153 lines
5.4 KiB
Python
153 lines
5.4 KiB
Python
#
|
||
# Copyright (c) 2024–2025, 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.audio.vad.vad_analyzer import VADParams
|
||
from pipecat.frames.frames import TranscriptionMessage
|
||
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.transcript_processor import TranscriptProcessor
|
||
from pipecat.runner.types import RunnerArguments
|
||
from pipecat.runner.utils import create_transport
|
||
from pipecat.services.gemini_multimodal_live.gemini import GeminiMultimodalLiveLLMService
|
||
from pipecat.transports.base_transport import BaseTransport, TransportParams
|
||
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
|
||
from pipecat.transports.services.daily import DailyParams
|
||
|
||
load_dotenv(override=True)
|
||
|
||
|
||
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
|
||
# instantiated. The function will be called when the desired transport gets
|
||
# selected.
|
||
transport_params = {
|
||
"daily": lambda: DailyParams(
|
||
audio_in_enabled=True,
|
||
audio_out_enabled=True,
|
||
# set stop_secs to something roughly similar to the internal setting
|
||
# of the Multimodal Live api, just to align events. This doesn't really
|
||
# matter because we can only use the Multimodal Live API's phrase
|
||
# endpointing, for now.
|
||
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)),
|
||
),
|
||
"twilio": lambda: FastAPIWebsocketParams(
|
||
audio_in_enabled=True,
|
||
audio_out_enabled=True,
|
||
# set stop_secs to something roughly similar to the internal setting
|
||
# of the Multimodal Live api, just to align events. This doesn't really
|
||
# matter because we can only use the Multimodal Live API's phrase
|
||
# endpointing, for now.
|
||
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)),
|
||
),
|
||
"webrtc": lambda: TransportParams(
|
||
audio_in_enabled=True,
|
||
audio_out_enabled=True,
|
||
# set stop_secs to something roughly similar to the internal setting
|
||
# of the Multimodal Live api, just to align events. This doesn't really
|
||
# matter because we can only use the Multimodal Live API's phrase
|
||
# endpointing, for now.
|
||
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)),
|
||
),
|
||
}
|
||
|
||
|
||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||
logger.info(f"Starting bot")
|
||
|
||
llm = GeminiMultimodalLiveLLMService(
|
||
api_key=os.getenv("GOOGLE_API_KEY"),
|
||
voice_id="Aoede", # Puck, Charon, Kore, Fenrir, Aoede
|
||
# system_instruction="Talk like a pirate."
|
||
# inference_on_context_initialization=False,
|
||
)
|
||
|
||
context = OpenAILLMContext(
|
||
[
|
||
{
|
||
"role": "user",
|
||
"content": "Say hello. Then ask if I want to hear a joke.",
|
||
},
|
||
# {"role": "assistant", "content": "Hello! Why don't scientists trust atoms?"},
|
||
# {
|
||
# "role": "user",
|
||
# "content": [
|
||
# {
|
||
# "type": "text",
|
||
# "text": "Oh, I know this one: because they make up everything.",
|
||
# }
|
||
# ],
|
||
# },
|
||
],
|
||
)
|
||
context_aggregator = llm.create_context_aggregator(context)
|
||
|
||
transcript = TranscriptProcessor()
|
||
|
||
pipeline = Pipeline(
|
||
[
|
||
transport.input(),
|
||
context_aggregator.user(),
|
||
transcript.user(),
|
||
llm,
|
||
transport.output(),
|
||
transcript.assistant(),
|
||
context_aggregator.assistant(),
|
||
]
|
||
)
|
||
|
||
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.
|
||
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(f"Client disconnected")
|
||
await task.cancel()
|
||
|
||
# Register event handler for transcript updates
|
||
@transcript.event_handler("on_transcript_update")
|
||
async def on_transcript_update(processor, frame):
|
||
for msg in frame.messages:
|
||
if isinstance(msg, TranscriptionMessage):
|
||
timestamp = f"[{msg.timestamp}] " if msg.timestamp else ""
|
||
line = f"{timestamp}{msg.role}: {msg.content}"
|
||
logger.info(f"Transcript: {line}")
|
||
|
||
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()
|