fastest vector database made in numpy
a simple and blazing fast vector database
there is no database you need to set up, no server to run, and no complex configuration. just install vlite and start using it. take the CTX file with you wherever you go. its like a browser cookie but with embeddings.
pip install vliteTo enable PDF OCR support (with surya), install the vlite[ocr] extra:
pip install vlite[ocr]from vlite import VLite
from vlite.utils import process_pdf
vdb = VLite()
vdb.add("hello world", metadata={"artist": "adele"})
vdb.add(process_pdf("attention-is-all-you-need.pdf", use_ocr=True))
results = vdb.retrieve("how do transformers work?")
print(results)…vlite is a vector database built for agents, ChatGPT Plugins, and other AI apps that need a fast and simple database to store vectors. It was developed to support the billions of embeddings generated, indexed, and sorted with ChatWith+ ChatGPT Plugins, which run for millions of users. Most vector databases either repeatedly crashed on a daily basis or were too expensive for the high throughput required.
vlite introduces the CTX file format, which acts like a browser cookie for user embeddings, providing efficient storage, retrieval of embeddings, composability, portability, and user context.
AGPL-3.0 License
Thanks to Claude and Ray for their contributions to vlite. If you'd like to contribute, please open an issue or a pull request.
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