A curated list of examples and resources for OpenAI's AgentKit.
AgentKit is a comprehensive toolkit provided by OpenAI for developers and enterprises to build, deploy, and optimize AI agents. It combines various components to help you create production-grade agents without the typical overhead associated with AI projects.
Key components include:
- Agent Builder: A visual canvas for designing agent logic and multi-step workflows with version control
- ChatKit: An embeddable chat interface that you can customize to match your brand
- Evals for Agents: Tools for trace grading, performance testing, and automated prompt optimization
- Connector Registry: A secure way to connect your internal tools and APIs under centralized admin control
Learn more at openai.com/introducing-agentkit
- Multi-Agent Workflows: Examples demonstrating how to design complex workflows with multiple agents collaborating together
- Workflow Versioning: Showcasing how to version, iterate, and manage different versions of agent workflows
- Agent Handoffs: Demonstrations of seamless agent-to-agent handoffs for complex multi-step tasks
- Custom Guardrails: Implementing safety checks and validation logic within agent workflows
- API Integrations: Examples of connecting agents to external APIs and services
- Database Connections: Demonstrating how to integrate various databases with your agents
- Tool Integration: Connecting internal tools and services to your agent workflows
- Admin Configuration: Setting up centralized admin controls for connector management across workspaces
- Embedded Chat Interfaces: Examples of embedding ChatKit into web applications
- Brand Customization: Customizing the chat interface to match your brand identity
- Multi-Modal Interactions: Implementing text, voice, and visual interactions in chat
- User Authentication: Integrating user authentication and authorization flows
- Trace Grading: Examples of evaluating agent performance through trace analysis
- A/B Testing: Running experiments to compare different agent configurations
- Prompt Optimization: Automated prompt engineering and optimization workflows
- Performance Monitoring: Setting up monitoring and analytics for production agents
- Getting Started with AgentKit
- Building Your First Agent with Agent Builder
- Embedding ChatKit in Your Application
Contributions are welcome! If you have examples, tutorials, or resources related to AgentKit, please submit a pull request. Please ensure:
- Your example is well-documented with clear instructions
- Code follows best practices and is properly tested
- You include a brief description of what the example demonstrates
- You add your contribution to the appropriate category
See CONTRIBUTING.md for detailed guidelines.
This repository is licensed under the MIT License. See LICENSE for more details.