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import { InferenceOutputError } from "../../lib/InferenceOutputError"; | |
import type { BaseArgs, Options } from "../../types"; | |
import { toArray } from "../../utils/toArray"; | |
import { request } from "../custom/request"; | |
export type ZeroShotClassificationArgs = BaseArgs & { | |
/** | |
* a string or list of strings | |
*/ | |
inputs: string | string[]; | |
parameters: { | |
/** | |
* a list of strings that are potential classes for inputs. (max 10 candidate_labels, for more, simply run multiple requests, results are going to be misleading if using too many candidate_labels anyway. If you want to keep the exact same, you can simply run multi_label=True and do the scaling on your end. | |
*/ | |
candidate_labels: string[]; | |
/** | |
* (Default: false) Boolean that is set to True if classes can overlap | |
*/ | |
multi_label?: boolean; | |
}; | |
}; | |
export interface ZeroShotClassificationOutputValue { | |
labels: string[]; | |
scores: number[]; | |
sequence: string; | |
} | |
export type ZeroShotClassificationOutput = ZeroShotClassificationOutputValue[]; | |
/** | |
* This task is super useful to try out classification with zero code, you simply pass a sentence/paragraph and the possible labels for that sentence, and you get a result. Recommended model: facebook/bart-large-mnli. | |
*/ | |
export async function zeroShotClassification( | |
args: ZeroShotClassificationArgs, | |
options?: Options | |
): Promise<ZeroShotClassificationOutput> { | |
const res = toArray( | |
await request<ZeroShotClassificationOutput[number] | ZeroShotClassificationOutput>(args, { | |
...options, | |
taskHint: "zero-shot-classification", | |
}) | |
); | |
const isValidOutput = | |
Array.isArray(res) && | |
res.every( | |
(x) => | |
Array.isArray(x.labels) && | |
x.labels.every((_label) => typeof _label === "string") && | |
Array.isArray(x.scores) && | |
x.scores.every((_score) => typeof _score === "number") && | |
typeof x.sequence === "string" | |
); | |
if (!isValidOutput) { | |
throw new InferenceOutputError("Expected Array<{labels: string[], scores: number[], sequence: string}>"); | |
} | |
return res; | |
} | |