knowledge/message_understanding.py

from typing import Optional

from services.intent_classifier_client import classify_message_with_model


def normalize_text(text: str) -> str:
    return (text or "").strip().lower()


def contains_any(text: str, keywords: list) -> bool:
    return any(k in text for k in keywords)


def is_yes(text: str) -> bool:
    t = normalize_text(text)
    return t in [
        "نعم", "اه", "أه", "ايوه", "أيوه", "yes", "y",
        "درست", "اه درست", "أيوه درست"
    ]


def is_no(text: str) -> bool:
    t = normalize_text(text)
    return t in [
        "لا", "لأ", "لاا", "no", "n",
        "مدرستش", "ما درستش", "لا مدرستش"
    ]


def is_new_student(text: str) -> bool:
    t = normalize_text(text)
    return contains_any(t, [
        "طالب جديد", "جديد", "عميل جديد", "اول مرة", "أول مرة",
        "لسه جديد", "مشترك جديد"
    ])


def is_current_student(text: str) -> bool:
    t = normalize_text(text)
    return contains_any(t, [
        "طالب حالي", "حالي", "عميل حالي", "مشترك", "مشترك حالي",
        "أنا طالب", "انا طالب عندكم", "انا مشترك"
    ])


def is_adults(text: str) -> bool:
    t = normalize_text(text)
    return contains_any(t, [
        "كبار", "adult", "adults", "الكبار", "كورسات الكبار"
    ])


def is_children(text: str) -> bool:
    t = normalize_text(text)
    return contains_any(t, [
        "اطفال", "أطفال", "طفل", "children", "kids",
        "كورسات الأطفال", "كورسات الاطفال"
    ])


def is_support_request(text: str) -> bool:
    t = normalize_text(text)
    return contains_any(t, [
        "استفسار", "سؤال", "عندي سؤال", "مشكلة", "مش فاهم",
        "عايز اسأل", "عايزة اسأل", "محتاج مساعدة", "محتاجه مساعدة",
        "support", "خدمة العملاء"
    ])


def is_next_level_booking(text: str) -> bool:
    t = normalize_text(text)
    return contains_any(t, [
        "حجز", "احجز", "المستوى التالي", "مستوى تالي",
        "next level", "احجز المستوى", "حجز مستوى"
    ])


def is_complaint(text: str) -> bool:
    t = normalize_text(text)
    return contains_any(t, [
        "شكوى", "اشتكي", "اشتك", "مشكلة كبيرة", "complaint"
    ])


def wants_direct_support(text: str) -> bool:
    t = normalize_text(text)
    return contains_any(t, [
        "تواصل", "اكلم", "عايز حد يكلمني", "عايزة حد يكلمني",
        "عايز اكلم خدمة العملاء", "عايزة اكلم خدمة العملاء"
    ])


def wants_start(text: str) -> bool:
    t = normalize_text(text)
    return contains_any(t, [
        "ابدأ", "ابدا", "مساعدة", "مساعده", "start", "menu", "القائمة"
    ])


def wants_restart(text: str) -> bool:
    t = normalize_text(text)
    return contains_any(t, [
        "من جديد", "ابدأ من جديد", "restart", "مينيو", "القائمة", "ابدأ"
    ])


def wants_new_topic(text: str) -> bool:
    t = normalize_text(text)
    return contains_any(t, [
        "عايز اسال عن حاجة تانية",
        "عايزة اسال عن حاجة تانية",
        "استفسار جديد",
        "موضوع تاني",
        "حاجة تانية"
    ])


def wants_courses_info(text: str) -> bool:
    t = normalize_text(text)
    return contains_any(t, [
        "كورسات",
        "الكورسات",
        "ايه الكورسات",
        "ما هي الكورسات",
        "الأنواع",
        "الانواع",
        "عايز اعرف الكورسات",
        "عايزة اعرف الكورسات",
        "ايه الكورسات المتاحة",
        "الكورسات المتاحة"
    ])


def asks_about_prior_study_case(text: str) -> bool:
    t = normalize_text(text)
    return contains_any(t, [
        "لو كنت درست",
        "لو كنت دارس",
        "لو درست قبل كده",
        "طب لو درست",
        "ولو درست",
        "اذا كنت درست",
        "إذا كنت درست",
        "اختبار تحديد مستوى",
        "تحديد مستوى"
    ])


