featureExtraction should use FeatureExtractionInput (#1235)

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https://github.com/huggingface/huggingface.js/pull/1235/files#r1973270449

Author: mishig25

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

@@ -1,16 +1,9 @@
+import type { FeatureExtractionInput } from "@huggingface/tasks";
 import { InferenceOutputError } from "../../lib/InferenceOutputError";
 import type { BaseArgs, Options } from "../../types";
 import { request } from "../custom/request";
 
-export type FeatureExtractionArgs = BaseArgs & {
-	/**
-	 *  The inputs is a string or a list of strings to get the features from.
-	 *
-	 *  inputs: "That is a happy person",
-	 *
-	 */
-	inputs: string | string[];
-};
+export type FeatureExtractionArgs = BaseArgs & FeatureExtractionInput;
 
 /**
  * Returned values are a multidimensional array of floats (dimension depending on if you sent a string or a list of string, and if the automatic reduction, usually mean_pooling for instance was applied for you or not. This should be explained on the model's README).

packages/inference/src/types.ts

@@ -1,4 +1,4 @@
-import type { ChatCompletionInput, PipelineType } from "@huggingface/tasks";
+import type { ChatCompletionInput, FeatureExtractionInput, PipelineType } from "@huggingface/tasks";
 
 /**
  * HF model id, like "meta-llama/Llama-3.3-70B-Instruct"
@@ -86,6 +86,7 @@ export type RequestArgs = BaseArgs &
 		| { text: string }
 		| { audio_url: string }
 		| ChatCompletionInput
+		| FeatureExtractionInput
 	) & {
 		parameters?: Record<string, unknown>;
 	};