🦥 SlothTab: Let Local AI Handle the Boring Stuff
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady 🦥 SlothTab: Let Local AI Handle the Boring Stuff What I Built I built SlothTab , a local-first AI assistant for people who keep saying: "I'll organize it later." We all have that one folder. Downloads full of: IMG_8273.png final_final2.pdf document123.pdf random screenshots lecture notes assignments…
This submission for the Hacktoberfest Open-Source AI Challenge focuses on creating SlothTab, a local-first AI assistant designed to handle mundane tasks such as organizing files. Users often have folders filled with disorganized documents like IMG_8273.png, final_final2.pdf, document123.pdf, and receipt.jpg. SlothTab allows users to drop these files into an inbox where local AI can categorize, summarize, and organize them efficiently.
The core functionality of SlothTab involves categorizing files, generating meaningful names, summarizing documents, creating tags, recommending where to store files, detecting duplicates, ensuring file safety, undoing file operations, and processing high-confidence files. Users can drop multiple files into SlothTab instead of manually organizing them, saving time and effort.
The application offers a separation between the AI and filesystem operations to enhance security and privacy. Users can choose from various local AI models such as LM Studio, Ollama, or any OpenAI-compatible local endpoint. This flexibility allows users to experiment with different models based on their hardware and workload requirements.
SlothTab is built on a local-first architecture, utilizing React + TypeScript for the frontend, Python + FastAPI for the backend, and SQLite for local persistence. Document processing occurs locally before sending relevant content to the chosen local model. The AI generates structured recommendations for file organization before the application performs any file operations.
One of the main advantages of SlothTab is its privacy and offline capabilities. Files never leave the user's machine, ensuring data security. The application can work without an internet connection, making organization possible even without connectivity. Moreover, users have the freedom to customize the AI's behavior, including changing categories, confidence thresholds, or even swapping models altogether.
The main goal of SlothTab is to automate the tedious tasks that often lead to procrastination. Instead of manually finding, opening, understanding, and moving files, users can simply drop their files into SlothTab. The AI takes care of the rest, and users can review the suggested actions before confirming the changes. This reduces the amount of effort required to keep digital spaces organized.
In summary, SlothTab leverages local AI to streamline file organization, offering privacy, offline functionality, and customization options. It aims to make the often tedious task of file management effortless, allowing users to spend less time on routine tasks and more on what truly matters.
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