7917766024
* feat: retry send * perf: qa default value * feat: dataset folder * feat: kb folder delete and path * fix: ts * perf: script load * feat: fileCard and dataCard * feat: search file * feat: max token * feat: select dataset * fix: preview chunk * perf: source update * export data limit file_id * docs * fix: export limit
71 lines
1.7 KiB
TypeScript
71 lines
1.7 KiB
TypeScript
import type { NextApiRequest, NextApiResponse } from 'next';
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import { jsonRes } from '@/service/response';
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import { authUser } from '@/service/utils/auth';
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import { PgClient } from '@/service/pg';
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import { withNextCors } from '@/service/utils/tools';
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import { KB, connectToDatabase } from '@/service/mongo';
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import { getVector } from '../plugin/vector';
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import { PgTrainingTableName } from '@/constants/plugin';
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export type Props = {
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dataId: string;
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kbId: string;
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a?: string;
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q?: string;
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};
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export default withNextCors(async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
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try {
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const { dataId, a = '', q = '', kbId } = req.body as Props;
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if (!dataId) {
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throw new Error('缺少参数');
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}
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await connectToDatabase();
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// auth user and get kb
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const [{ userId }, kb] = await Promise.all([
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authUser({ req }),
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KB.findById(kbId, 'vectorModel')
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]);
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if (!kb) {
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throw new Error("Can't find database");
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}
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// get vector
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const { vectors = [] } = await (async () => {
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if (q) {
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return getVector({
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userId,
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input: [q],
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model: kb.vectorModel
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});
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}
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return { vectors: [[]] };
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})();
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// 更新 pg 内容.仅修改a，不需要更新向量。
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await PgClient.update(PgTrainingTableName, {
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where: [['id', dataId], 'AND', ['user_id', userId]],
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values: [
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{ key: 'a', value: a.replace(/'/g, '"') },
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...(q
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? [
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{ key: 'q', value: q.replace(/'/g, '"') },
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{ key: 'vector', value: `[${vectors[0]}]` }
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]
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: [])
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]
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});
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jsonRes(res);
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} catch (err) {
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jsonRes(res, {
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code: 500,
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error: err
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});
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}
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});
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