Show HN: Magic Loops – Combine LLMs and code to create simple automations
15 by jumploops | 0 comments on Hacker News.
Howdy! We built this as an experiment in personal-programming, combining the best of LLMs and code to help automate tasks around you. I personally use it to track the tides and get notified when certain conditions are met, something that pure LLMs had trouble dealing with and pure code was often too brittle for. We created it after getting frustrated with the inability of LLMs to deal with numbers and the various hoops we had to jump through to make ChatGPT output repeatable. At the core, Magic Loops are just a series of "blocks" (JSON) that can be triggered with different inputs (email, time, webhook), then operate on those inputs using a combination of LLMs and code, and then output those results (email, text, webhook). Under the hood, the LLM calls are using GPT-4 via OpenAI and the code is run in sandboxed (no internet) Docker containers in AWS. You have full control over each step of the loop, but you can also create (or attempt to create) a Magic Loop by simply describing what you want. We use GPT-4 to break that request into feasible steps, and then create a Magic Loop scaffold. Of course, you should still validate the loop before publishing it! We've seen some neat use cases already: - "Text me when the tide is less than 1ft between 7am and 7pm at Fort Funston" - "Summarize an email using this format and forward it to this address" - "Text me every time our store does more than $1000/day in volume on Shopify" - "Take specific data from Cloudflare, format it, and send it to Mixpanel every hour" We hope you enjoy what's essentially an experiment at this point. If folks like the concept, we're thinking about open sourcing it so you can run the loops locally with the code runtimes you wish (rather than in our code runners). Let us know what you think, and more importantly, what you wish to build or automate! Cheers, Adam & Mihai
15 by jumploops | 0 comments on Hacker News.
Howdy! We built this as an experiment in personal-programming, combining the best of LLMs and code to help automate tasks around you. I personally use it to track the tides and get notified when certain conditions are met, something that pure LLMs had trouble dealing with and pure code was often too brittle for. We created it after getting frustrated with the inability of LLMs to deal with numbers and the various hoops we had to jump through to make ChatGPT output repeatable. At the core, Magic Loops are just a series of "blocks" (JSON) that can be triggered with different inputs (email, time, webhook), then operate on those inputs using a combination of LLMs and code, and then output those results (email, text, webhook). Under the hood, the LLM calls are using GPT-4 via OpenAI and the code is run in sandboxed (no internet) Docker containers in AWS. You have full control over each step of the loop, but you can also create (or attempt to create) a Magic Loop by simply describing what you want. We use GPT-4 to break that request into feasible steps, and then create a Magic Loop scaffold. Of course, you should still validate the loop before publishing it! We've seen some neat use cases already: - "Text me when the tide is less than 1ft between 7am and 7pm at Fort Funston" - "Summarize an email using this format and forward it to this address" - "Text me every time our store does more than $1000/day in volume on Shopify" - "Take specific data from Cloudflare, format it, and send it to Mixpanel every hour" We hope you enjoy what's essentially an experiment at this point. If folks like the concept, we're thinking about open sourcing it so you can run the loops locally with the code runtimes you wish (rather than in our code runners). Let us know what you think, and more importantly, what you wish to build or automate! Cheers, Adam & Mihai