This update replaces the previous ratatui history widget with an
append-only log so that the terminal can handle text selection and
scrolling. It also disables streaming responses, which we'll do our best
to bring back in a later PR. It also adds a small summary of token use
after the TUI exits.
Currently, codex on start shows the value for the approval policy as
name of
[AskForApproval](2437a8d17a/codex-rs/core/src/protocol.rs (L128))
enum, which differs from
[approval_policy](2437a8d17a/codex-rs/config.md (approval_policy))
config values.
E.g. "untrusted" becomes "UnlessTrusted", "on-failure" -> "OnFailure",
"never" -> "Never".
This PR changes render names of the approval policy to match with
configuration values.
1. Emit call_id to exec approval elicitations for mcp client convenience
2. Remove the `-retry` from the call id for the same reason as above but
upstream the reset behavior to the mcp client
## Summary
- extend rollout format to store all session data in JSON
- add resume/write helpers for rollouts
- track session state after each conversation
- support `LoadSession` op to resume a previous rollout
- allow starting Codex with an existing session via
`experimental_resume` config variable
We need a way later for exploring the available sessions in a user
friendly way.
## Testing
- `cargo test --no-run` *(fails: `cargo: command not found`)*
------
https://chatgpt.com/codex/tasks/task_i_68792a29dd5c832190bf6930d3466fba
This video is outdated. you should use `-c experimental_resume:<full
path>` instead of `--resume <full path>`
https://github.com/user-attachments/assets/7a9975c7-aa04-4f4e-899a-9e87defd947a
- Added support for message and reasoning deltas
- Skipped adding the support in the cli and tui for later
- Commented a failing test (wrong merge) that needs fix in a separate
PR.
Side note: I think we need to disable merge when the CI don't pass.
When using the OpenAI Responses API, we now record the `usage` field for
a `"response.completed"` event, which includes metrics about the number
of tokens consumed. We also introduce `openai_model_info.rs`, which
includes current data about the most common OpenAI models available via
the API (specifically `context_window` and `max_output_tokens`). If
Codex does not recognize the model, you can set `model_context_window`
and `model_max_output_tokens` explicitly in `config.toml`.
When then introduce a new event type to `protocol.rs`, `TokenCount`,
which includes the `TokenUsage` for the most recent turn.
Finally, we update the TUI to record the running sum of tokens used so
the percentage of available context window remaining can be reported via
the placeholder text for the composer:

We could certainly get much fancier with this (such as reporting the
estimated cost of the conversation), but for now, we are just trying to
achieve feature parity with the TypeScript CLI.
Though arguably this improves upon the TypeScript CLI, as the TypeScript
CLI uses heuristics to estimate the number of tokens used rather than
using the `usage` information directly:
296996d74e/codex-cli/src/utils/approximate-tokens-used.ts (L3-L16)
Fixes https://github.com/openai/codex/issues/1242
This PR reworks `assess_command_safety()` so that the combination of
`AskForApproval::Never` and `SandboxPolicy::DangerFullAccess` ensures
that commands are run without _any_ sandbox and the user should never be
prompted. In turn, it adds support for a new
`--dangerously-bypass-approvals-and-sandbox` flag (that cannot be used
with `--approval-policy` or `--full-auto`) that sets both of those
options.
Fixes https://github.com/openai/codex/issues/1254
For the `approval_policy` config option, renames `unless-allow-listed`
to `untrusted`. In general, when it comes to exec'ing commands, I think
"trusted" is a more accurate term than "safe."
Also drops the `AskForApproval::AutoEdit` variant, as we were not really
making use of it, anyway.
Fixes https://github.com/openai/codex/issues/1250.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/1378).
* #1379
* __->__ #1378
This is a major redesign of how sandbox configuration works and aims to
fix https://github.com/openai/codex/issues/1248. Specifically, it
replaces `sandbox_permissions` in `config.toml` (and the
`-s`/`--sandbox-permission` CLI flags) with a "table" with effectively
three variants:
```toml
# Safest option: full disk is read-only, but writes and network access are disallowed.
[sandbox]
mode = "read-only"
# The cwd of the Codex task is writable, as well as $TMPDIR on macOS.
# writable_roots can be used to specify additional writable folders.
[sandbox]
mode = "workspace-write"
writable_roots = [] # Optional, defaults to the empty list.
network_access = false # Optional, defaults to false.
