296 lines
10 KiB
Python
296 lines
10 KiB
Python
import uuid
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from datetime import date
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from unittest.mock import patch
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from sqlmodel import Session
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from innercontext.api.products import (
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ProductSuggestion,
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ShoppingSuggestionResponse,
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_build_shopping_context,
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_extract_requested_product_ids,
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build_product_details_tool_handler,
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)
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from innercontext.models import (
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Product,
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ProductCategory,
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ProductInventory,
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SexAtBirth,
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SkinConcern,
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SkinConditionSnapshot,
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)
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from innercontext.models.profile import UserProfile
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from innercontext.validators.shopping_validator import (
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ShoppingValidationContext,
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ShoppingValidator,
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)
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def test_build_shopping_context(session: Session):
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# Empty context
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ctx = _build_shopping_context(session, reference_date=date.today())
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assert "USER PROFILE: no data" in ctx
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assert "(brak danych)" in ctx
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assert "POSIADANE PRODUKTY" in ctx
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profile = UserProfile(birth_date=date(1990, 1, 10), sex_at_birth=SexAtBirth.MALE)
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session.add(profile)
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session.commit()
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# Add snapshot
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snap = SkinConditionSnapshot(
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id=uuid.uuid4(),
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snapshot_date=date.today(),
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overall_state="fair",
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skin_type="combination",
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hydration_level=3,
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sensitivity_level=4,
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barrier_state="mildly_compromised",
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active_concerns=["redness"],
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priorities=["soothing"],
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)
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session.add(snap)
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# Add product
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p = Product(
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id=uuid.uuid4(),
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short_id=str(uuid.uuid4())[:8],
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name="Soothing Serum",
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brand="BrandX",
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category="serum",
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recommended_time="both",
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leave_on=True,
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targets=["redness"],
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product_effect_profile={"soothing_strength": 4, "hydration_immediate": 1},
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actives=[{"name": "Centella"}],
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)
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session.add(p)
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session.commit()
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# Add inventory
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inv = ProductInventory(id=uuid.uuid4(), product_id=p.id, is_opened=True)
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session.add(inv)
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session.commit()
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ctx = _build_shopping_context(session, reference_date=date(2026, 3, 5))
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assert "USER PROFILE:" in ctx
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assert "Age: 36" in ctx
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assert "Sex at birth: male" in ctx
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assert "Typ skóry: combination" in ctx
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assert "Nawilżenie: 3/5" in ctx
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assert "Wrażliwość: 4/5" in ctx
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assert "Aktywne problemy: redness" in ctx
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assert "Priorytety: soothing" in ctx
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# Check product
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assert "[✓] id=" in ctx
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assert "Soothing Serum" in ctx
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assert f"id={p.id}" in ctx
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assert "BrandX" in ctx
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assert "targets: ['redness']" in ctx
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assert "actives: ['Centella']" in ctx
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assert "effects: {'soothing': 4}" in ctx
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def test_suggest_shopping(client, session):
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with patch(
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"innercontext.api.products.call_gemini_with_function_tools"
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) as mock_gemini:
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product = Product(
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id=uuid.uuid4(),
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short_id=str(uuid.uuid4())[:8],
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name="Owned Serum",
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brand="BrandX",
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category="serum",
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recommended_time="both",
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leave_on=True,
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product_effect_profile={},
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)
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session.add(product)
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session.commit()
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session.add(
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ProductInventory(id=uuid.uuid4(), product_id=product.id, is_opened=True)
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)
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session.commit()
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mock_response = type(
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"Response",
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(),
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{
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"text": '{"suggestions": [{"category": "cleanser", "product_type": "cleanser", "priority": "high", "key_ingredients": ["glycerin"], "target_concerns": ["dehydration"], "recommended_time": "am", "frequency": "daily", "short_reason": "Brakuje lagodnego kroku myjacego rano.", "reason_to_buy_now": "Obecnie nie masz delikatnego produktu do porannego oczyszczania i wsparcia bariery.", "reason_not_needed_if_budget_tight": "Mozesz tymczasowo ograniczyc sie do samego splukania twarzy rano, jesli skora jest spokojna.", "fit_with_current_routine": "To domknie podstawowy krok cleanse bez dokladania agresywnych aktywow.", "usage_cautions": ["unikaj mocnego domywania przy podraznieniu"]}], "reasoning": "Test shopping"}'
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},
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)
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mock_gemini.return_value = (mock_response, None)
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r = client.post("/products/suggest")
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assert r.status_code == 200
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data = r.json()
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assert len(data["suggestions"]) == 1
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assert data["suggestions"][0]["product_type"] == "cleanser"
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assert data["suggestions"][0]["priority"] == "high"
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assert data["suggestions"][0]["short_reason"]
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assert data["suggestions"][0]["usage_cautions"] == [
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"unikaj mocnego domywania przy podraznieniu"
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]
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assert data["reasoning"] == "Test shopping"
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kwargs = mock_gemini.call_args.kwargs
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assert "USER PROFILE:" in kwargs["contents"]
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assert (
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'category: "cleanser" | "toner" | "essence"'
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in kwargs["config"].system_instruction
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)
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assert (
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'recommended_time: "am" | "pm" | "both"'
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in kwargs["config"].system_instruction
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)
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assert "function_handlers" in kwargs
