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Remove deprecated text_aggregator and text_filter params from TTS

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Remove the deprecated text_aggregator parameter from TTSService,
CartesiaTTSService, and RimeTTSService, and the deprecated text_filter
parameter from TTSService. Users should use LLMTextProcessor before
the TTS service instead. Update the voice-switching example to use
LLMTextProcessor with PatternPairAggregator.
This commit is contained in:
Mark Backman
2026-03-31 19:12:33 -04:00
parent a3c7f6c2af
commit e74930b954
4 changed files with 34 additions and 80 deletions
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25
src/pipecat/services/cartesia/tts.py
View File

@@ -28,7 +28,6 @@ from pipecat.frames.frames import (
from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven
from pipecat.services.tts_service import TextAggregationMode, TTSService, WebsocketTTSService
from pipecat.transcriptions.language import Language, resolve_language
from pipecat.utils.text.base_text_aggregator import BaseTextAggregator
from pipecat.utils.text.skip_tags_aggregator import SkipTagsAggregator
from pipecat.utils.tracing.service_decorators import traced_tts
@@ -240,7 +239,6 @@ class CartesiaTTSService(WebsocketTTSService):
container: str = "raw",
params: Optional[InputParams] = None,
settings: Optional[Settings] = None,
text_aggregator: Optional[BaseTextAggregator] = None,
text_aggregation_mode: Optional[TextAggregationMode] = None,
aggregate_sentences: Optional[bool] = None,
**kwargs,
@@ -271,11 +269,6 @@ class CartesiaTTSService(WebsocketTTSService):
settings: Runtime-updatable settings. When provided alongside deprecated
parameters, ``settings`` values take precedence.
text_aggregator: Custom text aggregator for processing input text.
.. deprecated:: 0.0.95
Use an LLMTextProcessor before the TTSService for custom text aggregation.
text_aggregation_mode: How to aggregate incoming text before synthesis.
aggregate_sentences: Whether to aggregate sentences within the TTSService.
@@ -337,20 +330,18 @@ class CartesiaTTSService(WebsocketTTSService):
pause_frame_processing=False,
sample_rate=sample_rate,
push_start_frame=True,
text_aggregator=text_aggregator,
settings=default_settings,
**kwargs,
)
if not text_aggregator:
# Always skip tags added for spelled-out text
# Note: This is primarily to support backwards compatibility.
# The preferred way of taking advantage of Cartesia SSML Tags is
# to use an LLMTextProcessor and/or a text_transformer to identify
# and insert these tags for the purpose of the TTS service alone.
self._text_aggregator = SkipTagsAggregator(
[("<spell>", "</spell>")], aggregation_type=self._text_aggregation_mode
)
# Always skip tags added for spelled-out text
# Note: This is primarily to support backwards compatibility.
# The preferred way of taking advantage of Cartesia SSML Tags is
# to use an LLMTextProcessor and/or a text_transformer to identify
# and insert these tags for the purpose of the TTS service alone.
self._text_aggregator = SkipTagsAggregator(
[("<spell>", "</spell>")], aggregation_type=self._text_aggregation_mode
)
self._api_key = api_key
self._cartesia_version = cartesia_version

24
src/pipecat/services/rime/tts.py
View File

@@ -37,7 +37,6 @@ from pipecat.services.tts_service import (
WebsocketTTSService,
)
from pipecat.transcriptions.language import Language, resolve_language
from pipecat.utils.text.base_text_aggregator import BaseTextAggregator
from pipecat.utils.text.skip_tags_aggregator import SkipTagsAggregator
from pipecat.utils.tracing.service_decorators import traced_tts
@@ -176,7 +175,6 @@ class RimeTTSService(WebsocketTTSService):
sample_rate: Optional[int] = None,
params: Optional[InputParams] = None,
settings: Optional[Settings] = None,
text_aggregator: Optional[BaseTextAggregator] = None,
text_aggregation_mode: Optional[TextAggregationMode] = None,
aggregate_sentences: Optional[bool] = None,
**kwargs,
@@ -204,11 +202,6 @@ class RimeTTSService(WebsocketTTSService):
settings: Runtime-updatable settings. When provided alongside deprecated
parameters, ``settings`` values take precedence.
text_aggregator: Custom text aggregator for processing input text.
.. deprecated:: 0.0.95
Use an LLMTextProcessor before the TTSService for custom text aggregation.
text_aggregation_mode: How to aggregate incoming text before synthesis.
aggregate_sentences: Deprecated. Use text_aggregation_mode instead.
@@ -282,15 +275,14 @@ class RimeTTSService(WebsocketTTSService):
self._audio_format = "pcm"
self._sampling_rate = 0 # updated in start()
if not text_aggregator:
# Always skip tags added for spelled-out text
# Note: This is primarily to support backwards compatibility.
# The preferred way of taking advantage of Rime spelling is
# to use an LLMTextProcessor and/or a text_transformer to identify
# and insert these tags for the purpose of the TTS service alone.
self._text_aggregator = SkipTagsAggregator(
[("spell(", ")")], aggregation_type=self._text_aggregation_mode
)
# Always skip tags added for spelled-out text
# Note: This is primarily to support backwards compatibility.
# The preferred way of taking advantage of Rime spelling is
# to use an LLMTextProcessor and/or a text_transformer to identify
# and insert these tags for the purpose of the TTS service alone.
self._text_aggregator = SkipTagsAggregator(
[("spell(", ")")], aggregation_type=self._text_aggregation_mode
)
# Store service configuration
self._api_key = api_key

