feat: update default (#4076)
Changes: - Default model and docs now use gpt-5-codex. - Disables the GPT-5 Codex NUX by default. - Keeps presets available for API key users.
This commit is contained in:
Thibault Sottiaux
committed by
GitHub
GitHub
parent
c415827ac2
commit
c93e77b68b
@@ -1,4 +1,3 @@
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use codex_core::config::GPT_5_CODEX_MEDIUM_MODEL;
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use codex_core::protocol_config_types::ReasoningEffort;
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use codex_protocol::mcp_protocol::AuthMode;
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@@ -69,13 +68,6 @@ const PRESETS: &[ModelPreset] = &[
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},
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];
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pub fn builtin_model_presets(auth_mode: Option<AuthMode>) -> Vec<ModelPreset> {
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match auth_mode {
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Some(AuthMode::ApiKey) => PRESETS
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.iter()
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.copied()
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.filter(|p| p.model != GPT_5_CODEX_MEDIUM_MODEL)
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.collect(),
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_ => PRESETS.to_vec(),
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}
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pub fn builtin_model_presets(_auth_mode: Option<AuthMode>) -> Vec<ModelPreset> {
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PRESETS.to_vec()
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}
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@@ -37,7 +37,7 @@ use toml_edit::DocumentMut;
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use toml_edit::Item as TomlItem;
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use toml_edit::Table as TomlTable;
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const OPENAI_DEFAULT_MODEL: &str = "gpt-5";
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const OPENAI_DEFAULT_MODEL: &str = "gpt-5-codex";
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const OPENAI_DEFAULT_REVIEW_MODEL: &str = "gpt-5-codex";
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pub const GPT_5_CODEX_MEDIUM_MODEL: &str = "gpt-5-codex";
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@@ -54,7 +54,7 @@ pub struct Config {
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/// Optional override of model selection.
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pub model: String,
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/// Model used specifically for review sessions. Defaults to "gpt-5".
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/// Model used specifically for review sessions. Defaults to "gpt-5-codex".
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pub review_model: String,
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pub model_family: ModelFamily,
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@@ -1366,7 +1366,7 @@ startup_timeout_ms = 2500
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tokio::fs::write(
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&config_path,
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r#"
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model = "gpt-5"
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model = "gpt-5-codex"
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model_reasoning_effort = "medium"
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[profiles.dev]
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@@ -1441,7 +1441,7 @@ model = "gpt-4"
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model_reasoning_effort = "medium"
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[profiles.prod]
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model = "gpt-5"
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model = "gpt-5-codex"
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"#,
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)
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.await?;
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@@ -1472,7 +1472,7 @@ model = "gpt-5"
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.profiles
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.get("prod")
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.and_then(|profile| profile.model.as_deref()),
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Some("gpt-5"),
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Some("gpt-5-codex"),
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);
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Ok(())
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@@ -228,7 +228,7 @@ mod tests {
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codex_home,
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None,
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&[
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(&[CONFIG_KEY_MODEL], "gpt-5"),
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(&[CONFIG_KEY_MODEL], "gpt-5-codex"),
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(&[CONFIG_KEY_EFFORT], "high"),
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],
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)
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@@ -236,7 +236,7 @@ mod tests {
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.expect("persist");
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let contents = read_config(codex_home).await;
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let expected = r#"model = "gpt-5"
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let expected = r#"model = "gpt-5-codex"
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model_reasoning_effort = "high"
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"#;
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assert_eq!(contents, expected);
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@@ -348,7 +348,7 @@ model_reasoning_effort = "high"
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&[
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(&["a", "b", "c"], "v"),
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(&["x"], "y"),
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(&["profiles", "p1", CONFIG_KEY_MODEL], "gpt-5"),
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(&["profiles", "p1", CONFIG_KEY_MODEL], "gpt-5-codex"),
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],
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)
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.await
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@@ -361,7 +361,7 @@ model_reasoning_effort = "high"
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c = "v"
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[profiles.p1]
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model = "gpt-5"
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model = "gpt-5-codex"
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"#;
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assert_eq!(contents, expected);
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}
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@@ -454,7 +454,7 @@ existing = "keep"
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codex_home,
