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AI Agent Analysis
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huggingface/speech-to-speech

Build local voice agents with open-source models

stars
12k
Language
Python
GitHub
Source and compliance noteLast synced: Aug 12, 2026

Git-Stars is independent and not affiliated with GitHub or this project. Analysis may be AI-assisted and based on public repository metadata plus short README-derived summaries. We do not mirror full README files, docs, issues, or social comments.

Original GitHub sourceMethodologyEditorial Policy

Overview

Speech To Speech is a modular, low-latency voice-agent pipeline (VAD -> STT -> LLM -> TTS) that exposes an OpenAI Realtime-compatible WebSocket API, allowing developers to build fully local or hybrid voice agents using open-source models.

Installation

pip install speech-to-speech

Problem solved

It solves the fragmentation of building voice agents by providing a fully integrated, swappable pipeline that works with open-source models locally or with hosted providers, avoiding vendor lock-in and enabling privacy-sensitive or offline deployments.

What you can build

Developers can build real-time conversational voice agents, such as customer support bots, personal assistants, or interactive robots (e.g., Reachy Mini). The ceiling includes production-grade, low-latency voice interaction with custom LLMs, STT, and TTS components, all controllable via CLI and compatible with any OpenAI Realtime client.

Community sentiment

Positive

No community feedback yet.

Concerns

No concerns documented yet.

Bottom line

This framework is ideal for developers who want to build voice agents with full control over components and data privacy, using open-source models. It is not for those seeking a fully managed, no-code solution. The key trade-off is flexibility vs. operational complexity of self-hosting.

Analyzed by Git-Stars - 7/29/2026