draft: add hyperbolic support

.github/workflows/test.yml

@@ -41,14 +41,15 @@ jobs:
         run: VCR_MODE=playback pnpm --filter ...[${{ steps.since.outputs.SINCE }}] test
         env:
           HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          HF_BLACK_FOREST_LABS_KEY: dummy
           HF_FAL_KEY: dummy
+          HF_FIREWORKS_KEY: dummy
+          HF_HYPERBOLIC_KEY: dummy
           HF_NEBIUS_KEY: dummy
+          HF_NOVITA_KEY: dummy
           HF_REPLICATE_KEY: dummy
           HF_SAMBANOVA_KEY: dummy
           HF_TOGETHER_KEY: dummy
-          HF_NOVITA_KEY: dummy
-          HF_FIREWORKS_KEY: dummy
-          HF_BLACK_FOREST_LABS_KEY: dummy
 
   browser:
     runs-on: ubuntu-latest
@@ -85,14 +86,15 @@ jobs:
         run: VCR_MODE=playback pnpm --filter ...[${{ steps.since.outputs.SINCE }}] test:browser
         env:
           HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          HF_BLACK_FOREST_LABS_KEY: dummy
           HF_FAL_KEY: dummy
+          HF_FIREWORKS_KEY: dummy
+          HF_HYPERBOLIC_KEY: dummy
           HF_NEBIUS_KEY: dummy
+          HF_NOVITA_KEY: dummy
           HF_REPLICATE_KEY: dummy
           HF_SAMBANOVA_KEY: dummy
           HF_TOGETHER_KEY: dummy
-          HF_NOVITA_KEY: dummy
-          HF_FIREWORKS_KEY: dummy
-          HF_BLACK_FOREST_LABS_KEY: dummy
 
   e2e:
     runs-on: ubuntu-latest
@@ -156,11 +158,12 @@ jobs:
         env:
           NPM_CONFIG_REGISTRY: http://localhost:4874/
           HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          HF_BLACK_FOREST_LABS_KEY: dummy
           HF_FAL_KEY: dummy
+          HF_FIREWORKS_KEY: dummy
+          HF_HYPERBOLIC_KEY: dummy
           HF_NEBIUS_KEY: dummy
+          HF_NOVITA_KEY: dummy
           HF_REPLICATE_KEY: dummy
           HF_SAMBANOVA_KEY: dummy
           HF_TOGETHER_KEY: dummy
-          HF_NOVITA_KEY: dummy
-          HF_FIREWORKS_KEY: dummy
-          HF_BLACK_FOREST_LABS_KEY: dummy

packages/inference/README.md

@@ -49,6 +49,7 @@ You can send inference requests to third-party providers with the inference clie
 Currently, we support the following providers:
 - [Fal.ai](https://fal.ai)
 - [Fireworks AI](https://fireworks.ai)
+- [Hyperbolic](https://hyperbolic.xyz)
 - [Nebius](https://studio.nebius.ai)
 - [Novita](https://novita.ai/?utm_source=github_huggingface&utm_medium=github_readme&utm_campaign=link)
 - [Replicate](https://replicate.com)
@@ -74,6 +75,7 @@ When authenticated with a third-party provider key, the request is made directly
 Only a subset of models are supported when requesting third-party providers. You can check the list of supported models per pipeline tasks here:
 - [Fal.ai supported models](https://huggingface.co/api/partners/fal-ai/models)
 - [Fireworks AI supported models](https://huggingface.co/api/partners/fireworks-ai/models)
+- [Hyperbolic supported models](https://huggingface.co/api/partners/hyperbolic/models)
 - [Nebius supported models](https://huggingface.co/api/partners/nebius/models)
 - [Replicate supported models](https://huggingface.co/api/partners/replicate/models)
 - [Sambanova supported models](https://huggingface.co/api/partners/sambanova/models)

packages/inference/src/lib/makeRequestOptions.ts

@@ -6,6 +6,7 @@ import { SAMBANOVA_API_BASE_URL } from "../providers/sambanova";
 import { TOGETHER_API_BASE_URL } from "../providers/together";
 import { NOVITA_API_BASE_URL } from "../providers/novita";
 import { FIREWORKS_AI_API_BASE_URL } from "../providers/fireworks-ai";
+import { HYPERBOLIC_API_BASE_URL } from "../providers/hyperbolic";
 import { BLACKFORESTLABS_AI_API_BASE_URL } from "../providers/black-forest-labs";
 import type { InferenceProvider } from "../types";
 import type { InferenceTask, Options, RequestArgs } from "../types";
@@ -132,7 +133,11 @@ export async function makeRequestOptions(
 			? args.data
 			: JSON.stringify({
 					...otherArgs,
-					...(chatCompletion || provider === "together" || provider === "nebius" ? { model } : undefined),
+					...(taskHint === "text-to-image" && provider === "hyperbolic"
+						? { model_name: model }
+						: chatCompletion || provider === "together" || provider === "nebius" || provider === "hyperbolic"
+						  ? { model }
+						  : undefined),
 			  }),
 		...(credentials ? { credentials } : undefined),
 		signal: options?.signal,
@@ -229,6 +234,16 @@ function makeUrl(params: {
 			}
 			return baseUrl;
 		}
+		case "hyperbolic": {
+			const baseUrl = shouldProxy
+				? HF_HUB_INFERENCE_PROXY_TEMPLATE.replace("{{PROVIDER}}", params.provider)
+				: HYPERBOLIC_API_BASE_URL;
+
+			if (params.taskHint === "text-to-image") {
+				return `${baseUrl}/v1/images/generations`;
+			}
+			return `${baseUrl}/v1/chat/completions`;
+		}
 		case "novita": {
 			const baseUrl = shouldProxy
 				? HF_HUB_INFERENCE_PROXY_TEMPLATE.replace("{{PROVIDER}}", params.provider)

