Skip to content
hands-on lab

Deploy PolicyPal LLM Application

Difficulty: Intermediate
Duration: Up to 3 hours
Students: 12
Start lab
On average, students complete this lab in30m
Get guided in a real environmentPractice with a step-by-step scenario in a real, provisioned environment.
Learn and validateUse validations to check your solutions every step of the way.
See resultsTrack your knowledge and monitor your progress.
About
Author

Description

Deploy a Lendsafe to managed endpoint

By the end of this lab you will have a understanding of how to created managed endpoint in Azure ML studio, running conversational endpoint that retrieves relevant policy documents and generates sourced answers with safety guardrails.

Learning objectives

Upon completion of this intermediate level lab, you will be able to:

  • Understand the LLM
  • AI Search
  • Safety guardrails

Intended audience

  • Cloud Architects
  • Data Engineers
  • DevOps Engineers
  • Machine Learning Engineers
  • Software Engineers

Prerequisites

Familiarity with the following will be beneficial but is not required:

  • LLMs
  • AI Search
  • Machine Learning
Hands-on Lab UUID

Lab steps

0 of 5 steps completed.Use arrow keys to navigate between steps. Press Enter to go to a step if available.
  1. Logging in to the Microsoft Azure Portal
  2. Deploy LendSafe to Azure ML Managed Endpoint
  3. Deploy PolicyPal LLM Application
  4. Scaling and Load Testing
  5. Adding Basic Monitoring

Lab Rules