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fix(ai): derive Google thinking levels from models.dev
Extract Google catalog processing and apply models.dev reasoning effort metadata directly for Google, Vertex, and OpenCode models. Keep the provider-specific Gemma 4 toggle mapping.
This commit is contained in:
David Brailovsky
parent
1247476e6d
commit
aa50fe778a
2 changed files with 120 additions and 98 deletions
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@ -555,10 +555,6 @@ function supportsOpenAiMax(model: Model<Api>): boolean {
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);
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}
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function isGoogleThinkingApi(model: Model<any>): boolean {
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return model.api === "google-generative-ai" || model.api === "google-vertex";
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}
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const VERIFIED_ANTHROPIC_MID_CONVO_EFFORT_PROVIDERS = new Set(["anthropic", "openrouter"]);
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// OpenRouter rejects `configuration_update` system messages on Opus 5 ("Mid-conversation
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// reasoning effort (configuration_update) is not supported on anthropic/claude-opus-5-20260723")
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@ -930,19 +926,22 @@ function applyOpenAIExplicitPromptCacheMetadata(model: Model<Api>): void {
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};
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}
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function isGemini3ProModel(modelId: string): boolean {
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return /gemini-3(?:\.\d+)?-pro/.test(modelId.toLowerCase());
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}
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function isGemini3FlashModel(modelId: string): boolean {
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const id = modelId.toLowerCase();
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return /gemini-3(?:\.\d+)?-flash/.test(id) || id === "gemini-flash-latest" || id === "gemini-flash-lite-latest";
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}
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function isGemma4Model(modelId: string): boolean {
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return /gemma-?4/.test(modelId.toLowerCase());
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}
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function getGoogleThinkingLevelMap(
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modelId: string,
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reasoningOptions: readonly ModelsDevReasoningOption[],
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): NonNullable<Model<Api>["thinkingLevelMap"]> | undefined {
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const effortMap = getEffortThinkingLevelMap(reasoningOptions);
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if (effortMap) return effortMap;
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if (isGemma4Model(modelId)) {
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return { off: null, minimal: "MINIMAL", low: null, medium: null, high: "HIGH" };
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}
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return undefined;
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}
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function applyThinkingLevelMetadata(model: Model<any>): void {
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if (
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(model.api === "openai-responses" || model.api === "azure-openai-responses") &&
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@ -1036,15 +1035,6 @@ function applyThinkingLevelMetadata(model: Model<any>): void {
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: DEEPSEEK_V4_THINKING_LEVEL_MAP,
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);
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}
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if (isGoogleThinkingApi(model) && isGemini3ProModel(model.id)) {
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mergeThinkingLevelMap(model, { off: null, minimal: null, low: "LOW", medium: null, high: "HIGH" });
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}
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if (isGoogleThinkingApi(model) && isGemini3FlashModel(model.id)) {
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mergeThinkingLevelMap(model, { off: null });
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}
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if (isGoogleThinkingApi(model) && isGemma4Model(model.id)) {
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mergeThinkingLevelMap(model, { off: null, minimal: "MINIMAL", low: null, medium: null, high: "HIGH" });
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}
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if (model.provider === "groq" && model.id === "qwen/qwen3.6-27b") {
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mergeThinkingLevelMap(model, { minimal: null, low: null, medium: null, high: "default" });
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}
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@ -1496,6 +1486,84 @@ function processBasetenModels(provider: ModelsDevProvider | undefined): Model<Ap
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return models;
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}
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function processGoogleModels(data: ModelsDevCatalog): Model<Api>[] {
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const models: Model<Api>[] = [];
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const googleModels = data.google?.models;
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if (googleModels) {
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for (const [modelId, model] of Object.entries(googleModels)) {
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if (model.tool_call !== true) continue;
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const source =
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modelId === "gemini-flash-latest"
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? (googleModels["gemini-3.5-flash"] ?? model)
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: modelId === "gemini-flash-lite-latest"
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? (googleModels["gemini-3.1-flash-lite"] ?? model)
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: model;
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const thinkingLevelMap = getGoogleThinkingLevelMap(modelId, source.reasoning_options ?? []);
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models.push({
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id: modelId,
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name: model.name || modelId,
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api: "google-generative-ai",
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provider: "google",
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baseUrl: "https://generativelanguage.googleapis.com/v1beta",
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reasoning: source.reasoning === true,
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...(thinkingLevelMap ? { thinkingLevelMap } : {}),
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input: source.modalities?.input?.includes("image") ? ["text", "image"] : ["text"],
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cost: {
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input: source.cost?.input || 0,
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output: source.cost?.output || 0,
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cacheRead: source.cost?.cache_read || 0,
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cacheWrite: source.cost?.cache_write || 0,
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},
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contextWindow: source.limit?.context || 4096,
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maxTokens: source.limit?.output || 4096,
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});
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}
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}
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// The google-vertex models.dev catalog also includes Claude, OpenAI, and other
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// MaaS models that do not use the @google/genai Gemini streaming path.
