@n8n/n8n-nodes-langchain/dist/nodes/embeddings/EmbeddingsNvidia/helpers.js

"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.NvidiaEmbeddings = void 0;
const chunk_array_1 = require("@langchain/core/utils/chunk_array");
const openai_1 = require("@langchain/openai");
const n8n_workflow_1 = require("n8n-workflow");
class NvidiaEmbeddings extends openai_1.OpenAIEmbeddings {
    async embedDocuments(texts) {
        return await this.embedWithInputType(texts, 'passage');
    }
    async embedQuery(text) {
        const [embedding] = await this.embedWithInputType([text], 'query');
        return embedding;
    }
    async embedWithInputType(texts, inputType) {
        const input = this.stripNewLines ? texts.map((text) => text.replace(/\n/g, ' ')) : texts;
        const batches = (0, chunk_array_1.chunkArray)(input, this.batchSize);
        const batchRequests = batches.map(async (batch) => {
            const params = {
                model: this.model,
                input: batch,
                input_type: inputType,
            };
            if (this.dimensions)
                params.dimensions = this.dimensions;
            if (this.encodingFormat)
                params.encoding_format = this.encodingFormat;
            const { data } = await this.embeddingWithRetry(params);
            return { expected: batch.length, data };
        });
        const batchResponses = await Promise.all(batchRequests);
        const embeddings = [];
        for (const { expected, data } of batchResponses) {
            if (data.length !== expected) {
                throw new n8n_workflow_1.OperationalError(`NVIDIA embeddings API returned ${data.length} embeddings for a batch of ${expected} inputs`);
            }
            for (const entry of data) {
                embeddings.push(entry.embedding);
            }
        }
        return embeddings;
    }
}
exports.NvidiaEmbeddings = NvidiaEmbeddings;
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