Commit Graph

110 Commits

  • Remove legacy ModelInfo and merge it with ModelFamily (#7748)
    This is a step towards removing the need to know `model` when
    constructing config. We firstly don't need to know `model_info` and just
    respect if the user has already set it. Next step, we don't need to know
    `model` unless the user explicitly set it in `config.toml`
  • feat: exec policy integration in shell mcp (#7609)
    adding execpolicy support into the `posix` mcp
    
    Co-authored-by: Michael Bolin <mbolin@openai.com>
  • Inline response recording and remove process_items indirection (#7310)
    - Inline response recording during streaming: `run_turn` now records
    items as they arrive instead of building a `ProcessedResponseItem` list
    and post‑processing via `process_items`.
    - Simplify turn handling: `handle_output_item_done` returns the
    follow‑up signal + optional tool future; `needs_follow_up` is set only
    there, and in‑flight tool futures are drained once at the end (errors
    logged, no extra state writes).
    - Flattened stream loop: removed `process_items` indirection and the
    extra output queue
    - - Tests: relaxed `tool_parallelism::tool_results_grouped` to allow any
    completion order while still requiring matching call/output IDs.
  • Migrate model family to models manager (#7565)
    This PR moves `ModelsFamily` to `openai_models`. It also propagates
    `ModelsManager` to session services and use it to drive model family. We
    also make `derive_default_model_family` private because it's a step
    towards what we want: one place that gives model configuration.
    
    This is a second step at having one source of truth for models
    information and config: `ModelsManager`.
    
    Next steps would be to remove `ModelsFamily` from config. That's massive
    because it's being used in 41 occasions mostly pre launching `codex`.
    Also, we need to make `find_family_for_model` private. It's also big
    because it's being used in 21 occasions ~ all tests.
  • Migrate model preset (#7542)
    - Introduce `openai_models` in `/core`
    - Move `PRESETS` under it
    - Move `ModelPreset`, `ModelUpgrade`, `ReasoningEffortPreset`,
    `ReasoningEffortPreset`, and `ReasoningEffortPreset` to `protocol`
    - Introduce `Op::ListModels` and `EventMsg::AvailableModels`
    
    Next steps:
    - migrate `app-server` and `tui` to use the introduced Operation
  • feat: experimental support for skills.md (#7412)
    This change prototypes support for Skills with the CLI. This is an
    **experimental** feature for internal testing.
    
    ---------
    
    Co-authored-by: Gav Verma <gverma@openai.com>
  • feat: declare server capability in shell-tool-mcp (#7112)
    This introduces a new feature to Codex when it operates as an MCP
    _client_ where if an MCP _server_ replies that it has an entry named
    `"codex/sandbox-state"` in its _server capabilities_, then Codex will
    send it an MCP notification with the following structure:
    
    ```json
    {
      "method": "codex/sandbox-state/update",
      "params": {
        "sandboxPolicy": {
          "type": "workspace-write",
          "network-access": false,
          "exclude-tmpdir-env-var": false
          "exclude-slash-tmp": false
        },
        "codexLinuxSandboxExe": null,
        "sandboxCwd": "/Users/mbolin/code/codex2"
      }
    }
    ```
    
    or with whatever values are appropriate for the initial `sandboxPolicy`.
    
    **NOTE:** Codex _should_ continue to send the MCP server notifications
    of the same format if these things change over the lifetime of the
    thread, but that isn't wired up yet.
    
    The result is that `shell-tool-mcp` can consume these values so that
    when it calls `codex_core::exec::process_exec_tool_call()` in
    `codex-rs/exec-server/src/posix/escalate_server.rs`, it is now sure to
    call it with the correct values (whereas previously we relied on
    hardcoded values).
    
