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Nahida4479

@Nahida4479

Joined July 11th, 2026

  • 39Devlogs
  • 6Projects
  • 6Ships
  • 120Votes
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1h 25m 30s logged

Devlog 8

New

  • Added OpenRouter free models API support
  • The AI can use the Discord server’s custom emojis in its responses (emojis from the Discord cache)

Models (reminder)

All AI models are free and use free API keys (Groq, Gemini, HackClub, OpenRouter).

const geminiModels = ['gemini-2.5-flash', 'gemini-2.5-flash-lite']
const groqModels = ["openai/gpt-oss-120b", "openai/gpt-oss-20b", "qwen/qwen3.6-27b"]
const HackClubModels = ['meta-llama/llama-3.3-70b-instruct']
const visionModel = ["qwen/qwen3.6-27b", "qwen/qwen3.8-27b"]
const openroute = ["openrouter/free"]

Planned

I plan to continuously develop and improve this project.

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Ship Pending review

NevAI - Discord AI Bot

Hello everyone, I’ve finally finished my open-source Discord AI bot with some unique mechanics!

Features

  • Only the Discord server administrator can use /ai, /ai_settings, /language, and /logs.
  • The bot responds using the AI models listed below.
  • The bot supports vision models (image understanding).
  • Responses are limited to 1500 characters.
  • Pre-built Docker image available.
  • Custom success and error emoji.
  • The bot reacts with an emoji when responding in a Discord chat.
  • The server administrator can set a custom AI prompt.
  • Multi-language support (add your own language more info CONTRIBUTING.md)).
  • The bot saves the last 15 messages for chat context.
  • Live logs support (/logs command).

How to use?

You can try it on my Discord server: https://discord.gg/3BqyZMQ85V

Or run it locally (recommended if you plan to use it daily, since free AI APIs have rate limits).

Docker (pre-built image)

  1. Create a .env file
  2. docker pull ghcr.io/nahida4479/nevai:latest
  3. docker run --env-file .env ghcr.io/nahida4479/nevai:latest

AI models list

Gemini

  • gemini-2.5-flash
  • gemini-2.5-flash-lite

Groq

  • openai/gpt-oss-120b
  • openai/gpt-oss-20b

HackClub

  • meta-llama/llama-3.3-70b-instruct

Vision models

Groq

  • qwen/qwen3.6-27b
  • qwen/qwen3.8-27b

Finally

I’ve spent a lot of time on this project, so thanks for reading! Feedback, issues, and pull requests are always welcome - good luck with your own projects too!

  • 7 devlogs
  • 12h
Try project → See source code →
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1h 45m 3s logged

Devlog 7

New

  • Added CONTRIBUTING.md (how to add your language)
  • New /help command with a description of all commands
  • Finalized README.md with features, how to run it, etc.
  • Added /logs command with live bot logs (question and AI model)

Planned

I plan to ship this project.

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1h 58m 58s logged

Devlog 6

New

  • Added image support (vision, Qwen models)
  • Added AI response error handling
  • Added validation for Add custom AI reaction emoji (supports Discord emoji format)
  • Added .env example in README.md
  • Added MIT LICENSE on GitHub
  • Added base AI prompt with a character limit (1500 characters)

Planned

I plan to add a /logs command.

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2h 5m 29s logged

Devlog 5

New

  • New settings image
  • Changed /ai_settings panel design
  • Created 2 new bot emojis (success and failure)
  • Added Discord emoji format support in the Add custom AI reaction emoji panel
  • Added bot_name typing... indicator

Planned

I plan to add an embed AI response with an on/off option in /ai_settings.

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1h 31m 27s logged

Devlog 4

New

  • Created the bot’s profile image
  • Added the AI response system (with 15-message context history)
  • Created the /ai_settings panel with custom prompt and thinking emoji options
  • Extended the language files with new translation keys

Planned

I’m planning to add support for Discord’s custom emoji format in /ai_settings, and start working on a logs system showing the question asked and which AI model responded.

