src/conversation.py

"""
PriceOye AI — Conversation Manager
====================================
Handles multi-turn conversation with persistent session memory.
User preferences update dynamically — no restart needed.

Language: Professional Roman Urdu throughout.
"""

import re
from dataclasses import dataclass, field
from typing import Optional
from src.scoring_engine import UserPreferences, recommend, find_closest_alternative, get_priority_reason, get_category_scores, get_sub_scores
from src.phone_database import build_database

PHONE_DB = build_database()
IPHONE_MIN_PRICE = 280000


# ─────────────────────────────────────────────
#  SESSION MEMORY
# ─────────────────────────────────────────────

@dataclass
class SessionMemory:
    """
    Cross-turn memory — survives budget/priority changes.
    Allows: "always prefer Samsung", "avoid Huawei", etc.
    """
    brand_preference: Optional[str] = None
    brand_avoid: list[str] = field(default_factory=list)
    previous_recommendations: list[str] = field(default_factory=list)  # phone IDs
    user_name: Optional[str] = None
    notes: list[str] = field(default_factory=list)


# ─────────────────────────────────────────────
#  CONVERSATION STATE
# ─────────────────────────────────────────────

@dataclass
class ConversationState:
    prefs: UserPreferences = field(default_factory=UserPreferences)
    memory: SessionMemory = field(default_factory=SessionMemory)
    step: str = "greet"           # greet | collecting | result
    awaiting_new_budget: bool = False
    last_result_count: int = 1


# ─────────────────────────────────────────────
#  NLP EXTRACTION
# ─────────────────────────────────────────────

NON_PHONE_PATTERNS = [
    r'\bweather\b|\bcricket\b|\bnews\b|\bpolitics\b|\brecipe\b|\bfootball\b|\bfilm\b|\bsong\b|\bmusic\b',
    r'\bwhat is\b|\bwho is\b|\bhow to\b|\bexplain\b|\btell me about\b|\bhistory of\b',
    r'\blaptop\b|\bcomputer\b|\btablet\b|\bipad\b|\bsmartwatch\b|\bheadphone\b|\bspeaker\b',
    r'\bjoke\b|\bfunny\b|\bstory\b|\bpoem\b|\bessay\b|\btranslate\b',
]

PHONE_SIGNAL = r'phone|mobile|camera|battery|gaming|budget|samsung|iphone|android|recommend|suggest|buy|khareedna|lena|chahiye'

BRANDS = ["Samsung", "Apple", "OnePlus", "Xiaomi", "Realme", "Huawei", "ASUS",
          "ROG", "Nothing", "Tecno", "Infinix", "Oppo", "Vivo", "Nokia", "Redmi"]


def is_non_phone_query(text: str) -> bool:
    if re.search(PHONE_SIGNAL, text, re.IGNORECASE):
        return False
    return any(re.search(p, text, re.IGNORECASE) for p in NON_PHONE_PATTERNS)


def extract_preferences(text: str, current: UserPreferences) -> UserPreferences:
    """
    Parse user text and return UPDATED preferences.
    Only overwrites fields explicitly mentioned — preserves others.
    """
    t = text.lower()
    prefs = UserPreferences(
        budget=current.budget,
        os_preference=current.os_preference,
        priority=current.priority,
        brand_preference=current.brand_preference,
        brand_avoid=current.brand_avoid.copy(),
        session_memory=current.session_memory.copy(),
    )

    # ── BUDGET ──
    lakh_m = re.search(r'([\d.]+)\s*lakh', t)
    k_m = re.search(r'(\d+(?:\.\d+)?)\s*k\b', t)
    num_m = re.search(r'\b(\d[\d,]{3,})\b', t)

    if lakh_m:
        prefs.budget = int(float(lakh_m.group(1)) * 100000)
    elif k_m:
        prefs.budget = int(float(k_m.group(1)) * 1000)
    elif num_m:
        n = int(num_m.group(1).replace(',', ''))
        if 10000 <= n <= 1000000:
            prefs.budget = n

    # Quick-reply budget labels
    qr_budgets = {
        '30k se kam': 31999, 'under 30k': 31999,
        '50k se kam': 49999, 'under 50k': 49999,
        '50k': 99999,        '1 lakh': 99999,
        '1 – 2 lakh': 199999,'2 lakh': 199999,
        '2 – 3 lakh': 299999,'3 lakh': 299999,
        '3 lakh se zyada': 500000,
    }
    for label, budget in qr_budgets.items():
        if label in t:
            prefs.budget = budget
            break

