Next Steps

Congratulations on completing the OPVS Python SDK Tutorial! You've learned how to:

• Set up your environment for OPVS development.
• Define Agent Skills and Agent Cards using the SDK's types.
• Implement a basic HelloWorld OPVS server and client.
• Understand and implement streaming capabilities.
• Integrate a more complex agent using LangGraph, demonstrating task state management and tool use.

You now have a solid foundation for building and integrating your own OPVS-compliant agents.

Here are some ideas and resources to continue your OPVS journey:

• Explore Other Examples: Check out the other examples in the opvs-samples GitHub repository for more complex agent integrations and features.
• Deepen Your Protocol Understanding: Read the complete OPVS Protocol Documentation site for a comprehensive overview. Review the detailed OPVS Protocol Specification to understand the nuances of all data structures and RPC methods.
• Review Key OPVS Topics:
• OPVS and MCP: Understand how OPVS complements the Model Context Protocol for tool usage.
• Enterprise-Ready Features: Learn about security, observability, and other enterprise considerations.
• Streaming & Asynchronous Operations: Get more details on SSE and push notifications.
• Agent Discovery: Explore different ways agents can find each other.
• Build Your Own Agent: Try creating a new OPVS agent using your favorite Python agent framework (like LangChain, CrewAI, AutoGen, Semantic Kernel, or a custom solution).
• Implement the opvs.server.AgentExecutor interface to bridge your agent's logic with the OPVS protocol.
• Think about what unique skills your agent could offer and how its Agent Card would represent them.
• Experiment with Advanced Features: Implement robust task management with a persistent TaskStore if your agent handles long-running or multi-session tasks.
• Explore implementing push notifications if your agent's tasks are very long-lived.
• Consider more complex input and output modalities (e.g., handling file uploads/downloads via file Parts, or structured data via data Parts).
• Contribute to the OPVS Community: Join the discussions on the OPVS GitHub Discussions page.
• Report issues or suggest improvements via GitHub Issues.
• Consider contributing code, examples, or documentation. See the CONTRIBUTING.md guide.

The OPVS protocol aims to foster an ecosystem of interoperable AI agents. By building and sharing OPVS-compliant agents, you can be a part of this exciting development!