mirror of
https://github.com/labring/FastGPT.git
synced 2025-07-30 10:28:42 +00:00
new framwork
This commit is contained in:
archer
16
client/src/utils/adapt.ts
Normal file
16
client/src/utils/adapt.ts
Normal file
@@ -0,0 +1,16 @@
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import { formatPrice } from './user';
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import dayjs from 'dayjs';
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import type { BillSchema } from '../types/mongoSchema';
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import type { UserBillType } from '@/types/user';
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export const adaptBill = (bill: BillSchema): UserBillType => {
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return {
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id: bill._id,
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type: bill.type,
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modelName: bill.modelName,
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time: bill.time,
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textLen: bill.textLen,
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tokenLen: bill.tokenLen,
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price: formatPrice(bill.price)
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};
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};
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264
client/src/utils/file.ts
Normal file
264
client/src/utils/file.ts
Normal file
@@ -0,0 +1,264 @@
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import mammoth from 'mammoth';
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import Papa from 'papaparse';
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import { getOpenAiEncMap } from './plugin/openai';
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import { getErrText } from './tools';
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/**
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* 读取 txt 文件内容
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*/
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export const readTxtContent = (file: File) => {
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return new Promise((resolve: (_: string) => void, reject) => {
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try {
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const reader = new FileReader();
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reader.onload = () => {
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resolve(reader.result as string);
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};
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reader.onerror = (err) => {
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console.log('error txt read:', err);
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reject('读取 txt 文件失败');
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};
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reader.readAsText(file);
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} catch (error) {
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reject('浏览器不支持文件内容读取');
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}
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});
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};
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/**
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* 读取 pdf 内容
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*/
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export const readPdfContent = (file: File) =>
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new Promise<string>((resolve, reject) => {
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try {
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const pdfjsLib = window['pdfjs-dist/build/pdf'];
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pdfjsLib.workerSrc = '/js/pdf.worker.js';
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const readPDFPage = async (doc: any, pageNo: number) => {
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const page = await doc.getPage(pageNo);
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const tokenizedText = await page.getTextContent();
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const pageText = tokenizedText.items.map((token: any) => token.str).join(' ');
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return pageText;
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};
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let reader = new FileReader();
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reader.readAsArrayBuffer(file);
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reader.onload = async (event) => {
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if (!event?.target?.result) return reject('解析 PDF 失败');
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try {
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const doc = await pdfjsLib.getDocument(event.target.result).promise;
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const pageTextPromises = [];
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for (let pageNo = 1; pageNo <= doc.numPages; pageNo++) {
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pageTextPromises.push(readPDFPage(doc, pageNo));
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}
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const pageTexts = await Promise.all(pageTextPromises);
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resolve(pageTexts.join('\n'));
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} catch (err) {
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console.log(err, 'pdfjs error');
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reject('解析 PDF 失败');
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}
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};
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reader.onerror = (err) => {
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console.log(err, 'reader error');
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reject('解析 PDF 失败');
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};
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} catch (error) {
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reject('浏览器不支持文件内容读取');
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}
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});
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/**
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* 读取doc
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*/
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export const readDocContent = (file: File) =>
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new Promise<string>((resolve, reject) => {
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try {
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const reader = new FileReader();
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reader.readAsArrayBuffer(file);
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reader.onload = async ({ target }) => {
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if (!target?.result) return reject('读取 doc 文件失败');
