perf: retry to load image;perf: default index check (#4004)

* perf: retry to load image

* perf: default index check
This commit is contained in:
Archer
2025-03-06 18:27:47 +08:00
committed by archer
parent 8980664b8a
commit d05259dedd
9 changed files with 112 additions and 81 deletions

View File

@@ -1063,10 +1063,12 @@ curl --location --request DELETE 'http://localhost:3000/api/core/dataset/collect
| 字段 | 类型 | 说明 | 必填 |
| --- | --- | --- | --- |
| defaultIndex | Boolean | 是否为默认索引 | |
| dataId | String | 关联的向量ID | |
| type | String | 可选索引类型default-默认索引; custom-自定义索引; summary-总结索引; question-问题索引; image-图片索引 | |
| dataId | String | 关联的向量ID,变更数据时候传入该 ID会进行差量更新而不是全量更新 | |
| text | String | 文本内容 | ✅ |
`type` 不填则默认为 `custom` 索引,还会基于 q/a 组成一个默认索引。如果传入了默认索引,则不会额外创建。
### 为集合批量添加添加数据
注意,每次最多推送 200 组数据。
@@ -1298,8 +1300,7 @@ curl --location --request GET 'http://localhost:3000/api/core/dataset/data/detai
"chunkIndex": 0,
"indexes": [
{
"defaultIndex": true,
"type": "chunk",
"type": "default",
"dataId": "3720083",
"text": "N o . 2 0 2 2 1 2中 国 信 息 通 信 研 究 院京东探索研究院2022年 9月人工智能生成内容AIGC白皮书(2022 年)版权声明本白皮书版权属于中国信息通信研究院和京东探索研究院,并受法律保护。转载、摘编或利用其它方式使用本白皮书文字或者观点的,应注明“来源:中国信息通信研究院和京东探索研究院”。违反上述声明者,编者将追究其相关法律责任。前 言习近平总书记曾指出“数字技术正以新理念、新业态、新模式全面融入人类经济、政治、文化、社会、生态文明建设各领域和全过程”。在当前数字世界和物理世界加速融合的大背景下人工智能生成内容Artificial Intelligence Generated Content简称 AIGC正在悄然引导着一场深刻的变革重塑甚至颠覆数字内容的生产方式和消费模式将极大地丰富人们的数字生活是未来全面迈向数字文明新时代不可或缺的支撑力量。",
"_id": "65abd4b29d1448617cba61dc"
@@ -1335,12 +1336,18 @@ curl --location --request PUT 'http://localhost:3000/api/core/dataset/data/updat
"a":"sss",
"indexes":[
{
"dataId": "xxx",
"defaultIndex":false,
"text":"自定义索引1"
"dataId": "xxxx",
"type": "default",
"text": "默认索引"
},
{
"text":"修改后的自定义索引2。会删除原来的自定义索引2并插入新的自定义索引2"
"dataId": "xxx",
"type": "custom",
"text": "旧的自定义索引1"
},
{
"type":"custom",
"text":"新增的自定义索引"
}
]
}'

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@@ -168,7 +168,7 @@ export const markdownProcess = async ({
return simpleMarkdownText(imageProcess);
};
export const matchMdImgTextAndUpload = (text: string) => {
export const matchMdImg = (text: string) => {
const base64Regex = /!\[([^\]]*)\]\((data:image\/[^;]+;base64[^)]+)\)/g;
const imageList: ImageType[] = [];

View File

@@ -6,6 +6,7 @@ import { guessBase64ImageType } from '../utils';
import { readFromSecondary } from '../../mongo/utils';
import { addHours } from 'date-fns';
import { imageFileType } from '@fastgpt/global/common/file/constants';
import { retryFn } from '@fastgpt/global/common/system/utils';
export const maxImgSize = 1024 * 1024 * 12;
const base64MimeRegex = /data:image\/([^\)]+);base64/;
@@ -40,13 +41,15 @@ export async function uploadMongoImg({
return Promise.reject(`Invalid image file type: ${mime}`);
}
const { _id } = await MongoImage.create({
teamId,
binary,
metadata: Object.assign({ mime }, metadata),
shareId,
expiredTime: forever ? undefined : addHours(new Date(), 1)
});
const { _id } = await retryFn(() =>
MongoImage.create({
teamId,
binary,
metadata: Object.assign({ mime }, metadata),
shareId,
expiredTime: forever ? undefined : addHours(new Date(), 1)
})
);
return `${process.env.NEXT_PUBLIC_BASE_URL || ''}${imageBaseUrl}${String(_id)}.${extension}`;
}

