llmx/codex-rs/core/src/config.rs

use crate::config_profile::ConfigProfile;
use crate::config_types::History;
use crate::config_types::McpServerConfig;
use crate::config_types::ReasoningEffort;
use crate::config_types::ReasoningSummary;
use crate::config_types::SandboxMode;
use crate::config_types::SandboxWorkspaceWrite;
use crate::config_types::ShellEnvironmentPolicy;
use crate::config_types::ShellEnvironmentPolicyToml;
use crate::config_types::Tui;
use crate::config_types::UriBasedFileOpener;
use crate::model_family::ModelFamily;
use crate::model_family::find_family_for_model;
use crate::model_provider_info::ModelProviderInfo;
use crate::model_provider_info::built_in_model_providers;
use crate::openai_model_info::get_model_info;
use crate::protocol::AskForApproval;
use crate::protocol::SandboxPolicy;
use dirs::home_dir;
use serde::Deserialize;
use std::collections::HashMap;
use std::path::Path;
use std::path::PathBuf;
use tempfile::NamedTempFile;
use toml::Value as TomlValue;
use toml_edit::DocumentMut;

const OPENAI_DEFAULT_MODEL: &str = "gpt-5";

/// Maximum number of bytes of the documentation that will be embedded. Larger
/// files are *silently truncated* to this size so we do not take up too much of
/// the context window.
pub(crate) const PROJECT_DOC_MAX_BYTES: usize = 32 * 1024; // 32 KiB

const CONFIG_TOML_FILE: &str = "config.toml";

/// Application configuration loaded from disk and merged with overrides.
#[derive(Debug, Clone, PartialEq)]
pub struct Config {
    /// Optional override of model selection.
    pub model: String,

    pub model_family: ModelFamily,

    /// Size of the context window for the model, in tokens.
    pub model_context_window: Option<u64>,

    /// Maximum number of output tokens.
    pub model_max_output_tokens: Option<u64>,

    /// Key into the model_providers map that specifies which provider to use.
    pub model_provider_id: String,

    /// Info needed to make an API request to the model.
    pub model_provider: ModelProviderInfo,

    /// Approval policy for executing commands.
    pub approval_policy: AskForApproval,

    pub sandbox_policy: SandboxPolicy,

    pub shell_environment_policy: ShellEnvironmentPolicy,

    /// When `true`, `AgentReasoning` events emitted by the backend will be
    /// suppressed from the frontend output. This can reduce visual noise when
    /// users are only interested in the final agent responses.
    pub hide_agent_reasoning: bool,

    /// When set to `true`, `AgentReasoningRawContentEvent` events will be shown in the UI/output.
    /// Defaults to `false`.
    pub show_raw_agent_reasoning: bool,

    /// Disable server-side response storage (sends the full conversation
    /// context with every request). Currently necessary for OpenAI customers
    /// who have opted into Zero Data Retention (ZDR).
    pub disable_response_storage: bool,

    /// User-provided instructions from AGENTS.md.
    pub user_instructions: Option<String>,

    /// Base instructions override.
    pub base_instructions: Option<String>,

    /// Optional external notifier command. When set, Codex will spawn this
    /// program after each completed *turn* (i.e. when the agent finishes
    /// processing a user submission). The value must be the full command
    /// broken into argv tokens **without** the trailing JSON argument - Codex
    /// appends one extra argument containing a JSON payload describing the
    /// event.
    ///
    /// Example `~/.codex/config.toml` snippet:
    ///
    /// ```toml
    /// notify = ["notify-send", "Codex"]
    /// ```
    ///
    /// which will be invoked as:
    ///
    /// ```shell
    /// notify-send Codex '{"type":"agent-turn-complete","turn-id":"12345"}'
    /// ```
    ///
    /// If unset the feature is disabled.
    pub notify: Option<Vec<String>>,

    /// The directory that should be treated as the current working directory
    /// for the session. All relative paths inside the business-logic layer are
    /// resolved against this path.
    pub cwd: PathBuf,

    /// Definition for MCP servers that Codex can reach out to for tool calls.
    pub mcp_servers: HashMap<String, McpServerConfig>,

    /// Combined provider map (defaults merged with user-defined overrides).
    pub model_providers: HashMap<String, ModelProviderInfo>,

    /// Maximum number of bytes to include from an AGENTS.md project doc file.
    pub project_doc_max_bytes: usize,

    /// Directory containing all Codex state (defaults to `~/.codex` but can be
    /// overridden by the `CODEX_HOME` environment variable).
    pub codex_home: PathBuf,

    /// Settings that govern if and what will be written to `~/.codex/history.jsonl`.
    pub history: History,

    /// Optional URI-based file opener. If set, citations to files in the model
    /// output will be hyperlinked using the specified URI scheme.
    pub file_opener: UriBasedFileOpener,

