Files
llmx/codex-rs/README.md
Michael Bolin e924070cee feat: support the chat completions API in the Rust CLI (#862)
This is a substantial PR to add support for the chat completions API,
which in turn makes it possible to use non-OpenAI model providers (just
like in the TypeScript CLI):

* It moves a number of structs from `client.rs` to `client_common.rs` so
they can be shared.
* It introduces support for the chat completions API in
`chat_completions.rs`.
* It updates `ModelProviderInfo` so that `env_key` is `Option<String>`
instead of `String` (for e.g., ollama) and adds a `wire_api` field
* It updates `client.rs` to choose between `stream_responses()` and
`stream_chat_completions()` based on the `wire_api` for the
`ModelProviderInfo`
* It updates the `exec` and TUI CLIs to no longer fail if the
`OPENAI_API_KEY` environment variable is not set
* It updates the TUI so that `EventMsg::Error` is displayed more
prominently when it occurs, particularly now that it is important to
alert users to the `CodexErr::EnvVar` variant.
* `CodexErr::EnvVar` was updated to include an optional `instructions`
field so we can preserve the behavior where we direct users to
https://platform.openai.com if `OPENAI_API_KEY` is not set.
* Cleaned up the "welcome message" in the TUI to ensure the model
provider is displayed.
* Updated the docs in `codex-rs/README.md`.

To exercise the chat completions API from OpenAI models, I added the
following to my `config.toml`:

```toml
model = "gpt-4o"
model_provider = "openai-chat-completions"

[model_providers.openai-chat-completions]
name = "OpenAI using Chat Completions"
base_url = "https://api.openai.com/v1"
env_key = "OPENAI_API_KEY"
wire_api = "chat"
```

Though to test a non-OpenAI provider, I installed ollama with mistral
locally on my Mac because ChatGPT said that would be a good match for my
hardware:

```shell
brew install ollama
ollama serve
ollama pull mistral
```

Then I added the following to my `~/.codex/config.toml`:

```toml
model = "mistral"
model_provider = "ollama"
```

Note this code could certainly use more test coverage, but I want to get
this in so folks can start playing with it.

For reference, I believe https://github.com/openai/codex/pull/247 was
roughly the comparable PR on the TypeScript side.
2025-05-08 21:46:06 -07:00

