Pass realtime_service_mode=RealtimeServiceModeConfig() through every
realtime LLM service example (base, async-tool, video, text-output,
persistent-context, update-settings, MCP) so context aggregation uses
the new realtime-mode semantics instead of relying on local VAD as a
workaround.
Where examples previously wired SileroVADAnalyzer into
LLMUserAggregatorParams to coax turn frames out of services that don't
emit them server-side (AWS Nova Sonic, Ultravox, Gemini Live), the local
VAD is now removed. realtime_service_mode keeps context writes correct
without it, and the Phase 1.5 server-side InterruptionFrame fixes for
Nova Sonic and Ultravox keep the bot from talking past the user when
they barge in.
Transcript-logging event handlers move from on_user_turn_stopped /
on_assistant_turn_stopped to on_user_message_added /
on_assistant_message_added, which carry the finalized text in realtime
mode (the turn-stopped events fire before the message is finalized, so
their `content` is None in that mode).
For services that don't emit user-turn frames (Gemini Live, AWS Nova
Sonic, Ultravox) the example now carries a Tier 1 comment block that
spells out which downstream processors won't activate, how to add local
VAD if needed, and the caveat that locally-generated turn boundaries
are a heuristic that may diverge from server-side ground truth.
Adds examples/realtime/realtime-openai-local-vad.py, a new variant of
the OpenAI Realtime example that disables OpenAI's server-side turn
detection and drives turn boundaries locally — useful when you want a
turn analyzer like LocalSmartTurnV3 to decide when the user is done
speaking. Server-emitted turn frames are still preferred when available.
The Gemini Live local-VAD variant already existed; it's been updated in
place rather than rewritten.
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