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https://github.com/badlogic/pi-mono.git
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2e0f175bd5
This builds the model catalog from per-provider definitions and models.dev v2 data. It eplacer `generate-models.ts` with one `defineProvider()` file per built-in provider, shared model-family rules (Claude, GPT, DeepSeek, Kimi, Google), and source adapters. models.dev is read through its v2 API. Outputs and CLI flags are unchanged.
95 lines
3.4 KiB
TypeScript
95 lines
3.4 KiB
TypeScript
import {
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DEFAULT_RADIUS_GATEWAY,
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getRadiusModelsFromConfig,
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loadRadiusGatewayConfig,
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} from "../../src/providers/radius-config.ts";
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import type { Model } from "../../src/types.ts";
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import {
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MODELS_DEV_DECISIONS_URL,
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MODELS_DEV_URL,
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type ModelsDevDecisionMetadata,
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type ModelsDevV2Catalog,
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} from "./models-dev.ts";
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import { fetchOpenRouterCatalog, type OpenRouterCatalog } from "./openrouter.ts";
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import { type AiGatewayCatalog, fetchAiGatewayCatalog } from "./vercel-ai-gateway.ts";
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export const NVIDIA_BASE_URL = "https://integrate.api.nvidia.com/v1";
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/** Everything fetched from upstream before the catalog is built. */
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export interface CatalogSources {
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modelsDev: ModelsDevV2Catalog;
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modelsDevDecisions: Record<string, ModelsDevDecisionMetadata>;
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openRouter: OpenRouterCatalog;
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aiGateway: AiGatewayCatalog;
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/** Live NVIDIA NIM ids, keyed by both the raw and the normalized id. */
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nvidiaModelIds: Map<string, string>;
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radius: Model<"pi-messages">[];
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}
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async function fetchJson<T>(url: string, label: string): Promise<T> {
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const response = await fetch(url);
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if (!response.ok) throw new Error(`${label} returned ${response.status}`);
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return (await response.json()) as T;
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}
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export function normalizeNvidiaModelId(modelId: string): string {
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return modelId.toLowerCase().replaceAll("_", ".");
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}
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async function fetchNvidiaModelIds(): Promise<Map<string, string>> {
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const data = await fetchJson<{ data?: { id: string }[] }>(`${NVIDIA_BASE_URL}/models`, "NVIDIA NIM API");
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const modelIds = new Map<string, string>();
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for (const model of data.data ?? []) {
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modelIds.set(model.id, model.id);
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modelIds.set(normalizeNvidiaModelId(model.id), model.id);
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}
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return modelIds;
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}
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async function fetchRadiusModels(): Promise<Model<"pi-messages">[]> {
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const config = await loadRadiusGatewayConfig(DEFAULT_RADIUS_GATEWAY);
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const models = getRadiusModelsFromConfig("radius", config);
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if (models.length === 0) throw new Error("Radius API returned no models");
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return models;
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}
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/**
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* Fetch every upstream source. In strict mode any failure aborts generation;
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* otherwise a failed source contributes nothing.
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*/
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export async function loadCatalogSources(strict: boolean): Promise<CatalogSources> {
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async function load<T>(label: string, fetcher: () => Promise<T>, fallback: T): Promise<T> {
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try {
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console.log(`Fetching ${label}...`);
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return await fetcher();
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} catch (error) {
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console.error(`Failed to fetch ${label}:`, error);
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if (strict) throw error;
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return fallback;
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}
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}
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const modelsDev = await load(
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"models.dev catalog",
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() => fetchJson<ModelsDevV2Catalog>(MODELS_DEV_URL, "models.dev API"),
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{},
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);
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const modelsDevDecisions = await load(
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"models.dev decision models",
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() => fetchJson<Record<string, ModelsDevDecisionMetadata>>(MODELS_DEV_DECISIONS_URL, "models.dev decision API"),
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{},
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);
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const nvidiaModelIds = modelsDev.nvidia?.models
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? await load("NVIDIA NIM models", fetchNvidiaModelIds, new Map<string, string>())
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: new Map<string, string>();
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const openRouter = await load("OpenRouter models", fetchOpenRouterCatalog, {
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chat: [],
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images: [],
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classifiers: [],
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});
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if (strict && openRouter.images.length === 0) throw new Error("OpenRouter API returned no usable image models");
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const aiGateway = await load("Vercel AI Gateway models", fetchAiGatewayCatalog, { chat: [], classifiers: [] });
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const radius = await load("Radius models", fetchRadiusModels, []);
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return { modelsDev, modelsDevDecisions, openRouter, aiGateway, nvidiaModelIds, radius };
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}
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