dtamind-components
Version:
DTAmindai Components
83 lines • 3.39 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
const contextual_compression_1 = require("langchain/retrievers/contextual_compression");
const chain_extract_1 = require("langchain/retrievers/document_compressors/chain_extract");
const utils_1 = require("../../../src/utils");
class LLMFilterCompressionRetriever_Retrievers {
constructor() {
this.label = 'LLM Filter Retriever';
this.name = 'llmFilterRetriever';
this.version = 1.0;
this.type = 'LLMFilterRetriever';
this.icon = 'llmFilterRetriever.svg';
this.category = 'Retrievers';
this.description =
'Iterate over the initially returned documents and extract, from each, only the content that is relevant to the query';
this.baseClasses = [this.type, 'BaseRetriever'];
this.inputs = [
{
label: 'Vector Store Retriever',
name: 'baseRetriever',
type: 'VectorStoreRetriever'
},
{
label: 'Language Model',
name: 'model',
type: 'BaseLanguageModel'
},
{
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
}
];
this.outputs = [
{
label: 'LLM Filter 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) {
const baseRetriever = nodeData.inputs?.baseRetriever;
const model = nodeData.inputs?.model;
const query = nodeData.inputs?.query;
const output = nodeData.outputs?.output;
if (!model)
throw new Error('There must be a LLM model connected to LLM Filter Retriever');
const retriever = new contextual_compression_1.ContextualCompressionRetriever({
baseCompressor: chain_extract_1.LLMChainExtractor.fromLLM(model),
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, utils_1.handleEscapeCharacters)(finaltext, false);
}
return retriever;
}
}
module.exports = { nodeClass: LLMFilterCompressionRetriever_Retrievers };
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