Commit Graph

83 Commits

  • Tint chat composer background (#1921)
    ## Summary
    - give the chat composer a subtle custom background and apply it across
    the full area drawn
    
    <img width="1008" height="718" alt="composer-bg"
    src="https://github.com/user-attachments/assets/4b0f7f69-722a-438a-b4e9-0165ae8865a6"
    />
    
    - update turn interrupted to be more human readable
    <img width="648" height="170" alt="CleanShot 2025-08-06 at 22 44 47@2x"
    src="https://github.com/user-attachments/assets/8d35e53a-bbfa-48e7-8612-c280a54e01dd"
    />
    
    ## Testing
    - `cargo test --all-features` *(fails: `let` expressions in
    `core/src/client.rs` require newer rustc)*
    - `just fix` *(fails: `let` expressions in `core/src/client.rs` require
    newer rustc)*
    
    ------
    https://chatgpt.com/codex/tasks/task_i_68941f32c1008322bbcc39ee1d29a526
  • Ensure exec command end always emitted (#1908)
    ## Summary
    - defer ExecCommandEnd emission until after sandbox resolution
    - make sandbox error handler return final exec output and response
    - align sandbox error stderr with response content and rename to
    `final_output`
    - replace unstable `let` chains in client command header logic
    
    ## Testing
    - `just fmt`
    - `just fix`
    - `cargo test --all-features` *(fails: NotPresent in
    core/tests/client.rs)*
    
    ------
    https://chatgpt.com/codex/tasks/task_i_6893e63b0c408321a8e1ff2a052c4c51
  • [env] Remove git config for now (#1884)
    ## Summary
    Forgot to remove this in #1869 last night! Too much of a performance hit
    on the main thread. We can bring it back via an async thread on startup.
  • [prompts] Add <environment_context> (#1869)
    ## Summary
    Includes a new user message in the api payload which provides useful
    environment context for the model, so it knows about things like the
    current working directory and the sandbox.
    
    ## Testing
    Updated unit tests
  • [approval_policy] Add OnRequest approval_policy (#1865)
    ## Summary
    A split-up PR of #1763 , stacked on top of a tools refactor #1858 to
    make the change clearer. From the previous summary:
    
    > Let's try something new: tell the model about the sandbox, and let it
    decide when it will need to break the sandbox. Some local testing
    suggests that it works pretty well with zero iteration on the prompt!
    
    ## Testing
    - [x] Added unit tests
    - [x] Tested locally and it appears to work smoothly!
  • [core] Separate tools config from openai client (#1858)
    ## Summary
    In an effort to make tools easier to work with and more configurable,
    I'm introducing `ToolConfig` and updating `Prompt` to take in a general
    list of Tools. I think this is simpler and better for a few reasons:
    - We can easily assemble tools from various sources (our own harness,
    mcp servers, etc.) and we can consolidate the logic for constructing the
    logic in one place that is separate from serialization.
    - client.rs no longer needs arbitrary config values, it just takes in a
    list of tools to serialize
    
    A hefty portion of the PR is now updating our conversion of
    `mcp_types::Tool` to `OpenAITool`, but considering that @bolinfest
    accurately called this out as a TODO long ago, I think it's time we
    tackled it.
    
    ## Testing
    - [x] Experimented locally, no changes, as expected
    - [x] Added additional unit tests
    - [x] Responded to rust-review
  • [core] Stop escalating timeouts (#1853)
    ## Summary
    Escalating out of sandbox is (almost always) not going to fix
    long-running commands timing out - therefore we should just pass the
    failure back to the model instead of asking the user to re-run a command
    that took a long time anyway.
    
    ## Testing
    - [x] Ran locally with a timeout and confirmed this worked as expected
  • Rescue chat completion changes (#1846)
    https://github.com/openai/codex/pull/1835 has some messed up history.
    
    This adds support for streaming chat completions, which is useful for ollama. We should probably take a very skeptical eye to the code introduced in this PR.
    
    ---------
    
    Co-authored-by: Ahmed Ibrahim <aibrahim@openai.com>
  • Stream model responses (#1810)
    Stream models thoughts and responses instead of waiting for the whole
    thing to come through. Very rough right now, but I'm making the risk call to push through.
  • Add a TurnDiffTracker to create a unified diff for an entire turn (#1770)
    This lets us show an accumulating diff across all patches in a turn.
    Refer to the docs for TurnDiffTracker for implementation details.
    