# Disable sandboxing: use at your own risk!!!
[sandbox]
mode = "danger-full-access"
```
This should make sandboxing easier to reason about. While we have
dropped support for `-s`, the way it works now is:
- no flags => `read-only`
- `--full-auto` => `workspace-write`
- currently, there is no way to specify `danger-full-access` via a CLI
flag, but we will revisit that as part of
https://github.com/openai/codex/issues/1254
Outstanding issue:
- As noted in the `TODO` on `SandboxPolicy::is_unrestricted()`, we are
still conflating sandbox preferences with approval preferences in that
case, which needs to be cleaned up.
Previous to this PR, we always set `reasoning` when making a request
using the Responses API:
d7245cbbc9/codex-rs/core/src/client.rs (L108-L111)
Though if you tried to use the Rust CLI with `--model gpt-4.1`, this
would fail with:
```shell
"Unsupported parameter: 'reasoning.effort' is not supported with this model."
```
We take a cue from the TypeScript CLI, which does a check on the model
name:
d7245cbbc9/codex-cli/src/utils/agent/agent-loop.ts (L786-L789)
This PR does a similar check, though also adds support for the following
config options:
```
model_reasoning_effort = "low" | "medium" | "high" | "none"
model_reasoning_summary = "auto" | "concise" | "detailed" | "none"
```
This way, if you have a model whose name happens to start with `"o"` (or
`"codex"`?), you can set these to `"none"` to explicitly disable
reasoning, if necessary. (That said, it seems unlikely anyone would use
the Responses API with non-OpenAI models, but we provide an escape
hatch, anyway.)
This PR also updates both the TUI and `codex exec` to show `reasoning
effort` and `reasoning summaries` in the header.
The output of an MCP server tool call can be one of several types, but
to date, we treated all outputs as text by showing the serialized JSON
as the "tool output" in Codex:
25a9949c49/codex-rs/mcp-types/src/lib.rs (L96-L101)
This PR adds support for the `ImageContent` variant so we can now
display an image output from an MCP tool call.
In making this change, we introduce a new
`ResponseInputItem::McpToolCallOutput` variant so that we can work with
the `mcp_types::CallToolResult` directly when the function call is made
to an MCP server.
Though arguably the more significant change is the introduction of
`HistoryCell::CompletedMcpToolCallWithImageOutput`, which is a cell that
uses `ratatui_image` to render an image into the terminal. To support
this, we introduce `ImageRenderCache`, cache a
`ratatui_image::picker::Picker`, and `ensure_image_cache()` to cache the
appropriate scaled image data and dimensions based on the current
terminal size.
To test, I created a minimal `package.json`:
```json
{
"name": "kitty-mcp",
"version": "1.0.0",
"type": "module",
"description": "MCP that returns image of kitty",
"main": "index.js",
"dependencies": {
"@modelcontextprotocol/sdk": "^1.12.0"
}
}
```
with the following `index.js` to define the MCP server:
```js
#!/usr/bin/env node
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { readFile } from "node:fs/promises";
import { join } from "node:path";
const IMAGE_URI = "image://Ada.png";
const server = new McpServer({
name: "Demo",
version: "1.0.0",
});
server.tool(
"get-cat-image",
"If you need a cat image, this tool will provide one.",
async () => ({
content: [
{ type: "image", data: await getAdaPngBase64(), mimeType: "image/png" },
],
})
);
server.resource("Ada the Cat", IMAGE_URI, async (uri) => {
const base64Image = await getAdaPngBase64();
return {
contents: [
{
uri: uri.href,
mimeType: "image/png",
blob: base64Image,
},
],
};
});
async function getAdaPngBase64() {
const __dirname = new URL(".", import.meta.url).pathname;
// From 9705ce2c59/assets/Ada.png
const filePath = join(__dirname, "Ada.png");
const imageData = await readFile(filePath);
const base64Image = imageData.toString("base64");
return base64Image;
}
const transport = new StdioServerTransport();
await server.connect(transport);
```
With the local changes from this PR, I added the following to my
`config.toml`:
```toml
[mcp_servers.kitty]
command = "node"
args = ["/Users/mbolin/code/kitty-mcp/index.js"]
```
Running the TUI from source:
```
cargo run --bin codex -- --model o3 'I need a picture of a cat'
```
I get:
<img width="732" alt="image"
src="https://github.com/user-attachments/assets/bf80b721-9ca0-4d81-aec7-77d6899e2869"
/>
Now, that said, I have only tested in iTerm and there is definitely some
funny business with getting an accurate character-to-pixel ratio
(sometimes the `CompletedMcpToolCallWithImageOutput` thinks it needs 10
rows to render instead of 4), so there is still work to be done here.
