Feature/Custom Retriever

packages/components/nodes/retrievers/CustomRetriever/CustomRetriever.ts

@@ -0,0 +1,159 @@
+import { get } from 'lodash'
+import { Document } from '@langchain/core/documents'
+import { VectorStore, VectorStoreRetriever, VectorStoreRetrieverInput } from '@langchain/core/vectorstores'
+import { INode, INodeData, INodeParams, INodeOutputsValue } from '../../../src/Interface'
+import { handleEscapeCharacters } from '../../../src'
+
+const defaultReturnFormat = '{{context}}\nSource: {{metadata.source}}'
+
+class CustomRetriever_Retrievers implements INode {
+    label: string
+    name: string
+    version: number
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    inputs: INodeParams[]
+    outputs: INodeOutputsValue[]
+
+    constructor() {
+        this.label = 'Custom Retriever'
+        this.name = 'customRetriever'
+        this.version = 1.0
+        this.type = 'CustomRetriever'
+        this.icon = 'customRetriever.svg'
+        this.category = 'Retrievers'
+        this.description = 'Return results based on predefined format'
+        this.baseClasses = [this.type, 'BaseRetriever']
+        this.inputs = [
+            {
+                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: 'Result Format',
+                name: 'resultFormat',
+                type: 'string',
+                rows: 4,
+                description:
+                    'Format to return the results in. Use {{context}} to insert the pageContent of the document and {{metadata.key}} to insert metadata values.',
+                default: defaultReturnFormat
+            },
+            {
+                label: 'Top K',
+                name: 'topK',
+                description: 'Number of top results to fetch. Default to vector store topK',
+                placeholder: '4',
+                type: 'number',
+                additionalParams: true,
+                optional: true
+            }
+        ]
+        this.outputs = [
+            {
+                label: 'Custom 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: INodeData, input: string): Promise<any> {
+        const vectorStore = nodeData.inputs?.vectorStore as VectorStore
+        const query = nodeData.inputs?.query as string
+        const topK = nodeData.inputs?.topK as string
+        const resultFormat = nodeData.inputs?.resultFormat as string
+
+        const output = nodeData.outputs?.output as string
+
+        const retriever = CustomRetriever.fromVectorStore(vectorStore, {
+            resultFormat,
+            topK: topK ? parseInt(topK, 10) : (vectorStore as any)?.k ?? 4
+        })
+
+        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 handleEscapeCharacters(finaltext, false)
+        }
+
+        return retriever
+    }
+}
+
+type RetrieverInput<V extends VectorStore> = Omit<VectorStoreRetrieverInput<V>, 'k'> & {
+    topK?: number
+    resultFormat?: string
+}
+
+class CustomRetriever<V extends VectorStore> extends VectorStoreRetriever<V> {
+    resultFormat: string
+    topK = 4
+
+    constructor(input: RetrieverInput<V>) {
+        super(input)
+        this.topK = input.topK ?? this.topK
+        this.resultFormat = input.resultFormat ?? this.resultFormat
+    }
+
+    async getRelevantDocuments(query: string): Promise<Document[]> {
+        const results = await this.vectorStore.similaritySearchWithScore(query, this.topK, this.filter)
+
+        const finalDocs: Document[] = []
+        for (const result of results) {
+            let res = this.resultFormat.replace(/{{context}}/g, result[0].pageContent)
+            res = replaceMetadata(res, result[0].metadata)
+            finalDocs.push(
+                new Document({
+                    pageContent: res,
+                    metadata: result[0].metadata
+                })
+            )
+        }
+        return finalDocs
+    }
+
+    static fromVectorStore<V extends VectorStore>(vectorStore: V, options: Omit<RetrieverInput<V>, 'vectorStore'>) {
+        return new this<V>({ ...options, vectorStore })
+    }
+}
+
+function replaceMetadata(template: string, metadata: Record<string, any>): string {
+    const metadataRegex = /{{metadata\.([\w.]+)}}/g
+
+    return template.replace(metadataRegex, (match, path) => {
+        const value = get(metadata, path)
+        return value !== undefined ? String(value) : match
+    })
+}
+
+module.exports = { nodeClass: CustomRetriever_Retrievers }