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None,
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&[
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(&[CONFIG_KEY_MODEL], "gpt-5"),
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(&[CONFIG_KEY_MODEL], "gpt-5-codex"),
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(&[CONFIG_KEY_EFFORT], "minimal"),
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],
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)
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@@ -466,7 +466,7 @@ existing = "keep"
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# should be preserved
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existing = "keep"
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model = "gpt-5"
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model = "gpt-5-codex"
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model_reasoning_effort = "minimal"
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"#;
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assert_eq!(contents, expected);
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@@ -524,7 +524,7 @@ model = "o3"
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let codex_home = tmpdir.path();
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// Seed with a model value only
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let seed = "model = \"gpt-5\"\n";
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let seed = "model = \"gpt-5-codex\"\n";
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tokio::fs::write(codex_home.join(CONFIG_TOML_FILE), seed)
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.await
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.expect("seed write");
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@@ -535,7 +535,7 @@ model = "o3"
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.expect("persist");
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let contents = read_config(codex_home).await;
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let expected = r#"model = "gpt-5"
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let expected = r#"model = "gpt-5-codex"
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model_reasoning_effort = "high"
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"#;
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assert_eq!(contents, expected);
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@@ -579,7 +579,7 @@ model = "o4-mini"
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// No active profile key; we'll target an explicit override
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let seed = r#"[profiles.team]
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model = "gpt-5"
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model = "gpt-5-codex"
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"#;
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tokio::fs::write(codex_home.join(CONFIG_TOML_FILE), seed)
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.await
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@@ -595,7 +595,7 @@ model = "gpt-5"
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let contents = read_config(codex_home).await;
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let expected = r#"[profiles.team]
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model = "gpt-5"
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model = "gpt-5-codex"
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model_reasoning_effort = "minimal"
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"#;
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assert_eq!(contents, expected);
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@@ -611,7 +611,7 @@ model_reasoning_effort = "minimal"
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codex_home,
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None,
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&[
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(&[CONFIG_KEY_MODEL], Some("gpt-5")),
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(&[CONFIG_KEY_MODEL], Some("gpt-5-codex")),
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(&[CONFIG_KEY_EFFORT], None),
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],
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)
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@@ -619,7 +619,7 @@ model_reasoning_effort = "minimal"
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.expect("persist");
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let contents = read_config(codex_home).await;
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let expected = "model = \"gpt-5\"\n";
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let expected = "model = \"gpt-5-codex\"\n";
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assert_eq!(contents, expected);
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}
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@@ -670,7 +670,7 @@ model = "o3"
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let tmpdir = tempdir().expect("tmp");
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let codex_home = tmpdir.path();
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let seed = r#"model = "gpt-5"
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let seed = r#"model = "gpt-5-codex"
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model_reasoning_effort = "medium"
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"#;
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tokio::fs::write(codex_home.join(CONFIG_TOML_FILE), seed)
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@@ -7,14 +7,27 @@ use std::path::PathBuf;
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pub(crate) const INTERNAL_STORAGE_FILE: &str = "internal_storage.json";
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#[derive(Debug, Default, Clone, Serialize, Deserialize)]
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct InternalStorage {
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#[serde(skip)]
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storage_path: PathBuf,
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#[serde(default)]
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#[serde(default = "default_gpt_5_codex_model_prompt_seen")]
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pub gpt_5_codex_model_prompt_seen: bool,
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}
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const fn default_gpt_5_codex_model_prompt_seen() -> bool {
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true
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}
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impl Default for InternalStorage {
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fn default() -> Self {
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Self {
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storage_path: PathBuf::new(),
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gpt_5_codex_model_prompt_seen: default_gpt_5_codex_model_prompt_seen(),
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}
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}
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}
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// TODO(jif) generalise all the file writers and build proper async channel inserters.
