š OpenAI can be accessed through the OpenAI API directly or via the Azure version of OpenAI's API.
š» 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.
š By following these steps, you can effectively use LangChain with OpenAI in Azure to access the power of OpenAI's API.
š To get started with Azure OpenAI in LangChain, you need to create a resource group and set up security networks.
š ļø Once the deployment is complete, you can find the new resource in Azure OpenAI and obtain the endpoint.
š Using the endpoint, you can access the Azure OpenAI in LangChain through the notebook.
š The video demonstrates how to set up the Azure OpenAI API base and version.
š The process involves obtaining the OpenAI API key and setting it in the code.
š The video highlights the main differences between the default OpenAI version and the Azure version.
š In Azure OpenAI, you need to create a deployment for each model you want to use.
š§ To create a deployment, choose a model and specify a unique deployment name.
āØļø Update the deployment name in the code to connect to the desired deployment.
š§ Deployment of the chat model requires some waiting time for it to work.
š¬ 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.
š The chat model relies on previous messages to understand the context of the query.
š” An example of an interpretation of the meaning of life is found within the philosophy of existentialism.
š« The chat model is unable to answer simple questions like the color of cheese.
š The video explains the use of Azure's OpenAI offering instead of the typical Open AI API endpoints.
š± The speaker demonstrates that everything is functioning properly with the Azure OpenAI integration.
š” The video concludes by expressing gratitude and anticipation for future content.