mirror of
https://github.com/badlogic/pi-mono.git
synced 2026-11-05 23:37:25 +00:00
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
|
|
@ -555,10 +555,6 @@ function supportsOpenAiMax(model: Model<Api>): boolean {
|
|||
);
|
||||
}
|
||||
|
||||
function isGoogleThinkingApi(model: Model<any>): boolean {
|
||||
return model.api === "google-generative-ai" || model.api === "google-vertex";
|
||||
}
|
||||
|
||||
const VERIFIED_ANTHROPIC_MID_CONVO_EFFORT_PROVIDERS = new Set(["anthropic", "openrouter"]);
|
||||
// OpenRouter rejects `configuration_update` system messages on Opus 5 ("Mid-conversation
|
||||
// reasoning effort (configuration_update) is not supported on anthropic/claude-opus-5-20260723")
|
||||
|
|
@ -930,19 +926,22 @@ function applyOpenAIExplicitPromptCacheMetadata(model: Model<Api>): void {
|
|||
};
|
||||
}
|
||||
|
||||
function isGemini3ProModel(modelId: string): boolean {
|
||||
return /gemini-3(?:\.\d+)?-pro/.test(modelId.toLowerCase());
|
||||
}
|
||||
|
||||
function isGemini3FlashModel(modelId: string): boolean {
|
||||
const id = modelId.toLowerCase();
|
||||
return /gemini-3(?:\.\d+)?-flash/.test(id) || id === "gemini-flash-latest" || id === "gemini-flash-lite-latest";
|
||||
}
|
||||
|
||||
function isGemma4Model(modelId: string): boolean {
|
||||
return /gemma-?4/.test(modelId.toLowerCase());
|
||||
}
|
||||
|
||||
function getGoogleThinkingLevelMap(
|
||||
modelId: string,
|
||||
reasoningOptions: readonly ModelsDevReasoningOption[],
|
||||
): NonNullable<Model<Api>["thinkingLevelMap"]> | undefined {
|
||||
const effortMap = getEffortThinkingLevelMap(reasoningOptions);
|
||||
if (effortMap) return effortMap;
|
||||
if (isGemma4Model(modelId)) {
|
||||
return { off: null, minimal: "MINIMAL", low: null, medium: null, high: "HIGH" };
|
||||
}
|
||||
return undefined;
|
||||
}
|
||||
|
||||
function applyThinkingLevelMetadata(model: Model<any>): void {
|
||||
if (
|
||||
(model.api === "openai-responses" || model.api === "azure-openai-responses") &&
|
||||
|
|
@ -1036,15 +1035,6 @@ function applyThinkingLevelMetadata(model: Model<any>): void {
|
|||
: DEEPSEEK_V4_THINKING_LEVEL_MAP,
|
||||
);
|
||||
}
|
||||
if (isGoogleThinkingApi(model) && isGemini3ProModel(model.id)) {
|
||||
mergeThinkingLevelMap(model, { off: null, minimal: null, low: "LOW", medium: null, high: "HIGH" });
|
||||
}
|
||||
if (isGoogleThinkingApi(model) && isGemini3FlashModel(model.id)) {
|
||||
mergeThinkingLevelMap(model, { off: null });
|
||||
}
|
||||
if (isGoogleThinkingApi(model) && isGemma4Model(model.id)) {
|
||||
mergeThinkingLevelMap(model, { off: null, minimal: "MINIMAL", low: null, medium: null, high: "HIGH" });
|
||||
}
|
||||
if (model.provider === "groq" && model.id === "qwen/qwen3.6-27b") {
|
||||
mergeThinkingLevelMap(model, { minimal: null, low: null, medium: null, high: "default" });
|
||||
}
|
||||
|
|
@ -1496,6 +1486,84 @@ function processBasetenModels(provider: ModelsDevProvider | undefined): Model<Ap
|
|||
return models;
|
||||
}
|
||||
|
||||
function processGoogleModels(data: ModelsDevCatalog): Model<Api>[] {
|
||||
const models: Model<Api>[] = [];
|
||||
const googleModels = data.google?.models;
|
||||
if (googleModels) {
|
||||
for (const [modelId, model] of Object.entries(googleModels)) {
|
||||
if (model.tool_call !== true) continue;
|
||||
const source =
|
||||
modelId === "gemini-flash-latest"
|
||||
? (googleModels["gemini-3.5-flash"] ?? model)
|
||||
: modelId === "gemini-flash-lite-latest"
|
||||
? (googleModels["gemini-3.1-flash-lite"] ?? model)
|
||||
: model;
|
||||
const thinkingLevelMap = getGoogleThinkingLevelMap(modelId, source.reasoning_options ?? []);
|
||||
|
||||
models.push({
|
||||
id: modelId,
|
||||
name: model.name || modelId,
|
||||
api: "google-generative-ai",
|
||||
provider: "google",
|
||||
baseUrl: "https://generativelanguage.googleapis.com/v1beta",
|
||||
reasoning: source.reasoning === true,
|
||||
...(thinkingLevelMap ? { thinkingLevelMap } : {}),
|
||||
input: source.modalities?.input?.includes("image") ? ["text", "image"] : ["text"],
