This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady.
What I Built
LazyDesk AI is a Python and Streamlit application designed to make everyday tasks easier using local AI. I worked on adding a “Break It Down” mode that turns a large task into smaller, actionable steps.
The goal is to make overwhelming tasks feel easier to start, one small step at a time.
Demo
The feature is currently under development. I have not yet verified a working demo.
Code
Original repository: https://github.com/prarthanas9917/lazydesk-ai
How I Built It
The project uses Python, Streamlit, and Ollama. I extended the task selection interface and added instructions intended to guide the local model to produce 3–7 manageable steps.
Testing and further improvements are still needed.
Why Does Open Innovation Matter?
Open-source AI lets developers learn from existing projects, adapt tools to their needs, and experiment with models that can run locally. Local inference can help keep prompts on a user's own machine instead of sending them to a third-party AI provider.
The Lazy Payoff
The idea is simple: spend less time figuring out where to start and more time taking the first small step. The intended benefit is reducing the effort needed to organize a large task.
Project Status
This is an early contribution. The new mode has been added to the code, but I still need to verify the feature, test the local model integration, and complete the contribution workflow.
Top comments (0)