Add GPT4Vision Image loader (#1089)
Co-authored-by: Deshraj Yadav <deshrajdry@gmail.com>
This commit is contained in:
@@ -1,78 +0,0 @@
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import unittest
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from embedchain.chunkers.images import ImagesChunker
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from embedchain.config import ChunkerConfig
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from embedchain.models.data_type import DataType
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class TestImageChunker(unittest.TestCase):
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def test_chunks(self):
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"""
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Test the chunks generated by TextChunker.
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# TODO: Not a very precise test.
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"""
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chunker_config = ChunkerConfig(chunk_size=1, chunk_overlap=0, length_function=len, min_chunk_size=0)
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chunker = ImagesChunker(config=chunker_config)
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# Data type must be set manually in the test
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chunker.set_data_type(DataType.IMAGES)
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image_path = "./tmp/image.jpeg"
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app_id = "app1"
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result = chunker.create_chunks(MockLoader(), image_path, app_id=app_id)
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expected_chunks = {
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"doc_id": f"{app_id}--123",
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"documents": [image_path],
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"embeddings": ["embedding"],
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"ids": ["140bedbf9c3f6d56a9846d2ba7088798683f4da0c248231336e6a05679e4fdfe"],
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"metadatas": [{"data_type": "images", "doc_id": f"{app_id}--123", "url": "none"}],
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}
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self.assertEqual(expected_chunks, result)
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def test_chunks_with_default_config(self):
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"""
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Test the chunks generated by ImageChunker with default config.
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"""
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chunker = ImagesChunker()
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# Data type must be set manually in the test
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chunker.set_data_type(DataType.IMAGES)
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image_path = "./tmp/image.jpeg"
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app_id = "app1"
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result = chunker.create_chunks(MockLoader(), image_path, app_id=app_id)
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expected_chunks = {
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"doc_id": f"{app_id}--123",
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"documents": [image_path],
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"embeddings": ["embedding"],
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"ids": ["140bedbf9c3f6d56a9846d2ba7088798683f4da0c248231336e6a05679e4fdfe"],
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"metadatas": [{"data_type": "images", "doc_id": f"{app_id}--123", "url": "none"}],
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}
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self.assertEqual(expected_chunks, result)
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def test_word_count(self):
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chunker_config = ChunkerConfig(chunk_size=1, chunk_overlap=0, length_function=len, min_chunk_size=0)
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chunker = ImagesChunker(config=chunker_config)
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chunker.set_data_type(DataType.IMAGES)
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document = [["ab cd", "ef gh"], ["ij kl", "mn op"]]
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result = chunker.get_word_count(document)
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self.assertEqual(result, 1)
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class MockLoader:
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def load_data(self, src):
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"""
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Mock loader that returns a list of data dictionaries.
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Adjust this method to return different data for testing.
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"""
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return {
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"doc_id": "123",
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"data": [
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{
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"content": src,
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"embedding": "embedding",
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"meta_data": {"url": "none"},
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}
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],
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}
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