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2h 2m 17s logged

Devlog 3

New

  • Added multi-language support
  • Created /ai_settings panel
  • Added English and Polish language support
  • Added mention detection - the bot now checks if it was mentioned on the configured AI channel

Planned

I’m planning to connect the AI system to the bot’s replies and finish the custom prompt settings (via the modal opened from /ai_settings).

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1h 11m 2s logged

Devlog 2

New

  • Created the Dockerfile and .dockerignore
  • Set up a pre-built Docker image (built automatically via GitHub Actions)
  • Created the /ai slash command
  • Created save_data.js and a save system for the AI channel

Planned

I’m planning to create the bot’s profile picture and start working on getting AI responses inside Discord.

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1h 35m 3s logged

Devlog 1

New

  • Added 3 AI providers: Groq, Gemini, HackClub
  • Added 6 LLM models across those providers
  • Tested the connection with each provider

LLM models

Gemini API

gemini-2.5-flash, gemini-2.5-flash-lite

Groq API

openai/gpt-oss-120b, openai/gpt-oss-20b, qwen/qwen3.6-27b

HackClub API

meta-llama/llama-3.3-70b-instruct

Planned

I’m planning to integrate these models with the Discord bot

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Ship

WFC-ards is finished!

Hi everyone, I’ve finished my PHP web application with flashcards for learning. Create folders, add your own flashcards, and study them with an interactive interface.

How to use

Test it:

flashcards.nahida4479.org

Or run it locally with the pre-built Docker image:
docker pull ghcr.io/nahida4479/wfc-ards:latest
docker run -d -p 8000:8000 ghcr.io/nahida4479/wfc-ards:latest

How it works

  1. Create an account (your password is hashed!)
  2. Click “Add flashcards” in the top right corner
  3. Create a folder, then click on the folder name
  4. Add your flashcards (you can delete a flashcard by clicking the trash icon in the “Your flashcards” section)
  5. After saving a flashcard, click I finish to finish adding cards
  6. Click the flashcard panel to flip it, and click “Next” to move to the next one (once you’ve created more than one flashcard)

You can create unlimited folders, and switch between them using the “Your flashcards folder” panel on the left.

Summary

I spent a lot of time on this project since it was my first time working with PHP. My biggest struggle was CSS styling. Good luck with your own projects :)

  • 7 devlogs
  • 17h
  • 2.01x multiplier
  • 34 Stardust
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56m 2s logged

Devlog 7

New

  • Added a “Your flashcards folder” panel on the main page
  • Fully functional flashcard study system (question/answer card with flip animation, folder selection, Next/Previous navigation)
  • Pages now require login to access

Planned

I’m planning to ship my project.

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2h 31m 43s logged

Devlog 6

New

  • Created a Docker image for the app (PHP + MariaDB in one container)
  • Added a GitHub Actions workflow that builds the Docker image with buildx
  • Added the ability to create and delete flashcards within a folder
  • Added a live preview for the flashcard question and answer while typing
  • Added a “Your flashcards” list showing existing flashcards in the folder

Planned

I’m planning to update the styling of the main page (index.php).

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1h 26m 40s logged

Devlog 5

New

  • Added a “How to use” section
  • Cleaned up the CSS (reorganized and simplified the code)
  • Created the createflashcard.php file, with a query pulling the selected folder’s name

Challenges

Rebuilt the whole page layout using nested flexbox containers instead of the manual negative margins.

Planned

I’m planning to build the flashcard creation form for the selected folder.

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2h 12m 38s logged

Devlog 4

New

  • Finished the “Your Folders” GUI
  • Created the “Delete Folder” panel
  • New styling for the create and delete buttons

Challenges

Spent a while debugging why my delete panel wouldn’t stay hidden

Planned

I’m starting work on the flashcard creation panel with a live preview of the flashcard.

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2h 6m 8s logged

Devlog 3

New

  • Added a flashcard folder system (users can create folders to organize flashcards by subject)
  • Started working on the “Your Folders” GUI
  • Added a new user_id column to the subjects table, linked with a foreign key to users

Planned

I’m planning to finish the folder system.

