OpenEye

alpha software. interfaces may change. file issues at github.com/dumbspacecookie/openeye.

every AR headset maker — HoloLens, Snap Spectacles, Apple, Android — ships a device that can see. none of them ship a brain. every developer building on these platforms has to figure out the intelligence layer themselves, from scratch, every time, for every device. the work doesn't compound. what one team learns on HoloLens doesn't help the team building on WebXR. every deployment is a silo.

OpenEye is the shared brain.

a thin piece of software sits on the device, captures what the camera sees, and turns it into a natural-language description of the scene. that description goes to OpenEye. OpenEye runs an AI agent with tools for verifying procedure steps, recalling prior sessions, and writing down what it learns. each session becomes structured memory the agent can search later, and an exportable training trajectory you can fine-tune on.

OpenEye doesn't ship a vision model — you bring your own. drop in Claude vision, GPT-4o, Gemini, Groq Llama vision, or a local Ollama model with moondream/llava. a working reference adapter for both cloud and local is in examples/vision-adapter/.

install

npm install @dumbspacecookie/openeye
pip install -r node_modules/@dumbspacecookie/openeye/sidecar/requirements.txt

the Python sidecar (FastAPI + SQLite) handles state and auto-spawns when you create an agent — you don't have to start it yourself.

prefer to hack on it locally? clone instead:

git clone https://github.com/dumbspacecookie/openeye.git
cd openeye && npm install && npm run build
pip install -r sidecar/requirements.txt

quick start

import { OpenEyeAgent, setupProviders, makeStreamFn, ANTHROPIC_SONNET } from "@dumbspacecookie/openeye";
import { describeFrameWithClaude } from "./examples/vision-adapter/claude-vision-adapter.js";
import * as fs from "node:fs";

setupProviders();

const agent = await OpenEyeAgent.create({
  model: ANTHROPIC_SONNET,
  streamFn: makeStreamFn(),
  systemPrompt: "You are a procedure assistant. Verify steps with precision.",
  tenantId: "your-org",
});

const vsId = await agent.client.createVisualSession({
  deviceType: "android-tablet",
  procedureId: "bolt-assembly-v1",
  procedureName: "M6 Bolt Assembly",
});

// 1. vision adapter (you bring this) turns a camera frame into text
const frameBytes = fs.readFileSync("./frame.jpg");
const description = await describeFrameWithClaude(
  frameBytes,
  "Operator is installing an M6 bolt. Describe hand position, tool, and bolt state.",
);

// 2. OpenEye logs the description and lets the agent verify the step
const frameId = await agent.client.logFrame({
  visualSessionId: vsId!,
  sequenceNum: 1,
  sceneDescription: description,
  stepContext: "step-1-position-bracket",
});

await agent.prompt(`Frame 1: ${description}\nVerify step-1-position-bracket.`);

await agent.client.endVisualSession(vsId!, "completed");
await agent.captureAndClose({ completed: true, visualSessionId: vsId! });

no API key for the agent? run it locally with Ollama:

ollama pull llama3.3

import { ollamaModel } from "@dumbspacecookie/openeye";
const agent = await OpenEyeAgent.create({ model: ollamaModel("llama3.3"), streamFn: make

... [View full README on GitHub](https://github.com/dumbspacecookie/openeye#readme)