
codex-shim-byok-models
Run Codex Desktop with Factory BYOK models and ChatGPT GPT-5.5 via local API shim
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/reason-machines/codex-skills --skill codex-shim-byok-models- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads codex-shim-byok-models automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Codex Shim BYOK Models
Skill by ara.so — Codex Skills collection.
Overview
codex-shim is a local Python API shim that intercepts Codex Desktop's model requests and routes them to:
- Any model in your
~/.factory/settings.json(Factory BYOK) - Your ChatGPT subscription GPT-5.5
- Custom OpenAI/Anthropic/generic chat completion endpoints
It exposes a local Responses API endpoint that Codex Desktop points to, bypassing Codex's server-side Statsig model allowlist.
Key capabilities:
- Use any OpenAI, Anthropic, DeepSeek, Gemini, OpenRouter, or Z.ai model
- Keep ChatGPT subscription GPT-5.5 alongside BYOK models
- No modification to
~/.codex/config.toml(uses launch-time overrides) - Translates between Codex Responses API ↔ upstream APIs (OpenAI chat completions, Anthropic messages)
Installation
# Clone repository
git clone https://github.com/0xSero/codex-shim ~/Documents/codex-shim
cd ~/Documents/codex-shim
# Install Python dependencies (requires 3.11+)
python3 -m pip install --user aiohttp pytest
# Symlink commands to PATH
ln -s "$PWD/bin/codex-shim" ~/.local/bin/codex-shim
ln -s "$PWD/bin/codex-app" ~/.local/bin/codex-app
ln -s "$PWD/bin/codex-model" ~/.local/bin/codex-model
Verify installation:
codex-shim --help
Configuration
Factory Settings File
The shim reads ~/.factory/settings.json by default. Structure:
{
"customModels": [
{
"model": "gpt-5.5",
"provider": "openai",
"baseUrl": "https://api.openai.com/v1",
"apiKey": "${OPENAI_API_KEY}",
"displayName": "OpenAI GPT-5.5",
"maxContextLimit": 400000
},
{
"model": "claude-opus-4-7-20251109",
"provider": "anthropic",
"baseUrl": "https://api.anthropic.com/v1",
"apiKey": "${ANTHROPIC_API_KEY}",
"displayName": "Claude Opus 4.7"
},
{
"model": "deepseek-v4-pro",
"provider": "anthropic",
"baseUrl": "https://api.deepseek.com/anthropic",
"apiKey": "${DEEPSEEK_API_KEY}",
"displayName": "DeepSeek V4 Pro",
"noImageSupport": true
}
]
}
Supported providers:
openai→ OpenAI/v1/chat/completionsgeneric-chat-completion-api→ OpenAI-compatible endpointsanthropic→ Anthropic/v1/messages
Custom Config Path
codex-shim --settings /path/to/custom-models.json generate
codex-shim --settings /path/to/custom-models.json start
Environment Variables
Store API keys in environment:
export OPENAI_API_KEY="sk-..."
export ANTHROPIC_API_KEY="sk-ant-..."
export DEEPSEEK_API_KEY="..."
Key Commands
Generate Catalog
Reads Factory settings and creates .codex-shim/custom_model_catalog.json:
codex-shim generate
Start/Stop Daemon
# Start shim on 127.0.0.1:8765
codex-shim start
# Check status
codex-shim status
# Stop daemon
codex-shim stop
# Restart
codex-shim restart
List Available Models
# Show all generated slugs and upstream routes
codex-shim list
# Show models currently in Codex Desktop picker
codex-model list
Launch Codex Desktop
# Launch with shim wired in (doesn't modify ~/.codex/config.toml)
codex-app
# Launch and open specific path
codex-app /path/to/project
# Equivalent long form
codex-shim app /path/to/project
Switch Active Model
# List available slugs
codex-model list
# Set default model for next launch
codex-model openai-gpt-5-5
# Relaunch Codex
codex-app
Run Codex CLI Through Shim
codex-shim codex -- chat "explain this code"
codex-shim codex -- edit main.py "add error handling"
Model Routing Architecture
Codex Desktop → /v1/responses → codex-shim (127.0.0.1:8765)
┃
┏━━━━━━━━━━━━━━╋━━━━━━━━━━━━━━┓
┃ ┃ ┃
slug "openai-gpt-5-5" provider provider
┃ "openai" "anthropic"
┃ ┃ ┃
chatgpt.com/backend-api baseUrl/ baseUrl/
/codex/responses chat/ messages
(Bearer token) completions (x-api-key)
The shim:
- Receives Codex Responses API request
- Looks up slug in catalog
- Translates to upstream format (OpenAI chat completions or Anthropic messages)
- Streams upstream response
- Translates back to Responses API format
Code Examples
Python: Implementing Custom Provider Translation
# codex_shim/translator.py example pattern
async def translate_to_openai(responses_request):
"""Convert Codex Responses API → OpenAI chat completions."""
