chore(community): Deprecate CouchbaseVectorStore and create CouchbaseSearchVectorStore

.changeset/chubby-guests-sink.md

@@ -0,0 +1,5 @@
+---
+"@langchain/community": patch
+---
+
+chore(couchbase): Deprecate CouchbaseVectorStore and create CouchbaseSearchVectorStore

docs/core_docs/docs/integrations/vectorstores/couchbase.mdx

@@ -144,11 +144,11 @@ For more details on how to create a search index with support for Vector fields,
 - [Couchbase Capella](https://docs.couchbase.com/cloud/search/create-search-indexes.html)
 - [Couchbase Server](https://docs.couchbase.com/server/current/search/create-search-indexes.html)
 
-For using this vector store, CouchbaseVectorStoreArgs needs to be configured.
+For using this vector store, CouchbaseSearchVectorStoreArgs needs to be configured.
 textKey and embeddingKey are optional fields, required if you want to use specific keys
 
 ```typescript
-const couchbaseConfig: CouchbaseVectorStoreArgs = {
+const couchbaseConfig: CouchbaseSearchVectorStoreArgs = {
   cluster: couchbaseClient,
   bucketName: "testing",
   scopeName: "_default",
@@ -164,7 +164,7 @@ const couchbaseConfig: CouchbaseVectorStoreArgs = {
 We create the vector store object with the cluster information and the search index name.
 
