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make turn detection configurable

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This commit is contained in:
Abhishek Kumar 2026-02-05 13:09:11 +05:30
parent 2d4a7b49b0
commit 8f67e48d45
5 changed files with 115 additions and 111 deletions
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30
api/services/pipecat/run_pipeline.py
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@ -44,6 +44,7 @@ from api.services.telephony.stasis_rtp_connection import StasisRTPConnection
from api.services.workflow.dto import ReactFlowDTO
from api.services.workflow.pipecat_engine import PipecatEngine
from api.services.workflow.workflow import WorkflowGraph
from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.extensions.voicemail.voicemail_detector import VoicemailDetector
from pipecat.pipeline.base_task import PipelineTaskParams
@ -66,6 +67,7 @@ from pipecat.turns.user_start.vad_user_turn_start_strategy import (
)
from pipecat.turns.user_stop import (
ExternalUserTurnStopStrategy,
TranscriptionUserTurnStopStrategy,
TurnAnalyzerUserTurnStopStrategy,
)
from pipecat.turns.user_turn_strategies import UserTurnStrategies
@ -453,6 +455,8 @@ async def _run_pipeline(
# Extract configurations from workflow configurations
max_call_duration_seconds = 300 # Default 5 minutes
max_user_idle_timeout = 10.0 # Default 10 seconds
smart_turn_stop_secs = 2.0 # Default 2 seconds for incomplete turn timeout
turn_stop_strategy = "transcription" # Default to transcription-based detection
keyterms = None # Dictionary words for STT boosting
if workflow.workflow_configurations:
@ -468,6 +472,16 @@ async def _run_pipeline(
"max_user_idle_timeout"
]
# Use workflow-specific smart turn stop timeout if provided
if "smart_turn_stop_secs" in workflow.workflow_configurations:
smart_turn_stop_secs = workflow.workflow_configurations[
"smart_turn_stop_secs"
]
# Use workflow-specific turn stop strategy if provided
if "turn_stop_strategy" in workflow.workflow_configurations:
turn_stop_strategy = workflow.workflow_configurations["turn_stop_strategy"]
# Extract dictionary words and convert to keyterms list
if "dictionary" in workflow.workflow_configurations:
dictionary = workflow.workflow_configurations["dictionary"]
@ -551,9 +565,9 @@ async def _run_pipeline(
correct_aggregation_callback=engine.create_aggregation_correction_callback(),
)
# Configure turn strategies based on STT provider and model
# Configure turn strategies based on STT provider, model, and workflow configuration
# Deepgram Flux uses external turn detection (VAD + External start/stop)
# Other models use transcription-based turn detection with smart turn analyzer
# Other models use configurable turn detection strategy
is_deepgram_flux = (
user_config.stt.provider == ServiceProviders.DEEPGRAM.value
and user_config.stt.model == "flux-general-en"
@ -564,15 +578,23 @@ async def _run_pipeline(
start=[VADUserTurnStartStrategy(), TranscriptionUserTurnStartStrategy()],
stop=[ExternalUserTurnStopStrategy()],
)
else:
elif turn_stop_strategy == "turn_analyzer":
# Smart Turn Analyzer: best for longer responses with natural pauses
smart_turn_params = SmartTurnParams(stop_secs=smart_turn_stop_secs)
user_turn_strategies = UserTurnStrategies(
start=[VADUserTurnStartStrategy(), TranscriptionUserTurnStartStrategy()],
stop=[
TurnAnalyzerUserTurnStopStrategy(
turn_analyzer=LocalSmartTurnAnalyzerV3()
turn_analyzer=LocalSmartTurnAnalyzerV3(params=smart_turn_params)
)
],
)
else:
# Transcription-based (default): best for short 1-2 word responses
user_turn_strategies = UserTurnStrategies(
start=[VADUserTurnStartStrategy(), TranscriptionUserTurnStartStrategy()],
stop=[TranscriptionUserTurnStopStrategy()],
)
# Create user mute strategies
# - CallbackUserMuteStrategy: mutes based on engine's _mute_pipeline state