Handle Daily's on_dtmf_event callback, convert it to an
InputDTMFFrame pushed into the input transport. Also add __str__
methods to InputDTMFFrame and OutputDTMFFrame for better logging.
Now that the base TTSService and STTService handle Language enum
conversion at init time, subclasses no longer need to convert in their
own __init__ methods. Remove conversion calls from hardcoded defaults,
params paths, and deprecated direct arg paths across 22 service files.
Services just pass raw Language enums and let the base class convert
via language_to_service_language() polymorphic dispatch.
When a Language enum (e.g. Language.ES) is passed via
settings=Service.Settings(language=Language.ES), it gets stored as-is
without conversion to the service-specific code. The base
_update_settings() handles this for runtime updates, but at init time
apply_update() copies the raw enum. This causes API errors because
services send the unconverted enum value.
Add language conversion in TTSService.__init__ and STTService.__init__
after super().__init__(), using the subclass language_to_service_language()
via normal method resolution.
Both analyzers are superseded by LocalSmartTurnAnalyzerV3. Added
deprecation warnings and docstring notices following the existing
pattern from LocalSmartTurnAnalyzer.
Perplexity appears to have statefulness within a conversation, so
converting a system message to "user" in one call and then back to
"system" in the next (after more messages are appended) causes API
errors. Remove the trailing system→user conversion entirely — if the
context only has system messages, the API call will fail but the
mistake will be caught right away.
Add test exercising the step 3 ordering where stripping a trailing
assistant exposes a system message that then gets converted to user.
Move the reasoning about when a trailing system message can occur
into the docstring.
Perplexity allows multiple initial system messages, so don't merge them.
Instead, skip system-system pairs during the consecutive same-role merge
step. Broaden the trailing message fix to convert any trailing system
message to user (not just a lone system message), so contexts with only
system messages don't fail.
Perplexity's API is stricter than OpenAI about conversation history:
- Requires strict alternation between user/tool and assistant messages
- Disallows system messages except as the initial message
- Requires the last message to be user or tool
The new adapter transforms messages before sending to satisfy all three
constraints: merging consecutive initial system messages, converting
non-initial system to user, merging consecutive same-role messages, and
removing trailing assistant messages.
Also adds dual-system-instruction warnings to Cerebras, Fireworks,
Mistral, Perplexity, and SambaNova services (matching the existing
BaseOpenAILLMService pattern), and updates the warning text in
BaseOpenAILLMService to be more descriptive.
EndTaskFrame and StopTaskFrame are now ControlFrames instead of
SystemFrames, so they flow through the pipeline and queue behind
pending work. This prevents races where EndFrame could overtake
in-flight frames (e.g. function call responses).
CancelTaskFrame and InterruptionTaskFrame remain SystemFrames
(via new TaskSystemFrame base): since they need immediate propagation.
The sink now catches EndTaskFrame, StopTaskFrame and CancelTaskFrame
downstream and re-queues it upstream to the task, ensuring the full
pipeline drains before shutdown begins.
Wait for _audio_context_task to finish draining the contexts queue
before canceling _stop_frame_task, ensuring all pending audio
contexts are processed during shutdown.
Flush buffered frames before pushing the synchronization frame so
downstream processors see the buffered frames first. Switch to a
while-loop with pop(0) so frames added to the buffer during flush
are also drained.
