Search Results for "virtual test shell"

...It blends knowledge of your local workspace with command-line context to suggest commands, explain flags, and scaffold files or workflows. The tool aims to shorten the gap between intent and action by letting you request operations like creating a test, refactoring a function, or drafting a Dockerfile without leaving the shell. It also integrates with common developer flows, offering autocompletion and step-by-step plans before running potentially destructive actions. The CLI targets macOS and Linux and is designed to coexist with standard tools rather than replace them, acting as a smart layer on top. ...

...It uses a Mixture-of-Experts (MoE) architecture with 230 billion total parameters but only 10 billion activated per token, giving it the behavior of a very large model at a fraction of the runtime cost. The model is tuned for end-to-end developer flows such as multi-file edits, compile–run–fix loops, and test-validated repairs across real repositories and diverse programming languages. It is also optimized for multi-step agent tasks, planning and executing long toolchains that span shell commands, browsers, retrieval systems, and code runners. Benchmarks show that it achieves highly competitive scores on a wide range of intelligence and agent benchmarks, including SWE-Bench variants, Terminal-Bench, BrowseComp, GAIA, and several long-context reasoning suites.

GitHub Copilot CLI is a command-line interface tool. It brings AI-powered coding assistance directly into your terminal. GitHub Copilot CLI allows you to build, debug, refactor, and understand code via natural language conversations. You can have these conversations within the Active Directory. It integrates tightly with your GitHub context—repositories, issues, pull requests. The Copilot can leverage repository context when making suggestions. The tool is currently in public preview and is...

The main Kite repo (originally kiteco/kiteco) was intended for private use. It has been lightly adapted for publication here by replacing private information with XXXXXXX. As a result, many components here may not work out of the box. We used a variety of infrastructure, on a mix of cloud platforms, depending on what was most economical, though it was mostly on AWS. You should be able to develop, build, and test Kite entirely on your local machine. However, we do have cloud instances & VMs...