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const vertexModels = data["google-vertex"]?.models;
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if (vertexModels) {
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for (const [modelId, model] of Object.entries(vertexModels)) {
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if (model.tool_call !== true || !modelId.startsWith("gemini-")) continue;
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if (modelId === "gemini-3.1-flash-lite-preview") continue;
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const source =
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modelId === "gemini-flash-latest"
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? (vertexModels["gemini-3.5-flash"] ?? model)
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: modelId === "gemini-flash-lite-latest"
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? (vertexModels["gemini-3.1-flash-lite"] ?? model)
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: model;
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const thinkingLevelMap = getGoogleThinkingLevelMap(modelId, source.reasoning_options ?? []);
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// models.dev reports Vertex cache_read/cache_write values for Gemini 2.5 Flash that
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// do not match the official Gemini API standard pricing table. pi only accounts
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// cachedContentTokenCount as cacheRead.
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const cacheRead = modelId === "gemini-2.5-flash" ? 0.03 : source.cost?.cache_read || 0;
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models.push({
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id: modelId,
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name: model.name || modelId,
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api: "google-vertex",
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provider: "google-vertex",
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baseUrl: VERTEX_BASE_URL,
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reasoning: source.reasoning === true,
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...(thinkingLevelMap ? { thinkingLevelMap } : {}),
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input: source.modalities?.input?.includes("image") ? ["text", "image"] : ["text"],
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cost: {
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input: source.cost?.input || 0,
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output: source.cost?.output || 0,
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cacheRead,
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cacheWrite: 0,
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},
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contextWindow: source.limit?.context || 4096,
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maxTokens: source.limit?.output || 4096,
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});
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}
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}
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return models;
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}
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function processFireworksModels(provider: ModelsDevProvider | undefined): Model<Api>[] {
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if (!provider?.models) return [];
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@ -1660,81 +1728,7 @@ async function loadModelsDevData(): Promise<Model<any>[]> {
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}
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}
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// Process Google models
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if (data.google?.models) {
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for (const [modelId, model] of Object.entries(data.google.models)) {
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const m = model as ModelsDevModel;
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if (m.tool_call !== true) continue;
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let source = m;
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if (modelId === "gemini-flash-latest") {
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source = (data.google.models["gemini-3.5-flash"] as ModelsDevModel | undefined) ?? m;
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}
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if (modelId === "gemini-flash-lite-latest") {
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source = (data.google.models["gemini-3.1-flash-lite"] as ModelsDevModel | undefined) ?? m;
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}
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models.push({
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id: modelId,
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name: m.name || modelId,
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api: "google-generative-ai",
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provider: "google",
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baseUrl: "https://generativelanguage.googleapis.com/v1beta",
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reasoning: source.reasoning === true,
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input: source.modalities?.input?.includes("image") ? ["text", "image"] : ["text"],
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cost: {
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input: source.cost?.input || 0,
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output: source.cost?.output || 0,
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cacheRead: source.cost?.cache_read || 0,
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cacheWrite: source.cost?.cache_write || 0,
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},
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contextWindow: source.limit?.context || 4096,
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maxTokens: source.limit?.output || 4096,
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});
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recordModelsDevReasoningOptions("google", modelId, source);
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}
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}
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// Process Google Vertex Gemini models. The google-vertex models.dev catalog also includes
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// Claude, OpenAI, and other MaaS models that do not use the @google/genai Gemini streaming
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// path implemented by our google-vertex provider.