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impl InternalStorage {
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pub fn load(codex_home: &Path) -> Self {
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@@ -822,7 +822,7 @@ async fn token_count_includes_rate_limits_snapshot() {
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"reasoning_output_tokens": 0,
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"total_tokens": 123
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},
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// Default model is gpt-5 in tests → 272000 context window
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// Default model is gpt-5-codex in tests → 272000 context window
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"model_context_window": 272000
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},
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"rate_limits": {
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@@ -133,7 +133,7 @@ async fn compact_resume_and_fork_preserve_model_history_view() {
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.to_string();
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let user_turn_1 = json!(
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{
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"model": "gpt-5",
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"model": "gpt-5-codex",
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"instructions": prompt,
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"input": [
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{
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@@ -182,7 +182,7 @@ async fn compact_resume_and_fork_preserve_model_history_view() {
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});
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let compact_1 = json!(
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{
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"model": "gpt-5",
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"model": "gpt-5-codex",
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"instructions": "You have exceeded the maximum number of tokens, please stop coding and instead write a short memento message for the next agent. Your note should:
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- Summarize what you finished and what still needs work. If there was a recent update_plan call, repeat its steps verbatim.
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- List outstanding TODOs with file paths / line numbers so they're easy to find.
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@@ -255,7 +255,7 @@ async fn compact_resume_and_fork_preserve_model_history_view() {
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});
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let user_turn_2_after_compact = json!(
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{
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"model": "gpt-5",
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"model": "gpt-5-codex",
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"instructions": prompt,
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"input": [
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{
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@@ -320,7 +320,7 @@ SUMMARY_ONLY_CONTEXT"
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});
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let usert_turn_3_after_resume = json!(
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{
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"model": "gpt-5",
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"model": "gpt-5-codex",
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"instructions": prompt,
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"input": [
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{
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@@ -405,7 +405,7 @@ SUMMARY_ONLY_CONTEXT"
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});
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let user_turn_3_after_fork = json!(
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{
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"model": "gpt-5",
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"model": "gpt-5-codex",
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"instructions": prompt,
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"input": [
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{
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@@ -184,6 +184,7 @@ async fn prompt_tools_are_consistent_across_requests() {
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let conversation_manager =
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ConversationManager::with_auth(CodexAuth::from_api_key("Test API Key"));
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let expected_instructions = config.model_family.base_instructions.clone();
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let codex = conversation_manager
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.new_conversation(config)
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.await
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@@ -213,7 +214,6 @@ async fn prompt_tools_are_consistent_across_requests() {
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let requests = server.received_requests().await.unwrap();
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assert_eq!(requests.len(), 2, "expected two POST requests");
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let expected_instructions: &str = include_str!("../../prompt.md");
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// our internal implementation is responsible for keeping tools in sync
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// with the OpenAI schema, so we just verify the tool presence here
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let expected_tools_names: &[&str] = &["shell", "update_plan", "apply_patch", "view_image"];
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@@ -51,7 +51,7 @@ Start a new session with optional overrides:
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Request `newConversation` params (subset):
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- `model`: string model id (e.g. "o3", "gpt-5")
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- `model`: string model id (e.g. "o3", "gpt-5", "gpt-5-codex")
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- `profile`: optional named profile
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- `cwd`: optional working directory
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- `approvalPolicy`: `untrusted` | `on-request` | `on-failure` | `never`
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@@ -120,4 +120,3 @@ While processing, the server emits `codex/event` notifications containing agent
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## Compatibility and stability
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This interface is experimental. Method names, fields, and event shapes may evolve. For the authoritative schema, consult `protocol/src/mcp_protocol.rs` and the corresponding server wiring in `mcp-server/`.
