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mongo.ts 1.88 KiB
import { MongoClient } from "mongodb";
import { Document } from "../../packages/core/src/Node";
import { VectorStoreIndex } from "../../packages/core/src/indices";
import { SimpleMongoReader } from "../../packages/core/src/readers/SimpleMongoReader";
import { stdin as input, stdout as output } from "node:process";
import readline from "node:readline/promises";
async function main() {
//Dummy test code
const query: object = { _id: "waldo" };
const options: object = {};
const projections: object = { embedding: 0 };
const limit: number = Infinity;
const uri: string = process.env.MONGODB_URI ?? "fake_uri";
const client: MongoClient = new MongoClient(uri);
//Where the real code starts
const MR = new SimpleMongoReader(client);
const documents: Document[] = await MR.loadData(
"data",
"posts",
1,
{},
options,
projections,
);
//
//If you need to look at low-level details of
// a queryEngine (for example, needing to check each individual node)
//
// Split text and create embeddings. Store them in a VectorStoreIndex
// var storageContext = await storageContextFromDefaults({});
// var serviceContext = serviceContextFromDefaults({});
// const docStore = storageContext.docStore;
// for (const doc of documents) {
// docStore.setDocumentHash(doc.id_, doc.hash);
// }
// const nodes = serviceContext.nodeParser.getNodesFromDocuments(documents);
// console.log(nodes);
//
//Making Vector Store from documents
//
const index = await VectorStoreIndex.fromDocuments(documents);
// Create query engine
const queryEngine = index.asQueryEngine();
const rl = readline.createInterface({ input, output });
while (true) {
const query = await rl.question("Query: ");
if (!query) {
break;
}
const response = await queryEngine.query(query);
// Output response
console.log(response.toString());
}
}
main();