# app.py (HF Spaces CPU-Optimized)
# RAG sekolah super hemat CPU:
# - Default model: 3B instruct (GGUF) + ctx 1024
# - Retrieval cepat: FAISS top-12 → pilih kalimat pakai lexical overlap (tanpa encode per-kalimat)
# - Encoder dipakai HANYA untuk query & FAISS (1x per request)
# - Jawaban final lewat <final>...</final>, stop di </final>, retry kalau kosong/ellipsis
# - Admin + Auth Postgres tetap sama

import os, json, re, time, logging
from functools import lru_cache, wraps
from typing import Dict, List, Tuple
from dataclasses import dataclass
from datetime import datetime
from zoneinfo import ZoneInfo
from pathlib import Path

from flask import (
    Flask, render_template, request, redirect, url_for, session, jsonify, flash
)

import numpy as np
import faiss
import torch
from transformers import AutoTokenizer, AutoModel
from dotenv import load_dotenv

load_dotenv()

# ========= ENV & LOGGING =========
os.environ.setdefault("KMP_DUPLICATE_LIB_OK", "TRUE")
os.environ.setdefault("OMP_NUM_THREADS", "1")
try:
    torch.set_num_threads(int(os.environ.get("NUM_THREADS", "3")))  # 3 thread cukup di CPU Spaces
    torch.set_num_interop_threads(1)
except Exception:
    pass

logging.basicConfig(level=logging.INFO, format="%(asctime)s | %(levelname)s | %(message)s")
log = logging.getLogger("rag-app")

# ========= IMPORT EKSTERNAL (wrapper & guardrail) =========
from Guardrail import validate_input           # -> bool
from Model import load_model, generate         # -> llama.cpp wrapper

# ========= PATH ROOT =========
BASE_DIR = Path(__file__).resolve().parent

# ========= KONFIG MODEL & RAG (di-tune untuk CPU) =========
GGUF_DEFAULT = "DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf"  # kecil & cepat; upload ke /models
MODEL_PATH   = str(BASE_DIR / "models" / os.getenv("GGUF_FILENAME", GGUF_DEFAULT))
CTX_WINDOW   = int(os.environ.get("CTX_WINDOW", 1024))
N_GPU_LAYERS = int(os.environ.get("N_GPU_LAYERS", 0))
N_THREADS    = int(os.environ.get("NUM_THREADS", 3))

ENCODER_NAME   = os.environ.get("ENCODER_NAME", "intfloat/multilingual-e5-large")
ENCODER_DEVICE = torch.device("cpu")

# Dataset sudah ada di Space → path RELATIF (samakan dengan struktur kamu)
SUBJECTS: Dict[str, Dict[str, str]] = {
    "ipas": {
        "index": str(BASE_DIR / "Rag-Pipeline" / "Vektor Database" / "Ipas" / "IPA_index.index"),
        "chunks": str(BASE_DIR / "Dataset" / "Ipas" / "Chunk" / "ipas_chunks.json"),
        "embeddings": str(BASE_DIR / "Dataset" / "Ipas" / "Embedd"/ "ipas_embeddings.npy"),
        "label": "IPAS",
        "desc": "Ilmu Pengetahuan Alam dan Sosial"
    },
    "penjas": {
        "index": str(BASE_DIR / "Rag-Pipeline" / "Vektor Database" / "Penjas" / "PENJAS_index.index"),
        "chunks": str(BASE_DIR / "Dataset" / "Penjas" / "Chunk" / "penjas_chunks.json"),
        "embeddings": str(BASE_DIR / "Dataset" / "Penjas" / "Embedd" / "penjas_embeddings.npy"),
        "label": "PJOK",
        "desc": "Pendidikan Jasmani, Olahraga, dan Kesehatan"
    },
    "pancasila": {
        "index": str(BASE_DIR / "Rag-Pipeline" / "Vektor Database" / "Pancasila" / "PANCASILA_index.index"),
        "chunks": str(BASE_DIR / "Dataset" / "Pancasila" / "Chunk" / "pancasila_chunks.json"),
        "embeddings": str(BASE_DIR / "Dataset" / "Pancasila" / "Embedd" / "pancasila_embeddings.npy"),
        "label": "PANCASILA",
        "desc": "Pendidikan Pancasila dan Kewarganegaraan"
    }
}

