wehub-resource-sync
94 lines
4.0 KiB
Python
94 lines
4.0 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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import logging
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from samples.concepts.realtime.utils import AudioPlayerWebsocket, AudioRecorderWebsocket, check_audio_devices
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from semantic_kernel.connectors.ai.open_ai import (
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AzureRealtimeExecutionSettings,
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AzureRealtimeWebsocket,
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ListenEvents,
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)
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from semantic_kernel.contents import RealtimeAudioEvent, RealtimeTextEvent
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logging.basicConfig(level=logging.WARNING)
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utils_log = logging.getLogger("samples.concepts.realtime.utils")
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utils_log.setLevel(logging.INFO)
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logger = logging.getLogger(__name__)
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logger.setLevel(logging.INFO)
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"""
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This simple sample demonstrates how to use the OpenAI Realtime API to create
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a chat bot that can listen and respond directly through audio.
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It requires installing:
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- semantic-kernel[realtime]
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- pyaudio
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- sounddevice
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- pydub
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e.g. pip install pyaudio sounddevice pydub semantic-kernel[realtime]
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For more details of the exact setup, see the README.md in the realtime folder.
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"""
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# The characterics of your speaker and microphone are a big factor in a smooth conversation
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# so you may need to try out different devices for each.
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# you can also play around with the turn_detection settings to get the best results.
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# It has device id's set in the AudioRecorderStream and AudioPlayerAsync classes,
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# so you may need to adjust these for your system.
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# you can disable the check for available devices by commenting the line below
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check_audio_devices()
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async def main() -> None:
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# create the realtime client and optionally add the audio output function, this is optional
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# you can define the protocol to use, either "websocket" or "webrtc"
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# they will behave the same way, even though the underlying protocol is quite different
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settings = AzureRealtimeExecutionSettings(
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instructions="""
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You are a chat bot. Your name is Mosscap and
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you have one goal: figure out what people need.
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Your full name, should you need to know it, is
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Splendid Speckled Mosscap. You communicate
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effectively, but you tend to answer with long
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flowery prose.
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""",
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# there are different voices to choose from, since that list is bound to change, it is not checked beforehand,
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# see https://platform.openai.com/docs/api-reference/realtime-sessions/create#realtime-sessions-create-voice
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# for more details.
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voice="shimmer",
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)
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# Note: api_version (either through settings or directly in the client) must be set to "2025-08-28"
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# for Azure OpenAI deployments realtime deployments.
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realtime_client = AzureRealtimeWebsocket(
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settings=settings,
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)
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audio_player = AudioPlayerWebsocket()
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audio_recorder = AudioRecorderWebsocket(realtime_client=realtime_client)
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# Create the settings for the session
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# the context manager calls the create_session method on the client and starts listening to the audio stream
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async with audio_player, audio_recorder, realtime_client:
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async for event in realtime_client.receive():
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match event:
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# this can be used as an alternative to the callback function used in other samples,
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# the callback is faster and smoother
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case RealtimeAudioEvent():
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await audio_player.add_audio(event.audio)
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case RealtimeTextEvent():
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# the model returns both audio and transcript of the audio, which we will print
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print(event.text.text, end="")
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case _:
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# OpenAI Specific events
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if event.service_type == ListenEvents.SESSION_UPDATED:
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print("Session updated")
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if event.service_type == ListenEvents.RESPONSE_CREATED:
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print("\nMosscap (transcript): ", end="")
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if __name__ == "__main__":
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print(
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"Instructions: Start speaking when you see 'Session updated.' "
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"The model will detect when you stop and automatically start responding. "
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"Press ctrl + c to stop the program."
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)
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asyncio.run(main())
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