86 lines
2.8 KiB
Python
86 lines
2.8 KiB
Python
import asyncio
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import logging
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import os
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import aiohttp
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from dailyai.pipeline.merge_pipeline import SequentialMergePipeline
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from dailyai.pipeline.pipeline import Pipeline
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from dailyai.transports.daily_transport import DailyTransport
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from dailyai.services.azure_ai_services import AzureLLMService, AzureTTSService
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from dailyai.services.deepgram_ai_services import DeepgramTTSService
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from dailyai.pipeline.frames import EndPipeFrame, LLMMessagesFrame, TextFrame
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from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
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from runner import configure
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from dotenv import load_dotenv
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load_dotenv(override=True)
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logging.basicConfig(format=f"%(levelno)s %(asctime)s %(message)s")
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logger = logging.getLogger("dailyai")
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logger.setLevel(logging.DEBUG)
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async def main(room_url: str):
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async with aiohttp.ClientSession() as session:
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transport = DailyTransport(
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room_url,
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None,
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"Static And Dynamic Speech",
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duration_minutes=1,
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mic_enabled=True,
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mic_sample_rate=16000,
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)
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llm = AzureLLMService(
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api_key=os.getenv("AZURE_CHATGPT_API_KEY"),
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endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"),
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model=os.getenv("AZURE_CHATGPT_MODEL"),
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)
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azure_tts = AzureTTSService(
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api_key=os.getenv("AZURE_SPEECH_API_KEY"),
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region=os.getenv("AZURE_SPEECH_REGION"),
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)
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deepgram_tts = DeepgramTTSService(
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aiohttp_session=session,
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api_key=os.getenv("DEEPGRAM_API_KEY"),
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)
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elevenlabs_tts = ElevenLabsTTSService(
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aiohttp_session=session,
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api_key=os.getenv("ELEVENLABS_API_KEY"),
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voice_id=os.getenv("ELEVENLABS_VOICE_ID"),
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)
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messages = [{"role": "system",
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"content": "tell the user a joke about llamas"}]
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# Start a task to run the LLM to create a joke, and convert the LLM output to audio frames. This task
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# will run in parallel with generating and speaking the audio for static text, so there's no delay to
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# speak the LLM response.
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llm_pipeline = Pipeline([llm, elevenlabs_tts])
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await llm_pipeline.queue_frames([LLMMessagesFrame(messages), EndPipeFrame()])
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simple_tts_pipeline = Pipeline([azure_tts])
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await simple_tts_pipeline.queue_frames(
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[
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TextFrame("My friend the LLM is going to tell a joke about llamas."),
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EndPipeFrame(),
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]
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)
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merge_pipeline = SequentialMergePipeline(
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[simple_tts_pipeline, llm_pipeline])
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await asyncio.gather(
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transport.run(merge_pipeline),
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simple_tts_pipeline.run_pipeline(),
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llm_pipeline.run_pipeline(),
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)
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if __name__ == "__main__":
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(url, token) = configure()
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asyncio.run(main(url))
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