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import { InferenceOutputError } from "../../lib/InferenceOutputError"; | |
import type { BaseArgs, Options } from "../../types"; | |
import { request } from "../custom/request"; | |
export type TextClassificationArgs = BaseArgs & { | |
/** | |
* A string to be classified | |
*/ | |
inputs: string; | |
}; | |
export type TextClassificationOutput = { | |
/** | |
* The label for the class (model specific) | |
*/ | |
label: string; | |
/** | |
* A floats that represents how likely is that the text belongs to this class. | |
*/ | |
score: number; | |
}[]; | |
/** | |
* Usually used for sentiment-analysis this will output the likelihood of classes of an input. Recommended model: distilbert-base-uncased-finetuned-sst-2-english | |
*/ | |
export async function textClassification( | |
args: TextClassificationArgs, | |
options?: Options | |
): Promise<TextClassificationOutput> { | |
const res = ( | |
await request<TextClassificationOutput[]>(args, { | |
...options, | |
taskHint: "text-classification", | |
}) | |
)?.[0]; | |
const isValidOutput = | |
Array.isArray(res) && res.every((x) => typeof x?.label === "string" && typeof x.score === "number"); | |
if (!isValidOutput) { | |
throw new InferenceOutputError("Expected Array<{label: string, score: number}>"); | |
} | |
return res; | |
} | |