Deploying Chat Models with Azure OpenAI in LangChain

Learn how to use Azure OpenAI in LangChain to deploy resources and create a chat model. Explore the differences between Azure and OpenAI Studio.

00:00:00 Learn how to use LangChain with OpenAI in Azure. Create a new deployment in Azure Open AI and get started with using OpenAI API through LangChain.

šŸ”‘ OpenAI can be accessed through the OpenAI API directly or via the Azure version of OpenAI's API.

šŸ’» To get started with Azure OpenAI in LangChain, go to portal.azure.com and create a subscription. Then, create a new deployment in Azure OpenAI.

šŸš€ By following these steps, you can effectively use LangChain with OpenAI in Azure to access the power of OpenAI's API.

00:01:24 Learn how to set up Azure OpenAI in LangChain and deploy resources for a YouTube demo with network security settings.

šŸ”‘ To get started with Azure OpenAI in LangChain, you need to create a resource group and set up security networks.

šŸ› ļø Once the deployment is complete, you can find the new resource in Azure OpenAI and obtain the endpoint.

šŸ“ Using the endpoint, you can access the Azure OpenAI in LangChain through the notebook.

00:02:49 Learn how to use Azure OpenAI in LangChain by setting up the API base, version, and key. Explore the differences between Azure and default OpenAI Studio.

šŸ“ The video demonstrates how to set up the Azure OpenAI API base and version.

šŸ”‘ The process involves obtaining the OpenAI API key and setting it in the code.

šŸŒ The video highlights the main differences between the default OpenAI version and the Azure version.

00:04:14 Learn how to create a new deployment in Azure OpenAI LangChain and connect to it using the deployment name 'chat endpoint'.

šŸ“ In Azure OpenAI, you need to create a deployment for each model you want to use.

šŸ”§ To create a deployment, choose a model and specify a unique deployment name.

āŒØļø Update the deployment name in the code to connect to the desired deployment.

00:05:40 A tutorial on deploying a chat model in Azure OpenAI using LangChain, including initializing the model and appending AI messages.

šŸ”§ Deployment of the chat model requires some waiting time for it to work.

šŸ’¬ The chat model uses a combination of human messages and AI messages to create a chat log.

ā“ The model can't answer questions about certain topics, like cheese, because it doesn't understand them.

00:07:04 The video explores how Azure OpenAI in LangChain incorporates conversational history to provide interpretations of the meaning of life, using the example of existentialism.

šŸ“š The chat model relies on previous messages to understand the context of the query.

šŸ’” An example of an interpretation of the meaning of life is found within the philosophy of existentialism.

šŸš« The chat model is unable to answer simple questions like the color of cheese.

00:08:27 This video demonstrates how to use Azure OpenAI in LangChain. It showcases the successful integration and offers useful information. Watch for a helpful tutorial!

šŸ”‘ The video explains the use of Azure's OpenAI offering instead of the typical Open AI API endpoints.

šŸ“± The speaker demonstrates that everything is functioning properly with the Azure OpenAI integration.

šŸ’” The video concludes by expressing gratitude and anticipation for future content.

Summary of a video "Azure OpenAI in LangChain: Getting Started" by James Briggs on YouTube.

Chat with any YouTube video

ChatTube - Chat with any YouTube video | Product Hunt