# ======= Threshold & parameter cepat (sudah dilonggarkan & adaptif) =======
TOP_K_FAISS   = int(os.environ.get("TOP_K_FAISS", 15))
TOP_K_FINAL   = int(os.environ.get("TOP_K_FINAL", 10))
MIN_COSINE    = float(os.environ.get("MIN_COSINE", 0.83))  # dulu 0.83
MIN_LEXICAL   = float(os.environ.get("MIN_LEXICAL", 0.10))  # dulu 0.8 → terlalu ketat utk query pendek
FALLBACK_TEXT = os.environ.get("FALLBACK_TEXT", "maap pengetahuan tidak ada dalam database")
GUARDRAIL_BLOCK_TEXT = os.environ.get("GUARDRAIL_BLOCK_TEXT", "maap, pertanyaan ditolak oleh guardrail")
ENABLE_PROFILING = os.environ.get("ENABLE_PROFILING", "false").lower() == "true"

# ========= APP =========
app = Flask(__name__)
app.secret_key = os.environ.get("FLASK_SECRET_KEY", "dev-secret-please-change")

from werkzeug.middleware.proxy_fix import ProxyFix
app.wsgi_app = ProxyFix(app.wsgi_app, x_for=1, x_proto=1, x_host=1)
app.config.update(
    SESSION_COOKIE_NAME="session",
    SESSION_COOKIE_SAMESITE="None",
    SESSION_COOKIE_SECURE=True,
    SESSION_COOKIE_HTTPONLY=True,
    SESSION_COOKIE_PATH="/",
    PREFERRED_URL_SCHEME="https",
)

# ========= GLOBALS =========
ENCODER_TOKENIZER = None
ENCODER_MODEL     = None
LLM               = None

@dataclass(frozen=True)
class SubjectAssets:
    index: faiss.Index
    texts: List[str]
    embs: np.ndarray

# ========= TEKS UTIL =========
STOPWORDS_ID = {
    "yang","dan","atau","pada","di","ke","dari","itu","ini","adalah","dengan",
    "untuk","serta","sebagai","oleh","dalam","akan","kamu","apa","karena",
    "agar","sehingga","terhadap","dapat","juga","para","diri",
}
TOKEN_RE = re.compile(r"[A-Za-zÀ-ÖØ-öø-ÿ]+", re.UNICODE)

@lru_cache(maxsize=4096)
def _tok_cached(word: str) -> str:
    return word.lower()

def tok_id(text: str) -> List[str]:
    return [tw for w in TOKEN_RE.findall(text or "") if (tw := _tok_cached(w)) not in STOPWORDS_ID]

def lexical_overlap(query: str, sent: str) -> float:
    q = set(tok_id(query)); s = set(tok_id(sent))
    if not q or not s:
        return 0.0
    return len(q & s) / max(1, len(q | s))

QUESTION_LIKE_RE = re.compile(r"(^\s*(apa|mengapa|bagaimana|sebutkan|jelaskan)\b|[?]$)", re.IGNORECASE)
# Relaksasi filter instruksi: hanya pola yang benar-benar instruksi tugas di awal kalimat
INSTRUCTION_RE   = re.compile(r"^\s*(kerjakan|tugas\s*:|diskusikan|latihan\s*:)\b", re.IGNORECASE)

META_PREFIX_PATTERNS = [
    r"berdasarkan\s+(?:kalimat|sumber|teks|konten|informasi)(?:\s+(?:di\s+atas|tersebut))?",
    r"menurut\s+(?:sumber|teks|konten)",
    r"merujuk\s+pada",
    r"mengacu\s+pada",
    r"bersumber\s+dari",
    r"dari\s+(?:kalimat|sumber|teks|konten)"
]
META_PREFIX_RE = re.compile(r"^\s*(?:" + r"|".join(META_PREFIX_PATTERNS) + r")\s*[:\-–—,]?\s*", re.IGNORECASE)

def clean_prefix(t: str) -> str:
    t = (t or "").strip()
    for _ in range(3):
        t2 = META_PREFIX_RE.sub("", t).lstrip()
        if t2 == t:
            break
        t = t2
    return t

def strip_meta_sentence(s: str) -> str:
    s = clean_prefix(s or "")
    if re.match(r"^\s*(berdasarkan|menurut|merujuk|mengacu|bersumber|dari)\b", s, re.IGNORECASE):
        s = re.sub(r"^\s*[^,.;!?]*[,.;!?]\s*", "", s) or s
    s = clean_prefix(s)
    return s.strip()

