From 3a8d3cc8419228530c4c520210004c74181378c6 Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 19 Feb 2026 18:36:12 -0300 Subject: [PATCH 1/2] Allowing to define the list of frame processors whose frames should be silently ignored by the RTVI observer. --- .../53-concurrent-llm-rtvi-ignored-sources.py | 193 ++++++++++++++++++ src/pipecat/processors/frameworks/rtvi.py | 37 ++++ 2 files changed, 230 insertions(+) create mode 100644 examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py diff --git a/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py b/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py new file mode 100644 index 000000000..c679a4cc4 --- /dev/null +++ b/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py @@ -0,0 +1,193 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +"""RTVIObserver ignored sources example. + +This example shows how to suppress RTVI messages from a specific pipeline +processor so that secondary branches don't leak events to the client. + +""" + +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import LLMRunFrame +from pipecat.pipeline.parallel_pipeline import ParallelPipeline +from pipecat.pipeline.pipeline import Pipeline +from pipecat.pipeline.runner import PipelineRunner +from pipecat.pipeline.task import PipelineParams, PipelineTask +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.aggregators.llm_response_universal import ( + LLMContextAggregatorPair, + LLMUserAggregatorParams, +) +from pipecat.processors.audio.vad_processor import VADProcessor +from pipecat.processors.frameworks.rtvi import RTVIObserverParams +from pipecat.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.cartesia.tts import CartesiaTTSService +from pipecat.services.deepgram.stt import DeepgramSTTService +from pipecat.services.openai.llm import OpenAILLMService +from pipecat.transports.base_transport import BaseTransport, TransportParams +from pipecat.transports.daily.transport import DailyParams +from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams +from pipecat.turns.user_turn_processor import UserTurnProcessor +from pipecat.turns.user_turn_strategies import ExternalUserTurnStrategies + +load_dotenv(override=True) + +# We use lambdas to defer transport parameter creation until the transport +# type is selected at runtime. +transport_params = { + "daily": lambda: DailyParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "twilio": lambda: FastAPIWebsocketParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), + "webrtc": lambda: TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + ), +} + + +async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): + logger.info("Starting bot") + + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + # Main LLM — drives the conversation. Its RTVI events reach the client. + main_llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + main_messages = [ + { + "role": "system", + "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.", + }, + ] + + # Evaluator LLM — silently grades the user's message in the background. + # Its RTVI events will be suppressed so the client is unaware of this branch. + evaluator_llm = OpenAILLMService( + api_key=os.getenv("OPENAI_API_KEY"), + name="EvaluatorLLM", + ) + + evaluator_messages = [ + { + "role": "system", + "content": ( + "You are a silent quality evaluator. When given a user message, " + "respond with a single JSON object: " + '{"score": <1-5>, "reason": ""}. ' + "Do not respond conversationally." + ), + }, + ] + + main_context = LLMContext(main_messages) + evaluator_context = LLMContext(evaluator_messages) + + # We use an external VADProcessor because the UserTurnProcessor is shared + # across multiple parallel aggregators. The VADProcessor emits + # VADUserStartedSpeakingFrame and VADUserStoppedSpeakingFrame which the + # UserTurnProcessor needs to manage turn lifecycle. + vad_processor = VADProcessor(vad_analyzer=SileroVADAnalyzer()) + + # We use this external user turn processor. This processor will push + # UserStartedSpeakingFrame and UserStoppedSpeakingFrame as well as + # interruptions. This can be used in advanced cases when there are multiple + # aggregators in the pipeline. + user_turn_processor = UserTurnProcessor() + + # We use external user turn strategies for both aggregators since the turn + # management is done by the common UserTurnProcessor. + main_context_aggregator = LLMContextAggregatorPair( + main_context, + user_params=LLMUserAggregatorParams(user_turn_strategies=ExternalUserTurnStrategies()), + ) + evaluator_context_aggregator = LLMContextAggregatorPair( + evaluator_context, + user_params=LLMUserAggregatorParams(user_turn_strategies=ExternalUserTurnStrategies()), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, # STT + vad_processor, + user_turn_processor, + ParallelPipeline( + # Main branch: speaks to the user. + [ + main_context_aggregator.user(), + main_llm, + tts, + transport.output(), + main_context_aggregator.assistant(), + ], + # Evaluator branch: silent background scoring, no audio output. + [ + evaluator_context_aggregator.user(), + evaluator_llm, + evaluator_context_aggregator.assistant(), + ], + ), + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + rtvi_observer_params=RTVIObserverParams( + ignored_sources=[evaluator_llm] + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info("Client connected") + main_messages.append( + {"role": "system", "content": "Please introduce yourself to the user."