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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@@ -218,11 +218,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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api_key=os.getenv("GOOGLE_API_KEY"),
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settings=GoogleLLMSettings(
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model="gemini-2.5-flash",
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system_instruction=system_message,
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# force a certain amount of thinking if you want it
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# thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096)
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),
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# force a certain amount of thinking if you want it
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# params=GoogleLLMService.InputParams(
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# thinking=GoogleLLMService.ThinkingConfig(thinking_budget=4096)
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# ),
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)
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tts = GoogleTTSService(
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@@ -234,18 +233,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"),
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)
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messages = [
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{
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"role": "system",
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"content": system_message,
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},
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{
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"role": "user",
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"content": "Start by saying hello.",
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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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@@ -281,7 +269,7 @@ 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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@transport.event_handler("on_client_disconnected")
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