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- # import os
- # import tempfile
- # import urllib
- # import pytest
- # from PIL import Image
- # TODO: Uncomment after fixing clip dependency issue
- # from embedchain.models.clip_processor import ClipProcessor
- # class TestClipProcessor:
- # @pytest.mark.xfail(reason="This test is failing because of the missing CLIP dependency.")
- # def test_load_model(self):
- # # Test that the `load_model()` method loads the CLIP model and image preprocessing correctly.
- # model, preprocess = ClipProcessor.load_model()
- # assert model is not None
- # assert preprocess is not None
- # @pytest.mark.xfail(reason="This test is failing because of the missing CLIP dependency.")
- # def test_get_image_features(self):
- # # Clone the image to a temporary folder.
- # with tempfile.TemporaryDirectory() as tmp_dir:
- # urllib.request.urlretrieve("https://upload.wikimedia.org/wikipedia/en/a/a9/Example.jpg", "image.jpg")
- # image = Image.open("image.jpg")
- # image.save(os.path.join(tmp_dir, "image.jpg"))
- # # Get the image features.
- # model, preprocess = ClipProcessor.load_model()
- # ClipProcessor.get_image_features(os.path.join(tmp_dir, "image.jpg"), model, preprocess)
- # # Delete the temporary file.
- # os.remove(os.path.join(tmp_dir, "image.jpg"))
- # @pytest.mark.xfail(reason="This test is failing because of the missing CLIP dependency.")
- # def test_get_text_features(self):
- # # Test that the `get_text_features()` method returns a list containing the text embedding.
- # query = "This is a text query."
- # model, preprocess = ClipProcessor.load_model()
- # text_features = ClipProcessor.get_text_features(query)
- # # Assert that the text embedding is not None.
- # assert text_features is not None
- # # Assert that the text embedding is a list of floats.
- # assert isinstance(text_features, list)
- # # Assert that the text embedding has the correct length.
- # assert len(text_features) == 512
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