This introduces an experimental `--output-last-message` flag that can be
used to identify a file where the final message from the agent will be
written. Two use cases:
- Ultimately, we will likely add a `--quiet` option to `exec`, but even
if the user does not want any output written to the terminal, they
probably want to know what the agent did. Writing the output to a file
makes it possible to get that information in a clean way.
- Relatedly, when using `exec` in CI, it is easier to review the
transcript written "normally," (i.e., not as JSON or something with
extra escapes), but getting programmatic access to the last message is
likely helpful, so writing the last message to a file gets the best of
both worlds.
I am calling this "experimental" because it is possible that we are
overfitting and will want a more general solution to this problem that
would justify removing this flag.
This is a large change to support a "history" feature like you would
expect in a shell like Bash.
History events are recorded in `$CODEX_HOME/history.jsonl`. Because it
is a JSONL file, it is straightforward to append new entries (as opposed
to the TypeScript file that uses `$CODEX_HOME/history.json`, so to be
valid JSON, each new entry entails rewriting the entire file). Because
it is possible for there to be multiple instances of Codex CLI writing
to `history.jsonl` at once, we use advisory file locking when working
with `history.jsonl` in `codex-rs/core/src/message_history.rs`.
Because we believe history is a sufficiently useful feature, we enable
it by default. Though to provide some safety, we set the file
permissions of `history.jsonl` to be `o600` so that other users on the
system cannot read the user's history. We do not yet support a default
list of `SENSITIVE_PATTERNS` as the TypeScript CLI does:
3fdf9df133/codex-cli/src/utils/storage/command-history.ts (L10-L17)
We are going to take a more conservative approach to this list in the
Rust CLI. For example, while `/\b[A-Za-z0-9-_]{20,}\b/` might exclude
sensitive information like API tokens, it would also exclude valuable
information such as references to Git commits.
As noted in the updated documentation, users can opt-out of history by
adding the following to `config.toml`:
```toml
[history]
persistence = "none"
```
Because `history.jsonl` could, in theory, be quite large, we take a[n
arguably overly pedantic] approach in reading history entries into
memory. Specifically, we start by telling the client the current number
of entries in the history file (`history_entry_count`) as well as the
inode (`history_log_id`) of `history.jsonl` (see the new fields on
`SessionConfiguredEvent`).
The client is responsible for keeping new entries in memory to create a
"local history," but if the user hits up enough times to go "past" the
end of local history, then the client should use the new
`GetHistoryEntryRequest` in the protocol to fetch older entries.
Specifically, it should pass the `history_log_id` it was given
originally and work backwards from `history_entry_count`. (It should
really fetch history in batches rather than one-at-a-time, but that is
something we can improve upon in subsequent PRs.)
The motivation behind this crazy scheme is that it is designed to defend
against:
* The `history.jsonl` being truncated during the session such that the
index into the history is no longer consistent with what had been read
up to that point. We do not yet have logic to enforce a `max_bytes` for
`history.jsonl`, but once we do, we will aspire to implement it in a way
that should result in a new inode for the file on most systems.
* New items from concurrent Codex CLI sessions amending to the history.
Because, in absence of truncation, `history.jsonl` is an append-only
log, so long as the client reads backwards from `history_entry_count`,
it should always get a consistent view of history. (That said, it will
not be able to read _new_ commands from concurrent sessions, but perhaps
we will introduce a `/` command to reload latest history or something
down the road.)
