Workshop: Developing Microservices for Chatbot on Azure Function along with Azure Whisper Modeland AI Vision

Large Language Models (LLMs) like GPT-4 have revolutionized how we interact with technology, offering unparalleled convenience in everyday tasks. However, these models often fall short when it comes to addressing questions specific to a college's teaching content, as they aren't trained on institution-specific materials.

Retrieval Augmented Generation (RAG) provides a powerful solution, enabling chatbots to integrate and utilize customized content for accurate and context-aware responses. Azure Functions is a serverless cloud service offered by Azure that streamlines the deployment and scalability of applications without the need to manage infrastructure. Designed to handle a wide range of workloads, Azure Functions operates on a pay-as-you-go model, making it cost-effective for projects of any size. Whether you're automating tasks, integrating systems, or hosting applications like chatbots, Azure Functions ensures seamless performance and flexibility, allowing developers to focus on building solutions rather than worrying about servers.

In this workshop, you’ll learn how to build a simple RAGbased chatbot using Python and deploy it seamlessly with Azure Functions.

In today’s digital landscape, spoken language and visual content are emerging as dominant modes of communication. The proliferation of voice assistants and video-based platforms highlights the need for AI systems that can process speech and images as seamlessly as text.

This workshop explores the integration of Azure's Whisper Model and AI Vision/Video Indexer services into chatbot development, focusing on how these technologies can process spoken and visual inputs. The session will cover configuring Azure services, designing workflows to process speech and visual content, and creating a chatbot that can seamlessly handle complex, multimodal interactions.