|
||||
cost: {
|
||||
input: source.cost?.input || 0,
|
||||
output: source.cost?.output || 0,
|
||||
cacheRead: source.cost?.cache_read || 0,
|
||||
cacheWrite: source.cost?.cache_write || 0,
|
||||
},
|
||||
contextWindow: source.limit?.context || 4096,
|
||||
maxTokens: source.limit?.output || 4096,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// The google-vertex models.dev catalog also includes Claude, OpenAI, and other
|
||||
// MaaS models that do not use the @google/genai Gemini streaming path.
|
||||
const vertexModels = data["google-vertex"]?.models;
|
||||
if (vertexModels) {
|
||||
for (const [modelId, model] of Object.entries(vertexModels)) {
|
||||
if (model.tool_call !== true || !modelId.startsWith("gemini-")) continue;
|
||||
if (modelId === "gemini-3.1-flash-lite-preview") continue;
|
||||
const source =
|
||||
modelId === "gemini-flash-latest"
|
||||
? (vertexModels["gemini-3.5-flash"] ?? model)
|
||||
: modelId === "gemini-flash-lite-latest"
|
||||
? (vertexModels["gemini-3.1-flash-lite"] ?? model)
|
||||
: model;
|
||||
const thinkingLevelMap = getGoogleThinkingLevelMap(modelId, source.reasoning_options ?? []);
|
||||
// models.dev reports Vertex cache_read/cache_write values for Gemini 2.5 Flash that
|
||||
// do not match the official Gemini API standard pricing table. pi only accounts
|
||||
// cachedContentTokenCount as cacheRead.
|
||||
const cacheRead = modelId === "gemini-2.5-flash" ? 0.03 : source.cost?.cache_read || 0;
|
||||
|
||||
models.push({
|
||||
id: modelId,
|
||||
name: model.name || modelId,
|
||||
api: "google-vertex",
|
||||
provider: "google-vertex",
|
||||
baseUrl: VERTEX_BASE_URL,
|
||||
reasoning: source.reasoning === true,
|
||||
...(thinkingLevelMap ? { thinkingLevelMap } : {}),
|
||||
input: source.modalities?.input?.includes("image") ? ["text", "image"] : ["text"],
|
||||
cost: {
|
||||
input: source.cost?.input || 0,
|
||||
output: source.cost?.output || 0,
|
||||
cacheRead,
|
||||
cacheWrite: 0,
|
||||
},
|
||||
contextWindow: source.limit?.context || 4096,
|
||||
maxTokens: source.limit?.output || 4096,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
return models;
|
||||
}
|
||||
|
||||
function processFireworksModels(provider: ModelsDevProvider | undefined): Model<Api>[] {
|
||||
if (!provider?.models) return [];
|
||||
|
||||
|
|
@ -1660,81 +1728,7 @@ async function loadModelsDevData(): Promise<Model<any>[]> {
|
|||
}
|
||||
}
|
||||
|
||||
// Process Google models
|
||||
if (data.google?.models) {
|
||||
for (const [modelId, model] of Object.entries(data.google.models)) {
|
||||
const m = model as ModelsDevModel;
|
||||
if (m.tool_call !== true) continue;
|
||||
let source = m;
|
||||
if (modelId === "gemini-flash-latest") {
|
||||
source = (data.google.models["gemini-3.5-flash"] as ModelsDevModel | undefined) ?? m;
|
||||
}
|
||||
if (modelId === "gemini-flash-lite-latest") {
|
||||
source = (data.google.models["gemini-3.1-flash-lite"] as ModelsDevModel | undefined) ?? m;
|
||||
}
|
||||
|
||||
models.push({
|
||||
id: modelId,
|
||||
name: m.name || modelId,
|
||||
api: "google-generative-ai",
|
||||
provider: "google",
|
||||
baseUrl: "https://generativelanguage.googleapis.com/v1beta",
|
||||
reasoning: source.reasoning === true,
|
||||
input: source.modalities?.input?.includes("image") ? ["text", "image"] : ["text"],
|
||||
cost: {
|
||||
input: source.cost?.input || 0,
|
||||
output: source.cost?.output || 0,
|
||||
cacheRead: source.cost?.cache_read || 0,
|
||||
cacheWrite: source.cost?.cache_write || 0,
|
||||
},
|
||||
contextWindow: source.limit?.context || 4096,
|
||||
maxTokens: source.limit?.output || 4096,
|
||||
});
|
||||
recordModelsDevReasoningOptions("google", modelId, source);
|
||||
}
|
||||
}
|
||||
|
||||
// Process Google Vertex Gemini models. The google-vertex models.dev catalog also includes
|
||||
// Claude, OpenAI, and other MaaS models that do not use the @google/genai Gemini streaming
|
||||
// path implemented by our google-vertex provider.
