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So if you had 3 markdown cells and 3 python cells, I would design the tool to pull all the content out of those cells and present it (sans all that ipynb markup

So if you had 3 markdown cells and 3 python cells, I would design the tool to pull all the content out of those cells and present it (sans all that ipynb markup, just contents, probably in markdown) to the model as the full context for every edit you want to make. So the tool would need to know how to transform a given notebook into a collection of markdown/python cells which it would present to the model to make edits. The model would need to return updated cells in the same format, and the tool would update the cells in the document (or just replace them entire with new cells from the response). I would be fine with this just blowing away all previous evaluation results. Do you think that approach would work? Not sure if I'm misunderstanding the issue you're describing and I recognize it is likely much messier than I imagine.

prasoonds 2y ago
This is something we're planning on doing - just generate a large bit of text with markdown text and code in the middle. This is actually how the newer models already generate code - with the only difference being there's only one code block. Via the use of <thinking></thinking> blocks, it's pretty straightforward to get the the model to evaluate it's own work and plan the next steps (basically chain of thought) but then you can filter out the <thinking> block in the final output. The last trick to making this actually work is to give the AI model evaluation power - make it be able to run certain inspection code to evaluate its decisions so far and feel that evaluation to the next set of steps. Combining all of this, it's very possible to convert an AI chat into a multi-step markdown + code notebook that actually works.