From d7ce1eedd956ea320d7fb980172494cb1aa8c3e2 Mon Sep 17 00:00:00 2001 From: zack Date: Fri, 27 Feb 2026 17:58:18 -0500 Subject: [PATCH] Add foundational examples for AssemblyAI u3-rt-pro - 07o-interruptible-assemblyai.py: Basic example using Pipecat VAD mode - 07o-interruptible-assemblyai-stt.py: Advanced example using STT-controlled turn detection with comprehensive documentation on u3-rt-pro features (turn detection tuning, prompt-based enhancement, speaker diarization) --- .../07o-interruptible-assemblyai-stt.py | 175 ++++++++++++++++++ 1 file changed, 175 insertions(+) create mode 100644 examples/foundational/07o-interruptible-assemblyai-stt.py diff --git a/examples/foundational/07o-interruptible-assemblyai-stt.py b/examples/foundational/07o-interruptible-assemblyai-stt.py new file mode 100644 index 000000000..5deaa82a1 --- /dev/null +++ b/examples/foundational/07o-interruptible-assemblyai-stt.py @@ -0,0 +1,175 @@ +# +# Copyright (c) 2024-2026, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + + +import os + +from dotenv import load_dotenv +from loguru import logger + +from pipecat.frames.frames import LLMRunFrame +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.runner.types import RunnerArguments +from pipecat.runner.utils import create_transport +from pipecat.services.assemblyai.models import AssemblyAIConnectionParams +from pipecat.services.assemblyai.stt import AssemblyAISTTService +from pipecat.services.cartesia.tts import CartesiaTTSService +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_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): + """AssemblyAI u3-rt-pro STT Example with STT-Controlled Turn Detection + + This example demonstrates using AssemblyAI's u3-rt-pro Speech-to-Text model + with STT-controlled turn detection for more natural conversation flow. + + Key features: + + 1. STT-Controlled Turn Detection + - Set `vad_force_turn_endpoint=False` to enable STT mode + - AssemblyAI's model determines when user starts/stops speaking + - Uses `ExternalUserTurnStrategies` instead of Pipecat's VAD + - More natural turn detection based on speech patterns and pauses + + 2. Advanced Turn Detection Tuning (STT Mode) + - `min_end_of_turn_silence_when_confident`: Minimum silence (ms) when confident + about end-of-turn. Lower values = faster responses. Default: 200ms + - `max_turn_silence`: Maximum silence (ms) before forcing end-of-turn. + Prevents long pauses. Default: 1000ms + + 3. Prompt-Based Transcription Enhancement + - Use `prompt` parameter to improve accuracy for specific names/terms + - Particularly useful for proper nouns, technical terms, domain vocabulary + - Example: "Names: Xiomara, Saoirse, Krzystof. Technical terms: API, OAuth." + + 4. Speaker Diarization (Optional) + - Enable with `speaker_labels=True` + - Automatically identifies different speakers in multi-party conversations + - TranscriptionFrame includes speaker_id field (e.g., "Speaker A", "Speaker B") + + 5. Language Detection (Optional, multilingual model only) + - Enable with `language_detection=True` + - Automatically detects spoken language + - Available with universal-streaming-multilingual model + + For more information: https://www.assemblyai.com/docs/speech-to-text/streaming + """ + logger.info(f"Starting bot") + + stt = AssemblyAISTTService( + api_key=os.getenv("ASSEMBLYAI_API_KEY"), + vad_force_turn_endpoint=False, # Enable STT-controlled turn detection + connection_params=AssemblyAIConnectionParams( + speech_model="u3-rt-pro", + # Optional: Tune turn detection timing (defaults shown below) + # min_end_of_turn_silence_when_confident=100, # Default + # max_turn_silence=1000, # Default + # Optional: Boost accuracy for specific names/terms + # prompt="Names: Xiomara, Saoirse, Krzystof. Technical terms: API, OAuth.", + # Optional: Enable speaker diarization + # speaker_labels=True, + ), + ) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY"), + voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) + + 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.", + }, + ] + + context = LLMContext(messages) + user_aggregator, assistant_aggregator = LLMContextAggregatorPair( + context, + user_params=LLMUserAggregatorParams(user_turn_strategies=ExternalUserTurnStrategies()), + ) + + pipeline = Pipeline( + [ + transport.input(), # Transport user input + stt, # STT + user_aggregator, # User responses + llm, # LLM + tts, # TTS + transport.output(), # Transport bot output + assistant_aggregator, # Assistant spoken responses + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + enable_metrics=True, + enable_usage_metrics=True, + ), + idle_timeout_secs=runner_args.pipeline_idle_timeout_secs, + ) + + @transport.event_handler("on_client_connected") + async def on_client_connected(transport, client): + logger.info(f"Client connected") + # Kick off the conversation. + messages.append({"role": "system", "content": "Please introduce yourself to the user."}) + await task.queue_frames([LLMRunFrame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"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()