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if (data["google-vertex"]?.models) {
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for (const [modelId, model] of Object.entries(data["google-vertex"].models)) {
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const m = model as ModelsDevModel;
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if (m.tool_call !== true) continue;
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if (!modelId.startsWith("gemini-")) continue;
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if (modelId === "gemini-3.1-flash-lite-preview") continue;
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let source = m;
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if (modelId === "gemini-flash-latest") {
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source = (data["google-vertex"].models["gemini-3.5-flash"] as ModelsDevModel | undefined) ?? m;
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}
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if (modelId === "gemini-flash-lite-latest") {
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source = (data["google-vertex"].models["gemini-3.1-flash-lite"] as ModelsDevModel | undefined) ?? m;
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}
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// models.dev reports Vertex cache_read/cache_write values for Gemini 2.5 Flash that
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// do not match the official Gemini API standard pricing table. pi only accounts
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// cachedContentTokenCount as cacheRead.
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const cacheRead = modelId === "gemini-2.5-flash" ? 0.03 : source.cost?.cache_read || 0;
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models.push({
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id: modelId,
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name: m.name || modelId,
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api: "google-vertex",
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provider: "google-vertex",
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baseUrl: VERTEX_BASE_URL,
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reasoning: source.reasoning === true,
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input: source.modalities?.input?.includes("image") ? ["text", "image"] : ["text"],
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cost: {
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input: source.cost?.input || 0,
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output: source.cost?.output || 0,
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cacheRead,
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cacheWrite: 0,
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},
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contextWindow: source.limit?.context || 4096,
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maxTokens: source.limit?.output || 4096,
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});
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recordModelsDevReasoningOptions("google-vertex", modelId, source);
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}
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}
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models.push(...processGoogleModels(data));
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// Process OpenAI models
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if (data.openai?.models) {
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@ -2186,6 +2180,10 @@ async function loadModelsDevData(): Promise<Model<any>[]> {
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}
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}
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const thinkingLevelMap =
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api === "google-generative-ai"
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? getGoogleThinkingLevelMap(modelId, m.reasoning_options ?? [])
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: undefined;
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models.push({
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id: modelId,
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name: m.name || modelId,
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@ -2193,6 +2191,7 @@ async function loadModelsDevData(): Promise<Model<any>[]> {
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provider: variant.provider,
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baseUrl,
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reasoning: m.reasoning === true,
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...(thinkingLevelMap ? { thinkingLevelMap } : {}),
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input: m.modalities?.input?.includes("image") ? ["text", "image"] : ["text"],
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cost: {
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input: m.cost?.input || 0,
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@ -2,7 +2,7 @@ import { describe, expect, it } from "vitest";
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import { lazyApi } from "../src/api/lazy.ts";
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import { envApiKeyAuth } from "../src/auth/helpers.ts";
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import type { AuthContext, AuthEvent } from "../src/auth/types.ts";
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import { createModels, createProvider } from "../src/models.ts";
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import { createModels, createProvider, getSupportedThinkingLevels } from "../src/models.ts";
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import { InMemoryModelsStore } from "../src/models-store.ts";
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import { builtinModels, builtinProviders, getBuiltinModel } from "../src/providers/all.ts";
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import { amazonBedrockProvider } from "../src/providers/amazon-bedrock.ts";
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@ -66,6 +66,29 @@ describe("builtin providers", () => {
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expect(getBuiltinModel("anthropic", "claude-haiku-4-5").compat?.supportsStrictTools).toBe(true);
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});
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it("uses models.dev effort levels for Google thinking models", () => {
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// Regression test for https://github.com/earendil-works/pi/issues/9455
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for (const provider of ["google", "google-vertex"] as const) {
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expect(getSupportedThinkingLevels(getBuiltinModel(provider, "gemini-3.6-flash"))).toContain("minimal");
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expect(getSupportedThinkingLevels(getBuiltinModel(provider, "gemini-3.8-flash"))).toEqual([
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"low",
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"medium",
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"high",
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]);
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expect(getSupportedThinkingLevels(getBuiltinModel(provider, "gemini-3.1-pro-preview"))).toEqual([
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"low",
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"medium",
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"high",
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]);
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}
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expect(getSupportedThinkingLevels(getBuiltinModel("opencode", "gemini-3.8-flash"))).toEqual([
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"low",
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"medium",
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"high",
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]);
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expect(getSupportedThinkingLevels(getBuiltinModel("google", "gemma-4-31b-it"))).toEqual(["minimal", "high"]);
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});
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it("enables mid-conversation system messages only for verified models", () => {
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const models = builtinModels();
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const supported = [
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