98 lines
3.7 KiB
Python
98 lines
3.7 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.pipeline import Pipeline
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from dailyai.services.daily_transport_service import DailyTransportService
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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 EndFrame, LLMMessagesQueueFrame
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from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
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from examples.support.runner import configure
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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 = DailyTransportService(
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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", "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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buffer_queue = asyncio.Queue()
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source_queue = asyncio.Queue()
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pipeline = Pipeline(
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source=source_queue, sink=buffer_queue, processors=[llm, elevenlabs_tts]
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)
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await source_queue.put(LLMMessagesQueueFrame(messages))
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await source_queue.put(EndFrame())
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pipeline_run_task = pipeline.run_pipeline()
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@transport.event_handler("on_first_other_participant_joined")
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async def on_first_other_participant_joined(transport):
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await azure_tts.say(
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"My friend the LLM is now going to tell a joke about llamas.",
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transport.send_queue,
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)
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# khk: deepgram_tts.say() doesn't seem to put bytes in the transport
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# queue. I get a debug log line that indicates we're set up okay, but
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# no further log lines or audio bytes. debug this later:
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# 20 2024-03-10 13:24:46,235 Running deepgram tts for My friend the LLM is now going to tell a joke about llamas.
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# await deepgram_tts.say(
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# "My friend the LLM is now going to tell a joke about llamas.",
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# transport.send_queue,
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# )
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async def buffer_to_send_queue():
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while True:
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frame = await buffer_queue.get()
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await transport.send_queue.put(frame)
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buffer_queue.task_done()
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if isinstance(frame, EndFrame):
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break
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await asyncio.gather(pipeline_run_task, buffer_to_send_queue())
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await transport.stop_when_done()
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await transport.run()
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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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