opencodex-gateway

name	opencodex-gateway
description	Local gateway for Codex Desktop with custom API support, web dashboard, Computer Use engine, and Vision Bridge for text-only models
triggers	["set up OpenCodex gateway for Codex Desktop","configure custom API models in OpenCodex","add a third-party model to Codex Desktop","enable Vision Bridge for text-only models","configure Computer Use with OpenCodex","manage OpenCodex dashboard settings","troubleshoot OpenCodex API integration","reset Codex to native configuration"]

OpenCodex Gateway

Skill by ara.so — Codex Skills collection.

OpenCodex is a zero-config local gateway that enables Codex Desktop to use third-party APIs (OpenAI-compatible endpoints). It features a bilingual web dashboard for model management, a custom Computer Use engine with native macOS control, and Vision Bridge that lets text-only models handle visual tasks by automatically describing screenshots.

Installation

git clone https://github.com/AITabby/opencodex.git
cd opencodex
npm install
npm start

The server starts on http://localhost:8765 and automatically:

• Patches ~/.codex/config.toml (creates backup)
• Opens the dashboard in your browser
• Enables the API gateway

Architecture

OpenCodex sits between Codex Desktop and third-party APIs:

Codex Desktop → OpenCodex Gateway (localhost:8765) → Third-party API
                      ↓
                Vision Bridge (optional)
                Computer Use Engine

Web Dashboard

Access at http://localhost:8765/dashboard

Key Features

• API Configuration: Set base URL, API key, model names
• Model Management: Add/remove models, toggle visibility in Codex
• Language Toggle: Switch between English and Chinese
• Live Logs: SSE-streamed request/response logs
• One-Click Actions: Restart Codex, reset to native config

Configuration Flow

1. Open dashboard
2. Enter API endpoint (e.g., https://api.openai.com/v1 or https://api.deepseek.com)
3. Add API key (stored in ~/.codex/config.toml)
4. Add model names (e.g., gpt-4, deepseek-chat)
5. Check boxes for models you want visible in Codex
6. Click "Save Configuration"

Configuration Files

Auto-Generated Config

OpenCodex modifies ~/.codex/config.toml:

[api]
base_url = "http://localhost:8765/v1"
api_key = "your-actual-api-key"

[[models]]
name = "gpt-4"
enabled = true

[[models]]
name = "deepseek-chat"
enabled = true

Original config backed up to ~/.codex/config.toml.backup

Environment Variables

For development or custom deployments:

export OPENCODEX_PORT=8765
export OPENCODEX_API_KEY=sk-your-key-here
export OPENCODEX_BASE_URL=https://api.openai.com/v1

Vision Bridge

Vision Bridge enables text-only models to handle Computer Use tasks by converting screenshots to text descriptions.

How It Works

1. Codex sends Computer Use request with screenshot
2. OpenCodex detects text-only model
3. Screenshot compressed to 1200px with sips
4. Vision model describes the screenshot
5. Description injected into the prompt
6. Text-only model receives modified request

Configuration

In the dashboard, configure Vision Bridge settings:

{
  "vision_bridge": {
    "enabled": true,
    "endpoint": "https://api.openai.com/v1",
    "model": "gpt-4-vision-preview",
    "api_key": "process.env.VISION_API_KEY",
    "max_dimension": 1200
  }
}

Programmatic Example

If extending OpenCodex, here's how Vision Bridge is invoked:

import { VisionBridge } from './vision-bridge';

const bridge = new VisionBridge({
  endpoint: process.env.VISION_ENDPOINT,
  model: 'gpt-4-vision-preview',
  apiKey: process.env.VISION_API_KEY
});

// Automatically converts screenshot to description
const description = await bridge.describeImage(screenshotBase64);
// Injects into prompt for text-only model
const modifiedPrompt = bridge.injectDescription(originalPrompt, description);

Computer Use Engine

OpenCodex implements custom Computer Use actions for macOS using native CGEvent APIs.

Supported Actions

• Mouse: Click, move, drag, scroll
• Keyboard: Type text, press keys, shortcuts
• Window: Focus, resize, minimize
• Screenshot: Capture and compress

Action Format

Codex sends tool calls in this format:

{
  "type": "computer_use",
  "action": "mouse_click",
  "params": {
    "x": 500,
    "y": 300,
    "button": "left"
  }
}

Example Actions

Mouse Click

{
  "action": "mouse_click",
  "params": { "x": 500, "y": 300, "button": "left" }
}

Type Text

{
  "action": "type_text",
  "params": { "text": "Hello, world!" }
}

Screenshot

{
  "action": "screenshot",
  "params": { "max_dimension": 1200 }
}

Response includes base64 image:

{
  "success": true,
  "image": "iVBORw0KGgoAAAANS..."
}

API Reference

Proxy Endpoint

All OpenAI-compatible requests go through:

POST http://localhost:8765/v1/chat/completions

Headers:

