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t6_mem0/tests/models/test_clip_processor.py

52 lines
2.1 KiB
Python

# 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