Admittedly, my testing of this feature thus far has been fairly light. I
expect we will find bugs and introduce enhancements/fixes going forward.
For now, this removes the `#[non_exhaustive]` directive on `EventMsg` so
that we are forced to handle all `EventMsg` by default. (We may revisit
this if/when we publish `core/` as a `lib` crate.) For now, it is
helpful to have this as a forcing function because we have effectively
two UIs (`tui` and `exec`) and usually when we add a new variant to
`EventMsg`, we want to be sure that we update both.
https://github.com/openai/codex/pull/922 did this for the
`SessionConfigured` enum variant, and I think it is generally helpful to
be able to work with the values as each enum variant as their own type,
so this converts the remaining variants and updates all of the
callsites.
Added a simple unit test to verify that the JSON-serialized version of
`Event` does not have any unexpected nesting.
* update `SessionConfigured` event to include the UUID for the session
* show the UUID in the Rust TUI
* use local timestamps in log files instead of UTC
* include timestamps in log file names for easier discovery
As shown in the screenshot, we now include reasoning messages from the
model in the TUI under the heading "codex reasoning":

To ensure these are visible by default when using `o4-mini`, this also
changes the default value for `summary` (formerly `generate_summary`,
which is deprecated in favor of `summary` according to the docs) from
unset to `"auto"`.
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.
This is the first step in supporting other model providers in the Rust
CLI. Specifically, this PR adds support for the new entries in `Config`
and `ConfigOverrides` to specify a `ModelProviderInfo`, which is the
basic config needed for an LLM provider. This PR does not get us all the
way there yet because `client.rs` still categorically appends
`/responses` to the URL and expects the endpoint to support the OpenAI
Responses API. Will fix that next!
This adds initial support for MCP servers in the style of Claude Desktop
and Cursor. Note this PR is the bare minimum to get things working end
to end: all configured MCP servers are launched every time Codex is run,
there is no recovery for MCP servers that crash, etc.
(Also, I took some shortcuts to change some fields of `Session` to be
`pub(crate)`, which also means there are circular deps between
`codex.rs` and `mcp_tool_call.rs`, but I will clean that up in a
subsequent PR.)
`codex-rs/README.md` is updated as part of this PR to explain how to use
this feature. There is a bit of plumbing to route the new settings from
`Config` to the business logic in `codex.rs`. The most significant
chunks for new code are in `mcp_connection_manager.rs` (which defines
the `McpConnectionManager` struct) and `mcp_tool_call.rs`, which is
responsible for tool calls.
This PR also introduces new `McpToolCallBegin` and `McpToolCallEnd`
event types to the protocol, but does not add any handlers for them.
(See https://github.com/openai/codex/pull/836 for initial usage.)
To test, I added the following to my `~/.codex/config.toml`:
```toml
# Local build of https://github.com/hideya/mcp-server-weather-js
[mcp_servers.weather]
command = "/Users/mbolin/code/mcp-server-weather-js/dist/index.js"
args = []
```
And then I ran the following:
```
codex-rs$ cargo run --bin codex exec 'what is the weather in san francisco'
[2025-05-06T22:40:05] Task started: 1
[2025-05-06T22:40:18] Agent message: Here’s the latest National Weather Service forecast for San Francisco (downtown, near 37.77° N, 122.42° W):
This Afternoon (Tue):
• Sunny, high near 69 °F
• West-southwest wind around 12 mph
Tonight:
• Partly cloudy, low around 52 °F
• SW wind 7–10 mph
...
```
Note that Codex itself is not able to make network calls, so it would
not normally be able to get live weather information like this. However,
the weather MCP is [currently] not run under the Codex sandbox, so it is
able to hit `api.weather.gov` and fetch current weather information.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/829).
* #836
* __->__ #829
In order to expose Codex via an MCP server, I realized that we should be
taking `cwd` as a parameter rather than assuming
`std::env::current_dir()` as the `cwd`. Specifically, the user may want
to start a session in a directory other than the one where the MCP
server has been started.
