[inference provider] Add wavespeed.ai as an inference provider #1424

arabot777 · 2025-05-05T02:28:49Z

What’s in this PR
WaveSpeedAI is a high-performance AI image and video generation service platform, offering industry-leading generation speeds. Now, want to be listed as an Inference Provider on the Hugging Face Hub

The JS Client Integration was completed based on the inference-providers help documentation and passed the test. I am submitting the pr now and look forward to further communication with you

Test

pnpm --filter @huggingface/inference test "test/InferenceClient.spec.ts" -t "^Wavespeed AI"

> @huggingface/[email protected] test /Users/shanliu/work/huggingface.js/packages/inference
> vitest run --config vitest.config.mts "test/InferenceClient.spec.ts"


 RUN  v0.34.6 /Users/shanliu/work/huggingface.js/packages/inference

 ✓ test/InferenceClient.spec.ts (104) 198160ms
   ✓ InferenceClient (104) 198160ms
     ✓ backward compatibility (1)
       ✓ works with old HfInference name
     ↓ HF Inference (49) [skipped]
       ↓ throws error if model does not exist [skipped]
       ↓ fillMask [skipped]
       ↓ works without model [skipped]
       ↓ summarization [skipped]
       ↓ questionAnswering [skipped]
       ↓ tableQuestionAnswering [skipped]
       ↓ documentQuestionAnswering [skipped]
       ↓ documentQuestionAnswering with non-array output [skipped]
       ↓ visualQuestionAnswering [skipped]
       ↓ textClassification [skipped]
       ↓ textGeneration - gpt2 [skipped]
       ↓ textGeneration - openai-community/gpt2 [skipped]
       ↓ textGenerationStream - meta-llama/Llama-3.2-3B [skipped]
       ↓ textGenerationStream - catch error [skipped]
       ↓ textGenerationStream - Abort [skipped]
       ↓ tokenClassification [skipped]
       ↓ translation [skipped]
       ↓ zeroShotClassification [skipped]
       ↓ sentenceSimilarity [skipped]
       ↓ FeatureExtraction [skipped]
       ↓ FeatureExtraction - auto-compatibility sentence similarity [skipped]
       ↓ FeatureExtraction - facebook/bart-base [skipped]
       ↓ FeatureExtraction - facebook/bart-base, list input [skipped]
       ↓ automaticSpeechRecognition [skipped]
       ↓ audioClassification [skipped]
       ↓ audioToAudio [skipped]
       ↓ textToSpeech [skipped]
       ↓ imageClassification [skipped]
       ↓ zeroShotImageClassification [skipped]
       ↓ objectDetection [skipped]
       ↓ imageSegmentation [skipped]
       ↓ imageToImage [skipped]
       ↓ imageToImage blob data [skipped]
       ↓ textToImage [skipped]
       ↓ textToImage with parameters [skipped]
       ↓ imageToText [skipped]
       ↓ request - openai-community/gpt2 [skipped]
       ↓ tabularRegression [skipped]
       ↓ tabularClassification [skipped]
       ↓ endpoint - makes request to specified endpoint [skipped]
       ↓ endpoint - makes request to specified endpoint - alternative syntax [skipped]
       ↓ chatCompletion modelId - OpenAI Specs [skipped]
       ↓ chatCompletionStream modelId - OpenAI Specs [skipped]
       ↓ chatCompletionStream modelId Fail - OpenAI Specs [skipped]
       ↓ chatCompletion - OpenAI Specs [skipped]
       ↓ chatCompletionStream - OpenAI Specs [skipped]
       ↓ custom mistral - OpenAI Specs [skipped]
       ↓ custom openai - OpenAI Specs [skipped]
       ↓ OpenAI client side routing - model should have provider as prefix [skipped]
     ↓ Fal AI (4) [skipped]
       ↓ textToImage - black-forest-labs/FLUX.1-schnell [skipped]
