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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

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.