|
||||
if (data["google-vertex"]?.models) {
|
||||
for (const [modelId, model] of Object.entries(data["google-vertex"].models)) {
|
||||
const m = model as ModelsDevModel;
|
||||
if (m.tool_call !== true) continue;
|
||||
if (!modelId.startsWith("gemini-")) continue;
|
||||
if (modelId === "gemini-3.1-flash-lite-preview") continue;
|
||||
let source = m;
|
||||
if (modelId === "gemini-flash-latest") {
|
||||
source = (data["google-vertex"].models["gemini-3.5-flash"] as ModelsDevModel | undefined) ?? m;
|
||||
}
|
||||
if (modelId === "gemini-flash-lite-latest") {
|
||||
source = (data["google-vertex"].models["gemini-3.1-flash-lite"] as ModelsDevModel | undefined) ?? m;
|
||||
}
|
||||
|
||||
// models.dev reports Vertex cache_read/cache_write values for Gemini 2.5 Flash that
|
||||
// do not match the official Gemini API standard pricing table. pi only accounts
|
||||
// cachedContentTokenCount as cacheRead.
|
||||
const cacheRead = modelId === "gemini-2.5-flash" ? 0.03 : source.cost?.cache_read || 0;
|
||||
models.push({
|
||||
id: modelId,
|
||||
name: m.name || modelId,
|
||||
api: "google-vertex",
|
||||
provider: "google-vertex",
|
||||
baseUrl: VERTEX_BASE_URL,
|
||||
reasoning: source.reasoning === true,
|
||||
input: source.modalities?.input?.includes("image") ? ["text", "image"] : ["text"],
|
||||
cost: {
|
||||
input: source.cost?.input || 0,
|
||||
output: source.cost?.output || 0,
|
||||
cacheRead,
|
||||
cacheWrite: 0,
|
||||
},
|
||||
contextWindow: source.limit?.context || 4096,
|
||||
maxTokens: source.limit?.output || 4096,
|
||||
});
|
||||
recordModelsDevReasoningOptions("google-vertex", modelId, source);
|
||||
}
|
||||
}
|
||||
models.push(...processGoogleModels(data));
|
||||
|
||||
// Process OpenAI models
|
||||
if (data.openai?.models) {
|
||||
|
|
@ -2186,6 +2180,10 @@ async function loadModelsDevData(): Promise<Model<any>[]> {
|
|||
}
|
||||
}
|
||||
|
||||
const thinkingLevelMap =
|
||||
api === "google-generative-ai"
|
||||
? getGoogleThinkingLevelMap(modelId, m.reasoning_options ?? [])
|
||||
: undefined;
|
||||
models.push({
|
||||
id: modelId,
|
||||
name: m.name || modelId,
|
||||
|
|
@ -2193,6 +2191,7 @@ async function loadModelsDevData(): Promise<Model<any>[]> {
|
|||
provider: variant.provider,
|
||||
baseUrl,
|
||||
reasoning: m.reasoning === true,
|
||||
...(thinkingLevelMap ? { thinkingLevelMap } : {}),
|
||||
input: m.modalities?.input?.includes("image") ? ["text", "image"] : ["text"],
|
||||
cost: {
|
||||
input: m.cost?.input || 0,
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue