examples(foundational): use system_instruction in all examples
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@@ -64,7 +64,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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voice_id="a167e0f3-df7e-4d52-a9c3-f949145efdab",
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)
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llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"))
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llm = GoogleLLMService(
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api_key=os.getenv("GOOGLE_API_KEY"),
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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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tavus = TavusVideoService(
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api_key=os.getenv("TAVUS_API_KEY"),
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@@ -72,14 +75,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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session=session,
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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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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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@@ -113,7 +109,7 @@ 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(
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context.add_message(
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{
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"role": "system",
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"content": "Start by greeting the user and ask how you can help.",
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