examples/voice_agent.py runs in console mode or joins LiveKit rooms. It
scopes memory from dispatch metadata, SUPERMEMORY_CONTAINER_TAG, or the
participant, preloads the caller's profile, and greets returning callers
by name. Tested on LiveKit Cloud: a second call greeted the caller by name
and used a fact from the first call.
The example is not included in the wheel or sdist.
Found in live LiveKit Cloud voice calls:
- Recalling in on_user_turn_completed changed the turn context, so
LiveKit discarded its preemptive generation on every turn with memory.
SupermemoryAgent now recalls only in llm_node, and uses the turn hook
only for realtime models, which skip llm_node.
- A turn with no memory recalled twice (hook, then llm_node), and tool
follow-ups recalled again. Each user message is now recalled once;
retries and follow-ups share the result.
- A preloaded profile made llm_node skip recall for the rest of the
call. Fresh recall now replaces the earlier injection.
- remember used the default dynamic dreaming, so an explicit fact took
about 18 minutes to become recallable. It now uses instant (~40s).
The call transcript mode is configurable via capture_dreaming.
- recall_timeout defaults to 2s; profile calls measured 0.5-1.4s.
- Require livekit-agents>=1.3.6: AgentServer (used in the quick start)
arrived in 1.3.1, and 1.3.1-1.3.5 no longer import with current
opentelemetry-sdk.
session.run and generate_reply never call on_user_turn_completed, so a
text turn reached the model with no memory. SupermemoryAgent now recalls
inside llm_node and skips the fetch when the voice hook already injected.
