Migrate Agno to Pydantic AI

Preserve observable behavior, not Agno's object model. Migrate the smallest complete caller path and keep application infrastructure in place.

Trace the source before choosing a target

1. Read repository instructions, dependencies, tests, and the runtime entrypoint. Record the installed Agno, Pydantic AI, and Harness versions.
2. Trace one real request from Agent.run() / arun(), Team.run() / arun(), a Workflow, or an AgentOS endpoint through instructions, model and tool calls, hooks, session loading, memory or knowledge retrieval, events, results, state, and side effects. Establish a focused baseline or characterization test.
3. Separate these source contracts when present:
   • trusted dependencies, model-chosen tool input, session state, and workflow state;
   • conversation history, session summaries, user memories, knowledge retrieval, workflow checkpoints, and model-owned plans;
   • final content, structured output, token deltas, run events, pauses, and terminal status;
   • confirmation, user input, external tool execution, authenticated authorization, and process isolation;
   • team delegation, deterministic workflow control, AgentOS transport, queues, and deployment.
4. Record each observed contract, its owner, semantic difference, and executable proof. An unused Agno feature is not migration scope.

Read Research and concept mapping for the detected features. Read Verification and cutover before implementation.

Choose the smallest target