LLMs as a knowledge source

GenAI with vector databases

Course coverage and prerequisites

What is a vector?

Vectorization in NLP

Vector similarity search

Vector databases

Pros and cons of vector databases

Introduction to Milvus DB

Milvus architecture

Collections in Milvus

Partitions in Milvus

Indexes in Milvus

Managing data in Milvus

Query and search in Milvus

Set up Milvus and exercise files

Create a connection

Create databases and users

Create collections

Insert data into Milvus

Build an index

Query scalar data

Search vector fields

Delete objects and entities

LLMs and caching

Prompt caching workflow

Set up the Milvus cache

Inference process and caching

Cache management

Introduction to retrieval augmented generation

RAG: Knowledge curation process

RAG question-answering process

Applications of RAG

Set up Milvus for RAG

Prepare data for the knowledge base

Populate the Milvus database

Answer questions with RAG

Choose a vector database

Combine vector and scalar data

Distance measure considerations

Tune vector DB performance

Continue with LLMs