FEAGI Python SDK

Build AI agents that learn like biological brains

FEAGI Brain Visualizer: spatial brain view, neural architecture graph, and real-time activity

What is FEAGI?

FEAGI (Framework for Evolutionary Artificial General Intelligence) is a biologically inspired, modular neural execution engine designed for embodied AI and robotics. FEAGI enables perception, cognition, and control through spiking neural circuits across simulated and physical embodiments, with a strong emphasis on real-time interaction, modularity, and cross-platform deployment.

FEAGI includes a 3D brain visualizer for real-time neural activity and official open source SDKs for Python (this repository), Rust, and Java. Together they support a growing ecosystem of reusable neural components ("brains"), tools, and integrations for robotics and physical AI.

Neurorobotics Studio is FEAGI's desktop application for working with brains, simulations, and embodiments in a unified environment.

The FEAGI Python SDK

The FEAGI Python SDK provides the tools you need to:

Connect robots and devices to FEAGI's neural network
Build learning agents for robots, simulators, and games
Visualize neural activity in real-time with Brain Visualizer
Control and manage FEAGI from Python code
Interface with diverse embodiments through standardized communication protocols

Quick Start

pip install feagi
feagi start
feagi bv start

That installs the feagi package (engine, Brain Visualizer, and SDK), starts FEAGI with default configuration, and opens the Brain Visualizer. The same flow works on Linux, macOS, and Windows.

Installation

Quick Start uses feagi. If you need a smaller install without Brain Visualizer, use feagi-core instead. Imports are the same for both (from feagi import ...).

Command	What you get
`pip install feagi`	Full install: neuronal engine, Brain Visualizer (adds ~196MB of platform binaries), Rust-backed Python bindings, and the agent SDK. Recommended for most users.
`pip install feagi-core`	Engine, bindings, and agent SDK only—no Brain Visualizer. Recommended for production, CI, or headless setups.

Key Concepts

Neuromorphic by Design – FEAGI is built as a neuromorphic framework inspired by biological neural computation. While it currently runs on conventional CPUs and GPUs, native support for neuromorphic hardware is a near-term roadmap item, enabling direct execution on event-driven, spike-based accelerators as they mature.
Embodied Intelligence First – FEAGI is designed to control bodies (robots, agents, simulations), not just process static data.
Spiking Neural Networks (SNNs) – Uses event-driven neuron firing rather than frame-based inference.
Modular Neural Architecture – Neural circuits can be composed like building blocks (Lego-like micro-circuits).
Real-Time Closed Loop – Continuous perception → cognition → action loop.
Cross-Simulator & Hardware Support – One brain, many bodies.

Documentation

Configuration Management

Initialize FEAGI environment with default configuration:

feagi init

This creates:

Configuration: ~/.feagi/config/feagi_configuration.toml
Genomes directory: ~/Documents/FEAGI/Genomes/ (macOS/Windows) or ~/FEAGI/genomes/ (Linux)
Connectomes directory: ~/Documents/FEAGI/Connectomes/ or ~/FEAGI/connectomes/
Logs and cache directories

For complete configuration options and customization, see DEPLOY.md.

Start FEAGI Engine from Python

from feagi.engine import FeagiEngine

engine = FeagiEngine()
engine.load_config()  # Uses default config
engine.load_genome("my_brain.genome")  # Loads from genomes directory
engine.start()

To restore a trained connectome instead:

engine = FeagiEngine()
engine.load_config()
engine.load_connectome("trained_brain.connectome")
engine.start()

Genome and connectome startup artifacts are mutually exclusive. The equivalent command-line forms are:

feagi start --config ~/.feagi/config/feagi_configuration.toml --genome my_brain.genome
feagi start --config ~/.feagi/config/feagi_configuration.toml --connectome trained_brain.connectome

Download the active brain using the API connection from the selected config. The timeout is explicit so large artifacts do not depend on an implicit network limit:

feagi download genome --output current.genome --timeout <SECONDS>
feagi download connectome --mode full --output current.connectome --timeout <SECONDS>
feagi download connectome --mode lite --output current-lite.connectome --timeout <SECONDS>

Genome artifacts contain JSON but must use .genome. The SDK rejects .json genome filenames; connectome artifacts continue to use .connectome.

SDK Architecture

feagi/
├── agent/           # Agent framework (BaseAgent)
├── pns/             # Peripheral Nervous System (communication)
├── engine/          # Engine control
├── config/          # Configuration management
├── paths/           # Cross-platform path utilities
├── cli/             # Command-line tools
├── genome/          # Genome artifact I/O, validation, and live operations
├── connectome/      # Connectome artifact I/O, migration, and live operations
└── packaging/       # Marketplace packages (coming soon)

Examples

See examples/ for complete agent implementations:

Basic sensory agent
Robot agent (SDK-based)
Simulator agent (Webots)
Vision processing

Community & Support

Discord: Join our community
Issues: Report bugs
Neurorobotics Studio: Design and deployment desktop application
Homepage: feagi.org

Requirements

Python 3.10 or higher
Works on Linux, macOS, and Windows

License

Apache 2.0 - See LICENSE for details.

About Neuraville

FEAGI is developed by Neuraville, a company focused on democratizing robotics and enabling the next generation of embodied AI through modular, biologically inspired intelligence systems.

Metadata

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