    There are multiple ways this could have been done and this felt like the
    right tradeoff between reliability and completeness:
    *Pros*
    * It will pick up all changes to files that the model touched including
    if they prettier or another command that updates them.
    * It will not pick up changes made by the user or other agents to files
    it didn't modify.
    
    *Cons*
    * It will pick up changes that the user made to a file that the model
    also touched
    * It will not pick up changes to codegen or files that were not modified
    with apply_patch
  • fix command duration display (#1806)
    we were always displaying "0ms" before.
    
    <img width="731" height="101" alt="Screenshot 2025-08-02 at 10 51 22 PM"
    src="https://github.com/user-attachments/assets/f56814ed-b9a4-4164-9e78-181c60ce19b7"
    />
  • Fix compact (#1798)
    We are not recording the summary in the history.
  • feat: stream exec stdout events (#1786)
    ## Summary
    - stream command stdout as `ExecCommandStdout` events
    - forward streamed stdout to clients and ignore in human output
    processor
    - adjust call sites for new streaming API
  • Add /compact (#1527)
    - Add operation to summarize the context so far.
    - The operation runs a compact task that summarizes the context.
    - The operation clear the previous context to free the context window
    - The operation didn't use `run_task` to avoid corrupting the session
    - Add /compact in the tui
    
    
    
    https://github.com/user-attachments/assets/e06c24e5-dcfb-4806-934a-564d425a919c
  • fix: ensure PatchApplyBeginEvent and PatchApplyEndEvent are dispatched reliably (#1760)
    This is a follow-up to https://github.com/openai/codex/pull/1705, as
    that PR inadvertently lost the logic where `PatchApplyBeginEvent` and
    `PatchApplyEndEvent` events were sent when patches were auto-approved.
    
    Though as part of this fix, I believe this also makes an important
    safety fix to `assess_patch_safety()`, as there was a case that returned
    `SandboxType::None`, which arguably is the thing we were trying to avoid
    in #1705.
    
    On a high level, we want there to be only one codepath where
    `apply_patch` happens, which should be unified with the patch to run
    `exec`, in general, so that sandboxing is applied consistently for both
    cases.
    
    Prior to this change, `apply_patch()` in `core` would either:
    
    * exit early, delegating to `exec()` to shell out to `apply_patch` using
    the appropriate sandbox
    * proceed to run the logic for `apply_patch` in memory
    
    
    https://github.com/openai/codex/blob/549846b29ad52f6cb4f8560365a731966054a9b3/codex-rs/core/src/apply_patch.rs#L61-L63
    
    In this implementation, only the latter would dispatch
    `PatchApplyBeginEvent` and `PatchApplyEndEvent`, though the former would
    dispatch `ExecCommandBeginEvent` and `ExecCommandEndEvent` for the
    `apply_patch` call (or, more specifically, the `codex
    --codex-run-as-apply-patch PATCH` call).
    
    To unify things in this PR, we:
    
    * Eliminate the back half of the `apply_patch()` function, and instead
    have it also return with `DelegateToExec`, though we add an extra field
    to the return value, `user_explicitly_approved_this_action`.
    * In `codex.rs` where we process `DelegateToExec`, we use
    `SandboxType::None` when `user_explicitly_approved_this_action` is
    `true`. This means **we no longer run the apply_patch logic in memory**,
    as we always `exec()`. (Note this is what allowed us to delete so much
    code in `apply_patch.rs`.)
    * In `codex.rs`, we further update `notify_exec_command_begin()` and
    `notify_exec_command_end()` to take additional fields to determine what
    type of notification to send: `ExecCommand` or `PatchApply`.
    
    Admittedly, this PR also drops some of the functionality about giving
    the user the opportunity to expand the set of writable roots as part of
    approving the `apply_patch` command. I'm not sure how much that was
    used, and we should probably rethink how that works as we are currently
    tidying up the protocol to the TUI, in general.
  • fix: run apply_patch calls through the sandbox (#1705)
    Building on the work of https://github.com/openai/codex/pull/1702, this
    changes how a shell call to `apply_patch` is handled.
    
    Previously, a shell call to `apply_patch` was always handled in-process,
    never leveraging a sandbox. To determine whether the `apply_patch`
    operation could be auto-approved, the
    `is_write_patch_constrained_to_writable_paths()` function would check if
    all the paths listed in the paths were writable. If so, the agent would
    apply the changes listed in the patch.
    