 ```typescript
-const store = await CouchbaseVectorStore.initialize(
+const store = await CouchbaseSearchVectorStore.initialize(
   embeddings, // embeddings object to create embeddings from text
   couchbaseConfig
 );
@@ -183,9 +183,9 @@ At the end, it also shows how to get similarity score
 ```ts
 import { OpenAIEmbeddings } from "@langchain/openai";
 import {
-  CouchbaseVectorStoreArgs,
-  CouchbaseVectorStore,
-} from "@langchain/community/vectorstores/couchbase";
+  CouchbaseSearchVectorStoreArgs,
+  CouchbaseSearchVectorStore,
+} from "@langchain/community/vectorstores/couchbase_search";
 import { Cluster } from "couchbase";
 import { TextLoader } from "langchain/document_loaders/fs/text";
 import { CharacterTextSplitter } from "@langchain/textsplitters";
@@ -215,7 +215,7 @@ const embeddings = new OpenAIEmbeddings({
   apiKey: process.env.OPENAI_API_KEY,
 });
 
-const couchbaseConfig: CouchbaseVectorStoreArgs = {
+const couchbaseConfig: CouchbaseSearchVectorStoreArgs = {
   cluster: couchbaseClient,
   bucketName: "testing",
   scopeName: "_default",
@@ -225,7 +225,7 @@ const couchbaseConfig: CouchbaseVectorStoreArgs = {
   embeddingKey: "embedding",
 };
 
-const store = await CouchbaseVectorStore.fromDocuments(
+const store = await CouchbaseSearchVectorStore.fromDocuments(
   docs,
   embeddings,
   couchbaseConfig
@@ -291,7 +291,7 @@ for (let i = 0; i < docs.length; i += 1) {
   docs[i].metadata.author = ["John Doe", "Jane Doe"][i % 2];
 }
 
-const store = await CouchbaseVectorStore.fromDocuments(
+const store = await CouchbaseSearchVectorStore.fromDocuments(
   docs,
   embeddings,
   couchbaseConfig
@@ -405,9 +405,9 @@ Please refer to the documentation for more details on the available query method
 
 # Frequently Asked Questions
 
-## Question: Should I create the Search index before creating the CouchbaseVectorStore object?
+## Question: Should I create the Search index before creating the CouchbaseSearchVectorStore object?
 
-Yes, currently you need to create the Search index before creating the `CouchbaseVectorStore` object.
+Yes, currently you need to create the Search index before creating the `CouchbaseSearchVectorStore` object.
 
 ## Question: I am not seeing all the fields that I specified in my search results.
 

docs/core_docs/src/theme/FeatureTables.js

@@ -622,8 +622,8 @@ const FEATURE_TABLES = {
         idsInAddDocuments: false,
       },
       {
-        name: "CouchbaseVectorStore",
-        link: "couchbase",
+        name: "CouchbaseSearchVectorStore",
+        link: "couchbase_search",
         deleteById: true,
         filtering: true,
         searchByVector: false,

libs/langchain-community/.gitignore

@@ -382,6 +382,10 @@ vectorstores/couchbase.cjs
 vectorstores/couchbase.js
 vectorstores/couchbase.d.ts
 vectorstores/couchbase.d.cts
+vectorstores/couchbase_search.cjs
+vectorstores/couchbase_search.js
+vectorstores/couchbase_search.d.ts
+vectorstores/couchbase_search.d.cts
 vectorstores/elasticsearch.cjs
 vectorstores/elasticsearch.js
 vectorstores/elasticsearch.d.ts

libs/langchain-community/langchain.config.js

@@ -134,6 +134,7 @@ export const config = {
     "vectorstores/cloudflare_vectorize": "vectorstores/cloudflare_vectorize",
     "vectorstores/convex": "vectorstores/convex",
     "vectorstores/couchbase": "vectorstores/couchbase",
+    "vectorstores/couchbase_search": "vectorstores/couchbase_search",
     "vectorstores/elasticsearch": "vectorstores/elasticsearch",
     "vectorstores/faiss": "vectorstores/faiss",
     "vectorstores/googlevertexai": "vectorstores/googlevertexai",

libs/langchain-community/package.json

@@ -152,7 +152,7 @@
     "closevector-web": "0.1.6",
     "cohere-ai": ">=6.0.0",
     "convex": "^1.3.1",
-    "couchbase": "^4.3.0",
+    "couchbase": "^4.4.6",
     "crypto-js": "^4.2.0",
     "d3-dsv": "^2.0.0",
     "datastore-core": "^9.2.9",
@@ -1592,6 +1592,15 @@
       "import": "./vectorstores/couchbase.js",
       "require": "./vectorstores/couchbase.cjs"
     },
+    "./vectorstores/couchbase_search": {
+      "types": {
+        "import": "./vectorstores/couchbase_search.d.ts",
+        "require": "./vectorstores/couchbase_search.d.cts",
+        "default": "./vectorstores/couchbase_search.d.ts"
+      },
+      "import": "./vectorstores/couchbase_search.js",
+      "require": "./vectorstores/couchbase_search.cjs"
+    },
     "./vectorstores/elasticsearch": {
       "types": {
         "import": "./vectorstores/elasticsearch.d.ts",
@@ -3663,6 +3672,10 @@
     "vectorstores/couchbase.js",
     "vectorstores/couchbase.d.ts",
     "vectorstores/couchbase.d.cts",
+    "vectorstores/couchbase_search.cjs",
+    "vectorstores/couchbase_search.js",
+    "vectorstores/couchbase_search.d.ts",
+    "vectorstores/couchbase_search.d.cts",
     "vectorstores/elasticsearch.cjs",
     "vectorstores/elasticsearch.js",
     "vectorstores/elasticsearch.d.ts",

libs/langchain-community/src/load/import_map.ts

@@ -43,6 +43,7 @@ export * as llms__friendli from "../llms/friendli.js";
 export * as llms__ollama from "../llms/ollama.js";
 export * as llms__togetherai from "../llms/togetherai.js";
 export * as llms__yandex from "../llms/yandex.js";
+export * as vectorstores__couchbase_search from "../vectorstores/couchbase_search.js";
 export * as vectorstores__prisma from "../vectorstores/prisma.js";
 export * as vectorstores__turbopuffer from "../vectorstores/turbopuffer.js";
 export * as vectorstores__vectara from "../vectorstores/vectara.js";

libs/langchain-community/src/vectorstores/couchbase.ts

@@ -16,27 +16,15 @@ import { Document } from "@langchain/core/documents";
 import { v4 as uuid } from "uuid";
 
 /**
- * This interface define the optional fields for adding vector
- * - `ids` - vector of ids for each document. If undefined, then uuid will be used
- * - `metadata` - vector of metadata object for each document
+ * @deprecated This interface has been relocated to `@langchain/community/vectorstores/couchbase_search`. This interface will be removed in a future release.
  */
 export interface AddVectorOptions {
   ids?: string[];
   metadata?: Record<string, any>[];
 }
 
 /**
- * This interface defines the fields required to initialize a vector store
- * These are the fields part of config:
- * @property {Cluster} cluster - The Couchbase cluster that the store will interact with.
- * @property {string} bucketName - The name of the bucket in the Couchbase cluster.
- * @property {string} scopeName - The name of the scope within the bucket.
- * @property {string} collectionName - The name of the collection within the scope.
- * @property {string} indexName - The name of the index to be used for vector search.
- * @property {string} textKey - The key to be used for text in the documents. Defaults to "text".
- * @property {string} embeddingKey - The key to be used for embeddings in the documents. Defaults to "embedding".
- * @property {boolean} scopedIndex - Whether to use a scoped index for vector search. Defaults to true.
- * @property {AddVectorOptions} addVectorOptions - Options for adding vectors with specific id/metadata
+ * @deprecated Use CouchbaseSearchVectorStoreArgs from `@langchain/community/vectorstores/couchbase_search` instead. This interface will be removed in a future release.
  */
 export interface CouchbaseVectorStoreArgs {
   cluster: Cluster;
@@ -63,10 +51,7 @@ type CouchbaseVectorStoreFilter = {
 };
 
 /**
- * Class for interacting with the Couchbase database. It extends the
- * VectorStore class and provides methods for adding vectors and
- * documents, and searching for similar vectors.
- * Initiate the class using initialize() method.
+ * @deprecated Use CouchbaseSearchVectorStore from `@langchain/community/vectorstores/couchbase_search` instead. This class will be removed in a future release.
  */
 export class CouchbaseVectorStore extends VectorStore {
   declare FilterType: CouchbaseVectorStoreFilter;