SENT_SPLIT_RE = re.compile(r"(?<=[.!?])\s+")

def split_sentences_fast(text: str) -> List[str]:
    outs = []
    for p in SENT_SPLIT_RE.split(text or ""):
        s = clean_prefix((p or "").strip())
        if not s:
            continue
        # Opsi: jika dataset kamu sering tanpa tanda akhir, boleh aktifkan ini:
        # if s and s[-1] not in ".!?":
        #     s += "."
        if QUESTION_LIKE_RE.search(s):
            continue
        if INSTRUCTION_RE.search(s):
            continue
        if len(s) < 12:
            continue
        outs.append(s)
    return outs

# ========= MODEL WARMUP =========
def warmup_models():
    global ENCODER_TOKENIZER, ENCODER_MODEL, LLM
    if ENCODER_TOKENIZER is None or ENCODER_MODEL is None:
        log.info(f"[INIT] Load encoder: {ENCODER_NAME} (CPU)")
        ENCODER_TOKENIZER = AutoTokenizer.from_pretrained(ENCODER_NAME)
        ENCODER_MODEL = AutoModel.from_pretrained(ENCODER_NAME).to(ENCODER_DEVICE).eval()
    if LLM is None:
        log.info(f"[INIT] Load LLM: {MODEL_PATH} | ctx={CTX_WINDOW} | threads={N_THREADS}")
        LLM = load_model(MODEL_PATH, n_ctx=CTX_WINDOW, n_gpu_layers=N_GPU_LAYERS, n_threads=N_THREADS)

# ========= ASSETS =========
@lru_cache(maxsize=8)
def load_subject_assets(subject_key: str) -> "SubjectAssets":
    if subject_key not in SUBJECTS:
        raise ValueError(f"Unknown subject: {subject_key}")
    cfg = SUBJECTS[subject_key]
    log.info(f"[ASSETS] Loading subject={subject_key} | index={cfg['index']}")
    if not os.path.exists(cfg["index"]):
        raise FileNotFoundError(cfg["index"])
    if not os.path.exists(cfg["chunks"]):
        raise FileNotFoundError(cfg["chunks"])
    if not os.path.exists(cfg["embeddings"]):
        raise FileNotFoundError(cfg["embeddings"])
    index = faiss.read_index(cfg["index"])
    with open(cfg["chunks"], "r", encoding="utf-8") as f:
        texts = [it.get("text", "") for it in json.load(f)]
    embs = np.load(cfg["embeddings"])  # (N, dim)
    if index.ntotal != len(embs):
        raise RuntimeError(f"Mismatch ntotal({index.ntotal}) vs emb({len(embs)})")
    return SubjectAssets(index=index, texts=texts, embs=embs)

# ========= ENCODER =========
@torch.inference_mode()
@lru_cache(maxsize=1024)
def encode_query_exact(text: str) -> np.ndarray:
    toks = ENCODER_TOKENIZER(text, padding=True, truncation=True, return_tensors="pt").to(ENCODER_DEVICE)
    out = ENCODER_MODEL(**toks)
    vec = out.last_hidden_state.mean(dim=1)
    return vec.cpu().numpy()

def cosine_sim(a: np.ndarray, b: np.ndarray) -> float:
    a = np.asarray(a).reshape(-1); b = np.asarray(b).reshape(-1)
    denom = (np.linalg.norm(a) * np.linalg.norm(b)) + 1e-12
    return float(np.dot(a, b) / denom)

# ========= RETRIEVAL CEPAT =========
def best_cosine_from_faiss(query: str, subject_key: str) -> float:
    assets = load_subject_assets(subject_key)
    q = encode_query_exact(query)
    _, I = assets.index.search(q, TOP_K_FAISS)
    qv = q.reshape(-1)
    best = -1.0
    for i in I[0]:
        if 0 <= i < len(assets.texts):
            best = max(best, cosine_sim(qv, assets.embs[i]))
    return best

def retrieve_top_chunks(query: str, subject_key: str) -> List[str]:
    assets = load_subject_assets(subject_key)
    q = encode_query_exact(query)
    _, idx = assets.index.search(q, TOP_K_FAISS)
    idxs = [i for i in idx[0] if 0 <= i < len(assets.texts)]
    return [assets.texts[i] for i in idxs[:TOP_K_FINAL]]