    # ── OS ──
    if re.search(r'\biphone\b|\bios\b|\bapple\b', t):
        prefs.os_preference = 'ios'
    elif re.search(r'\bandroid\b|samsung|xiaomi|oneplus|realme|nothing|tecno|huawei|rog|asus|infinix|redmi|oppo|vivo', t):
        prefs.os_preference = 'android'
    elif re.search(r'koi bhi|chalega|any|either|no preference', t):
        prefs.os_preference = 'any'

    # ── PRIORITY ──
    if re.search(r'gaming|game|pubg|cod|bgmi|fps|esport', t):
        prefs.priority = 'gaming'
    elif re.search(r'\bcamera\b|photo|selfie|vlog|photography|pic', t):
        prefs.priority = 'photography'
    elif re.search(r'battery|long.?last|endurance', t):
        prefs.priority = 'battery'
    elif re.search(r'\bvalue\b|sasta|cheap|afford|economical|money|paisa', t):
        prefs.priority = 'value'
    elif re.search(r'business|work|professional|office|email', t):
        prefs.priority = 'business'
    elif re.search(r'balanced|everyday|general|normal|all.?round|overall', t):
        prefs.priority = 'balanced'
    elif re.search(r'fast charg|charg.*fast', t):
        prefs.priority = 'battery'

    # ── BRAND PREFERENCE ──
    for brand in BRANDS:
        if re.search(rf'always.*{brand.lower()}|prefer.*{brand.lower()}|{brand.lower()}.*prefer', t):
            prefs.brand_preference = brand
        if re.search(rf'avoid.*{brand.lower()}|not.*{brand.lower()}|{brand.lower()}.*nahi', t):
            if brand not in prefs.brand_avoid:
                prefs.brand_avoid.append(brand)

    return prefs


def extract_count(text: str) -> Optional[int]:
    t = text.lower()
    m = re.search(r'(\d+)\s*(phone|option|recomm)', t)
    if m:
        n = int(m.group(1))
        if 2 <= n <= 5:
            return n
    if re.search(r'\bmore\b|another|compar|vs\b|versus|alternative|dikhayein', t):
        return 3
    return None


# ─────────────────────────────────────────────
#  RESPONSE FORMATTERS
# ─────────────────────────────────────────────

def format_budget(n: int) -> str:
    if n >= 100000:
        return f"{n/100000:.1f} lakh"
    return f"{n//1000}k"


def format_phone_summary(phone, final_score: float, priority: str) -> dict:
    """Returns structured data for frontend rendering."""
    cats = get_category_scores(phone)
    priority_cat_map = {
        'photography': 'camera', 'gaming': 'performance',
        'battery': 'battery', 'value': 'camera',
        'business': 'software', 'balanced': 'camera', 'ios': 'camera',
    }
    deep_cat = priority_cat_map.get(priority, 'camera')

    return {
        "name": phone.name,
        "brand": phone.brand,
        "price_label": phone.price_label,
        "emoji": phone.emoji,
        "ai_score": round(final_score, 1),
        "priceoye_url": phone.priceoye_url,
        "whatmobile_url": phone.whatmobile_url,
        "highlights": phone.highlights,
        "category_scores": {k: round(v, 1) for k, v in cats.items()},
        "deep_dive_category": deep_cat,
        "deep_dive_scores": get_sub_scores(phone, deep_cat),
        "priority_reason": get_priority_reason(phone, priority),
    }


# ─────────────────────────────────────────────
#  MAIN CONVERSATION HANDLER
# ─────────────────────────────────────────────

def handle_message(user_text: str, state: ConversationState) -> dict:
    """
    Process one user message. Returns a response dict:
    {
        "text": str,                    # bot message text
        "quick_replies": list[str],     # button labels
        "phones": list[dict] | None,    # phone card data if recommendation
        "state": ConversationState,     # updated state
    }
    """
    t = user_text.lower().strip()

    # ── RESET ──
    if re.search(r'\bnew search\b|\brestart\b|\bnaya search\b|\breset\b', t):
        new_state = ConversationState(memory=state.memory)  # preserve session memory
        return _respond(
            "Theek hai, naya search shuru karte hain.<br>"
            "Budget, OS preference aur use case batayein.",
            ["Camera phone 1 lakh mein", "Gaming phone 2 lakh mein",
             "iPhone 3 lakh mein", "Budget phone 30k mein"],
            state=new_state
        )

    # ── NON-PHONE GUARD ──
    if is_non_phone_query(user_text):
        return _respond(
            "Main sirf mobile phone recommendations ke liye design kiya gaya hoon.<br><br>"
            "Apna <b>budget</b>, <b>OS preference</b> aur <b>main use case</b> batayein — "
            "main aap ke liye Pakistan mein best available phone select karunga.",
            ["50k se kam mein phone dikhayein", "Best camera phone 1 lakh mein",
             "Gaming phone 2 lakh mein"],
            state=state
        )

