Update 55zn example (UIltravox dynamic settings updates) to exercise changing modality, which is a setting that supports dynamic updates
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@@ -5,18 +5,23 @@
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#
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import asyncio
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import datetime
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import os
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from dotenv import load_dotenv
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from loguru import logger
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from pipecat.adapters.schemas.tools_schema import ToolsSchema
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from pipecat.audio.vad.silero import SileroVADAnalyzer
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from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame
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from pipecat.pipeline.pipeline import Pipeline
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from pipecat.pipeline.runner import PipelineRunner
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from pipecat.pipeline.task import PipelineParams, PipelineTask
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from pipecat.processors.aggregators.llm_context import LLMContext
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from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
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from pipecat.processors.aggregators.llm_response_universal import (
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AssistantTurnStoppedMessage,
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LLMContextAggregatorPair,
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)
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from pipecat.runner.types import RunnerArguments
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from pipecat.runner.utils import create_transport
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from pipecat.services.ultravox.llm import (
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@@ -52,17 +57,22 @@ transport_params = {
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async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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logger.info(f"Starting bot")
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system_prompt = "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."
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llm = UltravoxRealtimeLLMService(
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params=OneShotInputParams(
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api_key=os.getenv("ULTRAVOX_API_KEY"),
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system_prompt="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.",
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system_prompt=system_prompt,
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temperature=0.3,
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max_duration=datetime.timedelta(minutes=3),
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),
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one_shot_selected_tools=ToolsSchema(standard_tools=[]),
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)
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messages = [
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{
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"role": "system",
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"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.",
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"content": system_prompt,
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},
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]
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@@ -88,15 +98,27 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
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)
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@assistant_aggregator.event_handler("on_assistant_turn_stopped")
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async def on_assistant_turn_stopped(aggregator, message: AssistantTurnStoppedMessage):
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timestamp = f"[{message.timestamp}] " if message.timestamp else ""
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line = f"{timestamp}assistant: {message.content}"
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logger.info(f"Transcript: {line}")
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@transport.event_handler("on_client_connected")
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async def on_client_connected(transport, client):
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logger.info(f"Client connected")
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await task.queue_frames([LLMRunFrame()])
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await asyncio.sleep(10)
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logger.info("Updating Ultravox Realtime LLM settings: temperature=0.1")
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logger.info("Updating Ultravox Realtime LLM settings: output_medium=text")
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await task.queue_frame(
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LLMUpdateSettingsFrame(update=UltravoxRealtimeLLMSettings(temperature=0.1))
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LLMUpdateSettingsFrame(update=UltravoxRealtimeLLMSettings(output_medium="text"))
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)
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await asyncio.sleep(10)
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logger.info("Updating Ultravox Realtime LLM settings: output_medium=voice")
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await task.queue_frame(
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LLMUpdateSettingsFrame(update=UltravoxRealtimeLLMSettings(output_medium="voice"))
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)
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@transport.event_handler("on_client_disconnected")
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