       ↓ textToImage - SD LoRAs [skipped]
       ↓ textToImage - Flux LoRAs [skipped]
       ↓ automaticSpeechRecognition - openai/whisper-large-v3 [skipped]
     ↓ Featherless (3) [skipped]
       ↓ chatCompletion [skipped]
       ↓ chatCompletion stream [skipped]
       ↓ textGeneration [skipped]
     ↓ Replicate (10) [skipped]
       ↓ textToImage canonical - black-forest-labs/FLUX.1-schnell [skipped]
       ↓ textToImage canonical - black-forest-labs/FLUX.1-dev [skipped]
       ↓ textToImage canonical - stabilityai/stable-diffusion-3.5-large-turbo [skipped]
       ↓ textToImage versioned - ByteDance/SDXL-Lightning [skipped]
       ↓ textToImage versioned - ByteDance/Hyper-SD [skipped]
       ↓ textToImage versioned - playgroundai/playground-v2.5-1024px-aesthetic [skipped]
       ↓ textToImage versioned - stabilityai/stable-diffusion-xl-base-1.0 [skipped]
       ↓ textToSpeech versioned [skipped]
       ↓ textToSpeech OuteTTS -  usually Cold [skipped]
       ↓ textToSpeech Kokoro [skipped]
     ↓ SambaNova (3) [skipped]
       ↓ chatCompletion [skipped]
       ↓ chatCompletion stream [skipped]
       ↓ featureExtraction [skipped]
     ↓ Together (4) [skipped]
       ↓ chatCompletion [skipped]
       ↓ chatCompletion stream [skipped]
       ↓ textToImage [skipped]
       ↓ textGeneration [skipped]
     ↓ Nebius (3) [skipped]
       ↓ chatCompletion [skipped]
       ↓ chatCompletion stream [skipped]
       ↓ textToImage [skipped]
     ↓ 3rd party providers (1) [skipped]
       ↓ chatCompletion - fails with unsupported model [skipped]
     ↓ Fireworks (2) [skipped]
       ↓ chatCompletion [skipped]
       ↓ chatCompletion stream [skipped]
     ↓ Hyperbolic (4) [skipped]
       ↓ chatCompletion - hyperbolic [skipped]
       ↓ chatCompletion stream [skipped]
       ↓ textToImage [skipped]
       ↓ textGeneration [skipped]
     ↓ Novita (2) [skipped]
       ↓ chatCompletion [skipped]
       ↓ chatCompletion stream [skipped]
     ↓ Black Forest Labs (2) [skipped]
       ↓ textToImage [skipped]
       ↓ textToImage URL [skipped]
     ↓ Cohere (2) [skipped]
       ↓ chatCompletion [skipped]
       ↓ chatCompletion stream [skipped]
     ↓ Cerebras (2) [skipped]
       ↓ chatCompletion [skipped]
       ↓ chatCompletion stream [skipped]
     ↓ Nscale (3) [skipped]
       ↓ chatCompletion [skipped]
       ↓ chatCompletion stream [skipped]
       ↓ textToImage [skipped]
     ↓ Groq (2) [skipped]
       ↓ chatCompletion [skipped]
       ↓ chatCompletion stream [skipped]
     ↓ OVHcloud (4) [skipped]
       ↓ chatCompletion [skipped]
       ↓ chatCompletion stream [skipped]
       ↓ textGeneration [skipped]
       ↓ textGeneration stream [skipped]
     ✓ Wavespeed AI (5) 89033ms
       ✓ textToImage - wavespeed-ai/flux-schnell 89032ms
       ✓ textToImage - wavespeed-ai/flux-dev-lora 12369ms
       ✓ textToImage - wavespeed-ai/flux-dev-lora-ultra-fast 17936ms
       ✓ textToVideo - wavespeed-ai/wan-2.1/t2v-480p 79507ms
       ✓ imageToImage - wavespeed-ai/hidream-e1-full 74481ms

 Test Files  1 passed (1)
      Tests  5 passed | 103 skipped (108)
   Start at  14:33:17
   Duration  89.62s (transform 315ms, setup 14ms, collect 368ms, tests 89.03s, environment 0ms, prepare 74ms)

SBrandeis

Hello, thank you for your contribution
The code is of great quality overall - I left a few comments regarding our code style.
Please make sure the client can be used to query your API for all supported tasks, and that the payload are matching your API.
Thanks again!

