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.

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ChatGPT Boilerplates

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ChatGPT API libraries and connectors

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

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OpenAI ChatGPT AI technology Hackathon projects

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

OpenClaw Github Dependencies Guardian

OpenClaw Github Dependencies Guardian

Overview OpenClaw Guardian is an autonomous AI agent built to automatically monitor GitHub repositories for outdated npm dependencies, upgrade them, and create pull requests with minimal human intervention. Developed for the OpenClaw hackathon, it demonstrates how AI-driven automation can simplify one of the most repetitive yet critical software maintenance tasks—keeping dependencies up to date, secure, and production-ready. The Idea The core vision behind OpenClaw Guardian is to build a self-sustaining system that independently manages dependency updates. Instead of relying on manual checks or irregular maintenance cycles, the agent runs continuously in the background. It periodically scans target repositories, detects outdated npm packages, applies compatible upgrades, and automatically submits well-structured pull requests for review. To enhance efficiency, the agent maintains persistent memory, ensuring it does not repeatedly upgrade recently updated packages. This intelligent behavior reduces redundant operations, minimizes noise in repositories, and ensures clean, meaningful update cycles. Technologies Used OpenClaw Guardian is powered by a carefully selected technology stack designed for automation and seamless integrations: Python 3.8+ – Core language powering the application logic PyYAML – Parses YAML configuration files for flexible settings Requests – Handles HTTP communication with external APIs GitPython – Enables programmatic Git operations (clone, branch, commit) python-dotenv – Secure environment variable management GitHub API – Repository management and pull request automation Node.js & npm – Executes dependency checks and upgrades Moltbook – Sends live progress notifications during demos Architecture The project follows a modular, skill-based architecture. Responsibilities are divided into dedicated modules: repository monitoring, dependency analysis, upgrade execution, pull request generation, notification handling, and memory management.

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.

RoboGraph

RoboGraph

RoboGraph is a simulation-based safety gate for warehouse AMR (Autonomous Mobile Robot) software releases**. It answers one question: "Is this robot software safe to deploy in a real warehouse?" Before any code update reaches a physical robot, RoboGraph runs it through hundreds of simulated warehouse scenarios — robots navigating aisles, humans crossing paths, forklifts in tight spaces, forbidden zones — and checks 10 safety metrics against configurable thresholds. If anything fails, the release is blocked. RoboGraph does NOT: - Analyze source code or scan for bugs - Require access to a GitHub repository (optional integration) - Need physical robots or external simulators - Replace unit tests or CI pipelines — it adds a safety gate on top RoboGraph DOES: - Run a built-in 2D physics simulator at 20 Hz - Execute hundreds of warehouse scenarios per release - Measure 10 safety metrics (collisions, clearance, zone compliance, speed, etc.) - Automatically pass/fail releases based on configurable requirements - Generate audit-ready safety case documents - Map results to ISO 3691-4, ISO 13849-1, and ANSI/RIA R15.08 compliance standards

NeuroPilot

NeuroPilot

People who could benefit from hands-free control, for example those with limited mobility, often cannot access it. NeuroPilot changes that: open-source BCI middleware that turns a Muse 2 headband into a real control interface. Muse 2 is already connected to the app, and we have a working integration with DJI Tello. Users train in a 3D simulation and in a training environment; when their brainwave pattern matches a chosen action (move left, right, up, down), the backend fires configurable webhooks or WebSockets. We accumulate 5 actions from the headband; YOLOv8 runs on the Tello camera feed to detect obstacles and Tello state. That batch and the vision data are sent to Gemini, which decides the movement. Every command sent to the DJI Tello is the result of an AI API call, so BCI intent is refined by vision and reasoning before it reaches the drone. The stack is software-only and simulation-first: a Next.js frontend, a FastAPI + WebSocket backend, a web Lab (Three.js), a machine/Connect dashboard for status and live feedback, and per-control webhook URLs. No lab hardware or locked-in vendors. Teams can integrate with existing sims, digital twins, or robots via HTTP.

Coffee Flow AI

Coffee Flow AI

Coffee Flow AI is an autonomous, simulation-first AI system designed to optimize coffee harvesting operations. Many coffee farms face inefficiencies due to manual decision-making, lack of real-time data, and limited automation. My solution simulates harvesting processes and applies AI-driven optimization to improve task execution, productivity, and operational efficiency. Through an interactive dashboard, I can monitor performance metrics, analyze outcomes, and make data-informed decisions. Coffee Flow AI targets coffee producers and agricultural cooperatives seeking scalable, data-driven solutions. The platform is designed to be adaptable to other crops and future integration with robotics and real-world sensors, contributing to increased sustainability and profitability in agriculture.