    Unfortunately, this approach afforded a loophole: symlinks!
    
    * For a soft link, we could fix this issue by tracing the link and
    checking whether the target is in the set of writable paths, however...
    * ...For a hard link, things are not as simple. We can run `stat FILE`
    to see if the number of links is greater than 1, but then we would have
    to do something potentially expensive like `find . -inum <inode_number>`
    to find the other paths for `FILE`. Further, even if this worked, this
    approach runs the risk of a
    [TOCTOU](https://en.wikipedia.org/wiki/Time-of-check_to_time-of-use)
    race condition, so it is not robust.
    
    The solution, implemented in this PR, is to take the virtual execution
    of the `apply_patch` CLI into an _actual_ execution using `codex
    --codex-run-as-apply-patch PATCH`, which we can run under the sandbox
    the user specified, just like any other `shell` call.
    
    This, of course, assumes that the sandbox prevents writing through
    symlinks as a mechanism to write to folders that are not in the writable
    set configured by the sandbox. I verified this by testing the following
    on both Mac and Linux:
    
    ```shell
    #!/usr/bin/env bash
    set -euo pipefail
    
    # Can running a command in SANDBOX_DIR write a file in EXPLOIT_DIR?
    
    # Codex is run in SANDBOX_DIR, so writes should be constrianed to this directory.
    SANDBOX_DIR=$(mktemp -d -p "$HOME" sandboxtesttemp.XXXXXX)
    # EXPLOIT_DIR is outside of SANDBOX_DIR, so let's see if we can write to it.
    EXPLOIT_DIR=$(mktemp -d -p "$HOME" sandboxtesttemp.XXXXXX)
    
    echo "SANDBOX_DIR: $SANDBOX_DIR"
    echo "EXPLOIT_DIR: $EXPLOIT_DIR"
    
    cleanup() {
      # Only remove if it looks sane and still exists
      [[ -n "${SANDBOX_DIR:-}" && -d "$SANDBOX_DIR" ]] && rm -rf -- "$SANDBOX_DIR"
      [[ -n "${EXPLOIT_DIR:-}" && -d "$EXPLOIT_DIR" ]] && rm -rf -- "$EXPLOIT_DIR"
    }
    
    trap cleanup EXIT
    
    echo "I am the original content" > "${EXPLOIT_DIR}/original.txt"
    
    # Drop the -s to test hard links.
    ln -s "${EXPLOIT_DIR}/original.txt" "${SANDBOX_DIR}/link-to-original.txt"
    
    cat "${SANDBOX_DIR}/link-to-original.txt"
    
    if [[ "$(uname)" == "Linux" ]]; then
        SANDBOX_SUBCOMMAND=landlock
    else
        SANDBOX_SUBCOMMAND=seatbelt
    fi
    
    # Attempt the exploit
    cd "${SANDBOX_DIR}"
    
    codex debug "${SANDBOX_SUBCOMMAND}" bash -lc "echo pwned > ./link-to-original.txt" || true
    
    cat "${EXPLOIT_DIR}/original.txt"
    ```
    
    Admittedly, this change merits a proper integration test, but I think I
    will have to do that in a follow-up PR.
  • Add support for a separate chatgpt auth endpoint (#1712)
    Adds a `CodexAuth` type that encapsulates information about available
    auth modes and logic for refreshing the token.
    Changes `Responses` API to send requests to different endpoints based on
    the auth type.
    Updates login_with_chatgpt to support API-less mode and skip the key
    exchange.
  • Add an experimental plan tool (#1726)
    This adds a tool the model can call to update a plan. The tool doesn't
    actually _do_ anything but it gives clients a chance to read and render
    the structured plan. We will likely iterate on the prompt and tools
    exposed for planning over time.
  • chore: split apply_patch logic out of codex.rs and into apply_patch.rs (#1703)
    This is a straight refactor, moving apply-patch-related code from
    `codex.rs` and into the new `apply_patch.rs` file. The only "logical"
    change is inlining `#[allow(clippy::unwrap_used)]` instead of declaring
    `#![allow(clippy::unwrap_used)]` at the top of the file (which is
    currently the case in `codex.rs`).
    