def asks_about_beginner_case(text: str) -> bool:
    t = normalize_text(text)
    return contains_any(t, [
        "لو مكنتش درست",
        "لو ما درستش",
        "لو مدرستش",
        "لو لسه جديد",
        "لو مبتدئ",
        "لو بادئ",
        "لو اول مرة",
        "لو أول مرة"
    ])


def detect_level(text: str) -> Optional[str]:
    t = normalize_text(text)

    if contains_any(t, ["1a", "a1", "a1.1", "1 a"]):
        return "1A"

    if contains_any(t, ["2a", "a2", "a1.2", "2 a"]):
        return "2A"

    if contains_any(t, ["1b", "b1", "b1.1", "1 b"]):
        return "1B"

    if contains_any(t, ["1c", "2b", "b2", "1c2/b", "1 c", "2 b"]):
        return "1C2/B"

    return None


def detect_payment_method(text: str) -> Optional[str]:
    t = normalize_text(text)

    if contains_any(t, ["فرع", "فروع", "كاش", "cash"]):
        return "branch_or_cash"

    if contains_any(t, ["تحويل", "بنكي", "bank", "transfer"]):
        return "bank_transfer"

    if contains_any(t, ["فودافون", "vodafone", "vodafone cash"]):
        return "vodafone_cash"

    if contains_any(t, ["فيزا", "visa", "ماستر", "master", "credit card", "card"]):
        return "card"

    if contains_any(t, ["تقسيط", "value", "فاليو"]):
        return "installments"

    return None


def _make_result(kind: str, value: Optional[str], confidence: float, entities: Optional[dict] = None, source: str = "rules", raw_model_output: Optional[str] = None):
    result = {
        "kind": kind,
        "value": value,
        "confidence": confidence,
        "entities": entities or {},
        "source": source,
    }
    if raw_model_output is not None:
        result["raw_model_output"] = raw_model_output
    return result


def _map_model_intent_to_result(state: str, text: str, model_intent: str, raw_output: str = ""):
    # ===== Topic switch labels =====
    if model_intent == "restart":
        return _make_result("topic_switch", "restart", 0.90, {}, "model", raw_output)

    if model_intent == "new_topic":
        return _make_result("topic_switch", "new_topic", 0.88, {}, "model", raw_output)

    if model_intent == "complaint":
        return _make_result("topic_switch", "complaint", 0.92, {}, "model", raw_output)

    if model_intent == "direct_support":
        return _make_result("topic_switch", "direct_support", 0.90, {}, "model", raw_output)

    if model_intent == "courses_info":
        return _make_result("topic_switch", "courses_info", 0.88, {}, "model", raw_output)

    if model_intent == "children_courses":
        return _make_result(
            "topic_switch",
            "children_courses",
            0.88,
            {"audience": "children"},
            "model",
            raw_output
        )

    if model_intent == "adults_courses":
        return _make_result(
            "topic_switch",
            "adults_courses",
            0.88,
            {"audience": "adults"},
            "model",
            raw_output
        )

    if model_intent == "new_student":
        target_kind = "direct_answer" if state == "WAITING_USER_TYPE" else "topic_switch"
        return _make_result(
            target_kind,
            "new_student",
            0.90,
            {"customer_type": "new"},
            "model",
            raw_output
        )

    if model_intent == "current_student":
        target_kind = "direct_answer" if state == "WAITING_USER_TYPE" else "topic_switch"
        return _make_result(
            target_kind,
            "current_student",
            0.90,
            {"customer_type": "current"},
            "model",
            raw_output
        )

    # ===== Direct answers =====
    if model_intent == "adults":
        return _make_result("direct_answer", "adults", 0.93, {"audience": "adults"}, "model", raw_output)

    if model_intent == "children":
        return _make_result("direct_answer", "children", 0.93, {"audience": "children"}, "model", raw_output)

    if model_intent == "prior_study_yes":
        return _make_result("direct_answer", "prior_study_yes", 0.94, {"prior_study": True}, "model", raw_output)

    if model_intent == "prior_study_no":
        return _make_result("direct_answer", "prior_study_no", 0.94, {"prior_study": False}, "model", raw_output)

    if model_intent == "confirm_schedule_reviewed":
        return _make_result("direct_answer", "confirm_schedule_reviewed", 0.90, {}, "model", raw_output)

    if model_intent == "proceed_booking":
        return _make_result("direct_answer", "proceed_booking", 0.90, {}, "model", raw_output)

