feat(routines): add inventory-aware product selection rules
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1 changed files with 126 additions and 2 deletions
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@ -14,6 +14,7 @@ from innercontext.llm import call_gemini
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from innercontext.models import (
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GroomingSchedule,
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Product,
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ProductInventory,
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Routine,
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RoutineStep,
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SkinConditionSnapshot,
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@ -267,18 +268,53 @@ def _build_recent_history(session: Session) -> str:
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def _build_products_context(session: Session, time_filter: Optional[str] = None) -> str:
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stmt = select(Product).where(Product.is_tool == False) # noqa: E712
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products = session.exec(stmt).all()
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product_ids = [p.id for p in products]
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inventory_rows = (
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session.exec(
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select(ProductInventory).where(ProductInventory.product_id.in_(product_ids))
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).all()
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if product_ids
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else []
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)
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inv_by_product: dict[UUID, list[ProductInventory]] = {}
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for inv in inventory_rows:
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inv_by_product.setdefault(inv.product_id, []).append(inv)
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lines = ["DOSTĘPNE PRODUKTY:"]
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for p in products:
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if p.is_medication and not _is_minoxidil_product(p):
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continue
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if time_filter and _ev(p.recommended_time) not in (time_filter, "both"):
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continue
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p.inventory = inv_by_product.get(p.id, [])
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ctx = p.to_llm_context()
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entry = (
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f" - id={ctx['id']} name=\"{ctx['name']}\" brand=\"{ctx['brand']}\""
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f" category={ctx.get('category', '')} recommended_time={ctx.get('recommended_time', '')}"
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f" targets={ctx.get('targets', [])}"
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)
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active_inventory = [inv for inv in p.inventory if inv.finished_at is None]
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open_inventory = [inv for inv in active_inventory if inv.is_opened]
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sealed_inventory = [inv for inv in active_inventory if not inv.is_opened]
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entry += (
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" inventory_status={"
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f"active:{len(active_inventory)},opened:{len(open_inventory)},sealed:{len(sealed_inventory)}"
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"}"
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)
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if open_inventory:
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expiry_dates = sorted(
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inv.expiry_date.isoformat() for inv in open_inventory if inv.expiry_date
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)
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if expiry_dates:
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entry += f" nearest_open_expiry={expiry_dates[0]}"
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if p.pao_months is not None:
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pao_deadlines = sorted(
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(inv.opened_at + timedelta(days=30 * p.pao_months)).isoformat()
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for inv in open_inventory
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if inv.opened_at
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)
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if pao_deadlines:
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entry += f" nearest_open_pao_deadline={pao_deadlines[0]}"
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profile = ctx.get("product_effect_profile", {})
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if profile:
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notable = {k: v for k, v in profile.items() if v and v > 0}
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@ -296,6 +332,84 @@ def _build_products_context(session: Session, time_filter: Optional[str] = None)
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return "\n".join(lines) + "\n"
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def _build_inventory_context(
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session: Session, time_filter: Optional[str] = None
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) -> str:
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products = session.exec(
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select(Product).where(Product.is_tool == False)
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).all() # noqa: E712
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product_ids = [p.id for p in products]
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inventory_rows = (
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session.exec(
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select(ProductInventory).where(ProductInventory.product_id.in_(product_ids))
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).all()
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if product_ids
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else []
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)
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inv_by_product: dict[UUID, list[ProductInventory]] = {}
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for inv in inventory_rows:
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inv_by_product.setdefault(inv.product_id, []).append(inv)
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lines = ["KONTEKST INWENTARZA (PRIORYTET ZUŻYCIA):"]
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open_by_category: dict[str, list[str]] = {}
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has_any = False
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for p in products:
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if p.is_medication and not _is_minoxidil_product(p):
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continue
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if time_filter and _ev(p.recommended_time) not in (time_filter, "both"):
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continue
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active_inventory = [
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inv for inv in inv_by_product.get(p.id, []) if inv.finished_at is None
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]
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if not active_inventory:
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continue
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has_any = True
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open_inventory = [inv for inv in active_inventory if inv.is_opened]
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sealed_inventory = [inv for inv in active_inventory if not inv.is_opened]
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category = _ev(p.category)
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if open_inventory:
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open_by_category.setdefault(category, []).append(p.name)
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line = (
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f' - product_id={p.id} name="{p.name}" category={category}'
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f" active={len(active_inventory)} opened={len(open_inventory)} sealed={len(sealed_inventory)}"
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)
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expiry_dates = sorted(
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inv.expiry_date.isoformat() for inv in open_inventory if inv.expiry_date
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)
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if expiry_dates:
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line += f" nearest_open_expiry={expiry_dates[0]}"
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if p.pao_months is not None and open_inventory:
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pao_deadlines = sorted(
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(inv.opened_at + timedelta(days=30 * p.pao_months)).isoformat()
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for inv in open_inventory
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if inv.opened_at
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)
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if pao_deadlines:
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line += f" nearest_open_pao_deadline={pao_deadlines[0]}"
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if p.pao_months is not None:
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line += f" pao_months={p.pao_months}"
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lines.append(line)
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if not has_any:
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return "KONTEKST INWENTARZA (PRIORYTET ZUŻYCIA): brak aktywnych opakowań\n"
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duplicate_open_categories = {
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cat: names for cat, names in open_by_category.items() if len(names) > 1
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}
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if duplicate_open_categories:
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lines.append(" Otwarte równolegle podobne kategorie (ograniczaj rotację):")
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for cat, names in duplicate_open_categories.items():
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lines.append(f" - {cat}: {', '.join(sorted(set(names)))}")
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return "\n".join(lines) + "\n"
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def _build_objectives_context(include_minoxidil_beard: bool) -> str:
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if include_minoxidil_beard:
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return (
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@ -330,6 +444,12 @@ ZASADY PLANOWANIA:
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- Kolejność warstw: cleanser -> toner -> essence -> serum -> moisturizer -> [SPF dla AM].
