@langchain/community/dist/vectorstores/tests/vercel_postgres.int.test.js

Third-party integrations for LangChain.js

import { expect, test } from "@jest/globals";
import { OpenAIEmbeddings } from "@langchain/openai";
import { VercelPostgres } from "../vercel_postgres.js";
let vercelPostgresStore;
const config = {
    tableName: "testvercelvectorstorelangchain2",
    columns: {
        idColumnName: "id",
        vectorColumnName: "vector",
        contentColumnName: "content",
        metadataColumnName: "metadata",
    },
};
describe("Test VercelPostgres store", () => {
    afterEach(async () => {
        await vercelPostgresStore?.delete({ deleteAll: true });
        await vercelPostgresStore?.end();
    });
    test("Test embeddings creation", async () => {
        vercelPostgresStore = await VercelPostgres.initialize(new OpenAIEmbeddings(), config);
        expect(vercelPostgresStore).toBeDefined();
        const docHello = {
            pageContent: "hello",
            metadata: { a: 1 },
        };
        const docCat = {
            pageContent: "Cat drinks milk",
            metadata: { a: 2 },
        };
        const docHi = { pageContent: "hi", metadata: { a: 1 } };
        const ids = await vercelPostgresStore.addDocuments([
            docHello,
            docHi,
            docCat,
        ]);
        const results = await vercelPostgresStore.similaritySearch("hello", 2, {
            a: 2,
        });
        expect(results).toHaveLength(1);
        expect(results[0].pageContent).toEqual(docCat.pageContent);
        await vercelPostgresStore.addDocuments([{ pageContent: "Dog drinks milk", metadata: { a: 2 } }], { ids: [ids[2]] });
        const results2 = await vercelPostgresStore.similaritySearch("hello", 2, {
            a: 2,
        });
        expect(results2).toHaveLength(1);
        expect(results2[0].pageContent).toEqual("Dog drinks milk");
        await vercelPostgresStore.delete({ ids: [ids[2]] });
        const results3 = await vercelPostgresStore.similaritySearch("hello", 2, {
            a: 2,
        });
        expect(results3).toHaveLength(0);
    });
    test("Test metadata filtering", async () => {
        vercelPostgresStore = await VercelPostgres.initialize(new OpenAIEmbeddings(), config);
        const docGreen = {
            pageContent: "Hi, I am the color green.",
            metadata: { color: "green" },
        };
        const docBlue = {
            pageContent: "Hi, I am the color blue.",
            metadata: { color: "blue" },
        };
        const docYellow = {
            pageContent: "Hi, I am the color yellow.",
            metadata: { color: "yellow" },
        };
        const docIrrelevant = {
            pageContent: "Hi, I am an irrelevant doc without metadata.",
            metadata: {},
        };
        await vercelPostgresStore.addDocuments([
            docGreen,
            docBlue,
            docYellow,
            docIrrelevant,
        ]);
        const results1 = await vercelPostgresStore.similaritySearch("color", 5, {
            color: "blue",
        });
        expect(results1).toHaveLength(1);
        const results2 = await vercelPostgresStore.similaritySearch("irrelevant query", 5, {
            color: { in: ["blue", "yellow"] },
        });
        expect(results2).toHaveLength(2);
        const results2WithColorGreen = results2.filter((result) => result.metadata.color === "green");
        expect(results2WithColorGreen).toHaveLength(0);
    });
});