SBrandeis · 2025-05-19T14:36:21Z

packages/inference/README.md

+- [HF Inference API (serverless)](https://huggingface.co/models?inference=warm&sort=trending)



Suggested change

- [HF Inference API (serverless)](https://huggingface.co/models?inference=warm&sort=trending)

has deleted

SBrandeis · 2025-05-19T14:41:26Z

packages/inference/test/InferenceClient.spec.ts

+					hfModelId: "wavespeed-ai/wan-2.1/i2v-480p",
+					providerId: "wavespeed-ai/wan-2.1/i2v-480p",
+					status: "live",
+					task: "image-to-video",


this task is not supported in the client code - let's remove it for now

has deleted

SBrandeis · 2025-05-19T14:43:28Z

packages/inference/src/providers/wavespeed-ai.ts

+import { InferenceOutputError } from "../lib/InferenceOutputError";
+import { ImageToImageArgs } from "../tasks";
+import type { BodyParams, HeaderParams, RequestArgs, UrlParams } from "../types";
+import { delay } from "../utils/delay";
+import { omit } from "../utils/omit";
+import { base64FromBytes } from "../utils/base64FromBytes";
+import {
+	TaskProviderHelper,
+	TextToImageTaskHelper,
+	TextToVideoTaskHelper,
+	ImageToImageTaskHelper,
+} from "./providerHelper";
+


We use import type when the import is only used as a type

Suggested change

import { InferenceOutputError } from "../lib/InferenceOutputError";

import { ImageToImageArgs } from "../tasks";

import type { BodyParams, HeaderParams, RequestArgs, UrlParams } from "../types";

import { delay } from "../utils/delay";

import { omit } from "../utils/omit";

import { base64FromBytes } from "../utils/base64FromBytes";

import {

TaskProviderHelper,

TextToImageTaskHelper,

TextToVideoTaskHelper,

ImageToImageTaskHelper,

} from "./providerHelper";

import { InferenceOutputError } from "../lib/InferenceOutputError";

import type { ImageToImageArgs } from "../tasks";

import type { BodyParams, HeaderParams, RequestArgs, UrlParams } from "../types";

import { delay } from "../utils/delay";

import { omit } from "../utils/omit";

import { base64FromBytes } from "../utils/base64FromBytes";

import type {

TaskProviderHelper,

TextToImageTaskHelper,

TextToVideoTaskHelper,

ImageToImageTaskHelper,

} from "./providerHelper";

Modify as suggested

SBrandeis · 2025-05-19T15:08:19Z

packages/inference/src/providers/wavespeed-ai.ts

+	};
+}
+
+type WaveSpeedAIResponse<T = WaveSpeedAITaskResponse> = WaveSpeedAICommonResponse<T>;


I'm not sure this type alias is needed, can we remove it?

Suggested change

type WaveSpeedAIResponse<T = WaveSpeedAITaskResponse> = WaveSpeedAICommonResponse<T>;

WaveSpeedAICommonResponse can be renamed to WaveSpeedAIResponse

This type is needed and will be used in two places. It's uncertain whether it will be used again in the future.
It follows the DRY (Don't Repeat Yourself) principle
It provides better type safety (through default generic parameters)
It makes the code more readable and maintainable

SBrandeis · 2025-05-19T15:20:13Z

packages/inference/src/providers/wavespeed-ai.ts

+				case "completed": {
+					// Get the video data from the first output URL
+					if (!taskResult.outputs?.[0]) {
+						throw new InferenceOutputError("No video URL in completed response");
+					}
+					const videoResponse = await fetch(taskResult.outputs[0]);
+					if (!videoResponse.ok) {
+						throw new InferenceOutputError("Failed to fetch video data");
+					}
+					return await videoResponse.blob();


From what I understand, the payload can be something else than a video (eg an image)
Let's update the error message to reflect that

yes,
I revised it.