# ======= Seleksi kalimat dua-fase (ketat → longgar) =======
def pick_best_sentences_fast(query: str, chunks: List[str], top_k: int = 4) -> List[str]:
    """
    Fase-1: ambil kalimat dg overlap >= MIN_LEXICAL
    Fase-2 (fallback): kalau hasil < top_k, ambil kalimat skor tertinggi meski < MIN_LEXICAL
    """
    cands: List[Tuple[float, str]] = []
    for ch in chunks:
        for s in split_sentences_fast(ch):
            ovl = lexical_overlap(query, s)
            L = len(s)
            len_bonus = 0.05 if 50 <= L <= 220 else 0.0
            score = ovl + len_bonus
            cands.append((score, clean_prefix(s)))

    if not cands:
        log.info("[RAG] Tidak ada kandidat kalimat (split_sentences menghasilkan 0).")
        return []

    cands.sort(key=lambda x: x[0], reverse=True)

    strict = [s for sc, s in cands if sc + 1e-6 >= MIN_LEXICAL]
    if len(strict) >= top_k:
        return strict[:top_k]

    log.info(f"[RAG] Kalimat relevan < {top_k} pada MIN_LEXICAL={MIN_LEXICAL}; fallback longgar dipakai.")
    return [s for _, s in cands[:top_k]]

# ========= PROMPT =========
def build_prompt(user_query: str, sentences: List[str]) -> str:
    block = "\n".join(f"- {clean_prefix(s)}" for s in sentences)
    system = (
        "Kamu asisten RAG.\n"
        f"- Jika tidak ada kalimat yang relevan, tulis persis: {FALLBACK_TEXT}\n"
        "- Jawab TEPAT 1 kalimat, ringkas, Bahasa Indonesia baku (≥ 6 kata).\n"
        "- Tanpa frasa meta (berdasarkan/menurut/merujuk/mengacu/bersumber).\n"
        "- Tulis jawaban final di dalam tag <final>Jawaban.</final> dan jangan menulis apa pun setelah </final>."
    )
    fewshot = (
        "Contoh format: \n"
        "KALIMAT SUMBER:\n- Air memuai saat dipanaskan.\n"
        "PERTANYAAN: Apa yang terjadi pada air saat dipanaskan?\n"
        "<final>Air akan memuai ketika dipanaskan.</final>\n"
    )
    return (
        f"{system}\n\n{fewshot}\n"
        f"KALIMAT SUMBER:\n{block}\n\n"
        f"PERTANYAAN: {user_query}\n"
        f"TULIS JAWABAN DI DALAM <final>...</final> SAJA:"
    )

@lru_cache(maxsize=1024)
def validate_input_cached(q: str) -> bool:
    try:
        return validate_input(q)
    except Exception as e:
        log.exception(f"[GUARDRAIL] error: {e}")
        return False

# ========= AUTH (POSTGRES) =========
from werkzeug.security import generate_password_hash, check_password_hash
from sqlalchemy import create_engine, Column, Integer, String, Text, Boolean, func, or_
from sqlalchemy.orm import sessionmaker, scoped_session, declarative_base, Session

POSTGRES_URL = os.environ.get("POSTGRES_URL")
if not POSTGRES_URL:
    raise RuntimeError("POSTGRES_URL tidak ditemukan. Set di Settings → Variables.")

engine = create_engine(POSTGRES_URL, pool_pre_ping=True, future=True, echo=False)
SessionLocal = scoped_session(sessionmaker(bind=engine, autoflush=False, autocommit=False, future=True))
Base = declarative_base()

class User(Base):
    __tablename__ = "users"
    id = Column(Integer, primary_key=True)
    username = Column(String(50), unique=True, nullable=False, index=True)
    email = Column(String(120), unique=True, nullable=False, index=True)
    password = Column(Text, nullable=False)
    is_active = Column(Boolean, default=True, nullable=False)
    is_admin  = Column(Boolean, default=False, nullable=False)

class ChatHistory(Base):
    __tablename__ = "chat_history"
    id = Column(Integer, primary_key=True)
    user_id = Column(Integer, nullable=False, index=True)
    subject_key = Column(String(50), nullable=False, index=True)
    role = Column(String(10), nullable=False)
    message = Column(Text, nullable=False)
    timestamp = Column(Integer, server_default=func.extract("epoch", func.now()))

