scripts(evals): use new vad_analyzer from LLMUSerAggregator
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@@ -42,7 +42,10 @@ from pipecat.pipeline.pipeline import Pipeline
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from pipecat.pipeline.runner import PipelineRunner
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from pipecat.pipeline.runner import PipelineRunner
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from pipecat.pipeline.task import PipelineParams, PipelineTask
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from pipecat.pipeline.task import PipelineParams, PipelineTask
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from pipecat.processors.aggregators.llm_context import LLMContext
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from pipecat.processors.aggregators.llm_context import LLMContext
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from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
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from pipecat.processors.aggregators.llm_response_universal import (
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LLMContextAggregatorPair,
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LLMUserAggregatorParams,
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)
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from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor
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from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor
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from pipecat.processors.frame_processor import FrameDirection
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from pipecat.processors.frame_processor import FrameDirection
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from pipecat.runner.types import RunnerArguments
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from pipecat.runner.types import RunnerArguments
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@@ -207,7 +210,6 @@ async def run_example_pipeline(script_path: Path, eval_config: EvalConfig):
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audio_in_enabled=True,
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audio_in_enabled=True,
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audio_out_enabled=True,
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audio_out_enabled=True,
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video_in_enabled=True,
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video_in_enabled=True,
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vad_analyzer=SileroVADAnalyzer(),
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),
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),
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)
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)
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@@ -309,7 +311,12 @@ async def run_eval_pipeline(
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]
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]
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context = LLMContext(messages, tools)
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context = LLMContext(messages, tools)
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context_aggregator = LLMContextAggregatorPair(context)
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context_aggregator = LLMContextAggregatorPair(
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context,
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user_params=LLMUserAggregatorParams(
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vad_analyzer=SileroVADAnalyzer(),
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),
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)
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audio_buffer = AudioBufferProcessor()
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audio_buffer = AudioBufferProcessor()
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