FastGPT/src/pages/api/model/data/pushModelDataJson.ts
2023-04-01 22:31:56 +08:00

79 lines
2.2 KiB
TypeScript

import type { NextApiRequest, NextApiResponse } from 'next';
import { jsonRes } from '@/service/response';
import { connectToDatabase, Model } from '@/service/mongo';
import { authToken } from '@/service/utils/tools';
import { generateVector } from '@/service/events/generateVector';
import { vectorToBuffer, formatVector } from '@/utils/tools';
import { connectRedis } from '@/service/redis';
import { VecModelDataPrefix, ModelDataStatusEnum } from '@/constants/redis';
import { customAlphabet } from 'nanoid';
const nanoid = customAlphabet('abcdefghijklmnopqrstuvwxyz1234567890', 12);
export default async function handler(req: NextApiRequest, res: NextApiResponse<any>) {
try {
const { modelId, data } = req.body as {
modelId: string;
data: { prompt: string; completion: string; vector?: number[] }[];
};
const { authorization } = req.headers;
if (!authorization) {
throw new Error('无权操作');
}
if (!modelId || !Array.isArray(data)) {
throw new Error('缺少参数');
}
// 凭证校验
const userId = await authToken(authorization);
await connectToDatabase();
const redis = await connectRedis();
// 验证是否是该用户的 model
const model = await Model.findOne({
_id: modelId,
userId
});
if (!model) {
throw new Error('无权操作该模型');
}
// 插入 redis
const insertRedisRes = await Promise.allSettled(
data.map((item) => {
const vector = item.vector;
return redis.sendCommand([
'HMSET',
`${VecModelDataPrefix}:${nanoid()}`,
'userId',
userId,
'modelId',
String(modelId),
...(vector ? ['vector', vectorToBuffer(formatVector(vector))] : []),
'q',
item.prompt,
'text',
item.completion,
'status',
vector ? ModelDataStatusEnum.ready : ModelDataStatusEnum.waiting
]);
})
);
generateVector(true);
jsonRes(res, {
data: insertRedisRes.filter((item) => item.status === 'rejected').length
});
} catch (err) {
jsonRes(res, {
code: 500,
error: err
});
}
}