    if model_intent == "confirm_pdf_reviewed":
        return _make_result("direct_answer", "confirm_pdf_reviewed", 0.90, {}, "model", raw_output)

    if model_intent == "confirm_placement_test_reviewed":
        return _make_result("direct_answer", "confirm_placement_test_reviewed", 0.90, {}, "model", raw_output)

    if model_intent == "current_student_support":
        return _make_result("direct_answer", "current_student_support", 0.90, {}, "model", raw_output)

    if model_intent == "current_student_next_level":
        return _make_result("direct_answer", "current_student_next_level", 0.90, {}, "model", raw_output)

    if model_intent == "support_question_text":
        return _make_result(
            "direct_answer",
            "support_question_text",
            0.85,
            {"support_question": text},
            "model",
            raw_output
        )

    if model_intent == "level_selected":
        level = detect_level(text)
        if level:
            return _make_result(
                "direct_answer",
                "level_selected",
                0.92,
                {"selected_level": level},
                "model",
                raw_output
            )

    if model_intent == "payment_method_selected":
        payment_method = detect_payment_method(text)
        if payment_method:
            return _make_result(
                "direct_answer",
                "payment_method_selected",
                0.92,
                {"payment_method": payment_method},
                "model",
                raw_output
            )

    if model_intent == "complaint_form_submitted":
        return _make_result("direct_answer", "complaint_form_submitted", 0.90, {}, "model", raw_output)

    if model_intent == "thanks":
        return _make_result("direct_answer", "thanks", 0.95, {}, "model", raw_output)

    # ===== State switches =====
    if model_intent == "switch_to_prior_study_true":
        return _make_result(
            "state_switch",
            "switch_to_prior_study_true",
            0.90,
            {"prior_study": True},
            "model",
            raw_output
        )

    if model_intent == "switch_to_prior_study_false":
        return _make_result(
            "state_switch",
            "switch_to_prior_study_false",
            0.90,
            {"prior_study": False},
            "model",
            raw_output
        )

    if model_intent == "support_needed":
        return _make_result("state_switch", "support_needed", 0.86, {}, "model", raw_output)

    return None


def _fallback_rule_based_classification(state: str, text: str, flow_data: dict | None = None):
    """
    ده اللوجيك القديم كما هو تقريبًا، عشان ما نكسرش أي حاجة.
    """
    flow_data = flow_data or {}
    t = normalize_text(text)

    # ===== Global topic switches =====
    if wants_restart(t):
        return _make_result("topic_switch", "restart", 0.99, {})

    if wants_new_topic(t):
        return _make_result("topic_switch", "new_topic", 0.95, {})

    if is_complaint(t):
        return _make_result("topic_switch", "complaint", 0.98, {})

    if wants_direct_support(t):
        return _make_result("topic_switch", "direct_support", 0.95, {})

    if wants_courses_info(t):
        return _make_result("topic_switch", "courses_info", 0.90, {})

    if is_children(t):
        return _make_result("topic_switch", "children_courses", 0.88, {"audience": "children"})

    if is_adults(t):
        return _make_result("topic_switch", "adults_courses", 0.88, {"audience": "adults"})

    if is_new_student(t):
        return _make_result("topic_switch", "new_student", 0.90, {"customer_type": "new"})

    if is_current_student(t):
        return _make_result("topic_switch", "current_student", 0.90, {"customer_type": "current"})

    # ===== State-specific understanding =====
    if state == "WAITING_USER_TYPE":
        if is_new_student(t):
            return _make_result("direct_answer", "new_student", 0.95, {"customer_type": "new"})
        if is_current_student(t):
            return _make_result("direct_answer", "current_student", 0.95, {"customer_type": "current"})

    if state == "WAITING_AUDIENCE":
        if is_adults(t):
            return _make_result("direct_answer", "adults", 0.95, {"audience": "adults"})
        if is_children(t):
            return _make_result("direct_answer", "children", 0.95, {"audience": "children"})

    if state == "WAITING_PRIOR_STUDY":
        if is_yes(t):
            return _make_result("direct_answer", "prior_study_yes", 0.96, {"prior_study": True})
        if is_no(t):
            return _make_result("direct_answer", "prior_study_no", 0.96, {"prior_study": False})