} + ) + evaluator_messages.append({"role": "system", "content": "Ready to evaluate user messages."}) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info("Client disconnected") + await task.cancel() + + runner = PipelineRunner(handle_sigint=runner_args.handle_sigint) + + await runner.run(task) + + +async def bot(runner_args: RunnerArguments): + """Main bot entry point compatible with Pipecat Cloud.""" + transport = await create_transport(runner_args, transport_params) + await run_bot(transport, runner_args) + + +if __name__ == "__main__": + from pipecat.runner.run import main + + main() diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py index eb074699a..e01e95714 100644 --- a/src/pipecat/processors/frameworks/rtvi.py +++ b/src/pipecat/processors/frameworks/rtvi.py @@ -25,6 +25,7 @@ from typing import ( Literal, Mapping, Optional, + Set, Tuple, Union, ) @@ -1026,6 +1027,11 @@ class RTVIObserverParams: metrics_enabled: Indicates if metrics messages should be sent. system_logs_enabled: Indicates if system logs should be sent. errors_enabled: [Deprecated] Indicates if errors messages should be sent. + ignored_sources: List of frame processors whose frames should be silently ignored + by this observer. Useful for suppressing RTVI messages from secondary pipeline + branches (e.g. a silent evaluation LLM) that should not be visible to clients. + Sources can also be added and removed dynamically via ``add_ignored_source()`` + and ``remove_ignored_source()``. skip_aggregator_types: List of aggregation types to skip sending as tts/output messages. Note: if using this to avoid sending secure information, be sure to also disable bot_llm_enabled to avoid leaking through LLM messages. @@ -1065,6 +1071,7 @@ class RTVIObserverParams: metrics_enabled: bool = True system_logs_enabled: bool = False errors_enabled: Optional[bool] = None + ignored_sources: List[FrameProcessor] = field(default_factory=list) skip_aggregator_types: Optional[List[AggregationType | str]] = None bot_output_transforms: Optional[ List[ @@ -1110,6 +1117,7 @@ class RTVIObserver(BaseObserver): self._rtvi = rtvi self._params = params or RTVIObserverParams() + self._ignored_sources: Set[FrameProcessor] = set(self._params.ignored_sources) self._frames_seen = set() self._bot_transcription = "" @@ -1170,6 +1178,31 @@ class RTVIObserver(BaseObserver): if not (agg_type == aggregation_type and func == transform_function) ] + def add_ignored_source(self, source: FrameProcessor): + """Ignore all frames pushed by the given processor. + + Any frame whose source matches ``source`` will be silently skipped, + preventing RTVI messages from being emitted for activity in that + processor. Useful for suppressing events from secondary pipeline + branches (e.g. a silent evaluation LLM) that should not be visible + to clients. + + Args: + source: The frame processor to ignore. + """ + self._ignored_sources.add(source) + + def remove_ignored_source(self, source: FrameProcessor): + """Stop ignoring frames pushed by the given processor. + + Reverses a previous call to ``add_ignored_source()``. If ``source`` + was not previously ignored this is a no-op. + + Args: + source: The frame processor to stop ignoring. + """ + self._ignored_sources.discard(source) + def _get_function_call_report_level(self, function_name: str) -> RTVIFunctionCallReportLevel: """Get the report level for a specific function call. @@ -1220,6 +1253,10 @@ class RTVIObserver(BaseObserver): frame = data.frame direction = data.direction + # Frames from explicitly ignored sources are always skipped. + if self._ignored_sources and src in self._ignored_sources: + return + # For broadcast frames (pushed in both directions), only process # the downstream copy to avoid sending duplicate RTVI messages. if frame.broadcast_sibling_id is not None and direction != FrameDirection.DOWNSTREAM: From 18630c94788f18d32b68751c9fe1a9383b6742eb Mon Sep 17 00:00:00 2001 From: filipi87 Date: Thu, 19 Feb 2026 18:41:05 -0300 Subject: [PATCH 2/2] Adding changelog entry for RTVI observer ignored_sources feature. --- changelog/3779.added.md | 1 + .../foundational/53-concurrent-llm-rtvi-ignored-sources.py | 4 +--- 2 files changed, 2 insertions(+), 3 deletions(-) create mode 100644 changelog/3779.added.md diff --git a/changelog/3779.added.md b/changelog/3779.added.md new file mode 100644 index 000000000..8800cfc04 --- /dev/null +++ b/changelog/3779.added.md @@ -0,0 +1 @@ +- Added `ignored_sources` parameter to `RTVIObserverParams` and `add_ignored_source()`/`remove_ignored_source()` methods to `RTVIObserver` to suppress RTVI messages from specific pipeline processors (e.g. a silent evaluation LLM). diff --git a/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py b/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py index c679a4cc4..b16f8831f 100644 --- a/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py +++ b/examples/foundational/53-concurrent-llm-rtvi-ignored-sources.py @@ -156,9 +156,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments): enable_metrics=True, enable_usage_metrics=True, ), - rtvi_observer_params=RTVIObserverParams( - ignored_sources=[evaluator_llm] - ), + rtvi_observer_params=RTVIObserverParams(ignored_sources=[evaluator_llm]), idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, )