Commit Graph

27 Commits

  • chore: introduce ModelFamily abstraction (#1838)
    To date, we have a number of hardcoded OpenAI model slug checks spread
    throughout the codebase, which makes it hard to audit the various
    special cases for each model. To mitigate this issue, this PR introduces
    the idea of a `ModelFamily` that has fields to represent the existing
    special cases, such as `supports_reasoning_summaries` and
    `uses_local_shell_tool`.
    
    There is a `find_family_for_model()` function that maps the raw model
    slug to a `ModelFamily`. This function hardcodes all the knowledge about
    the special attributes for each model. This PR then replaces the
    hardcoded model name checks with checks against a `ModelFamily`.
    
    Note `ModelFamily` is now available as `Config::model_family`. We should
    ultimately remove `Config::model` in favor of
    `Config::model_family::slug`.
  • [codex] stop printing error message when --output-last-message is not specified (#1828)
    Previously, `codex exec` was printing `Warning: no file to write last
    message to` as a warning to stderr even though `--output-last-message`
    was not specified, which is wrong. This fixes the code and changes
    `handle_last_message()` so that it is only called when
    `last_message_path` is `Some`.
  • Update render name in tui for approval_policy to match with config values (#1675)
    Currently, codex on start shows the value for the approval policy as
    name of
    [AskForApproval](https://github.com/openai/codex/blob/2437a8d17a0cf972d1a6e7f303d469b6e2f57eae/codex-rs/core/src/protocol.rs#L128)
    enum, which differs from
    [approval_policy](https://github.com/openai/codex/blob/2437a8d17a0cf972d1a6e7f303d469b6e2f57eae/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.
  • Flaky CI fix (#1647)
    Flushing before sending `TaskCompleteEvent` and ending the submission
    loop to avoid race conditions.
  • feat: add --json flag to codex exec (#1603)
    This is designed to facilitate programmatic use of Codex in a more
    lightweight way than using `codex mcp`.
    
    Passing `--json` to `codex exec` will print each event as a line of JSON
    to stdout. Note that it does not print the individual tokens as they are
    streamed, only full messages, as this is aimed at programmatic use
    rather than to power UI.
    
    <img width="1348" height="1307" alt="image"
    src="https://github.com/user-attachments/assets/fc7908de-b78d-46e4-a6ff-c85de28415c7"
    />
    
    I changed the existing `EventProcessor` into a trait and moved the
    implementation to `EventProcessorWithHumanOutput`. Then I introduced an
    alternative implementation, `EventProcessorWithJsonOutput`. The `--json`
    flag determines which implementation to use.
  • Add streaming to exec and tui (#1594)
    Added support for streaming in `tui`
    Added support for streaming in `exec`
    
    
    https://github.com/user-attachments/assets/4215892e-d940-452c-a1d0-416ed0cf14eb
  • 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)
    ```
  • 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
  • fix: pretty-print the sandbox config in the TUI/exec modes (#1376)
    Now that https://github.com/openai/codex/pull/1373 simplified the
    sandbox config, we can print something much simpler in the TUI (and in
    `codex exec`) to summarize the sandbox config.
    
    Before:
    
    ![Screenshot 2025-06-24 at 5 45
    52 PM](https://github.com/user-attachments/assets/b7633efb-a619-43e1-9abe-7bb0be2d0ec0)
    
    With this change:
    
    ![Screenshot 2025-06-24 at 5 46
    44 PM](https://github.com/user-attachments/assets/8d099bdd-a429-4796-a08d-70931d984e4f)
    
    For reference, my `config.toml` contains:
    
    ```
    [sandbox]
    mode = "workspace-write"
    writable_roots = ["/tmp", "/Users/mbolin/.pyenv/shims"]
    ```
    
    Fixes https://github.com/openai/codex/issues/1248
  • 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.
  • feat: show the version when starting Codex (#1182)
    The TypeScript version of the CLI shows the version when it starts up,
    which is helpful when users share screenshots (and nice to know, as a
    user).
  • feat: add hide_agent_reasoning config option (#1181)
    This PR introduces a `hide_agent_reasoning` config option (that defaults
    to `false`) that users can enable to make the output less verbose by
    suppressing reasoning output.
    
