innercontext/backend/tests/test_products_helpers.py
Piotr Oleszczyk b58fcb1440 feat(api): add tool-calling flow for shopping suggestions
Keep /products/suggest lean by exposing product UUIDs and fetching INCI, safety rules, actives, and usage notes on demand through Gemini function tools. Add conservative fallback behavior for tool roundtrip limits and expand helper tests to cover tool wiring and payload handlers.
2026-03-04 12:05:33 +01:00

157 lines
5.1 KiB
Python

import uuid
from datetime import date
from unittest.mock import patch
from sqlmodel import Session
from innercontext.api.products import (
_build_actives_tool_handler,
_build_inci_tool_handler,
_build_safety_rules_tool_handler,
_build_shopping_context,
_build_usage_notes_tool_handler,
_extract_requested_product_ids,
)
from innercontext.models import Product, ProductInventory, SkinConditionSnapshot
def test_build_shopping_context(session: Session):
# Empty context
ctx = _build_shopping_context(session)
assert "(brak danych)" in ctx
assert "POSIADANE PRODUKTY" in ctx
# Add snapshot
snap = SkinConditionSnapshot(
id=uuid.uuid4(),
snapshot_date=date.today(),
overall_state="fair",
skin_type="combination",
hydration_level=3,
sensitivity_level=4,
barrier_state="mildly_compromised",
active_concerns=["redness"],
priorities=["soothing"],
)
session.add(snap)
# Add product
p = Product(
id=uuid.uuid4(),
name="Soothing Serum",
brand="BrandX",
category="serum",
recommended_time="both",
leave_on=True,
targets=["redness"],
product_effect_profile={"soothing_strength": 4, "hydration_immediate": 1},
actives=[{"name": "Centella"}],
)
session.add(p)
session.commit()
# Add inventory
inv = ProductInventory(id=uuid.uuid4(), product_id=p.id, is_opened=True)
session.add(inv)
session.commit()
ctx = _build_shopping_context(session)
assert "Typ skóry: combination" in ctx
assert "Nawilżenie: 3/5" in ctx
assert "Wrażliwość: 4/5" in ctx
assert "Aktywne problemy: redness" in ctx
assert "Priorytety: soothing" in ctx
# Check product
assert "[✓] id=" in ctx
assert "Soothing Serum" in ctx
assert f"id={p.id}" in ctx
assert "BrandX" in ctx
assert "targets: ['redness']" in ctx
assert "actives: ['Centella']" in ctx
assert "effects: {'soothing': 4}" in ctx
def test_suggest_shopping(client, session):
with patch(
"innercontext.api.products.call_gemini_with_function_tools"
) as mock_gemini:
mock_response = type(
"Response",
(),
{
"text": '{"suggestions": [{"category": "cleanser", "product_type": "cleanser", "priority": "high", "key_ingredients": [], "target_concerns": [], "why_needed": "reason", "recommended_time": "am", "frequency": "daily"}], "reasoning": "Test shopping"}'
},
)
mock_gemini.return_value = mock_response
r = client.post("/products/suggest")
assert r.status_code == 200
data = r.json()
assert len(data["suggestions"]) == 1
assert data["suggestions"][0]["product_type"] == "cleanser"
assert data["reasoning"] == "Test shopping"
kwargs = mock_gemini.call_args.kwargs
assert "function_handlers" in kwargs
assert "get_product_inci" in kwargs["function_handlers"]
assert "get_product_safety_rules" in kwargs["function_handlers"]
assert "get_product_actives" in kwargs["function_handlers"]
assert "get_product_usage_notes" in kwargs["function_handlers"]
def test_shopping_context_medication_skip(session: Session):
p = Product(
id=uuid.uuid4(),
name="Epiduo",
brand="Galderma",
category="serum",
recommended_time="pm",
leave_on=True,
is_medication=True,
product_effect_profile={},
)
session.add(p)
session.commit()
ctx = _build_shopping_context(session)
assert "Epiduo" not in ctx
def test_extract_requested_product_ids_dedupes_and_limits():
ids = _extract_requested_product_ids(
{"product_ids": ["a", "b", "a", 1, "c", "d"]},
max_ids=3,
)
assert ids == ["a", "b", "c"]
def test_shopping_tool_handlers_return_payloads(session: Session):
product = Product(
id=uuid.uuid4(),
name="Test Product",
brand="Brand",
category="serum",
recommended_time="both",
leave_on=True,
usage_notes="Use AM and PM on clean skin.",
inci=["Water", "Niacinamide"],
actives=[{"name": "Niacinamide", "percent": 5, "functions": ["niacinamide"]}],
incompatible_with=[{"target": "Vitamin C", "scope": "same_step"}],
context_rules={"safe_after_shaving": True},
product_effect_profile={},
)
payload = {"product_ids": [str(product.id)]}
inci_data = _build_inci_tool_handler([product])(payload)
assert inci_data["products"][0]["inci"] == ["Water", "Niacinamide"]
actives_data = _build_actives_tool_handler([product])(payload)
assert actives_data["products"][0]["actives"][0]["name"] == "Niacinamide"
notes_data = _build_usage_notes_tool_handler([product])(payload)
assert notes_data["products"][0]["usage_notes"] == "Use AM and PM on clean skin."
safety_data = _build_safety_rules_tool_handler([product])(payload)
assert "incompatible_with" in safety_data["products"][0]
assert "context_rules" in safety_data["products"][0]