Authorization: Bearer <your-api-key>
Content-Type: application/json

Dashboard API

Get Configuration

curl http://localhost:8765/api/config

Update Configuration

curl -X POST http://localhost:8765/api/config \
  -H "Content-Type: application/json" \
  -d '{
    "base_url": "https://api.deepseek.com",
    "api_key": "sk-...",
    "models": [
      {"name": "deepseek-chat", "enabled": true}
    ]
  }'

Restart Codex

curl -X POST http://localhost:8765/api/restart-codex

Reset to Native

curl -X POST http://localhost:8765/api/reset-native

Live Logs (SSE)

curl -N http://localhost:8765/api/logs

Stream format:

data: {"timestamp": "2026-06-04T10:30:00Z", "level": "info", "message": "Request to gpt-4"}

data: {"timestamp": "2026-06-04T10:30:01Z", "level": "info", "message": "Response 200"}

Common Patterns

Adding Multiple Models

const models = [
  { name: 'gpt-4-turbo', enabled: true },
  { name: 'gpt-4', enabled: true },
  { name: 'claude-3-opus', enabled: false }
];

await fetch('http://localhost:8765/api/config', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({ models })
});

Switching Providers

To switch from OpenAI to DeepSeek:

1. Open dashboard
2. Change base URL to https://api.deepseek.com
3. Update API key
4. Change model name to deepseek-chat
5. Enable Vision Bridge (DeepSeek is text-only)
6. Save configuration

Custom Vision Model

Use a different vision model for Vision Bridge:

{
  "vision_bridge": {
    "enabled": true,
    "endpoint": "https://api.anthropic.com/v1",
    "model": "claude-3-opus-20240229",
    "api_key": "process.env.ANTHROPIC_API_KEY"
  }
}

Troubleshooting

Codex Not Connecting

Symptom: Codex shows "API Error" or "Connection Failed"

Solution:

1. Verify OpenCodex is running: curl http://localhost:8765/health
2. Check ~/.codex/config.toml has base_url = "http://localhost:8765/v1"
3. Restart Codex via dashboard or manually
4. Check logs: http://localhost:8765/dashboard → scroll to logs

Models Not Appearing

Symptom: Added models don't show in Codex

Solution:

1. Ensure model checkbox is checked in dashboard
2. Click "Save Configuration"
3. Restart Codex (one-click button in dashboard)
4. Verify ~/.codex/config.toml includes the model with enabled = true

Vision Bridge Not Working

Symptom: Text-only model fails on Computer Use tasks

Solution:

1. Enable Vision Bridge in dashboard
2. Configure vision model endpoint and API key
3. Test vision model separately: curl -X POST <vision_endpoint>/chat/completions
4. Check OpenCodex logs for vision errors
5. Ensure screenshot compression succeeds: verify sips is available (which sips)

Rate Limiting

Symptom: 429 errors in logs

Solution:

• OpenCodex passes through rate limits from upstream API
• Reduce request frequency in Codex
• Check API provider's rate limits
• Consider adding retry logic (upstream API responsibility)

Port Already in Use

Symptom: Error: listen EADDRINUSE: address already in use :::8765

Solution:

# Find process on port 8765
lsof -i :8765
# Kill it
kill -9 <PID>
# Or change port
export OPENCODEX_PORT=8766
npm start

Config Corruption

Symptom: Codex behaves unexpectedly after config changes

Solution:

1. Click "Reset to Native Codex" in dashboard
2. Restores ~/.codex/config.toml.backup
3. Restart Codex
4. Reconfigure OpenCodex carefully

Screenshot Too Large

Symptom: Vision API rejects screenshots

Solution:

• Default max dimension: 1200px
• Reduce in Vision Bridge settings:

{ "max_dimension": 800 }

• Verify compression: check OpenCodex logs for sips output

Development

Project Structure

opencodex/
├── src/
│   ├── server.ts          # Main Express server
│   ├── vision-bridge.ts   # Vision Bridge logic
│   ├── computer-use.ts    # macOS automation
│   └── config.ts          # Config patching
├── public/
│   └── dashboard.html     # Web UI
└── package.json

Running in Dev Mode

npm run dev  # Enables hot-reload

Adding Custom Actions

Extend Computer Use engine:

// src/computer-use.ts
export async function customAction(params: any) {
  // Use node-mac-automation or applescript
  const result = execSync(`osascript -e 'tell application "Finder" to ...'`);
  return { success: true, result: result.toString() };
}

Register in action handler:

case 'custom_action':
  return await customAction(params);

Logging

Add custom logs visible in dashboard:

import { logger } from './logger';

logger.info('Custom event', { data: someData });
logger.error('Something failed', { error });

Integration with OpenCodexBar

For the ultimate experience, pair with OpenCodexBar:

1. Run OpenCodex gateway: npm start
2. Clone and compile OpenCodexBar
3. Launch bar app
4. Press Option + Space for system-wide voice activation
5. Enjoy real-time audio VAD and cinematic visualizer

Both projects work independently but are designed to complement each other.