Files
llmx/codex-rs/common/src/model_presets.rs
2025-09-15 08:17:13 -07:00

82 lines
2.6 KiB
Rust

use codex_core::config::GPT_5_CODEX_MEDIUM_MODEL;
use codex_core::protocol_config_types::ReasoningEffort;
use codex_protocol::mcp_protocol::AuthMode;
/// A simple preset pairing a model slug with a reasoning effort.
#[derive(Debug, Clone, Copy)]
pub struct ModelPreset {
/// Stable identifier for the preset.
pub id: &'static str,
/// Display label shown in UIs.
pub label: &'static str,
/// Short human description shown next to the label in UIs.
pub description: &'static str,
/// Model slug (e.g., "gpt-5").
pub model: &'static str,
/// Reasoning effort to apply for this preset.
pub effort: Option<ReasoningEffort>,
}
const PRESETS: &[ModelPreset] = &[
ModelPreset {
id: "gpt-5-codex-low",
label: "gpt-5-codex low",
description: "",
model: "gpt-5-codex",
effort: Some(ReasoningEffort::Low),
},
ModelPreset {
id: "gpt-5-codex-medium",
label: "gpt-5-codex medium",
description: "",
model: "gpt-5-codex",
effort: None,
},
ModelPreset {
id: "gpt-5-codex-high",
label: "gpt-5-codex high",
description: "",
model: "gpt-5-codex",
effort: Some(ReasoningEffort::High),
},
ModelPreset {
id: "gpt-5-minimal",
label: "gpt-5 minimal",
description: "— fastest responses with limited reasoning; ideal for coding, instructions, or lightweight tasks",
model: "gpt-5",
effort: Some(ReasoningEffort::Minimal),
},
ModelPreset {
id: "gpt-5-low",
label: "gpt-5 low",
description: "— balances speed with some reasoning; useful for straightforward queries and short explanations",
model: "gpt-5",
effort: Some(ReasoningEffort::Low),
},
ModelPreset {
id: "gpt-5-medium",
label: "gpt-5 medium",
description: "— default setting; provides a solid balance of reasoning depth and latency for general-purpose tasks",
model: "gpt-5",
effort: Some(ReasoningEffort::Medium),
},
ModelPreset {
id: "gpt-5-high",
label: "gpt-5 high",
description: "— maximizes reasoning depth for complex or ambiguous problems",
model: "gpt-5",
effort: Some(ReasoningEffort::High),
},
];
pub fn builtin_model_presets(auth_mode: Option<AuthMode>) -> Vec<ModelPreset> {
match auth_mode {
Some(AuthMode::ApiKey) => PRESETS
.iter()
.copied()
.filter(|p| p.model != GPT_5_CODEX_MEDIUM_MODEL)
.collect(),
_ => PRESETS.to_vec(),
}
}