release-to-lemonade-hq

.yarnrc.yml

@@ -1,5 +1,7 @@
 nodeLinker: node-modules
 
+npmRegistryServer: "https://npm.pkg.github.com/lemonade-hq"
+
 plugins:
   - path: .yarn/plugins/@yarnpkg/plugin-typescript.cjs
     spec: "@yarnpkg/plugin-typescript"

docs/docs/modules/indexes/vector_stores/integrations/opensearch.md

@@ -0,0 +1,103 @@
+# OpenSearch
+
+Langchain.js accepts [@opensearch-project/opensearch](https://opensearch.org/docs/latest/clients/javascript/index/)
+as the client for OpenSearch vectorstore. Install the client with
+
+```bash npm2yarn
+npm install -S dotenv langchain @opensearch-project/opensearch
+```
+
+## Index docs
+
+```typescript
+import { Client } from "@opensearch-project/opensearch";
+import * as dotenv from "dotenv";
+import { Document } from "langchain/document";
+import { OpenAIEmbeddings } from "langchain/embeddings";
+import { OpenSearchVectorStore } from "langchain/vectorstores";
+
+dotenv.config();
+
+const client = new Client({
+  nodes: [process.env.OPENSEARCH_URL ?? "http://127.0.0.1:9200"],
+});
+
+const docs = [
+  new Document({
+    metadata: { foo: "bar" },
+    pageContent: "opensearch is also a vector db",
+  }),
+  new Document({
+    metadata: { foo: "bar" },
+    pageContent: "the quick brown fox jumped over the lazy dog",
+  }),
+  new Document({
+    metadata: { baz: "qux" },
+    pageContent: "lorem ipsum dolor sit amet",
+  }),
+  new Document({
+    metadata: { baz: "qux" },
+    pageContent: "OpenSearch is a scalable, flexible, and extensible open-source software suite for search, analytics, and observability applications",
+  }),
+];
+
+await OpenSearchVectorStore.fromDocuments(docs, new OpenAIEmbeddings(), {
+  client,
+  indexName: process.env.OPENSEARCH_INDEX, // Will default to `documents`
+});
+```
+
+## Query docs
+
+```typescript
+import { Client } from "@opensearch-project/opensearch";
+import * as dotenv from "dotenv";
+import { VectorDBQAChain } from "langchain/chains";
+import { OpenAIEmbeddings } from "langchain/embeddings";
+import { OpenAI } from "langchain/llms";
+import { OpenSearchVectorStore } from "langchain/vectorstores";
+
+dotenv.config();
+
+const client = new Client({
+  nodes: [process.env.OPENSEARCH_URL ?? "http://127.0.0.1:9200"],
+});
+
+const vectorStore = new OpenSearchVectorStore(new OpenAIEmbeddings(), {
+  client,
+});
+
+/* Search the vector DB independently with meta filters */
+const results = await vectorStore.similaritySearch("hello world", 1);
+console.log(JSON.stringify(results, null, 2));
+/* [
+    {
+      "pageContent": "Hello world",
+      "metadata": {
+        "id": 2
+      }
+    }
+  ] */
+
+/* Use as part of a chain (currently no metadata filters) */
+const model = new OpenAI();
+const chain = VectorDBQAChain.fromLLM(model, vectorStore, {
+  k: 1,
+  returnSourceDocuments: true,
+});
+const response = await chain.call({ query: "What is opensearch?" });
+console.log(JSON.stringify(response, null, 2));
+/* 
+  {
+    "text": " Opensearch is a collection of technologies that allow search engines to publish search results in a standard format, making it easier for users to search across multiple sites.",
+    "sourceDocuments": [
+      {
+        "pageContent": "What's this?",
+        "metadata": {
+          "id": 3
+        }
+      }
+    ]
+  } 
+  */
+```

examples/.env.example

@@ -2,6 +2,7 @@ ANTHROPIC_API_KEY=ADD_YOURS_HERE
 COHERE_API_KEY=ADD_YOURS_HERE
 HUGGINGFACEHUB_API_KEY=ADD_YOURS_HERE
 OPENAI_API_KEY=ADD_YOURS_HERE
+OPENSEARCH_URL=http://127.0.0.1:9200
 PINECONE_API_KEY=ADD_YOURS_HERE
 PINECONE_ENVIRONMENT=ADD_YOURS_HERE
 PINECONE_INDEX=ADD_YOURS_HERE

examples/package.json

@@ -24,6 +24,7 @@
   "dependencies": {
     "@dqbd/tiktoken": "^1.0.2",
     "@getmetal/metal-sdk": "^1.0.12",
+    "@opensearch-project/opensearch": "^2.2.0",
     "@pinecone-database/pinecone": "^0.0.10",
     "@prisma/client": "^4.11.0",
     "@supabase/supabase-js": "^2.10.0",