SBrandeis · 2025-05-19T15:24:51Z

packages/inference/src/providers/wavespeed-ai.ts

+		if (!args.parameters) {
+			return {
+				...args,
+				model: args.model,
+				data: args.inputs,
+			};
+		} else {
+			return {
+				...args,
+				inputs: base64FromBytes(
+					new Uint8Array(args.inputs instanceof ArrayBuffer ? args.inputs : await (args.inputs as Blob).arrayBuffer())
+				),
+			};
+		}
+	}
+
+	override preparePayload(params: BodyParams): Record<string, unknown> {
+		return {
+			...omit(params.args, ["inputs", "parameters"]),
+			...(params.args.parameters as Record<string, unknown>),
+			image: params.args.inputs,
+		};
+	}


I think only one of the two ( preparePayload or preparePayloadAsync) should be responsible for building the payload, meaning, I'd rather move the rename of inputs to image in preparePayloadAsync an have preparePayload as dumb as possible

cc @hanouticelina - would love your opinion on that specific point

I only kept preparePayloadAsync func

I think only one of the two ( preparePayload or preparePayloadAsync) should be responsible for building the payload, meaning, I'd rather move the rename of inputs to image in preparePayloadAsync an have preparePayload as dumb as possible

yes agree!

SBrandeis · 2025-05-19T15:27:55Z

packages/inference/src/providers/wavespeed-ai.ts

+				inputs: base64FromBytes(
+					new Uint8Array(args.inputs instanceof ArrayBuffer ? args.inputs : await (args.inputs as Blob).arrayBuffer())
+				),


Does the wavespeed API support base64-encoded images as inputs?

hanouticelina

thank you @arabot777 for the PR! I left some minor comments. I tested the 3 tasks supported by Wavespeed.ai and it works as expected with the changes I suggested.

packages/inference/src/lib/getProviderHelper.ts

packages/inference/src/providers/wavespeed-ai.ts

Co-authored-by: célina <[email protected]>

SBrandeis

Second round of code review, thank you! We're getting there

Note: make sure you run pnpm format and pnpm lint to conform our code style.

SBrandeis · 2025-05-22T14:17:44Z

packages/inference/src/providers/wavespeed-ai.ts

+/**
+ * Common response structure for all WaveSpeed AI API responses
+ */
+interface WaveSpeedAICommonResponse<T> {
+	code: number;
+	message: string;
+	data: T;
+}
+


This abstraction is not necessary IMO, let's remove it (see my other comment)

Suggested change

/**

* Common response structure for all WaveSpeed AI API responses

*/

interface WaveSpeedAICommonResponse<T> {

code: number;

message: string;

data: T;

}

It has been modified as suggested

SBrandeis · 2025-05-22T14:19:34Z

packages/inference/src/providers/wavespeed-ai.ts

+type WaveSpeedAIResponse<T = WaveSpeedAITaskResponse> = WaveSpeedAICommonResponse<T>;
+


Following the previous comment - let's remove one level of abstraction

Suggested change

type WaveSpeedAIResponse<T = WaveSpeedAITaskResponse> = WaveSpeedAICommonResponse<T>;

interface WaveSpeedAIResponse {

code: number;

message: string;

data: WaveSpeedAITaskResponse

}

It has been modified as suggested

SBrandeis · 2025-05-22T14:25:25Z

packages/inference/src/providers/wavespeed-ai.ts

+	preparePayload(params: BodyParams): Record<string, unknown> {
+		const payload: Record<string, unknown> = {
+			...omit(params.args, ["inputs", "parameters"]),
+			...(params.args.parameters as Record<string, unknown>),
+			prompt: params.args.inputs,
+		};
+		// Add LoRA support if adapter is specified in the mapping


We don't need to cast into Result<string, unknown> if the params have the proper type
ImageToImageArgs, TextToImageArgs, and TextToVideoArgs need to be improrted from "../tasks"

Suggested change

preparePayload(params: BodyParams): Record<string, unknown> {

const payload: Record<string, unknown> = {

...omit(params.args, ["inputs", "parameters"]),

...(params.args.parameters as Record<string, unknown>),

prompt: params.args.inputs,

};