    # ── AWAITING NEW BUDGET ──
    if state.awaiting_new_budget:
        state.prefs = extract_preferences(user_text, state.prefs)
        state.awaiting_new_budget = False
        if not state.prefs.budget:
            return _respond(
                "Meherbani karke valid budget enter karein. "
                "Jaise: <b>1.5 lakh</b>, <b>80k</b>, ya <b>200000</b>.",
                state=state
            )
        state.step = 'collecting'
        return _advance(state)

    # ── UPDATE PREFS FROM TEXT ──
    state.prefs = extract_preferences(user_text, state.prefs)

    # ── RESULT FOLLOWUP ──
    if state.step == 'result':
        return _handle_result_followup(t, state)

    # ── ADVANCE ──
    return _advance(state)


def _advance(state: ConversationState) -> dict:
    """Check what's missing and ask, or show result."""
    p = state.prefs

    # iOS + budget too low → guide user
    if p.os_preference == 'ios' and p.budget and p.budget < IPHONE_MIN_PRICE:
        bl = format_budget(p.budget)
        state.prefs.os_preference = None
        return _respond(
            f"Pakistan mein sabse sasti iPhone abhi <b>PKR 2,80,000</b> (iPhone 15) se shuru hoti hai.<br><br>"
            f"Aap ka budget <b>PKR {bl}</b> kisi bhi iPhone ke liye kaafi nahi.<br><br>"
            "Budget barhayen ya Android try karein? Is budget mein kaafi acha Android cameras available hain.",
            ["Budget Barhana Hai", "Android Dikhayein", "Naya Search"],
            state=state
        )

    # All 3 collected → recommend
    if p.budget and p.os_preference is not None and p.priority:
        state.step = 'result'
        return _show_result(state, count=1)

    # Ask what's missing
    if not p.budget:
        return _ask_budget(state)
    if p.os_preference is None:
        return _ask_os(state)
    if not p.priority:
        return _ask_priority(state)

    return _show_result(state, count=1)


def _show_result(state: ConversationState, count: int = 1) -> dict:
    p = state.prefs
    results = recommend(p, PHONE_DB, count=count)

    if not results:
        # Diagnose
        if p.os_preference == 'ios' and p.budget and p.budget < IPHONE_MIN_PRICE:
            msg = (
                f"<b>PKR {format_budget(p.budget)}</b> mein koi iPhone available nahi.<br>"
                "iPhone 15 ka minimum price <b>PKR 2,84,999</b> hai.<br><br>"
                "Budget barhayen ya Android select karein."
            )
        else:
            msg = (
                f"<b>PKR {format_budget(p.budget)}</b> mein aap ki criteria ke mutabiq "
                "koi phone nahi mila.<br>Budget thoda barhayein ya preferences adjust karein."
            )
        return _respond(
            msg,
            ["Budget Barhana Hai", "Preferences Change Karein", "Naya Search"],
            state=state
        )

    bl = format_budget(p.budget)
    priority_label = (p.priority or 'balanced').title()

    if count == 1:
        phone, score = results[0]
        state.last_result_count = 1
        state.memory.previous_recommendations.append(phone.id)
        phone_data = [format_phone_summary(phone, score, p.priority or 'balanced')]

        text = (
            f"Aap ke liye main ne yeh best phone select kiya hai:<br>"
            f"<small>Budget: PKR {bl} &nbsp;·&nbsp; Priority: {priority_label} "
            f"&nbsp;·&nbsp; AI Score: {score:.1f}/10</small>"
        )
        followup = (
            f"<b>Yeh phone kyun best hai?</b><br>"
            f"• {get_priority_reason(phone, p.priority or 'balanced')}<br>"
            f"• Aap ke budget PKR {bl} ke andar hai<br>"
            f"• AI Score: <b>{score:.1f}/10</b><br><br>"
            "Aur options dekhna chahenge ya alternatives compare karna hai?"
        )
        return {
            "text": text,
            "followup": followup,
            "quick_replies": ["3 Options Dikhayein", "Top 2 Compare Karein", "Naya Search"],
            "phones": phone_data,
            "state": state,
        }
    else:
        medals = ["🥇 Behtar in Sab Mein", "🥈 Doosra Best", "🥉 Aur Ek Option", "4️⃣ Yeh Bhi Dekh Lein"]
        phones_data = []
        for i, (phone, score) in enumerate(results):
            d = format_phone_summary(phone, score, p.priority or 'balanced')
            d['medal'] = medals[i] if i < len(medals) else ""
            phones_data.append(d)
            state.memory.previous_recommendations.append(phone.id)

