Update foundational examples to use "user" role
Use system_instruction on LLM service constructors instead of adding system messages to LLMContext. Messages added to context now use "user" role.
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@@ -52,20 +52,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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secret_access_key=os.getenv("AWS_SECRET_ACCESS_KEY"),
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access_key_id=os.getenv("AWS_ACCESS_KEY_ID"),
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region=os.getenv("AWS_REGION"),
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system_instruction="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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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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"role": "user",
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"content": "Tell me a fun fact!",
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},
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]
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context = LLMContext(messages)
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context = LLMContext()
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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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@@ -93,7 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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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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messages.append({"role": "system", "content": "Please introduce yourself to the user."})
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context.add_message({"role": "user", "content": "Tell me a fun fact."})
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await task.queue_frames([LLMRunFrame()])
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await asyncio.sleep(10)
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