253 lines
8.8 KiB
Markdown

# codex-rs
April 24, 2025
Today, Codex CLI is written in TypeScript and requires Node.js 22+ to run it. For a number of users, this runtime requirement inhibits adoption: they would be better served by a standalone executable. As maintainers, we want Codex to run efficiently in a wide range of environments with minimal overhead. We also want to take advantage of operating system-specific APIs to provide better sandboxing, where possible.
To that end, we are moving forward with a Rust implementation of Codex CLI contained in this folder, which has the following benefits:
- The CLI compiles to small, standalone, platform-specific binaries.
- Can make direct, native calls to [seccomp](https://man7.org/linux/man-pages/man2/seccomp.2.html) and [landlock](https://man7.org/linux/man-pages/man7/landlock.7.html) in order to support sandboxing on Linux.
- No runtime garbage collection, resulting in lower memory consumption and better, more predictable performance.
Currently, the Rust implementation is materially behind the TypeScript implementation in functionality, so continue to use the TypeScript implmentation for the time being. We will publish native executables via GitHub Releases as soon as we feel the Rust version is usable.
## Code Organization
This folder is the root of a Cargo workspace. It contains quite a bit of experimental code, but here are the key crates:
- [`core/`](./core) contains the business logic for Codex. Ultimately, we hope this to be a library crate that is generally useful for building other Rust/native applications that use Codex.
- [`exec/`](./exec) "headless" CLI for use in automation.
- [`tui/`](./tui) CLI that launches a fullscreen TUI built with [Ratatui](https://ratatui.rs/).
- [`cli/`](./cli) CLI multitool that provides the aforementioned CLIs via subcommands.
## Config
The CLI can be configured via `~/.codex/config.toml`. It supports the following options:
### model
The model that Codex should use.
```toml
model = "o3" # overrides the default of "o4-mini"
```
### model_provider
Codex comes bundled with a number of "model providers" predefined. This config value is a string that indicates which provider to use. You can also define your own providers via `model_providers`.
For example, if you are running ollama with Mistral locally, then you would need to add the following to your config:
```toml
model = "mistral"
model_provider = "ollama"
```
because the following definition for `ollama` is included in Codex:
```toml
[model_providers.ollama]
name = "Ollama"
base_url = "http://localhost:11434/v1"
wire_api = "chat"
```
This option defaults to `"openai"` and the corresponding provider is defined as follows:
```toml
[model_providers.openai]
name = "OpenAI"
base_url = "https://api.openai.com/v1"
env_key = "OPENAI_API_KEY"
wire_api = "responses"
```
### model_providers
This option lets you override and amend the default set of model providers bundled with Codex. This value is a map where the key is the value to use with `model_provider` to select the correspodning provider.
For example, if you wanted to add a provider that uses the OpenAI 4o model via the chat completions API, then you
```toml
# Recall that in TOML, root keys must be listed before tables.
model = "gpt-4o"
model_provider = "openai-chat-completions"
[model_providers.openai-chat-completions]
# Name of the provider that will be displayed in the Codex UI.
name = "OpenAI using Chat Completions"
# The path `/chat/completions` will be amended to this URL to make the POST
# request for the chat completions.
base_url = "https://api.openai.com/v1"
# If `env_key` is set, identifies an environment variable that must be set when
# using Codex with this provider. The value of the environment variable must be
# non-empty and will be used in the `Bearer TOKEN` HTTP header for the POST request.
env_key = "OPENAI_API_KEY"
# valid values for wire_api are "chat" and "responses".
wire_api = "chat"
```
### approval_policy
Determines when the user should be prompted to approve whether Codex can execute a command:
```toml
# This is analogous to --suggest in the TypeScript Codex CLI
approval_policy = "unless-allow-listed"
```
```toml
# If the command fails when run in the sandbox, Codex asks for permission to
# retry the command outside the sandbox.
approval_policy = "on-failure"
```
```toml
# User is never prompted: if the command fails, Codex will automatically try
# something out. Note the `exec` subcommand always uses this mode.
approval_policy = "never"
```
### sandbox_permissions
List of permissions to grant to the sandbox that Codex uses to execute untrusted commands:
```toml
# This is comparable to --full-auto in the TypeScript Codex CLI, though
# specifying `disk-write-platform-global-temp-folder` adds /tmp as a writable
# folder in addition to $TMPDIR.
sandbox_permissions = [
"disk-full-read-access",
"disk-write-platform-user-temp-folder",
"disk-write-platform-global-temp-folder",
"disk-write-cwd",
]
```
To add additional writable folders, use `disk-write-folder`, which takes a parameter (this can be specified multiple times):
```toml
sandbox_permissions = [
# ...
"disk-write-folder=/Users/mbolin/.pyenv/shims",
]
```
### mcp_servers
Defines the list of MCP servers that Codex can consult for tool use. Currently, only servers that are launched by executing a program that communicate over stdio are supported. For servers that use the SSE transport, consider an adapter like [mcp-proxy](https://github.com/sparfenyuk/mcp-proxy).
**Note:** Codex may cache the list of tools and resources from an MCP server so that Codex can include this information in context at startup without spawning all the servers. This is designed to save resources by loading MCP servers lazily.
This config option is comparable to how Claude and Cursor define `mcpServers` in their respective JSON config files, though because Codex uses TOML for its config language, the format is slightly different. For example, the following config in JSON:
```json
{
"mcpServers": {
"server-name": {
"command": "npx",
"args": ["-y", "mcp-server"],
"env": {
"API_KEY": "value"
}
}
}
}
```
Should be represented as follows in `~/.codex/config.toml`:
```toml
# IMPORTANT: the top-level key is `mcp_servers` rather than `mcpServers`.
[mcp_servers.server-name]
command = "npx"
args = ["-y", "mcp-server"]
env = { "API_KEY" = "value" }
```
### disable_response_storage
Currently, customers whose accounts are set to use Zero Data Retention (ZDR) must set `disable_response_storage` to `true` so that Codex uses an alternative to the Responses API that works with ZDR:
```toml
disable_response_storage = true
```
### notify
Specify a program that will be executed to get notified about events generated by Codex. Note that the program will receive the notification argument as a string of JSON, e.g.:
```json
{
"type": "agent-turn-complete",
"turn-id": "12345",
"input-messages": ["Rename `foo` to `bar` and update the callsites."],
"last-assistant-message": "Rename complete and verified `cargo build` succeeds."
}
```
The `"type"` property will always be set. Currently, `"agent-turn-complete"` is the only notification type that is supported.
As an example, here is a Python script that parses the JSON and decides whether to show a desktop push notification using [terminal-notifier](https://github.com/julienXX/terminal-notifier) on macOS:
```python
#!/usr/bin/env python3
import json
import subprocess
import sys
def main() -> int:
if len(sys.argv) != 2:
print("Usage: notify.py <NOTIFICATION_JSON>")
return 1
try:
notification = json.loads(sys.argv[1])
except json.JSONDecodeError:
return 1
match notification_type := notification.get("type"):
case "agent-turn-complete":
assistant_message = notification.get("last-assistant-message")
if assistant_message:
title = f"Codex: {assistant_message}"
else:
title = "Codex: Turn Complete!"
input_messages = notification.get("input_messages", [])
message = " ".join(input_messages)
title += message
case _:
print(f"not sending a push notification for: {notification_type}")
return 0
subprocess.check_output(
[
"terminal-notifier",
"-title",
title,
"-message",
message,
"-group",
"codex",
"-ignoreDnD",
"-activate",
"com.googlecode.iterm2",
]
)
return 0
if __name__ == "__main__":
sys.exit(main())
```
To have Codex use this script for notifications, you would configure it via `notify` in `~/.codex/config.toml` using the appropriate path to `notify.py` on your computer:
```toml
notify = ["python3", "/Users/mbolin/.codex/notify.py"]
```