DEV Community: JAY SAWWALAKHE

LazyFile: An AI File Organizer for Lazy People

JAY SAWWALAKHE — Fri, 23 Oct 2026 13:55:53 +0000

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady.

What I Built

I built LazyFile, a small AI tool for people who are too lazy to organize their files.

My Downloads folder usually becomes a mess with PDFs, images, notes, projects, resumes and random files.

Instead of spending time moving everything into different folders, I wanted something that could just do it for me.

With LazyFile, I select a folder and the AI checks the files and suggests where they should go.

Demo

How I Built It

I built LazyFile using Python and FastAPI, with a simple frontend.

The important part is the open-source AI model that is used to understand the files and decide which category they belong to.

I wanted to keep the project simple and useful instead of adding a lot of features.

Why Does Open Innovation Matter?

I wanted the AI part of LazyFile to be based on an open model instead of depending on a paid AI API.

Files can contain personal information, so keeping the processing local is also useful.

Using an open model gives me more control. I can try different models, change the categories and improve the project without being locked into one company's API.

It also means I can experiment with the project without paying for every AI request.

The Lazy Payoff

The whole idea of this project is simple:

So I built something that can do most of the boring part for me.

Instead of manually opening folders and moving files one by one, LazyFile can sort them in a few clicks.

I also want to improve it later so it can automatically watch a Downloads folder and organize new files when they arrive.

BirdLens: Side Hustle

JAY SAWWALAKHE — Fri, 16 Oct 2026 08:19:48 +0000

What I Built
I built BirdLens, a simple AI tool that identifies birds from a photo.

The idea came from a simple problem: you see a bird while travelling or walking outside, but you don't know what it is.

With BirdLens, you can upload a bird photo and get the predicted species along with useful information about it.

Demo

How I Built It
I used:

React.js for the frontend
Python + FastAPI for the backend
Hugging Face for the AI model
An open-weight bird classification model for identifying the bird
Why Open-Source AI?
I wanted the AI part of the project to be something I could actually experiment with and control.

Instead of depending completely on a paid vision API, I can use an open model, change it, try other models, and potentially run it locally.

This can also help keep the cost low and gives me more control over how BirdLens works.

For me, that's the main reason open-source AI is interesting: I can build on top of it instead of only using it as a service.

What's Next?
I want to improve the accuracy, add more bird species, improve the UI, and eventually explore offline/local bird identification.

This started as a small project, but I'd like to see if it can become something useful for bird watchers, students, travellers, and nature lovers.

Thanks for checking out BirdLens! 🐦

BirdLens: An Open-Source AI Bird Identifier for Outdoor Explorers

JAY SAWWALAKHE — Fri, 16 Oct 2026 08:14:49 +0000

What I Built

I built BirdLens, a simple AI tool that identifies birds from a photo.

The idea came from a simple problem: you see a bird while travelling or walking outside, but you don't know what it is.

With BirdLens, you can upload a bird photo and get the predicted species along with useful information about it.

Demo

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How I Built It

I used:

React.js for the frontend
Python + FastAPI for the backend
Hugging Face for the AI model
An open-weight bird classification model for identifying the bird

Why Open-Source AI?

I wanted the AI part of the project to be something I could actually experiment with and control.

Instead of depending completely on a paid vision API, I can use an open model, change it, try other models, and potentially run it locally.

This can also help keep the cost low and gives me more control over how BirdLens works.

For me, that's the main reason open-source AI is interesting: I can build on top of it instead of only using it as a service.

What's Next?

I want to improve the accuracy, add more bird species, improve the UI, and eventually explore offline/local bird identification.

This started as a small project, but I'd like to see if it can become something useful for bird watchers, students, travellers, and nature lovers.

Thanks for checking out BirdLens! 🐦

BirdLens- App

JAY SAWWALAKHE — Fri, 09 Oct 2026 08:06:54 +0000

BirdLens

This is a submission for the Hacktoberfest Open-Source AI Challenge

What I Built

I built BirdLens, a simple bird identification app that encourages people to go outside and explore nature.

The idea is simple: take a photo of a bird while you are outside, upload it to BirdLens, and the app tries to identify the bird. It then shows some basic information about it.

Instead of sitting inside and searching about birds on the internet, the goal is to go outside, find a bird, take a photo, and learn about it.

The app is mainly for people who are interested in birds, nature, photography, or just want a small reason to spend some time outdoors.

Demo: 1-

Code

GitHub:

The project contains the frontend and backend code, along with the AI part used for bird identification.

How I Built It

I built BirdLens using:

React.js for the frontend
Python and FastAPI for the backend
An open-source AI model for bird identification
API/backend logic to process the uploaded image and return the result

The main flow is:

Take or upload a bird photo → AI identifies the bird → BirdLens shows the bird information.

I wanted to keep the project simple so that it can be improved later with more bird species, better information, and more features.

Why Does Open Innovation Matter?

For this project, open-source AI made it possible for me to experiment with an AI model without building everything from zero.

I could learn how an image classification model works and connect it to my own application. It also means other developers can look at the project, improve it, add new features, or use the idea for their own projects.

For me, open source is also a good way to learn by building real projects instead of only following tutorials.

Diet Plan App

JAY SAWWALAKHE — Sun, 04 Oct 2026 08:55:11 +0000

What I Built?

I built Safe Plate for my roommate, Mayur, who is allergic to nuts.

Whenever we cook together, we spend a long time reading labels and googling whether a recipe is safe. Most recipe sites also don't know what's in our kitchen.

With Safe Plate, you tick the dietary needs, type the ingredients you have (like "rice, tomato, spinach, onion"), and get 3 recipes. If a recipe has anything unsafe, like almonds or peanuts, the app removes it automatically.

Demo-

Example: I selected "Nut allergy", entered "rice, tomato, spinach, onion", and got 3 recipes. The page also showed "1 recipe(s) removed by the safety filter" because one suggestion had cashews.

GitHub: https://github.com/JAYMS07/Diet-App.git[](https://github.com/JAYMS07/Diet-App.git)

How I Built It
Frontend: HTML, CSS, and JavaScript
Backend: Node.js and Express
AI: Gemma 3 running locally with Ollama

The AI suggests the recipes. Then my code checks every ingredient against a list of banned foods (for nuts: almond, cashew, peanut, walnut, and more) and removes any recipe that matches. I didn't want to trust the AI alone with allergies, because it can make mistakes.

Why Does Open Innovation Matter?

Allergy and health details are private. Because the model runs on my own laptop, Riya's information never goes to anyone else's server. It's also free, with no API key.

Since the project is open source, anyone can make it safer by adding more foods to the banned list, like shellfish, soy or local ingredient names.