GIA/core/events/shadow.py

from __future__ import annotations

from django.db.models import Count, Max, Q

from core.models import ConversationEvent, Person, User


def _kind_from_event_type(event_type: str) -> str:
    normalized = str(event_type or "").strip().lower()
    return {
        "message_created": "message_sent",
        "delivery_receipt": "message_delivered",
        "read_receipt": "message_read",
        "typing_started": "composing_started",
        "typing_stopped": "composing_stopped",
        "composing_abandoned": "composing_abandoned",
        "presence_available": "presence_available",
        "presence_unavailable": "presence_unavailable",
    }.get(normalized, normalized)


def get_shadow_behavioral_availability_stats(*, user: User) -> list[dict]:
    person_map = {
        str(row["id"]): str(row["name"] or "")
        for row in Person.objects.filter(user=user).values("id", "name")
    }
    rows = (
        ConversationEvent.objects.filter(
            user=user,
            session__identifier__person__isnull=False,
        )
        .values("session__identifier__person_id", "origin_transport")
        .annotate(
            total_events=Count("id"),
            presence_events=Count(
                "id",
                filter=Q(event_type__in=["presence_available", "presence_unavailable"]),
            ),
            read_events=Count("id", filter=Q(event_type="read_receipt")),
            typing_events=Count(
                "id",
                filter=Q(
                    event_type__in=["typing_started", "typing_stopped"]
                ),
            ),
            message_events=Count("id", filter=Q(event_type="message_created")),
            abandoned_events=Count("id", filter=Q(event_type="composing_abandoned")),
            last_event_ts=Max("ts"),
        )
        .order_by("-total_events", "session__identifier__person_id", "origin_transport")
    )
    output = []
    for row in rows:
        person_id = str(row.get("session__identifier__person_id") or "").strip()
        output.append(
            {
                "person_id": person_id,
                "person_name": person_map.get(person_id, person_id or "-"),
                "service": str(row.get("origin_transport") or "").strip().lower(),
                "total_events": int(row.get("total_events") or 0),
                "presence_events": int(row.get("presence_events") or 0),
                "read_events": int(row.get("read_events") or 0),
                "typing_events": int(row.get("typing_events") or 0),
                "message_events": int(row.get("message_events") or 0),
                "abandoned_events": int(row.get("abandoned_events") or 0),
                "last_event_ts": int(row.get("last_event_ts") or 0),
            }
        )
    return output


def get_shadow_behavioral_latest_states(
    *, user: User, person_ids: list[str], transport: str = ""
) -> list[dict]:
    queryset = ConversationEvent.objects.filter(
        user=user,
        session__identifier__person_id__in=[str(value) for value in person_ids],
        event_type__in=[
            "message_created",
            "delivery_receipt",
            "read_receipt",
            "typing_started",
            "typing_stopped",
            "composing_abandoned",
            "presence_available",
            "presence_unavailable",
        ],
    ).select_related("session__identifier")
    if transport:
        queryset = queryset.filter(origin_transport=str(transport).strip().lower())
    rows = []
    seen = set()
    for row in queryset.order_by(
        "session__identifier__person_id", "-ts", "-created_at"
    )[:500]:
        person_id = str(getattr(row.session.identifier, "person_id", "") or "").strip()
        if not person_id or person_id in seen:
            continue
        seen.add(person_id)
        rows.append(
            {
                "person_id": person_id,
                "transport": str(row.origin_transport or "").strip().lower(),
                "kind": _kind_from_event_type(row.event_type),
                "ts": int(row.ts or 0),
            }
        )
    return rows


def get_shadow_behavioral_events_for_range(
    *,
    user: User,
    person_id: str,
    start_ts: int,
    end_ts: int,
    transport: str = "",
) -> list[dict]:
    queryset = ConversationEvent.objects.filter(
        user=user,
        session__identifier__person_id=str(person_id or "").strip(),
        ts__gte=int(start_ts),
        ts__lte=int(end_ts),
        event_type__in=[
            "message_created",
            "delivery_receipt",
            "read_receipt",
            "typing_started",
            "typing_stopped",
            "composing_abandoned",
            "presence_available",
            "presence_unavailable",
        ],
    ).order_by("ts", "created_at")
    if transport:
        queryset = queryset.filter(origin_transport=str(transport).strip().lower())
    return [
        {
            "person_id": str(person_id or "").strip(),
            "session_id": str(row.session_id or ""),
            "transport": str(row.origin_transport or "").strip().lower(),
            "kind": _kind_from_event_type(row.event_type),
            "direction": str(row.direction or "").strip().lower(),
            "ts": int(row.ts or 0),
            "payload": dict(row.payload or {}),
        }
        for row in queryset[:1000]
    ]