    /// Collection of settings that are specific to the TUI.
    pub tui: Tui,

    /// Path to the `codex-linux-sandbox` executable. This must be set if
    /// [`crate::exec::SandboxType::LinuxSeccomp`] is used. Note that this
    /// cannot be set in the config file: it must be set in code via
    /// [`ConfigOverrides`].
    ///
    /// When this program is invoked, arg0 will be set to `codex-linux-sandbox`.
    pub codex_linux_sandbox_exe: Option<PathBuf>,

    /// If not "none", the value to use for `reasoning.effort` when making a
    /// request using the Responses API.
    pub model_reasoning_effort: ReasoningEffort,

    /// If not "none", the value to use for `reasoning.summary` when making a
    /// request using the Responses API.
    pub model_reasoning_summary: ReasoningSummary,

    /// Base URL for requests to ChatGPT (as opposed to the OpenAI API).
    pub chatgpt_base_url: String,

    /// Experimental rollout resume path (absolute path to .jsonl; undocumented).
    pub experimental_resume: Option<PathBuf>,

    /// Include an experimental plan tool that the model can use to update its current plan and status of each step.
    pub include_plan_tool: bool,

    /// Include the `apply_patch` tool for models that benefit from invoking
    /// file edits as a structured tool call. When unset, this falls back to the
    /// model family's default preference.
    pub include_apply_patch_tool: bool,

    /// The value for the `originator` header included with Responses API requests.
    pub internal_originator: Option<String>,
}

impl Config {
    /// Load configuration with *generic* CLI overrides (`-c key=value`) applied
    /// **in between** the values parsed from `config.toml` and the
    /// strongly-typed overrides specified via [`ConfigOverrides`].
    ///
    /// The precedence order is therefore: `config.toml` < `-c` overrides <
    /// `ConfigOverrides`.
    pub fn load_with_cli_overrides(
        cli_overrides: Vec<(String, TomlValue)>,
        overrides: ConfigOverrides,
    ) -> std::io::Result<Self> {
        // Resolve the directory that stores Codex state (e.g. ~/.codex or the
        // value of $CODEX_HOME) so we can embed it into the resulting
        // `Config` instance.
        let codex_home = find_codex_home()?;

        // Step 1: parse `config.toml` into a generic JSON value.
        let mut root_value = load_config_as_toml(&codex_home)?;

        // Step 2: apply the `-c` overrides.
        for (path, value) in cli_overrides.into_iter() {
            apply_toml_override(&mut root_value, &path, value);
        }

        // Step 3: deserialize into `ConfigToml` so that Serde can enforce the
        // correct types.
        let cfg: ConfigToml = root_value.try_into().map_err(|e| {
            tracing::error!("Failed to deserialize overridden config: {e}");
            std::io::Error::new(std::io::ErrorKind::InvalidData, e)
        })?;

        // Step 4: merge with the strongly-typed overrides.
        Self::load_from_base_config_with_overrides(cfg, overrides, codex_home)
    }
}

pub fn load_config_as_toml_with_cli_overrides(
    codex_home: &Path,
    cli_overrides: Vec<(String, TomlValue)>,
) -> std::io::Result<ConfigToml> {
    let mut root_value = load_config_as_toml(codex_home)?;

    for (path, value) in cli_overrides.into_iter() {
        apply_toml_override(&mut root_value, &path, value);
    }

    let cfg: ConfigToml = root_value.try_into().map_err(|e| {
        tracing::error!("Failed to deserialize overridden config: {e}");
        std::io::Error::new(std::io::ErrorKind::InvalidData, e)
    })?;

    Ok(cfg)
}

/// Read `CODEX_HOME/config.toml` and return it as a generic TOML value. Returns
/// an empty TOML table when the file does not exist.
pub fn load_config_as_toml(codex_home: &Path) -> std::io::Result<TomlValue> {
    let config_path = codex_home.join(CONFIG_TOML_FILE);
    match std::fs::read_to_string(&config_path) {
        Ok(contents) => match toml::from_str::<TomlValue>(&contents) {
            Ok(val) => Ok(val),
            Err(e) => {
                tracing::error!("Failed to parse config.toml: {e}");
                Err(std::io::Error::new(std::io::ErrorKind::InvalidData, e))
            }
        },
        Err(e) if e.kind() == std::io::ErrorKind::NotFound => {
            tracing::info!("config.toml not found, using defaults");
            Ok(TomlValue::Table(Default::default()))
        }
        Err(e) => {
            tracing::error!("Failed to read config.toml: {e}");
            Err(e)
        }
    }
}

/// Patch `CODEX_HOME/config.toml` project state.
/// Use with caution.
pub fn set_project_trusted(codex_home: &Path, project_path: &Path) -> anyhow::Result<()> {
    let config_path = codex_home.join(CONFIG_TOML_FILE);
    // Parse existing config if present; otherwise start a new document.
    let mut doc = match std::fs::read_to_string(config_path.clone()) {
        Ok(s) => s.parse::<DocumentMut>()?,
        Err(e) if e.kind() == std::io::ErrorKind::NotFound => DocumentMut::new(),
        Err(e) => return Err(e.into()),
    };

    // Mark the project as trusted. toml_edit is very good at handling
    // missing properties
    let project_key = project_path.to_string_lossy().to_string();
    doc["projects"][project_key.as_str()]["trust_level"] = toml_edit::value("trusted");