37
src/pipecat/services/tts_service.py
View File

@@ -58,7 +58,6 @@ from pipecat.services.ai_service import AIService
from pipecat.services.settings import TTSSettings, is_given
from pipecat.services.websocket_service import WebsocketService
from pipecat.transcriptions.language import Language
from pipecat.utils.text.base_text_aggregator import BaseTextAggregator
from pipecat.utils.text.base_text_filter import BaseTextFilter
from pipecat.utils.text.simple_text_aggregator import SimpleTextAggregator
from pipecat.utils.time import seconds_to_nanoseconds
@@ -168,8 +167,6 @@ class TTSService(AIService):
append_trailing_space: bool = False,
# TTS output sample rate
sample_rate: Optional[int] = None,
# Text aggregator to aggregate incoming tokens and decide when to push to the TTS.
text_aggregator: Optional[BaseTextAggregator] = None,
# Types of text aggregations that should not be spoken.
skip_aggregator_types: Optional[List[str]] = [],
# A list of callables to transform text before just before sending it to TTS.
@@ -182,7 +179,6 @@ class TTSService(AIService):
] = None,
# Text filter executed after text has been aggregated.
text_filters: Optional[Sequence[BaseTextFilter]] = None,
text_filter: Optional[BaseTextFilter] = None,
# Audio transport destination of the generated frames.
transport_destination: Optional[str] = None,
settings: Optional[TTSSettings] = None,
@@ -215,11 +211,6 @@ class TTSService(AIService):
append_trailing_space: Whether to append a trailing space to text before sending to TTS.
This helps prevent some TTS services from vocalizing trailing punctuation (e.g., "dot").
sample_rate: Output sample rate for generated audio.
text_aggregator: Custom text aggregator for processing incoming text.
.. deprecated:: 0.0.95
Use an LLMTextProcessor before the TTSService for custom text aggregation.
skip_aggregator_types: List of aggregation types that should not be spoken.
text_transforms: A list of callables to transform text before just before sending it
to TTS. Each callable takes the aggregated text and its type, and returns the
@@ -227,11 +218,6 @@ class TTSService(AIService):
(aggregation_type | '*', transform_function).
text_filters: Sequence of text filters to apply after aggregation.
text_filter: Single text filter (deprecated, use text_filters).
.. deprecated:: 0.0.59
Use `text_filters` instead, which allows multiple filters.
transport_destination: Destination for generated audio frames.
settings: The runtime-updatable settings for the TTS service.
reuse_context_id_within_turn: Whether the service should reuse context IDs within the
@@ -300,18 +286,7 @@ class TTSService(AIService):
self._append_trailing_space: bool = append_trailing_space
self._init_sample_rate = sample_rate
self._sample_rate = 0
self._text_aggregator: BaseTextAggregator = text_aggregator or SimpleTextAggregator(
aggregation_type=self._text_aggregation_mode
)
if text_aggregator:
import warnings
with warnings.catch_warnings():
warnings.simplefilter("always")
warnings.warn(
"Parameter 'text_aggregator' is deprecated. Use an LLMTextProcessor before the TTSService for custom text aggregation.",
DeprecationWarning,
)
self._text_aggregator = SimpleTextAggregator(aggregation_type=self._text_aggregation_mode)
self._skip_aggregator_types: List[str] = skip_aggregator_types or []
self._text_transforms: List[
@@ -320,16 +295,6 @@ class TTSService(AIService):
# TODO: Deprecate _text_filters when added to LLMTextProcessor
self._text_filters: Sequence[BaseTextFilter] = text_filters or []
self._transport_destination: Optional[str] = transport_destination
if text_filter:
import warnings
with warnings.catch_warnings():
warnings.simplefilter("always")
warnings.warn(
"Parameter 'text_filter' is deprecated, use 'text_filters' instead.",
DeprecationWarning,
)
self._text_filters = [text_filter]
self._resampler = create_stream_resampler()