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

AutoGen

AutoGen is an advanced open-source framework developed by Chi Wang designed to simplify the creation of multi-agent systems powered by large language models (LLMs). The platform allows developers to build conversational AI agents that can interact with each other, humans, and various tools in a coordinated manner. AutoGen is highly modular and supports a wide range of applications, making it an essential tool for developers looking to implement complex, automated workflows with minimal manual intervention.

General
AuthorChi Wang
Release DateSeptember 2023
Websitehttps://microsoft.github.io/autogen/
Repositoryhttps://github.com/microsoft/autogen
Documentationhttps://microsoft.github.io/autogen/docs/Getting-Started
Discordhttps://discord.com/invite/pAbnFJrkgZ
Technology TypeAI/ML Framework

Key Features

  • Multi-Agent Framework: Facilitates the design of agents with specialized roles, enabling them to communicate and collaborate efficiently.

  • Enhanced LLM Inference: Provides advanced APIs for improving LLM performance, reducing inference costs.

  • Customizable Workflows: Supports complex, dynamic workflows by allowing agents to interact through conversational patterns, enabling seamless automation.

  • Tool Integration: Agents can be configured to use external tools, adding flexibility and enhancing their problem-solving capabilities.

  • Human-in-the-Loop: Integrates human feedback into the workflow, allowing for oversight and intervention when necessary.

Start Building with AutoGen

AutoGen simplifies the development of complex AI applications by providing a robust framework for creating multi-agent systems. With its modular design, developers can quickly build and customize AI workflows that combine LLMs, human intelligence, and various tools to tackle intricate tasks. Whether you are looking to automate customer support, enhance software development processes, or optimize supply chains, AutoGen offers the flexibility and power needed to create sophisticated AI-driven solutions. Explore the community-built use cases and applications to see the full potential of what AutoGen can do.

👉 Start building with AutoGen

👉 Examples

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AutoGen AI technology page Hackathon projects

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

Autonomous Agent Commerce on Arc

Autonomous Agent Commerce on Arc

SystemicShift enables AI agents to participate in the economy autonomously. Agents research, decide, and execute real USDC payments on Arc blockchain — zero human intervention. ## The Problem AI agents can't pay for anything. The API economy needs autonomous payment infrastructure with programmatic wallets, machine-to-machine protocols, and sub-second settlement. ## Our Solution - Autonomous AI Agents (GPT-4o + Semantic Kernel) - Circle Developer Controlled Wallets on Arc - x402 Payment Protocol for pay-per-call micropayments - Sub-second deterministic finality ## How It Works 1. Create Agent → Gets USDC wallet with budget 2. Assign Task → "Research APIs, buy $5 credits" 3. Agent Executes → Researches, decides, pays automatically 4. Verify On-Chain → Transaction on Arc explorer ## x402 Implementation API returns 402 Payment Required → Agent auto-pays USDC → Retries with proof → Gets data. No subscriptions, pay only what you use. ## Circle Product Feedback **Products Used:** Arc, USDC, Developer Controlled Wallets, x402 **Why Chosen:** Deterministic finality critical for autonomous systems. USDC as native gas eliminates fee volatility. **What Worked Well:** Sub-second finality, clear documentation, smooth wallet creation, easy testnet faucet. **What Could Be Improved:** More .NET/C# examples (most docs are JS/TS), limited x402 implementation patterns, clearer Gateway vs Wallets distinction. **Recommendations:** Official .NET SDK, x402 reference implementation, agent-specific documentation, local dev tools like Ganache for Arc.

Qubic WhaleWatch - Asset Creation Monitor

Qubic WhaleWatch - Asset Creation Monitor

Qubic WhaleWatch is an automated asset creation monitoring system built for the lablab.ai Qubic Hackathon (EasyConnect Track). It solves the critical problem of missing new asset launches and whale movements on the Qubic network. The system monitors the Qubic QX Smart Contract's IssueAsset method and triggers alerts when new assets have supply exceeding 1,000,000 tokens. Using EasyConnect's no-code platform, it sends real-time notifications via webhooks to Discord, email, or Google Sheets, while displaying all alerts on a live auto-updating dashboard. Unique value: First to monitor ASSET CREATION (not just transfers). Solved technical challenge: Qubic's 55 lowercase address format vs EasyConnect's 56 uppercase requirement. Working prototype built in under 3 hours. Key features: No coding required, real-time monitoring, early warning for traders, competitive intelligence for teams, compliance tracking for institutions. Live dashboard shows all alerts with automatic updates every 30 seconds. Built with: EasyConnect (no-code automation), Qubic Network, JavaScript/HTML dashboard, webhook integration. Perfect for traders wanting early project discovery, teams monitoring competitors, and institutions needing compliance tracking. Demo: Fully functional system with active EasyConnect alert, verified webhook integration, and live dashboard. Ready for immediate use with 5-minute setup.

