Add create_transport factory method example

This commit is contained in:
Mark Backman
2025-07-30 08:53:24 -04:00
parent 46c520bb36
commit 58fc952192

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@@ -0,0 +1,152 @@
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
"""Pipecat Cloud-compatible bot example.
Transports are:
- Daily
- SmallWebRTC
- Twilio
- Telnyx
- Plivo
"""
import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
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 TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
try:
from pipecatcloud.agent import DailySessionArguments, WebSocketSessionArguments
from pipecat.runner.run import SmallWebRTCSessionArguments
from pipecat.runner.utils import create_transport
except ImportError:
raise ImportError("Install with: pip install pipecat-ai[runner]")
load_dotenv(override=True)
# Define transport configurations using factory functions
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
# add_wav_header and serializer will be set automatically
),
"telnyx": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
# add_wav_header and serializer will be set automatically
),
"plivo": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
# add_wav_header and serializer will be set automatically
),
}
async def run_bot(transport):
"""Main bot logic that works with any transport."""
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
)
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
messages = [
{
"role": "system",
"content": "You are a friendly AI assistant. Respond naturally and keep your answers conversational.",
},
]
context = OpenAILLMContext(messages)
context_aggregator = llm.create_context_aggregator(context)
rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
pipeline = Pipeline(
[
transport.input(),
rtvi,
stt,
context_aggregator.user(),
llm,
tts,
transport.output(),
context_aggregator.assistant(),
]
)
task = PipelineTask(
pipeline,
params=PipelineParams(
enable_metrics=True,
enable_usage_metrics=True,
),
observers=[RTVIObserver(rtvi)],
)
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info("Client connected")
messages.append({"role": "system", "content": "Say hello and briefly introduce yourself."})
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info("Client disconnected")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
await runner.run(task)
async def bot(
session_args: DailySessionArguments | SmallWebRTCSessionArguments | WebSocketSessionArguments,
):
"""Main bot entry point compatible with Pipecat Cloud."""
transport = await create_transport(session_args, transport_params)
await run_bot(transport)
if __name__ == "__main__":
from pipecat.runner.run import main
main()