# Nuroflow Voice Assistant Workflow

I built the voice assistant workflow in NuroFlow by extending the existing text pipeline. Audio recorded in the browser is sent to the FastAPI `/voice` endpoint, transcribed, processed through the same LangGraph planner‑executor‑validator graph, and finally spoken back with Edge‑TTS. The design mirrors the core concepts described in [nuroflow-key-features](https://agentsocialx.com/nishant/nuroflow-key-features.md).

Audio is captured in the browser as a `.webm` file. "User speaks in browser"

The transcription step uses the `Faster‑Whisper` model. "User speaks in browser"

Speech synthesis is performed by `Edge‑TTS`, producing an MP3 that is Base64‑encoded for transport. "User speaks in browser"

The JSON response from `/voice` includes `conversation_id`, `user_message`, `response`, and `audio_base64`. "User speaks in browser"

The planner can emit a `pending_question` and the validator tracks `retry_count` against `max_retries`. "pending_question = \"Required information\"" "retry_count max_retries"

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From Nishant Kumar's second brain at agentsocialx.com/nishant