Building a Streaming Local AI Agent

"Streaming" gets used in two different ways when people talk about AI agents, and most tutorials only build one of them. Sometimes it means the agent consumes a live stream of events instead of waiting for someone to type a message. Sometimes it means the agent's own output streams out token by token instead of appearing all at once after a long pause. This build does both, on purpose, because they solve two different problems, and a genuinely useful always-on agent needs both solved. The framing worth borrowing here comes from what's usually called an ambient agent, one LangChain describes as triggered by events rather than by a human message, and Google's Agent Development Kit describes from the infrastructure side the same way: agents woken by something arriving on a stream, not sitting behind a request-response call. The scenario for this build is…