Revert "Bugfix/OpenSearch illegal invocation"

packages/components/nodes/vectorstores/OpenSearch/core.ts

@@ -1,8 +0,0 @@
-export const buildMetadataTerms = (filter?: object): { term: Record<string, unknown> }[] => {
-    if (filter == null) return []
-    const result = []
-    for (const [key, value] of Object.entries(filter)) {
-        result.push({ term: { [`metadata.${key}`]: value } })
-    }
-    return result
-}

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

@@ -1,10 +1,8 @@
 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, RequestParams } from '@opensearch-project/opensearch'
+import { Client } from '@opensearch-project/opensearch'
 import { getBaseClasses } from '../../../src/utils'
-import { buildMetadataTerms } from './core'
 
 class OpenSearch_Existing_VectorStores implements INode {
     label: string
@@ -44,13 +42,6 @@ class OpenSearch_Existing_VectorStores implements INode {
                 name: 'indexName',
                 type: 'string'
             },
-            {
-                label: 'OpenSearch Metadata Filter',
-                name: 'openSearchMetadataFilter',
-                type: 'json',
-                optional: true,
-                additionalParams: true
-            },
             {
                 label: 'Top K',
                 name: 'topK',
@@ -82,7 +73,6 @@ class OpenSearch_Existing_VectorStores implements INode {
         const output = nodeData.outputs?.output as string
         const topK = nodeData.inputs?.topK as string
         const k = topK ? parseFloat(topK) : 4
-        const openSearchMetadataFilter = nodeData.inputs?.openSearchMetadataFilter
 
         const client = new Client({
             nodes: [opensearchURL]
@@ -93,46 +83,6 @@ class OpenSearch_Existing_VectorStores implements INode {
             indexName
         })
 
-        vectorStore.similaritySearchVectorWithScore = async (
-            query: number[],
-            k: number,
-            filter?: object | undefined
-        ): Promise<[Document, number][]> => {
-            if (openSearchMetadataFilter) {
-                const metadatafilter =
-                    typeof openSearchMetadataFilter === 'object' ? openSearchMetadataFilter : JSON.parse(openSearchMetadataFilter)
-                filter = metadatafilter
-            }
-            const search: RequestParams.Search = {
-                index: indexName,
-                body: {
-                    query: {
-                        bool: {
-                            filter: { bool: { must: buildMetadataTerms(filter) } },
-                            must: [
-                                {
-                                    knn: {
-                                        embedding: { vector: query, k }
-                                    }
-                                }
-                            ]
-                        }
-                    },
-                    size: k
-                }
-            }
-
-            const { body } = await client.search(search)
-
-            return body.hits.hits.map((hit: any) => [
-                new Document({
-                    pageContent: hit._source.text,
-                    metadata: hit._source.metadata
-                }),
-                hit._score
-            ])
-        }
-
         if (output === 'retriever') {
             const retriever = vectorStore.asRetriever(k)
             return retriever

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

@@ -2,10 +2,9 @@ import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/I
 import { OpenSearchVectorStore } from 'langchain/vectorstores/opensearch'
 import { Embeddings } from 'langchain/embeddings/base'
 import { Document } from 'langchain/document'
-import { Client, RequestParams } from '@opensearch-project/opensearch'
+import { Client } from '@opensearch-project/opensearch'
 import { flatten } from 'lodash'
 import { getBaseClasses } from '../../../src/utils'
-import { buildMetadataTerms } from './core'
 
 class OpenSearchUpsert_VectorStores implements INode {
     label: string
@@ -96,44 +95,9 @@ class OpenSearchUpsert_VectorStores implements INode {
 
         const vectorStore = await OpenSearchVectorStore.fromDocuments(finalDocs, embeddings, {
             client,
-            indexName
+            indexName: indexName
         })
 
-        vectorStore.similaritySearchVectorWithScore = async (
-            query: number[],
-            k: number,
-            filter?: object | undefined
-        ): Promise<[Document, number][]> => {
-            const search: RequestParams.Search = {
-                index: indexName,
-                body: {
-                    query: {
-                        bool: {
-                            filter: { bool: { must: buildMetadataTerms(filter) } },
-                            must: [
-                                {
-                                    knn: {
-                                        embedding: { vector: query, k }
-                                    }
-                                }
-                            ]
-                        }
-                    },
-                    size: k
-                }
-            }
-
-            const { body } = await client.search(search)
-
-            return body.hits.hits.map((hit: any) => [
-                new Document({
-                    pageContent: hit._source.text,
-                    metadata: hit._source.metadata
-                }),
-                hit._score
-            ])
-        }
-
         if (output === 'retriever') {
             const retriever = vectorStore.asRetriever(k)
             return retriever