    ---
    [//]: # (BEGIN SAPLING FOOTER)
    Stack created with [Sapling](https://sapling-scm.com). Best reviewed
    with [ReviewStack](https://reviewstack.dev/openai/codex/pull/1703).
    * #1705
    * __->__ #1703
    * #1702
    * #1698
    * #1697
  • chore: update Codex::spawn() to return a struct instead of a tuple (#1677)
    Also update `init_codex()` to return a `struct` instead of a tuple, as well.
  • Record Git metadata to rollout (#1598)
    # Summary
    
    - Writing effective evals for codex sessions requires context of the
    overall repository state at the moment the session began
    - This change adds this metadata (git repository, branch, commit hash)
    to the top of the rollout of the session (if available - if not it
    doesn't add anything)
    - Currently, this is only effective on a clean working tree, as we can't
    track uncommitted/untracked changes with the current metadata set.
    Ideally in the future we may want to track unclean changes somehow, or
    perhaps prompt the user to stash or commit them.
    
    # Testing
    - Added unit tests
    - `cargo test && cargo clippy --tests && cargo fmt -- --config
    imports_granularity=Item`
    
    ### Resulting Rollout
    <img width="1243" height="127" alt="Screenshot 2025-07-17 at 1 50 00 PM"
    src="https://github.com/user-attachments/assets/68108941-f015-45b2-985c-ea315ce05415"
    />
  • Flaky CI fix (#1647)
    Flushing before sending `TaskCompleteEvent` and ending the submission
    loop to avoid race conditions.
  • Add call_id to patch approvals and elicitations (#1660)
    Builds on https://github.com/openai/codex/pull/1659 and adds call_id to
    a few more places for the same reason.
  • Improve messages emitted for exec failures (#1659)
    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
  • Always send entire request context (#1641)
    Always store the entire conversation history.
    Request encrypted COT when not storing Responses.
    Send entire input context instead of sending previous_response_id
  • Add support for custom base instructions (#1645)
    Allows providing custom instructions file as a config parameter and
    custom instruction text via MCP tool call.
  • [mcp-server] Add reply tool call (#1643)
    ## Summary
    Adds a new mcp tool call, `codex-reply`, so we can continue existing
    sessions. This is a first draft and does not yet support sessions from
    previous processes.
    
    ## Testing
    - [x] tested with mcp client
  • chore: support MCP schema 2025-06-18 (#1621)
    This updates the schema in `generate_mcp_types.py` from `2025-03-26` to
    `2025-06-18`, regenerates `mcp-types/src/lib.rs`, and then updates all
    the code that uses `mcp-types` to honor the changes.
    
    Ran
    
    ```
    npx @modelcontextprotocol/inspector just codex mcp
    ```
    
    and verified that I was able to invoke the `codex` tool, as expected.
    
    
    ---
    [//]: # (BEGIN SAPLING FOOTER)
    Stack created with [Sapling](https://sapling-scm.com). Best reviewed
    with [ReviewStack](https://reviewstack.dev/openai/codex/pull/1621).
    * #1623
    * #1622
    * __->__ #1621
  • Add session loading support to Codex (#1602)
    ## 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
  • Refactor env settings into config (#1601)
    ## Summary
    - add OpenAI retry and timeout fields to Config
    - inject these settings in tests instead of mutating env vars
    - plumb Config values through client and chat completions logic
    - document new configuration options
    
    ## Testing
    - `cargo test -p codex-core --no-run`
    
    ------
    https://chatgpt.com/codex/tasks/task_i_68792c5b04cc832195c03050c8b6ea94
    
    ---------
    
    Co-authored-by: Michael Bolin <mbolin@openai.com>
  • feat: ensure session ID header is sent in Response API request (#1614)
    Include the current session id in Responses API requests.
  • fix: trim MCP tool names to fit into tool name length limit (#1571)
    Store fully qualified names along with tool entries so we don't have to re-parse them.
    
    Fixes: https://github.com/openai/codex/issues/1289
  • support deltas in core (#1587)
    - 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.
  • feat: add new config option: model_supports_reasoning_summaries (#1524)
    As noted in the updated docs, this makes it so that you can set:
    
    ```toml
    model_supports_reasoning_summaries = true
    ```
    
    as a way of overriding the existing heuristic for when to set the
    `reasoning` field on a sampling request:
    
    
    https://github.com/openai/codex/blob/341c091c5b09dc706ab5c7d629516e6ef5aaf902/codex-rs/core/src/client_common.rs#L152-L166
  • chore(rs): update dependencies (#1494)
    ### Chores
    - Update cargo dependencies
    - Remove unused cargo dependencies
    - Fix clippy warnings
    - Update Dockerfile (package.json requires node 22)
    - Let Dependabot update bun, cargo, devcontainers, docker,
    github-actions, npm (nix still not supported)
    
