Similar to traditional code notebooks like Jupyter Notebooks, but with a seamless integration with large-language models. Code when you want, skip when you don't. Export notebooks for portability.
A playground for ideas - LLM prompts in code notebooks
Similar to traditional code notebooks like Jupyter Notebooks, but with a seamless integration with large-language models. Code when you want, skip when you don't. Export notebooks for portability.
This is a great idea. I've spent so much time changing prompts in the local version of my app, when really it'd be far quicker and easier to use a notebok like this. Congrats on the launch!
Hello folks! An idea recently struck me and I wanted to try it out. LLMs today are great with dealing with data and understanding natural instructions. What if I could combine them in a code notebook? A notebook where you can code as well as write LLM prompts that operate on the same set of data - a seamless transition between regular coding and natural language instructions. Code when you want the power of text-based code, offload it to LLMs when you don't feel like it! Try Slate here: https://
Seamless integration of large-language models, this notebook offers flexibility like never before. Code on your terms and export for easy sharing—simplicity and power combined. Congrats on your launch Product
Hello there! If you like reading written posts, I also noted down my thoughts in this post: https://mohitkarekar.com/posts/2... Have fun using and reading!
Categories come from the product's launch tags. Most products appear in 2-3 categories. The primary category is listed first.
The scores reflect launch-period engagement. Historical data is preserved and doesn't change retroactively. The build date at the bottom shows when the index was last refreshed.
Check the similar products section on this page, or browse the category pages linked in the tags above. Each category page shows all products for a given year, sorted by engagement.
A measure of community engagement at launch. Higher means more people noticed and interacted with the product. It's a traction signal, not a quality rating.