knowledge/classifier_prompt.py

from typing import Dict, List


GLOBAL_INTENTS = [
    "restart",
    "new_topic",
    "complaint",
    "direct_support",
    "courses_info",
    "children_courses",
    "adults_courses",
    "new_student",
    "current_student",
    "unclear",
]

STATE_ALLOWED_INTENTS: Dict[str, List[str]] = {
    "WAITING_MAIN_MENU": [
        "new_student",
        "current_student",
        "courses_info",
        "complaint",
        "direct_support",
    ],
    "WAITING_USER_TYPE": [
        "new_student",
        "current_student",
    ],
    "WAITING_AUDIENCE": [
        "adults",
        "children",
    ],
    "WAITING_PRIOR_STUDY": [
        "prior_study_yes",
        "prior_study_no",
    ],
    "WAITING_BEGINNER_SCHEDULE_CHOICE": [
        "confirm_schedule_reviewed",
        "proceed_booking",
        "switch_to_prior_study_true",
        "switch_to_prior_study_false",
        "support_needed",
    ],
    "WAITING_PDF_102_CONFIRMATION": [
        "confirm_pdf_reviewed",
        "switch_to_prior_study_true",
        "switch_to_prior_study_false",
        "support_needed",
    ],
    "WAITING_PLACEMENT_TEST_CONFIRMATION": [
        "confirm_placement_test_reviewed",
        "switch_to_prior_study_true",
        "switch_to_prior_study_false",
        "support_needed",
    ],
    "WAITING_CURRENT_STUDENT_ACTION": [
        "current_student_support",
        "current_student_next_level",
    ],
    "WAITING_SUPPORT_QUESTION": [
        "support_question_text",
    ],
    "WAITING_LEVEL_SELECTION": [
        "level_selected",
        "support_needed",
    ],
    "WAITING_PAYMENT_METHOD": [
        "payment_method_selected",
        "support_needed",
    ],
    "WAITING_COMPLAINT_FORM": [
        "complaint_form_submitted",
    ],
    "HANDOFF_DONE": [
        "thanks",
        "courses_info",
        "children_courses",
        "adults_courses",
        "new_student",
        "current_student",
        "direct_support",
        "complaint",
        "restart",
        "new_topic",
    ],
}

INTENT_DESCRIPTIONS: Dict[str, str] = {
    "restart": "The user wants to restart the conversation from the beginning.",
    "new_topic": "The user explicitly wants to ask about something else or start a new topic.",
    "complaint": "The user is making or asking to make a complaint.",
    "direct_support": "The user wants to talk to customer support or service directly.",
    "courses_info": "The user is asking generally about available courses.",
    "children_courses": "The user is asking about children courses.",
    "adults_courses": "The user is asking about adult courses.",
    "new_student": "The user indicates they are a new student.",
    "current_student": "The user indicates they are a current student.",
    "adults": "Direct answer: adults.",
    "children": "Direct answer: children.",
    "prior_study_yes": "Direct answer: user studied German before.",
    "prior_study_no": "Direct answer: user did not study German before.",
    "confirm_schedule_reviewed": "The user confirms they reviewed the beginner schedule.",
    "proceed_booking": "The user wants to proceed with booking.",
    "switch_to_prior_study_true": "The user changes to the path where they studied German before.",
    "switch_to_prior_study_false": "The user changes to the beginner path.",
    "support_needed": "The user needs help or wants support within the current topic.",
    "confirm_pdf_reviewed": "The user confirms they reviewed the PDF/details file.",
    "confirm_placement_test_reviewed": "The user confirms they reviewed placement test details.",
    "current_student_support": "Current student wants support or has a question.",
    "current_student_next_level": "Current student wants to book the next level.",
    "support_question_text": "The message itself is the support question text.",
    "level_selected": "The user selected a course level.",
    "payment_method_selected": "The user selected a payment method.",
    "complaint_form_submitted": "The user says they submitted the complaint form.",
    "thanks": "The user is thanking the bot.",
    "unclear": "The message is unclear and should not be confidently routed.",
}


def get_allowed_intents_for_state(state: str) -> List[str]:
    state_specific = STATE_ALLOWED_INTENTS.get(state, [])
    final = []
    for item in GLOBAL_INTENTS + state_specific:
        if item not in final:
            final.append(item)
    return final


def _summarize_flow_data(flow_data: dict) -> str:
    if not flow_data:
        return "No extra context."

    fields = []
    for key in [
        "customer_type",
        "audience",
        "prior_study",
        "selected_level",
        "payment_method",
        "gender",
    ]:
        if key in flow_data and flow_data[key] is not None:
            fields.append(f"{key}={flow_data[key]}")

    return ", ".join(fields) if fields else "No extra context."


def build_system_prompt(state: str, flow_data: dict, allowed_intents: List[str]) -> str:
    descriptions = []
    for intent in allowed_intents:
        desc = INTENT_DESCRIPTIONS.get(intent, "")
        descriptions.append(f"- {intent}: {desc}")

    description_block = "\n".join(descriptions)

    context_summary = _summarize_flow_data(flow_data)

    return f"""
You are a state-aware intent classifier for an Arabic WhatsApp bot.

Your task:
- Read the user's Arabic message.
- Understand the CURRENT conversation state.
- Choose exactly ONE intent label from the allowed list.
- Return ONLY the label.
- Do not explain.
- Do not add punctuation.
- Do not add extra words.

Current state:
{state}

Known context:
{context_summary}

Allowed intent labels:
{", ".join(allowed_intents)}

Intent descriptions:
{description_block}

Decision rules:
- If the message is a direct answer to the current question, choose the direct answer label.
- If the user changes path but stays in the same broad topic, choose the appropriate state-switch label.
- If the user changes to a new topic, choose the correct topic-switch label.
- If you are not confident, return: unclear

Return only one label from the allowed list.
""".strip()