lint

Author: SBrandeis

packages/inference/src/lib/makeRequestOptions.ts

@@ -126,7 +126,7 @@ export async function makeRequestOptions(
 				throw new Error("Inference proxying is not implemented yet");
 			} else {
 				switch (provider) {
-					case 'fal-ai':
+					case "fal-ai":
 						return `${FAL_AI_API_BASE_URL}/${model}`;
 					case "replicate":
 						return `${REPLICATE_API_BASE_URL}/v1/models/${model}/predictions`;
@@ -166,10 +166,10 @@ export async function makeRequestOptions(
 		body: binary
 			? args.data
 			: JSON.stringify({
-				...((otherArgs.model && isUrl(otherArgs.model)) || provider === "replicate" || provider === "fal-ai"
-					? omit(otherArgs, "model")
-					: { ...otherArgs, model }),
-			}),
+					...((otherArgs.model && isUrl(otherArgs.model)) || provider === "replicate" || provider === "fal-ai"
+						? omit(otherArgs, "model")
+						: { ...otherArgs, model }),
+			  }),
 		...(credentials ? { credentials } : undefined),
 		signal: options?.signal,
 	};

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

@@ -1,6 +1,6 @@
 import type { ModelId } from "../types";
 
-export const FAL_AI_API_BASE_URL = "https://fal.run"
+export const FAL_AI_API_BASE_URL = "https://fal.run";
 
 type FalAiId = string;
 
@@ -10,4 +10,4 @@ export const FAL_AI_MODEL_IDS: Record<ModelId, FalAiId> = {
 	"black-forest-labs/FLUX.1-Redux-dev": "fal-ai/flux/dev/redux",
 	"openai/whisper-large-v3": "fal-ai/wizper",
 	"TencentARC/PhotoMaker": "fal-ai/photomaker",
-}
+};

packages/inference/src/tasks/audio/automaticSpeechRecognition.ts

@@ -25,10 +25,11 @@ export async function automaticSpeechRecognition(
 	args: AutomaticSpeechRecognitionArgs,
 	options?: Options
 ): Promise<AutomaticSpeechRecognitionOutput> {
-
 	if (args.provider === "fal-ai") {
 		const contentType = args.data instanceof Blob ? args.data.type : "audio/mpeg";
-		const base64audio = base64FromBytes(new Uint8Array(args.data instanceof ArrayBuffer ? args.data : await args.data.arrayBuffer()));
+		const base64audio = base64FromBytes(
+			new Uint8Array(args.data instanceof ArrayBuffer ? args.data : await args.data.arrayBuffer())
+		);
 		(args as RequestArgs & { audio_url: string }).audio_url = `data:${contentType};base64,${base64audio}`;
 		delete (args as RequestArgs & { data: unknown }).data;
 	}

packages/inference/src/tasks/custom/request.ts

@@ -27,14 +27,12 @@ export async function request<T>(
 
 	if (!response.ok) {
 		const contentType = response.headers.get("Content-Type");
-		if (
-			["application/json", "application/problem+json"].some(
-				(ct) => contentType?.startsWith(ct)
-			)
-		) {
+		if (["application/json", "application/problem+json"].some((ct) => contentType?.startsWith(ct))) {
 			const output = await response.json();
 			if ([400, 422, 404, 500].includes(response.status) && options?.chatCompletion) {
-				throw new Error(`Server ${args.model} does not seem to support chat completion. Error: ${JSON.stringify(output.error)}`);
+				throw new Error(
+					`Server ${args.model} does not seem to support chat completion. Error: ${JSON.stringify(output.error)}`
+				);
 			}
 			if (output.error || output.detail) {
 				throw new Error(JSON.stringify(output.error ?? output.detail));

packages/inference/test/HfInference.spec.ts

@@ -5,7 +5,6 @@ import type { ChatCompletionStreamOutput } from "@huggingface/tasks";
 import { HfInference } from "../src";
 import "./vcr";
 import { readTestFile } from "./test-files";
-import { fail } from "assert";
 
 const TIMEOUT = 60000 * 3;
 const env = import.meta.env;
@@ -551,7 +550,8 @@ describe.concurrent(
 			});
 			it("textToImage", async () => {
 				const res = await hf.textToImage({
-					inputs: "award winning high resolution photo of a giant tortoise/((ladybird)) hybrid, [trending on artstation]",
+					inputs:
+						"award winning high resolution photo of a giant tortoise/((ladybird)) hybrid, [trending on artstation]",
 					model: "stabilityai/stable-diffusion-2",
 				});
 				expect(res).toBeInstanceOf(Blob);
@@ -563,7 +563,8 @@ describe.concurrent(
 				const num_inference_steps = 10;
 
 				const res = await hf.textToImage({
-					inputs: "award winning high resolution photo of a giant tortoise/((ladybird)) hybrid, [trending on artstation]",
+					inputs:
+						"award winning high resolution photo of a giant tortoise/((ladybird)) hybrid, [trending on artstation]",
 					model: "stabilityai/stable-diffusion-2",
 					parameters: {
 						negative_prompt: "blurry",
@@ -758,11 +759,10 @@ describe.concurrent(
 				}
 				expect(out).toContain("two");
 			});
-
 		});
 		/**
-				 * Compatibility with third-party Inference Providers
-				 */
+		 * Compatibility with third-party Inference Providers
+		 */
 		describe.concurrent("SambaNova", () => {
 			const client = new HfInference(env.HF_SAMBANOVA_KEY);
 
@@ -831,8 +831,7 @@ describe.concurrent(
 				});
 				expect(res).toBeInstanceOf(Blob);
 			});
-		})
-
+		});
 
 		describe.concurrent("Replicate", () => {
 			const client = new HfInference(env.HF_REPLICATE_KEY);
@@ -857,7 +856,7 @@ describe.concurrent(
 					inputs: "black forest gateau cake spelling out the words FLUX SCHNELL, tasty, food photography, dynamic shot",
 				});
 				expect(res).toBeInstanceOf(Blob);
-			})
+			});
 
 			it("speechToText fal-ai", async () => {
 				const res = await client.automaticSpeechRecognition({
@@ -868,9 +867,8 @@ describe.concurrent(
 				expect(res).toMatchObject({
 					text: "HE HAS GRAVE DOUBTS WHETHER SIR FREDERICK LEIGHTON'S WORK IS REALLY GREEK AFTER ALL AND CAN DISCOVER IN IT BUT LITTLE OF ROCKY ITHACA",
 				});
-			})
-		})
-
+			});
+		});
 	},
 	TIMEOUT
 );