examples/src/indexes/vector_stores/opensearch/docker-compose.yml

@@ -0,0 +1,42 @@
+# Reference:
+#   https://opensearch.org/docs/latest/install-and-configure/install-opensearch/docker/#sample-docker-composeyml
+version: '3'
+services:
+  opensearch:
+    image: opensearchproject/opensearch:2.6.0
+    container_name: opensearch
+    environment:
+      - cluster.name=opensearch
+      - node.name=opensearch
+      - discovery.type=single-node
+      - bootstrap.memory_lock=true
+      - "OPENSEARCH_JAVA_OPTS=-Xms512m -Xmx512m"
+      - "DISABLE_INSTALL_DEMO_CONFIG=true"
+      - "DISABLE_SECURITY_PLUGIN=true"
+    ulimits:
+      memlock:
+        soft: -1
+        hard: -1
+    volumes:
+      - opensearch_data:/usr/share/opensearch/data
+    ports:
+      - 9200:9200
+      - 9600:9600
+    networks:
+      - opensearch
+  opensearch-dashboards:
+    image: opensearchproject/opensearch-dashboards:latest # Make sure the version of opensearch-dashboards matches the version of opensearch installed on other nodes
+    container_name: opensearch-dashboards
+    ports:
+      - 5601:5601 # Map host port 5601 to container port 5601
+    expose:
+      - "5601" # Expose port 5601 for web access to OpenSearch Dashboards
+    environment:
+      OPENSEARCH_HOSTS: '["http://opensearch:9200"]' # Define the OpenSearch nodes that OpenSearch Dashboards will query
+      DISABLE_SECURITY_DASHBOARDS_PLUGIN: "true" # disables security dashboards plugin in OpenSearch Dashboards
+    networks:
+      - opensearch
+networks:
+  opensearch:
+volumes:
+  opensearch_data:

examples/src/indexes/vector_stores/opensearch/opensearch.ts

@@ -0,0 +1,24 @@
+// Run with: yarn example src/indexes/vector_stores/opensearch/opensearch.ts
+
+import { Client } from "@opensearch-project/opensearch";
+import { OpenAIEmbeddings } from "langchain/embeddings";
+import { OpenSearchVectorStore } from "langchain/vectorstores";
+
+export async function run() {
+  const client = new Client({
+    nodes: [process.env.OPENSEARCH_URL ?? "http://127.0.0.1:9200"],
+  });
+
+  const vectorStore = await OpenSearchVectorStore.fromTexts(
+    ["Hello world", "Bye bye", "What's this?"],
+    [{ id: 2 }, { id: 1 }, { id: 3 }],
+    new OpenAIEmbeddings(),
+    {
+      client,
+      indexName: "documents",
+    }
+  );
+
+  const resultOne = await vectorStore.similaritySearch("Hello world", 1);
+  console.log(resultOne);
+}

langchain/.env.example

@@ -2,6 +2,7 @@ ANTHROPIC_API_KEY=ADD_YOURS_HERE
 COHERE_API_KEY=ADD_YOURS_HERE
 HUGGINGFACEHUB_API_KEY=ADD_YOURS_HERE
 OPENAI_API_KEY=ADD_YOURS_HERE
+OPENSEARCH_URL=http://127.0.0.1:9200
 PINECONE_API_KEY=ADD_YOURS_HERE
 PINECONE_ENVIRONMENT=ADD_YOURS_HERE
 PINECONE_INDEX=ADD_YOURS_HERE

langchain/package.json

@@ -76,7 +76,7 @@
   ],
   "repository": {
     "type": "git",
-    "url": "[email protected]:hwchase17/langchainjs.git"
+    "url": "[email protected]:lemonade-hq/langchainjs.git"
   },
   "scripts": {
     "build": "yarn clean && yarn build:esm && yarn build:cjs && node scripts/create-entrypoints.js && node scripts/check-tree-shaking.js",
@@ -106,6 +106,7 @@
     "@getmetal/metal-sdk": "^1.0.12",
     "@huggingface/inference": "^1.5.1",
     "@jest/globals": "^29.5.0",
+    "@opensearch-project/opensearch": "^2.2.0",
     "@pinecone-database/pinecone": "^0.0.10",
     "@supabase/supabase-js": "^2.10.0",
     "@tsconfig/recommended": "^1.0.2",
@@ -153,6 +154,7 @@
     "@dqbd/tiktoken": "^1.0.2",
     "@getmetal/metal-sdk": "*",
     "@huggingface/inference": "^1.5.1",
+    "@opensearch-project/opensearch": "*",
     "@pinecone-database/pinecone": "^0.0.10",
     "@supabase/supabase-js": "^2.10.0",
     "cheerio": "^1.0.0-rc.12",
@@ -246,7 +248,8 @@
     "zod": "^3.21.4"
   },
   "publishConfig": {
-    "access": "public"
+    "access": "public",
+    "registry": "https://npm.pkg.github.com/lemonade-hq"
   },
   "keywords": [
     "llm",
@@ -370,4 +373,4 @@
     },
     "./package.json": "./package.json"
   }
-}
+}

langchain/src/vectorstores/index.ts

@@ -4,3 +4,4 @@ export { PineconeStore } from "./pinecone.js";
 export { VectorStore, SaveableVectorStore } from "./base.js";
 export { SupabaseVectorStore } from "./supabase.js";
 export { PrismaVectorStore } from "./prisma.js";
+export { OpenSearchVectorStore } from "./opensearch.js";