Merge pull request #512 from vjsai/opensearch

Added support for OpenSearch

packages/components/nodes/vectorstores/OpenSearch_Existing/OpenSearch_existing.ts

@@ -0,0 +1,95 @@
+import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
+import { OpenSearchVectorStore } from 'langchain/vectorstores/opensearch'
+import { Embeddings } from 'langchain/embeddings/base'
+import { Client } from '@opensearch-project/opensearch'
+import { getBaseClasses } from '../../../src/utils'
+
+class OpenSearch_Existing_VectorStores implements INode {
+    label: string
+    name: string
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    inputs: INodeParams[]
+    outputs: INodeOutputsValue[]
+
+    constructor() {
+        this.label = 'OpenSearch Load Existing Index'
+        this.name = 'openSearchExistingIndex'
+        this.type = 'OpenSearch'
+        this.icon = 'opensearch.png'
+        this.category = 'Vector Stores'
+        this.description = 'Load existing index from OpenSearch (i.e: Document has been upserted)'
+        this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
+        this.inputs = [
+            {
+                label: 'Embeddings',
+                name: 'embeddings',
+                type: 'Embeddings'
+            },
+            {
+                label: 'OpenSearch URL',
+                name: 'opensearchURL',
+                type: 'string',
+                placeholder: 'http://127.0.0.1:9200'
+            },
+            {
+                label: 'Index Name',
+                name: 'indexName',
+                type: 'string'
+            },
+            {
+                label: 'Top K',
+                name: 'topK',
+                description: 'Number of top results to fetch. Default to 4',
+                placeholder: '4',
+                type: 'number',
+                additionalParams: true,
+                optional: true
+            }
+        ]
+        this.outputs = [
+            {
+                label: 'OpenSearch Retriever',
+                name: 'retriever',
+                baseClasses: this.baseClasses
+            },
+            {
+                label: 'OpenSearch Vector Store',
+                name: 'vectorStore',
+                baseClasses: [this.type, ...getBaseClasses(OpenSearchVectorStore)]
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData): Promise<any> {
+        const embeddings = nodeData.inputs?.embeddings as Embeddings
+        const opensearchURL = nodeData.inputs?.opensearchURL as string
+        const indexName = nodeData.inputs?.indexName as string
+        const output = nodeData.outputs?.output as string
+        const topK = nodeData.inputs?.topK as string
+        const k = topK ? parseInt(topK, 10) : 4
+
+        const client = new Client({
+            nodes: [opensearchURL]
+        })
+
+        const vectorStore = new OpenSearchVectorStore(embeddings, {
+            client,
+            indexName
+        })
+
+        if (output === 'retriever') {
+            const retriever = vectorStore.asRetriever(k)
+            return retriever
+        } else if (output === 'vectorStore') {
+            ;(vectorStore as any).k = k
+            return vectorStore
+        }
+        return vectorStore
+    }
+}
+
+module.exports = { nodeClass: OpenSearch_Existing_VectorStores }

packages/components/nodes/vectorstores/OpenSearch_Upsert/OpenSearch_Upsert.ts

@@ -0,0 +1,110 @@
+import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
+import { OpenSearchVectorStore } from 'langchain/vectorstores/opensearch'
+import { Embeddings } from 'langchain/embeddings/base'
+import { Document } from 'langchain/document'
+import { Client } from '@opensearch-project/opensearch'
+import { flatten } from 'lodash'
+import { getBaseClasses } from '../../../src/utils'
+
+class OpenSearchUpsert_VectorStores implements INode {
+    label: string
+    name: string
+    description: string
+    type: string
+    icon: string
+    category: string
+    baseClasses: string[]
+    inputs: INodeParams[]
+    outputs: INodeOutputsValue[]
+
+    constructor() {
+        this.label = 'OpenSearch Upsert Document'
+        this.name = 'openSearchUpsertDocument'
+        this.type = 'OpenSearch'
+        this.icon = 'opensearch.png'
+        this.category = 'Vector Stores'
+        this.description = 'Upsert documents to OpenSearch'
+        this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
+        this.inputs = [
+            {
+                label: 'Document',
+                name: 'document',
+                type: 'Document',
+                list: true
+            },
+            {
+                label: 'Embeddings',
+                name: 'embeddings',
+                type: 'Embeddings'
+            },
+            {
+                label: 'OpenSearch URL',
+                name: 'opensearchURL',
+                type: 'string',
+                placeholder: 'http://127.0.0.1:9200'
+            },
+            {
+                label: 'Index Name',
+                name: 'indexName',
+                type: 'string'
+            },
+            {
+                label: 'Top K',
+                name: 'topK',
+                description: 'Number of top results to fetch. Default to 4',
+                placeholder: '4',
+                type: 'number',
+                additionalParams: true,
+                optional: true
+            }
+        ]
+        this.outputs = [
+            {
+                label: 'OpenSearch Retriever',
+                name: 'retriever',
+                baseClasses: this.baseClasses
+            },
+            {
+                label: 'OpenSearch Vector Store',
+                name: 'vectorStore',
+                baseClasses: [this.type, ...getBaseClasses(OpenSearchVectorStore)]
+            }
+        ]
+    }
+
+    async init(nodeData: INodeData): Promise<any> {
+        const docs = nodeData.inputs?.document as Document[]
+        const embeddings = nodeData.inputs?.embeddings as Embeddings
+        const opensearchURL = nodeData.inputs?.opensearchURL as string
+        const indexName = nodeData.inputs?.indexName as string
+        const output = nodeData.outputs?.output as string
+        const topK = nodeData.inputs?.topK as string
+        const k = topK ? parseInt(topK, 10) : 4
+
+        const flattenDocs = docs && docs.length ? flatten(docs) : []
+        const finalDocs = []
+        for (let i = 0; i < flattenDocs.length; i += 1) {
+            finalDocs.push(new Document(flattenDocs[i]))
+        }
+
+        const client = new Client({
+            nodes: [opensearchURL]
+        })
+
+        const vectorStore = await OpenSearchVectorStore.fromDocuments(finalDocs, embeddings, {
+            client,
+            indexName: indexName
+        })
+
+        if (output === 'retriever') {
+            const retriever = vectorStore.asRetriever(k)
+            return retriever
+        } else if (output === 'vectorStore') {
+            ;(vectorStore as any).k = k
+            return vectorStore
+        }
+        return vectorStore
+    }
+}
+
+module.exports = { nodeClass: OpenSearchUpsert_VectorStores }

packages/components/package.json

@@ -20,6 +20,7 @@
         "@dqbd/tiktoken": "^1.0.7",
         "@getzep/zep-js": "^0.3.1",
         "@huggingface/inference": "^2.6.1",
+        "@opensearch-project/opensearch": "^1.2.0",
         "@pinecone-database/pinecone": "^0.0.12",
         "@qdrant/js-client-rest": "^1.2.2",
         "@supabase/supabase-js": "^2.21.0",