Rename examples files, update quickstart

This commit is contained in:
Mark Backman
2025-07-27 16:19:45 -04:00
parent 49af1553e0
commit 16c80b2335
12 changed files with 174 additions and 10 deletions

View File

@@ -0,0 +1,185 @@
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
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.runner.cloud import SmallWebRTCSessionArguments
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
try:
from pipecatcloud.agent import DailySessionArguments, WebSocketSessionArguments
except ImportError:
raise ImportError(
"pipecatcloud package is required for cloud-compatible bots. "
"Install with: pip install pipecat-ai[[pipecatcloud]]"
)
load_dotenv(override=True)
async def run_bot(transport):
"""Main bot logic that works with any transport."""
logger.info(f"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."""
if isinstance(session_args, DailySessionArguments):
from pipecat.transports.services.daily import DailyParams, DailyTransport
transport = DailyTransport(
session_args.room_url,
session_args.token,
"Pipecat Bot",
params=DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
elif isinstance(session_args, SmallWebRTCSessionArguments):
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
transport = SmallWebRTCTransport(
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
webrtc_connection=session_args.webrtc_connection,
)
elif isinstance(session_args, WebSocketSessionArguments):
from pipecat.transports.network.fastapi_websocket import (
FastAPIWebsocketParams,
FastAPIWebsocketTransport,
)
# Create base parameters for telephony
params = FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
add_wav_header=False,
)
# Create appropriate serializer based on transport type
transport_type = getattr(session_args, "transport_type", "unknown")
call_info = getattr(session_args, "call_info", {})
if transport_type == "twilio":
from pipecat.serializers.twilio import TwilioFrameSerializer
params.serializer = TwilioFrameSerializer(
stream_sid=call_info["stream_sid"],
call_sid=call_info["call_sid"],
account_sid=os.getenv("TWILIO_ACCOUNT_SID", ""),
auth_token=os.getenv("TWILIO_AUTH_TOKEN", ""),
)
elif transport_type == "telnyx":
from pipecat.serializers.telnyx import TelnyxFrameSerializer
params.serializer = TelnyxFrameSerializer(
stream_id=call_info["stream_id"],
call_control_id=call_info["call_control_id"],
outbound_encoding=call_info["outbound_encoding"],
inbound_encoding="PCMU",
)
elif transport_type == "plivo":
from pipecat.serializers.plivo import PlivoFrameSerializer
params.serializer = PlivoFrameSerializer(
stream_id=call_info["stream_id"],
call_id=call_info["call_id"],
)
else:
raise ValueError(f"Unsupported WebSocket transport type: {transport_type}")
transport = FastAPIWebsocketTransport(websocket=session_args.websocket, params=params)
else:
raise ValueError(f"Unsupported session arguments type: {type(session_args)}")
await run_bot(transport)
if __name__ == "__main__":
from pipecat.runner.cloud import main
main()