web-llm-embed / src /pages /api /docHandle.ts
matt HOFFNER
use chromadb to run in browser
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import type { NextApiRequest, NextApiResponse } from 'next';
import { RecursiveCharacterTextSplitter } from 'langchain/text_splitter';
import { Chroma } from "langchain/vectorstores/chroma";
import XenovaTransformersEmbeddings from '../../embed/hf'
async function handleDocs(text: string) {
const textSplitter = new RecursiveCharacterTextSplitter({ chunkSize: 1000 });
const docs = await textSplitter.createDocuments([text]);
const vectorStore = await Chroma.fromDocuments(docs, new XenovaTransformersEmbeddings(), {
collectionName: 'docs'
});
return vectorStore;
}
export default async function handler(
req: NextApiRequest,
res: NextApiResponse,
) {
const { text } = JSON.parse(req.body);
// console.log(text);
if (!text) {
return res.status(400).json({ message: 'No question in the request' });
}
const vectorStore = await handleDocs(text);
res.status(200).send({
model: vectorStore,
});
}
export const config = {
api: {
bodyParser: true, // Disallow body parsing, consume as stream
},
};