Base.metadata.create_all(bind=engine)

JKT_TZ = ZoneInfo("Asia/Jakarta")

@app.template_filter("fmt_ts")
def fmt_ts(epoch_int: int):
    try:
        dt = datetime.fromtimestamp(int(epoch_int), tz=JKT_TZ)
        return dt.strftime("%d %b %Y %H:%M")
    except Exception:
        return "-"

def db():
    return SessionLocal()

def login_required(view_func):
    @wraps(view_func)
    def wrapper(*args, **kwargs):
        if not session.get("logged_in"):
            return redirect(url_for("auth_login"))
        return view_func(*args, **kwargs)
    return wrapper

def admin_required(view_func):
    @wraps(view_func)
    def wrapper(*args, **kwargs):
        if not session.get("logged_in"):
            return redirect(url_for("auth_login"))
        if not session.get("is_admin"):
            flash("Hanya admin yang boleh mengakses halaman itu.", "error")
            return redirect(url_for("subjects"))
        return view_func(*args, **kwargs)
    return wrapper

# ========= ROUTES =========
@app.route("/")
def root():
    return redirect(url_for("auth_login"))

@app.route("/auth/login", methods=["GET", "POST"])
def auth_login():
    if request.method == "POST":
        identity = (
            request.form.get("identity") or request.form.get("email") or request.form.get("username") or ""
        ).strip().lower()
        pw_input = (request.form.get("password") or "").strip()
        if not identity or not pw_input:
            flash("Mohon isi email/username dan password.", "error")
            return render_template("login.html"), 400
        s = db()
        try:
            user = (
                s.query(User)
                .filter(or_(func.lower(User.username) == identity, func.lower(User.email) == identity))
                .first()
            )
            log.info(f"[LOGIN] identity='{identity}' found={bool(user)} active={getattr(user,'is_active',None)}")
            ok = bool(user and user.is_active and check_password_hash(user.password, pw_input))
        finally:
            s.close()
        if not ok:
            flash("Identitas atau password salah.", "error")
            return render_template("login.html"), 401
        session["logged_in"] = True
        session["user_id"] = user.id
        session["username"] = user.username
        session["is_admin"] = bool(user.is_admin)
        log.info(f"[LOGIN] OK user_id={user.id}; session set.")
        return redirect(url_for("subjects"))
    return render_template("login.html")

@app.route("/whoami")
def whoami():
    return {
        "logged_in": bool(session.get("logged_in")),
        "user_id": session.get("user_id"),
        "username": session.get("username"),
        "is_admin": session.get("is_admin"),
    }

@app.route("/auth/register", methods=["GET", "POST"])
def auth_register():
    if request.method == "POST":
        username = (request.form.get("username") or "").strip().lower()
        email    = (request.form.get("email") or "").strip().lower()
        pw       = (request.form.get("password") or "").strip()
        confirm  = (request.form.get("confirm") or "").strip()
        if not username or not email or not pw:
            flash("Semua field wajib diisi.", "error")
            return render_template("register.html"), 400
        if len(pw) < 6:
            flash("Password minimal 6 karakter.", "error")
            return render_template("register.html"), 400
        if pw != confirm:
            flash("Konfirmasi password tidak cocok.", "error")
            return render_template("register.html"), 400
        s = db()
        try:
            existed = (
                s.query(User)
                .filter(or_(func.lower(User.username) == username, func.lower(User.email) == email))
                .first()
            )
            if existed:
                flash("Username/Email sudah terpakai.", "error")
                return render_template("register.html"), 409
            u = User(username=username, email=email, password=generate_password_hash(pw), is_active=True)
            s.add(u); s.commit()
        finally:
            s.close()
        flash("Registrasi berhasil. Silakan login.", "success")
        return redirect(url_for("auth_login"))
    return render_template("register.html")

@app.route("/auth/logout")
def auth_logout():
    session.clear()
    return redirect(url_for("auth_login"))

@app.route("/about")
def about():
    return render_template("about.html")

@app.route("/subjects")
@login_required
def subjects():
    log.info(f"[SESSION DEBUG] logged_in={session.get('logged_in')} user_id={session.get('user_id')}")
    return render_template("home.html", subjects=SUBJECTS)

