mirror of
https://github.com/instructkr/claude-code.git
synced 2026-05-06 14:10:52 +08:00
Cap OpenAI default output tokens using model metadata
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@@ -252,17 +252,16 @@ pub fn detect_provider_kind(model: &str) -> ProviderKind {
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#[must_use]
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pub fn max_tokens_for_model(model: &str) -> u32 {
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model_token_limit(model).map_or_else(
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|| {
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let canonical = resolve_model_alias(model);
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if canonical.contains("opus") {
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32_000
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} else {
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64_000
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}
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},
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|limit| limit.max_output_tokens,
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)
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let canonical = resolve_model_alias(model);
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let heuristic = if canonical.contains("opus") {
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32_000
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} else {
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64_000
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};
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model_token_limit(model)
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.map(|limit| heuristic.min(limit.max_output_tokens))
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.unwrap_or(heuristic)
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}
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/// Returns the effective max output tokens for a model, preferring a plugin
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@@ -276,7 +275,8 @@ pub fn max_tokens_for_model_with_override(model: &str, plugin_override: Option<u
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#[must_use]
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pub fn model_token_limit(model: &str) -> Option<ModelTokenLimit> {
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let canonical = resolve_model_alias(model);
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match canonical.as_str() {
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let base_model = canonical.rsplit('/').next().unwrap_or(canonical.as_str());
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match base_model {
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"claude-opus-4-6" => Some(ModelTokenLimit {
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max_output_tokens: 32_000,
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context_window_tokens: 200_000,
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@@ -289,6 +289,20 @@ pub fn model_token_limit(model: &str) -> Option<ModelTokenLimit> {
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max_output_tokens: 64_000,
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context_window_tokens: 131_072,
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}),
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// GPT-4.1 family via the OpenAI API.
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"gpt-4.1" | "gpt-4.1-mini" | "gpt-4.1-nano" => Some(ModelTokenLimit {
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max_output_tokens: 32_768,
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context_window_tokens: 1_047_576,
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}),
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// GPT-5.4 family via the OpenAI API.
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"gpt-5.4" => Some(ModelTokenLimit {
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max_output_tokens: 128_000,
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context_window_tokens: 1_000_000,
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}),
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"gpt-5.4-mini" | "gpt-5.4-nano" => Some(ModelTokenLimit {
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max_output_tokens: 128_000,
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context_window_tokens: 400_000,
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}),
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// Kimi models via DashScope (Moonshot AI)
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// Source: https://platform.moonshot.cn/docs/intro
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"kimi-k2.5" | "kimi-k1.5" => Some(ModelTokenLimit {
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@@ -614,6 +628,15 @@ mod tests {
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fn keeps_existing_max_token_heuristic() {
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assert_eq!(max_tokens_for_model("opus"), 32_000);
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assert_eq!(max_tokens_for_model("grok-3"), 64_000);
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assert_eq!(max_tokens_for_model("gpt-5.4"), 64_000);
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}
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#[test]
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fn caps_default_max_tokens_to_openai_model_limits() {
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assert_eq!(max_tokens_for_model("gpt-4.1-mini"), 32_768);
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assert_eq!(max_tokens_for_model("openai/gpt-4.1-mini"), 32_768);
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assert_eq!(max_tokens_for_model("gpt-5.4"), 64_000);
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assert_eq!(max_tokens_for_model("openai/gpt-5.4"), 64_000);
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}
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#[test]
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@@ -680,6 +703,18 @@ mod tests {
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.context_window_tokens,
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131_072
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);
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assert_eq!(
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model_token_limit("openai/gpt-4.1-mini")
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.expect("openai/gpt-4.1-mini should be registered")
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.context_window_tokens,
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1_047_576
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);
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assert_eq!(
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model_token_limit("gpt-5.4")
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.expect("gpt-5.4 should be registered")
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.context_window_tokens,
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1_000_000
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);
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}
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#[test]
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@@ -728,6 +763,42 @@ mod tests {
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}
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}
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#[test]
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fn preflight_blocks_oversized_requests_for_gpt_5_4() {
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let request = MessageRequest {
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model: "gpt-5.4".to_string(),
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max_tokens: 64_000,
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messages: vec![InputMessage {
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role: "user".to_string(),
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content: vec![InputContentBlock::Text {
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text: "x".repeat(3_900_000),
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}],
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}],
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system: Some("Keep the answer short.".to_string()),
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tools: None,
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tool_choice: None,
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stream: true,
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..Default::default()
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};
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let error = preflight_message_request(&request)
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.expect_err("oversized gpt-5.4 request should be rejected before the provider call");
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match error {
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ApiError::ContextWindowExceeded {
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model,
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requested_output_tokens,
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context_window_tokens,
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..
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} => {
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assert_eq!(model, "gpt-5.4");
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assert_eq!(requested_output_tokens, 64_000);
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assert_eq!(context_window_tokens, 1_000_000);
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}
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other => panic!("expected context-window preflight failure, got {other:?}"),
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}
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}
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#[test]
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fn preflight_skips_unknown_models() {
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let request = MessageRequest {
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@@ -148,11 +148,7 @@ impl ModelProvenance {
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}
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fn max_tokens_for_model(model: &str) -> u32 {
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if model.contains("opus") {
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32_000
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} else {
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64_000
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}
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api::max_tokens_for_model(model)
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}
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// Build-time constants injected by build.rs (fall back to static values when
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// build.rs hasn't run, e.g. in doc-test or unusual toolchain environments).
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