packages/inference/src/providers/consts.ts

@@ -20,6 +20,7 @@ export const HARDCODED_MODEL_ID_MAPPING: Record<InferenceProvider, Record<ModelI
 	"fal-ai": {},
 	"fireworks-ai": {},
 	"hf-inference": {},
+	hyperbolic: {},
 	nebius: {},
 	replicate: {},
 	sambanova: {},

packages/inference/src/providers/hyperbolic.ts

@@ -0,0 +1,18 @@
+export const HYPERBOLIC_API_BASE_URL = "https://api.hyperbolic.xyz";
+
+/**
+ * See the registered mapping of HF model ID => Hyperbolic model ID here:
+ *
+ * https://huggingface.co/api/partners/hyperbolic/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 Hyperbolic 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 Hyperbolic, please open an issue on the present repo
+ * and we will tag Hyperbolic team members.
+ *
+ * Thanks!
+ */

packages/inference/src/tasks/cv/textToImage.ts

@@ -15,6 +15,10 @@ interface Base64ImageGeneration {
 interface OutputUrlImageGeneration {
 	output: string[];
 }
+interface HyperbolicTextToImageOutput {
+	images: Array<{ image: string }>;
+}
+
 interface BlackForestLabsResponse {
 	id: string;
 	polling_url: string;
@@ -50,7 +54,11 @@ export async function textToImage(args: TextToImageArgs, options?: Options): Pro
 					prompt: args.inputs,
 			  };
 	const res = await request<
-		TextToImageOutput | Base64ImageGeneration | OutputUrlImageGeneration | BlackForestLabsResponse
+		| TextToImageOutput
+		| Base64ImageGeneration
+		| OutputUrlImageGeneration
+		| BlackForestLabsResponse
+		| HyperbolicTextToImageOutput
 	>(payload, {
 		...options,
 		taskHint: "text-to-image",
@@ -64,6 +72,17 @@ export async function textToImage(args: TextToImageArgs, options?: Options): Pro
 			const image = await fetch(res.images[0].url);
 			return await image.blob();
 		}
+		if (
+			args.provider === "hyperbolic" &&
+			"images" in res &&
+			Array.isArray(res.images) &&
+			res.images[0] &&
+			typeof res.images[0].image === "string"
+		) {
+			const base64Response = await fetch(`data:image/jpeg;base64,${res.images[0].image}`);
+			const blob = await base64Response.blob();
+			return blob;
+		}
 		if ("data" in res && Array.isArray(res.data) && res.data[0].b64_json) {
 			const base64Data = res.data[0].b64_json;
 			const base64Response = await fetch(`data:image/jpeg;base64,${base64Data}`);

packages/inference/src/tasks/nlp/textGeneration.ts

@@ -8,6 +8,7 @@ import { InferenceOutputError } from "../../lib/InferenceOutputError";
 import type { BaseArgs, Options } from "../../types";
 import { toArray } from "../../utils/toArray";
 import { request } from "../custom/request";
+import { omit } from "../../utils/omit";
 
 export type { TextGenerationInput, TextGenerationOutput };
 
@@ -21,6 +22,12 @@ interface TogeteherTextCompletionOutput extends Omit<ChatCompletionOutput, "choi
 	}>;
 }
 