    ### TODO
    - Upgrade dependencies with breaking changes
    
    ```shell
    $ cargo update --verbose
       Unchanged crossterm v0.28.1 (available: v0.29.0)
       Unchanged schemars v0.8.22 (available: v1.0.4)
    ```
  • [Rust] Allow resuming a session that was killed with ctrl + c (#1387)
    Previously, if you ctrl+c'd a conversation, all subsequent turns would
    400 because the Responses API never got a response for one of its call
    ids. This ensures that if we aren't sending a call id by hand, we
    generate a synthetic aborted call.
    
    Fixes #1244 
    
    
    https://github.com/user-attachments/assets/5126354f-b970-45f5-8c65-f811bca8294a
  • feat: show number of tokens remaining in UI (#1388)
    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:
    
    ![Screenshot 2025-06-25 at 11 20
    55 PM](https://github.com/user-attachments/assets/6fd6982f-7247-4f14-84b2-2e600cb1fd49)
    
    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:
    
    
    https://github.com/openai/codex/blob/296996d74e345b1b05d8c3451a06ace21c5ada96/codex-cli/src/utils/approximate-tokens-used.ts#L3-L16
    
    Fixes https://github.com/openai/codex/issues/1242
  • feat: add --dangerously-bypass-approvals-and-sandbox (#1384)
    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
  • fix: always send full instructions when using the Responses API (#1207)
    This fixes a longstanding error in the Rust CLI where `codex.rs`
    contained an errant `is_first_turn` check that would exclude the user
    instructions for subsequent "turns" of a conversation when using the
    responses API (i.e., when `previous_response_id` existed).
    
    While here, renames `Prompt.instructions` to `Prompt.user_instructions`
    since we now have quite a few levels of instructions floating around.
    Also removed an unnecessary use of `clone()` in
    `Prompt.get_full_instructions()`.
  • feat: make reasoning effort/summaries configurable (#1199)
    Previous to this PR, we always set `reasoning` when making a request
    using the Responses API:
    
    
    https://github.com/openai/codex/blob/d7245cbbc9d8ff5446da45e5951761103492476d/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:
    
    
    https://github.com/openai/codex/blob/d7245cbbc9d8ff5446da45e5951761103492476d/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.
  • fix: chat completions API now also passes tools along (#1167)
    Prior to this PR, there were two big misses in `chat_completions.rs`:
    
    1. The loop in `stream_chat_completions()` was only including items of
    type `ResponseItem::Message` when building up the `"messages"` JSON for
    the `POST` request to the `chat/completions` endpoint. This fixes things
    by ensuring other variants (`FunctionCall`, `LocalShellCall`, and
    `FunctionCallOutput`) are included, as well.
    2. In `process_chat_sse()`, we were not recording tool calls and were
    only emitting items of type
    `ResponseEvent::OutputItemDone(ResponseItem::Message)` to the stream.
    Now we introduce `FunctionCallState`, which is used to accumulate the
    `delta`s of type `tool_calls`, so we can ultimately emit a
    `ResponseItem::FunctionCall`, when appropriate.
    
    While function calling now appears to work for chat completions with my
    local testing, I believe that there are still edge cases that are not
    covered and that this codepath would benefit from a battery of
    integration tests. (As part of that further cleanup, we should also work
    to support streaming responses in the UI.)
    
    The other important part of this PR is some cleanup in
    `core/src/codex.rs`. In particular, it was hard to reason about how
    `run_task()` was building up the list of messages to include in a
    request across the various cases:
    
    - Responses API
    - Chat Completions API
    - Responses API used in concert with ZDR
    
    I like to think things are a bit cleaner now where:
    
    - `zdr_transcript` (if present) contains all messages in the history of
    the conversation, which includes function call outputs that have not
    been sent back to the model yet
    - `pending_input` includes any messages the user has submitted while the
    turn is in flight that need to be injected as part of the next `POST` to
    the model
    - `input_for_next_turn` includes the tool call outputs that have not
    been sent back to the model yet
  • fix: overhaul how we spawn commands under seccomp/landlock on Linux (#1086)
    Historically, we spawned the Seatbelt and Landlock sandboxes in
    substantially different ways:
    
