Welcome to a journey where we explore the incredible capabilities of the Azure OpenAI Service! With REST API access to OpenAI’s powerful language models, you’ll learn how to create applications for content generation, summarization, semantic search, and more.

Introduction

This workshop is designed to empower you with hands-on experience using the Azure OpenAI API. By the end of this article, you will not only understand the basics of Azure OpenAI but also develop applications that can tackle various NLP tasks.

Goals of the Workshop

• Understand OpenAI basics on LLMs (Large Language Models), APIs, and application scenarios.
• Learn about prompt engineering.
• Explore common NLP tasks: summarization, classification, entity recognition, and sentiment analysis.
• Understand generative tasks, including content and code generation.
• Familiarize yourself with conversational dialog and learning methods: zero shot, few-shot, and in-context learning.

Building Your First AOAI Application

To get started with Azure OpenAI, you’ll be building applications using multiple platforms such as PowerApps and Python. The following are advanced application ideas you can try:

• Your first AOAI application with PowerApp
• A natural language query application on SQL data
• An AOAI data pipeline to extract insights from unstructured data
• Make ChatGPT work on your own proprietary dataset

Understanding the Code: An Analogy

Imagine you’re a chef trying to create a fantastic dish. Here, the Azure OpenAI API is your culinary assistant. Just as a chef selects ingredients and methods to create a dish, you send prompts (ingredients) to the model to get the desired outputs (the final dish!). This can range from basic ingredients for a simple meal (e.g., content generation) to complex culinary techniques for gourmet meals (e.g., data pipelines). The magic lies in how skillfully you combine these prompt recipes!

Troubleshooting Section

While working on your AOAI applications, you might encounter some hiccups. Here are a few troubleshooting tips:

• Ensure that your API keys are valid and you have appropriate access permissions.
• If you encounter errors during model requests, double-check your prompt formatting.
• Make sure Azure services are up and running; sometimes, downtime may affect your requests.
• For specific API use cases, refer to the documentation for best practices.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Conclusion

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

By leveraging Azure OpenAI, you are now equipped to transform your ideas into powerful AI applications. Happy coding!