examples(foundational): use system_instruction in all examples
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@@ -10,7 +10,7 @@ from dotenv import load_dotenv
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from loguru import logger
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from pipecat.audio.vad.silero import SileroVADAnalyzer
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from pipecat.frames.frames import TTSSpeakFrame
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from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
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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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@@ -59,18 +59,14 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
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)
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llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
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messages = [
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{
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"role": "system",
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"content": "You are a helpful assistant. Respond to what the user said in a creative and helpful way. Keep your responses brief.",
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},
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]
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llm = OpenAILLMService(
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api_key=os.getenv("OPENAI_API_KEY"),
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system_instruction="You are a helpful assistant. Respond to what the user said in a creative and helpful way. Keep your responses brief.",
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)
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hey_robot_filter = WakeCheckFilter(["hey robot", "hey, robot"])
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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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@@ -102,7 +98,13 @@ 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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await task.queue_frame(TTSSpeakFrame("Hi! If you want to talk to me, just say 'Hey Robot'"))
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context.add_message(
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{
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"role": "system",
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"content": "Please introduce yourself. Tell the user they should say 'Hey Robot' before talking to you.",
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}
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)
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await task.queue_frames([LLMRunFrame()])
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@transport.event_handler("on_client_disconnected")
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async def on_client_disconnected(transport, client):
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