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Make the mechanism of adding spaces when concatenating TTS (or speech-to-speech LLM) output text explicit and deterministic, rather than heuristic-based.

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This fixes a bug where spaces were sometimes missing from assistant messages in context.
This commit is contained in:
Paul Kompfner
2025-11-10 12:28:40 -05:00
parent c2ce143e6c
commit 913194844e
10 changed files with 113 additions and 44 deletions
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51
tests/test_context_aggregators.py
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@@ -35,6 +35,7 @@ from pipecat.frames.frames import (
)
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.task import PipelineParams
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response import (
LLMAssistantAggregatorParams,
LLMUserAggregatorParams,
@@ -651,12 +652,20 @@ class BaseTestAssistantContextAggregator:
aggregator = self.AGGREGATOR_CLASS(
context, params=self.create_assistant_aggregator_params(expect_stripped_words=False)
)
# The newer LLMAssistantAggregator expects TextFrames to declare
# when they include inter-frame spaces.
def make_text_frame(text: str) -> TextFrame:
frame = TextFrame(text=text)
frame.includes_inter_frame_spaces = True
return frame
frames_to_send = [
LLMFullResponseStartFrame(),
TextFrame(text="Hello "),
TextFrame(text="Pipecat. "),
TextFrame(text="How are "),
TextFrame(text="you?"),
make_text_frame("Hello "),
make_text_frame("Pipecat. "),
make_text_frame("How are "),
make_text_frame("you?"),
LLMFullResponseEndFrame(),
]
expected_down_frames = [*self.EXPECTED_CONTEXT_FRAMES]
@@ -697,14 +706,22 @@ class BaseTestAssistantContextAggregator:
aggregator = self.AGGREGATOR_CLASS(
context, params=self.create_assistant_aggregator_params(expect_stripped_words=False)
)
# The newer LLMAssistantAggregator expects TextFrames to declare
# when they include inter-frame spaces.
def make_text_frame(text: str) -> TextFrame:
frame = TextFrame(text=text)
frame.includes_inter_frame_spaces = True
return frame
frames_to_send = [
LLMFullResponseStartFrame(),
TextFrame(text="Hello "),
TextFrame(text="Pipecat."),
make_text_frame("Hello "),
make_text_frame("Pipecat."),
LLMFullResponseEndFrame(),
LLMFullResponseStartFrame(),
TextFrame(text="How are "),
TextFrame(text="you?"),
make_text_frame(text="How are "),
make_text_frame(text="you?"),
LLMFullResponseEndFrame(),
]
expected_down_frames = [*self.EXPECTED_CONTEXT_FRAMES, *self.EXPECTED_CONTEXT_FRAMES]
@@ -724,16 +741,24 @@ class BaseTestAssistantContextAggregator:
aggregator = self.AGGREGATOR_CLASS(
context, params=self.create_assistant_aggregator_params(expect_stripped_words=False)
)
# The newer LLMAssistantAggregator expects TextFrames to declare
# when they include inter-frame spaces.
def make_text_frame(text: str) -> TextFrame:
frame = TextFrame(text=text)
frame.includes_inter_frame_spaces = True
return frame
frames_to_send = [
LLMFullResponseStartFrame(),
TextFrame(text="Hello "),
TextFrame(text="Pipecat."),
make_text_frame("Hello "),
make_text_frame("Pipecat."),
LLMFullResponseEndFrame(),
SleepFrame(AGGREGATION_SLEEP),
InterruptionFrame(),
LLMFullResponseStartFrame(),
TextFrame(text="How are "),
TextFrame(text="you?"),
make_text_frame("How are "),
make_text_frame("you?"),
LLMFullResponseEndFrame(),
]
expected_down_frames = [
@@ -969,7 +994,7 @@ class TestOpenAIAssistantContextAggregator(
class TestLLMAssistantAggregator(
BaseTestAssistantContextAggregator, unittest.IsolatedAsyncioTestCase
):
CONTEXT_CLASS = OpenAILLMContext
CONTEXT_CLASS = LLMContext
AGGREGATOR_CLASS = LLMAssistantAggregator
EXPECTED_CONTEXT_FRAMES = [LLMContextFrame, LLMContextAssistantTimestampFrame]