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try {
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const res = await mammoth.extractRawText({
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arrayBuffer: target.result as ArrayBuffer
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});
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resolve(res?.value);
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} catch (error) {
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reject('读取 doc 文件失败, 请转换成 PDF');
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}
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};
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reader.onerror = (err) => {
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console.log('error doc read:', err);
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reject('读取 doc 文件失败');
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};
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} catch (error) {
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reject('浏览器不支持文件内容读取');
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}
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});
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/**
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* 读取csv
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*/
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export const readCsvContent = async (file: File) => {
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try {
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const textArr = await readTxtContent(file);
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const json = Papa.parse(textArr).data as string[][];
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if (json.length === 0) {
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throw new Error('csv 解析失败');
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}
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return {
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header: json.shift()?.filter((item) => item) as string[],
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data: json.map((item) => item?.filter((item) => item))
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};
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} catch (error) {
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return Promise.reject('解析 csv 文件失败');
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}
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};
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/**
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* file download
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*/
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export const fileDownload = ({
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text,
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type,
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filename
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}: {
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text: string;
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type: string;
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filename: string;
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}) => {
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// 导出为文件
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const blob = new Blob([`\uFEFF${text}`], { type: `${type};charset=utf-8;` });
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// 创建下载链接
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const downloadLink = document.createElement('a');
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downloadLink.href = window.URL.createObjectURL(blob);
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downloadLink.download = filename;
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// 添加链接到页面并触发下载
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document.body.appendChild(downloadLink);
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downloadLink.click();
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document.body.removeChild(downloadLink);
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};
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/**
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* text split into chunks
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* maxLen - one chunk len. max: 3500
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* slideLen - The size of the before and after Text
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* maxLen > slideLen
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*/
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export const splitText_token = ({
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text,
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maxLen,
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slideLen
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}: {
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text: string;
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maxLen: number;
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slideLen: number;
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}) => {
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try {
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const enc = getOpenAiEncMap()['gpt-3.5-turbo'];
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// filter empty text. encode sentence
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const encodeText = enc.encode(text);
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const chunks: string[] = [];
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let tokens = 0;
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let startIndex = 0;
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let endIndex = Math.min(startIndex + maxLen, encodeText.length);
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let chunkEncodeArr = encodeText.slice(startIndex, endIndex);
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const decoder = new TextDecoder();
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while (startIndex < encodeText.length) {
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tokens += chunkEncodeArr.length;
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chunks.push(decoder.decode(enc.decode(chunkEncodeArr)));
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startIndex += maxLen - slideLen;
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endIndex = Math.min(startIndex + maxLen, encodeText.length);
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chunkEncodeArr = encodeText.slice(
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Math.min(encodeText.length - slideLen, startIndex),
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endIndex
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);
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}
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return {
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chunks,
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tokens
