LifeAdmin-AI: Turning Documents into Actionable Tasks with Local AI

Description and use

LifeAdmin‑AI automatically extracts tasks and deadlines from notices, delivering structured JSON with model validation and uncertainty flags.

Problem

Users manually read notices to extract tasks and deadlines, risking missed deadlines.

Outcome

LifeAdmin-AI automates extraction of actionable items from notices, producing structured JSON that includes tasks, deadlines, priorities, and evidence, with Python validation to surface uncertainties.

Workflow

• Upload PDF/TXT or paste text into Streamlit UI
• Ollama runs Gemma 3 locally to extract text and generate structured JSON
• Python validates JSON structure and flags uncertainties
• Display tasks, deadlines, priorities, and evidence excerpts to the user

Evidence

LifeAdmin-AI is a document assistant designed to turn notices and other text documents into actionable tasks.

Source

Instead of manually reading an entire notice and trying to remember every deadline, users can upload a PDF or TXT file, or paste text, and get a structured summary of the tasks, deadlines, priorities, and supporting evidence.

Source

The application asks the model to return structured JSON containing a summary, tasks, and uncertainties. Python validation checks the response structure before the results are displayed.

Source

Running the model locally means the application does not need a hosted model API for its current demo setup.

Source