caxai

Cal AI: An AI Powered Personal ToDo Web App

A simple Gen AI Powered AI First Microsrvice and Frontend Showcasing the Architecture for API forst Modern Web.

• Layered Architecture Development
• Gen AI Powered API Microservice & NextJS14 Frontend
• Serverless Posgtgress Database Powered with SQL ALCHEMY ORM
• Pytests for Unit Tests, API Tests and End to End Tests

An End to End Cloud GenAI Project.

Starting from a simple todo app here I will be adding all features I wanted in any task mangement web app I have tried.

This is more like a project build for personal use and open sourced for others to learn and maybe try using it.

• A Notion like Weekly to do list where I can add each week todos

  • At week end the sheet is deleted while the todos are saved in database.
  • AI can talk or inform in text about my daily tasks
  • At week end ana analysization about what I did and a segregation showing
    1. Time Spend on learning
    2. Recursive Tasks etc…

• Whatsapp, Skype or Slack message/notifications about daily work

Features To Add in the future

Adaptive Task Prioritization:

• Problem: Users struggle with constantly changing priorities and task overload.
• AI Solution: Implement an AI algorithm that learns from the user’s task completion patterns and adjusts task priorities accordingly. For instance, if a user consistently prioritizes work-related tasks in the mornings, the app could automatically adjust future task priorities. Predictive Scheduling and Reminders:

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• Problem: Users often underestimate the time required for tasks or forget deadlines.
• AI Solution: AI could analyze past task completion times and suggest realistic timeframes for new tasks. It could also anticipate and remind users of recurring tasks based on historical data. Integration with Other Tools:

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• Problem: Current apps often exist in isolation, not syncing well with other productivity tools.
• AI Solution: Develop AI capabilities to integrate and sync data with other apps (like calendars, emails) to provide a unified task management system. For example, AI can suggest to-do items from emails or meetings scheduled in the calendar. Context-Aware Suggestions:

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• Problem: Users receive generic task suggestions that might not align with their current context or needs.
• AI Solution: Utilize AI to offer context-aware suggestions, like recommending grocery shopping when the user is near a supermarket, based on location data and past behavior. Voice-Activated Controls:

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• Problem: Manual entry of tasks can be cumbersome.
• AI Solution: Implement sophisticated voice recognition to allow users to add tasks hands-free, enhancing accessibility and convenience.

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Run Migrations One Time Using Alembic

Reason: It’s recommended in SQLAlchemcy documentation to use alembic for db migrations in big projects.

We are using Neon Serverless Postgress Database and SQL Alchemy ORM.

Run Migratiosn:

1. alembic init migrations

In alembic.ini rm the url here sqlalchemy.url =

In migrations/env.py import dotenv and then:

config = context.config

---------------- added code here -------------------------#

this will overwrite the ini-file sqlalchemy.url path

with the path given in the config of the main code

config.set_main_option("sqlalchemy.url", os.environ.get("DB_URL"))

Replace # target_metadata = None with

from app.data sqlalchemy_models
target_metadata = sqlalchemy_models.Base.metadata

Here I made fastapi_backend a module and then used an absolute import above.

2. alembic revision --autogenerate -m "Add Todos Table alembic upgrade head

Helpful Reference: https://ahmed-nafies.medium.com/fastapi-with-sqlalchemy-postgresql-and-alembic-and-of-course-docker-f2b7411ee396