    While I would argue this is a supported use case within the MCP
    protocol, the `rmcp` crate that we are using today does not support
    custom notifications. As such, I had to patch it and I submitted it for
    review, so hopefully it will be accepted in some form:
    
    https://github.com/modelcontextprotocol/rust-sdk/pull/556
    
    To test out this change from end-to-end:
    
    - I ran `cargo build` in `~/code/codex2/codex-rs/exec-server`
    - I built the fork of Bash in `~/code/bash/bash`
    - I added the following to my `~/.codex/config.toml`:
    
    ```toml
    # Use with `codex --disable shell_tool`.
    [mcp_servers.execshell]
    args = ["--bash", "/Users/mbolin/code/bash/bash"]
    command = "/Users/mbolin/code/codex2/codex-rs/target/debug/codex-exec-mcp-server"
    ```
    
    - From `~/code/codex2/codex-rs`, I ran `just codex --disable shell_tool`
    - When the TUI started up, I verified that the sandbox mode is
    `workspace-write`
    - I ran `/mcp` to verify that the shell tool from the MCP is there:
    
    <img width="1387" height="1400" alt="image"
    src="https://github.com/user-attachments/assets/1a8addcc-5005-4e16-b59f-95cfd06fd4ab"
    />
    
    - Then I asked it:
    
    > what is the output of `gh issue list`
    
    because this should be auto-approved with our existing dummy policy:
    
    
    https://github.com/openai/codex/blob/af63e6eccc35783f1bf4dca3c61adb090efb6b8a/codex-rs/exec-server/src/posix.rs#L157-L164
    
    And it worked:
    
    <img width="1387" height="1400" alt="image"
    src="https://github.com/user-attachments/assets/7568d2f7-80da-4d68-86d0-c265a6f5e6c1"
    />
  • Fix: Improve text encoding for shell output in VSCode preview (#6178) (#6182)
    ## 🐛 Problem
    
    Users running commands with non-ASCII characters (like Russian text
    "пример") in Windows/WSL environments experience garbled text in
    VSCode's shell preview window, with Unicode replacement characters (�)
    appearing instead of the actual text.
    
    **Issue**: https://github.com/openai/codex/issues/6178
    
    ## 🔧 Root Cause
    
    The issue was in `StreamOutput<Vec<u8>>::from_utf8_lossy()` method in
    `codex-rs/core/src/exec.rs`, which used `String::from_utf8_lossy()` to
    convert shell output bytes to strings. This function immediately
    replaces any invalid UTF-8 byte sequences with replacement characters,
    without attempting to decode using other common encodings.
    
    In Windows/WSL environments, shell output often uses encodings like:
    
    - Windows-1252 (common Windows encoding)
    - Latin-1/ISO-8859-1 (extended ASCII)
    
    ## 🛠️ Solution
    
    Replaced the simple `String::from_utf8_lossy()` call with intelligent
    encoding detection via a new `bytes_to_string_smart()` function that
    tries multiple encoding strategies:
    
    1. **UTF-8** (fast path for valid UTF-8)
    2. **Windows-1252** (handles Windows-specific characters in 0x80-0x9F
    range)
    3. **Latin-1** (fallback for extended ASCII)
    4. **Lossy UTF-8** (final fallback, same as before)
    
    ## 📁 Changes
    
    ### New Files
    
    - `codex-rs/core/src/text_encoding.rs` - Smart encoding detection module
    - `codex-rs/core/tests/suite/text_encoding_fix.rs` - Integration tests
    
    ### Modified Files
    
    - `codex-rs/core/src/lib.rs` - Added text_encoding module
    - `codex-rs/core/src/exec.rs` - Updated StreamOutput::from_utf8_lossy()
    - `codex-rs/core/tests/suite/mod.rs` - Registered new test module
    
    ##  Testing
    
    - **5 unit tests** covering UTF-8, Windows-1252, Latin-1, and fallback
    scenarios
    - **2 integration tests** simulating the exact Issue #6178 scenario
    - **Demonstrates improvement** over the previous
    `String::from_utf8_lossy()` approach
    
    All tests pass:
    
    ```bash
    cargo test -p codex-core text_encoding
    cargo test -p codex-core test_shell_output_encoding_issue_6178
    ```
    
    ## 🎯 Impact
    
    -  **Eliminates garbled text** in VSCode shell preview for non-ASCII
    content
    -  **Supports Windows/WSL environments** with proper encoding detection
    -  **Zero performance impact** for UTF-8 text (fast path)
    -  **Backward compatible** - UTF-8 content works exactly as before
    -  **Handles edge cases** with robust fallback mechanism
    
