mirror of
https://github.com/diegosouzapw/OmniRoute.git
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9be4fd0a0e
Obrigado! Validado em lote combinado (8 PRs, release/v3.8.51): - Follow-up correto de #10590/#10591 — omite modelos Gemini Live-only da descoberta dinâmica, preserva chat para modelos híbridos. - Teste focado atualizado: `tests/unit/gemini-models-parser.test.ts` — 6/6 verde. - Gates estáticos do lote OK (typecheck, lint sem regressão, complexity, cognitive, file-size, changelog-integrity).
106 lines
3.8 KiB
TypeScript
106 lines
3.8 KiB
TypeScript
/**
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* Parses the Google Generative Language `v1beta/models` listing into discovery models.
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*
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* Each model's `supportedGenerationMethods` is mapped to OmniRoute endpoints:
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* - generateContent / generateAnswer → "chat"
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* - predict → "images" (Imagen image generation)
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* - predictLongRunning → "videos" (Veo video generation)
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* - embedContent → "embeddings"
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* - bidiGenerateContent → ignored (Gemini Live is not proxied)
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*
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* Model-id heuristics refine the long-running bucket because Google exposes both
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* Imagen and Veo via long-running methods on the same endpoint:
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* - id contains "veo" → ensure "videos"
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* - id contains "imagen" → force "images" (never "videos")
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*
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* Note: `gemini-*-image` models (e.g. gemini-3-pro-image) generate images via the
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* regular `generateContent` path, so they stay "chat" (image output is a chat
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* modality) and are intentionally NOT reclassified as "images".
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*
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* This is shared by the `gemini` discovery config and the `vertex` /
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* `vertex-partner` (incl. Vertex AI Express key) discovery branches, so every
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* supported model the account can access — chat, image, video and embeddings —
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* surfaces dynamically instead of being limited to the small static registry.
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*/
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const METHOD_TO_ENDPOINT: Record<string, string> = {
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generateContent: "chat",
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embedContent: "embeddings",
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predict: "images",
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predictLongRunning: "videos",
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generateAnswer: "chat",
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};
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const IGNORED_METHODS = new Set([
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"countTokens",
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"countTextTokens",
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"createCachedContent",
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"batchGenerateContent",
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"asyncBatchEmbedContent",
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"bidiGenerateContent",
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]);
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const RETIRED_GEMINI_MODEL_IDS = new Set(["gemini-3.5-flash"]);
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export interface GeminiDiscoveryModel {
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id: string;
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name: string;
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supportedEndpoints: string[];
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inputTokenLimit?: number;
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outputTokenLimit?: number;
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description?: string;
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supportsThinking?: boolean;
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[key: string]: unknown;
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}
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export function parseGeminiModelsList(data: any): GeminiDiscoveryModel[] {
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return (data?.models || [])
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.map((m: Record<string, unknown>) => {
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const methods: string[] = Array.isArray(m.supportedGenerationMethods)
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? (m.supportedGenerationMethods as string[])
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: [];
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const endpoints = new Set<string>(
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methods
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.filter((method) => !IGNORED_METHODS.has(method))
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.map((method) => METHOD_TO_ENDPOINT[method] || "chat")
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);
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const id = ((m.name as string) || (m.id as string) || "").replace(/^models\//, "");
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const lowerId = id.toLowerCase();
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// Google exposes Imagen (image) and Veo (video) via long-running methods; the
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// method alone can't always distinguish them, so refine by model id.
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if (lowerId.includes("veo")) {
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endpoints.add("videos");
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}
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if (lowerId.includes("imagen")) {
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endpoints.delete("videos");
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endpoints.add("images");
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}
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if (
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endpoints.size === 0 &&
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methods.length > 0 &&
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methods.every((method) => IGNORED_METHODS.has(method))
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) {
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return null;
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}
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if (endpoints.size === 0) endpoints.add("chat");
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return {
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...m,
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id,
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name: (m.displayName as string) || id,
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supportedEndpoints: [...endpoints],
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...(typeof m.inputTokenLimit === "number" ? { inputTokenLimit: m.inputTokenLimit } : {}),
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...(typeof m.outputTokenLimit === "number" ? { outputTokenLimit: m.outputTokenLimit } : {}),
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...(typeof m.description === "string" ? { description: m.description } : {}),
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...(m.thinking === true ? { supportsThinking: true } : {}),
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} as GeminiDiscoveryModel;
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})
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.filter(
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(model: GeminiDiscoveryModel | null): model is GeminiDiscoveryModel =>
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Boolean(model) && !RETIRED_GEMINI_MODEL_IDS.has(model.id)
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);
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}
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