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Moving the environment variables to inside the demo.

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This commit is contained in:
Filipi Fuchter
2025-04-17 16:28:50 -03:00
parent 53ee3fb64c
commit a80f82cdb6
4 changed files with 30 additions and 25 deletions
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4
examples/foundational/38-smart-turn.py
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@@ -29,6 +29,8 @@ load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection):
logger.info(f"Starting bot")
remote_smart_turn_url = os.getenv("REMOTE_SMART_TURN_URL")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
@@ -37,7 +39,7 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection):
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
vad_audio_passthrough=True,
end_of_turn_analyzer=SmartTurnAnalyzer(),
end_of_turn_analyzer=SmartTurnAnalyzer(url=remote_smart_turn_url),
),
)

21
examples/foundational/38a-local-smart-turn.py
View File

@@ -30,6 +30,23 @@ load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection):
logger.info(f"Starting bot")
# To use this locally, set the environment variable LOCAL_SMART_TURN_MODEL_PATH
# to the path where the smart-turn repo is cloned.
#
# Example setup:
#
# # Git LFS (Large File Storage)
# brew install git-lfs
# # Hugging Face uses LFS to store large model files, including .mlpackage
# git lfs install
# # Clone the repo with the smart_turn_classifier.mlpackage
# git clone https://huggingface.co/pipecat-ai/smart-turn
#
# Then set the env variable:
# export LOCAL_SMART_TURN_MODEL_PATH=./smart-turn
# or add it to your .env file
smart_turn_model_path = os.getenv("LOCAL_SMART_TURN_MODEL_PATH")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
@@ -38,7 +55,9 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection):
vad_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
vad_audio_passthrough=True,
end_of_turn_analyzer=LocalCoreMLSmartTurnAnalyzer(params=SmartTurnParams(stop_secs=5)),
end_of_turn_analyzer=LocalCoreMLSmartTurnAnalyzer(
smart_turn_model_path=smart_turn_model_path, params=SmartTurnParams(stop_secs=5)
),
),
)