Refactor language_to_soniox_language to use resolve_language + LANGUAGE_MAP
pattern consistent with other services. Fix resolve_language fallback to use
str(language) instead of language.value so plain strings don't crash.
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.
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.
Move the warning helper into AIService as _warn_init_param_moved_to_settings.
It now uses type(self).__name__ to produce messages like
"Use settings=AnthropicLLMService.Settings(model=...)" instead of the raw
settings class name "AnthropicLLMSettings(model=...)". Callers no longer need
to pass the settings class explicitly.
Replace direct references to settings class names (e.g. `FooSettings`) with the nested `Settings` alias form throughout all 87 service files:
- Type annotations: `Settings`
- Runtime code: `self.Settings`
- Docstrings: `ServiceClass.Settings`
- Cross-file inheritance: `ParentService.Settings`
This makes the `Settings` alias the canonical way to reference a service's settings, keeping only the class definition and alias assignment as the remaining hits for each raw settings class name.