    // ensure codex_home exists
    std::fs::create_dir_all(codex_home)?;

    // create a tmp_file
    let tmp_file = NamedTempFile::new_in(codex_home)?;
    std::fs::write(tmp_file.path(), doc.to_string())?;

    // atomically move the tmp file into config.toml
    tmp_file.persist(config_path)?;

    Ok(())
}

/// Apply a single dotted-path override onto a TOML value.
fn apply_toml_override(root: &mut TomlValue, path: &str, value: TomlValue) {
    use toml::value::Table;

    let segments: Vec<&str> = path.split('.').collect();
    let mut current = root;

    for (idx, segment) in segments.iter().enumerate() {
        let is_last = idx == segments.len() - 1;

        if is_last {
            match current {
                TomlValue::Table(table) => {
                    table.insert(segment.to_string(), value);
                }
                _ => {
                    let mut table = Table::new();
                    table.insert(segment.to_string(), value);
                    *current = TomlValue::Table(table);
                }
            }
            return;
        }

        // Traverse or create intermediate object.
        match current {
            TomlValue::Table(table) => {
                current = table
                    .entry(segment.to_string())
                    .or_insert_with(|| TomlValue::Table(Table::new()));
            }
            _ => {
                *current = TomlValue::Table(Table::new());
                if let TomlValue::Table(tbl) = current {
                    current = tbl
                        .entry(segment.to_string())
                        .or_insert_with(|| TomlValue::Table(Table::new()));
                }
            }
        }
    }
}

/// Base config deserialized from ~/.codex/config.toml.
#[derive(Deserialize, Debug, Clone, Default)]
pub struct ConfigToml {
    /// Optional override of model selection.
    pub model: Option<String>,

    /// Provider to use from the model_providers map.
    pub model_provider: Option<String>,

    /// Size of the context window for the model, in tokens.
    pub model_context_window: Option<u64>,

    /// Maximum number of output tokens.
    pub model_max_output_tokens: Option<u64>,

    /// Default approval policy for executing commands.
    pub approval_policy: Option<AskForApproval>,

    #[serde(default)]
    pub shell_environment_policy: ShellEnvironmentPolicyToml,

    /// Sandbox mode to use.
    pub sandbox_mode: Option<SandboxMode>,

    /// Sandbox configuration to apply if `sandbox` is `WorkspaceWrite`.
    pub sandbox_workspace_write: Option<SandboxWorkspaceWrite>,

    /// Disable server-side response storage (sends the full conversation
    /// context with every request). Currently necessary for OpenAI customers
    /// who have opted into Zero Data Retention (ZDR).
    pub disable_response_storage: Option<bool>,

    /// Optional external command to spawn for end-user notifications.
    #[serde(default)]
    pub notify: Option<Vec<String>>,

    /// System instructions.
    pub instructions: Option<String>,

    /// Definition for MCP servers that Codex can reach out to for tool calls.
    #[serde(default)]
    pub mcp_servers: HashMap<String, McpServerConfig>,

    /// User-defined provider entries that extend/override the built-in list.
    #[serde(default)]
    pub model_providers: HashMap<String, ModelProviderInfo>,

    /// Maximum number of bytes to include from an AGENTS.md project doc file.
    pub project_doc_max_bytes: Option<usize>,

    /// Profile to use from the `profiles` map.
    pub profile: Option<String>,

    /// Named profiles to facilitate switching between different configurations.
    #[serde(default)]
    pub profiles: HashMap<String, ConfigProfile>,

    /// Settings that govern if and what will be written to `~/.codex/history.jsonl`.
    #[serde(default)]
    pub history: Option<History>,

    /// Optional URI-based file opener. If set, citations to files in the model
    /// output will be hyperlinked using the specified URI scheme.
    pub file_opener: Option<UriBasedFileOpener>,

    /// Collection of settings that are specific to the TUI.
    pub tui: Option<Tui>,

    /// When set to `true`, `AgentReasoning` events will be hidden from the
    /// UI/output. Defaults to `false`.
    pub hide_agent_reasoning: Option<bool>,

    /// When set to `true`, `AgentReasoningRawContentEvent` events will be shown in the UI/output.
    /// Defaults to `false`.
    pub show_raw_agent_reasoning: Option<bool>,

    pub model_reasoning_effort: Option<ReasoningEffort>,
    pub model_reasoning_summary: Option<ReasoningSummary>,

    /// Override to force-enable reasoning summaries for the configured model.
    pub model_supports_reasoning_summaries: Option<bool>,

    /// Base URL for requests to ChatGPT (as opposed to the OpenAI API).
    pub chatgpt_base_url: Option<String>,

    /// Experimental rollout resume path (absolute path to .jsonl; undocumented).
    pub experimental_resume: Option<PathBuf>,

    /// Experimental path to a file whose contents replace the built-in BASE_INSTRUCTIONS.
    pub experimental_instructions_file: Option<PathBuf>,