    For **Seatbelt**, we would run `/usr/bin/sandbox-exec` with our policy
    specified as an arg followed by the original command:
    
    
    https://github.com/openai/codex/blob/d1de7bb383552e8fadd94be79d65d188e00fd562/codex-rs/core/src/exec.rs#L147-L219
    
    For **Landlock/Seccomp**, we would do
    `tokio::runtime::Builder::new_current_thread()`, _invoke
    Landlock/Seccomp APIs to modify the permissions of that new thread_, and
    then spawn the command:
    
    
    https://github.com/openai/codex/blob/d1de7bb383552e8fadd94be79d65d188e00fd562/codex-rs/core/src/exec_linux.rs#L28-L49
    
    While it is neat that Landlock/Seccomp supports applying a policy to
    only one thread without having to apply it to the entire process, it
    requires us to maintain two different codepaths and is a bit harder to
    reason about. The tipping point was
    https://github.com/openai/codex/pull/1061, in which we had to start
    building up the `env` in an unexpected way for the existing
    Landlock/Seccomp approach to continue to work.
    
    This PR overhauls things so that we do similar things for Mac and Linux.
    It turned out that we were already building our own "helper binary"
    comparable to Mac's `sandbox-exec` as part of the `cli` crate:
    
    
    https://github.com/openai/codex/blob/d1de7bb383552e8fadd94be79d65d188e00fd562/codex-rs/cli/Cargo.toml#L10-L12
    
    We originally created this to build a small binary to include with the
    Node.js version of the Codex CLI to provide support for Linux
    sandboxing.
    
    Though the sticky bit is that, at this point, we still want to deploy
    the Rust version of Codex as a single, standalone binary rather than a
    CLI and a supporting sandboxing binary. To satisfy this goal, we use
    "the arg0 trick," in which we:
    
    * use `std::env::current_exe()` to get the path to the CLI that is
    currently running
    * use the CLI as the `program` for the `Command`
    * set `"codex-linux-sandbox"` as arg0 for the `Command`
    
    A CLI that supports sandboxing should check arg0 at the start of the
    program. If it is `"codex-linux-sandbox"`, it must invoke
    `codex_linux_sandbox::run_main()`, which runs the CLI as if it were
    `codex-linux-sandbox`. When acting as `codex-linux-sandbox`, we make the
    appropriate Landlock/Seccomp API calls and then use `execvp(3)` to spawn
    the original command, so do _replace_ the process rather than spawn a
    subprocess. Incidentally, we do this before starting the Tokio runtime,
    so the process should only have one thread when `execvp(3)` is called.
    
    Because the `core` crate that needs to spawn the Linux sandboxing is not
    a CLI in its own right, this means that every CLI that includes `core`
    and relies on this behavior has to (1) implement it and (2) provide the
    path to the sandboxing executable. While the path is almost always
    `std::env::current_exe()`, we needed to make this configurable for
    integration tests, so `Config` now has a `codex_linux_sandbox_exe:
    Option<PathBuf>` property to facilitate threading this through,
    introduced in https://github.com/openai/codex/pull/1089.
    
    This common pattern is now captured in
    `codex_linux_sandbox::run_with_sandbox()` and all of the `main.rs`
    functions that should use it have been updated as part of this PR.
    
    The `codex-linux-sandbox` crate added to the Cargo workspace as part of
    this PR now has the bulk of the Landlock/Seccomp logic, which makes
    `core` a bit simpler. Indeed, `core/src/exec_linux.rs` and
    `core/src/landlock.rs` were removed/ported as part of this PR. I also
    moved the unit tests for this code into an integration test,
    `linux-sandbox/tests/landlock.rs`, in which I use
    `env!("CARGO_BIN_EXE_codex-linux-sandbox")` as the value for
    `codex_linux_sandbox_exe` since `std::env::current_exe()` is not
    appropriate in that case.
  • feat: introduce support for shell_environment_policy in config.toml (#1061)
    To date, when handling `shell` and `local_shell` tool calls, we were
    spawning new processes using the environment inherited from the Codex
    process itself. This means that the sensitive `OPENAI_API_KEY` that
    Codex needs to talk to OpenAI models was made available to everything
    run by `shell` and `local_shell`. While there are cases where that might
    be useful, it does not seem like a good default.
    
    This PR introduces a complex `shell_environment_policy` config option to
    control the `env` used with these tool calls. It is inevitably a bit
    complex so that it is possible to override individual components of the
    policy so without having to restate the entire thing.
    