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@@ -26,7 +26,7 @@ fn create_config_toml(codex_home: &Path) -> std::io::Result<()> {
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std::fs::write(
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config_toml,
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r#"
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model = "gpt-5"
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model = "gpt-5-codex"
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approval_policy = "on-request"
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sandbox_mode = "workspace-write"
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model_reasoning_summary = "detailed"
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@@ -92,7 +92,7 @@ async fn get_config_toml_parses_all_fields() {
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exclude_tmpdir_env_var: Some(true),
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exclude_slash_tmp: Some(true),
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}),
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model: Some("gpt-5".into()),
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model: Some("gpt-5-codex".into()),
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model_reasoning_effort: Some(ReasoningEffort::High),
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model_reasoning_summary: Some(ReasoningSummary::Detailed),
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model_verbosity: Some(Verbosity::Medium),
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@@ -69,7 +69,7 @@ fn create_config_toml(codex_home: &Path) -> std::io::Result<()> {
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std::fs::write(
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config_toml,
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r#"
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model = "gpt-5"
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model = "gpt-5-codex"
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model_reasoning_effort = "medium"
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"#,
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)
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@@ -710,7 +710,7 @@ mod tests {
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let request = ClientRequest::NewConversation {
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request_id: RequestId::Integer(42),
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params: NewConversationParams {
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model: Some("gpt-5".to_string()),
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model: Some("gpt-5-codex".to_string()),
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profile: None,
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cwd: None,
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approval_policy: Some(AskForApproval::OnRequest),
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@@ -726,7 +726,7 @@ mod tests {
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"method": "newConversation",
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"id": 42,
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"params": {
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"model": "gpt-5",
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"model": "gpt-5-codex",
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"approvalPolicy": "on-request"
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}
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}),
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@@ -1,6 +1,5 @@
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---
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source: tui/src/chatwidget/tests.rs
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assertion_line: 648
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expression: visible_after
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---
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> I’m going to scan the workspace and Cargo manifests to see build profiles and
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@@ -10,6 +9,14 @@ expression: visible_after
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└ List ls -la
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Read Cargo.toml
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• I'm reviewing the workspace's release profile, which has settings like
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lto=fat, strip=symbols, and codegen-units=1 to reduce binary size. However, it
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seems that "strip = symbols" only removes symbols, not debug information. In
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Rust 1.73+, both "symbols" and "debuginfo" stripping options are available. I
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should check whether using these results in a smaller binary. I’ll also skim
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through crates for heavy dependencies in Cargo.toml, including cli, core,
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exec, linux-sandbox, tui, login, ollama, and mcp.
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• Ran
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└ for d in ansi-escape apply-patch arg0 cli common core exec execpolicy
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file-search linux-sandbox login mcp-client mcp-server mcp-types ollama
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@@ -19,6 +26,79 @@ expression: visible_after
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• Explored
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└ Read Cargo.toml
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• I’m evaluating how binary size is influenced by various factors. There are
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many binaries, such as codex and codex-exec, which include dependencies by
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default, pulling in features like Tokio and hyper. For instance, reqwest
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includes default features like TLS through rustls. If default features remain
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enabled, it inflates the size with many additional components. I notice
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that for musl targets, using vendored builds of OpenSSL could significantly
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increase binary size. This is quite the intricate web of dependencies!
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|
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Analyzing musl and binary size
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I’m considering the implications of building for musl with static linking.
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In this case, OpenSSL might come into play through some crates, but reqwest
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defaults to using rustls, although openssl-sys vendored could increase
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binary size. It’s interesting to think about whether they’re targeting musl,
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especially since it seems they might often be building for Mac and Linux with
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dynamic linking instead.
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I also realize there’s a difference between debug and release builds — release
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should be smaller due to optimizations, but if they’re defaulting to debug
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builds, that could lead to much larger binaries.
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Assessing crate impacts on size
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I need to be precise when analyzing binary sizes from various crates. Some
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crates, like ratatui-image, include heavy features such as libjpeg decoders,
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which can really bulk things up. Then there are the tree-sitter crates that
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contain large static grammar tables, adding significant size. The starlark
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crate and tracing-subscriber also contribute to size increases.
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With static linking per binary being standard in Rust, it leads to multiple
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copies of the same dependencies unless cdylibs are used. That makes the
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compile times longer, but using LTO helps reduce bloat somewhat through
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deduplication.
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Evaluating binary size factors
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Having multiple binaries indeed increases the overall size significantly.
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I'm considering options like upgrading to "opt-level = 'z'" or using
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"strip=debuginfo" for reducing size. It's interesting that while the profile
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only sets symbols for stripping, not debuginfo, this could inflate sizes if
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retained in release builds.
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The distinction between "symbols" and "debuginfo" is critical; "symbols"
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keeps debug information which may not align with the goal of minimizing
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size. I’d like to verify with the Rust documentation, but my network access
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is restricted.
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|
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Explaining large binary sizes
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|
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I’m analyzing why binaries in this project are so large. The primary reasons
|
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include monolithic static linking, where each binary includes the full
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dependency graph without shared libraries. Heavy dependencies such as reqwest,
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hyper, and TLS components also contribute significantly to size, along with
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image decoders and other libraries.
