fix(products): work around Gemini int-enum schema rejection in parse-text
Gemini API rejects int-valued enums (StrengthLevel) in response_schema, raising a validation error before any request is sent. Fix by introducing AIActiveIngredient (inherits ActiveIngredient, overrides strength_level and irritation_potential as Optional[int]) and ProductParseLLMResponse used only as the Gemini schema. The two-step validation converts ints back to StrengthLevel via Pydantic coercion. Adds a test covering the numeric strength level path. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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2 changed files with 35 additions and 2 deletions
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@ -199,3 +199,22 @@ def test_create_inventory(client, created_product):
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def test_create_inventory_product_not_found(client):
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r = client.post(f"/products/{uuid.uuid4()}/inventory", json={})
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assert r.status_code == 404
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def test_parse_text_accepts_numeric_strength_levels(client, monkeypatch):
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from innercontext.api import products as products_api
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class _FakeResponse:
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text = (
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'{"name":"Test Serum","actives":[{"name":"Niacinamide","percent":10,'
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'"functions":["niacinamide"],"strength_level":2,"irritation_potential":1}]}'
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)
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monkeypatch.setattr(products_api, "call_gemini", lambda **kwargs: _FakeResponse())
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r = client.post("/products/parse-text", json={"text": "dummy input"})
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assert r.status_code == 200
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data = r.json()
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assert data["name"] == "Test Serum"
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assert data["actives"][0]["strength_level"] == 2
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assert data["actives"][0]["irritation_potential"] == 1
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