> ## Documentation Index
> Fetch the complete documentation index at: https://docs.llmeasy.ru/llms.txt
> Use this file to discover all available pages before exploring further.

# How to configure Codex CLI config.toml

> Learn where Codex CLI config.toml lives, which fields matter, how custom providers work, and how API Key, Base URL, and model settings differ.

## Short answer

`config.toml` is the main local configuration file for Codex CLI. You can use it to set the default model, model provider, sandbox, approvals, reasoning effort, retry behavior, and other settings.

For a custom OpenAI-compatible provider, the important part is to make `model_provider` point to `[model_providers.<id>]`, then define `base_url`, `wire_api`, and authentication behavior in that provider table.

Do not commit API Keys to a public repository. Keep API Keys in local environment variables, CLI login state, protected local configuration, or a secure store managed by your tool.

## When you need it

* You want Codex CLI to use a third-party OpenAI-compatible provider
* You need a fixed default model or review model
* You want to adjust sandbox, approval, or reasoning effort
* You are fixing wrong `model_provider`, `base_url`, or `wire_api` values
* You are preparing a reusable Codex CLI config example for a team

## Common locations

| System        | Typical path                            |
| ------------- | --------------------------------------- |
| macOS / Linux | `~/.codex/config.toml`                  |
| Windows       | `C:\Users\YOUR_USER\.codex\config.toml` |

Project-level instructions usually belong in `AGENTS.md` inside the repository. Do not mix them with user-level `config.toml`.

## Recommended config example

The following example follows the Codex setup page in this documentation. Copy the current model ID from the **GPT Key group** in the model plaza before using it.

```toml theme={null}
model_provider = "custom"
model = "gpt-5.5"
review_model = "gpt-5.4"
model_reasoning_effort = "high"
model_context_window = 1000000
model_auto_compact_token_limit = 900000
windows_wsl_setup_acknowledged = true

[model_providers]
[model_providers.custom]
name = "LLMEasy"
base_url = "https://www.llmeasy.ru/v1"
wire_api = "responses"
requires_openai_auth = false
request_max_retries = 4
stream_max_retries = 8
stream_idle_timeout_ms = 300000
supports_websockets = false
```

## Common mistakes

* Defining `[model_providers.custom]` but forgetting `model_provider = "custom"`.
* Putting the Claude Code `https://www.llmeasy.ru` into Codex CLI.
* Using a marketing model name instead of an API model ID.
* Committing API Keys, tokens, or login state to a repository.
* Running untrusted commands with overly broad sandbox or approval settings.

## About LLMEasy

In Codex CLI, LLMEasy is a custom OpenAI-compatible provider. Use `https://www.llmeasy.ru/v1` for `base_url` and choose a model ID from the **GPT Key group**.

This only changes where model requests are sent. Codex CLI still controls file access, command execution, sandbox, and approvals.

## Related docs

* [Codex LLMEasy setup guide](/en/ai-tools/codex)
* [What are model\_provider, base\_url, and wire\_api?](/en/faq/codex/model-provider-base-url-wire-api)
* [What are Codex CLI sandbox and approval modes?](/en/faq/codex/sandbox-approval)
* [OpenAI-compatible API vs Anthropic-compatible API](/en/faq/concepts/openai-compatible-vs-anthropic-compatible)

## References

* [Codex basic configuration](https://developers.openai.com/codex/config-basic)
* [Codex advanced configuration](https://developers.openai.com/codex/config-advanced)
* [Codex configuration reference](https://developers.openai.com/codex/config-reference)
* [Codex sample config](https://developers.openai.com/codex/config-sample)