zerolabel/dist/index.d.mts

Zero-shot multimodal classification SDK - classify text and images with custom labels, no training required

/**
 * Result of a single classification
 */
interface ClassificationResult {
    /** Original text that was classified */
    text: string;
    /** The predicted label */
    predicted_label: string;
    /** Confidence score (0-100) */
    confidence: number;
    /** Probability distribution over all labels (0-100 scale) */
    probabilities: Record<string, number>;
    /** Log probabilities for each label (raw values) */
    logprobs: Record<string, number | null>;
    /** All log probabilities from the model response */
    all_logprobs: Record<string, number>;
    /** The prompt that was sent to the model */
    prompt: string;
}
/**
 * Error thrown by the SDK
 */
declare class ZeroLabelError extends Error {
    readonly code?: string | undefined;
    readonly statusCode?: number | undefined;
    constructor(message: string, code?: string | undefined, statusCode?: number | undefined);
}

/**
 * ZeroLabel SDK - Zero-shot multimodal classification
 *
 * Classify text and images with custom labels, no training required.
 * Powered by Google Gemma 3-27B under the hood.
 *
 * @example
 * ```typescript
 * import { classify } from '@zerolabel/sdk';
 *
 * const results = await classify({
 *   texts: ['I love this product!'],
 *   labels: ['positive', 'negative', 'neutral'],
 *   apiKey: process.env.apiKey
 * });
 *
 * console.log(results[0].predicted_label); // 'positive'
 * ```
 */

interface ClassifyInput {
    /** Array of texts to classify (optional if using images) */
    texts?: string[];
    /** Array of images as base64 data URIs (optional if using text) */
    images?: string[];
    /** Array of possible classification labels */
    labels: string[];
    /** Your Inference.net API key */
    apiKey: string;
    /** Optional additional criteria for classification */
    criteria?: string;
    /** Optional additional instructions for the model */
    additionalInstructions?: string;
}

/**
 * Classify text and/or images with custom labels.
 *
 * @example
 * ```typescript
 * import { classify } from '@zerolabel/sdk';
 *
 * // Text classification
 * const results = await classify({
 *   texts: ['Amazing product!'],
 *   labels: ['positive', 'negative', 'neutral'],
 *   apiKey: process.env.apiKey
 * });
 *
 * // Image classification
 * const results = await classify({
 *   images: ['data:image/jpeg;base64,...'],
 *   labels: ['cat', 'dog', 'bird'],
 *   apiKey: process.env.apiKey
 * });
 *
 * // Multimodal classification
 * const results = await classify({
 *   texts: ['Check out this cute animal!'],
 *   images: ['data:image/jpeg;base64,...'],
 *   labels: ['cute cat', 'cute dog', 'not cute'],
 *   apiKey: process.env.apiKey
 * });
 * ```
 */
declare const classify: (input: ClassifyInput) => Promise<ClassificationResult[]>;

export { type ClassificationResult, type ClassifyInput, ZeroLabelError, classify };