    /// The value for the `originator` header included with Responses API requests.
    pub internal_originator: Option<String>,

    pub projects: Option<HashMap<String, ProjectConfig>>,
}

#[derive(Deserialize, Debug, Clone, PartialEq, Eq)]
pub struct ProjectConfig {
    pub trust_level: Option<String>,
}

impl ConfigToml {
    /// Derive the effective sandbox policy from the configuration.
    fn derive_sandbox_policy(&self, sandbox_mode_override: Option<SandboxMode>) -> SandboxPolicy {
        let resolved_sandbox_mode = sandbox_mode_override
            .or(self.sandbox_mode)
            .unwrap_or_default();
        match resolved_sandbox_mode {
            SandboxMode::ReadOnly => SandboxPolicy::new_read_only_policy(),
            SandboxMode::WorkspaceWrite => match self.sandbox_workspace_write.as_ref() {
                Some(SandboxWorkspaceWrite {
                    writable_roots,
                    network_access,
                    exclude_tmpdir_env_var,
                    exclude_slash_tmp,
                }) => SandboxPolicy::WorkspaceWrite {
                    writable_roots: writable_roots.clone(),
                    network_access: *network_access,
                    exclude_tmpdir_env_var: *exclude_tmpdir_env_var,
                    exclude_slash_tmp: *exclude_slash_tmp,
                },
                None => SandboxPolicy::new_workspace_write_policy(),
            },
            SandboxMode::DangerFullAccess => SandboxPolicy::DangerFullAccess,
        }
    }

    pub fn is_cwd_trusted(&self, resolved_cwd: &Path) -> bool {
        let projects = self.projects.clone().unwrap_or_default();

        projects
            .get(&resolved_cwd.to_string_lossy().to_string())
            .map(|p| p.trust_level.clone().unwrap_or("".to_string()) == "trusted")
            .unwrap_or(false)
    }

    pub fn get_config_profile(
        &self,
        override_profile: Option<String>,
    ) -> Result<ConfigProfile, std::io::Error> {
        let profile = override_profile.or_else(|| self.profile.clone());

        match profile {
            Some(key) => {
                if let Some(profile) = self.profiles.get(key.as_str()) {
                    return Ok(profile.clone());
                }

                Err(std::io::Error::new(
                    std::io::ErrorKind::NotFound,
                    format!("config profile `{key}` not found"),
                ))
            }
            None => Ok(ConfigProfile::default()),
        }
    }
}

/// Optional overrides for user configuration (e.g., from CLI flags).
#[derive(Default, Debug, Clone)]
pub struct ConfigOverrides {
    pub model: Option<String>,
    pub cwd: Option<PathBuf>,
    pub approval_policy: Option<AskForApproval>,
    pub sandbox_mode: Option<SandboxMode>,
    pub model_provider: Option<String>,
    pub config_profile: Option<String>,
    pub codex_linux_sandbox_exe: Option<PathBuf>,
    pub base_instructions: Option<String>,
    pub include_plan_tool: Option<bool>,
    pub include_apply_patch_tool: Option<bool>,
    pub disable_response_storage: Option<bool>,
    pub show_raw_agent_reasoning: Option<bool>,
}

impl Config {
    /// Meant to be used exclusively for tests: `load_with_overrides()` should
    /// be used in all other cases.
    pub fn load_from_base_config_with_overrides(
        cfg: ConfigToml,
        overrides: ConfigOverrides,
        codex_home: PathBuf,
    ) -> std::io::Result<Self> {
        let user_instructions = Self::load_instructions(Some(&codex_home));

        // Destructure ConfigOverrides fully to ensure all overrides are applied.
        let ConfigOverrides {
            model,
            cwd,
            approval_policy,
            sandbox_mode,
            model_provider,
            config_profile: config_profile_key,
            codex_linux_sandbox_exe,
            base_instructions,
            include_plan_tool,
            include_apply_patch_tool,
            disable_response_storage,
            show_raw_agent_reasoning,
        } = overrides;

        let config_profile = match config_profile_key.as_ref().or(cfg.profile.as_ref()) {
            Some(key) => cfg
                .profiles
                .get(key)
                .ok_or_else(|| {
                    std::io::Error::new(
                        std::io::ErrorKind::NotFound,
                        format!("config profile `{key}` not found"),
                    )
                })?
                .clone(),
            None => ConfigProfile::default(),
        };

        let sandbox_policy = cfg.derive_sandbox_policy(sandbox_mode);

        let mut model_providers = built_in_model_providers();
        // Merge user-defined providers into the built-in list.
        for (key, provider) in cfg.model_providers.into_iter() {
            model_providers.entry(key).or_insert(provider);
        }

        let model_provider_id = model_provider
            .or(config_profile.model_provider)
            .or(cfg.model_provider)
            .unwrap_or_else(|| "openai".to_string());
        let model_provider = model_providers
            .get(&model_provider_id)
            .ok_or_else(|| {
                std::io::Error::new(
                    std::io::ErrorKind::NotFound,
                    format!("Model provider `{model_provider_id}` not found"),
                )
            })?
            .clone();

