@huggingface/inference
Version:
Typescript client for the Hugging Face Inference Providers and Inference Endpoints
160 lines (139 loc) • 4.59 kB
text/typescript
/**
* See the registered mapping of HF model ID => Nebius model ID here:
*
* https://huggingface.co/api/partners/nebius/models
*
* This is a publicly available mapping.
*
* If you want to try to run inference for a new model locally before it's registered on huggingface.co,
* you can add it to the dictionary "HARDCODED_MODEL_ID_MAPPING" in consts.ts, for dev purposes.
*
* - If you work at Nebius and want to update this mapping, please use the model mapping API we provide on huggingface.co
* - If you're a community member and want to add a new supported HF model to Nebius, please open an issue on the present repo
* and we will tag Nebius team members.
*
* Thanks!
*/
import type { FeatureExtractionOutput, TextGenerationOutput } from "@huggingface/tasks";
import type { BodyParams } from "../types.js";
import { omit } from "../utils/omit.js";
import {
BaseConversationalTask,
BaseTextGenerationTask,
TaskProviderHelper,
type FeatureExtractionTaskHelper,
type TextToImageTaskHelper,
} from "./providerHelper.js";
import { InferenceClientProviderOutputError } from "../errors.js";
import type { ChatCompletionInput } from "../../../tasks/dist/commonjs/index.js";
const NEBIUS_API_BASE_URL = "https://api.studio.nebius.ai";
interface NebiusBase64ImageGeneration {
data: Array<{
b64_json: string;
}>;
}
interface NebiusEmbeddingsResponse {
data: Array<{
embedding: number[];
}>;
}
interface NebiusTextGenerationOutput extends Omit<TextGenerationOutput, "choices"> {
choices: Array<{
text: string;
}>;
}
export class NebiusConversationalTask extends BaseConversationalTask {
constructor() {
super("nebius", NEBIUS_API_BASE_URL);
}
override preparePayload(params: BodyParams<ChatCompletionInput>): Record<string, unknown> {
const payload = super.preparePayload(params) as Record<string, unknown>;
const responseFormat = params.args.response_format;
if (responseFormat?.type === "json_schema" && responseFormat.json_schema?.schema) {
payload["guided_json"] = responseFormat.json_schema.schema;
}
return payload;
}
}
export class NebiusTextGenerationTask extends BaseTextGenerationTask {
constructor() {
super("nebius", NEBIUS_API_BASE_URL);
}
override preparePayload(params: BodyParams): Record<string, unknown> {
return {
...params.args,
model: params.model,
prompt: params.args.inputs,
};
}
override async getResponse(response: NebiusTextGenerationOutput): Promise<TextGenerationOutput> {
if (
typeof response === "object" &&
"choices" in response &&
Array.isArray(response?.choices) &&
response.choices.length > 0 &&
typeof response.choices[0]?.text === "string"
) {
return {
generated_text: response.choices[0].text,
};
}
throw new InferenceClientProviderOutputError("Received malformed response from Nebius text generation API");
}
}
export class NebiusTextToImageTask extends TaskProviderHelper implements TextToImageTaskHelper {
constructor() {
super("nebius", NEBIUS_API_BASE_URL);
}
preparePayload(params: BodyParams): Record<string, unknown> {
return {
...omit(params.args, ["inputs", "parameters"]),
...(params.args.parameters as Record<string, unknown>),
response_format: "b64_json",
prompt: params.args.inputs,
model: params.model,
};
}
makeRoute(): string {
return "v1/images/generations";
}
async getResponse(
response: NebiusBase64ImageGeneration,
url?: string,
headers?: HeadersInit,
outputType?: "url" | "blob"
): Promise<string | Blob> {
if (
typeof response === "object" &&
"data" in response &&
Array.isArray(response.data) &&
response.data.length > 0 &&
"b64_json" in response.data[0] &&
typeof response.data[0].b64_json === "string"
) {
const base64Data = response.data[0].b64_json;
if (outputType === "url") {
return `data:image/jpeg;base64,${base64Data}`;
}
return fetch(`data:image/jpeg;base64,${base64Data}`).then((res) => res.blob());
}
throw new InferenceClientProviderOutputError("Received malformed response from Nebius text-to-image API");
}
}
export class NebiusFeatureExtractionTask extends TaskProviderHelper implements FeatureExtractionTaskHelper {
constructor() {
super("nebius", NEBIUS_API_BASE_URL);
}
preparePayload(params: BodyParams): Record<string, unknown> {
return {
input: params.args.inputs,
model: params.model,
};
}
makeRoute(): string {
return "v1/embeddings";
}
async getResponse(response: NebiusEmbeddingsResponse): Promise<FeatureExtractionOutput> {
return response.data.map((item) => item.embedding);
}
}