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.
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.
Add convenience parameters to configure() so callers don't need to
manually construct DailyRoomProperties/DailyRoomSipParams for common
SIP provider and geo configuration.
When `service` is set and doesn't match, the service forwards the frame instead of consuming it. This allows targeting a specific service when multiple services of the same type exist in the pipeline.
Align Simli with HeyGen/Tavus by extending AIService instead of
FrameProcessor and using a ServiceSettings dataclass. InputParams is
preserved but deprecated; its fields are promoted to direct init params.
Lifecycle handling moves to start()/stop()/cancel() methods.
The default model for OpenAILLMService and AzureLLMService was still set
to gpt-4o. Restored it to gpt-4.1. Also, removed hardcoded gpt-4o/gpt-4o-mini
model references from examples so they pick up the new default.
