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even the parameters are fixed, keep aic ready for processing.

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Gökmen Görgen
2026-01-19 16:20:45 +01:00
parent bdded9b026
commit dcab79753b
1 changed files with 55 additions and 45 deletions
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100
src/pipecat/audio/filters/aic_filter.py
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@@ -18,7 +18,14 @@ import os
from typing import List, Optional from typing import List, Optional
import numpy as np import numpy as np
from aic_sdk import Model, ProcessorAsync, ProcessorConfig, ProcessorParameter, set_sdk_id from aic_sdk import (
Model,
ParameterFixedError,
ProcessorAsync,
ProcessorConfig,
ProcessorParameter,
set_sdk_id,
)
from loguru import logger from loguru import logger
from pipecat.audio.filters.base_audio_filter import BaseAudioFilter from pipecat.audio.filters.base_audio_filter import BaseAudioFilter
@@ -156,61 +163,64 @@ class AICFilter(BaseAudioFilter):
""" """
self._sample_rate = sample_rate self._sample_rate = sample_rate
# Load or download model
if self._model_path:
logger.debug(f"Loading AIC model from: {self._model_path}")
self._model = Model.from_file(self._model_path)
else:
logger.debug(f"Downloading AIC model: {self._model_id}")
os.makedirs(self._model_download_dir, exist_ok=True)
model_path = await Model.download_async(self._model_id, self._model_download_dir)
logger.debug(f"Model downloaded to: {model_path}")
self._model = Model.from_file(model_path)
# Get optimal frames for this sample rate
self._frames_per_block = self._model.get_optimal_num_frames(self._sample_rate)
# Allocate processing buffers now that we know the block size
self._in_f32 = np.zeros((1, self._frames_per_block), dtype=np.float32)
self._out_i16 = np.zeros(self._frames_per_block, dtype=np.int16)
# Create configuration
config = ProcessorConfig.optimal(
self._model,
sample_rate=self._sample_rate,
)
# Create async processor
try: try:
# Load or download model
if self._model_path:
logger.debug(f"Loading AIC model from: {self._model_path}")
self._model = Model.from_file(self._model_path)
else:
logger.debug(f"Downloading AIC model: {self._model_id}")
os.makedirs(self._model_download_dir, exist_ok=True)
model_path = await Model.download_async(self._model_id, self._model_download_dir)
logger.debug(f"Model downloaded to: {model_path}")
self._model = Model.from_file(model_path)
# Get optimal frames for this sample rate
self._frames_per_block = self._model.get_optimal_num_frames(self._sample_rate)
# Allocate processing buffers now that we know the block size
self._in_f32 = np.zeros((1, self._frames_per_block), dtype=np.float32)
self._out_i16 = np.zeros(self._frames_per_block, dtype=np.int16)
# Create configuration
config = ProcessorConfig.optimal(
self._model,
sample_rate=self._sample_rate,
)
# Create async processor
self._processor = ProcessorAsync(self._model, self._license_key, config) self._processor = ProcessorAsync(self._model, self._license_key, config)
self._aic_ready = True
except Exception as e: # noqa: BLE001 - surfacing SDK initialization errors
logger.error(f"AIC model initialization failed: {e}")
self._aic_ready = False
# Get contexts for parameter control and VAD # Get contexts for parameter control and VAD
self._processor_ctx = self._processor.get_processor_context() self._processor_ctx = self._processor.get_processor_context()
self._vad_ctx = self._processor.get_vad_context() self._vad_ctx = self._processor.get_vad_context()
try:
# Apply initial parameters # Apply initial parameters
if self._enhancement_level is not None: if self._enhancement_level is not None:
level = self._enhancement_level if self._enabled else 0.0 level = self._enhancement_level if self._enabled else 0.0
self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level) self._processor_ctx.set_parameter(ProcessorParameter.EnhancementLevel, level)
if self._voice_gain is not None: if self._voice_gain is not None:
self._processor_ctx.set_parameter(ProcessorParameter.VoiceGain, self._voice_gain) self._processor_ctx.set_parameter(ProcessorParameter.VoiceGain, self._voice_gain)
except ParameterFixedError as e:
logger.error(f"AIC parameter update failed: {e}")
self._aic_ready = True # Log processor information
logger.debug(f"ai-coustics filter started:")
# Log processor information logger.debug(f" Model ID: {self._model.get_id()}")
logger.debug(f"ai-coustics filter started:") logger.debug(f" Sample rate: {self._sample_rate} Hz")
logger.debug(f" Model ID: {self._model.get_id()}") logger.debug(f" Frames per chunk: {self._frames_per_block}")
logger.debug(f" Sample rate: {self._sample_rate} Hz") logger.debug(f" Enhancement strength: {int((self._enhancement_level or 1.0) * 100)}%")
logger.debug(f" Frames per chunk: {self._frames_per_block}") logger.debug(f" Optimal sample rate: {self._model.get_optimal_sample_rate()} Hz")
logger.debug(f" Enhancement strength: {int((self._enhancement_level or 1.0) * 100)}%") logger.debug(
logger.debug(f" Optimal sample rate: {self._model.get_optimal_sample_rate()} Hz") f" Output delay: {self._processor_ctx.get_output_delay()} samples "
logger.debug( f"({self._processor_ctx.get_output_delay() / self._sample_rate * 1000:.2f}ms)"
f" Output delay: {self._processor_ctx.get_output_delay()} samples " )
f"({self._processor_ctx.get_output_delay() / self._sample_rate * 1000:.2f}ms)"
)
except Exception as e: # noqa: BLE001 - surfacing SDK initialization errors
logger.error(f"AIC model initialization failed: {e}")
self._aic_ready = False
async def stop(self): async def stop(self):
"""Clean up the AIC processor when stopping. """Clean up the AIC processor when stopping.