58 lines
2.1 KiB
Python
58 lines
2.1 KiB
Python
import sys
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from types import ModuleType
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import pytest
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from fastapi.testclient import TestClient
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from great_ai import GreatAI
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def test_keyword_only_inputs_are_validated_and_exposed(isolated_context: None) -> None:
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@GreatAI.create
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def predict(*, value: int) -> int:
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return value
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trace = predict(value=7)
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assert trace.output == 7
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assert trace.logged_values["arg:value:value"] == 7
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with pytest.raises(TypeError):
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predict(value="wrong")
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with TestClient(predict.app) as client:
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assert client.post("/predict", json={"value": 8}).json()["output"] == 8
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assert client.post("/predict", json={"value": "wrong"}).status_code == 422
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def test_positional_only_inputs_keep_their_bindings(isolated_context: None) -> None:
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@GreatAI.create
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def predict(first: str, /, second: int = 7) -> str:
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return first * second
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trace = predict("a", 2)
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assert trace.output == "aa"
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assert trace.logged_values["arg:first:value"] == "a"
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assert trace.logged_values["arg:second:value"] == 2
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with TestClient(predict.app) as client:
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response = client.post("/predict", json={"first": "b", "second": 3})
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assert response.status_code == 200
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assert response.json()["output"] == "bbb"
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def test_postponed_model_annotations_resolve_in_their_module(
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isolated_context: None, monkeypatch: pytest.MonkeyPatch
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) -> None:
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module = ModuleType("great_ai_test_annotations")
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monkeypatch.setitem(sys.modules, module.__name__, module)
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exec(
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"from __future__ import annotations\n"
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"from pydantic import BaseModel\n"
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"class Payload(BaseModel):\n value: int\n"
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"def predict(data: Payload) -> int:\n return data.value\n",
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module.__dict__,
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)
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service = GreatAI.create(module.predict)
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with pytest.raises(TypeError):
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service("wrong")
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with TestClient(service.app) as client:
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response = client.post("/predict", json={"data": {"value": 7}})
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assert response.status_code == 200
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assert response.json()["output"] == 7
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assert client.get("/openapi.json").status_code == 200
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