        let shell_environment_policy = cfg.shell_environment_policy.into();

        let resolved_cwd = {
            use std::env;

            match cwd {
                None => {
                    tracing::info!("cwd not set, using current dir");
                    env::current_dir()?
                }
                Some(p) if p.is_absolute() => p,
                Some(p) => {
                    // Resolve relative path against the current working directory.
                    tracing::info!("cwd is relative, resolving against current dir");
                    let mut current = env::current_dir()?;
                    current.push(p);
                    current
                }
            }
        };

        let history = cfg.history.unwrap_or_default();

        let model = model
            .or(config_profile.model)
            .or(cfg.model)
            .unwrap_or_else(default_model);
        let model_family = find_family_for_model(&model).unwrap_or_else(|| {
            let supports_reasoning_summaries =
                cfg.model_supports_reasoning_summaries.unwrap_or(false);
            ModelFamily {
                slug: model.clone(),
                family: model.clone(),
                needs_special_apply_patch_instructions: false,
                supports_reasoning_summaries,
                uses_local_shell_tool: false,
                uses_apply_patch_tool: false,
            }
        });

        let openai_model_info = get_model_info(&model_family);
        let model_context_window = cfg
            .model_context_window
            .or_else(|| openai_model_info.as_ref().map(|info| info.context_window));
        let model_max_output_tokens = cfg.model_max_output_tokens.or_else(|| {
            openai_model_info
                .as_ref()
                .map(|info| info.max_output_tokens)
        });

        let experimental_resume = cfg.experimental_resume;

        // Load base instructions override from a file if specified. If the
        // path is relative, resolve it against the effective cwd so the
        // behaviour matches other path-like config values.
        let experimental_instructions_path = config_profile
            .experimental_instructions_file
            .as_ref()
            .or(cfg.experimental_instructions_file.as_ref());
        let file_base_instructions =
            Self::get_base_instructions(experimental_instructions_path, &resolved_cwd)?;
        let base_instructions = base_instructions.or(file_base_instructions);

        let include_apply_patch_tool_val =
            include_apply_patch_tool.unwrap_or(model_family.uses_apply_patch_tool);

        let config = Self {
            model,
            model_family,
            model_context_window,
            model_max_output_tokens,
            model_provider_id,
            model_provider,
            cwd: resolved_cwd,
            approval_policy: approval_policy
                .or(config_profile.approval_policy)
                .or(cfg.approval_policy)
                .unwrap_or_else(AskForApproval::default),
            sandbox_policy,
            shell_environment_policy,
            disable_response_storage: config_profile
                .disable_response_storage
                .or(cfg.disable_response_storage)
                .or(disable_response_storage)
                .unwrap_or(false),
            notify: cfg.notify,
            user_instructions,
            base_instructions,
            mcp_servers: cfg.mcp_servers,
            model_providers,
            project_doc_max_bytes: cfg.project_doc_max_bytes.unwrap_or(PROJECT_DOC_MAX_BYTES),
            codex_home,
            history,
            file_opener: cfg.file_opener.unwrap_or(UriBasedFileOpener::VsCode),
            tui: cfg.tui.unwrap_or_default(),
            codex_linux_sandbox_exe,

            hide_agent_reasoning: cfg.hide_agent_reasoning.unwrap_or(false),
            show_raw_agent_reasoning: cfg
                .show_raw_agent_reasoning
                .or(show_raw_agent_reasoning)
                .unwrap_or(false),
            model_reasoning_effort: config_profile
                .model_reasoning_effort
                .or(cfg.model_reasoning_effort)
                .unwrap_or_default(),
            model_reasoning_summary: config_profile
                .model_reasoning_summary
                .or(cfg.model_reasoning_summary)
                .unwrap_or_default(),

            chatgpt_base_url: config_profile
                .chatgpt_base_url
                .or(cfg.chatgpt_base_url)
                .unwrap_or("https://chatgpt.com/backend-api/".to_string()),

            experimental_resume,
            include_plan_tool: include_plan_tool.unwrap_or(false),
            include_apply_patch_tool: include_apply_patch_tool_val,
            internal_originator: cfg.internal_originator,
        };
        Ok(config)
    }

    fn load_instructions(codex_dir: Option<&Path>) -> Option<String> {
        let mut p = match codex_dir {
            Some(p) => p.to_path_buf(),
            None => return None,
        };

        p.push("AGENTS.md");
        std::fs::read_to_string(&p).ok().and_then(|s| {
            let s = s.trim();
            if s.is_empty() {
                None
            } else {
                Some(s.to_string())
            }
        })
    }

    fn get_base_instructions(
        path: Option<&PathBuf>,
        cwd: &Path,
    ) -> std::io::Result<Option<String>> {
        let p = match path.as_ref() {
            None => return Ok(None),
            Some(p) => p,
        };