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@@ -2,23 +2,30 @@ import axios from 'axios';
import { addLog } from '../../system/log';
import { serverRequestBaseUrl } from '../../api/serverRequest';
import { getFileContentTypeFromHeader, guessBase64ImageType } from '../utils';
import { retryFn } from '@fastgpt/global/common/system/utils';
export const getImageBase64 = async (url: string) => {
addLog.debug(`Load image to base64: ${url}`);
try {
const response = await axios.get(url, {
baseURL: serverRequestBaseUrl,
responseType: 'arraybuffer',
proxy: false
});
const response = await retryFn(() =>
axios.get(url, {
baseURL: serverRequestBaseUrl,
responseType: 'arraybuffer',
proxy: false
})
);
const base64 = Buffer.from(response.data, 'binary').toString('base64');
const imageType =
getFileContentTypeFromHeader(response.headers['content-type']) ||
guessBase64ImageType(base64);
return `data:${imageType};base64,${base64}`;
return {
completeBase64: `data:${imageType};base64,${base64}`,
base64,
mime: imageType
};
} catch (error) {
addLog.debug(`Load image to base64 failed: ${url}`);
console.log(error);

View File

@@ -6,11 +6,12 @@ import type { ImageType, ReadFileResponse } from '../../../worker/readFile/type'
import axios from 'axios';
import { addLog } from '../../system/log';
import { batchRun } from '@fastgpt/global/common/system/utils';
import { htmlTable2Md, matchMdImgTextAndUpload } from '@fastgpt/global/common/string/markdown';
import { htmlTable2Md, matchMdImg } from '@fastgpt/global/common/string/markdown';
import { createPdfParseUsage } from '../../../support/wallet/usage/controller';
import { getErrText } from '@fastgpt/global/common/error/utils';
import { delay } from '@fastgpt/global/common/system/utils';
import { getNanoid } from '@fastgpt/global/common/string/tools';
import { getImageBase64 } from '../image/utils';
export type readRawTextByLocalFileParams = {
teamId: string;
@@ -99,7 +100,7 @@ export const readRawContentByFileBuffer = async ({
addLog.info(`Custom file parsing is complete, time: ${Date.now() - start}ms`);
const rawText = response.markdown;
const { text, imageList } = matchMdImgTextAndUpload(rawText);
const { text, imageList } = matchMdImg(rawText);
createPdfParseUsage({
teamId,
@@ -120,8 +121,8 @@ export const readRawContentByFileBuffer = async ({
const parseTextImage = async (text: string) => {
// Extract image links and convert to base64
const imageList: { id: string; url: string }[] = [];
const processedText = text.replace(/!\[.*?\]\((http[^)]+)\)/g, (match, url) => {
const id = getNanoid();
let processedText = text.replace(/!\[.*?\]\((http[^)]+)\)/g, (match, url) => {
const id = `IMAGE_${getNanoid()}_IMAGE`;
imageList.push({
id,
url
@@ -129,22 +130,24 @@ export const readRawContentByFileBuffer = async ({
return `![](${id})`;
});
// Get base64 from image url
let resultImageList: ImageType[] = [];
await Promise.all(
imageList.map(async (item) => {
await batchRun(
imageList,
async (item) => {
try {
const response = await axios.get(item.url, { responseType: 'arraybuffer' });
const mime = response.headers['content-type'] || 'image/jpeg';
const base64 = response.data.toString('base64');
const { base64, mime } = await getImageBase64(item.url);
resultImageList.push({
uuid: item.id,
mime,
base64
});
} catch (error) {
processedText = processedText.replace(item.id, item.url);
addLog.warn(`Failed to get image from ${item.url}: ${getErrText(error)}`);
}
})
},
5
);
return {
@@ -312,14 +315,14 @@ export const readRawContentByFileBuffer = async ({
return await uploadMongoImg({
base64Img: `data:${item.mime};base64,${item.base64}`,
teamId,
// expiredTime: addHours(new Date(), 1),
metadata: {
...metadata,
mime: item.mime
}
});
} catch (error) {
return '';
addLog.warn('Upload file image error', { error });
return 'Upload load image error';
}
})();
rawText = rawText.replace(item.uuid, src);

