chore: import upstream snapshot with attribution

tests/pyfunc/test_pyfunc_input_converter.py

@@ -0,0 +1,89 @@
+from dataclasses import asdict, dataclass
+from typing import Optional
+
+import pandas as pd
+import pytest
+
+from mlflow.models.rag_signatures import ChatCompletionRequest
+from mlflow.pyfunc.utils.input_converter import _hydrate_dataclass
+
+
+def test_hydrate_dataclass_input_no_dataclass():
+    # Define a class that is not a dataclass
+    class NotADataclass:
+        pass
+
+    # Create some dummy data as a pandas df
+    data = {"a": 1, "b": 2}
+    df = pd.DataFrame(data, index=[0])
+
+    # Check that an error is raised when trying to hydrate the dataclass
+    with pytest.raises(ValueError, match="NotADataclass is not a dataclass"):
+        _hydrate_dataclass(NotADataclass, df.iloc[0])
+
+
+def test_hydrate_dataclass_simple():
+    # Define a dataclass
+    @dataclass
+    class MyDataclass:
+        a: int
+        b: int
+
+    # Create some dummy data as a pandas df
+    df = pd.DataFrame({"a": [1], "b": [2]})
+
+    # Check that the dataclass is hydrated
+    result = _hydrate_dataclass(MyDataclass, df.iloc[0])
+    assert result == MyDataclass(a=1, b=2)
+
+
+def test_hydrate_dataclass_complex():
+    # Define a more complex dataclass
+    @dataclass
+    class MyDataclass:
+        a: int
+        b: int
+
+    @dataclass
+    class MyListDataclass:
+        c: list[MyDataclass]
+
+    # Create some dummy data as a pandas df
+    df = pd.DataFrame({"c": [[{"a": 1, "b": 2}, {"a": 3, "b": 4}]]})
+
+    # Check that the dataclass is hydrated
+    result = _hydrate_dataclass(MyListDataclass, df.iloc[0])
+    assert result == MyListDataclass(c=[MyDataclass(a=1, b=2), MyDataclass(a=3, b=4)])
+
+
+@dataclass
+class CustomInput:
+    id: int = 0
+
+
+@dataclass
+class FlexibleChatCompletionRequest(ChatCompletionRequest):
+    custom_input: Optional[CustomInput] = None  # noqa: UP045
+    another_custom_input: CustomInput | None = None
+
+
+def test_hydrate_child_dataclass():
+    result = _hydrate_dataclass(
+        FlexibleChatCompletionRequest,
+        asdict(
+            FlexibleChatCompletionRequest(
+                custom_input=CustomInput(), another_custom_input=CustomInput()
+            )
+        ),
+    )
+    assert result == FlexibleChatCompletionRequest(
+        custom_input=CustomInput(), another_custom_input=CustomInput()
+    )
+
+
+def test_hydrate_optional_dataclass():
+    result = _hydrate_dataclass(
+        FlexibleChatCompletionRequest,
+        asdict(FlexibleChatCompletionRequest(custom_input=None, another_custom_input=None)),
+    )
+    assert result == FlexibleChatCompletionRequest(custom_input=None, another_custom_input=None)