@app.route("/chat/<subject_key>")
@login_required
def chat_subject(subject_key: str):
    if subject_key not in SUBJECTS:
        return redirect(url_for("subjects"))
    session["subject_selected"] = subject_key
    label = SUBJECTS[subject_key]["label"]
    s = db()
    try:
        uid = session.get("user_id")
        rows = (
            s.query(ChatHistory)
            .filter_by(user_id=uid, subject_key=subject_key)
            .order_by(ChatHistory.id.asc())
            .all()
        )
        history = [{"role": r.role, "message": r.message} for r in rows]
    finally:
        s.close()
    return render_template("chat.html", subject=subject_key, subject_label=label, history=history)

@app.route("/health")
def health():
    return jsonify({
        "ok": True,
        "encoder_loaded": ENCODER_MODEL is not None,
        "llm_loaded": LLM is not None,
        "model_path": MODEL_PATH,
        "ctx_window": CTX_WINDOW,
        "threads": N_THREADS,
    })

@app.route("/ask/<subject_key>", methods=["POST"])
@login_required
def ask(subject_key: str):
    if subject_key not in SUBJECTS:
        return jsonify({"ok": False, "error": "invalid subject"}), 400
    warmup_models()
    t0 = time.perf_counter()

    data = request.get_json(silent=True) or {}
    query = (data.get("message") or "").strip()
    if not query:
        return jsonify({"ok": False, "error": "empty query"}), 400
    if not validate_input_cached(query):
        return jsonify({"ok": True, "answer": GUARDRAIL_BLOCK_TEXT})

    try:
        _ = load_subject_assets(subject_key)
    except Exception as e:
        log.exception(f"[ASSETS] error: {e}")
        return jsonify({"ok": False, "error": f"subject assets error: {e}"}), 500

    best = best_cosine_from_faiss(query, subject_key)
    log.info(f"[RAG] Subject={subject_key.upper()} | Best cosine={best:.3f}")
    if best < MIN_COSINE:
        log.info(f"[RAG] Fallback by cosine: {best:.3f} < {MIN_COSINE}")
        return jsonify({"ok": True, "answer": FALLBACK_TEXT})

    chunks = retrieve_top_chunks(query, subject_key)
    if not chunks:
        log.info("[RAG] Fallback by chunks=0")
        return jsonify({"ok": True, "answer": FALLBACK_TEXT})

    sentences = pick_best_sentences_fast(query, chunks, top_k=5)
    log.info(f"[RAG] sentences_selected={len(sentences)} (min_lex={MIN_LEXICAL}, top_k={5})")
    if not sentences:
        log.info("[RAG] Fallback by sentences=0")
        return jsonify({"ok": True, "answer": FALLBACK_TEXT})

    prompt = build_prompt(query, sentences)

    try:
        # PASS-1: deterministik & singkat
        raw_answer = generate(
            LLM,
            prompt,
            max_tokens=int(os.environ.get("MAX_TOKENS", 64)),
            temperature=float(os.environ.get("TEMP", 0.2)),
            top_p=1.0,
            stop=["</final>"]
        ) or ""
        raw_answer = raw_answer.strip()
        log.info(f"[LLM] Raw answer repr (pass1): {repr(raw_answer)}")

        # Bersihkan tag <think> dan ambil isi <final>
        text = re.sub(r"<think\b[^>]*>.*?</think>", "", raw_answer, flags=re.DOTALL | re.IGNORECASE).strip()
        text = re.sub(r"</?think\b[^>]*>", "", text, flags=re.IGNORECASE).strip()
        m_final = re.search(r"<final>\s*(.+)$", text, flags=re.IGNORECASE | re.DOTALL)
        cleaned = (m_final.group(1).strip() if m_final else re.sub(r"<[^>]+>", "", text).strip())

        def _alpha_tokens(s: str) -> List[str]:
            return re.findall(r"[A-Za-zÀ-ÖØ-öø-ÿ]+", s or "")

        def _is_bad(s: str) -> bool:
            s2 = (s or "").strip()
            if not s2:
                return True
            if s2 in {"...", ".", "..", "…"}:
                return True
            toks = _alpha_tokens(s2)
            if len(toks) >= 4:
                return False
            if any(t.lower() in {"newton","n","kg","m","s"} for t in toks) and len(toks) >= 3:
                return False
            return True