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5h 39m 21s logged

Devlog 2

New

  • New users table in the database
  • Login and registration system with password hashing
  • Login and registration website panels
  • Login session system
  • Logout system
  • Mobile device support for login and registration panels
  • Login and registration error handling

Login/Registration System

I built my first login and registration system, based on PHP and a MySQL/MariaDB database. I used the password_hash function for user security. I also added $_SESSION support across the website, so the app remembers which user is logged in between pages. The registration system requires a minimum of 8 characters for the password.

Planned

I’m planning to style the header tag and build the flashcards panel. I also plan to add the ability to export flashcards.

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2h 15m 1s logged

Devlog 1

New

  • Planned work on the project
  • Created the MySQL database
  • Connected to the MySQL database
  • Created a temporary flashcard design
  • Added flashcard flip animation
  • Created the schema.sql file

Idea

I am planning to create a flashcard web app with support for mobile devices and desktop. I will use the MySQL/MariaDB database for the application. For the backend, I will use the PHP language.

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Ship

Hello everyone, I have finished my FFvert project. In this project I built a system based on ffmpeg, @imgly/background-removal-node, and youtube-dl-exec, which enables converting images and videos, removing image backgrounds, and downloading YouTube videos.


Conversion video system

For this system I use the ffmpeg package.

This system supports 6 video and 1 audio formats:

  • gif
  • mov
  • mp3
  • mp4
  • avi
  • mkv
  • wmv

The supported resolutions: 4K, 1440p, 1080p, 720p, 480p

I’m proud that the GIF format additionally generates a color palette for better color accuracy.

Conversion image system

This system is based on the ffmpeg package.

Supports 7 image formats:

  • png
  • jpg
  • webp
  • bmp
  • tiff
  • ico
  • qoi

Remove background system

This is a special option in the FFvert panel when you upload an image. The background removal system is based on the @imgly/background-removal-node package. The AI model isnet_fp16 is downloaded from IMG.LY servers and runs locally.

YouTube Downloader system

The YouTube Downloader is based on the youtube-dl-exec package. The file is downloaded and converted using FFmpeg for the user-selected format and resolution.

Supported 12 formats:

  • MP4
  • MP3
  • MOV
  • GIF
  • MKV
  • WEBM
  • AAC
  • M4A
  • FLAC
  • WAV
  • OPUS
  • VORBIS

The supported resolutions: 1440p, 1080p, 720p, 480p, 360p, 240p, 144p


How to use

You can try my project at:

convert.nahida4479.org

If you prefer to run it locally, I have 2 options for you :)

You can run the image using a pre-built Docker image.

docker pull ghcr.io/nahida4479/ffvert:latest
docker run -p 3003:3003 ghcr.io/nahida4479/ffvert:latest

or build it yourself

git clone https://github.com/Nahida4479/FFvert.git
cd FFvert
docker build -t ffvert .
docker run -p 3003:3003 ffvert

Summary

I spent a lot of time on this project and thoroughly enjoyed studying CSS and improving my JavaScript skills. I hope you like this project. Good luck with your own projects :)

  • 7 devlogs
  • 17h
  • 15.92x multiplier
  • 279 Stardust
Try project → See source code →
Open comments for this post

3h 41m 56s logged

Devlog 12

New

  • Built and published a Docker container on GitHub
  • Added a progress bar for YouTube Downloader
  • Disabled the OK button until the file is ready
  • Adjusted YouTube Downloader GUI for mobile devices
  • Added a 2GB file upload limit to FFvert
  • Updated README.md

Docker

You can run the image using a pre-built Docker image.

docker pull ghcr.io/nahida4479/ffvert:latest
docker run -p 3003:3003 ghcr.io/nahida4479/ffvert:latest

or build it yourself

git clone https://github.com/Nahida4479/FFvert.git
cd FFvert
docker build -t ffvert .
docker run -p 3003:3003 ffvert
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2h 40m 58s logged

Devlog 11

New

  • Section How to use
  • Change name yt-dlp –> YouTube Downloader
  • Full YouTube video download system

YouTube download video system:

I use the node package youtube-dl-exec for this system. The file is downloaded by the backend and converted using FFmpeg for the user-selected format. For GIF files FFmpeg generates a special palette for better color accuracy.

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