Vector Databases for Your LLM + Streamlit Applications

Vector Databases for Your LLM + Streamlit Applications.


Author(s): Yaksh Birla

Originally published on Towards AI.

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If you’ve been toying with large language models (LLM) and their applications long enough, you’ve probably heard of vector databases. In the boundless realm of LLM applications, vector databases stand as crucial pillars that codify and handle our data. They play a pivotal role in managing and querying vector information efficiently, making them indispensable for current generative AI applications.

Here’s my effort at distilling in bullets what vector databases are and why they are important for AI applications.

Vector embedding and storage diagram from PineconeEmbedding Conversion: Vector databases convert textual information into vector embeddings, which are mathematical representations that… Read the full blog for free on Medium.

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AI Applications

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