Adds tests for AggregatedFrameSequencer, WordCompletionTracker, and
word_timestamp_utils (including CJK language scenarios). Updates existing
Cartesia TTS and TTS frame ordering tests to cover the new behaviours.
TTSTextFrame entries were losing their original text structure when word
timestamps were enabled. AggregatedTextFrame now carries a raw_text field with
the original LLM-produced text (including pattern delimiters such as
<card>...</card>). The assistant context receives properly-tagged content
rather than the cleaned words returned by the TTS provider. Also handles words
that straddle two sentence boundaries by splitting and attributing each part
to its correct source frame.
SSML markup (e.g. <spell>, <emotion>, <break>) was leaking into word entries
returned by the Cartesia word-timestamps API. Tags are now stripped before
processing so word-to-text attribution remains accurate when SSML is present
in the TTS input.
Frames sharing the same presentation timestamp were being reordered by the
priority queue. Adds a monotonic counter as a tiebreaker so frames with equal
PTS are always emitted in insertion order, preventing subtle audio/text
sequencing bugs.
Skipped frames (e.g. code blocks filtered via skip_aggregator_types) were
emitted to the assistant context immediately instead of waiting for preceding
spoken frames to finish. Introduces AggregatedFrameSequencer to hold each
frame's slot and flush only after all earlier spoken sentences are complete,
keeping context ordering correct.
Mirrors the deprecation in ``OpenAITTSService.__init__``: ``instructions``
is now a Settings field. The constructor still accepts it for backward
compatibility but the canonical path is through ``Settings``.
A copy of ``turn-management-filter-incomplete-turns.py`` extended with
a ``get_weather(location)`` direct function. Exercises the path where
the LLM responds to a complete user turn by calling a tool — used to
reproduce (and now verify the fix for) the ``_user_speaking`` gating
bug between filter-incomplete and function calls.
With ``filter_incomplete_user_turns`` enabled, an LLM that responded to
a user turn by calling a tool (without first emitting a ✓ marker)
never finalized the user turn. ``UserStoppedSpeakingFrame`` stayed
deferred, the assistant aggregator kept ``_user_speaking=True``, and
when ``FunctionCallResultFrame`` arrived its ``not self._user_speaking``
gate dropped the context push — the LLM continuation never ran and
the call hung silently.
Broadcast ``UserTurnInferenceCompletedFrame`` on
``FunctionCallsStartedFrame`` (i.e. the moment the LLM commits to a
tool call, before the function dispatches), gated by a new
``_turn_completion_broadcasted`` flag so the ✓ path and the tool-call
path don't both fire. The flag resets in ``_turn_reset`` alongside
the other per-turn state.
Emitting on the start frame rather than ``LLMFullResponseEndFrame``
also shrinks the race window — ``UserStoppedSpeakingFrame`` (a
``SystemFrame``) has the maximum possible head start over the
``FunctionCallResultFrame`` (``DataFrame``) that follows.
Drop the EU-region default from the STT/TTS WebSocket URLs in favor of
the generic api.gradium.ai endpoint, and remove the explicit overrides
from the examples so they pick up the new defaults.