// Add LoRA support if adapter is specified in the mapping

preparePayload(params: BodyParams<ImageToImageArgs | TextToImageArgs | TextToVideoArgs>): Record<string, unknown> {

const payload: Record<string, unknown> = {

...omit(params.args, ["inputs", "parameters"]),

...params.args.parameters,

prompt: params.args.inputs,

};

// Add LoRA support if adapter is specified in the mapping

It has been modified as suggested

SBrandeis · 2025-05-22T14:31:43Z

packages/inference/src/providers/wavespeed-ai.ts

+		if (params.mapping?.adapter === "lora" && params.mapping.adapterWeightsPath) {
+			payload.loras = [
+				{
+					path: params.mapping.adapterWeightsPath,


For reference, adapterWeightsPath is the path to the LoRA weights inside the associated HF repo
eg, for nerijs/pixel-art-xl, it will be

"pixel-art-xl.safetensors"

Let's make sure that is indeed what your API is expecting when running LoRAs

Here I see that fal is the endpoint that has been concatenated with hf.
Can I directly set the adapterWeightsPath to a lora http address? Or any other address.

In the test cases, I conducted the test in this way. The adapterWeightsPath was directly passed over as an input parameter of lora.

"wavespeed-ai/flux-dev-lora": { hfModelId: "wavespeed-ai/flux-dev-lora", providerId: "wavespeed-ai/flux-dev-lora", status: "live", task: "text-to-image", adapter: "lora", adapterWeightsPath: "https://d32s1zkpjdc4b1.cloudfront.net/predictions/599f3739f5354afc8a76a12042736bfd/1.safetensors", }, "wavespeed-ai/flux-dev-lora-ultra-fast": { hfModelId: "wavespeed-ai/flux-dev-lora-ultra-fast", providerId: "wavespeed-ai/flux-dev-lora-ultra-fast", status: "live", task: "text-to-image", adapter: "lora", adapterWeightsPath: "linoyts/yarn_art_Flux_LoRA", },

in wavespeedai task is :

However, I'm not sure whether the input parameters submitted by hf to lora must be the abbreviation of the file path of the hf model and then concatenated with the hf address in the code. If it is this kind of specification, I can complete it in the format of fal

I think your API can just take the hf model id as the loras path, right?

Suggested change

path: params.mapping.adapterWeightsPath,

path: params.mapping.hfModelId,,

As mentioned by @SBrandeis, this part depends on what your API is expecting as inputs when using LoRAs weights.

Yes, you're correct.
In the example, linoyts/yarn_art_Flux_LoRA is the lora model address of hf. We will automatically match and download the hf model。

I completed the modification and ran the use case successfully

SBrandeis · 2025-05-22T14:33:14Z

packages/inference/src/providers/wavespeed-ai.ts

+	override prepareHeaders(params: HeaderParams, isBinary: boolean): Record<string, string> {
+		this.accessToken = params.accessToken;
+		const headers: Record<string, string> = { Authorization: `Bearer ${params.accessToken}` };
+		if (!isBinary) {
+			headers["Content-Type"] = "application/json";
+		}
+		return headers;
+	}


This is the same behavior as the blanket implementation here:
https://github.com/arabot777/huggingface.js/blob/f706e02d6128f559bd5551072344ff6e31b9c4be/packages/inference/src/providers/providerHelper.ts#L114-L124

No need for an override IMO

Suggested change

override prepareHeaders(params: HeaderParams, isBinary: boolean): Record<string, string> {

this.accessToken = params.accessToken;

const headers: Record<string, string> = { Authorization: `Bearer ${params.accessToken}` };

if (!isBinary) {

headers["Content-Type"] = "application/json";

}

return headers;

}

I removed this part of the logic at the beginning. However, the getresponse method of imageToimage.ts did not pass in header information.

