Fast-Voice-Assistant

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fast-voice-assistant is a GitHub repository for building AI voice assistants. It enables developers to create low-latency voice assistants with sub-500ms response times.

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At a glance

Pricing

open-source

Free tier

Yes

API

—

Skill level

Technical

About

What is fast-voice-assistant?

fast-voice-assistant is an open-source project available on GitHub, designed to help developers create highly responsive AI voice assistants. The repository provides the necessary tools and framework to achieve response times under 500 milliseconds. It integrates several advanced technologies, including LiveKit for transport, Deepgram for Speech-to-Text (STT) conversion, Cerebras for Large Language Model (LLM) processing, and Cartesia for Text-to-Speech (TTS) generation. This combination allows developers to build and experiment with cutting-edge, low-latency voice assistant applications.

Best used for

Building and experimenting with low-latency AI voice assistants.

Common actions

Build voice assistants

Experiment with AI

Achieve low latency

Integrate STT/TTS

Develop AI applications

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Capabilities

Key features

Sub-500ms response times
LiveKit transport
Deepgram STT
Cerebras LLM
Cartesia TTS

Target Audience

DevelopersAI EngineersResearchers

Integrations

Not yet documented

Pricing & Plans

open-source

Free

FAQs

What are the primary costs associated with deploying a fast-voice-assistant, given it's open-source?

While fast-voice-assistant is open-source, you will incur costs for the integrated services like Deepgram (STT), Cerebras (LLM), and Cartesia (TTS), as well as hosting for LiveKit and your application. These are typically usage-based.

Can I swap out the default Deepgram, Cerebras, or Cartesia integrations for other providers?

Yes, the project is designed to be modular. While it provides examples with these specific services, developers can integrate alternative STT, LLM, or TTS providers by modifying the relevant components in the codebase.

What kind of technical expertise is required to set up and customize fast-voice-assistant?

Setting up and customizing fast-voice-assistant requires advanced development skills, including proficiency in programming (likely Python/TypeScript), understanding of real-time communication protocols, and experience with API integrations for STT, LLM, and TTS services.

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