        // Resolve relative paths against the provided cwd to make CLI
        // overrides consistent regardless of where the process was launched
        // from.
        let full_path = if p.is_relative() {
            cwd.join(p)
        } else {
            p.to_path_buf()
        };

        let contents = std::fs::read_to_string(&full_path).map_err(|e| {
            std::io::Error::new(
                e.kind(),
                format!(
                    "failed to read experimental instructions file {}: {e}",
                    full_path.display()
                ),
            )
        })?;

        let s = contents.trim().to_string();
        if s.is_empty() {
            Err(std::io::Error::new(
                std::io::ErrorKind::InvalidData,
                format!(
                    "experimental instructions file is empty: {}",
                    full_path.display()
                ),
            ))
        } else {
            Ok(Some(s))
        }
    }
}

fn default_model() -> String {
    OPENAI_DEFAULT_MODEL.to_string()
}

/// Returns the path to the Codex configuration directory, which can be
/// specified by the `CODEX_HOME` environment variable. If not set, defaults to
/// `~/.codex`.
///
/// - If `CODEX_HOME` is set, the value will be canonicalized and this
///   function will Err if the path does not exist.
/// - If `CODEX_HOME` is not set, this function does not verify that the
///   directory exists.
pub fn find_codex_home() -> std::io::Result<PathBuf> {
    // Honor the `CODEX_HOME` environment variable when it is set to allow users
    // (and tests) to override the default location.
    if let Ok(val) = std::env::var("CODEX_HOME") {
        if !val.is_empty() {
            return PathBuf::from(val).canonicalize();
        }
    }

    let mut p = home_dir().ok_or_else(|| {
        std::io::Error::new(
            std::io::ErrorKind::NotFound,
            "Could not find home directory",
        )
    })?;
    p.push(".codex");
    Ok(p)
}

/// Returns the path to the folder where Codex logs are stored. Does not verify
/// that the directory exists.
pub fn log_dir(cfg: &Config) -> std::io::Result<PathBuf> {
    let mut p = cfg.codex_home.clone();
    p.push("log");
    Ok(p)
}

#[cfg(test)]
mod tests {
    use crate::config_types::HistoryPersistence;

    use super::*;
    use pretty_assertions::assert_eq;
    use tempfile::TempDir;

    #[test]
    fn test_toml_parsing() {
        let history_with_persistence = r#"
[history]
persistence = "save-all"
"#;
        let history_with_persistence_cfg = toml::from_str::<ConfigToml>(history_with_persistence)
            .expect("TOML deserialization should succeed");
        assert_eq!(
            Some(History {
                persistence: HistoryPersistence::SaveAll,
                max_bytes: None,
            }),
            history_with_persistence_cfg.history
        );

        let history_no_persistence = r#"
[history]
persistence = "none"
"#;

        let history_no_persistence_cfg = toml::from_str::<ConfigToml>(history_no_persistence)
            .expect("TOML deserialization should succeed");
        assert_eq!(
            Some(History {
                persistence: HistoryPersistence::None,
                max_bytes: None,
            }),
            history_no_persistence_cfg.history
        );
    }

    #[test]
    fn test_sandbox_config_parsing() {
        let sandbox_full_access = r#"
sandbox_mode = "danger-full-access"

[sandbox_workspace_write]
network_access = false  # This should be ignored.
"#;
        let sandbox_full_access_cfg = toml::from_str::<ConfigToml>(sandbox_full_access)
            .expect("TOML deserialization should succeed");
        let sandbox_mode_override = None;
        assert_eq!(
            SandboxPolicy::DangerFullAccess,
            sandbox_full_access_cfg.derive_sandbox_policy(sandbox_mode_override)
        );

        let sandbox_read_only = r#"
sandbox_mode = "read-only"

[sandbox_workspace_write]
network_access = true  # This should be ignored.
"#;

        let sandbox_read_only_cfg = toml::from_str::<ConfigToml>(sandbox_read_only)
            .expect("TOML deserialization should succeed");
        let sandbox_mode_override = None;
        assert_eq!(
            SandboxPolicy::ReadOnly,
            sandbox_read_only_cfg.derive_sandbox_policy(sandbox_mode_override)
        );

        let sandbox_workspace_write = r#"
sandbox_mode = "workspace-write"

[sandbox_workspace_write]
writable_roots = [
    "/my/workspace",
]
exclude_tmpdir_env_var = true
exclude_slash_tmp = true
"#;

        let sandbox_workspace_write_cfg = toml::from_str::<ConfigToml>(sandbox_workspace_write)
            .expect("TOML deserialization should succeed");
        let sandbox_mode_override = None;
        assert_eq!(
            SandboxPolicy::WorkspaceWrite {
                writable_roots: vec![PathBuf::from("/my/workspace")],
                network_access: false,
                exclude_tmpdir_env_var: true,
                exclude_slash_tmp: true,
            },
            sandbox_workspace_write_cfg.derive_sandbox_policy(sandbox_mode_override)
        );
    }

    struct PrecedenceTestFixture {
        cwd: TempDir,
        codex_home: TempDir,
        cfg: ConfigToml,
        model_provider_map: HashMap<String, ModelProviderInfo>,
        openai_provider: ModelProviderInfo,
        openai_chat_completions_provider: ModelProviderInfo,
    }

    impl PrecedenceTestFixture {
        fn cwd(&self) -> PathBuf {
            self.cwd.path().to_path_buf()
        }

        fn codex_home(&self) -> PathBuf {
            self.codex_home.path().to_path_buf()
        }
    }

    fn create_test_fixture() -> std::io::Result<PrecedenceTestFixture> {
        let toml = r#"
model = "o3"
approval_policy = "untrusted"
disable_response_storage = false

