OmniVector provides a simple interface to vector databases. We integrate the main functionalities of different vector dbs, generally indexing and searching, into a single interface. This allows us to easily switch between different vector dbs.
db = WeaviateDB() # or PineconeDB() or LanceDB()
encoder = SentenceTransformerEmbedder("paraphrase-MiniLM-L6-v2", device="cpu")
docs = ["the cat is on the table", "the table is on the cat", "the dog is mining bitcoins"]
ids = list(range(4, len(docs) + 4))
embeddings = encoder.embed(docs)
db.create_index()
db.add(ids, docs, embeddings)
search_vector = encoder.embed(["the dog is mining bitcoins"])[0]
print(db.vector_search(search_vector, k=1))- Free software: MIT license
- Documentation: https://omnivector.readthedocs.io.
- The AbstractDB requires setting OMNIVECTOR_CONFIG env variable to a config file (an example is in config.yaml)
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.