INTPYTHON-598 - Create an AI/ML helper library #1
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pymongo_vectorsearch_utils/index.py
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| embedding_field: str, | ||
| n_docs: int, | ||
| ) -> bool: | ||
| """Inserts texts using the provided insert_func and then waits for texts |
pymongo_vectorsearch_utils/index.py
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| wait_until_complete: float | None = None, | ||
| **kwargs: Any, | ||
| ) -> None: | ||
| """Experimental Utility function to create an Atlas Search index |
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I'd say these aren't experimental anymore
| assert len(indexes) == 0 | ||
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| def test_search_index_update_vector_search_index(collection: Collection) -> None: |
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Note we'll have to skip this on local Atlas due to its limitations around update
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It works locally using the Atlas CLI, https://jira.mongodb.org/browse/CLOUDP-275518 is completed.
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Great! I updated https://jira.mongodb.org/browse/INTPYTHON-317
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I ended up having to replicate much of the logic in bulk_embed_and_insert_texts in crewai. |
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@blink1073 adding utilities for those cases sounds good. I'd prefer to put those changes in separate PRs to reduce the review burden. |
Yeah that works for me |
I brought over the most directly applicable utilities from langchain-mongodb and reworked or added tests. Feel free to suggest other utilities we want, this PR directly addresses only what's described in the ticket.