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Shameless plug. I have a VS Code extension that's very nearly ready.
Codespin CLI tools (ready to use): https://github.com/codespin-ai/codespin
VS Code extension for the CLI tool (soon): https://www.youtube.com/watch?v=2TJqosFmkao
I'll do a Show HN in a week or two.
Maybe I am bit dim, but how one can choose GPT-4 Turbo? Is this available from https://chat.openai.com/ ?
FWIW, I agree with you that each model has its own personality and that models may do better or worse on different kinds of coding tasks. Aider leans into both of these concepts.
The GPT-4 Turbo models have a lazy coding personality, and I spent months of effort figuring out how to both measure and reduce that laziness. This resulted in aider supporting "unified diffs" as a code editing format to reduce such laziness by 3X [0] and the aider refactoring benchmark as a way to quantify these benefits [1].
The benchmark results I just shared about GPT-4 Turbo with Vision cover both smaller, toy coding problems [2] as well as larger edits to larger source files [3]. The new model slightly underperforms on smaller coding tasks, and significantly underperforms on the larger edits where laziness is often a culprit.
[0] https://aider.chat/2023/12/21/unified-diffs.html
[1] https://github.com/paul-gauthier/refactor-benchmark
[2] https://aider.chat/2024/04/09/gpt-4-turbo.html#code-editing-...
[3] https://aider.chat/2024/04/09/gpt-4-turbo.html#lazy-coding
The ongoing model anchoring/grounding issue likely affects all GPT-4 checkpoints/variants, but is most prominent with the latest "gpt-4-turbo-2024-04-09" variant due to its most recent cutoff date, might imply deeper issues with the current model architecture, or at least how it's been updated:
https://github.com/openai/openai-python/issues/1310
See also the original thread on OpenAI's developer forums (linked on the GitHub issue) with confirmations from others.
A test code snippet is included in the GitHub issue to A/B test the problem yourself with your own questions if need be.