Create a note-to-task converter

A note-to-task converter transforms informal notes or text into structured tasks, typically including components like action items, deadlines, assignees, and priorities.

Here’s a simple note-to-task converter in Python that uses basic natural language processing. It extracts tasks from notes by identifying action verbs and structuring them into a task list.

Python Code: Note-to-Task Converter

python
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import re
from datetime import datetime
import spacy

# Load spaCy English model
nlp = spacy.load("en_core_web_sm")

# Define common action verbs (can be expanded)
ACTION_VERBS = {"create", "call", "email", "write", "schedule", "meet", "plan", "update", "fix", "review", "send", "complete", "organize"}

def extract_tasks_from_note(note):
    doc = nlp(note)
    tasks = []

    for sent in doc.sents:
        sent_text = sent.text.strip()
        for token in sent:
            if token.lemma_ in ACTION_VERBS and token.pos_ == "VERB":
                task = {
                    "description": sent_text,
                    "action": token.lemma_,
                    "due_date": extract_due_date(sent_text),
                    "priority": extract_priority(sent_text)
                }
                tasks.append(task)
                break  # Only extract first verb per sentence
    return tasks

def extract_due_date(text):
    date_patterns = [
        r"by (w+ d{1,2}(?:st|nd|rd|th)?)",     # e.g., by June 10th
        r"by (d{1,2}/d{1,2}/d{2,4})",          # e.g., by 06/10/2024
        r"on (w+ d{1,2})",                      # e.g., on July 15
        r"tomorrow|today|next week"
    ]
    for pattern in date_patterns:
        match = re.search(pattern, text.lower())
        if match:
            return match.group(0)
    return None

def extract_priority(text):
    if "urgent" in text.lower() or "asap" in text.lower():
        return "High"
    elif "low priority" in text.lower():
        return "Low"
    return "Normal"

# Example usage
note = """
Call John about the budget report by June 10th.
Email Sarah the updated roadmap tomorrow.
Schedule a team meeting next week.
Fix the login issue ASAP.
Organize files for the client presentation.
"""

tasks = extract_tasks_from_note(note)

for i, task in enumerate(tasks, 1):
    print(f"Task {i}:")
    print(f"  Description: {task['description']}")
    print(f"  Action: {task['action']}")
    print(f"  Due Date: {task['due_date']}")
    print(f"  Priority: {task['priority']}n")

This script uses spaCy for NLP and regex for simple date/priority detection. It can be extended to integrate with task management tools like Trello, Notion, or Todoist via their APIs.

Would you like this as a web app or integrated with a task manager?