import "fake-indexeddb/auto";
import { describe, it, expect } from 'vitest';
import { CloseVectorHNSWWeb } from '../src/hnswlibWasm';
import { FakeEmbeddings } from 'closevector-common/src/fake';
import { createUploadFileOperationUrl, createGetFileOperationUrl } from "../src/lib";

function sleep(ms: number) {
    return new Promise((resolve) => {
        setTimeout(resolve, ms);
    });
}

describe('CloseVectorHNSWWeb', () => {
    it('Test HNSWLib.fromTexts + addVectors', async () => {
        const vectorStore = await CloseVectorHNSWWeb.fromTexts(
            ['Hello world'],
            [{ id: 2 }],
            new FakeEmbeddings()
        );

        expect(vectorStore.index.getMaxElements()).toBe(1);
        expect(vectorStore.index.getCurrentCount()).toBe(1);

        await vectorStore.addVectors(
            [
                [0, 1, 0, 0],
                [1, 0, 0, 0],
                [0.5, 0.5, 0.5, 0.5],
            ],
            [
                {
                    pageContent: 'hello bye',
                    metadata: { id: 5 },
                },
                {
                    pageContent: 'hello worlddwkldnsk',
                    metadata: { id: 4 },
                },
                {
                    pageContent: 'hello you',
                    metadata: { id: 6 },
                },
            ]
        );
        expect(vectorStore.index.getMaxElements()).toBe(4);

        const resultTwo = await vectorStore.similaritySearchVectorWithScore([1, 0, 0, 0], 3);

        const resultTwoMetadatas = resultTwo.map(([{ metadata }]) => metadata);
        expect(resultTwoMetadatas).toEqual([{ id: 4 }, { id: 6 }, { id: 2 }]);
    });

    it('Test HNSWLib metadata filtering', async () => {
        const pageContent = 'Hello world';

        const vectorStore = await CloseVectorHNSWWeb.fromTexts(
            [pageContent, pageContent, pageContent],
            [{ id: 2 }, { id: 3 }, { id: 4 }],
            new FakeEmbeddings()
        );

        // If the filter wasn't working, we'd get all 3 documents back
        const results = await vectorStore.similaritySearch(
            pageContent,
            3,
            (document: any) => document.metadata.id === 3
        );

        expect(results).toEqual([{ metadata: { id: 3 }, pageContent }]);
    });

    it('Should save for load to or from cloud', async () => {
        const CLOSEVECTOR_KEY = "8b531157cbb0965e2954b33eae7f56e77f9d3128a5508615162704f340b71d48";
        const CLOSEVECTOR_SECRET = "6b27799b7412d5cdb98bb1cfb6d4406af3eb0c55303684794bbb3999ad6fcfad";
        const DATA_STORE_KEY = "file-8b531157cbb0965e2954b33eae7f56e77f9d3128a5508615162704f340b71d48-0389721c-4a68-4c40-95c4-a1ff016fba3e";

        const vectorStore = await CloseVectorHNSWWeb.fromTexts(
            ['Hello world'],
            [{ id: 2 }],
            new FakeEmbeddings()
        );

        await vectorStore.saveToCloud({
            uuid: DATA_STORE_KEY,
            credentials: {
                key: CLOSEVECTOR_KEY,
                secret: CLOSEVECTOR_SECRET
            }
        });

        expect(vectorStore.index.getMaxElements()).toBe(1);
        expect(vectorStore.index.getCurrentCount()).toBe(1);

        console.log("sleeping for 1 second");
        await sleep(1000);

        const storeDownloaded = await CloseVectorHNSWWeb.loadFromCloud({
            uuid: DATA_STORE_KEY,
            embeddings: new FakeEmbeddings(),
            credentials: {
                key: CLOSEVECTOR_KEY,
                secret: CLOSEVECTOR_SECRET
            }
        })

        expect(storeDownloaded.index.getMaxElements()).toBe(1);
        expect(storeDownloaded.index.getCurrentCount()).toBe(1);
    }, 60 * 1000);
});