Add GPT4Vision Image loader (#1089)

Co-authored-by: Deshraj Yadav <deshrajdry@gmail.com>

tests/models/test_clip_processor.py

@@ -1,44 +0,0 @@
-import os
-import tempfile
-import urllib
-
-from PIL import Image
-
-from embedchain.models.clip_processor import ClipProcessor
-
-
-class TestClipProcessor:
-    def test_load_model(self):
-        # Test that the `load_model()` method loads the CLIP model and image preprocessing correctly.
-        model = ClipProcessor.load_model()
-        assert model is not None
-
-    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 = ClipProcessor.load_model()
-            ClipProcessor.get_image_features(os.path.join(tmp_dir, "image.jpg"), model)
-
-            # Delete the temporary file.
-            os.remove(os.path.join(tmp_dir, "image.jpg"))
-            os.remove("image.jpg")
-
-    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."
-        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