In this technical workshop, you will get a comprehensive introduction to Azure OpenAI Service and Azure OpenAI Studio. You will learn how to create and refine prompts for various scenarios using hands-on exercises. You will also discover how to leverage Azure OpenAI Service to access and analyze your company data. Moreover, you will explore existing solution accelerators and best practices for prototyping and deploying use cases end-to-end. The workshop will end with a Q&A session and a wrap-up.
Fokus: Introduction and first steps
Focus: Solutions
📣 Presentation, 🧑🏼💻 Hands-on lab
This is only required for the hands-on lab. If you are only attending the presentation, you can skip this section.
Grant the participant access to the Azure OpenAI Service subscription and create the required deployments.
Ideally, grant the participants access to Azure OpenAI Service service be assigning the Cognitive Service OpenAI user
. If the participant is a Cognitive Service OpenAI contributor
, they can create the following deployments themselves.
Otherwise, create 'text-davinci-003' and 'text-embedding-ada-002' deployments (and assign the participant to the deployments).
There are two ways to authenticate (see Jupyter notebooks):
Get the Azure OpenAI Service endpoint (and key) from the Azure portal.
Choose one of the following options to set up your environment: Codespaces, Devcontainer or bring your own environment (Anaconda). Building the environment can take a few minutes, so please start early.
🌟 Highly recommended: Best option if you already have a Github account. You can develop on local VSCode or in a browser window.
Code
button.env
file in the base folder including Azure OpenAI Service endpoint and key before starting any notebooksUsually a good option if VSCode and Docker Desktop are already installed.
Reopen in Container
.env
file in the base folder including Azure OpenAI Service endpoint and key before starting any notebooksIf you already have a Python environment with Jupyter Notebook and the Azure CLI installed.
Make sure you have the requirements installed in your Python environment using pip install -r requirements.txt
.
Do not cheat! :sweat_smile:
If you want to quickly create a Q&A webapp using your own data, please follow the quickstart guide notebook.
If you want to use LangChain to build an interactive chat experience on your own data, follow the quickstart chat on private data using LangChain.
If you want to use LlamaIndex 🦙 (GPT Index), follow the quickstart guide notebook with llama-index.
Download Details:
Author: Microsoft
Official Github: https://github.com/microsoft/azure-openai-in-a-day-workshop
License: MIT