        if _is_bad(cleaned):
            prompt_retry = (
                prompt
                + "\n\nULANGI DENGAN TAAT FORMAT: "
                  "Tulis satu kalimat faktual tanpa placeholder/ellipsis, "
                  "mulai huruf kapital dan akhiri titik. "
                  "Tulis hanya di dalam <final>...</final>."
            )
            raw_answer2 = generate(
                LLM,
                prompt_retry,
                max_tokens=int(os.environ.get("MAX_TOKENS", 64)),
                temperature=0.2,
                top_p=1.0,
                stop=["</final>"]
            ) or ""
            raw_answer2 = raw_answer2.strip()
            log.info(f"[LLM] Raw answer repr (pass2): {repr(raw_answer2)}")

            text2 = re.sub(r"<think\b[^>]*>.*?</think>", "", raw_answer2, flags=re.DOTALL | re.IGNORECASE).strip()
            text2 = re.sub(r"</?think\b[^>]*>", "", text2, flags=re.IGNORECASE).strip()
            m_final2 = re.search(r"<final>\s*(.+)$", text2, flags=re.IGNORECASE | re.DOTALL)
            cleaned2 = (m_final2.group(1).strip() if m_final2 else re.sub(r"<[^>]+>", "", text2).strip())
            cleaned = cleaned2 or cleaned

        answer = cleaned

    except Exception as e:
        log.exception(f"[LLM] generate error: {e}")
        return jsonify({"ok": True, "answer": FALLBACK_TEXT})

    # Ambil 1 kalimat pertama saja
    m = re.search(r"(.+?[.!?])(\s|$)", answer)
    answer = (m.group(1) if m else answer).strip()
    answer = strip_meta_sentence(answer)

    # Simpan history
    try:
        s = db()
        uid = session.get("user_id")
        s.add_all([
            ChatHistory(user_id=uid, subject_key=subject_key, role="user", message=query),
            ChatHistory(user_id=uid, subject_key=subject_key, role="bot",  message=answer),
        ])
        s.commit()
    except Exception as e:
        log.exception(f"[DB] gagal simpan chat history: {e}")
    finally:
        try:
            s.close()
        except Exception:
            pass

    if not answer or len(answer) < 2:
        answer = FALLBACK_TEXT

    if ENABLE_PROFILING:
        log.info({
            "latency_total": time.perf_counter() - t0,
            "subject": subject_key,
            "faiss_best": best,
        })

    return jsonify({"ok": True, "answer": answer})

# ===== Admin =====
@app.route("/admin")
@admin_required
def admin_dashboard():
    s = db()
    try:
        total_users  = s.query(func.count(User.id)).scalar() or 0
        total_active = s.query(func.count(User.id)).filter(User.is_active.is_(True)).scalar() or 0
        total_admins = s.query(func.count(User.id)).filter(User.is_admin.is_(True)).scalar() or 0
        total_msgs   = s.query(func.count(ChatHistory.id)).scalar() or 0
    finally:
        s.close()
    return render_template("admin_dashboard.html", total_users=total_users, total_active=total_active, total_admins=total_admins, total_msgs=total_msgs)

@app.route("/admin/users")
@admin_required
def admin_users():
    q = (request.args.get("q") or "").strip().lower()
    page = max(int(request.args.get("page", 1)), 1)
    per_page = min(max(int(request.args.get("per_page", 20)), 5), 100)
    s = db()
    try:
        base = s.query(User)
        if q:
            base = base.filter(or_(func.lower(User.username).like(f"%{q}%"), func.lower(User.email).like(f"%{q}%")))
        total = base.count()
        users = base.order_by(User.id.asc()).offset((page - 1) * per_page).limit(per_page).all()
        user_ids = [u.id for u in users] or [-1]
        counts = dict(s.query(ChatHistory.user_id, func.count(ChatHistory.id)).filter(ChatHistory.user_id.in_(user_ids)).group_by(ChatHistory.user_id).all())
    finally:
        s.close()
    return render_template("admin_users.html", users=users, counts=counts, q=q, page=page, per_page=per_page, total=total)

