dtamind-components
Version:
Apps integration for Dtamind. Contain Nodes and Credentials.
127 lines • 5.16 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
const contextual_compression_1 = require("langchain/retrievers/contextual_compression");
const CohereRerank_1 = require("./CohereRerank");
const src_1 = require("../../../src");
class CohereRerankRetriever_Retrievers {
constructor() {
this.label = 'Cohere Rerank Retriever';
this.name = 'cohereRerankRetriever';
this.version = 1.0;
this.type = 'Cohere Rerank Retriever';
this.icon = 'Cohere.svg';
this.category = 'Retrievers';
this.description = 'Cohere Rerank indexes the documents from most to least semantically relevant to the query.';
this.baseClasses = [this.type, 'BaseRetriever'];
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
credentialNames: ['cohereApi']
};
this.inputs = [
{
label: 'Vector Store Retriever',
name: 'baseRetriever',
type: 'VectorStoreRetriever'
},
{
label: 'Model Name',
name: 'model',
type: 'options',
options: [
{
label: 'rerank-v3.5',
name: 'rerank-v3.5'
},
{
label: 'rerank-english-v3.0',
name: 'rerank-english-v3.0'
},
{
label: 'rerank-multilingual-v3.0',
name: 'rerank-multilingual-v3.0'
}
],
default: 'rerank-v3.5',
optional: true
},
{
label: 'Query',
name: 'query',
type: 'string',
description: 'Query to retrieve documents from retriever. If not specified, user question will be used',
optional: true,
acceptVariable: true
},
{
label: 'Top K',
name: 'topK',
description: 'Number of top results to fetch. Default to the TopK of the Base Retriever',
placeholder: '4',
type: 'number',
additionalParams: true,
optional: true
},
{
label: 'Max Chunks Per Doc',
name: 'maxChunksPerDoc',
description: 'The maximum number of chunks to produce internally from a document. Default to 10',
placeholder: '10',
type: 'number',
additionalParams: true,
optional: true
}
];
this.outputs = [
{
label: 'Cohere Rerank Retriever',
name: 'retriever',
baseClasses: this.baseClasses
},
{
label: 'Document',
name: 'document',
description: 'Array of document objects containing metadata and pageContent',
baseClasses: ['Document', 'json']
},
{
label: 'Text',
name: 'text',
description: 'Concatenated string from pageContent of documents',
baseClasses: ['string', 'json']
}
];
}
async init(nodeData, input, options) {
const baseRetriever = nodeData.inputs?.baseRetriever;
const model = nodeData.inputs?.model;
const query = nodeData.inputs?.query;
const credentialData = await (0, src_1.getCredentialData)(nodeData.credential ?? '', options);
const cohereApiKey = (0, src_1.getCredentialParam)('cohereApiKey', credentialData, nodeData);
const topK = nodeData.inputs?.topK;
const k = topK ? parseFloat(topK) : baseRetriever.k ?? 4;
const maxChunksPerDoc = nodeData.inputs?.maxChunksPerDoc;
const max_chunks_per_doc = maxChunksPerDoc ? parseFloat(maxChunksPerDoc) : 10;
const output = nodeData.outputs?.output;
const cohereCompressor = new CohereRerank_1.CohereRerank(cohereApiKey, model, k, max_chunks_per_doc);
const retriever = new contextual_compression_1.ContextualCompressionRetriever({
baseCompressor: cohereCompressor,
baseRetriever: baseRetriever
});
if (output === 'retriever')
return retriever;
else if (output === 'document')
return await retriever.getRelevantDocuments(query ? query : input);
else if (output === 'text') {
let finaltext = '';
const docs = await retriever.getRelevantDocuments(query ? query : input);
for (const doc of docs)
finaltext += `${doc.pageContent}\n`;
return (0, src_1.handleEscapeCharacters)(finaltext, false);
}
return retriever;
}
}
module.exports = { nodeClass: CohereRerankRetriever_Retrievers };
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