View File

@@ -165,7 +165,7 @@ export const loadRequestMessages = async ({
try {
// If imgUrl is a local path, load image from local, and set url to base64
if (imgUrl.startsWith('/') || process.env.MULTIPLE_DATA_TO_BASE64 === 'true') {
const base64 = await getImageBase64(imgUrl);
const { completeBase64: base64 } = await getImageBase64(imgUrl);
return {
...item,

View File

@@ -1,6 +1,6 @@
import TurndownService from 'turndown';
import { ImageType } from '../readFile/type';
import { matchMdImgTextAndUpload } from '@fastgpt/global/common/string/markdown';
import { matchMdImg } from '@fastgpt/global/common/string/markdown';
import { getNanoid } from '@fastgpt/global/common/string/tools';
// @ts-ignore
const turndownPluginGfm = require('joplin-turndown-plugin-gfm');
@@ -46,7 +46,7 @@ export const html2md = (
// Base64 img to id, otherwise it will occupy memory when going to md
const { processedHtml, images } = processBase64Images(html);
const md = turndownService.turndown(processedHtml);
const { text, imageList } = matchMdImgTextAndUpload(md);
const { text, imageList } = matchMdImg(md);
return {
rawText: text,

View File

@@ -1,5 +1,5 @@
import React, { useCallback, useEffect, useMemo, useRef, useState } from 'react';
import { Box, Flex, Button, Textarea, useTheme } from '@chakra-ui/react';
import { Box, Flex, Button, Textarea } from '@chakra-ui/react';
import {
FieldArrayWithId,
UseFieldArrayRemove,
@@ -19,8 +19,7 @@ import MyModal from '@fastgpt/web/components/common/MyModal';
import MyTooltip from '@fastgpt/web/components/common/MyTooltip';
import { useQuery } from '@tanstack/react-query';
import { useTranslation } from 'next-i18next';
import { useRequest, useRequest2 } from '@fastgpt/web/hooks/useRequest';
import { useConfirm } from '@fastgpt/web/hooks/useConfirm';
import { useRequest2 } from '@fastgpt/web/hooks/useRequest';
import { getSourceNameIcon } from '@fastgpt/global/core/dataset/utils';
import { DatasetDataIndexItemType } from '@fastgpt/global/core/dataset/type';
import DeleteIcon from '@fastgpt/web/components/common/Icon/delete';
@@ -30,10 +29,12 @@ import MyBox from '@fastgpt/web/components/common/MyBox';
import { getErrText } from '@fastgpt/global/common/error/utils';
import { useSystemStore } from '@/web/common/system/useSystemStore';
import QuestionTip from '@fastgpt/web/components/common/MyTooltip/QuestionTip';
import { useSystem } from '@fastgpt/web/hooks/useSystem';
import LightRowTabs from '@fastgpt/web/components/common/Tabs/LightRowTabs';
import styles from './styles.module.scss';
import { getDatasetIndexMapData } from '@fastgpt/global/core/dataset/data/constants';
import {
DatasetDataIndexTypeEnum,
getDatasetIndexMapData
} from '@fastgpt/global/core/dataset/data/constants';
export type InputDataType = {
q: string;
@@ -62,11 +63,10 @@ const InputDataModal = ({
onSuccess: (data: InputDataType & { dataId: string }) => void;
}) => {
const { t } = useTranslation();
const theme = useTheme();
const { toast } = useToast();
const [currentTab, setCurrentTab] = useState(TabEnum.content);
const { embeddingModelList, defaultModels } = useSystemStore();
const { isPc } = useSystem();
const { register, handleSubmit, reset, control } = useForm<InputDataType>();
const {
fields: indexes,
@@ -112,11 +112,6 @@ const InputDataModal = ({
}
];
const { ConfirmModal, openConfirm } = useConfirm({
content: t('common:dataset.data.Delete Tip'),
type: 'delete'
});
const { data: collection = defaultCollectionDetail } = useQuery(
['loadCollectionId', collectionId],
() => {
@@ -163,8 +158,8 @@ const InputDataModal = ({
}, [collection.dataset.vectorModel, defaultModels.embedding, embeddingModelList]);
// import new data
const { mutate: sureImportData, isLoading: isImporting } = useRequest({
mutationFn: async (e: InputDataType) => {
const { runAsync: sureImportData, loading: isImporting } = useRequest2(
async (e: InputDataType) => {
if (!e.q) {
setCurrentTab(TabEnum.content);
return Promise.reject(t('common:dataset.data.input is empty'));
@@ -181,12 +176,8 @@ const InputDataModal = ({
collectionId: collection._id,
q: e.q,
a: e.a,
// remove dataId
indexes:
e.indexes?.map((index) => ({
...index,
dataId: undefined
})) || []
// Contains no default index
indexes: e.indexes
});
return {
@@ -194,18 +185,20 @@ const InputDataModal = ({
dataId
};
},
successToast: t('common:dataset.data.Input Success Tip'),
onSuccess(e) {
reset({
...e,
q: '',
a: '',
indexes: []
});
onSuccess(e);
},
errorToast: t('common:common.error.unKnow')
});
{
successToast: t('common:dataset.data.Input Success Tip'),
onSuccess(e) {
reset({
...e,
q: '',
a: '',
indexes: []
});
onSuccess(e);
},
errorToast: t('common:common.error.unKnow')
}
);
// update
const { runAsync: onUpdateData, loading: isUpdating } = useRequest2(
@@ -239,6 +232,7 @@ const InputDataModal = ({
() => getSourceNameIcon({ sourceName: collection.sourceName, sourceId: collection.sourceId }),
[collection]
);
return (
<MyModal
isOpen={true}
@@ -291,9 +285,8 @@ const InputDataModal = ({
p={0}
onClick={() =>
appendIndexes({
type: 'custom',
text: '',
dataId: `${Date.now()}`
type: DatasetDataIndexTypeEnum.custom,
text: ''
})
}
>
@@ -331,7 +324,6 @@ const InputDataModal = ({
</MyTooltip>
</Flex>
</MyBox>
<ConfirmModal />
</MyModal>
);
};