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Using MUSL targets means vendored OpenSSL can drastically increase the
|
||||
size due to static linking. Furthermore, if the release profile keeps debug
|
||||
information due to using "strip = symbols," that can lead to larger binaries
|
||||
as well. It’s a mix of several factors, including panic strategies and
|
||||
platform-specific linking behavior.
|
||||
|
||||
Identifying binary size contributors
|
||||
|
||||
I’m considering why binaries are still large even without static linking. The
|
||||
tracing-subscriber crate potentially adds weight because it includes regex,
|
||||
though it can sometimes use a lighter version. References from files like
|
||||
"core/Cargo.toml" show dependencies like reqwest and tokio, while the tui uses
|
||||
the image crate.
|
||||
|
||||
To present this clearly, I’ll format the final answer with two main sections:
|
||||
"Main Causes" and "Build-Mode Notes." I can also include brief suggestions for
|
||||
reducing size, but I want to stay focused on answering the user's question.
|
||||
|
||||
> Here’s what’s driving size in this workspace’s binaries.
|
||||
|
||||
Main Causes
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
{"ts":"2025-08-09T15:51:04.827Z","dir":"meta","kind":"session_start","cwd":"/Users/easong/code/codex/codex-rs","model":"gpt-5","reasoning_effort":"medium","model_provider_id":"openai","model_provider_name":"OpenAI"}
|
||||
{"ts":"2025-08-09T15:51:04.827Z","dir":"meta","kind":"session_start","cwd":"/Users/easong/code/codex/codex-rs","model":"gpt-5-codex","reasoning_effort":"medium","model_provider_id":"openai","model_provider_name":"OpenAI"}
|
||||
{"ts":"2025-08-09T15:51:04.827Z","dir":"to_tui","kind":"key_event","event":"KeyEvent { code: Char('c'), modifiers: KeyModifiers(0x0), kind: Press, state: KeyEventState(0x0) }"}
|
||||
{"ts":"2025-08-09T15:51:04.827Z","dir":"to_tui","kind":"key_event","event":"KeyEvent { code: Char('o'), modifiers: KeyModifiers(0x0), kind: Press, state: KeyEventState(0x0) }"}
|
||||
{"ts":"2025-08-09T15:51:04.827Z","dir":"to_tui","kind":"key_event","event":"KeyEvent { code: Char('m'), modifiers: KeyModifiers(0x0), kind: Press, state: KeyEventState(0x0) }"}
|
||||
@@ -34,7 +34,7 @@
|
||||
{"ts":"2025-08-09T15:51:04.829Z","dir":"to_tui","kind":"app_event","variant":"RequestRedraw"}
|
||||
{"ts":"2025-08-09T15:51:04.829Z","dir":"to_tui","kind":"log_line","line":"[INFO codex_core::codex] resume_path: None"}
|
||||
{"ts":"2025-08-09T15:51:04.830Z","dir":"to_tui","kind":"app_event","variant":"Redraw"}
|
||||
{"ts":"2025-08-09T15:51:04.856Z","dir":"to_tui","kind":"codex_event","payload":{"id":"0","msg":{"type":"session_configured","session_id":"d126e3d0-80ed-480a-be8c-09d97ff602cf","model":"gpt-5","reasoning_effort":"medium","history_log_id":2532619,"history_entry_count":339,"rollout_path":"/tmp/codex-test-rollout.jsonl"}}}
|
||||
{"ts":"2025-08-09T15:51:04.856Z","dir":"to_tui","kind":"codex_event","payload":{"id":"0","msg":{"type":"session_configured","session_id":"d126e3d0-80ed-480a-be8c-09d97ff602cf","model":"gpt-5-codex","reasoning_effort":"medium","history_log_id":2532619,"history_entry_count":339,"rollout_path":"/tmp/codex-test-rollout.jsonl"}}}
|
||||
{"ts":"2025-08-09T15:51:04.856Z","dir":"to_tui","kind":"insert_history","lines":9}
|
||||
{"ts":"2025-08-09T15:51:04.857Z","dir":"to_tui","kind":"app_event","variant":"RequestRedraw"}