@app.route("/admin/history")
@admin_required
def admin_history():
    q        = (request.args.get("q") or "").strip().lower()
    username = (request.args.get("username") or "").strip().lower()
    subject  = (request.args.get("subject") or "").strip().lower()
    role     = (request.args.get("role") or "").strip().lower()
    page = max(int(request.args.get("page", 1)), 1)
    per_page = min(max(int(request.args.get("per_page", 30)), 5), 200)
    s = db()
    try:
        base = (s.query(ChatHistory, User).join(User, User.id == ChatHistory.user_id))
        if q:
            base = base.filter(func.lower(ChatHistory.message).like(f"%{q}%"))
        if username:
            base = base.filter(or_(func.lower(User.username) == username, func.lower(User.email) == username))
        if subject:
            base = base.filter(func.lower(ChatHistory.subject_key) == subject)
        if role in ("user", "bot"):
            base = base.filter(ChatHistory.role == role)
        total = base.count()
        rows = base.order_by(ChatHistory.id.desc()).offset((page - 1) * per_page).limit(per_page).all()
    finally:
        s.close()
    items = [{
        "id": r.ChatHistory.id,
        "username": r.User.username,
        "email": r.User.email,
        "subject": r.ChatHistory.subject_key,
        "role": r.ChatHistory.role,
        "message": r.ChatHistory.message,
        "timestamp": r.ChatHistory.timestamp,
    } for r in rows]
    return render_template("admin_history.html", items=items, subjects=SUBJECTS, q=q, username=username, subject=subject, role=role, page=page, per_page=per_page, total=total)

def _is_last_admin(s: Session) -> bool:
    return (s.query(func.count(User.id)).filter(User.is_admin.is_(True)).scalar() or 0) <= 1

@app.route("/admin/users/<int:user_id>/delete", methods=["POST"])
@admin_required
def admin_delete_user(user_id: int):
    s = db()
    try:
        me_id = session.get("user_id")
        user = s.query(User).filter_by(id=user_id).first()
        if not user:
            flash("User tidak ditemukan.", "error")
            return redirect(request.referrer or url_for("admin_users"))
        if user.id == me_id:
            flash("Tidak bisa menghapus akun yang sedang login.", "error")
            return redirect(request.referrer or url_for("admin_users"))
        if user.is_admin and _is_last_admin(s):
            flash("Tidak bisa menghapus admin terakhir.", "error")
            return redirect(request.referrer or url_for("admin_users"))
        s.query(ChatHistory).filter(ChatHistory.user_id == user.id).delete(synchronize_session=False)
        s.delete(user); s.commit()
        flash(f"User #{user_id} beserta seluruh riwayatnya telah dihapus.", "success")
    except Exception as e:
        s.rollback(); log.exception(f"[ADMIN] delete user error: {e}")
        flash("Gagal menghapus user.", "error")
    finally:
        s.close()
    return redirect(request.referrer or url_for("admin_users"))

@app.route("/admin/users/<int:user_id>/history/clear", methods=["POST"])
@admin_required
def admin_clear_user_history(user_id: int):
    s = db()
    try:
        exists = s.query(User.id).filter_by(id=user_id).first()
        if not exists:
            flash("User tidak ditemukan.", "error")
            return redirect(request.referrer or url_for("admin_history"))
        deleted = s.query(ChatHistory).filter(ChatHistory.user_id == user_id).delete(synchronize_session=False)
        s.commit()
        flash(f"Riwayat chat user #{user_id} dihapus ({deleted} baris).", "success")
    except Exception as e:
        s.rollback(); log.exception(f"[ADMIN] clear history error: {e}")
        flash("Gagal menghapus riwayat.", "error")
    finally:
        s.close()
    return redirect(request.referrer or url_for("admin_history"))

@app.route("/admin/history/<int:chat_id>/delete", methods=["POST"])
@admin_required
def admin_delete_chat(chat_id: int):
    s = db()
    try:
        row = s.query(ChatHistory).filter_by(id=chat_id).first()
        if not row:
            flash("Baris riwayat tidak ditemukan.", "error")
            return redirect(request.referrer or url_for("admin_history"))
        s.delete(row); s.commit()
        flash(f"Riwayat chat #{chat_id} dihapus.", "success")
    except Exception as e:
        s.rollback(); log.exception(f"[ADMIN] delete chat error: {e}")
        flash("Gagal menghapus riwayat.", "error")
    finally:
        s.close()
    return redirect(request.referrer or url_for("admin_history"))

# ========= ENTRY =========
if __name__ == "__main__":
    port = int(os.environ.get("PORT", 7860))
    app.run(host="0.0.0.0", port=port, debug=False)