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- Respektuj: incompatible_with (same_step / same_day / same_period), context_rules,
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min_interval_hours, max_frequency_per_week, usage_notes.
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- Zarządzanie inwentarzem:
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- najpierw zużywaj produkty już otwarte,
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- minimalizuj liczbę jednocześnie otwartych produktów funkcjonalnie podobnych,
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- nie rozpoczynaj nowego produktu, jeśli istnieje funkcjonalny odpowiednik otwarty i kompatybilny,
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- preferuj produkty z krótszym terminem ważności po otwarciu (expiry_date / PAO),
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- rotuj tylko gdy daje to wartość terapeutyczną.
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- Nie łącz retinoidów i kwasów w tej samej rutynie ani tego samego dnia (dla planu wielodniowego).
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- W AM zawsze uwzględnij SPF, jeśli kompatybilny produkt SPF istnieje na liście.
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- Dla minoksydylu (jeśli celem jest zarost i produkt jest dostępny): ustaw adekwatny region
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@ -416,6 +536,9 @@ def suggest_routine(
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grooming_ctx = _build_grooming_context(session, weekdays=[weekday])
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history_ctx = _build_recent_history(session)
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products_ctx = _build_products_context(session, time_filter=data.part_of_day.value)
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inventory_ctx = _build_inventory_context(
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session, time_filter=data.part_of_day.value
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)
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objectives_ctx = _build_objectives_context(data.include_minoxidil_beard)
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notes_line = f"\nKONTEKST OD UŻYTKOWNIKA: {data.notes}\n" if data.notes else ""
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@ -425,7 +548,7 @@ def suggest_routine(
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f"Zaproponuj rutynę pielęgnacyjną {data.part_of_day.value.upper()} "
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f"na {data.routine_date} ({day_name}).\n\n"
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"DANE WEJŚCIOWE:\n"
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f"{skin_ctx}\n{grooming_ctx}\n{history_ctx}\n{products_ctx}\n{objectives_ctx}"
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f"{skin_ctx}\n{grooming_ctx}\n{history_ctx}\n{products_ctx}\n{inventory_ctx}\n{objectives_ctx}"
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f"{notes_line}\n"
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"Zwróć JSON zgodny ze schematem."
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)
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@ -485,6 +608,7 @@ def suggest_batch(
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grooming_ctx = _build_grooming_context(session, weekdays=weekdays)
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history_ctx = _build_recent_history(session)
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products_ctx = _build_products_context(session)
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inventory_ctx = _build_inventory_context(session)
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objectives_ctx = _build_objectives_context(data.include_minoxidil_beard)
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date_range_lines = []
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@ -498,7 +622,7 @@ def suggest_batch(
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prompt = (
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f"Zaproponuj plan pielęgnacji AM + PM dla każdego dnia z zakresu:\n{dates_str}\n\n"
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"DANE WEJŚCIOWE:\n"
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f"{skin_ctx}\n{grooming_ctx}\n{history_ctx}\n{products_ctx}\n{objectives_ctx}"
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f"{skin_ctx}\n{grooming_ctx}\n{history_ctx}\n{products_ctx}\n{inventory_ctx}\n{objectives_ctx}"
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f"{notes_line}\n"
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"\nZwróć JSON zgodny ze schematem."
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)
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