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
Add `system_instruction=None` to `default_settings` for OpenAIRealtimeLLMService, GrokRealtimeLLMService, UltravoxRealtimeLLMService, AWSNovaSonicLLMService (Azure inherits from OpenAI), and OpenAIRealtimeBetaLLMService (Azure Beta inherits from OpenAI Beta).
Deprecate `system_instruction` init arg in AWSNovaSonicLLMService in favor of `settings=AWSNovaSonicLLMSettings(system_instruction=...)`. Use `self._settings.system_instruction` directly instead of storing a separate `self._system_instruction`.
Deprecation of `params` and `session_properties` in favor of `settings` for realtime services will be tackled in future work.
Add `system_instruction` field to `LLMSettings` so it is runtime-updatable via settings.
For Google (GoogleLLMService, GoogleVertexLLMService), deprecate the init-time arg since it was already shipped. For Anthropic, AWS Bedrock, and OpenAI, remove the init-time arg entirely since it was never shipped.
Still need to handle realtime services (OpenAI Realtime, Grok Realtime, Gemini Live).
Broaden the "Dynamic Settings Updates" section into "Service Settings"
covering the complete settings pattern: defining a Settings subclass,
wiring it into __init__ with defaults + apply_update, and distinguishing
init-only config from runtime-updatable fields.
- Add dedicated Settings subclasses to 20 LLM services that were
borrowing parent Settings classes (e.g. AzureLLMSettings,
GroqLLMSettings) so users don't need cross-module imports
- Fix field defaults to NOT_GIVEN in BaseWhisperSTTSettings,
OpenAIRealtimeSTTSettings, and NvidiaSegmentedSTTSettings for
delta-mode safety
- Fix incomplete default_settings in AWS, Cartesia, ElevenLabs,
Fish, and Whisper services so validate_complete() passes
- Add auto-discovered tests that verify all Settings classes default
to NOT_GIVEN (delta safety) and all services initialize with
complete settings (store completeness)
Move output_container, output_encoding, output_sample_rate out of
CartesiaTTSSettings into plain instance attributes since they cannot
change at runtime without breaking the audio pipeline. Remove deprecated
speed/emotion fields and their dead references in _build_msg() and
run_tts(). Remove the from_mapping override that only existed to
destructure those now-removed output format fields.
Update all ~192 call sites across 84 service files to pass class references
(e.g. `CartesiaTTSSettings`) instead of string names (`"CartesiaTTSSettings"`)
to `_warn_deprecated_param()`. This enables better IDE refactoring support.
Also fix `from_mapping` return type annotations in 5 settings subclasses to
use `typing.Self` instead of forward reference strings.
ServiceSettings types were introduced for runtime updates via ServiceUpdateSettingsFrame, but there was tension between init-time and runtime APIs: overlapping-but-different InputParams vs ServiceSettings classes, and runtime-updatable fields like `model` and `voice` scattered as direct init args rather than living in a settings object. This unifies them so developers use the same settings type at both init and runtime, improving ergonomics and consistency.
Every concrete AIService subclass (LLM, TTS, STT, ImageGen, Vision, Video) now accepts a `settings` parameter for runtime-updatable config. Old init args (`model`, `voice_id`, `params`/`InputParams`) still work but emit DeprecationWarnings pointing to the new API. When both are provided, `settings` takes precedence. Leaf classes emit warnings; base classes do not, avoiding double warnings in inheritance chains.
system_instruction from the constructor always takes precedence. A
warning is now logged when the context also contains a system message
so users can spot the conflict.
Add vad_threshold parameter to AssemblyAIConnectionParams to support
voice activity detection threshold configuration for the u3-rt-pro model.
This parameter allows users to align AssemblyAI's VAD threshold with
their external VAD systems (e.g., Silero VAD) to avoid the "dead zone"
where AssemblyAI transcribes speech that the external VAD hasn't
detected yet, which can delay interruption handling.
- Range: 0.0 to 1.0 (lower = more sensitive)
- Default: 0.3 (API default when not sent)
- Only applicable to u3-rt-pro model
- Automatically included in WebSocket query parameters
Recommended usage: Set vad_threshold to match your VAD's activation
threshold (e.g., both at 0.3) for optimal performance.
Widen version ranges for stable packages (anthropic, azure, deepgram,
groq, livekit, nvidia-riva-client, fastapi, ormsgpack, opentelemetry,
faster-whisper) and add upper bounds to previously uncapped packages
(hume, pyjwt, livekit-api, camb).
Replace CartesiaHttpTTSService's internal use of the Cartesia SDK with
direct aiohttp calls, accepting an optional aiohttp_session parameter.
Replace fal-client SDK calls in FalSTTService and FalImageGenService
with direct HTTP to bypass the SDK's aggressive retry/backoff logic
that caused significant latency regressions.
Widen version ranges for stable packages (aiofiles, docstring_parser,
onnxruntime) while adding upper bounds to previously uncapped packages
(transformers, numba, wait_for2). Bump soxr to 1.0.0 and pyloudnorm
to 0.2.0. Move silero extra to empty since onnxruntime is now a core dep.