I have to rewrite prepareHeaders here and by assignment
this.accessToken = params.accessToken; To ensure that the complete ak information of the header can be passed on when calling getresponse

I'd rather update ImageToImage to be able to pass headers to getResponse:

export async function imageToImage(args: ImageToImageArgs, options?: Options): Promise<Blob> { const provider = await resolveProvider(args.provider, args.model, args.endpointUrl); const providerHelper = getProviderHelper(provider, "image-to-image"); const payload = await providerHelper.preparePayloadAsync(args); const { data: res } = await innerRequest<Blob>(payload, providerHelper, { ...options, task: "image-to-image", }); const { url, info } = await makeRequestOptions(args, providerHelper, { ...options, task: "image-to-image" }); return providerHelper.getResponse(res, url, info.headers as Record<string, string>); }

rather than overriding prepareHeaders and doing this.accessToken = params.accessToken

Your suggestion makes sense. Initially, this was a common/public function, so I took a minimalistic approach and didn't modify it. Now, let me try making some changes here.

I completed the modification and ran the use case successfully

hanouticelina

thanks @arabot777 for the iteration. I left a few comments, but we're almost at something merge-ready!

hanouticelina · 2025-05-26T13:56:42Z

packages/inference/src/providers/wavespeed-ai.ts

+	override prepareHeaders(params: HeaderParams, isBinary: boolean): Record<string, string> {
+		this.accessToken = params.accessToken;
+		const headers: Record<string, string> = { Authorization: `Bearer ${params.accessToken}` };
+		if (!isBinary) {
+			headers["Content-Type"] = "application/json";
+		}
+		return headers;
+	}


I'd rather update ImageToImage to be able to pass headers to getResponse:

export async function imageToImage(args: ImageToImageArgs, options?: Options): Promise<Blob> { const provider = await resolveProvider(args.provider, args.model, args.endpointUrl); const providerHelper = getProviderHelper(provider, "image-to-image"); const payload = await providerHelper.preparePayloadAsync(args); const { data: res } = await innerRequest<Blob>(payload, providerHelper, { ...options, task: "image-to-image", }); const { url, info } = await makeRequestOptions(args, providerHelper, { ...options, task: "image-to-image" }); return providerHelper.getResponse(res, url, info.headers as Record<string, string>); }

rather than overriding prepareHeaders and doing this.accessToken = params.accessToken

packages/inference/src/providers/wavespeed-ai.ts

arabot777 · 2025-05-26T14:39:58Z

@hanouticelina Thank you for your suggestion. I completed the modification and ran the use case successfully

arabot777 · 2025-05-29T02:13:21Z

Hi, the code has been updated per the review comments. Appreciate if you could verify the changes and point out any remaining concerns for us to address. thanks @SBrandeis

HuggingFaceDocBuilderDev · 2025-06-03T10:19:49Z

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

hanouticelina

Hi @arabot777, we recently merged an improvement of error handling for inference (PR: #1504). i've added suggestions on how to incorporate it into the WaveSpeed AI inference provider implementation.
Other than that, the PR looks good to me but let's wait for @SBrandeis final review!

hanouticelina · 2025-06-03T10:18:53Z

packages/inference/src/providers/wavespeed-ai.ts

+		headers?: Record<string, string>
+	): Promise<Blob> {
+		if (!headers) {
+			throw new InferenceOutputError("Headers are required for WaveSpeed AI API calls");


Suggested change

throw new InferenceOutputError("Headers are required for WaveSpeed AI API calls");

throw new InferenceClientInputError("Headers are required for WaveSpeed AI API calls");

hanouticelina · 2025-06-03T10:20:11Z

packages/inference/src/providers/wavespeed-ai.ts

+			const resultResponse = await fetch(resultUrl, { headers });
+
+			if (!resultResponse.ok) {
+				throw new InferenceOutputError(`Failed to get result: ${resultResponse.statusText}`);


