Forward the on_summary_applied event from the internal summarizer to
the aggregator so users can listen for it without accessing private
members. Update summarization examples to use the new public event.
- mcp_service.py: remove unnecessary try/except around debug log,
use len(available_tools.tools) to match actual iteration target
- bedrock_adapter.py, aws/llm.py: add AttributeError to except tuple
to handle None content (previously caught by bare except)
Adds the explicit "no params object" step 3 comment to all
LLM services that skip from step 2 to step 4 in their
settings initialization sequence, matching the pattern
established in services that do have a params object.
Replace references to undefined `_params` with `self._settings` for
language and VAD config. Add missing `system_instruction` to default
settings to satisfy validate_complete(). Remove redundant line that
read language from the deprecated `params` arg.
- Speechmatics: move config build after super().__init__ and settings
delta so turn_detection_mode (e.g. ADAPTIVE) takes effect
- Google STT: fix example passing bare Language enum instead of list
- Google TTS: add missing explicit defaults for all custom settings fields
- Soniox: fix accidental tuple wrapping of STT service in example
- Speechmatics examples: fix system->user role in kick-off messages
- Deepgram Flux: move tag from settings to __init__ (billing metadata)
- ElevenLabs STT: default tag_audio_events to None (use API default)
- Fal STT: simplify language default handling
- Google TTS: rename GoogleStreamTTSSettings to GoogleTTSSettings
Use "AI service" language instead of listing specific types, add
ServiceSettings as a fallback for direct AIService subclasses, and
clarify delta mode description with a concrete frame example.
The audio fields (sample rates, sample sizes, channel counts) on the deprecated `Params` class had no non-deprecated equivalent. This adds an `AudioConfig` class and `audio_config` init arg so users can specify audio configuration without relying on the deprecated `params` parameter.
Move `session_properties` into `GrokRealtimeLLMSettings`, making `settings` the canonical way to configure Grok Realtime — matching the pattern used across the rest of the codebase. The `session_properties` init arg is now deprecated in favor of `settings=GrokRealtimeLLMSettings(session_properties=...)`.
`system_instruction` is synced bidirectionally between the top-level settings field and `session_properties.instructions`, with top-level taking precedence on conflict. (Unlike OpenAI Realtime, Grok's `SessionProperties` has no `model` field, so no model sync is needed.)
Replace the monolithic rtvi.py with a proper package split by concern
protocol version:
- models_v0.py: deprecated pre-1.0 Pydantic models
- models_v1.py: current RTVI protocol v1 message models
- frames.py: RTVI pipeline frame dataclasses
- observer.py: RTVIObserver and RTVIObserverParams
- processor.py: RTVIProcessor (now lean, imports from submodules)
- __init__.py: re-exports full public API for backward compatability
Move `session_properties` into `OpenAIRealtimeLLMSettings`, making `settings` the canonical way to configure OpenAI Realtime — matching the pattern used across the rest of the codebase. The `session_properties` init arg is now deprecated in favor of `settings=OpenAIRealtimeLLMSettings(session_properties=...)`.
`model` and `system_instruction` are synced bidirectionally between the top-level settings fields and `session_properties.model`/`.instructions`, with top-level taking precedence on conflict.