# Can be used to determine which profile to use if not specified by
# `ConfigOverrides`.
profile = "gpt3"

[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"
request_max_retries = 4            # retry failed HTTP requests
stream_max_retries = 10            # retry dropped SSE streams
stream_idle_timeout_ms = 300000    # 5m idle timeout

[profiles.o3]
model = "o3"
model_provider = "openai"
approval_policy = "never"
model_reasoning_effort = "high"
model_reasoning_summary = "detailed"

[profiles.gpt3]
model = "gpt-3.5-turbo"
model_provider = "openai-chat-completions"

[profiles.zdr]
model = "o3"
model_provider = "openai"
approval_policy = "on-failure"
disable_response_storage = true
"#;

        let cfg: ConfigToml = toml::from_str(toml).expect("TOML deserialization should succeed");

        // Use a temporary directory for the cwd so it does not contain an
        // AGENTS.md file.
        let cwd_temp_dir = TempDir::new().unwrap();
        let cwd = cwd_temp_dir.path().to_path_buf();
        // Make it look like a Git repo so it does not search for AGENTS.md in
        // a parent folder, either.
        std::fs::write(cwd.join(".git"), "gitdir: nowhere")?;

        let codex_home_temp_dir = TempDir::new().unwrap();

        let openai_chat_completions_provider = ModelProviderInfo {
            name: "OpenAI using Chat Completions".to_string(),
            base_url: Some("https://api.openai.com/v1".to_string()),
            env_key: Some("OPENAI_API_KEY".to_string()),
            wire_api: crate::WireApi::Chat,
            env_key_instructions: None,
            query_params: None,
            http_headers: None,
            env_http_headers: None,
            request_max_retries: Some(4),
            stream_max_retries: Some(10),
            stream_idle_timeout_ms: Some(300_000),
            requires_openai_auth: false,
        };
        let model_provider_map = {
            let mut model_provider_map = built_in_model_providers();
            model_provider_map.insert(
                "openai-chat-completions".to_string(),
                openai_chat_completions_provider.clone(),
            );
            model_provider_map
        };

        let openai_provider = model_provider_map
            .get("openai")
            .expect("openai provider should exist")
            .clone();

        Ok(PrecedenceTestFixture {
            cwd: cwd_temp_dir,
            codex_home: codex_home_temp_dir,
            cfg,
            model_provider_map,
            openai_provider,
            openai_chat_completions_provider,
        })
    }

    /// Users can specify config values at multiple levels that have the
    /// following precedence:
    ///
    /// 1. custom command-line argument, e.g. `--model o3`
    /// 2. as part of a profile, where the `--profile` is specified via a CLI
    ///    (or in the config file itself)
    /// 3. as an entry in `config.toml`, e.g. `model = "o3"`
    /// 4. the default value for a required field defined in code, e.g.,
    ///    `crate::flags::OPENAI_DEFAULT_MODEL`
    ///
    /// Note that profiles are the recommended way to specify a group of
    /// configuration options together.
    #[test]
    fn test_precedence_fixture_with_o3_profile() -> std::io::Result<()> {
        let fixture = create_test_fixture()?;

        let o3_profile_overrides = ConfigOverrides {
            config_profile: Some("o3".to_string()),
            cwd: Some(fixture.cwd()),
            ..Default::default()
        };
        let o3_profile_config: Config = Config::load_from_base_config_with_overrides(
            fixture.cfg.clone(),
            o3_profile_overrides,
            fixture.codex_home(),
        )?;
        assert_eq!(
            Config {
                model: "o3".to_string(),
                model_family: find_family_for_model("o3").expect("known model slug"),
                model_context_window: Some(200_000),
                model_max_output_tokens: Some(100_000),
                model_provider_id: "openai".to_string(),
                model_provider: fixture.openai_provider.clone(),
                approval_policy: AskForApproval::Never,
                sandbox_policy: SandboxPolicy::new_read_only_policy(),
                shell_environment_policy: ShellEnvironmentPolicy::default(),
                disable_response_storage: false,
                user_instructions: None,
                notify: None,
                cwd: fixture.cwd(),
                mcp_servers: HashMap::new(),
                model_providers: fixture.model_provider_map.clone(),
                project_doc_max_bytes: PROJECT_DOC_MAX_BYTES,
                codex_home: fixture.codex_home(),
                history: History::default(),
                file_opener: UriBasedFileOpener::VsCode,
                tui: Tui::default(),
                codex_linux_sandbox_exe: None,
                hide_agent_reasoning: false,
                show_raw_agent_reasoning: false,
                model_reasoning_effort: ReasoningEffort::High,
                model_reasoning_summary: ReasoningSummary::Detailed,
                chatgpt_base_url: "https://chatgpt.com/backend-api/".to_string(),
                experimental_resume: None,
                base_instructions: None,
                include_plan_tool: false,
                include_apply_patch_tool: false,
                internal_originator: None,
            },
            o3_profile_config
        );
        Ok(())
    }