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};
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} catch (err) {
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throw new Error(getErrText(err));
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}
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};
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export const fileToBase64 = (file: File) => {
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return new Promise((resolve, reject) => {
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const reader = new FileReader();
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reader.readAsDataURL(file);
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reader.onload = () => resolve(reader.result);
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reader.onerror = (error) => reject(error);
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});
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};
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/**
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* compress image. response base64
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* @param maxSize The max size of the compressed image
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*/
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export const compressImg = ({
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file,
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maxW = 200,
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maxH = 200,
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maxSize = 1024 * 100
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}: {
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file: File;
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maxW?: number;
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maxH?: number;
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maxSize?: number;
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}) =>
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new Promise<string>((resolve, reject) => {
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const reader = new FileReader();
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reader.readAsDataURL(file);
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reader.onload = () => {
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const img = new Image();
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// @ts-ignore
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img.src = reader.result;
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img.onload = () => {
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let width = img.width;
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let height = img.height;
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if (width > height) {
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if (width > maxW) {
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height *= maxW / width;
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width = maxW;
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}
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} else {
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if (height > maxH) {
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width *= maxH / height;
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height = maxH;
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}
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}
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const canvas = document.createElement('canvas');
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canvas.width = width;
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canvas.height = height;
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const ctx = canvas.getContext('2d');
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if (!ctx) {
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return reject('压缩图片异常');
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}
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ctx.drawImage(img, 0, 0, width, height);
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const compressedDataUrl = canvas.toDataURL(file.type, 1);
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// 移除 canvas 元素
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canvas.remove();
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if (compressedDataUrl.length > maxSize) {
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return reject('图片太大了');
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}
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resolve(compressedDataUrl);
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};
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};
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reader.onerror = (err) => {
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console.log(err);
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reject('压缩图片异常');
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};
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});
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36
client/src/utils/plugin/google.ts
Normal file
36
client/src/utils/plugin/google.ts
Normal file
@@ -0,0 +1,36 @@
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import axios from 'axios';
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import { Obj2Query } from '../tools';
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export const getClientToken = (googleVerKey: string) => {
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if (typeof grecaptcha === 'undefined' || !grecaptcha?.ready) return '';
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return new Promise<string>((resolve, reject) => {
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grecaptcha.ready(async () => {
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try {
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const token = await grecaptcha.execute(googleVerKey, {
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action: 'submit'
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});
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resolve(token);
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} catch (error) {
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reject(error);
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}
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});
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});
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};
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// service run
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export const authGoogleToken = async (data: {
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secret: string;
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response: string;
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remoteip?: string;
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}) => {
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const res = await axios.post<{
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score?: number;
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success: boolean;
