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ChatMock

Allows Codex to work in your favourite chat apps and coding tools.

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Install

Homebrew

brew tap RayBytes/chatmock
brew install chatmock

pipx / pip

pipx install chatmock

GUI

Download from releases (macOS & Windows)

Docker

See DOCKER.md


Getting Started

# 1. Sign in with your ChatGPT account
# If you are running this on a headless server, append --headless
chatmock login

# 2. Start the server
chatmock serve

The server runs at http://127.0.0.1:8000 by default. Use http://127.0.0.1:8000/v1 as your base URL for OpenAI-compatible apps.


Example usage

Raycast Integration
  1. Configure the Host URL
    Open your Raycast Extensions preferences, navigate to the Ollama settings section, and input the host URL (default is 127.0.0.1:8000).
    Raycast Ollama Host URL configuration

  2. Sync Your Models
    Click the Sync Models button, which will register all available models.

  3. Start Chatting
    Open the Raycast AI Chat interface. You will now see model slugs which you can chat with.

Terax (Agentic Terminal) Integration
  1. Configure the provider settings
    Open your Terax settings, and switch to the Models tab, add a new provider (OpenAI Compatible), and input the host URL (default is http://127.0.0.1:8000/v1), along with the model IDs you wish to use (API key may be anything).
    image

  2. Favourite, and start using it!
    Go back to your main chat window, select the model by going to the OpenAI Compatible icon, and clicking the model there (you may favourite it here to quickly select it the next time if you switch between models) image


Supported Models

ChatMock automatically discovers the models available to the signed-in ChatGPT account. The current catalog commonly includes:

  • gpt-5.6-sol
  • gpt-5.6-terra
  • gpt-5.6-luna
  • gpt-5.5
  • gpt-5.4
  • gpt-5.4-mini
  • gpt-5.3-codex-spark

Features

  • Tool / function calling
  • Vision / image input
  • Thinking summaries (via think tags)
  • Configurable thinking effort
  • Fast mode for supported models
  • Web search tool
  • OpenAI-compatible /v1/responses (HTTP + WebSocket)
  • Ollama-compatible endpoints
  • Reasoning effort exposed as separate models (optional)

Configuration

All flags go after chatmock serve. These can also be set as environment variables.

Flag Env var Options Default Description
--reasoning-effort CHATGPT_LOCAL_REASONING_EFFORT none, minimal, low, medium, high, xhigh, max, ultra medium How hard the model thinks
--reasoning-summary CHATGPT_LOCAL_REASONING_SUMMARY auto, concise, detailed, none auto Thinking summary verbosity
--reasoning-compat CHATGPT_LOCAL_REASONING_COMPAT legacy, o3, think-tags think-tags How reasoning is returned to the client
--fast-mode CHATGPT_LOCAL_FAST_MODE true/false false Priority processing for supported models
--enable-web-search CHATGPT_LOCAL_ENABLE_WEB_SEARCH true/false false Allow the model to search the web
--expose-reasoning-models CHATGPT_LOCAL_EXPOSE_REASONING_MODELS true/false false List each reasoning level as its own model
--model-sync CHATGPT_LOCAL_MODEL_SYNC true/false true Discover account models automatically
--model-refresh-interval CHATGPT_LOCAL_MODEL_REFRESH_INTERVAL seconds 3600 Refresh interval for model discovery
Web search in a request
{
  "model": "gpt-5.4",
  "messages": [{"role": "user", "content": "latest news on ..."}],
  "responses_tools": [{"type": "web_search"}],
  "responses_tool_choice": "auto"
}
Fast mode in a request
{
  "model": "gpt-5.4",
  "input": "summarize this",
  "fast_mode": true
}

Important notice

Use responsibly and at your own risk. This project is not affiliated with OpenAI.


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