This repository introduces and helps organizations get started with building AI Apps and incorporating Large Language Models (LLMs) into them.
The objective of this workshop is to practice realistic AI orchestration scenarios towards learning how to build intelligent apps. At the end of the workshop you will:
- Know how to use prompt engineering techniques for effective generative AI responses on OpenAI
- Understand the implications of the usage of tokens and embeddings when interacting with an LLM
- Have experience in leveraging AI orchestrators like Langchain/ Semantic Kernel with Azure OpenAI
- Have evaluated different Vectorstores like Qdrant/ Azure Cognitive Search to enhance LLM responses with your data and context
- Know how to turn a business scenario with data, context and user input into an intelligent application on Azure
Focus: Introduction, First Steps & Prompt Engineering
- 📣 Intro (30min)
- Introductions & Setting Expectations
- Use Case Ideation & Brainstorming
- 📣 Intro to Azure OpenAI, Prompt Engineering & Demos (105min)
- Azure OpenAI Service
- Demo(s)
- Break
- 🧑🏼💻 Lab #1 - Hands-on with Prompt Engineering Exercises
- 📣 Intro to AI Orchestration (60min)
- AI Orchestration
- Demo(s)
Focus: Building AI Apps & Incorporating LLMs
- 📣 Intro to AI Orchestration Continued (135min)
- Wrapping-up (60min)
- Use Case Validation
- QnA & Closing Remarks
The steps in this section will take you through setting up Azure OpenAI and some configuration files so that you can complete all of the hands-on labs successfully.
When you're done with this workshop and ready to move on, the following may be useful.
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