Suggested change

throw new InferenceOutputError(`Failed to get result: ${resultResponse.statusText}`);

throw new InferenceClientProviderApiError(

"Failed to fetch response status from WaveSpeed AI API",

{ url: resultUrl, method: "GET" },

{

requestId: resultResponse.headers.get("x-request-id") ?? "",

body: await resultResponse.text(),

}

);

hanouticelina · 2025-06-03T10:21:17Z

packages/inference/src/providers/wavespeed-ai.ts

+
+			const result: WaveSpeedAIResponse = await resultResponse.json();
+			if (result.code !== 200) {
+				throw new InferenceOutputError(`API request failed with code ${result.code}: ${result.message}`);


Suggested change

throw new InferenceOutputError(`API request failed with code ${result.code}: ${result.message}`);

throw new InferenceClientProviderOutputError(`API request to WaveSpeed AI API failed with code ${result.code}: ${result.message}`);

hanouticelina · 2025-06-03T10:22:00Z

packages/inference/src/providers/wavespeed-ai.ts

+				case "completed": {
+					// Get the media data from the first output URL
+					if (!taskResult.outputs?.[0]) {
+						throw new InferenceOutputError("No output URL in completed response");


Suggested change

throw new InferenceOutputError("No output URL in completed response");

throw new InferenceClientProviderOutputError("Received malformed response from WaveSpeed AI API: No output URL in completed response");

hanouticelina · 2025-06-03T10:24:05Z

packages/inference/src/providers/wavespeed-ai.ts

+					}
+					const mediaResponse = await fetch(taskResult.outputs[0]);
+					if (!mediaResponse.ok) {
+						throw new InferenceOutputError("Failed to fetch output data");


Suggested change

throw new InferenceOutputError("Failed to fetch output data");

throw new InferenceClientProviderApiError(

"Failed to fetch response status from WaveSpeed AI API",

{ url: taskResult.outputs[0], method: "GET" },

{

requestId: mediaResponse.headers.get("x-request-id") ?? "",

body: await mediaResponse.text(),

}

);

hanouticelina · 2025-06-03T10:26:13Z

packages/inference/src/providers/wavespeed-ai.ts

+					return await mediaResponse.blob();
+				}
+				case "failed": {
+					throw new InferenceOutputError(taskResult.error || "Task failed");


Suggested change

throw new InferenceOutputError(taskResult.error || "Task failed");

throw new InferenceClientProviderOutputError(taskResult.error || "Task failed");

hanouticelina · 2025-06-03T10:26:49Z

packages/inference/src/providers/wavespeed-ai.ts

+					continue;
+
+				default: {
+					throw new InferenceOutputError(`Unknown status: ${taskResult.status}`);


Suggested change

throw new InferenceOutputError(`Unknown status: ${taskResult.status}`);

throw new InferenceClientProviderOutputError(`Unknown status: ${taskResult.status}`);

packages/inference/src/providers/wavespeed-ai.ts

arabot777 · 2025-06-03T15:30:37Z

Hi @arabot777, we recently merged an improvement of error handling for inference (PR: #1504). i've added suggestions on how to incorporate it into the WaveSpeed AI inference provider implementation. Other than that, the PR looks good to me but let's wait for @SBrandeis final review!

Thank you for your reminder. I have completed the new error handling

arabot777 · 2025-06-09T15:02:23Z

Hi @SBrandeis ,

Just checking in—is there anything I can do to help move this PR forward? Let me know if you'd like any changes or have questions. Thanks for your time!

arabot777 added 2 commits May 5, 2025 09:45

add wavespeed.ai as an inference provider

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delete debug log

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arabot777 requested review from julien-c, hanouticelina and SBrandeis as code owners May 5, 2025 02:28

arabot777 and others added 6 commits May 5, 2025 17:31

Merge branch 'main' into feat/wavespeedai

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Merge branch 'main' into feat/wavespeedai

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Merge branch 'main' into feat/wavespeedai

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Merge branch 'main' into feat/wavespeedai

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Merge branch 'main' into feat/wavespeedai

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support lora

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SBrandeis reviewed May 19, 2025

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hanouticelina added the inference-providers integration of a new or existing Inference Provider label May 20, 2025

arabot777 and others added 4 commits May 20, 2025 21:31

code review

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Merge branch 'main' into feat/wavespeedai