    #[test]
    fn test_precedence_fixture_with_gpt3_profile() -> std::io::Result<()> {
        let fixture = create_test_fixture()?;

        let gpt3_profile_overrides = ConfigOverrides {
            config_profile: Some("gpt3".to_string()),
            cwd: Some(fixture.cwd()),
            ..Default::default()
        };
        let gpt3_profile_config = Config::load_from_base_config_with_overrides(
            fixture.cfg.clone(),
            gpt3_profile_overrides,
            fixture.codex_home(),
        )?;
        let expected_gpt3_profile_config = Config {
            model: "gpt-3.5-turbo".to_string(),
            model_family: find_family_for_model("gpt-3.5-turbo").expect("known model slug"),
            model_context_window: Some(16_385),
            model_max_output_tokens: Some(4_096),
            model_provider_id: "openai-chat-completions".to_string(),
            model_provider: fixture.openai_chat_completions_provider.clone(),
            approval_policy: AskForApproval::UnlessTrusted,
            sandbox_policy: SandboxPolicy::new_read_only_policy(),
            shell_environment_policy: ShellEnvironmentPolicy::default(),
            disable_response_storage: false,
            user_instructions: None,
            notify: None,
            cwd: fixture.cwd(),
            mcp_servers: HashMap::new(),
            model_providers: fixture.model_provider_map.clone(),
            project_doc_max_bytes: PROJECT_DOC_MAX_BYTES,
            codex_home: fixture.codex_home(),
            history: History::default(),
            file_opener: UriBasedFileOpener::VsCode,
            tui: Tui::default(),
            codex_linux_sandbox_exe: None,
            hide_agent_reasoning: false,
            show_raw_agent_reasoning: false,
            model_reasoning_effort: ReasoningEffort::default(),
            model_reasoning_summary: ReasoningSummary::default(),
            chatgpt_base_url: "https://chatgpt.com/backend-api/".to_string(),
            experimental_resume: None,
            base_instructions: None,
            include_plan_tool: false,
            include_apply_patch_tool: false,
            internal_originator: None,
        };

        assert_eq!(expected_gpt3_profile_config, gpt3_profile_config);

        // Verify that loading without specifying a profile in ConfigOverrides
        // uses the default profile from the config file (which is "gpt3").
        let default_profile_overrides = ConfigOverrides {
            cwd: Some(fixture.cwd()),
            ..Default::default()
        };

        let default_profile_config = Config::load_from_base_config_with_overrides(
            fixture.cfg.clone(),
            default_profile_overrides,
            fixture.codex_home(),
        )?;

        assert_eq!(expected_gpt3_profile_config, default_profile_config);
        Ok(())
    }

    #[test]
    fn test_precedence_fixture_with_zdr_profile() -> std::io::Result<()> {
        let fixture = create_test_fixture()?;

        let zdr_profile_overrides = ConfigOverrides {
            config_profile: Some("zdr".to_string()),
            cwd: Some(fixture.cwd()),
            ..Default::default()
        };
        let zdr_profile_config = Config::load_from_base_config_with_overrides(
            fixture.cfg.clone(),
            zdr_profile_overrides,
            fixture.codex_home(),
        )?;
        let expected_zdr_profile_config = Config {
            model: "o3".to_string(),
            model_family: find_family_for_model("o3").expect("known model slug"),
            model_context_window: Some(200_000),
            model_max_output_tokens: Some(100_000),
            model_provider_id: "openai".to_string(),
            model_provider: fixture.openai_provider.clone(),
            approval_policy: AskForApproval::OnFailure,
            sandbox_policy: SandboxPolicy::new_read_only_policy(),
            shell_environment_policy: ShellEnvironmentPolicy::default(),
            disable_response_storage: true,
            user_instructions: None,
            notify: None,
            cwd: fixture.cwd(),
            mcp_servers: HashMap::new(),
            model_providers: fixture.model_provider_map.clone(),
            project_doc_max_bytes: PROJECT_DOC_MAX_BYTES,
            codex_home: fixture.codex_home(),
            history: History::default(),
            file_opener: UriBasedFileOpener::VsCode,
            tui: Tui::default(),
            codex_linux_sandbox_exe: None,
            hide_agent_reasoning: false,
            show_raw_agent_reasoning: false,
            model_reasoning_effort: ReasoningEffort::default(),
            model_reasoning_summary: ReasoningSummary::default(),
            chatgpt_base_url: "https://chatgpt.com/backend-api/".to_string(),
            experimental_resume: None,
            base_instructions: None,
            include_plan_tool: false,
            include_apply_patch_tool: false,
            internal_originator: None,
        };

        assert_eq!(expected_zdr_profile_config, zdr_profile_config);

        Ok(())
    }
}