annotated[User, Depends(get_current_active_user)],
    db: Annotated[AsyncSession, Depends(get_db)],
):
    """Abandon a chat session."""
    session = await get_chat_session(session_id, current_user.id, db)
    session.status = "abandoned"
    await db.commit()