A simulated fruit-fly brain (FlyWire connectome) plays Game Boy games on a 24/7 stream.
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acamilo d324ec825a fly-edge: serve the feed WebSocket from the feed bus
A new workspace binary. It reads flysim's own configuration (same env file,
same FLY_FEED_BIND, FLY_BUS_DIR and idle cadence), subscribes to
fly.feed.snapshots as fly-edge with one latest slot and one delivery in
flight, turns each publication back into a Snapshot with feedbus::receive and
serves it through flysim's feed::router, so hello, wants, drop-oldest and the
2 Hz idle header are flysim's code and the bytes are flysim's bytes.

The port is bound only once the first snapshot has arrived, and when the bus
goes away every client is dropped and the port unbound, which is what a
stopped flysim looks like to the stage; then it reconnects every 500 ms.
FLY_EDGE_METRICS_ADDR serves /metrics (fly_frames_sent_total and
fly_feed_clients under their flysim names, plus fly_edge_*) and /healthz.
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flybrain

A simulated fruit-fly brain that plays video games. A connectome-constrained spiking network reads the screen, its population rates become controller inputs, and a scalar reward nudges a bounded set of Kenyon-cell to MBON gains.

The library is @flybrain/brain in packages/brain. It holds the connectome dataset format, the LIF kernel, the plasticity rule, the population-rate readout and the activity-map geometry. It holds no game, no emulator and no reward rules: those belong to whatever embeds it.

Workspace layout

Path Contents
packages/brain the library (@flybrain/brain)
data/fafb-v783 FlyWire-derived browser artifacts (CC BY-NC 4.0)
tools/ the Python builder that regenerates data/ from official Codex exports
docs/ overview, dataset format, model, plasticity, readout, integration, limitations, verification
services/flysim the Rust service: brain, emulator, snapshot feed, control API, checkpoints
apps/ planned: one directory per game demo
infra/ planned: deployment for the 24/7 stream (see docs/streaming-plan.md)

Quick start

npm ci
npm test
npm run typecheck

76 tests, about 7 seconds. There is no build step. npx tsx packages/brain/examples/node-random-frames.ts 60 runs the full 139,255-neuron brain with the Game Boy readout on noise frames in plain Node (about 0.9x Game Boy real time single-threaded on a WSL laptop).

Usage

import { NeuralAgent, gameboyDecoderConfig, toButtonMask } from '@flybrain/brain';
import { loadBrainDatasetFromDir } from '@flybrain/brain/node';

const dataset = await loadBrainDatasetFromDir('data/fafb-v783');
const agent = new NeuralAgent(dataset, { decoder: gameboyDecoderConfig() });
agent.warmup(firstFrame);                        // 2,500 ms with plasticity off, then calibrate

// every emulator frame:
const { active } = agent.tick(framebuffer, {     // RGBA 160x144 by default; any size via config
  rewards: [{ value: 0.5 }],                     // scalar rewards your game adapter detected
  boot: !inGame,                                 // relaxes Start/Select throttling on title screens
});
emulator.setButtons(toButtonMask(active));

const checkpoint = agent.exportState();          // bit-exact resume, validated on import

The lower layers (LifNetwork, RewardModulatedStdp, PopulationDecoder) are exported too for hosts that want to run the loop themselves.

integration.md has the full per-frame loop, the fractional frame timing and the checkpoint contract.

Documentation

  • Overview: the pipeline, the layer map and the design principles.
  • Dataset format: artifacts, CSR layout, weight encoding, every role and its count, fingerprinting, regeneration, license.
  • Model: the 1-ms LIF kernel step by step, every default constant, the retina projection, the RNG, state export and version strings.
  • Plasticity: edge selection, the eligibility and reinforcement equations, statistics, topology hash and the explicit non-claims.
  • Readout: scores, exclusive groups, pulse channels, the blocked-direction cooldown, the Game Boy preset table and checkpoint versions.
  • Integration: what a game must provide, the Pokemon Red integration as a worked example, and a sketch of a platformer adapter.
  • Limitations: what is not claimed, what is unproven, measured throughput.
  • Verification: the oracle-test strategy and what each test file covers.
  • Streaming plan: headless capture, Twitch, VM design and the phased plan for a 24/7 stream.
  • Artifact builder: how to regenerate and verify data/fafb-v783.
  • Data attribution: source, license and citations.

Provenance

The network, plasticity rule, readout, FlyWire pipeline and activity viewer were extracted from the fly-plays-pokemon prototype so several game demos can share one core. The default configuration reproduces that prototype's kernel bit for bit, and verbatim copies of its modules live in packages/brain/tests/legacy/ as oracles. Built with Astra.

Licensing

The data/fafb-v783 artifacts are derived from the FlyWire FAFB public Codex v783 exports and are licensed CC BY-NC 4.0. That is a non-commercial license, so a commercial demo needs a different data source or separate permission. Citations and the list of modifications are in data/fafb-v783/ATTRIBUTION.md.

No license has been chosen for the code in this repository yet.

ROMs and save states never enter this repository.