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.
Same async-tool routing approach as #4441: detect async-tool messages in
the LLM context, deliver the final result via the formal tool-result
channel.
Caveat: as of this writing, Inworld Realtime doesn't appear to handle
the resulting delayed tool result reliably, so the routing is
best-effort and the service emits a one-time warning when async-tool
messages are seen. Streamed intermediate results remain unsupported.
Also adds function calling to the realtime-inworld.py example, and
softens the Inworld mention in the #4447 changelog now that the
exclusion is being closed.
Remove `examples/` from the `pyrightconfig.json` ignore list and fix
the resulting type errors across all example files. Common fixes:
- Required API keys: `os.getenv("X")` -> `os.environ["X"]` so the
return type is `str` rather than `str | None`, and misconfiguration
fails fast.
- Narrow `LLMContextMessage` union members with `isinstance(..., dict)`
before dict-style access.
- `assert isinstance(params.llm, ...)` before calling service-specific
methods that aren't on the base `LLMService`.
- Guard optional frame fields (e.g. `LLMSearchResponseFrame.search_result`)
before use.
* Add Inworld Realtime LLM service
Adds a WebSocket-based realtime service for Inworld's cascade
STT/LLM/TTS API with semantic VAD, function calling, and streaming
transcription support.
New files:
- src/pipecat/services/inworld/realtime/ (service, events)
- src/pipecat/adapters/services/inworld_realtime_adapter.py
- examples/foundational/19zb-inworld-realtime.py
Also includes:
- websockets dependency for inworld extra in pyproject.toml
- Adapter and settings tests matching OpenAI/Grok realtime patterns
- Fix for double-response when server-side VAD is enabled
* Prefer init-provided system instruction in Inworld Realtime
Adopt _resolve_system_instruction() from BaseLLMAdapter, matching the
pattern applied to OpenAI Realtime, Grok Realtime, Gemini Live, and
Nova Sonic in the pk/realtime-services-init-v-context-system-instructions-cleanup
branch.
* Update changelog entry with PR number
* Fix changelog format to use bullet point
* Polish PR: default model, example cleanup, changelog update
- Change default model from gpt-4.1-nano to gpt-4.1-mini
- Add function calling demo to example
- Remove demo-testing artifact from system instruction
- Mention Router support in changelog
* Address PR review feedback for Inworld Realtime
- Move example to examples/realtime/realtime-inworld.py
- Change initial context role from "user" to "developer"
- Remove explicit sample rates from example; sync them in
_ensure_audio_config so Inworld gets the transport's actual rates
- Add audio race condition guard in _handle_evt_audio_delta (matches
OpenAI realtime pattern)
- Convert remaining "system"/"developer" messages to "user" in adapter
- Add clarifying comment for local-VAD vs server-VAD metrics paths
* Simplify example, add provider tracking, remove local VAD path
- Remove function calling from example, switch model to xai/grok-4-1-fast-non-reasoning
- Add pipecat-realtime session key prefix and provider_data metadata
for Inworld traffic attribution
- Remove local VAD code path (Inworld only supports server-side VAD)
- Use typed InputAudioBufferAppendEvent for audio sends
* Default TTS model to inworld-tts-1.5-max
* Remove dead shimmed tools code, set STT/VAD defaults
- Remove non-functional AdapterType.SHIM custom tools code from adapter
- Default STT model to assemblyai/u3-rt-pro
- Default VAD eagerness to low
