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✨ Fully autonomous AI Agent that can perform complicated tasks and projects using terminal, browser, and editor.

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Fully autonomous AI Agent that can perform complicated tasks and projects using terminal, browser, and editor.

Discord: https://discord.gg/uMaGSHNjzc

Features

  • 🔓 Secure. Everything is running in a sandboxed Docker environment.
  • 🤖 Autonomous. Automatically detects the next step and performs it.
  • 🔍 Built-in browser. Fetches latest information from the web (tutorials, docs, etc.) if needed.
  • 📙 Built-in text editor. View all the modified files right in your browser.
  • 🧠 All the history commands and outputs are saved in the PostgreSQL database.
  • 📦 Automatic Docker-image picker based on the user task.
  • 🤳 Self-hosted
  • 💅 Modern UI

How to run

Prerequisites

  • golang
  • nodejs
  • docker
  • postgresql

Environment variables

Add to .env file in the backend folder.

Backend

  • OPEN_AI_KEY - OpenAI API key
  • DATABASE_URL - PostgreSQL database URL (eg. postgres://user:password@localhost:5432/database)
  • DOCKER_HOST - Docker SDK API (eg. DOCKER_HOST=unix:///Users/<my-user>/Library/Containers/com.docker.docker/Data/docker.raw.sock) more info

Optional:

  • OPEN_AI_MODEL - OpenAI model (default: gpt-4-0125-preview). The list of supported OpenAI models can be found here.

Frontend

Frontend environment variables can be set by creating a .env.local file in the frontend folder.

  • VITE_API_URL - Backend API URL. Omit the URL scheme (e.g., localhost:8080 NOT http://localhost:8080).

Steps

  • Run go run . in backend folder
  • Run yarn dev in frontend folder
  • Open your browser and enjoy!

Roadmap

  • Agent API
  • Frontend
  • Backend API + PostgreSQL integration
  • Docker runner
  • Terminal output streaming
  • Editor output
  • SWE-bench
  • Better way to run it (eg a single docker command)

See more detailed roadmap here.

Credits

This project wouldn't be possible without:

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