The API-provided full model name is more specific than the
user-provided model name (e.g. includes version/snapshot details).
Reorder the lookup in _get_model_name and add a comment where the
Responses service sets the field.
The override would re-add `instructions` after the adapter had
intentionally converted it to a developer message for empty contexts.
Added a regression test.
Set store=False in Responses API calls since we send full conversation
history as input items and don't use previous_response_id.
Add 5 run_inference tests for OpenAIResponsesLLMService using real
LLMContext and adapter (only HTTP client mocked).
Add OpenAIResponsesLLMService using the Responses API, with a dedicated
adapter that converts LLMContext messages to Responses API input items
(system→developer, tool_calls→function_call, tool→function_call_output,
multimodal content conversion, and tools schema flattening).
- New adapter: open_ai_responses_adapter.py
- New service: openai/responses/llm.py
- Examples: 07-interruptible and 14-function-calling variants
- 19 unit tests for adapter conversion logic
- Eval entries for both examples
List-valued settings like keyterm, keywords, search, redact, and replace
were being converted to strings before being passed to the SDK connect()
method. The SDK expects lists so its encode_query can produce repeated
query params (keyterm=a&keyterm=b).
Raw strings like "de-DE" passed as the language parameter to TTS/STT services
were bypassing the Language enum resolution logic, causing silent failures
(e.g. ElevenLabs expects "de" not "de-DE"). Now raw strings are first converted
to Language enums so they go through the same resolve_language() path, with a
warning logged for unrecognized strings.
Reset stop strategies at turn start (not just turn stop) so that late
transcriptions arriving between turns do not leave stale _text that
causes premature stops on the next turn. Also cancel pending timeout
tasks in reset() for both SpeechTimeout and TurnAnalyzer strategies.
Expose enable_dialout as a configure() parameter (default False) so
dial-out examples can opt in without needing to build DailyRoomProperties
manually.
Narrow misleading Optional type hints on parameters that never accept
None, extract the duplicated token_exp_duration * 60 * 60 calculation,
remove unnecessary forward-reference quotes on DailyMeetingTokenProperties,
and clarify why enable_dialout is explicitly set to False.
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.
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.
The base_url parameter previously forced wss:// and https:// schemes,
breaking air-gapped or private deployments that need ws:// or http://.
Extract URL derivation into _derive_deepgram_urls() helper that respects
the developers scheme choice while deriving the paired WebSocket and
HTTP URLs the Deepgram SDK requires.
Closes#4019
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.
Add convenience parameters to configure() so callers don't need to
manually construct DailyRoomProperties/DailyRoomSipParams for common
SIP provider and geo configuration.