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assert "get_product_details" in kwargs["function_handlers"]
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def test_suggest_shopping_invalid_json_returns_502(client):
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with patch(
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"innercontext.api.products.call_gemini_with_function_tools"
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) as mock_gemini:
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mock_response = type("Response", (), {"text": "{"})
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mock_gemini.return_value = (mock_response, None)
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r = client.post("/products/suggest")
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assert r.status_code == 502
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assert "LLM returned invalid JSON" in r.json()["detail"]
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def test_suggest_shopping_invalid_schema_returns_502(client):
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with patch(
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"innercontext.api.products.call_gemini_with_function_tools"
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) as mock_gemini:
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mock_response = type(
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"Response",
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(),
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{
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"text": '{"suggestions": [{"category": "cleanser", "product_type": "cleanser", "priority": "urgent", "key_ingredients": [], "target_concerns": [], "recommended_time": "am", "frequency": "daily", "short_reason": "x", "reason_to_buy_now": "y", "fit_with_current_routine": "z", "usage_cautions": []}], "reasoning": "Test shopping"}'
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},
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)
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mock_gemini.return_value = (mock_response, None)
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r = client.post("/products/suggest")
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assert r.status_code == 502
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assert "LLM returned invalid shopping suggestion schema" in r.json()["detail"]
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assert "suggestions/0/priority" in r.json()["detail"]
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def test_shopping_context_medication_skip(session: Session):
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p = Product(
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id=uuid.uuid4(),
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short_id=str(uuid.uuid4())[:8],
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name="Epiduo",
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brand="Galderma",
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category="serum",
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recommended_time="pm",
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leave_on=True,
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is_medication=True,
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product_effect_profile={},
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)
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session.add(p)
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session.commit()
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ctx = _build_shopping_context(session, reference_date=date.today())
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assert "Epiduo" not in ctx
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def test_extract_requested_product_ids_dedupes_and_limits():
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ids = _extract_requested_product_ids(
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{"product_ids": ["a", "b", "a", 1, "c", "d"]},
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max_ids=3,
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)
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assert ids == ["a", "b", "c"]
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def test_shopping_tool_handlers_return_payloads(session: Session):
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product = Product(
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id=uuid.uuid4(),
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short_id=str(uuid.uuid4())[:8],
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name="Test Product",
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brand="Brand",
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category="serum",
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recommended_time="both",
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leave_on=True,
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inci=["Water", "Niacinamide"],
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actives=[{"name": "Niacinamide", "percent": 5, "functions": ["niacinamide"]}],
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context_rules={"safe_after_shaving": True},
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product_effect_profile={},
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)
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payload = {"product_ids": [str(product.id)]}
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details = build_product_details_tool_handler([product])(payload)
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assert details["products"][0]["actives"][0]["name"] == "Niacinamide"
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assert "context_rules" in details["products"][0]
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assert details["products"][0]["last_used_on"] is None
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assert "inci" not in details["products"][0]
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def test_shopping_tool_handler_includes_last_used_on_from_mapping(session: Session):
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product = Product(
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id=uuid.uuid4(),
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name="Mapped Product",
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brand="Brand",
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category="serum",
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recommended_time="both",
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leave_on=True,
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product_effect_profile={},
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)
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payload = {"product_ids": [str(product.id)]}
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details = build_product_details_tool_handler(
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[product],
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last_used_on_by_product={str(product.id): date(2026, 3, 1)},
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)(payload)
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assert details["products"][0]["last_used_on"] == "2026-03-01"
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def test_shopping_validator_accepts_freeform_product_type_and_frequency():
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response = ShoppingSuggestionResponse(
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suggestions=[
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ProductSuggestion(
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category="spot_treatment",
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product_type="Punktowy preparat na wypryski z ichtiolem lub cynkiem",
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priority="high",
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key_ingredients=["ichtiol", "cynk"],
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target_concerns=["acne"],
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recommended_time="pm",
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frequency="Codziennie (punktowo na zmiany)",
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short_reason="Pomaga opanowac aktywne zmiany bez dokladania pelnego aktywu na cala twarz.",
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reason_to_buy_now="Brakuje Ci dedykowanego produktu punktowego na pojedyncze wypryski.",
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fit_with_current_routine="Mozesz dolozyc go tylko na zmiany po serum lub zamiast mocniejszego aktywu.",
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usage_cautions=["stosuj tylko miejscowo"],
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),
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ProductSuggestion(
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category="mask",
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product_type="Lagodna maska oczyszczajaca",
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priority="low",
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key_ingredients=["glinka"],
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target_concerns=["sebum_excess"],
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recommended_time="pm",
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frequency="1 raz w tygodniu",
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short_reason="To opcjonalne wsparcie przy nadmiarze sebum.",
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reason_to_buy_now="Moze pomoc domknac sporadyczne oczyszczanie, gdy skora jest bardziej przetluszczona.",
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fit_with_current_routine="Najlepiej traktowac to jako dodatkowy krok, nie zamiennik podstaw rutyny.",
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usage_cautions=[],
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),
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],
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reasoning="Test",
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)
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result = ShoppingValidator().validate(
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response,
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ShoppingValidationContext(
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owned_product_ids=set(),
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valid_categories=set(ProductCategory),
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valid_targets=set(SkinConcern),
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),
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)
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assert not any("unusual frequency" in warning for warning in result.warnings)
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