Update examples
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@@ -27,9 +27,9 @@ from pipecat.processors.aggregators.llm_response_universal import (
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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.cartesia.stt import CartesiaSTTService
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from pipecat.services.cartesia.tts import CartesiaTTSService
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from pipecat.services.cartesia.tts import CartesiaTTSService, CartesiaTTSSettings
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from pipecat.services.deepgram.stt import DeepgramSTTService
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from pipecat.services.deepgram.tts import DeepgramTTSService
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from pipecat.services.deepgram.tts import DeepgramTTSService, DeepgramTTSSettings
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from pipecat.services.google.llm import GoogleLLMService
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from pipecat.services.llm_service import FunctionCallParams
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from pipecat.services.openai.llm import OpenAILLMService
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@@ -102,15 +102,24 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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tts_cartesia = CartesiaTTSService(
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api_key=os.getenv("CARTESIA_API_KEY"),
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voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",
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settings=CartesiaTTSSettings(
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voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
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),
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)
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tts_deepgram = DeepgramTTSService(
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api_key=os.getenv("DEEPGRAM_API_KEY"),
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settings=DeepgramTTSSettings(
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voice="aura-2-helena-en",
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),
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)
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tts_deepgram = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"))
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tts_switcher = ServiceSwitcher(
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services=[tts_cartesia, tts_deepgram], strategy_type=ServiceSwitcherStrategyManual
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)
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llm_openai = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
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llm_google = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"))
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system = "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_openai = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), system_instruction=system)
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llm_google = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), system_instruction=system)
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llm_switcher = LLMSwitcher(
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llms=[llm_openai, llm_google], strategy_type=ServiceSwitcherStrategyManual
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)
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@@ -119,15 +128,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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# Register a "direct" function
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llm_switcher.register_direct_function(get_restaurant_recommendation)
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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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},
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]
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tools = ToolsSchema(standard_tools=[weather_function, get_restaurant_recommendation])
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context = LLMContext(messages, tools)
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context = LLMContext(tools=tools)
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user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
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context,
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user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
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@@ -158,7 +161,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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async def on_client_connected(transport, client):
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logger.info(f"Client connected")
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# Kick off the conversation.
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messages.append({"role": "system", "content": "Please introduce yourself to the user."})
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context.add_message({"role": "user", "content": "Please introduce yourself to the user."})
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await task.queue_frames([LLMRunFrame()])
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await asyncio.sleep(15)
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print(f"Switching to {stt_deepgram}")
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