    To test, verified that this includes agent reasoning in the output:
    
    ```
    echo hello | just exec
    ```
    
    whereas this does not:
    
    ```
    echo hello | just exec --config hide_agent_reasoning=false
    ```
  • feat: dim the timestamp in the exec output (#1180)
    This required changing `ts_println!()` to take `$self:ident`, which is a
    bit more verbose, but the usability improvement seems worth it.
    
    Also eliminated an unnecessary `.to_string()` while here.
  • feat: grab-bag of improvements to exec output (#1179)
    Fixes:
    
    * Instantiate `EventProcessor` earlier in `lib.rs` so
    `print_config_summary()` can be an instance method of it and leverage
    its various `Style` fields to ensure it honors `with_ansi` properly.
    * After printing the config summary, print out user's prompt with the
    heading `User instructions:`. As noted in the comment, now that we can
    read the instructions via stdin as of #1178, it is helpful to the user
    to ensure they know what instructions were given to Codex.
    * Use same colors/bold/italic settings for headers as the TUI, making
    the output a bit easier to read.
  • fix: introduce ResponseInputItem::McpToolCallOutput variant (#1151)
    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:
    
    
    https://github.com/openai/codex/blob/25a9949c49194d5a64de54a11bcc5b4724ac9bd5/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 https://github.com/benjajaja/ratatui-image/blob/9705ce2c59ec669abbce2924cbfd1f5ae22c9860/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.
  • feat: show Config overview at start of exec (#1073)
    Now the `exec` output starts with something like:
    
    ```
    --------
    workdir:  /Users/mbolin/code/codex/codex-rs
    model:  o3
    provider:  openai
    approval:  Never
    sandbox:  SandboxPolicy { permissions: [DiskFullReadAccess, DiskWritePlatformUserTempFolder, DiskWritePlatformGlobalTempFolder, DiskWriteCwd, DiskWriteFolder { folder: "/Users/mbolin/.pyenv/shims" }] }
    --------
    ```
    
    which makes it easier to reason about when looking at logs.
  • 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.
  • chore: update exec crate to use std::time instead of chrono (#952)
    When I originally wrote `elapsed.rs`, I realized we were using both
    `std::time` and `chrono` with no real benefit of having both. We should
    try to keep the `exec` subcommand trim (as it also buildable as a
    standalone executable), so this helps tighten things up.
  • feat: record messages from user in ~/.codex/history.jsonl (#939)
    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:
    
    
    https://github.com/openai/codex/blob/3fdf9df1335ac9501e3fb0e61715359145711e8b/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.
  • chore: handle all cases for EventMsg (#936)
    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.
  • fix: change EventMsg enum so every variant takes a single struct (#925)
    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.
  • chore: introduce codex-common crate (#843)
    I started this PR because I wanted to share the `format_duration()`
    utility function in `codex-rs/exec/src/event_processor.rs` with the TUI.
    The question was: where to put it?
    
    `core` should have as few dependencies as possible, so moving it there
    would introduce a dependency on `chrono`, which seemed undesirable.
    `core` already had this `cli` feature to deal with a similar situation
    around sharing common utility functions, so I decided to:
    
    * make `core` feature-free
    * introduce `common`
    * `common` can have as many "special interest" features as it needs,
    each of which can declare their own deps
    * the first two features of common are `cli` and `elapsed`
    
    In practice, this meant updating a number of `Cargo.toml` files,
    replacing this line:
    
    ```toml
    codex-core = { path = "../core", features = ["cli"] }
    ```
    
    with these:
    
    ```toml
    codex-core = { path = "../core" }
    codex-common = { path = "../common", features = ["cli"] }
    ```
    
    Moving `format_duration()` into its own file gave it some "breathing
    room" to add a unit test, so I had Codex generate some tests and new
    support for durations over 1 minute.
  • feat: show MCP tool calls in codex exec subcommand (#841)
    This is analogous to the change for the TUI in
    https://github.com/openai/codex/pull/836, but for `codex exec`.
    
    To test, I ran:
    
    ```
    cargo run --bin codex-exec -- 'what is the weather in wellesley ma tomorrow'
    ```
    
    and saw:
    
    
    ![image](https://github.com/user-attachments/assets/5714e07f-88c7-4dd9-aa0d-be54c1670533)
  • feat: make cwd a required field of Config so we stop assuming std::env::current_dir() in a session (#800)
    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`.