|
||||
{"ts":"2025-08-09T15:51:04.857Z","dir":"to_tui","kind":"app_event","variant":"RequestRedraw"}
|
||||
@@ -16447,7 +16447,7 @@
|
||||
{"ts":"2025-08-09T16:06:58.083Z","dir":"to_tui","kind":"app_event","variant":"RequestRedraw"}
|
||||
{"ts":"2025-08-09T16:06:58.085Z","dir":"to_tui","kind":"app_event","variant":"Redraw"}
|
||||
{"ts":"2025-08-09T16:06:58.085Z","dir":"to_tui","kind":"log_line","line":"[INFO codex_core::codex] resume_path: None"}
|
||||
{"ts":"2025-08-09T16:06:58.136Z","dir":"to_tui","kind":"codex_event","payload":{"id":"0","msg":{"type":"session_configured","session_id":"c7df96da-daec-4fe9-aed9-3cd19b7a6192","model":"gpt-5","reasoning_effort":"medium","history_log_id":2532619,"history_entry_count":342,"rollout_path":"/tmp/codex-test-rollout.jsonl"}}}
|
||||
{"ts":"2025-08-09T16:06:58.136Z","dir":"to_tui","kind":"codex_event","payload":{"id":"0","msg":{"type":"session_configured","session_id":"c7df96da-daec-4fe9-aed9-3cd19b7a6192","model":"gpt-5-codex","reasoning_effort":"medium","history_log_id":2532619,"history_entry_count":342,"rollout_path":"/tmp/codex-test-rollout.jsonl"}}}
|
||||
{"ts":"2025-08-09T16:06:58.136Z","dir":"to_tui","kind":"insert_history","lines":9}
|
||||
{"ts":"2025-08-09T16:06:58.136Z","dir":"to_tui","kind":"app_event","variant":"RequestRedraw"}
|
||||
{"ts":"2025-08-09T16:06:58.136Z","dir":"to_tui","kind":"app_event","variant":"RequestRedraw"}
|
||||
|
||||
@@ -21,7 +21,7 @@ Both the `--config` flag and the `config.toml` file support the following option
|
||||
The model that Codex should use.
|
||||
|
||||
```toml
|
||||
model = "o3" # overrides the default of "gpt-5"
|
||||
model = "o3" # overrides the default of "gpt-5-codex"
|
||||
```
|
||||
|
||||
## model_providers
|
||||
@@ -223,11 +223,11 @@ Users can specify config values at multiple levels. Order of precedence is as fo
|
||||
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 that comes with Codex CLI (i.e., Codex CLI defaults to `gpt-5`)
|
||||
4. the default value that comes with Codex CLI (i.e., Codex CLI defaults to `gpt-5-codex`)
|
||||
|
||||
## model_reasoning_effort
|
||||
|
||||
If the selected model is known to support reasoning (for example: `o3`, `o4-mini`, `codex-*`, `gpt-5`), reasoning is enabled by default when using the Responses API. As explained in the [OpenAI Platform documentation](https://platform.openai.com/docs/guides/reasoning?api-mode=responses#get-started-with-reasoning), this can be set to:
|
||||
If the selected model is known to support reasoning (for example: `o3`, `o4-mini`, `codex-*`, `gpt-5`, `gpt-5-codex`), reasoning is enabled by default when using the Responses API. As explained in the [OpenAI Platform documentation](https://platform.openai.com/docs/guides/reasoning?api-mode=responses#get-started-with-reasoning), this can be set to:
|
||||
|
||||
- `"minimal"`
|
||||
- `"low"`
|
||||
@@ -606,7 +606,7 @@ notifications = [ "agent-turn-complete", "approval-requested" ]
|
||||
|
||||
| Key | Type / Values | Notes |
|
||||
| --- | --- | --- |
|
||||
| `model` | string | Model to use (e.g., `gpt-5`). |
|
||||
| `model` | string | Model to use (e.g., `gpt-5-codex`). |
|
||||
| `model_provider` | string | Provider id from `model_providers` (default: `openai`). |
|
||||
| `model_context_window` | number | Context window tokens. |
|
||||
| `model_max_output_tokens` | number | Max output tokens. |
|
||||
|
||||
Reference in New Issue
Block a user