dtamind-components
Version:
Apps integration for Dtamind. Contain Nodes and Credentials.
176 lines • 6.57 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
const prompts_1 = require("@langchain/core/prompts");
const hyde_1 = require("langchain/retrievers/hyde");
const utils_1 = require("../../../src/utils");
class HydeRetriever_Retrievers {
constructor() {
this.label = 'HyDE Retriever';
this.name = 'HydeRetriever';
this.version = 3.0;
this.type = 'HydeRetriever';
this.icon = 'hyderetriever.svg';
this.category = 'Retrievers';
this.description = 'Use HyDE retriever to retrieve from a vector store';
this.baseClasses = [this.type, 'BaseRetriever'];
this.inputs = [
{
label: 'Language Model',
name: 'model',
type: 'BaseLanguageModel'
},
{
label: 'Vector Store',
name: 'vectorStore',
type: 'VectorStore'
},
{
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: 'Select Defined Prompt',
name: 'promptKey',
description: 'Select a pre-defined prompt',
type: 'options',
options: [
{
label: 'websearch',
name: 'websearch',
description: `Please write a passage to answer the question
Question: {question}
Passage:`
},
{
label: 'scifact',
name: 'scifact',
description: `Please write a scientific paper passage to support/refute the claim
Claim: {question}
Passage:`
},
{
label: 'arguana',
name: 'arguana',
description: `Please write a counter argument for the passage
Passage: {question}
Counter Argument:`
},
{
label: 'trec-covid',
name: 'trec-covid',
description: `Please write a scientific paper passage to answer the question
Question: {question}
Passage:`
},
{
label: 'fiqa',
name: 'fiqa',
description: `Please write a financial article passage to answer the question
Question: {question}
Passage:`
},
{
label: 'dbpedia-entity',
name: 'dbpedia-entity',
description: `Please write a passage to answer the question.
Question: {question}
Passage:`
},
{
label: 'trec-news',
name: 'trec-news',
description: `Please write a news passage about the topic.
Topic: {question}
Passage:`
},
{
label: 'mr-tydi',
name: 'mr-tydi',
description: `Please write a passage in Swahili/Korean/Japanese/Bengali to answer the question in detail.
Question: {question}
Passage:`
}
],
default: 'websearch'
},
{
label: 'Custom Prompt',
name: 'customPrompt',
description: 'If custom prompt is used, this will override Defined Prompt',
placeholder: 'Please write a passage to answer the question\nQuestion: {question}\nPassage:',
type: 'string',
rows: 4,
additionalParams: true,
optional: true
},
{
label: 'Top K',
name: 'topK',
description: 'Number of top results to fetch. Default to 4',
placeholder: '4',
type: 'number',
default: 4,
additionalParams: true,
optional: true
}
];
this.outputs = [
{
label: 'HyDE 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 llm = nodeData.inputs?.model;
const vectorStore = nodeData.inputs?.vectorStore;
const promptKey = nodeData.inputs?.promptKey;
const customPrompt = nodeData.inputs?.customPrompt;
const query = nodeData.inputs?.query;
const topK = nodeData.inputs?.topK;
const k = topK ? parseFloat(topK) : 4;
const output = nodeData.outputs?.output;
const obj = {
llm,
vectorStore,
k
};
if (customPrompt)
obj.promptTemplate = prompts_1.PromptTemplate.fromTemplate(customPrompt);
else if (promptKey)
obj.promptTemplate = promptKey;
const retriever = new hyde_1.HydeRetriever(obj);
retriever.filter = vectorStore?.lc_kwargs?.filter ?? vectorStore.filter;
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: HydeRetriever_Retrievers };
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