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Arjun Sharma
Arjun Sharma

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Sorta-AI : An AI Downloads Butler

Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady Submission 🦥

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady
My Downloads folder can get messy pretty quickly, so for Hactoberfest Week 3 challenge,I decided to build something that could help me organise it.

I made Sorta ,a small AI-powered app that suggests where a downloaded file could belong based on its filename.

What I Built

Sorta is built with Python, Streamlit, Ollama, and Gemma 3 1B.

I enter or select a filename, and Gemma suggests a folder category. I can review the suggestion in the app before deciding what to do with the file.

This is an early prototype: Sorta currently previews folder suggestions. It does not automatically move files, and its undo feature is not implemented yet.

Instead of having to think through a folder category for every download, Sorta gives me a quick suggestion to review. I haven’t measured a specific time saving yet, but I wanted to explore how AI could make this small, repetitive task easier.

Github Repository:https://github.com/codesnippet-lab/Sorta-AI

Code

GitHub logo codesnippet-lab / Sorta-AI

A local AI-powered downloads organizer that uses Gemma to suggest folders for your files—without sending filenames to a cloud AI.

Sorta — AI Downloads Butler 🪄

Sorta is a file-organization assistant that uses a locally running Gemma model to suggest folders for your files. You can review the suggestions before taking any action.

Features

  • Upload multiple files in a Streamlit interface
  • Use local Gemma AI through Ollama to suggest folders
  • Preview the proposed organization
  • Keep the user in control: this prototype does not move, rename, or delete files

Built with

  • Python
  • Streamlit
  • Ollama
  • Gemma 3 1B

Run locally

1. Install Ollama

Install Ollama for your operating system: https://ollama.com/download

2. Download Gemma

Open a terminal and run:

ollama pull gemma3:1b
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Ensure Ollama is running.

3. Set up Sorta

From the project folder:

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
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4. Launch the app

streamlit run app.py
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Open the local URL printed in your terminal.

Privacy and safety

Sorta sends filenames to the locally running Gemma model to generate…

How I Built It

I used Gemma 3 1B through Ollama, with the model running on my own computer. For this prototype, the filename is sent to the local model rather than a hosted AI API.

Using an open model gave me a chance to experiment with AI locally and connect it to an app I built myself.

Why Does Open Innovation Matter?

I used Gemma 3 1B through Ollama, with the model running on my own computer. For this prototype, the filename is sent to the local model rather than a hosted AI API.

Using an open model gave me a chance to experiment with AI locally and connect it to an app I built myself.

I used Gemma 3 1B through Ollama, with the model running on my own computer. For this prototype, the filename is sent to the local model rather than a hosted AI API.

Using an open model gave me a chance to experiment with AI locally and connect it to an app I built myself.

My Agent Session

The Lazy Payoff

Prize Categories

devchallenge #hf26challenge

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