cdb909958c
Introduce a new example `26d-gemini-multimodal-live-text.py` to demonstrate the use of GeminiMultimodalLiveLLMService with text-only responses. This example sets up a pipeline for audio input via DailyTransport, processing with Gemini, and output via Cartesia TTS.
86 lines
2.5 KiB
Python
86 lines
2.5 KiB
Python
#
|
|
# Copyright (c) 2024, Daily
|
|
#
|
|
# SPDX-License-Identifier: BSD 2-Clause License
|
|
#
|
|
|
|
import asyncio
|
|
import os
|
|
import sys
|
|
|
|
import aiohttp
|
|
from dotenv import load_dotenv
|
|
from loguru import logger
|
|
from runner import configure
|
|
|
|
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
|
from pipecat.audio.vad.vad_analyzer import VADParams
|
|
from pipecat.pipeline.pipeline import Pipeline
|
|
from pipecat.pipeline.runner import PipelineRunner
|
|
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
|
from pipecat.services.gemini_multimodal_live.gemini import GeminiMultimodalLiveLLMService
|
|
from agent.services.tts.cartesia_multilingual import CartesiaMultiLingualTTSService
|
|
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
|
|
|
load_dotenv(override=True)
|
|
|
|
logger.remove(0)
|
|
logger.add(sys.stderr, level="DEBUG")
|
|
|
|
|
|
async def main():
|
|
async with aiohttp.ClientSession() as session:
|
|
(room_url, token) = await configure(session)
|
|
|
|
transport = DailyTransport(
|
|
room_url,
|
|
token,
|
|
"Respond bot",
|
|
DailyParams(
|
|
audio_in_sample_rate=16000,
|
|
audio_out_sample_rate=24000,
|
|
audio_out_enabled=True,
|
|
vad_enabled=True,
|
|
vad_audio_passthrough=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)),
|
|
),
|
|
)
|
|
|
|
llm = GeminiMultimodalLiveLLMService(
|
|
api_key=os.getenv("GOOGLE_API_KEY"),
|
|
# system_instruction="Talk like a pirate."
|
|
)
|
|
llm.set_model_only_text() # This forces model to produce text only responses
|
|
|
|
tts = CartesiaMultiLingualTTSService(api_key=os.getenv("CARTESIA_API_KEY"))
|
|
|
|
pipeline = Pipeline(
|
|
[
|
|
transport.input(),
|
|
llm,
|
|
tts,
|
|
transport.output(),
|
|
]
|
|
)
|
|
|
|
task = PipelineTask(
|
|
pipeline,
|
|
PipelineParams(
|
|
allow_interruptions=True,
|
|
enable_metrics=True,
|
|
enable_usage_metrics=True,
|
|
),
|
|
)
|
|
|
|
runner = PipelineRunner()
|
|
|
|
await runner.run(task)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
asyncio.run(main())
|