Vector databases
Many LLM applications require context or user-specific data that is not part of the LLM's training set. This information is stored in the form of vector embeddings which are ideally suited to accurately capture semantically complex and context-rich unstructured data.
Vector databases offer optimized storage and querying capabilities for vector embeddings, making them a core building block of LLM-powered applications.
Konko AI is inter-operable with all major vector databases.
The following guides show how to use basic vector database functionality alongside Konko AI's APIs:
Updated 7 months ago
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