SlothFlow: An Open-Source AI-Powered Task Planner for Effortless Productivity
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady.
What I Built
Meet SlothFlow — a simple, AI-powered task planner inspired by one of nature's most relaxed creatures: the sloth! 🌿
We all have days when our to-do lists feel overwhelming. Between college assignments, coding projects, deadlines, and everyday responsibilities, even deciding where to start can take too much energy.
SlothFlow aims to solve this problem.
Users can enter their messy thoughts, tasks, and reminders into one text box. SlothFlow uses an open-weight AI model to turn that brain dump into a short, manageable action plan.
Key Features
- AI-powered planning: Turns a messy to-do list into smaller, clearer steps.
- Privacy-focused: Processes your text in the browser without sending it to a SlothFlow backend.
- Open-weight AI: Uses FLAN-T5 Small through Transformers.js.
- Simple task tracking: Check off completed tasks and copy your plan.
- No paid AI API: No paid inference API or usage charges are required.
The goal is simple: spend less energy organizing your tasks and more energy actually doing them.
Demo
Live Website: [https://er-simran-jaiswal.github.io/SlothFlow-website-files/]
Project Poster: See the attached SlothFlow poster.
The website is designed with a calming sage-green and cream theme to make planning feel less stressful and more approachable.
The live demo will be available after deployment.
Code
GitHub Repository: [ https://er-simran-jaiswal.github.io/SlothFlow-website-files]
The project is built with HTML, CSS, and JavaScript, with Transformers.js providing access to the open-weight AI model.
The repository includes the website files, instructions for running the project locally, and an MIT license.
How I Built It
I built SlothFlow using:
- HTML for the website structure.
- CSS for the responsive layout and calming visual design.
- JavaScript for task input, model inference, checklist generation, and interactions.
- Transformers.js to run an AI model directly in the browser.
- FLAN-T5 Small as the open-weight language model.
When a user enters a brain dump, the application sends the text to the model running in their browser and asks it to produce a short action plan.
The application also includes a basic checklist fallback if the AI model cannot load.
The first model download requires an internet connection. Afterward, browser caching may help avoid downloading the files again, although fully offline operation is not guaranteed.
Why Does Open Innovation Matter?
For SlothFlow, open innovation is about giving users more control over their tools, their data, and their costs.
1. More privacy
The application processes user input in the browser rather than sending it to a SlothFlow backend or a paid AI inference API. This gives users greater control over their personal notes.
2. Lower running costs
There are no paid AI API calls. This makes the project easier to experiment with and potentially maintain without usage-based inference costs.
3. Freedom to experiment
Using an open-weight model gives developers more flexibility to modify prompts, experiment with different models, and adapt the application to their needs.
4. Learning through open technology
As a beginner exploring AI and machine learning, I wanted to build something practical while learning how an AI model can be integrated into a real application.
Open-source tools made that exploration more accessible.
For this project, open innovation is not just about making the source code available. It is also about making AI-powered tools more approachable, adaptable, and affordable.
The Lazy Payoff 🦥
Imagine having ten tasks in your head and no idea where to begin.
Instead of spending extra time organizing everything manually, you can enter your tasks in one place and let SlothFlow help you decide on a manageable starting point.
The intended benefit is less planning friction, fewer overwhelming lists, and a clearer next step.
I have built the first version of the application, and the next step is to test the AI-generated plans with real task lists and improve the results based on what works.
Prize Categories
- Open-Source AI
- Open-Weight Models
- Local / Browser-Based AI
Please confirm the official challenge's eligible prize categories before submitting.
Sometimes productivity isn't about doing more. It's about making the next step easier.
Slow down. Make a plan. Keep moving. 🌿
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