return {
"model": responses_request["model"],
"messages": responses_request["messages"],
"stream": True,
"temperature": responses_request.get("temperature", 1.0),
"max_tokens": responses_request.get("max_tokens"),
}
async def translate_to_anthropic(responses_request):
"""Convert Codex Responses API → Anthropic messages."""
messages = []
system = None
for msg in responses_request["messages"]:
if msg["role"] == "system":
system = msg["content"]
else:
messages.append({
"role": msg["role"],
"content": msg["content"]
})
body = {
"model": responses_request["model"],
"messages": messages,
"stream": True,
"max_tokens": responses_request.get("max_tokens", 4096),
}
if system:
body["system"] = system
return body
Python: Adding Custom Model Programmatically
import json
from pathlib import Path
def add_custom_model(model_config):
"""Add model to Factory settings."""
settings_path = Path.home() / ".factory" / "settings.json"
if settings_path.exists():
with open(settings_path) as f:
settings = json.load(f)
else:
settings = {"customModels": []}
settings["customModels"].append(model_config)
with open(settings_path, "w") as f:
json.dump(settings, f, indent=2)
# Example: Add OpenRouter model
add_custom_model({
"model": "anthropic/claude-3.5-sonnet",
"provider": "openai",
"baseUrl": "https://openrouter.ai/api/v1",
"apiKey": "${OPENROUTER_API_KEY}",
"displayName": "Claude 3.5 Sonnet (OpenRouter)",
"maxContextLimit": 200000
})
Shell: Automated Setup Script
#!/bin/bash
# setup-codex-shim.sh
set -e
CODEX_SHIM_DIR="$HOME/Documents/codex-shim"
# Clone and install
if [ ! -d "$CODEX_SHIM_DIR" ]; then
git clone https://github.com/0xSero/codex-shim "$CODEX_SHIM_DIR"
fi
cd "$CODEX_SHIM_DIR"
python3 -m pip install --user aiohttp
# Symlink commands
mkdir -p "$HOME/.local/bin"
ln -sf "$CODEX_SHIM_DIR/bin/codex-shim" "$HOME/.local/bin/"
ln -sf "$CODEX_SHIM_DIR/bin/codex-app" "$HOME/.local/bin/"
ln -sf "$CODEX_SHIM_DIR/bin/codex-model" "$HOME/.local/bin/"
# Generate catalog and start
codex-shim generate
codex-shim start
echo "✓ Shim installed and running"
codex-shim status
macOS Picker Patch
Codex Desktop's Statsig config hides models not on a server-side allowlist. Apply this one-time ASAR patch to bypass:
APP=/Applications/Codex.app
# Backup
sudo cp -R "$APP" "$APP.unpatched-$(date +%Y%m%d-%H%M%S)"
# Extract ASAR
cd /tmp && rm -rf codex-asar-patch && mkdir codex-asar-patch && cd codex-asar-patch
npx --yes @electron/asar extract "$APP/Contents/Resources/app.asar" extracted
# Patch picker filter (disables useHiddenModels check)
PATCH_FILE=$(grep -RIl 'useHiddenModels' extracted/webview/assets/model-queries-*.js | head -n1)
sed -i.bak -E 's/let u=c\.useHiddenModels&&o!==`amazonBedrock`,d;/let u=!1,d;/' "$PATCH_FILE"
# Verify exactly one change
diff "$PATCH_FILE.bak" "$PATCH_FILE" && echo "ERROR: No changes made" && exit 1
rm "$PATCH_FILE.bak"
# Repack
npx --yes @electron/asar pack extracted app.asar.new
sudo cp app.asar.new "$APP/Contents/Resources/app.asar"
# Recompute ASAR header hash for Electron integrity check
HEADER_HASH=$(python3 - "$APP/Contents/Resources/app.asar" <<'PY'
import struct, hashlib, sys
with open(sys.argv[1], 'rb') as f:
data_size, header_size, _, json_size = struct.unpack('<4I', f.read(16))
header_json = f.read(json_size)
print(hashlib.sha256(header_json).hexdigest())
PY
)
# Update Info.plist
sudo /usr/libexec/PlistBuddy -c \
"Set :ElectronAsarIntegrity:Resources/app.asar:hash $HEADER_HASH" \
"$APP/Contents/Info.plist"
# Re-sign (ad-hoc)
sudo codesign --force --deep --sign - "$APP"
echo "✓ Patch applied. Launch Codex Desktop."
Rollback:
sudo rm -rf "$APP"
sudo mv "$APP.unpatched-YYYYMMDD-HHMMSS" "$APP"
ChatGPT GPT-5.5 Passthrough
If ~/.codex/auth.json exists with auth_mode: chatgpt, the shim auto-generates a synthetic slug openai-gpt-5-5 that proxies to:
https://chatgpt.com/backend-api/codex/responses
Authorization: Bearer <access_token from auth.json>
This bypasses Factory and uses your ChatGPT subscription quota.