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@@ -25,16 +25,35 @@ const formatIndexes = ({
a?: string;
}) => {
indexes = indexes || [];
const defaultIndex = getDefaultIndex({ q, a });
// If index not type, set it to custom
indexes = indexes
.map((item) => ({
text: typeof item.text === 'string' ? item.text : String(item.text),
type: item.type || DatasetDataIndexTypeEnum.custom,
dataId: item.dataId
}))
.filter((item) => !!item.text.trim());
// 1. Reset default index
// Recompute default indexes, Merge ids of the same index, reduce the number of rebuilds
const defaultIndexes = getDefaultIndex({ q, a });
const concatDefaultIndexes = defaultIndexes.map((item) => {
const oldIndex = indexes!.find((index) => index.text === item.text);
if (oldIndex) {
return {
type: DatasetDataIndexTypeEnum.default,
text: item.text,
dataId: oldIndex.dataId
};
} else {
return item;
}
});
indexes = indexes.filter((item) => item.type !== DatasetDataIndexTypeEnum.default);
// 2. Add default index
indexes.unshift(...defaultIndex);
// 3. Filter same text
indexes.push(...concatDefaultIndexes);
// Filter same text
indexes = indexes.filter(
(item, index, self) =>
!!item.text.trim() && index === self.findIndex((t) => t.text === item.text)
(item, index, self) => index === self.findIndex((t) => t.text === item.text)
);
return indexes.map((index) => ({
@@ -229,7 +248,7 @@ export async function updateData2Dataset({
const newIndexes = patchResult
.filter((item) => item.type !== 'delete')
.map((item) => item.index) as DatasetDataIndexItemType[];
console.log(newIndexes, '---');
// console.log(clonePatchResult2Insert);
await mongoSessionRun(async (session) => {
// Update MongoData