inference-playground / src /routes /+page.server.ts
mishig's picture
mishig HF staff
handle when /api/model err
4038e22
import type { ModelEntryWithTokenizer } from "$lib/components/InferencePlayground/types";
import type { ModelEntry } from "@huggingface/hub";
import type { PageServerLoad } from "./$types";
import { env } from "$env/dynamic/private";
export const load: PageServerLoad = async ({ fetch }) => {
const apiUrl = "https://huggingface.co/api/models?pipeline_tag=text-generation&inference=warm&filter=conversational";
const HF_TOKEN = env.HF_TOKEN;
const res = await fetch(apiUrl, {
headers: {
Authorization: `Bearer ${HF_TOKEN}`,
},
});
if (!res.ok) {
console.error(`Error fetching warm models`, res.status, res.statusText);
return { models: [] };
}
const compatibleModels: ModelEntry[] = await res.json();
compatibleModels.sort((a, b) => a.id.toLowerCase().localeCompare(b.id.toLowerCase()));
const promises = compatibleModels.map(async model => {
const configUrl = `https://huggingface.co/${model.id}/raw/main/tokenizer_config.json`;
const res = await fetch(configUrl, {
headers: {
Authorization: `Bearer ${HF_TOKEN}`,
},
});
if (!res.ok) {
console.error(`Error fetching tokenizer file for ${model.id}`, res.status, res.statusText);
return null; // Ignore failed requests by returning null
}
const tokenizerConfig = await res.json();
return { ...model, tokenizerConfig } satisfies ModelEntryWithTokenizer;
});
const models: ModelEntryWithTokenizer[] = (await Promise.all(promises)).filter(model => model !== null);
return { models };
};