LibreAI / Agents IA / Voyager
// agents · MineDojo/Voyager

Voyager

Voyager est un projet de agents IA open source, créé par MineDojo (MineDojo/Voyager sur GitHub). Il compte 7 250 étoiles sur GitHub et 706 forks, il est publié sous la licence MIT et a été mis à jour pour la dernière fois sur GitHub le 3 avril 2024.

Voyager — the open-ended embodied Minecraft agent that writes its own skills and keeps learning for life.

★ 7,2 k étoiles⑂ 706 forksMITmis à jour avr. 2024
▦ visuel — le README de ce projet ne contient aucune capture intégrable,
voici donc un emplacement réservé. Le guide ci-dessous est complet malgré tout.
// détails du projet

Détails du projet

Étoiles GitHub
7 250
Forks
706
Licence
MIT
Dernière mise à jour sur GitHub
3 avril 2024
Catégorie
Agents IA
Type de fiche
Guide d'installation complet
Site officiel
Official site
// fonctionnement

Comment ça marche

  1. Clarify your goal

    Set up the full environment first — Minecraft instance, Fabric mods, Node and Python parts — and decide whether to start lifelong learning fresh or resume from a checkpoint/skill library.

  2. Get the project

    Clone MineDojo/Voyager from GitHub (or use the install path in the run steps below) and skim its README for the parts relevant to your goal.

  3. Install and configure

    Follow the README's four install parts in order: Python install, Node.js install, Minecraft instance install, and Fabric mods install.

  4. Run your first task

    Start lifelong learning, watch Voyager propose and attempt its first tasks, and inspect the skills it writes into its library.

// fonctionnalités

Pourquoi on l'adore

Lifelong learning in Minecraft

An agent that continuously explores, learns new skills and takes on harder tasks without a fixed endpoint.

Executable skill library

Learned skills are stored as code in a skill library and reused — you can also load a learned library to run specific tasks.

Automatic curriculum

Voyager proposes its own next tasks based on its progress, rather than following a hand-written task list.

Iterative prompting with feedback

Environment feedback and execution errors feed back into prompting so the agent debugs its own attempts.

Checkpoint resume

Learning can resume from a checkpoint, and a learned skill library can be pointed at a new specific task.

Paper-backed research code

The official codebase for the Voyager paper, with the project site and arXiv paper linked from the repo.

Advertisement
// lancez-le

Lancez-le vous-même

  1. Clone the repository

    Get the source from the official GitHub repository for Voyager.

    git clone https://github.com/MineDojo/Voyager.git
    cd Voyager
  2. Install the components

    Complete the Python and Node.js installs from the README, including the package install and TypeScript build steps it lists.

    pip install -e .
    npm install
  3. Start lifelong learning

    With the Minecraft instance and Fabric mods running and your login configured, start Voyager's lifelong learning from the README's getting-started code.

    # Configure azure_login (recommended) in the getting-started snippet, then start lifelong learning — see README
// cas d'usage

Ce que vous pouvez créer

Advertisement
// faq

Questions fréquentes

Who maintains Voyager?

MineDojo, through the MineDojo/Voyager repository, with the project site at voyager.minedojo.org.

Is Voyager free to use?

Yes — the project is open source under the MIT license as recorded for this listing. You can use, modify and distribute it under the MIT terms.

Does Voyager need a paid API key?

Voyager's reasoning is driven by an LLM, so you need the model access its setup requires (the README recommends Azure login for the Minecraft connection and its GPT-class model setup); the code is free under MIT.

How does Voyager compare to a scripted Minecraft bot?

Scripted bots (for example Mineflayer scripts) do exactly what you coded. Voyager writes, tests and stores its own skills under an automatic curriculum — a research system for open-ended learning, with a much heavier setup than a bot script.

How do I get started with Voyager?

Clone the repository (or use the documented installer), follow the install and configure steps on this page, and run the smallest real task first — start lifelong learning, watch Voyager propose and attempt its first tasks, and inspect the skills it writes into its library.

// continuez l'exploration

Outils similaires

Agents IA

SkillSpector

NVIDIA's security scanner for AI agent skills - check before you install

★ 19,7 k étoilesApache-2.0
Voir le guide →
Agents IA

openwiki

A CLI that writes and maintains agent-ready docs for your codebase.

★ 17,0 k étoilesMIT
Voir le guide →
Agents IA

Auto-Company

An auto-company that works 24/7 on your own PC — 14 agent roles, a dashboard, real workflows.

★ 3,1 k étoilesMIT
Voir le guide →
Agents IA

dash

Agno's self-learning data agent: grounded text-to-SQL answers over your database that improve with use.

★ 2,3 k étoilesApache-2.0
Voir le guide →
Agents IA

gini-agent

Gini: a personal agent runtime that remembers, learns skills, and reaches you with the right control in time.

★ 1,9 k étoilesMIT
Voir le guide →
Agents IA

chops

Run chops locally: your ai agent skills, finally organized. a macos app to.

★ 1,9 k étoilesNOASSERTION
Voir le guide →
// alternatives

Alternatives en Agents IA

Les autres projets de la catégorie Agents IA avec le plus d'étoiles du catalogue LibreAI — la sélection réaliste d'alternatives si Voyager ne vous convient pas.

// plus en agents

Plus en Agents IA

Projets de la catégorie Agents IA proches dans le catalogue, les plus proches en étoiles de Voyager — continuez à explorer de part et d'autre.

Obtenir Voyager

Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.