No video of the event yet, sorry!

In this hands-on lab, you will build an agent-driven Retrieval-Augmented Generation (RAG) application using a U.S. Case Law dataset. You will work with Azure Database for PostgreSQL, Visual Studio Code, and the Semantic Kernel Agent Framework to explore AI-powered text and vector search. The lab also introduces GraphRAG with Apache AGE, enabling enriched querying across structured and graph-based data. By the end, you'll gain practical skills in semantic search, vector indexing, and intelligent data retrieval.

Topics Covered:

Setting up your Azure Database for PostgreSQL server

Launch PSQL Command Line Shell in VS Code

Using AI-driven features in Postgres

Using Semantic Vector Search and DiskANN Index

Perform a Semantic Search Query

Semantic Agent Configuration and Plugin Assembly

Learning Objectives:

After completing this training, attendees will be able to:

Deploy and configure Azure Database for PostgreSQL for AI-powered workloads.

Use Postgres vector search and DiskANN indexing to perform efficient semantic queries.

Build an agent-driven RAG application using the Semantic Kernel Agent Framework.

Integrate structured SQL data, vector embeddings, and graph-based relationships using GraphRAG with Apache AGE.

Assemble semantic plugins, configure agent workflows, and query a real dataset (U.S. Case Law) using enriched retrieval techniques.