74 lines
2.4 KiB
Rust
74 lines
2.4 KiB
Rust
use codex_app_server_protocol::AuthMode;
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use codex_core::protocol_config_types::ReasoningEffort;
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/// A simple preset pairing a model slug with a reasoning effort.
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#[derive(Debug, Clone, Copy)]
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pub struct ModelPreset {
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/// Stable identifier for the preset.
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pub id: &'static str,
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/// Display label shown in UIs.
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pub label: &'static str,
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/// Short human description shown next to the label in UIs.
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pub description: &'static str,
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/// Model slug (e.g., "gpt-5").
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pub model: &'static str,
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/// Reasoning effort to apply for this preset.
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pub effort: Option<ReasoningEffort>,
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}
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const PRESETS: &[ModelPreset] = &[
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ModelPreset {
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id: "gpt-5-codex-low",
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label: "gpt-5-codex low",
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description: "Fastest responses with limited reasoning",
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model: "gpt-5-codex",
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effort: Some(ReasoningEffort::Low),
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},
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ModelPreset {
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id: "gpt-5-codex-medium",
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label: "gpt-5-codex medium",
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description: "Dynamically adjusts reasoning based on the task",
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model: "gpt-5-codex",
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effort: Some(ReasoningEffort::Medium),
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},
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ModelPreset {
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id: "gpt-5-codex-high",
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label: "gpt-5-codex high",
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description: "Maximizes reasoning depth for complex or ambiguous problems",
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model: "gpt-5-codex",
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effort: Some(ReasoningEffort::High),
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},
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ModelPreset {
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id: "gpt-5-minimal",
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label: "gpt-5 minimal",
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description: "Fastest responses with little reasoning",
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model: "gpt-5",
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effort: Some(ReasoningEffort::Minimal),
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},
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ModelPreset {
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id: "gpt-5-low",
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label: "gpt-5 low",
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description: "Balances speed with some reasoning; useful for straightforward queries and short explanations",
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model: "gpt-5",
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effort: Some(ReasoningEffort::Low),
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},
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ModelPreset {
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id: "gpt-5-medium",
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label: "gpt-5 medium",
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description: "Provides a solid balance of reasoning depth and latency for general-purpose tasks",
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model: "gpt-5",
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effort: Some(ReasoningEffort::Medium),
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},
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ModelPreset {
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id: "gpt-5-high",
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label: "gpt-5 high",
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description: "Maximizes reasoning depth for complex or ambiguous problems",
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model: "gpt-5",
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effort: Some(ReasoningEffort::High),
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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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PRESETS.to_vec()
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}
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