make turn detection configurable

api/Dockerfile

@@ -13,6 +13,11 @@ RUN apt-get update && apt-get install -y \
 # Copy and install requirements
 COPY api/requirements.txt .
 
+# Install CPU-only PyTorch FIRST to prevent CUDA/NVIDIA dependencies
+# This satisfies torch dependency before other packages try to pull GPU version
+RUN pip install --user --no-cache-dir torch --index-url https://download.pytorch.org/whl/cpu && \
+    rm -rf /root/.cache/pip
+
 # Install dependencies to user directory for easy copying
 RUN pip install --user --no-cache-dir -r requirements.txt && \
     # Clean up pip cache after installation

api/services/pipecat/run_pipeline.py

@@ -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

api/tasks/knowledge_base_processing.py

@@ -125,15 +125,11 @@ async def process_knowledge_base_document(
         embeddings_api_key = None
         embeddings_model = None
         if document.created_by:
-            user_config = await db_client.get_user_configurations(
-                document.created_by
-            )
+            user_config = await db_client.get_user_configurations(document.created_by)
             if user_config.embeddings:
                 embeddings_api_key = user_config.embeddings.api_key
                 embeddings_model = user_config.embeddings.model
-                logger.info(
-                    f"Using user embeddings config: model={embeddings_model}"
-                )
+                logger.info(f"Using user embeddings config: model={embeddings_model}")
 
         # Check if API key is configured
         if not embeddings_api_key: