75 lines
1.9 KiB
TypeScript
75 lines
1.9 KiB
TypeScript
import type { NextApiRequest, NextApiResponse } from 'next';
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import { jsonRes } from '@/service/response';
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import { connectToDatabase, SplitData } from '@/service/mongo';
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import { authKb, authUser } from '@/service/utils/auth';
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import { generateVector } from '@/service/events/generateVector';
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import { generateQA } from '@/service/events/generateQA';
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import { PgClient } from '@/service/pg';
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import { SplitTextTypEnum } from '@/constants/plugin';
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import { withNextCors } from '@/service/utils/tools';
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/* split text */
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export default withNextCors(async function handler(req: NextApiRequest, res: NextApiResponse) {
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try {
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const { chunks, kbId, prompt, mode } = req.body as {
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kbId: string;
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chunks: string[];
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prompt: string;
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mode: `${SplitTextTypEnum}`;
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};
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if (!chunks || !kbId || !prompt) {
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throw new Error('参数错误');
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}
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await connectToDatabase();
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const { userId } = await authUser({ req });
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// 验证是否是该用户的 model
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await authKb({
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kbId,
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userId
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});
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if (mode === SplitTextTypEnum.qa) {
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// 批量QA拆分插入数据
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await SplitData.create({
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userId,
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kbId,
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textList: chunks,
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prompt
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});
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generateQA();
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} else if (mode === SplitTextTypEnum.subsection) {
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// 待优化，直接调用另一个接口
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// 插入记录
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await PgClient.insert('modelData', {
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values: chunks.map((item) => [
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{ key: 'user_id', value: userId },
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{ key: 'kb_id', value: kbId },
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{ key: 'q', value: item },
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{ key: 'a', value: '' },
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{ key: 'status', value: 'waiting' }
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])
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});
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generateVector();
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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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export const config = {
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api: {
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bodyParser: {
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sizeLimit: '100mb'
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}
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}
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};
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