[sbargaoui]

We've been building agents with pydantic-ai in production. The framework is great for defining agents, but we kept rewriting the same infrastructure to actually show them to users.

The pattern we landed on: agent runs in a background worker, emits events to Redis Streams, frontend consumes via SSE. Multiple clients can listen to the same stream. If the user navigates away or hits stop, we delete a key and the agent aborts gracefully at the next node boundary.

pydantic-ai gives you Agent.iter() and streaming primitives, but wiring this up - structured events, reconnection, history across turns - is a lot of glue.

This library wraps iter() and handles the lifecycle:

begin → [llm-begin → part-deltas → llm-end]+ → end

Each event is typed: text delta, tool call with args, tool return, error. Frontend gets structured JSON it can render directly.

It's thin (~400 LOC) and doesn't patch pydantic-ai internals. You bring your own session storage by implementing load/save.

Feedback welcome, especially on the event protocol.