Craig Dunn

Principal SW Engineer, Surface Duo Developer Experience

Craig works on the Surface Duo Developer Experience team, where he enjoys writing cross-platform code for Android using a variety of tools including the web, React Native, Flutter, Unity, and Xamarin.

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Jetchat with OpenAI on Android

Hello prompt engineers, The last three blogs have been about exploring the OpenAI API completion, edit, and image endpoints from Android, using HttpClient and crafting JSON requests and responses. This post is about implementing the chat API in an Android app, using the open-source client library openai-kotlin on GitHub. The library...

OpenAI API endpoints

Hello prompt engineers, Last week we implemented OpenAI APIs in a basic text editor sample to add features like spell checking. We used the ‘default’ completions endpoint which accepts a prompt string and returns the result, but there are other APIs that are suited to different purposes. For last week’s example, there is a better ...

ChatGPT on Android with OpenAI

Hello prompt engineers, OpenAI has been in the news a lot recently, with the release of ChatGPT 4 and the integration of Large Language Model (LLM)-driven features into a variety of products and services including Bing, GitHub, and Microsoft 365 applications. Inspired by Syncfusion’s blog post on adding ChatGPT to their ....

OpenAI Android developer assistance

Hello budding prompt engineers, Many developers are already getting assistance from GitHub Copilot completing code and more recently the conversational additions to GitHub pull requests, documentation, and the CLI. In this post we’ll look at some of the ways that Android developers can take advantage of OpenAI- and ChatGPT-powered...

Built-in model pre-processing with ONNX

Hello Android developers, Previously we looked at how to pre-process image inputs for an ONNX model using Kotlin. It’s useful to understand this process because the principles apply to any model that you wish to use. On the other hand, having to write boilerplate code for input processing can be tedious – it also means there’s...

Bringing ONNX models to Android

Hello Android developers, One of the advantages of the ONNX runtime is the ability to run locally on a variety of devices, including mobile devices. This means that your users get fast response times, but also comes with the need to respect mobile device limitations such as app size and the ability to support performance ...

ONNX runtime inputs and outputs

Hello Android developers, Last week we got an ONNX runtime demo running on Android, which classified the subject of images being streamed from the device’s camera. Setup required downloading a pre-trained model and adding it to the sample app on GitHub. This week we’re going to look into the details of preparing inputs for the ...

On-device machine learning with ONNX

Hello Android developers, This week we’re going to get started with on-device machine learning using the ONNX Runtime and check out an Android sample that identifies the objects using the camera video stream. What is ONNX? ONNX stands for Open Neural Network eXchange and is an open-source format for AI models. ONNX supports...

Happy Holidays 2022

Hello Android developers, Inspired by the growth of AI and its role in products like GitHub’s Copilot this year, we asked ChatGPT to “propose some applications for Surface Duo owners to use over the holidays”… One possible application for Surface Duo owners to use over the holidays could be to use the dual screens ...

Drag and drop with AndroidX

Hello Android developers, Foldable and large-screen devices are great for multi-tasking – you can position two apps side-by-side to compare data or just do two things at once! The other benefit of side-by-side apps is the ability to drag and drop content between them, whether the apps are across screens on a dual-screen device, or...

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