    ## 🧪 Test Scenarios
    
    The fix has been tested with:
    
    - Russian text ("пример")
    - Windows-1252 quotation marks (""test")
    - Latin-1 accented characters ("café")
    - Mixed encoding content
    - Invalid byte sequences (graceful fallback)
    
    ## 📋 Checklist
    
    - [X] Addresses the reported issue
    - [X] Includes comprehensive tests
    - [X] Maintains backward compatibility
    - [X] Follows project coding conventions
    - [X] No breaking changes
    
    ---------
    
    Co-authored-by: Josh McKinney <joshka@openai.com>
  • execpolicy2 core integration (#6641)
    This PR threads execpolicy2 into codex-core.
    
    activated via feature flag: exec_policy (on by default)
    
    reads and parses all .codexpolicy files in `codex_home/codex`
    
    refactored tool runtime API to integrate execpolicy logic
    
    ---------
    
    Co-authored-by: Michael Bolin <mbolin@openai.com>
  • feat: remote compaction (#6795)
    Co-authored-by: pakrym-oai <pakrym@openai.com>
  • fix(windows) shell_command on windows, minor parsing (#6811)
    ## Summary
    Enables shell_command for windows users, and starts adding some basic
    command parsing here, to at least remove powershell prefixes. We'll
    follow this up with command parsing but I wanted to land this change
    separately with some basic UX.
    
    **NOTE**: This implementation parses bash and powershell on both
    platforms. In theory this is possible, since you can use git bash on
    windows or powershell on linux. In practice, this may not be worth the
    complexity of supporting, so I don't feel strongly about the current
    approach vs. platform-specific branching.
    
    ## Testing
    - [x] Added a bunch of tests 
    - [x] Ran on both windows and os x
  • LM Studio OSS Support (#2312)
    ## Overview
    
    Adds LM Studio OSS support. Closes #1883
    
    
    ### Changes
    This PR enhances the behavior of `--oss` flag to support LM Studio as a
    provider. Additionally, it introduces a new flag`--local-provider` which
    can take in `lmstudio` or `ollama` as values if the user wants to
    explicitly choose which one to use.
    
    If no provider is specified `codex --oss` will auto-select the provider
    based on whichever is running.
    
    #### Additional enhancements 
    The default can be set using `oss-provider` in config like:
    
    ```
    oss_provider = "lmstudio"
    ```
    
    For non-interactive users, they will need to either provide the provider
    as an arg or have it in their `config.toml`
    
    ### Notes
    For best performance, [set the default context
    length](https://lmstudio.ai/docs/app/advanced/per-model) for gpt-oss to
    the maximum your machine can support
    
    ---------
    
    Co-authored-by: Matt Clayton <matt@lmstudio.ai>
    Co-authored-by: Eric Traut <etraut@openai.com>
  • Add user command event types (#6246)
    adding new user command event, logic in TUI to render user command
    events
  • [app-server] feat: v2 Thread APIs (#6214)
    Implements:
    ```
    thread/list
    thread/start
    thread/resume
    thread/archive
    ```
    
    along with their integration tests. These are relatively light wrappers
    around the existing core logic, and changes to core logic are minimal.
    
    However, an improvement made for developer ergonomics:
    - `thread/start` and `thread/resume` automatically attaches a
    conversation listener internally, so clients don't have to make a
    separate `AddConversationListener` call like they do today.
    
    For consistency, also updated `model/list` and `feedback/upload` (naming
    conventions, list API params).
  • refactor Conversation history file into its own directory (#6229)
    This is just a refactor of `conversation_history` file by breaking it up
    into multiple smaller ones with helper. This refactor will help us move
    more functionality related to context management here. in a clean way.
  • Do not skip trust prompt on Windows if sandbox is enabled. (#6167)
    If the experimental windows sandbox is enabled, the trust prompt should
    show on Windows.
  • Delegate review to codex instance (#5572)
    In this PR, I am exploring migrating task kind to an invocation of
    Codex. The main reason would be getting rid off multiple
    `ConversationHistory` state and streamlining our context/history
    management.
    
