feat: add scaleway inference provider (#1674)

Hi 🤗 
Register [Scaleway](https://www.scaleway.com/en/) as inference provider

Test passing 
```
> vitest run --config vitest.config.mts -t Scaleway


 RUN  v0.34.6 /Users/gnoale/git/huggingface.js/packages/inference

stderr | unknown test
Set HF_TOKEN in the env to run the tests for better rate limits

 ↓ src/vendor/fetch-event-source/parse.spec.ts (17) [skipped]
 ✓ test/InferenceClient.spec.ts (112) 6116ms

 Test Files  1 passed | 1 skipped (2)
      Tests  5 passed | 124 skipped (129)
   Start at  14:03:55
   Duration  6.58s (transform 253ms, setup 18ms, collect 327ms, tests 6.12s, environment 0ms, prepare 82ms)
   ```

---------

Co-authored-by: SBrandeis <simon@huggingface.co>

Author: Gnoale

packages/inference/README.md

@@ -58,6 +58,7 @@ Currently, we support the following providers:
 - [OVHcloud](https://endpoints.ai.cloud.ovh.net/)
 - [Replicate](https://replicate.com)
 - [Sambanova](https://sambanova.ai)
+- [Scaleway](https://www.scaleway.com/en/generative-apis/)
 - [Together](https://together.xyz)
 - [Blackforestlabs](https://blackforestlabs.ai)
 - [Cohere](https://cohere.com)
@@ -92,6 +93,7 @@ Only a subset of models are supported when requesting third-party providers. You
 - [OVHcloud supported models](https://huggingface.co/api/partners/ovhcloud/models)
 - [Replicate supported models](https://huggingface.co/api/partners/replicate/models)
 - [Sambanova supported models](https://huggingface.co/api/partners/sambanova/models)
+- [Scaleway supported models](https://huggingface.co/api/partners/scaleway/models)
 - [Together supported models](https://huggingface.co/api/partners/together/models)
 - [Cohere supported models](https://huggingface.co/api/partners/cohere/models)
 - [Cerebras supported models](https://huggingface.co/api/partners/cerebras/models)

packages/inference/src/lib/getProviderHelper.ts

@@ -47,6 +47,7 @@ import type {
 } from "../providers/providerHelper.js";
 import * as Replicate from "../providers/replicate.js";
 import * as Sambanova from "../providers/sambanova.js";
+import * as Scaleway from "../providers/scaleway.js";
 import * as Together from "../providers/together.js";
 import type { InferenceProvider, InferenceProviderOrPolicy, InferenceTask } from "../types.js";
 import { InferenceClientInputError } from "../errors.js";
@@ -148,6 +149,11 @@ export const PROVIDERS: Record<InferenceProvider, Partial<Record<InferenceTask,
 		conversational: new Sambanova.SambanovaConversationalTask(),
 		"feature-extraction": new Sambanova.SambanovaFeatureExtractionTask(),
 	},
+	scaleway: {
+		conversational: new Scaleway.ScalewayConversationalTask(),
+		"text-generation": new Scaleway.ScalewayTextGenerationTask(),
+		"feature-extraction": new Scaleway.ScalewayFeatureExtractionTask(),
+	},
 	together: {
 		"text-to-image": new Together.TogetherTextToImageTask(),
 		conversational: new Together.TogetherConversationalTask(),

packages/inference/src/providers/consts.ts

@@ -34,5 +34,6 @@ export const HARDCODED_MODEL_INFERENCE_MAPPING: Record<
 	ovhcloud: {},
 	replicate: {},
 	sambanova: {},
+	scaleway: {},
 	together: {},
 };

packages/inference/src/providers/scaleway.ts

@@ -0,0 +1,95 @@
+/**
+ * See the registered mapping of HF model ID => Scaleway model ID here:
+ *
+ * https://huggingface.co/api/partners/scaleway/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 Scaleway 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 Scaleway, please open an issue on the present repo
+ * and we will tag Scaleway team members.
+ *
+ * Thanks!
+ */
+import type { FeatureExtractionOutput, TextGenerationOutput } from "@huggingface/tasks";
+import type { BodyParams } from "../types.js";
+import { InferenceClientProviderOutputError } from "../errors.js";
+
+import type { FeatureExtractionTaskHelper } from "./providerHelper.js";
+import { BaseConversationalTask, TaskProviderHelper, BaseTextGenerationTask } from "./providerHelper.js";
+
+const SCALEWAY_API_BASE_URL = "https://api.scaleway.ai";
+
+interface ScalewayEmbeddingsResponse {
+	data: Array<{
+		embedding: number[];
+	}>;
+}
+
+export class ScalewayConversationalTask extends BaseConversationalTask {
+	constructor() {
+		super("scaleway", SCALEWAY_API_BASE_URL);
+	}
+}
+
+export class ScalewayTextGenerationTask extends BaseTextGenerationTask {
+	constructor() {
+		super("scaleway", SCALEWAY_API_BASE_URL);
+	}
+
+	override preparePayload(params: BodyParams): Record<string, unknown> {
+		return {
+			model: params.model,
+			...params.args,
+			prompt: params.args.inputs,
+		};
+	}
+
+	override async getResponse(response: unknown): Promise<TextGenerationOutput> {
+		if (
+			typeof response === "object" &&
+			response !== null &&
+			"choices" in response &&
+			Array.isArray(response.choices) &&
+			response.choices.length > 0
+		) {
+			const completion: unknown = response.choices[0];
+			if (
+				typeof completion === "object" &&
+				!!completion &&
+				"text" in completion &&
+				completion.text &&
+				typeof completion.text === "string"
+			) {
+				return {
+					generated_text: completion.text,
+				};
+			}
+		}
+		throw new InferenceClientProviderOutputError("Received malformed response from Scaleway text generation API");
+	}
+}
+
+export class ScalewayFeatureExtractionTask extends TaskProviderHelper implements FeatureExtractionTaskHelper {
+	constructor() {
+		super("scaleway", SCALEWAY_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: ScalewayEmbeddingsResponse): Promise<FeatureExtractionOutput> {
+		return response.data.map((item) => item.embedding);
+	}
+}

