Merge branch 'main' of https://github.com/langchain-ai/langchainjs in…

…to brace/agent-stream-example

docs/core_docs/docs/integrations/vectorstores/xata.mdx

@@ -17,7 +17,7 @@ npm install @xata.io/cli -g
 In the [Xata UI](https://app.xata.io) create a new database. You can name it whatever you want, but for this example we'll use `langchain`.
 Create a table, again you can name it anything, but we will use `vectors`. Add the following columns via the UI:
 
-- `content` of type "Long text". This is used to store the `Document.pageContent` values.
+- `content` of type "Text". This is used to store the `Document.pageContent` values.
 - `embedding` of type "Vector". Use the dimension used by the model you plan to use (1536 for OpenAI).
 - any other columns you want to use as metadata. They are populated from the `Document.metadata` object. For example, if in the `Document.metadata` object you have a `title` property, you can create a `title` column in the table and it will be populated.
 

langchain/package.json

@@ -944,7 +944,7 @@
     "@vercel/kv": "^0.2.3",
     "@vercel/postgres": "^0.5.0",
     "@writerai/writer-sdk": "^0.40.2",
-    "@xata.io/client": "^0.25.1",
+    "@xata.io/client": "^0.28.0",
     "@xenova/transformers": "^2.5.4",
     "@zilliz/milvus2-sdk-node": ">=2.2.11",
     "apify-client": "^2.7.1",
@@ -1066,7 +1066,7 @@
     "@vercel/kv": "^0.2.3",
     "@vercel/postgres": "^0.5.0",
     "@writerai/writer-sdk": "^0.40.2",
-    "@xata.io/client": "^0.25.1",
+    "@xata.io/client": "^0.28.0",
     "@xenova/transformers": "^2.5.4",
     "@zilliz/milvus2-sdk-node": ">=2.2.7",
     "apify-client": "^2.7.1",

langchain/src/vectorstores/tests/xata.int.test.ts

@@ -6,6 +6,11 @@ import { XataVectorSearch } from "../xata.js";
 import { OpenAIEmbeddings } from "../../embeddings/openai.js";
 import { Document } from "../../document.js";
 
+// Tests require a DB with a table called "docs" with:
+// * a column name content of type Text
+// * a column named embedding of type Vector
+// * a column named a of type Integer
+
 test.skip("XataVectorSearch integration", async () => {
   if (!process.env.XATA_API_KEY) {
     throw new Error("XATA_API_KEY not set");

langchain/src/vectorstores/xata.ts

@@ -118,7 +118,7 @@ export class XataVectorSearch<
     k: number,
     filter?: XataFilter | undefined
   ): Promise<[Document, number][]> {
-    const records = await this.client.db[this.table].vectorSearch(
+    const { records } = await this.client.db[this.table].vectorSearch(
       "embedding",
       query,
       {

yarn.lock

@@ -12665,6 +12665,15 @@ __metadata:
   languageName: node
   linkType: hard
 
+"@xata.io/client@npm:^0.28.0":
+  version: 0.28.0
+  resolution: "@xata.io/client@npm:0.28.0"
+  peerDependencies:
+    typescript: ">=4.5"
+  checksum: 39dbf590c320ba49623f44ab1124fb084f08f2820d04bc1f7c20459304ac4008227964ce4e5d9bf1ab34828c7d3fa3afb50f3455a1f37a981238463ae4289036
+  languageName: node
+  linkType: hard
+
 "@xenova/transformers@npm:^2.5.4":
   version: 2.5.4
   resolution: "@xenova/transformers@npm:2.5.4"
@@ -22690,7 +22699,7 @@ __metadata:
     "@vercel/kv": ^0.2.3
     "@vercel/postgres": ^0.5.0
     "@writerai/writer-sdk": ^0.40.2
-    "@xata.io/client": ^0.25.1
+    "@xata.io/client": ^0.28.0
     "@xenova/transformers": ^2.5.4
     "@zilliz/milvus2-sdk-node": ">=2.2.11"
     apify-client: ^2.7.1
@@ -22827,7 +22836,7 @@ __metadata:
     "@vercel/kv": ^0.2.3
     "@vercel/postgres": ^0.5.0
     "@writerai/writer-sdk": ^0.40.2
-    "@xata.io/client": ^0.25.1
+    "@xata.io/client": ^0.28.0
     "@xenova/transformers": ^2.5.4
     "@zilliz/milvus2-sdk-node": ">=2.2.7"
     apify-client: ^2.7.1