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4b8352e0f5
Adds Chroma (also known as ChromaDB) as a vector destination. Currently Chroma is an in-memory single-process oriented library with plans of a hosted and/or more production ready solution -https://docs.trychroma.com/deployment Though they now claim to support multiple Clients hitting the database at once, I found that it was inconsistent. Sometimes multiprocessing worked (maybe 1 out of 3 times) But the other times I would get different errors. So I kept it single process. --------- Co-authored-by: potter-potter <david.potter@gmail.com>
30 lines
816 B
Python
Executable File
30 lines
816 B
Python
Executable File
import chromadb
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import click
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@click.command()
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@click.option("--collection-name", type=str)
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def run_check(collection_name):
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print(f"Checking contents of Chroma collection: {collection_name}")
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chroma_client = chromadb.HttpClient(host="localhost", port=8000)
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collection = chroma_client.get_or_create_collection(name=collection_name)
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number_of_embeddings = collection.count()
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expected_embeddings = 3
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print(
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f"# of embeddings in collection vs expected: {number_of_embeddings}/{expected_embeddings}"
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)
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assert number_of_embeddings == expected_embeddings, (
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f"Number of rows in generated table ({number_of_embeddings}) "
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f"doesn't match expected value: {expected_embeddings}"
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)
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print("Table check complete")
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if __name__ == "__main__":
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run_check()
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