    Details are in the updated `README.md` in this PR, but here is the
    relevant bit that explains the individual fields of
    `shell_environment_policy`:
    
    | Field | Type | Default | Description |
    | ------------------------- | -------------------------- | ------- |
    -----------------------------------------------------------------------------------------------------------------------------------------------
    |
    | `inherit` | string | `core` | Starting template for the
    environment:<br>`core` (`HOME`, `PATH`, `USER`, …), `all` (clone full
    parent env), or `none` (start empty). |
    | `ignore_default_excludes` | boolean | `false` | When `false`, Codex
    removes any var whose **name** contains `KEY`, `SECRET`, or `TOKEN`
    (case-insensitive) before other rules run. |
    | `exclude` | array&lt;string&gt; | `[]` | Case-insensitive glob
    patterns to drop after the default filter.<br>Examples: `"AWS_*"`,
    `"AZURE_*"`. |
    | `set` | table&lt;string,string&gt; | `{}` | Explicit key/value
    overrides or additions – always win over inherited values. |
    | `include_only` | array&lt;string&gt; | `[]` | If non-empty, a
    whitelist of patterns; only variables that match _one_ pattern survive
    the final step. (Generally used with `inherit = "all"`.) |
    
    
    In particular, note that the default is `inherit = "core"`, so:
    
    * if you have extra env variables that you want to inherit from the
    parent process, use `inherit = "all"` and then specify `include_only`
    * if you have extra env variables where you want to hardcode the values,
    the default `inherit = "core"` will work fine, but then you need to
    specify `set`
    
    This configuration is not battle-tested, so we will probably still have
    to play with it a bit. `core/src/exec_env.rs` has the critical business
    logic as well as unit tests.
    
    Though if nothing else, previous to this change:
    
    ```
    $ cargo run --bin codex -- debug seatbelt -- printenv OPENAI_API_KEY
    # ...prints OPENAI_API_KEY...
    ```
    
    But after this change it does not print anything (as desired).
    
    One final thing to call out about this PR is that the
    `configure_command!` macro we use in `core/src/exec.rs` has to do some
    complex logic with respect to how it builds up the `env` for the process
    being spawned under Landlock/seccomp. Specifically, doing
    `cmd.env_clear()` followed by `cmd.envs(&$env_map)` (which is arguably
    the most intuitive way to do it) caused the Landlock unit tests to fail
    because the processes spawned by the unit tests started failing in
    unexpected ways! If we forgo `env_clear()` in favor of updating env vars
    one at a time, the tests still pass. The comment in the code talks about
    this a bit, and while I would like to investigate this more, I need to
    move on for the moment, but I do plan to come back to it to fully
    understand what is going on. For example, this suggests that we might
    not be able to spawn a C program that calls `env_clear()`, which would
    be...weird. We may still have to fiddle with our Landlock config if that
    is the case.
  • feat: experimental --output-last-message flag to exec subcommand (#1037)
    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.
  • feat: add support for OpenAI tool type, local_shell (#961)
    The new `codex-mini-latest` model expects a new tool with `{"type":
    "local_shell"}`. Its contract is similar to the existing `function` tool
    with `"name": "shell"`, so this takes the `local_shell` tool call into
    `ExecParams` and sends it through the existing
    `handle_container_exec_with_params()` code path.
    
    This also adds the following logic when adding the default set of tools
    to a request:
    
    ```rust
    let default_tools = if self.model.starts_with("codex") {
        &DEFAULT_CODEX_MODEL_TOOLS
    } else {
        &DEFAULT_TOOLS
    };
    ```
    
    That is, if the model name starts with `"codex"`, we add `{"type":
    "local_shell"}` to the list of tools; otherwise, we add the
    aforementioned `shell` tool.
    
    To test this, I ran the TUI with `-m codex-mini-latest` and verified
    that it used the `local_shell` tool. Though I also had some entries in
    `[mcp_servers]` in my personal `config.toml`. The `codex-mini-latest`
    model seemed eager to try the tools from the MCP servers first, so I
    have personally commented them out for now, so keep an eye out if you're
    testing `codex-mini-latest`!
    
    Perhaps we should include more details with `{"type": "local_shell"}` or
    update the following:
    
    
    https://github.com/openai/codex/blob/fd0b1b020818dfe8aaf7eb68425f09e86ab1b819/codex-rs/core/prompt.md
    
    For reference, the corresponding change in the TypeScript CLI is
    https://github.com/openai/codex/pull/951.