    This approach depends on opening a channel between the sub-codex and
    codex. This channel is responsible for forwarding `interactive`
    (`approvals`) and `non-interactive` events. The `task` is responsible
    for handling those events.
    
    This opens the door for implementing `codex as a tool`, replacing
    `compact` and `review`, and potentially subagents.
    
    One consideration is this code is very similar to `app-server` specially
    in the approval part. If in the future we wanted an interactive
    `sub-codex` we should consider using `codex-mcp`
  • feat: introduce GetConversationSummary RPC (#5803)
    This adds an RPC to the app server to the the `ConversationSummary` via
    a rollout path. Now that the VS Code extension supports showing the
    Codex UI in an editor panel where the URI of the panel maps to the
    rollout file, we need to be able to get the `ConversationSummary` from
    the rollout file directly.
  • Handle cancelling/aborting while processing a turn (#5543)
    Currently we collect all all turn items in a vector, then we add it to
    the history on success. This result in losing those items on errors
    including aborting `ctrl+c`.
    
    This PR:
    - Adds the ability for the tool call to handle cancellation
    - bubble the turn items up to where we are recording this info
    
    Admittedly, this logic is an ad-hoc logic that doesn't handle a lot of
    error edge cases. The right thing to do is recording to the history on
    the spot as `items`/`tool calls output` come. However, this isn't
    possible because of having different `task_kind` that has different
    `conversation_histories`. The `try_run_turn` has no idea what thread are
    we using. We cannot also pass an `arc` to the `conversation_histories`
    because it's a private element of `state`.
    
    That's said, `abort` is the most common case and we should cover it
    until we remove `task kind`
  • Add new thread items and rewire event parsing to use them (#5418)
    1. Adds AgentMessage,  Reasoning,  WebSearch items.
    2. Switches the ResponseItem parsing to use new items and then also emit
    3. Removes user-item kind and filters out "special" (environment) user
    items when returning to clients.
  • chore: rework tools execution workflow (#5278)
    Re-work the tool execution flow. Read `orchestrator.rs` to understand
    the structure
  • feat: feature flag (#4948)
    Add proper feature flag instead of having custom flags for everything.
    This is just for experimental/wip part of the code
    It can be used through CLI:
    ```bash
    codex --enable unified_exec --disable view_image_tool
    ```
    
    Or in the `config.toml`
    ```toml
    # Global toggles applied to every profile unless overridden.
    [features]
    apply_patch_freeform = true
    view_image_tool = false
    ```
    
    Follow-up:
    In a following PR, the goal is to have a default have `bundles` of
    features that we can associate to a model
  • [MCP] Add auth status to MCP servers (#4918)
    This adds a queryable auth status for MCP servers which is useful:
    1. To determine whether a streamable HTTP server supports auth or not
    based on whether or not it supports RFC 8414-3.2
    2. Allow us to build a better user experience on top of MCP status
  • add(core): managed config (#3868)
    ## Summary
    
    - Factor `load_config_as_toml` into `core::config_loader` so config
    loading is reusable across callers.
    - Layer `~/.codex/config.toml`, optional `~/.codex/managed_config.toml`,
    and macOS managed preferences (base64) with recursive table merging and
    scoped threads per source.
    
    ## Config Flow
    
    ```
    Managed prefs (macOS profile: com.openai.codex/config_toml_base64)
                                   ▲
                                   │
    ~/.codex/managed_config.toml   │  (optional file-based override)
                                   ▲
                                   │
                    ~/.codex/config.toml (user-defined settings)
    ```
    
    - The loader searches under the resolved `CODEX_HOME` directory
    (defaults to `~/.codex`).
    - Managed configs let administrators ship fleet-wide overrides via
    device profiles which is useful for enforcing certain settings like
    sandbox or approval defaults.
    - For nested hash tables: overlays merge recursively. Child tables are
    merged key-by-key, while scalar or array values replace the prior layer
    entirely. This lets admins add or tweak individual fields without
    clobbering unrelated user settings.
  • chore: refactor tool handling (#4510)
    # Tool System Refactor
    
