Wriju Ghosh
Developer who loves Cloud
Bengaluru, India
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Works as a Cloud Solution Architect. He is by training a professional developer started working since 2001. One of the early adopters of Azure. Have presented and worked since it's alpha days. Believes in OpenSource Learning.
Area of Expertise
Topics
Building Serverless Apps in Azure
Using Azure Serverless services we end up building an application, backend and data store with a pinch of AI
Build-Containerize-Deploy Web App to Azure Kubernetes Services (AKS)
Build an web application in .Net Core (or anything). Then containerize it. Move this image to a container registry say Azure Container Registry (ACR). Then using this Container image deploy a public facing website in AKS. It is demo only session needs some basic understanding of Web Application, Container and Kubernetes. However I will try my best to explain them while deploying.
Build and Deploy your Open AI Application in the Cloud
Chat applications are becoming more popular and powerful, thanks to the advances in natural language processing and artificial intelligence. In this session, you will learn how to create chat applications that leverage Azure OpenAI, LangChain, and Azure Container Apps.
Azure OpenAI is a cloud service that provides access to OpenAI’s powerful language models, such as GPT-3, which can generate natural and engaging responses for various conversational scenarios. LangChain is a Python framework that simplifies the development of chat applications by providing tools for data processing, embedding, indexing, querying, and reasoning. Azure Container Apps is a fully managed environment that enables you to run microservices and containerized applications on a serverless platform.
You will see how to use Terraform to deploy the infrastructure and the chat applications, which use a user-defined managed identity to authenticate and authorize against Azure OpenAI Service and Azure Container Registry, and use Azure Private Endpoints to connect privately and securely to these services. You will also learn how to use Chainlit, an open-source Python package that is designed to create user interfaces for AI applications, and how to integrate it with LangChain, ChromaDB, and LangFlow.
By the end of this session, you will have a better understanding of how to build chat applications that utilize cutting-edge technologies, empowering users with intelligent conversational capabilities.
In this session, you will learn how to create chat applications that leverage Azure OpenAI, LangChain, and Azure Container Apps.
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