Vector databases 101

The advent of large language models (LLMs) has unlocked new use cases for interacting with internal data through natural language queries, known as "retrieval-augmented generation" (RAG). However, deploying production-grade RAG systems presents challenges, from engineering to operational hurdles.

This white paper outlines best practices for addressing key challenges in developing and deploying RAG systems, including:

Efficient retrieval using vector databases for semantic search and relevance
Choosing the right LLM model and using prompt engineering and guardrail techniques to improve generation quality
And more

Read on now to find out how you can set up a production-ready RAG system.

Vendor:: Shakudo Inc.
Posted:: Sep 12, 2024
Published:: Sep 16, 2024
Format:: PDF
Type:: White Paper

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