Hello prompt engineers, We first introduced OpenAI chat functions with a weather service and then a time-based conference sessions query. Both of those examples work well for ‘point in time’ queries or questions about a static set of data (e.g., the conference schedule). But each time the JetchatAI app is opened, it has no recolle...
Hello prompt engineers, Last week’s post introduced the OpenAI chat function calling to implement a live weather response. This week, we’ll look at how to use function calling to enhance responses when using embeddings to retrieve data isn’t appropriate. The starting point will be the droidcon SF sample we’ve covered previously: F...
Hello prompt engineers, OpenAI recently announced a new feature – function calling – that makes it easier to extend the chat API with external data and functionality. This post will walk through the code to implement a “chat function” in the JetchatAI sample app (discussed in earlier posts). Following the function calling document...
Hello AI enthusiasts, This week, we’ll be talking about how you can use Azure Cognitive Services to enhance the types of inputs your Android AI scenarios can support. What makes an LLM multimodal? Popular LLMs like ChatGPT are trained on vast amounts of text from the internet. They accept text as input and provide text as output....
