test: update multimodal tests for autodetect_images parameter

Co-Authored-By: [email protected] <[email protected]>

tests/llm/test_mistral/test_multimodal.py

@@ -17,11 +17,13 @@
     "gif": "https://upload.wikimedia.org/wikipedia/commons/2/2c/Rotating_earth_%28large%29.gif",
 }
 
+
 class ImageDescription(BaseModel):
     objects: list[str] = Field(..., description="The objects in the image")
     scene: str = Field(..., description="The scene of the image")
     colors: list[str] = Field(..., description="The colors in the image")
 
+
 @pytest.mark.requires_mistral
 @pytest.mark.parametrize("model, mode", product(models, modes))
 def test_multimodal_image_description(model: str, mode: Mode, client: Any) -> None:
@@ -50,6 +52,7 @@ def test_multimodal_image_description(model: str, mode: Mode, client: Any) -> No
     assert response.scene != ""
     assert len(response.colors) > 0
 
+
 def test_image_size_validation(tmp_path: Path) -> None:
     """Test that images over 10MB are rejected."""
     large_image: Path = tmp_path / "large_image.jpg"
@@ -58,9 +61,13 @@ def test_image_size_validation(tmp_path: Path) -> None:
         typed_file: IO[bytes] = cast(IO[bytes], file_obj)
         typed_file.write(b"0" * (10 * 1024 * 1024 + 1))
 
-    with pytest.raises(ValueError, match=r"Image file size \(10\.0MB\) exceeds Mistral's limit of 10\.0MB"):
+    with pytest.raises(
+        ValueError,
+        match=r"Image file size \(10\.0MB\) exceeds Mistral's limit of 10\.0MB",
+    ):
         Image.from_path(large_image).to_mistral()
 
+
 def test_image_format_validation() -> None:
     """Test validation of supported image formats."""
     # Test valid formats
@@ -73,6 +80,7 @@ def test_image_format_validation() -> None:
     with pytest.raises(ValueError, match="Unsupported image format"):
         Image(source="test.bmp", media_type="image/bmp", data="fake_data").to_mistral()
 
+
 @pytest.mark.requires_mistral
 @pytest.mark.parametrize("model, mode", product(models, modes))
 def test_multiple_images(model: str, mode: Mode, client: Any) -> None:
@@ -107,6 +115,7 @@ def test_multiple_images(model: str, mode: Mode, client: Any) -> None:
             ],
         )
 
+
 def test_image_downscaling() -> None:
     """Test automatic downscaling of large images."""
     large_image_url = "https://example.com/large_image.jpg"  # Mock URL
@@ -125,18 +134,20 @@ def test_image_downscaling() -> None:
         assert mistral_format is not None
         # Note: Actual downscaling verification would require PIL/image processing
 
+
 def test_base64_image_handling(base64_image: str) -> None:
     """Test handling of base64-encoded images."""
     image = Image(
         source="data:image/jpeg;base64," + base64_image,
         media_type="image/jpeg",
-        data=base64_image
+        data=base64_image,
     )
 
     mistral_format = image.to_mistral()
     assert mistral_format["type"] == "image_url"
     assert mistral_format["data"].startswith("data:image/jpeg;base64,")
 
+
 @pytest.fixture
 def base64_image() -> str:
     """Fixture providing a valid base64-encoded test image."""

tests/llm/test_openai/test_multimodal.py

@@ -9,11 +9,13 @@
 
 image_url = "https://retail.degroot-inc.com/wp-content/uploads/2024/01/AS_Blueberry_Patriot_1-605x605.jpg"
 
+
 class ImageDescription(BaseModel):
     objects: list[str] = Field(..., description="The objects in the image")
     scene: str = Field(..., description="The scene of the image")
     colors: list[str] = Field(..., description="The colors in the image")
 
+
 @pytest.mark.requires_openai
 @pytest.mark.parametrize("model, mode", product(models, modes))
 def test_multimodal_image_description(model: str, mode: Mode, client: Any) -> None:
@@ -42,9 +44,12 @@ def test_multimodal_image_description(model: str, mode: Mode, client: Any) -> No
     assert response.scene != ""
     assert len(response.colors) > 0
 
+
 @pytest.mark.requires_openai
 @pytest.mark.parametrize("model, mode", product(models, modes))
-def test_multimodal_image_description_autodetect(model: str, mode: Mode, client: Any) -> None:
+def test_multimodal_image_description_autodetect(
+    model: str, mode: Mode, client: Any
+) -> None:
     client = instructor.from_openai(client, mode=mode)
     response = client.chat.completions.create(
         model=model,  # Ensure this is a vision-capable model
@@ -71,9 +76,12 @@ def test_multimodal_image_description_autodetect(model: str, mode: Mode, client:
     assert response.scene != ""
     assert len(response.colors) > 0
 
+
 @pytest.mark.requires_openai
 @pytest.mark.parametrize("model, mode", product(models, modes))
-def test_multimodal_image_description_autodetect_no_response_model(model: str, mode: Mode, client: Any) -> None:
+def test_multimodal_image_description_autodetect_no_response_model(
+    model: str, mode: Mode, client: Any
+) -> None:
     client = instructor.from_openai(client, mode=mode)
     response = client.chat.completions.create(
         response_model=None,

tests/test_multimodal.py

@@ -347,9 +347,7 @@ def test_image_autodetect(input_data, expected_type, expected_media_type, reques
 
 
 def test_image_autodetect_invalid_input():
-    with pytest.raises(
-        ValueError, match="Invalid or unsupported base64 image data"
-    ):
+    with pytest.raises(ValueError, match="Invalid or unsupported base64 image data"):
         Image.autodetect("not_an_image_input")
 
     # Test safely converting an invalid image