    - Centralizes tool definitions and execution in `core/src/tools/*`:
    specs (`spec.rs`), handlers (`handlers/*`), router (`router.rs`),
    registry/dispatch (`registry.rs`), and shared context (`context.rs`).
    One registry now builds the model-visible tool list and binds handlers.
    - Router converts model responses to tool calls; Registry dispatches
    with consistent telemetry via `codex-rs/otel` and unified error
    handling. Function, Local Shell, MCP, and experimental `unified_exec`
    all flow through this path; legacy shell aliases still work.
    - Rationale: reduce per‑tool boilerplate, keep spec/handler in sync, and
    make adding tools predictable and testable.
    
    Example: `read_file`
    - Spec: `core/src/tools/spec.rs` (see `create_read_file_tool`,
    registered by `build_specs`).
    - Handler: `core/src/tools/handlers/read_file.rs` (absolute `file_path`,
    1‑indexed `offset`, `limit`, `L#: ` prefixes, safe truncation).
    - E2E test: `core/tests/suite/read_file.rs` validates the tool returns
    the requested lines.
    
    ## Next steps:
    - Decompose `handle_container_exec_with_params` 
    - Add parallel tool calls
  • chore: sandbox refactor 2 (#4653)
    Revert the revert and fix the UI issue
  • Separate interactive and non-interactive sessions (#4612)
    Do not show exec session in VSCode/TUI selector.
  • chore: sanbox extraction (#4286)
    # Extract and Centralize Sandboxing
    - Goal: Improve safety and clarity by centralizing sandbox planning and
    execution.
      - Approach:
    - Add planner (ExecPlan) and backend registry (Direct/Seatbelt/Linux)
    with run_with_plan.
    - Refactor codex.rs to plan-then-execute; handle failures/escalation via
    the plan.
    - Delegate apply_patch to the codex binary and run it with an empty env
    for determinism.
  • OpenTelemetry events (#2103)
    ### Title
    
    ## otel
    
    Codex can emit [OpenTelemetry](https://opentelemetry.io/) **log events**
    that
    describe each run: outbound API requests, streamed responses, user
    input,
    tool-approval decisions, and the result of every tool invocation. Export
    is
    **disabled by default** so local runs remain self-contained. Opt in by
    adding an
    `[otel]` table and choosing an exporter.
    
    ```toml
    [otel]
    environment = "staging"   # defaults to "dev"
    exporter = "none"          # defaults to "none"; set to otlp-http or otlp-grpc to send events
    log_user_prompt = false    # defaults to false; redact prompt text unless explicitly enabled
    ```
    
    Codex tags every exported event with `service.name = "codex-cli"`, the
    CLI
    version, and an `env` attribute so downstream collectors can distinguish
    dev/staging/prod traffic. Only telemetry produced inside the
    `codex_otel`
    crate—the events listed below—is forwarded to the exporter.
    
    ### Event catalog
    
    Every event shares a common set of metadata fields: `event.timestamp`,
    `conversation.id`, `app.version`, `auth_mode` (when available),
    `user.account_id` (when available), `terminal.type`, `model`, and
    `slug`.
    
    With OTEL enabled Codex emits the following event types (in addition to
    the
    metadata above):
    
    - `codex.api_request`
      - `cf_ray` (optional)
      - `attempt`
      - `duration_ms`
      - `http.response.status_code` (optional)
      - `error.message` (failures)
    - `codex.sse_event`
      - `event.kind`
      - `duration_ms`
      - `error.message` (failures)
      - `input_token_count` (completion only)
      - `output_token_count` (completion only)
      - `cached_token_count` (completion only, optional)
      - `reasoning_token_count` (completion only, optional)
      - `tool_token_count` (completion only)
    - `codex.user_prompt`
      - `prompt_length`
      - `prompt` (redacted unless `log_user_prompt = true`)
    - `codex.tool_decision`
      - `tool_name`
      - `call_id`
    - `decision` (`approved`, `approved_for_session`, `denied`, or `abort`)
      - `source` (`config` or `user`)
    - `codex.tool_result`
      - `tool_name`
      - `call_id`
      - `arguments`
      - `duration_ms` (execution time for the tool)
      - `success` (`"true"` or `"false"`)
      - `output`
    
