Merge pull request #2927 from pipecat-ai/marcus/2025-10-28_sample_rtvi_fix
Add RTVIProcessor to foundational example 38b
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@@ -20,6 +20,7 @@ from pipecat.pipeline.runner import PipelineRunner
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from pipecat.pipeline.task import PipelineParams, PipelineTask
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from pipecat.processors.aggregators.llm_context import LLMContext
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from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
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from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
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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.tts import CartesiaTTSService
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@@ -78,9 +79,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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context = LLMContext(messages)
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context_aggregator = LLMContextAggregatorPair(context)
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rtvi = RTVIProcessor()
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pipeline = Pipeline(
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[
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transport.input(), # Transport user input
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rtvi,
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stt,
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context_aggregator.user(), # User responses
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llm, # LLM
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@@ -96,15 +100,20 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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enable_metrics=True,
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enable_usage_metrics=True,
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),
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observers=[RTVIObserver(rtvi)],
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idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
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)
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@rtvi.event_handler("on_client_ready")
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async def on_client_ready(rtvi):
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await rtvi.set_bot_ready()
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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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await task.queue_frames([LLMRunFrame()])
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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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# Kick off the conversation.
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messages.append({"role": "system", "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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async def on_client_disconnected(transport, client):
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