AudioCraft

Top Builders

Explore the top contributors showcasing the highest number of app submissions within our community.

Meta AudioCraft: Audio Processing and Generation Library

Welcome to the ultimate destination for groundbreaking audio technology. Crafted meticulously by Meta, AudioCraft is a cutting-edge library for deep learning-powered audio generation and research.

General
Author	Meta
Repository	https://github.com/facebookresearch/audiocraft
Type	The library for audio processing and generation

What is AudioCraft?

AudioCraft is a next-gen library revolutionizing the audio industry with its array of features. It's not just an audio library, it's the future of audio.

Key Features:

Advanced Audio Generation Models: With models like AudioGen and MusicGen, prepare to experience unparalleled audio quality.
EnCodec: An innovative audio compressor and tokenizer that is setting a new standard in audio processing.

Capabilities:

Generative Audio Needs: A comprehensive code base for all generative audio needs - be it music, sound effects, or compression after training on raw audio signals.
Simplified Model Design: The model design, especially for MusicGen and AudioGen, is simplified compared to previous generative models. With a single autoregressive Language Model (LM) that operates on compressed discrete music representation, or tokens, AudioCraft efficiently captures long-term dependencies in audio for high-quality generation.
EnCodec: A unique neural audio codec that converts audio signals to discrete tokens and vice-versa. It acts as the bridge between the raw waveform and the autoregressive language model.
Text-to-sound Generation: With AudioGen, you can convert text into environmental sounds.
Text-to-music Generation: MusicGen brings texts to life by crafting diverse, enchanting melodies based on the provided textual cues.

AI Tutorials

Audiocraft tutorial: How to create music with Audiocraft

👉 Discover more AudioCraft Tutorials on lablab.ai

AudioCraft Resources

A curated list of libraries and technologies to help you build great projects with AudioCraft.

Installation Guide: Get started with AudioCraft using the detailed guide on GitHub.
Models Overview:
- MusicGen - A top-tier controllable text-to-music model.
- AudioGen - A groundbreaking text-to-sound model.
- EnCodec - A high fidelity neural audio codec.
- Multi Band Diffusion - An EnCodec compatible decoder using diffusion.
API Documentation: Delve deeper into the features, functionalities, and integrations with the detailed API Documentation.
Meta Intro Article: Understand the technology, its creation, and its capabilities with this Meta Intro Article.

Edit on GitHub

AudioCraft AI technology page Hackathon projects

Discover innovative solutions crafted with AudioCraft AI technology page, developed by our community members during our engaging hackathons.

LabPiolet AI

LabPilot AI is an AI powered Laboratory Safety Assistant designed to improve safety, hazard awareness. It addresses a common problem where students and researchers often lack immediate access to accurate laboratory safety guidance while handling chemicals, biological materials, and laboratory equipment. By combining scientific knowledge with artificial intelligence, the platform delivers quick, reliable, and user friendly safety assistance to help reduce laboratory accidents. The project's aim is to promote safer laboratory practices through intelligent guidance. Its objectives include identifying chemical hazards, recommending appropriate Personal Protective Equipment (PPE), providing biology and physics safety guidance, supporting laboratory risk assessment, generating safety reports, and answering laboratory related questions through an AI assistant. Key features include AI powered laboratory consultation, chemical hazard search, PPE recommendations, chemistry, biology and physics safety modules, laboratory safety reports, dashboard analytics, voice search prototype, downloadable reports, and a simple, responsive interface for students and researchers. LabPilot AI was developed using HTML, CSS, JavaScript, Node.js, Express.js, REST APIs, Git, GitHub, and Fireworks AI for language model integration. Building the project required extensive effort in frontend and backend development, AI integration. The vision is to evolve LabPilot AI into a digital laboratory companion for universities, research institutions, pharmaceutical and biotechnology industries. Future versions will include multilingual support, image based hazard detection, Safety Data Sheet integration, cloud databases, experiment risk prediction, and laboratory monitoring. The project demonstrates how artificial intelligence can enhance laboratory education, improve compliance with safety standards, reduce human error, and create safer research environments through accessible and intelligent technology.

GhostWriter OCR: AI-Powered

GhostWriter OCR: Next-Gen AI Document Intelligence GhostWriter OCR is an advanced, agentic document processing platform designed to bridge the gap between messy, handwritten physical records and structured digital intelligence. While traditional OCR (Optical Character Recognition) simply converts images to text, GhostWriter goes a step further by interpreting intent, context, and compliance in real-time. Built to leverage the high-compute capabilities of AMD hardware, this project targets "high-stakes" industries like healthcare, legal services, and logistics, where handwritten forms remain a primary bottleneck. Key Features & Innovation Intent-Aware Extraction: GhostWriter doesn’t just read words; it understands fields. It can distinguish between a signature, a date of birth, and a medical prescription, mapping them to structured JSON/Database formats automatically. Agentic Verification: If the AI detects a smudge, a missing signature, or contradictory information (e.g., a "Date of Birth" that is in the future), an autonomous agent proactively flags the error. It can even generate a "Human-in-the-loop" notification to ask the user for clarification before the data is committed. Edge-Optimized Privacy: By utilizing AMD ROCm and local GPU acceleration, GhostWriter processes sensitive documents locally. This ensures that private data—like medical records or legal contracts—never needs to leave the local environment for cloud processing. Dynamic Document Reconstruction: Using a MERN-based dashboard, users can see a side-by-side comparison of the original scan and the digitized version, with "confidence scores" highlighted for every field. Technical Excellence GhostWriter is engineered for speed. By offloading the heavy lifting of Multi-modal Large Language Models onto AMD’s Developer Cloud infrastructure, we achieve near-instantaneous processing of multi-page documents. The frontend is a sleek, minimalist React interface, while the backend utilizes Node.js and

My FlashDeal Star: Voice-First Agentic Economy Hub

My FlashDeal Star** is more than just a payment app; it is a comprehensive agentic ecosystem designed to bridge the gap between human intent and instant execution. Built on the pillars of "Talk. Pay. Done.", it leverages advanced LLM agents to handle complex financial exchanges, smart home management, and vehicle control through a single, intuitive voice interface. > The project features a unique **"Cyber-Glass"** UI, ensuring a premium user experience. Security is paramount, integrated through a multi-layer biometric system (Face, Fingerprint, and Voice) coupled with a proprietary **"Mutual Token"** engine. Whether you are concluding a global trade deal or starting your car, **FlashDeal Star** acts as your personal autonomous conductor in the growing Agentic Economy.

ATLAS AI TRADING AGENT

ATLAS Swarm is a paradigm shift in how AI-driven automated trading operates. Most algorithmic trading bots operate in black boxes with no verifiable accountability. ATLAS changes this by requiring a multi-agent swarm to reach strict consensus before any trade is executed. We utilized Lang Graph to orchestrate specialized agents ranging from data accumulation nodes to sentiment analysts. Once the agent network identifies a profitable trade, it relies on the ERC-8004 identity registry deployed on Base Spolia. By securely tying the execution layer to a verifiable on-chain AI identity, every trade intent becomes cryptographically signed (EIP-712). Finally, for actual execution, we natively integrated the official Kraken CLI module into our workflow to handle programmatic paper trading. Our custom dashboard visualizes this entire flow: from the real-time swarm debate log to the final verified signature. This creates a fully accountable and transparent AI trading network.