    ### Choosing an exporter
    
    Set `otel.exporter` to control where events go:
    
    - `none` – leaves instrumentation active but skips exporting. This is
    the
      default.
    - `otlp-http` – posts OTLP log records to an OTLP/HTTP collector.
    Specify the
      endpoint, protocol, and headers your collector expects:
    
      ```toml
      [otel]
      exporter = { otlp-http = {
        endpoint = "https://otel.example.com/v1/logs",
        protocol = "binary",
        headers = { "x-otlp-api-key" = "${OTLP_TOKEN}" }
      }}
      ```
    
    - `otlp-grpc` – streams OTLP log records over gRPC. Provide the endpoint
    and any
      metadata headers:
    
      ```toml
      [otel]
      exporter = { otlp-grpc = {
        endpoint = "https://otel.example.com:4317",
        headers = { "x-otlp-meta" = "abc123" }
      }}
      ```
    
    If the exporter is `none` nothing is written anywhere; otherwise you
    must run or point to your
    own collector. All exporters run on a background batch worker that is
    flushed on
    shutdown.
    
    If you build Codex from source the OTEL crate is still behind an `otel`
    feature
    flag; the official prebuilt binaries ship with the feature enabled. When
    the
    feature is disabled the telemetry hooks become no-ops so the CLI
    continues to
    function without the extra dependencies.
    
    ---------
    
    Co-authored-by: Anton Panasenko <apanasenko@openai.com>
  • ref: state - 2 (#4229)
    Extracting tasks in a module and start abstraction behind a Trait (more
    to come on this but each task will be tackled in a dedicated PR)
    The goal was to drop the ActiveTask and to have a (potentially) set of
    tasks during each turn
  • ref: full state refactor (#4174)
    ## Current State Observations
    - `Session` currently holds many unrelated responsibilities (history,
    approval queues, task handles, rollout recorder, shell discovery, token
    tracking, etc.), making it hard to reason about ownership and lifetimes.
    - The anonymous `State` struct inside `codex.rs` mixes session-long data
    with turn-scoped queues and approval bookkeeping.
    - Turn execution (`run_task`) relies on ad-hoc local variables that
    should conceptually belong to a per-turn state object.
    - External modules (`codex::compact`, tests) frequently poke the raw
    `Session.state` mutex, which couples them to implementation details.
    - Interrupts, approvals, and rollout persistence all have bespoke
    cleanup paths, contributing to subtle bugs when a turn is aborted
    mid-flight.
    
    ## Desired End State
    - Keep a slim `Session` object that acts as the orchestrator and façade.
    It should expose a focused API (submit, approvals, interrupts, event
    emission) without storing unrelated fields directly.
    - Introduce a `state` module that encapsulates all mutable data
    structures:
    - `SessionState`: session-persistent data (history, approved commands,
    token/rate-limit info, maybe user preferences).
    - `ActiveTurn`: metadata for the currently running turn (sub-id, task
    kind, abort handle) and an `Arc<TurnState>`.
    - `TurnState`: all turn-scoped pieces (pending inputs, approval waiters,
    diff tracker, review history, auto-compact flags, last agent message,
    outstanding tool call bookkeeping).
    - Group long-lived helpers/managers into a dedicated `SessionServices`
    struct so `Session` does not accumulate "random" fields.
    - Provide clear, lock-safe APIs so other modules never touch raw
    mutexes.
    - Ensure every turn creates/drops a `TurnState` and that
    interrupts/finishes delegate cleanup to it.
  • adds a windows-specific method to check if a command is safe (#4119)
    refactors command_safety files into its own package, so we can add
    platform-specific ones
    Also creates a windows-specific of `is_known_safe_command` that just
    returns false always, since that is what happens today.
  • Simplify tool implemetations (#4160)
    Use Result<String, FunctionCallError> for all tool handling code and
    rely on error propagation instead of creating failed items everywhere.
  • Add dev message upon review out (#3758)
    Proposal: We want to record a dev message like so:
    