packages/inference/src/types.ts

@@ -61,6 +61,7 @@ export const INFERENCE_PROVIDERS = [
 	"ovhcloud",
 	"replicate",
 	"sambanova",
+	"scaleway",
 	"together",
 ] as const;
 

packages/inference/test/InferenceClient.spec.ts

@@ -1516,6 +1516,116 @@ describe.skip("InferenceClient", () => {
 		TIMEOUT
 	);
 
+	describe.concurrent(
+		"Scaleway",
+		() => {
+			const client = new InferenceClient(env.HF_SCALEWAY_KEY ?? "dummy");
+
+			HARDCODED_MODEL_INFERENCE_MAPPING.scaleway = {
+				"meta-llama/Llama-3.1-8B-Instruct": {
+					provider: "scaleway",
+					hfModelId: "meta-llama/Llama-3.1-8B-Instruct",
+					providerId: "llama-3.1-8b-instruct",
+					status: "live",
+					task: "conversational",
+				},
+				"BAAI/bge-multilingual-gemma2": {
+					provider: "scaleway",
+					hfModelId: "BAAI/bge-multilingual-gemma2",
+					providerId: "bge-multilingual-gemma2",
+					task: "feature-extraction",
+					status: "live",
+				},
+				"google/gemma-3-27b-it": {
+					provider: "scaleway",
+					hfModelId: "google/gemma-3-27b-it",
+					providerId: "gemma-3-27b-it",
+					task: "conversational",
+					status: "live",
+				},
+			};
+
+			it("chatCompletion", async () => {
+				const res = await client.chatCompletion({
+					model: "meta-llama/Llama-3.1-8B-Instruct",
+					provider: "scaleway",
+					messages: [{ role: "user", content: "Complete this sentence with words, one plus one is equal " }],
+					tool_choice: "none",
+				});
+				if (res.choices && res.choices.length > 0) {
+					const completion = res.choices[0].message?.content;
+					expect(completion).toMatch(/(to )?(two|2)/i);
+				}
+			});
+
+			it("chatCompletion stream", async () => {
+				const stream = client.chatCompletionStream({
+					model: "meta-llama/Llama-3.1-8B-Instruct",
+					provider: "scaleway",
+					messages: [{ role: "system", 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).toMatch(/(two|2)/i);
+			});
+
+			it("chatCompletion multimodal", async () => {
+				const res = await client.chatCompletion({
+					model: "google/gemma-3-27b-it",
+					provider: "scaleway",
+					messages: [
+						{
+							role: "user",
+							content: [
+								{
+									type: "image_url",
+									image_url: {
+										url: "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg",
+									},
+								},
+								{ type: "text", text: "What is this?" },
+							],
+						},
+					],
+				});
+				expect(res.choices).toBeDefined();
+				expect(res.choices?.length).toBeGreaterThan(0);
+				expect(res.choices?.[0].message?.content).toContain("Statue of Liberty");
+			});
+
+			it("textGeneration", async () => {
+				const res = await client.textGeneration({
+					model: "meta-llama/Llama-3.1-8B-Instruct",
+					provider: "scaleway",
+					inputs: "Once upon a time,",
+					temperature: 0,
+					max_tokens: 19,
+				});
+
+				expect(res).toMatchObject({
+					generated_text:
+						" in a small village nestled in the rolling hills of the countryside, there lived a young girl named",
+				});
+			});
+
+			it("featureExtraction", async () => {
+				const res = await client.featureExtraction({
+					model: "BAAI/bge-multilingual-gemma2",
+					provider: "scaleway",
+					inputs: "That is a happy person",
+				});
+
+				expect(res).toBeInstanceOf(Array);
+				expect(res[0]).toEqual(expect.arrayContaining([expect.any(Number)]));
+			});
+		},
+		TIMEOUT
+	);
+
 	describe.concurrent("3rd party providers", () => {
 		it("chatCompletion - fails with unsupported model", async () => {
 			expect(