This PR makes `cwd: PathBuf` a required field of `Session` and threads
it all the way through, though I think there is still an issue with not
honoring `workdir` for `apply_patch`, which is something we also had to
fix in the TypeScript version: https://github.com/openai/codex/pull/556.
This also adds `-C`/`--cd` to change the cwd via the command line.
To test, I ran:
```
cargo run --bin codex -- exec -C /tmp 'show the output of ls'
```
and verified it showed the contents of my `/tmp` folder instead of
`$PWD`.
With this change, you can specify a program that will be executed to get
notified about events generated by Codex. The notification info will be
packaged as a JSON object. The supported notification types are defined
by the `UserNotification` enum introduced in this PR. Initially, it
contains only one variant, `AgentTurnComplete`:
```rust
pub(crate) enum UserNotification {
#[serde(rename_all = "kebab-case")]
AgentTurnComplete {
turn_id: String,
/// Messages that the user sent to the agent to initiate the turn.
input_messages: Vec<String>,
/// The last message sent by the assistant in the turn.
last_assistant_message: Option<String>,
},
}
```
This is intended to support the common case when a "turn" ends, which
often means it is now your chance to give Codex further instructions.
For example, I have the following in my `~/.codex/config.toml`:
```toml
notify = ["python3", "/Users/mbolin/.codex/notify.py"]
```
I created my own custom notifier script that calls out to
[terminal-notifier](https://github.com/julienXX/terminal-notifier) to
show a desktop push notification on macOS. Contents of `notify.py`:
```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())
```
For reference, here are related PRs that tried to add this functionality
to the TypeScript version of the Codex CLI:
* https://github.com/openai/codex/pull/160
* https://github.com/openai/codex/pull/498
Previous to this PR, `SandboxPolicy` was a bit difficult to work with:
237f8a11e1/codex-rs/core/src/protocol.rs (L98-L108)
Specifically:
* It was an `enum` and therefore options were mutually exclusive as
opposed to additive.
* It defined things in terms of what the agent _could not_ do as opposed
to what they _could_ do. This made things hard to support because we
would prefer to build up a sandbox config by starting with something
extremely restrictive and only granting permissions for things the user
as explicitly allowed.
This PR changes things substantially by redefining the policy in terms
of two concepts:
* A `SandboxPermission` enum that defines permissions that can be
granted to the agent/sandbox.
* A `SandboxPolicy` that internally stores a `Vec<SandboxPermission>`,
but externally exposes a simpler API that can be used to configure
Seatbelt/Landlock.
Previous to this PR, we supported a `--sandbox` flag that effectively
mapped to an enum value in `SandboxPolicy`. Though now that
`SandboxPolicy` is a wrapper around `Vec<SandboxPermission>`, the single
`--sandbox` flag no longer makes sense. While I could have turned it
into a flag that the user can specify multiple times, I think the
current values to use with such a flag are long and potentially messy,
so for the moment, I have dropped support for `--sandbox` altogether and
we can bring it back once we have figured out the naming thing.
Since `--sandbox` is gone, users now have to specify `--full-auto` to
get a sandbox that allows writes in `cwd`. Admittedly, there is no clean
way to specify the equivalent of `--full-auto` in your `config.toml`
right now, so we will have to revisit that, as well.
Because `Config` presents a `SandboxPolicy` field and `SandboxPolicy`
changed considerably, I had to overhaul how config loading works, as
well. There are now two distinct concepts, `ConfigToml` and `Config`:
* `ConfigToml` is the deserialization of `~/.codex/config.toml`. As one
might expect, every field is `Optional` and it is `#[derive(Deserialize,
Default)]`. Consistent use of `Optional` makes it clear what the user
has specified explicitly.
* `Config` is the "normalized config" and is produced by merging
`ConfigToml` with `ConfigOverrides`. Where `ConfigToml` contains a raw
`Option<Vec<SandboxPermission>>`, `Config` presents only the final
`SandboxPolicy`.
The changes to `core/src/exec.rs` and `core/src/linux.rs` merit extra
special attention to ensure we are faithfully mapping the
`SandboxPolicy` to the Seatbelt and Landlock configs, respectively.