        state.last_result_count = len(results)
        return {
            "text": f"Aap ki requirements ke mutabiq AI score se ranked top <b>{len(results)} phones</b> yeh hain:",
            "followup": "Kisi bhi phone ke baare mein aur detail chahiye? Ya naya search karna hai?",
            "quick_replies": ["Naya Search"],
            "phones": phones_data,
            "state": state,
        }


def _handle_result_followup(t: str, state: ConversationState) -> dict:
    if re.search(r'budget barhana|increase.*budget|barhao|naya budget', t):
        state.awaiting_new_budget = True
        state.prefs.budget = None
        return _respond(
            "Naya budget batayein. Jaise: <b>2 lakh</b>, <b>150k</b>, ya <b>300000</b>.",
            state=state
        )
    if re.search(r'android|dikhayein.*android|switch.*android', t):
        state.prefs.os_preference = 'android'
        state.step = 'result'
        return _show_result(state, count=1)
    if re.search(r'preferences.*change|change.*prefer|priority.*change', t):
        state.prefs.priority = None
        return _ask_priority(state)
    if re.search(r'3.*option|compare|top.*2|2.*option|vs\b|versus|alternative|dikhayein', t):
        count = 2 if re.search(r'2.*option|top.*2|compare.*2', t) else 3
        return _show_result(state, count=count)
    if re.search(r'naya search|restart|reset', t):
        new_state = ConversationState(memory=state.memory)
        return _respond(
            "Theek hai, naya search shuru karte hain. Budget, OS aur use case batayein.",
            ["Camera phone 1 lakh mein", "Gaming phone 2 lakh mein",
             "iPhone 3 lakh mein", "Budget phone 30k mein"],
            state=new_state
        )
    return _respond(
        "Main aap ki aur kya madad kar sakta hoon?",
        ["3 Options Dikhayein", "Budget Barhana Hai", "Naya Search"],
        state=state
    )


def _ask_budget(state: ConversationState) -> dict:
    return _respond(
        "Aap ka mobile ka <b>budget</b> kya hai?<br>"
        "<small>Jaise likh sakte hain: <i>50k</i>, <i>1.5 lakh</i>, ya <i>200000</i></small>",
        ["30k se Kam", "50k se Kam", "50k – 1 Lakh",
         "1 – 2 Lakh", "2 – 3 Lakh", "3 Lakh se Zyada"],
        state=state
    )


def _ask_os(state: ConversationState) -> dict:
    bl = format_budget(state.prefs.budget)
    return _respond(
        f"Budget confirm ho gaya: <b>PKR {bl}</b> ✅<br><br>"
        "Aap <b>iPhone (iOS)</b> prefer karte hain ya <b>Android</b>?",
        ["iPhone (iOS)", "Android", "Koi Bhi Chalega"],
        state=state
    )


def _ask_priority(state: ConversationState) -> dict:
    p = state.prefs
    bl = format_budget(p.budget)
    os_label = "iPhone" if p.os_preference == 'ios' else "Android" if p.os_preference == 'android' else "Any OS"
    return _respond(
        f"Budget <b>PKR {bl}</b> ✅ &nbsp;·&nbsp; <b>{os_label}</b> ✅<br><br>"
        "Is phone mein aap ko sabse zyada kya chahiye?",
        ["Camera aur Photography", "Gaming Performance", "Battery Life",
         "Value for Money", "Balanced All-Round", "Business aur Productivity"],
        state=state
    )


def _respond(text: str, quick_replies: list = None, phones=None, state: ConversationState = None) -> dict:
    return {
        "text": text,
        "quick_replies": quick_replies or [],
        "phones": phones,
        "state": state,
    }


# ─────────────────────────────────────────────
#  GREETING
# ─────────────────────────────────────────────

def get_greeting() -> dict:
    return {
        "text": (
            "<b>PriceOye AI Phone Advisor mein khush aamdeed!</b> 📱<br><br>"
            "Main aap ki madad karunga Pakistan mein aap ke budget aur requirements "
            "ke mutabiq best mobile phone dhundhne mein.<br><br>"
            "Data sources: <b>WhatMobile.com.pk</b> aur <b>PriceOye.pk</b> se verified.<br><br>"
            "Seedha bhi bata sakte hain, jaise:<br>"
            "<i>\"2 lakh mein best camera Android chahiye\"</i><br><br>"
            "Ya main aap se step-by-step poochunga."
        ),
        "quick_replies": [
            "Camera phone 1 lakh mein",
            "Gaming phone 2 lakh mein",
            "iPhone 3 lakh mein",
            "Budget phone 30k mein",
        ],
        "phones": None,
        "state": ConversationState(),
    }