Top Builders

Explore the top contributors showcasing the highest number of app submissions within our community.

OpenAI ChatGPT

The ChatGPT model has been trained on a vast amount of text data, including conversations and other types of human-generated text, which allows it to generate text that is similar in style and content to human conversation. ChatGPT can be used to generate responses to questions, code, make suggestions, or provide information in a conversational manner, and it is able to do so in a way that is often indistinguishable from human-generated text. The initial model has been trained using Reinforcement Learning from Human Feedback (RLHF), using methods similar to InstructGPT, but with slight differences in the data collection setup. The model is trained using supervised fine-tuning, where human AI trainers provided conversations in which they played both sides—the user and an AI assistant. The trainers would have had access to model-written suggestions to help them compose their responses.

General
Relese dateNovember 30, 2022
AuthorOpenAI
API DocumentationChatGPT API
TypeAutoregressive, Transformer, Language model

Start building with ChatGPT

GPT-3 have a rich ecosystem of libraries and resources to help you get started. We have collected the best GPT-3 libraries and resources to help you get started to build with GPT-3 today. To see what others are building with GPT-3, check out the community built GPT-3 Use Cases and Applications.

All important links about ChatGPT in one place


ChatGPT Boilerplates

Boilerplates to help you get started" id="boilerplates


ChatGPT API libraries and connectors

The ChatGPT API endpoint provides a convenient way to incorporate advanced language understanding into your applications.


OpenAI ChatGPT AI technology Hackathon projects

Discover innovative solutions crafted with OpenAI ChatGPT AI technology, developed by our community members during our engaging hackathons.

SweetyAI

SweetyAI

SweetyAI is a communication-focused AI companion that lives directly inside messaging platforms like LINE. Instead of asking users to download and learn a new app, SweetyAI integrates into an environment people already use every day, lowering the barrier to AI adoption—especially for older or less tech-savvy users. Its core function is message refinement. Users can forward or draft messages through SweetyAI, and the AI will rewrite them in a tone that better fits the relationship context—whether professional, friendly, or romantic. This helps reduce social friction, avoid misunderstandings, and improve communication confidence in sensitive conversations. Beyond tone polishing, SweetyAI acts as a social bridge. It can help users initiate conversations, maintain rapport, and even explore new connections when both sides opt in. The goal is to create a sense that AI agents are assisting their users behind the scenes—matching communication styles and facilitating introductions in a natural, human-like way. Because SweetyAI operates inside chat platforms, it also has the potential to evolve into a daily-life automation gateway. Future capabilities may include setting reminders, making service requests, purchasing tickets, ordering food, or handling simple tasks—all through natural conversation without requiring users to navigate complex interfaces. By turning familiar chat apps into intelligent life portals, SweetyAI demonstrates how AI can move from a tool people occasionally use into an always-present assistant embedded in everyday human interaction.

Ladybug - The Robot Reader

Ladybug - The Robot Reader

There are 240 million children worldwide living with learning disabilities, and many struggle to access physical books independently. Ladybug: The Robot Reader was built to change that. Ladybug is an autonomous robotic system that reads physical books aloud from cover to cover with no human intervention. Built on the SO-101 robotic arm, it uses a perception-action loop powered by Claude Vision to assess the workspace, decide what to do next, and execute — opening a closed book, reading each page spread, turning pages, and closing the book when finished. Claude Vision analyzes camera frames to classify page types (content, title page, table of contents, index, blank) and extract text. ElevenLabs then streams natural-sounding speech in real time using a sentence-level prefetch pipeline so audio plays continuously without pauses. Motor skills — opening, closing, and page turning — are trained using ACT (Action Chunking with Transformers) policies. The system includes intelligent retry logic with frame hashing to detect failed page turns and automatically retry them. Ladybug supports multiple reading modes: verbose (reads everything), skim (headers and titles only), and silent (text extraction only). It also features a web dashboard for remote monitoring and a dry-run mode for testing without hardware. Our mission is accessibility in education — putting an autonomous reading companion in every special education classroom. We want 1,000,000 lady bug robot readers available to children around the world.