Also, take note that `core/src/seatbelt_readonly_policy.sbpl` has been
renamed to `codex-rs/core/src/seatbelt_base_policy.sbpl` and that
`(allow file-read*)` has been removed from the `.sbpl` file as now this
is added to the policy in `core/src/exec.rs` when
`sandbox_policy.has_full_disk_read_access()` is `true`.
This changes how instantiating `Config` works and also adds
`approval_policy` and `sandbox_policy` as fields. The idea is:
* All fields of `Config` have appropriate default values.
* `Config` is initially loaded from `~/.codex/config.toml`, so values in
`config.toml` will override those defaults.
* Clients must instantiate `Config` via
`Config::load_with_overrides(ConfigOverrides)` where `ConfigOverrides`
has optional overrides that are expected to be settable based on CLI
flags.
The `Config` should be defined early in the program and then passed
down. Now functions like `init_codex()` take fewer individual parameters
because they can just take a `Config`.
Also, `Config::load()` used to fail silently if `~/.codex/config.toml`
had a parse error and fell back to the default config. This seemed
really bad because it wasn't clear why the values in my `config.toml`
weren't getting picked up. I changed things so that
`load_with_overrides()` returns `Result<Config>` and verified that the
various CLIs print a reasonable error if `config.toml` is malformed.
Finally, I also updated the TUI to show which **sandbox** value is being
used, as we do for other key values like **model** and **approval**.
This was also a reminder that the various values of `--sandbox` are
honored on Linux but not macOS today, so I added some TODOs about fixing
that.
This adds support for the `--disable-response-storage` flag across our
multiple Rust CLIs to support customers who have opted into Zero-Data
Retention (ZDR). The analogous changes to the TypeScript CLI were:
* https://github.com/openai/codex/pull/481
* https://github.com/openai/codex/pull/543
For a client using ZDR, `previous_response_id` will never be available,
so the `input` field of an API request must include the full transcript
of the conversation thus far. As such, this PR changes the type of
`Prompt.input` from `Vec<ResponseInputItem>` to `Vec<ResponseItem>`.
Practically speaking, `ResponseItem` was effectively a "superset" of
`ResponseInputItem` already. The main difference for us is that
`ResponseItem` includes the `FunctionCall` variant that we have to
include as part of the conversation history in the ZDR case.
Another key change in this PR is modifying `try_run_turn()` so that it
returns the `Vec<ResponseItem>` for the turn in addition to the
`Vec<ResponseInputItem>` produced by `try_run_turn()`. This is because
the caller of `run_turn()` needs to record the `Vec<ResponseItem>` when
ZDR is enabled.
To that end, this PR introduces `ZdrTranscript` (and adds
`zdr_transcript: Option<ZdrTranscript>` to `struct State` in `codex.rs`)
to take responsibility for maintaining the conversation transcript in
the ZDR case.
##### What/Why
This PR makes it so that in Linux we actually respect the different
types of `--sandbox` flag, such that users can apply network and
filesystem restrictions in combination (currently the only supported
behavior), or just pick one or the other.
We should add similar support for OSX in a future PR.
##### Testing
From Linux devbox, updated tests to use more specific flags:
```
test linux::tests_linux::sandbox_blocks_ping ... ok
test linux::tests_linux::sandbox_blocks_getent ... ok
test linux::tests_linux::test_root_read ... ok
test linux::tests_linux::test_dev_null_write ... ok
test linux::tests_linux::sandbox_blocks_dev_tcp_redirection ... ok
test linux::tests_linux::sandbox_blocks_ssh ... ok
test linux::tests_linux::test_writable_root ... ok
test linux::tests_linux::sandbox_blocks_curl ... ok
test linux::tests_linux::sandbox_blocks_wget ... ok
test linux::tests_linux::sandbox_blocks_nc ... ok
test linux::tests_linux::test_root_write - should panic ... ok
```
##### Todo
- [ ] Add negative tests (e.g. confirm you can hit the network if you
configure filesystem only restrictions)
As stated in `codex-rs/README.md`:
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.