From c5e28b3befdea8d61e3c8fec37e5b648176e15d3 Mon Sep 17 00:00:00 2001 From: James Hush Date: Fri, 14 Nov 2025 12:59:15 +0100 Subject: [PATCH] save --- .../karumi-17-detect-user-idle.py | 180 ++++++++++++++++++ 1 file changed, 180 insertions(+) create mode 100644 examples/foundational/karumi-17-detect-user-idle.py diff --git a/examples/foundational/karumi-17-detect-user-idle.py b/examples/foundational/karumi-17-detect-user-idle.py new file mode 100644 index 000000000..acc0cf812 --- /dev/null +++ b/examples/foundational/karumi-17-detect-user-idle.py @@ -0,0 +1,180 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import os +from collections import deque +from math import log + +from dotenv import load_dotenv +from loguru import logger +from pipecat_whisker import WhiskerObserver + +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.audio.vad.silero import SileroVADAnalyzer +from pipecat.audio.vad.vad_analyzer import VADParams +from pipecat.frames.frames import EndFrame, LLMMessagesAppendFrame, LLMRunFrame, TTSSpeakFrame +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair +from pipecat.processors.frame_processor import FrameDirection +from pipecat.processors.transcript_processor import TranscriptProcessor +from pipecat.processors.user_idle_processor import UserIdleProcessor +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openrouter.llm import OpenRouterLLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams + +load_dotenv(override=True) + +# We store functions so objects (e.g. SileroVADAnalyzer) don't get +# instantiated. The function will be called when the desired transport gets +# selected. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()), + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()), + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()), + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info(f"Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenRouterLLMService( + api_key=os.getenv("OPENROUTER_API_KEY"), model="google/gemini-2.5-flash" + ) + + messages = [ + { + "role": "system", + "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.", + }, + ] + + context = LLMContext(messages) + context_aggregator = LLMContextAggregatorPair(context) + + async def handle_user_idle(user_idle: UserIdleProcessor, retry_count: int) -> bool: + if retry_count == 1: + # First attempt: Add a gentle prompt to the conversation + message = { + "role": "user", + "content": "The user has been quiet. Politely and briefly ask if they're still there.", + } + await user_idle.push_frame(LLMMessagesAppendFrame([message], run_llm=True)) + return True + elif retry_count == 2: + # Second attempt: More direct prompt + message = { + "role": "user", + "content": "The user is still inactive. Ask if they'd like to continue our conversation.", + } + await user_idle.push_frame(LLMMessagesAppendFrame([message], run_llm=True)) + return True + else: + # Third attempt: End the conversation + await user_idle.push_frame( + TTSSpeakFrame("It seems like you're busy right now. Have a nice day!") + ) + await task.queue_frame(EndFrame()) + return False + + user_idle = UserIdleProcessor(callback=handle_user_idle, timeout=5.0) + transcript = TranscriptProcessor() + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, + user_idle, # Idle user check-in + transcript.user(), + context_aggregator.user(), + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + context_aggregator.assistant(), + transcript.assistant(), + ] + ) + + whisker = WhiskerObserver(pipeline, file_name="whisker.bin") + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + observers=[whisker], + ) + + @transport.event_handler("on_app_message") + async def on_app_message(transport, message, sender): + logger.debug(f"Received app message: {message}") + if "message" not in message: + return + + message = { + "role": "user", + "content": f"The user wrote in the chat: {message['message']}", + } + await user_idle.push_frame(LLMMessagesAppendFrame([message], run_llm=True)) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + # Kick off the conversation. + messages.append({"role": "user", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main()