# app/api/chat.py
"""
RAG chat endpoint — retrieves relevant page chunks and synthesizes an answer.

BSL 1.1 — BYOK gate: requires PAGEPIPER_OLLAMA_URL or a Paid tier license.
Returns 402 with clear upgrade message if neither is configured.
"""
from __future__ import annotations

import logging
import os

from fastapi import APIRouter, Depends, HTTPException
from pydantic import BaseModel

from app.cloud_session import require_paid_tier
from app.deps import UserCtx, get_user_ctx
from app.services.retriever import Retriever
from app.services.synthesizer import Synthesizer

logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/chat", tags=["chat"])


class ChatTurn(BaseModel):
    role: str  # "user" | "assistant"
    content: str


class ChatRequest(BaseModel):
    message: str
    history: list[ChatTurn] = []
    doc_ids: list[str] | None = None
    top_k: int = 10


class ChatResponse(BaseModel):
    answer: str
    citations: list[dict]


class ChatFeedbackRequest(BaseModel):
    rating: int  # 1 = thumbs up, -1 = thumbs down
    question: str = ""
    answer: str = ""
    doc_ids: list[str] = []


def _get_llm_router():
    """Return LLMRouter if Ollama configured, else None."""
    from app.config import get_llm_config

    cfg = get_llm_config()
    if cfg is None:
        return None
    from circuitforge_core.llm import LLMRouter

    return LLMRouter(cfg)


def _require_llm():
    """Return LLMRouter or raise 402."""
    llm = _get_llm_router()
    if llm is None:
        raise HTTPException(
            status_code=402,
            detail={
                "error": "ollama_required",
                "message": (
                    "RAG chat requires Ollama. Set PAGEPIPER_OLLAMA_URL in your .env file, "
                    "then restart. Run: ollama pull nomic-embed-text && ollama pull mistral:7b"
                ),
            },
        )
    return llm


@router.post("")
def chat(
    req: ChatRequest,
    ctx: UserCtx = Depends(get_user_ctx),
    _tier: str = Depends(require_paid_tier),
) -> ChatResponse:
    llm = _require_llm()

    retriever = Retriever(ctx.bm25)
    chunks = retriever.hybrid_search(
        query=req.message,
        top_k=req.top_k,
        doc_ids=req.doc_ids,
        db_path=ctx.db_path,
        vec_db_path=ctx.vec_db_path,
        llm=llm,
    )

    if not chunks:
        return ChatResponse(
            answer=(
                "I couldn't find any relevant passages. "
                "Try a different query or check which documents are indexed."
            ),
            citations=[],
        )

    synth = Synthesizer(llm)
    result = synth.synthesize(
        message=req.message,
        history=[t.model_dump() for t in req.history],
        chunks=chunks,
    )

    return ChatResponse(
        answer=result.answer,
        citations=[
            {
                "doc_id": c.doc_id,
                "page_number": c.page_number,
                "snippet": c.snippet,
                "bm25_score": c.bm25_score,
            }
            for c in result.citations
        ],
    )


@router.get("/feedback/status")
def chat_feedback_status() -> dict:
    enabled = os.environ.get("PAGEPIPER_CHAT_FEEDBACK", "").lower() in ("1", "true", "yes")
    return {"enabled": enabled}


@router.post("/feedback")
def submit_chat_feedback(
    req: ChatFeedbackRequest,
    ctx: UserCtx = Depends(get_user_ctx),
) -> dict:
    import json
    import sqlite3

    if req.rating not in (1, -1):
        from fastapi import HTTPException
        raise HTTPException(status_code=422, detail="rating must be 1 or -1")

    con = sqlite3.connect(ctx.db_path)
    try:
        con.execute(
            "INSERT INTO chat_feedback (rating, question, answer, doc_ids) VALUES (?, ?, ?, ?)",
            (req.rating, req.question[:2000], req.answer[:4000], json.dumps(req.doc_ids)),
        )
        con.commit()
    finally:
        con.close()
    return {"ok": True}