Both GrokLLMService and XAIHttpTTSService use the same xAI API (api.x.ai),
so move Grok source files into the xai module. Leave deprecation shims in
the old grok/ paths for backward compatibility.
- Rename XAITTSService → XAIHttpTTSService and XAITTSSettings → XAIHttpTTSSettings
- Add language_to_xai_language() with explicit LANGUAGE_MAP using resolve_language()
- Remove deprecated InputParams, params, voice, language init params
- Remove XAI_DEFAULT_SAMPLE_RATE and XAI_PCM_CODEC constants; add encoding param
- Set sample_rate=None default (picked up from PipelineParams or user)
- Use Language.EN enum instead of string "en" for default language
- Add changelog/4031.added.md
- Add 07e-interruptible-xai.py foundational example
- Update 14g-function-calling-grok.py to use XAIHttpTTSService
- Register 07e in run-release-evals.py
Test that OpenAI Realtime, Grok Realtime, and Nova Sonic adapters
prefer init-provided system_instruction over context-provided, warn
on conflicts, and don't warn for developer messages.
OpenAI-compatible services that don't support the "developer" message
role can now set supports_developer_role = False on the service class.
BaseOpenAILLMService passes this as convert_developer_to_user to the
adapter, which converts developer messages to user messages before
sending them to the API. Applied to Cerebras and Perplexity.
Also removes the now-redundant developer→user conversion step from
PerplexityLLMAdapter (handled by the parent adapter via the flag).
OpenAI Realtime, Grok Realtime, and AWS Nova Sonic adapters now convert
"developer" role messages to "user" (consistent with all other non-OpenAI
adapters). Previously these messages were silently dropped. Adds starter
unit tests for all three realtime adapters.
Developer messages are now always converted to "user" in non-OpenAI
adapters, never promoted to the system instruction. This removes an
inconsistency where adding an unrelated message to context would change
whether a developer message got promoted.
Simplifications:
- Rename _extract_initial_system_or_developer → _extract_initial_system
- Return Optional[str] instead of Tuple (role is always "system")
- Drop initial_context_message_role from _resolve_system_instruction
- Drop system_role fields from all ConvertedMessages dataclasses
When the only message in context was a system message,
_extract_initial_system_or_developer would convert it to "user" (to
prevent empty history) without warning about the conflict with
system_instruction. Now warns inline before converting, with a message
explaining both the conflict and the user-role conversion.
Two goals:
1. Centralize system_instruction vs context system message resolution into
the LLM adapters. This eliminates duplication between in-pipeline and
out-of-band (run_inference) code paths across ~16 locations in service
llm.py files.
2. Add support for "developer" role messages in conversation context, which
is facilitated by the above centralization.
Shared helpers on BaseLLMAdapter:
- _extract_initial_system_or_developer: extracts/converts messages[0]
based on role and whether system_instruction is provided
- _resolve_system_instruction: warns on conflicts between system_instruction
and context system messages, returns the effective instruction
Developer message handling (new):
- Non-OpenAI adapters: an initial "developer" message is promoted to the
system instruction when no system_instruction is provided; otherwise it
is converted to "user". Subsequent "developer" messages are always
converted to "user". No conflict warning is emitted for developer
messages (unlike "system" messages).
- OpenAI adapter: "developer" messages pass through in conversation
history without triggering conflict warnings.
- OpenAI Responses adapter: "developer" messages are kept as "developer"
role (same as "system", which is also converted to "developer" for the
Responses API).
Other behavior changes:
- Gemini: "initial" system message detection now checks messages[0] only
(previously searched anywhere in the list)
- Bedrock: a lone system message is now converted to "user" instead of
being extracted to an empty message list (matches existing Anthropic
behavior)
Route LLMFullResponseEndFrame through the serialization queue instead
of pushing it directly downstream when push_text_frames is enabled.
This ensures the frame is emitted only after the audio context is
fully drained, preserving correct ordering relative to TTSTextFrames.
Previously, the final sentence TTSTextFrame would arrive at the
LLMAssistantAggregator after LLMFullResponseEndFrame, causing it to
be dropped from the conversation context (especially with RTVI text
input where no subsequent interruption would flush the orphaned text).
Add warnings in SpeechTimeoutUserTurnStopStrategy and
TurnAnalyzerUserTurnStopStrategy when stop_secs differs from the
recommended default (0.2s) or when stop_secs >= STT p99 latency,
which collapses the STT wait timeout to 0s. Document the stop_secs=0.2
assumption in stt_latency.py.
The AudioHook protocol requires every message to carry a `parameters`
object. `_create_message` conditionally included it only when parameters
were truthy, so pong responses and closed responses without
outputVariables were sent without the field.
Clients that validate message structure (including the Genesys reference
implementation) rejected these messages, which broke server sequence
tracking and prevented outputVariables from reaching the Architect flow.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
The override would re-add `instructions` after the adapter had
intentionally converted it to a developer message for empty contexts.
Added a regression test.
Adds a FrameOrder enum with ARRIVAL (default, existing behavior) and
PIPELINE (pushes frames in pipeline definition order). This lets callers
guarantee output ordering between parallel pipelines — e.g. ensuring
image frames precede audio frames — without needing a separate reordering
processor downstream.
Updates the 05-sync-speech-and-image example to use FrameOrder.PIPELINE,
removing the ImageBeforeAudioReorderer class entirely.
- Add WakePhraseUserTurnStartStrategy for gating interaction behind wake
phrase detection, with timeout and single_activation modes
- Add default_user_turn_start_strategies() and
default_user_turn_stop_strategies() helper functions
- Deprecate WakeCheckFilter in favor of the new strategy
- Extend ProcessFrameResult to stop strategies for short-circuit evaluation
- Fix MinWordsUserTurnStartStrategy including filtered text in output
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).
Uses real LLMContext and adapter (only HTTP client is mocked) to test
basic inference, client exception propagation, system_instruction
override, empty context fallback, and max_tokens override.
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
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.
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
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.
* Add ServiceSwitcherStrategyFailover for automatic error-based service switching
Introduce a strategy hierarchy: ServiceSwitcherStrategy (base) →
ServiceSwitcherStrategyManual (handles ManuallySwitchServiceFrame) →
ServiceSwitcherStrategyFailover (adds error-based failover). ServiceSwitcher
now defaults to ServiceSwitcherStrategyManual with strategy_type optional.
Non-fatal ErrorFrames are forwarded to the strategy via handle_error().
* Move metadata request into _set_active_if_available
Requesting metadata is part of making a service active, so it belongs
alongside setting _active_service and firing on_service_switched. This
removes the duplicate queue_frame calls from ServiceSwitcher push_frame
and process_frame.