    ```
    {
          "type": "message",
          "role": "user",
          "content": [
            {
              "type": "input_text",
              "text": "<user_action>
      <context>User initiated a review task. Here's the full review output from reviewer model. User may select one or more comments to resolve.</context>
      <action>review</action>
      <results>
      {findings_str}
      </results>
    </user_action>"
            }
          ]
        },
    ```
    
    Without showing in the chat transcript.
    
    Rough idea, but it fixes issue where the user finishes a review thread,
    and asks the parent "fix the rest of the review issues" thinking that
    the parent knows about it.
    
    ### Question: Why not a tool call?
    
    Because the agent didn't make the call, it was a human. + we haven't
    implemented sub-agents yet, and we'll need to think about the way we
    represent these human-led tool calls for the agent.
  • Review mode core updates (#3701)
    1. Adds the environment prompt (including cwd) to review thread
    2. Prepends the review prompt as a user message (temporary fix so the
    instructions are not replaced on backend)
    3. Sets reasoning to low
    4. Sets default review model to `gpt-5-codex`
  • enable-resume (#3537)
    Adding the ability to resume conversations.
    we have one verb `resume`. 
    
    Behavior:
    
    `tui`:
    `codex resume`: opens session picker
    `codex resume --last`: continue last message
    `codex resume <session id>`: continue conversation with `session id`
    
    `exec`:
    `codex resume --last`: continue last conversation
    `codex resume <session id>`: continue conversation with `session id`
    
    Implementation:
    - I added a function to find the path in `~/.codex/sessions/` with a
    `UUID`. This is helpful in resuming with session id.
    - Added the above mentioned flags
    - Added lots of testing
  • feat: TUI onboarding (#3398)
    Example of how onboarding could look like
  • Unified execution (#3288)
    ## Unified PTY-Based Exec Tool
    
    Note: this requires to have this flag in the config:
    `use_experimental_unified_exec_tool=true`
    
    - Adds a PTY-backed interactive exec feature (“unified_exec”) with
    session reuse via
      session_id, bounded output (128 KiB), and timeout clamping (≤ 60 s).
    - Protocol: introduces ResponseItem::UnifiedExec { session_id,
    arguments, timeout_ms }.
    - Tools: exposes unified_exec as a function tool (Responses API);
    excluded from Chat
      Completions payload while still supported in tool lists.
    - Path handling: resolves commands via PATH (or explicit paths), with
    UTF‑8/newline‑aware
      truncation (truncate_middle).
    - Tests: cover command parsing, path resolution, session
    persistence/cleanup, multi‑session
      isolation, timeouts, and truncation behavior.
  • Persist model & reasoning changes (#2799)
    Persists `/model` changes across both general and profile-specific
    sessions.
  • Move initial history to protocol (#3422)
    To fix an edge case of forking then resuming
    
    #3419
  • feat(core): re-export InitialHistory from conversation_manager (#3270)
    This commit adds a re-export for InitialHistory from the internal
    conversation_manager module in codex-core's lib.rs.
    
    The `RolloutRecorder::get_rollout_history` method (exposed via `pub use
    rollout::RolloutRecorder;`, already present in lib.rs) returns an
    `InitialHistory` type, which is defined in the private
    conversation_manager module. Without this re-export, consumers of the
    public RolloutRecorder API would not be able to directly use the return
    type, as they cannot access the private module. This would result in an
    inconvenient experience where the method's return value cannot be
    handled without additional, non-obvious imports.
    
    By adding `pub use conversation_manager::InitialHistory;`, we make
    InitialHistory available as `codex_core::InitialHistory`, improving API
    ergonomics for users of the rollout functionality while keeping the
    conversation_manager module internal.
    
    No functional changes are made; this is a pure re-export for better
    usability.
    
    Signed-off-by: M4n5ter <m4n5terrr@gmail.com>