Qubic Auto-Tracker

Qubic Auto-Tracker

Qubic Auto-Tracker is a tool that watches any Qubic wallet the moment money moves. As soon as a transaction happens on a your wallet, EasyConnect sends an alert, and our Make setup catches it instantly. It pulls the latest transaction details and owned assets from the Qubic network and puts everything neatly into two Google Sheets. The first sheet shows the wallet’s recent transactions with balance, when it was last updated, and a short, AI summary is generated, for example: “This wallet just received 300 QUBIC and now has 1,550 total”. The second sheet lists everything else the wallet owns like, QXMR shares, NFTs, tokens, one line per item. The AI adds a quick plain-English line for each, like “They own 1,610 QXMR shares” or “This person has 5 rare collectibles.” Both sheets stay fresh all day long, add nice colors and tiny charts, and you never have to do anything yourself. It just runs quietly in the background and tells you what’s happening in normal, easy words. Perfect for anyone who wants to keep an eye on Qubic wallets without any hassle.

DevAI Suite

DevAI Suite

The AI Developer Dashboard Suite is a next-generation productivity platform designed to empower developers with advanced AI-powered tools in a unified, intuitive interface. Built with Next.js, Tailwind CSS, and TypeScript, this dashboard offers real-time code assistance, intelligent code review, rapid prototyping, and seamless automation for tasks like testing and deployment. Developers can access interactive widgets, customize their workspace, and monitor key metrics to optimize their workflow. With features like dark mode, notifications, and team management, the dashboard streamlines the entire development lifecycle, making collaboration and productivity effortless for individuals and teams alike. Perfect for modern software development environments.

code mate

code mate

CodeMate is an intelligent AI assistant that streamlines your development workflow by automatically generating project structures, essential code files, and GitHub workflows from a simple project description. It integrates with GitHub to create repositories and push generated content, making project setup fast and effortless. How It Works Project Description Input: Users provide a natural language description, including project goals, features, and preferred tech stack. AI-Powered Code Generation: Using Novita AI, CodeMate creates: README.md with project overview and usage requirements.txt listing dependencies src/app.py as the main application script (e.g., a Streamlit app) .github/workflows/main.yml for CI/CD automation Organized Project Structure: CodeMate structures the generated files into a clean, navigable local directory to help developers get started quickly. GitHub Integration: Creates and initializes a new repository Pushes the generated content Links the repo in the README Robust Error Handling: It ensures successful GitHub operations with retry logic, and initializes empty repos using repo.create_file(). Secure Environment Management: Sensitive data like API keys and GitHub tokens are handled via environment variables, keeping your credentials safe. CodeMate helps developers move from idea to codebase in minutes—automating setup so you can focus on building.

MedisecAI

MedisecAI

Problem Statement: Access to timely and affordable medical advice is a global concern. Key challenges include: Long wait times for medical appointments Limited access to healthcare in remote and underserved areas High costs associated with routine consultations User hesitation in seeking advice for seemingly minor symptoms Misinformation online, making self-diagnosis risky Solution Overview MediSecAI provides a reliable AI-driven solution to address these challenges: 24/7 access to preliminary medical guidance User-friendly interface presenting structured and concise information Three-part consultations, including: Diagnosis based on reported symptoms Pharmacy recommendations for suitable medications or remedies Next-step consultation advice for follow-up actions Formatted delivery with visual cues and bullet points for readability Conversational and professional tone to enhance user engagement Key Features & Functionality Multi-Agent Medical Consultation Diagnosis Agent – Evaluates symptoms to suggest possible conditions Pharmacy Agent – Recommends medications and remedies Consultation Agent – Offers advice for next steps and follow-ups User Experience Intuitive Interface – Clean, modern, and easy to navigate Visual Differentiation – Icons indicate types of medical advice Formatted Output – Uses bullet points and bold text for emphasis Real-Time Interaction – Simulated typing for conversational realism Technical Capabilities Round-Robin Agent Interaction – Smooth, logical fl ow of dialogue between agents Concise Responses – Actionable and focused content delivery Robust Error Handling – Friendly notifi cations in case of issues Medical Disclaimer – Clearly highlights the platform’s role as a guidance tool only