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code review

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Merge branch 'main' into feat/wavespeedai

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arabot777 requested a review from SBrandeis May 20, 2025 13:44

arabot777 and others added 2 commits May 20, 2025 21:48

delete unused import

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Merge branch 'main' into feat/wavespeedai

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hanouticelina reviewed May 21, 2025

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arabot777 and others added 4 commits May 22, 2025 00:22

Update packages/inference/src/lib/getProviderHelper.ts

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Co-authored-by: célina <[email protected]>

Update packages/inference/src/lib/getProviderHelper.ts

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Co-authored-by: célina <[email protected]>

Merge branch 'main' into feat/wavespeedai

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Merge branch 'main' into feat/wavespeedai

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SBrandeis reviewed May 22, 2025

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code review modification

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arabot777 requested review from SBrandeis and hanouticelina May 22, 2025 15:32

Merge branch 'main' into feat/wavespeedai

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Merge branch 'main' into feat/wavespeedai

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SBrandeis self-assigned this May 23, 2025

arabot777 and others added 4 commits May 23, 2025 22:08

Merge branch 'main' into feat/wavespeedai

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import js file

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Merge branch 'main' into feat/wavespeedai

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Merge branch 'main' into feat/wavespeedai

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hanouticelina reviewed May 26, 2025

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lora optimize and image-to-image getresponse use header

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arabot777 requested a review from hanouticelina May 27, 2025 14:32

arabot777 added 3 commits May 27, 2025 23:15

Merge branch 'main' into feat/wavespeedai

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Merge branch 'main' into feat/wavespeedai

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Merge branch 'main' into feat/wavespeedai

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Merge branch 'main' into feat/wavespeedai

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hanouticelina reviewed Jun 3, 2025

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arabot777 and others added 3 commits June 3, 2025 22:14

Merge branch 'main' into feat/wavespeedai

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handle inference error; upgrade api v2 -> v3

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recode import

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arabot777 added 2 commits June 7, 2025 11:55

Merge branch 'main' into feat/wavespeedai

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Merge branch 'main' into feat/wavespeedai

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Merge branch 'main' into feat/wavespeedai

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		- [HF Inference API (serverless)](https://huggingface.co/models?inference=warm&sort=trending)

		type WaveSpeedAIResponse<T = WaveSpeedAITaskResponse> = WaveSpeedAICommonResponse<T>;

	path: params.mapping.adapterWeightsPath,
	path: params.mapping.hfModelId,,

	throw new InferenceOutputError("Headers are required for WaveSpeed AI API calls");
	throw new InferenceClientInputError("Headers are required for WaveSpeed AI API calls");

-				throw new InferenceOutputError(`Failed to get result: ${resultResponse.statusText}`);
+				throw new InferenceClientProviderApiError(
+					"Failed to fetch response status from WaveSpeed AI API",
+					{ url: resultUrl, method: "GET" },
+					{
+						requestId: resultResponse.headers.get("x-request-id") ?? "",
+						body: await resultResponse.text(),
+					}
+				);

	throw new InferenceOutputError(`API request failed with code ${result.code}: ${result.message}`);
	throw new InferenceClientProviderOutputError(`API request to WaveSpeed AI API failed with code ${result.code}: ${result.message}`);

	throw new InferenceOutputError("No output URL in completed response");
	throw new InferenceClientProviderOutputError("Received malformed response from WaveSpeed AI API: No output URL in completed response");

	throw new InferenceOutputError(taskResult.error \|\| "Task failed");
	throw new InferenceClientProviderOutputError(taskResult.error \|\| "Task failed");

	throw new InferenceOutputError(`Unknown status: ${taskResult.status}`);
	throw new InferenceClientProviderOutputError(`Unknown status: ${taskResult.status}`);

[inference provider] Add wavespeed.ai as an inference provider #1424

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[inference provider] Add wavespeed.ai as an inference provider #1424

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arabot777 May 22, 2025 • edited Loading Uh oh! There was an error while loading. Please reload this page.

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arabot777 commented May 5, 2025 •

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