    if state in [
        "WAITING_BEGINNER_SCHEDULE_CHOICE",
        "WAITING_PDF_102_CONFIRMATION",
        "WAITING_PLACEMENT_TEST_CONFIRMATION",
    ]:
        if asks_about_prior_study_case(t):
            return _make_result("state_switch", "switch_to_prior_study_true", 0.92, {"prior_study": True})

        if asks_about_beginner_case(t):
            return _make_result("state_switch", "switch_to_prior_study_false", 0.92, {"prior_study": False})

    if state == "WAITING_BEGINNER_SCHEDULE_CHOICE":
        if contains_any(t, ["تم", "اخترت", "اختارت", "جاهز", "جاهزة"]):
            return _make_result("direct_answer", "confirm_schedule_reviewed", 0.92, {})

        if contains_any(t, ["عايز احجز", "عايزة احجز", "احجز", "حجز", "اشترك", "اشتراك"]):
            return _make_result("direct_answer", "proceed_booking", 0.90, {})

        if is_support_request(t):
            return _make_result("state_switch", "support_needed", 0.88, {})

    if state == "WAITING_PDF_102_CONFIRMATION":
        if contains_any(t, ["تم", "خلصت", "قريت", "اطلعت", "جاهز", "جاهزة"]):
            return _make_result("direct_answer", "confirm_pdf_reviewed", 0.92, {})

        if is_support_request(t):
            return _make_result("state_switch", "support_needed", 0.88, {})

    if state == "WAITING_PLACEMENT_TEST_CONFIRMATION":
        if contains_any(t, ["تم", "اخترت", "اختارت", "جاهز", "جاهزة"]):
            return _make_result("direct_answer", "confirm_placement_test_reviewed", 0.92, {})

        if is_support_request(t):
            return _make_result("state_switch", "support_needed", 0.88, {})

    if state == "WAITING_CURRENT_STUDENT_ACTION":
        if is_support_request(t):
            return _make_result("direct_answer", "current_student_support", 0.92, {})

        if is_next_level_booking(t):
            return _make_result("direct_answer", "current_student_next_level", 0.92, {})

    if state == "WAITING_SUPPORT_QUESTION":
        if t:
            return _make_result(
                "direct_answer",
                "support_question_text",
                0.85,
                {"support_question": text}
            )

    if state == "WAITING_LEVEL_SELECTION":
        level = detect_level(t)
        if level:
            return _make_result("direct_answer", "level_selected", 0.95, {"selected_level": level})

        if is_support_request(t) or contains_any(t, ["مش عارف", "مش متأكد", "مش متاكدة"]):
            return _make_result("state_switch", "support_needed", 0.85, {})

    if state == "WAITING_PAYMENT_METHOD":
        payment_method = detect_payment_method(t)
        if payment_method:
            return _make_result(
                "direct_answer",
                "payment_method_selected",
                0.95,
                {"payment_method": payment_method}
            )

        if is_support_request(t):
            return _make_result("state_switch", "support_needed", 0.85, {})

    if state == "WAITING_COMPLAINT_FORM":
        if contains_any(t, ["تم", "خلصت", "سجلت", "قدمت", "بعت"]):
            return _make_result("direct_answer", "complaint_form_submitted", 0.90, {})

    if state == "HANDOFF_DONE":
        if contains_any(t, ["شكرا", "متشكر", "تسلم", "ميرسي"]):
            return _make_result("direct_answer", "thanks", 0.95, {})

        if is_support_request(t):
            return _make_result("topic_switch", "direct_support", 0.90, {})

    return _make_result("unclear", None, 0.30, {})


def classify_message(state: str, text: str, flow_data: dict | None = None):
    """
    Returns structured classification:
    {
      "kind": "direct_answer" | "state_switch" | "topic_switch" | "unclear",
      "value": str | None,
      "confidence": float,
      "entities": dict,
      "source": "model" | "rules"
    }
    """
    flow_data = flow_data or {}

    # 1) Try model classifier first
    try:
        model_res = classify_message_with_model(
            user_message=text,
            state=state,
            flow_data=flow_data,
        )

        if model_res and model_res.get("intent"):
            mapped = _map_model_intent_to_result(
                state=state,
                text=text,
                model_intent=model_res["intent"],
                raw_output=model_res.get("raw_output", "")
            )
            if mapped:
                return mapped

    except Exception as e:
        print(f"[message_understanding] model classifier failed: {repr(e)}")

    # 2) Fallback to existing rule-based logic
    return _fallback_rule_based_classification(state, text, flow_data)