Disable:
# Remove from catalog after generation
jq 'del(.models[] | select(.slug == "openai-gpt-5-5"))' \
.codex-shim/custom_model_catalog.json > tmp.json && mv tmp.json .codex-shim/custom_model_catalog.json
Common Patterns
Multi-Provider Setup
{
"customModels": [
{
"model": "gpt-5.5",
"provider": "openai",
"baseUrl": "https://api.openai.com/v1",
"apiKey": "${OPENAI_API_KEY}",
"displayName": "GPT-5.5"
},
{
"model": "claude-opus-4-7-20251109",
"provider": "anthropic",
"baseUrl": "https://api.anthropic.com/v1",
"apiKey": "${ANTHROPIC_API_KEY}",
"displayName": "Claude Opus 4.7"
},
{
"model": "gemini-2.0-flash-exp",
"provider": "openai",
"baseUrl": "https://generativelanguage.googleapis.com/v1beta/openai",
"apiKey": "${GOOGLE_API_KEY}",
"displayName": "Gemini 2.0 Flash"
}
]
}
OpenRouter Aggregation
{
"model": "meta-llama/llama-3.3-70b-instruct",
"provider": "openai",
"baseUrl": "https://openrouter.ai/api/v1",
"apiKey": "${OPENROUTER_API_KEY}",
"displayName": "Llama 3.3 70B (OpenRouter)"
}
DeepSeek with Anthropic-Style Thinking
{
"model": "deepseek-v4-pro",
"provider": "anthropic",
"baseUrl": "https://api.deepseek.com/anthropic",
"apiKey": "${DEEPSEEK_API_KEY}",
"displayName": "DeepSeek V4 Pro",
"noImageSupport": true
}
The shim translates extended thinking blocks from thinking items to reasoning.encrypted_content.
Troubleshooting
Models Don't Appear in Picker
Cause: Statsig allowlist still active.
Solution: Apply macOS picker patch (see section above).
"Connection refused" When Launching Codex
Cause: Shim daemon not running.
codex-shim status # Check if running
codex-shim start # Start if stopped
401 Unauthorized Errors
Cause: API key not found or invalid.
Check environment variables:
echo $OPENAI_API_KEY
echo $ANTHROPIC_API_KEY
Verify settings file:
cat ~/.factory/settings.json | jq '.customModels[].apiKey'
Test upstream directly:
curl https://api.openai.com/v1/models \
-H "Authorization: Bearer $OPENAI_API_KEY"
ChatGPT Passthrough Not Working
Verify auth.json exists:
cat ~/.codex/auth.json | jq '.auth_mode'
# Should output: "chatgpt"
Check access token validity:
TOKEN=$(jq -r '.access_token' ~/.codex/auth.json)
curl https://chatgpt.com/backend-api/me \
-H "Authorization: Bearer $TOKEN"
Shim Logs
# Tail daemon logs
tail -f ~/.codex-shim/codex-shim.log
# Check last 50 lines
tail -n 50 ~/.codex-shim/codex-shim.log
Port Already in Use
# Change default port (8765)
codex-shim --port 9876 start
codex-shim --port 9876 app
Extended Thinking Not Appearing
For Anthropic-shaped providers (Claude, DeepSeek), thinking blocks appear as reasoning.encrypted_content items in Codex UI.
Verify provider is set to anthropic:
jq '.customModels[] | select(.model=="deepseek-v4-pro") | .provider' \
~/.factory/settings.json
Should return "anthropic", not "openai".
Testing
Run test suite:
cd ~/Documents/codex-shim
python3 -m pytest tests/ -v
Test specific translation:
# tests/test_translation.py
import pytest
from codex_shim.translator import translate_to_anthropic
@pytest.mark.asyncio
async def test_system_message_extraction():
request = {
"model": "claude-opus-4-7",
"messages": [
{"role": "system", "content": "You are helpful"},
{"role": "user", "content": "Hello"}
]
}
result = await translate_to_anthropic(request)
assert result["system"] == "You are helpful"
assert len(result["messages"]) == 1
MCP Tool Forwarding
Codex Desktop forwards three generic MCP tools to all models (built-in and shim-routed):
list_mcp_resourceslist_mcp_resource_templatesread_mcp_resource
These are available in the function calling schema for every routed model. The model calls list_mcp_resources to discover available resources.
Note: Codex Desktop does not flatten individual MCP server tools. That's a Codex client behavior, not a shim limitation.
Official Repository: https://github.com/0xSero/codex-shim
License: MIT
Requires: Python 3.11+, aiohttp
FAQ
What does the codex-shim-byok-models skill do?
Run Codex Desktop with Factory BYOK models and ChatGPT GPT-5.5 via local API shim
How do I install codex-shim-byok-models?
Run npx skills add https://github.com/reason-machines/codex-skills --skill codex-shim-byok-models in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/codex-shim-byok-models/ (personal) or .claude/skills/codex-shim-byok-models/ (project).
Which AI agents can use codex-shim-byok-models?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is codex-shim-byok-models safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains codex-shim-byok-models?
It is published by reason-machines in reason-machines/codex-skills. It has 231 recorded installs.
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