+interface HyperbolicTextCompletionOutput extends Omit<ChatCompletionOutput, "choices"> {
+	choices: Array<{
+		message: { content: string };
+	}>;
+}
+
 /**
  * Use to continue text from a prompt. This is a very generic task. Recommended model: gpt2 (it’s a simple model, but fun to play with).
  */
@@ -43,6 +50,30 @@ export async function textGeneration(
 		return {
 			generated_text: completion.text,
 		};
+	} else if (args.provider === "hyperbolic") {
+		const payload = {
+			messages: [{ content: args.inputs, role: "user" }],
+			...(args.parameters
+				? {
+						max_tokens: args.parameters.max_new_tokens,
+						...omit(args.parameters, "max_new_tokens"),
+				  }
+				: undefined),
+			...omit(args, ["inputs", "parameters"]),
+		};
+		const raw = await request<HyperbolicTextCompletionOutput>(payload, {
+			...options,
+			taskHint: "text-generation",
+		});
+		const isValidOutput =
+			typeof raw === "object" && "choices" in raw && Array.isArray(raw?.choices) && typeof raw?.model === "string";
+		if (!isValidOutput) {
+			throw new InferenceOutputError("Expected ChatCompletionOutput");
+		}
+		const completion = raw.choices[0];
+		return {
+			generated_text: completion.message.content,
+		};
 	} else {
 		const res = toArray(
 			await request<TextGenerationOutput | TextGenerationOutput[]>(args, {

packages/inference/src/types.ts

@@ -33,6 +33,7 @@ export const INFERENCE_PROVIDERS = [
 	"fal-ai",
 	"fireworks-ai",
 	"hf-inference",
+	"hyperbolic",
 	"nebius",
 	"novita",
 	"replicate",

packages/inference/test/HfInference.spec.ts

@@ -2,7 +2,8 @@ import { assert, describe, expect, it } from "vitest";
 
 import type { ChatCompletionStreamOutput } from "@huggingface/tasks";
 
-import { chatCompletion, HfInference, textToImage } from "../src";
+import type { TextToImageArgs } from "../src";
+import { chatCompletion, chatCompletionStream, HfInference, textGeneration, textToImage } from "../src";
 import { textToVideo } from "../src/tasks/cv/textToVideo";
 import { readTestFile } from "./test-files";
 import "./vcr";
@@ -1176,6 +1177,85 @@ describe.concurrent("HfInference", () => {
 		TIMEOUT
 	);
 
+	describe.concurrent(
+		"Hyperbolic",
+		() => {
+			HARDCODED_MODEL_ID_MAPPING.hyperbolic = {
+				"meta-llama/Llama-3.2-3B-Instruct": "meta-llama/Llama-3.2-3B-Instruct",
+				"meta-llama/Llama-3.3-70B-Instruct": "meta-llama/Llama-3.3-70B-Instruct",
+				"stabilityai/stable-diffusion-2": "SD2",
+				"meta-llama/Llama-3.1-405B": "meta-llama/Meta-Llama-3.1-405B-Instruct",
+			};
+
+			it("chatCompletion - hyperbolic", async () => {
+				const res = await chatCompletion({
+					accessToken: env.HF_HYPERBOLIC_KEY,
+					model: "meta-llama/Llama-3.2-3B-Instruct",
+					provider: "hyperbolic",
+					messages: [{ role: "user", content: "Complete this sentence with words, one plus one is equal " }],
+					temperature: 0.1,
+				});
+
+				expect(res).toBeDefined();
+				expect(res.choices).toBeDefined();
+				expect(res.choices?.length).toBeGreaterThan(0);
+
+				if (res.choices && res.choices.length > 0) {
+					const completion = res.choices[0].message?.content;
+					expect(completion).toBeDefined();
+					expect(typeof completion).toBe("string");
+					expect(completion).toContain("two");
+				}
+			});
+
+			it("chatCompletion stream", async () => {
+				const stream = chatCompletionStream({
+					accessToken: env.HF_HYPERBOLIC_KEY,
+					model: "meta-llama/Llama-3.3-70B-Instruct",
+					provider: "hyperbolic",
+					messages: [{ role: "user", content: "Complete the equation 1 + 1 = , just the answer" }],
+				}) as AsyncGenerator<ChatCompletionStreamOutput>;
+				let out = "";
+				for await (const chunk of stream) {
+					if (chunk.choices && chunk.choices.length > 0) {
+						out += chunk.choices[0].delta.content;
+					}
+				}
+				expect(out).toContain("2");
+			});
+
+			it("textToImage", async () => {
+				const res = await textToImage({
+					accessToken: env.HF_HYPERBOLIC_KEY,
+					model: "stabilityai/stable-diffusion-2",
+					provider: "hyperbolic",
+					inputs: "award winning high resolution photo of a giant tortoise",
+					parameters: {
+						height: 128,
+						width: 128,
+					},
+				} satisfies TextToImageArgs);
+				expect(res).toBeInstanceOf(Blob);
+			});
+
+			it("textGeneration", async () => {
+				const res = await textGeneration({
+					accessToken: env.HF_HYPERBOLIC_KEY,
+					model: "meta-llama/Llama-3.1-405B",
+					provider: "hyperbolic",
+					inputs: "Paris is",
+					parameters: {
+						temperature: 0,
+						top_p: 0.01,
+						max_new_tokens: 10,
+					},
+				});
+				expect(res).toMatchObject({ generated_text: "...the capital and most populous city of France," });
+			});
+		},
+		TIMEOUT
+	);
+
 	describe.concurrent(
 		"Novita",
 		() => {