Implement Conversational Fastloop Integration and Clients #11
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jsun-m
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jsun-m
commented
Jul 29, 2025
examples/conversational/client.py
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| import asyncio | |||
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I'm planning to potentially build this client into fastloop as a helper. I'll make a similar one for node js
jsun-m
commented
Jul 29, 2025
| asyncio.create_task(self._handle_websocket_event(websocket, request_id)) | ||
| # llm_manager = LLMManager(self._fastloop, request_id) | ||
| # stt_task = self.executor.submit(stt_manager.on_voice_stream, websocket) | ||
| # tts_manager = TextToSpeechManager(self._fastloop, request_id) |
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i'm pretty sure I will either have tts_manager pipe directly into llm_manager or have it pass it through an event. If we pipe through an event, we can possibly allow for users to intercept it
jsun-m
commented
Jul 29, 2025
| # waiting for the transcription to be generated before sending the next chunk. | ||
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| class ElevenLabsSpeechToTextManager(BaseSpeechToTextManager): |
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eleven labs doesn't have live audio transcription yet but this is a good example of how we can implement it with non realtime api endpoints
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Many limitations from free tier API usage
(probably could be optimized)