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'error-codes': string[];
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}>(`https://www.recaptcha.net/recaptcha/api/siteverify?${Obj2Query(data)}`);
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if (res.data.success) {
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return Promise.resolve('');
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}
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return Promise.reject(res?.data?.['error-codes']?.[0] || '非法环境');
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};
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38
client/src/utils/plugin/index.ts
Normal file
38
client/src/utils/plugin/index.ts
Normal file
@@ -0,0 +1,38 @@
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import { ClaudeEnum, OpenAiChatEnum } from '@/constants/model';
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import type { ChatModelType } from '@/constants/model';
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import type { ChatItemSimpleType } from '@/types/chat';
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import { countOpenAIToken, openAiSliceTextByToken } from './openai';
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import { gpt_chatItemTokenSlice } from '@/pages/api/openapi/text/gptMessagesSlice';
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export const modelToolMap: Record<
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ChatModelType,
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{
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countTokens: (data: { messages: ChatItemSimpleType[] }) => number;
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sliceText: (data: { text: string; length: number }) => string;
|
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tokenSlice: (data: {
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messages: ChatItemSimpleType[];
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maxToken: number;
|
||||
}) => ChatItemSimpleType[];
|
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}
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> = {
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[OpenAiChatEnum.GPT35]: {
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countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT35, messages }),
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sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT35, ...data }),
|
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tokenSlice: (data) => gpt_chatItemTokenSlice({ model: OpenAiChatEnum.GPT35, ...data })
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},
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[OpenAiChatEnum.GPT4]: {
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||||
countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT4, messages }),
|
||||
sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT4, ...data }),
|
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tokenSlice: (data) => gpt_chatItemTokenSlice({ model: OpenAiChatEnum.GPT4, ...data })
|
||||
},
|
||||
[OpenAiChatEnum.GPT432k]: {
|
||||
countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT432k, messages }),
|
||||
sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT432k, ...data }),
|
||||
tokenSlice: (data) => gpt_chatItemTokenSlice({ model: OpenAiChatEnum.GPT432k, ...data })
|
||||
},
|
||||
[ClaudeEnum.Claude]: {
|
||||
countTokens: ({ messages }) => countOpenAIToken({ model: OpenAiChatEnum.GPT35, messages }),
|
||||
sliceText: (data) => openAiSliceTextByToken({ model: OpenAiChatEnum.GPT35, ...data }),
|
||||
tokenSlice: (data) => gpt_chatItemTokenSlice({ model: OpenAiChatEnum.GPT35, ...data })
|
||||
}
|
||||
};
|
||||
162
client/src/utils/plugin/openai.ts
Normal file
162
client/src/utils/plugin/openai.ts
Normal file
@@ -0,0 +1,162 @@
|
||||
import { encoding_for_model, type Tiktoken } from '@dqbd/tiktoken';
|
||||
import type { ChatItemSimpleType } from '@/types/chat';
|
||||
import { ChatRoleEnum } from '@/constants/chat';
|
||||
import { ChatCompletionRequestMessage, ChatCompletionRequestMessageRoleEnum } from 'openai';
|
||||
import { OpenAiChatEnum } from '@/constants/model';
|
||||
import Graphemer from 'graphemer';
|
||||
|
||||
const textDecoder = new TextDecoder();
|
||||
const graphemer = new Graphemer();
|
||||
|
||||
export const getOpenAiEncMap = () => {
|
||||
if (typeof window !== 'undefined') {
|
||||
window.OpenAiEncMap = window.OpenAiEncMap || {
|
||||
'gpt-3.5-turbo': encoding_for_model('gpt-3.5-turbo', {
|
||||
'<|im_start|>': 100264,
|
||||
'<|im_end|>': 100265,
|
||||
'<|im_sep|>': 100266
|
||||
}),
|
||||
'gpt-4': encoding_for_model('gpt-4', {
|
||||
'<|im_start|>': 100264,
|
||||
'<|im_end|>': 100265,
|
||||
'<|im_sep|>': 100266
|
||||
}),
|
||||
'gpt-4-32k': encoding_for_model('gpt-4-32k', {
|
||||
'<|im_start|>': 100264,
|
||||
'<|im_end|>': 100265,
|
||||
'<|im_sep|>': 100266
|
||||
})
|
||||
};
|
||||
return window.OpenAiEncMap;
|
||||
}
|
||||
if (typeof global !== 'undefined') {
|
||||
global.OpenAiEncMap = global.OpenAiEncMap || {
|
||||
'gpt-3.5-turbo': encoding_for_model('gpt-3.5-turbo', {
|
||||
'<|im_start|>': 100264,
|
||||
'<|im_end|>': 100265,
|
||||
'<|im_sep|>': 100266
|
||||
}),
|
||||
'gpt-4': encoding_for_model('gpt-4', {
|
||||
'<|im_start|>': 100264,
|
||||
'<|im_end|>': 100265,
|
||||
'<|im_sep|>': 100266
|
||||
}),
|
||||
'gpt-4-32k': encoding_for_model('gpt-4-32k', {
|
||||
'<|im_start|>': 100264,
|
||||
'<|im_end|>': 100265,
|
||||
'<|im_sep|>': 100266
|
||||
})
|
||||
};
|
||||
return global.OpenAiEncMap;
|
||||
}
|
||||
return {
|
||||
'gpt-3.5-turbo': encoding_for_model('gpt-3.5-turbo', {
|
||||
'<|im_start|>': 100264,
|
||||
'<|im_end|>': 100265,
|
||||
'<|im_sep|>': 100266
|
||||
}),
|
||||
'gpt-4': encoding_for_model('gpt-4', {
|
||||
'<|im_start|>': 100264,
|
||||
'<|im_end|>': 100265,
|
||||
'<|im_sep|>': 100266
|
||||
}),
|
||||
'gpt-4-32k': encoding_for_model('gpt-4-32k', {
|
||||
'<|im_start|>': 100264,
|
||||
'<|im_end|>': 100265,
|
||||
'<|im_sep|>': 100266
|
||||
})
|
||||
};
|
||||
};
|
||||
|
||||
export const adaptChatItem_openAI = ({
|
||||
messages
|
||||
}: {
|
||||
messages: ChatItemSimpleType[];
|
||||
}): ChatCompletionRequestMessage[] => {
|
||||
const map = {
|
||||
[ChatRoleEnum.AI]: ChatCompletionRequestMessageRoleEnum.Assistant,
|
||||
[ChatRoleEnum.Human]: ChatCompletionRequestMessageRoleEnum.User,
|
||||
[ChatRoleEnum.System]: ChatCompletionRequestMessageRoleEnum.System
|
||||
};
|
||||
return messages.map((item) => ({
|
||||
role: map[item.obj] || ChatCompletionRequestMessageRoleEnum.System,
|
||||
content: item.value || ''
|
||||
}));
|
||||
};
|
||||
|
||||
export function countOpenAIToken({
|
||||
messages,
|
||||
model
|
||||
}: {
|
||||
messages: ChatItemSimpleType[];
|
||||
model: `${OpenAiChatEnum}`;
|
||||
}) {
|
||||
function getChatGPTEncodingText(
|
||||
messages: {
|
||||
role: 'system' | 'user' | 'assistant';
|
||||
content: string;
|
||||
name?: string;
|
||||
}[],
|
||||
model: 'gpt-3.5-turbo' | 'gpt-4' | 'gpt-4-32k'
|
||||
) {
|
||||
const isGpt3 = model === 'gpt-3.5-turbo';
|
||||
|
||||
const msgSep = isGpt3 ? '\n' : '';
|
||||
const roleSep = isGpt3 ? '\n' : '<|im_sep|>';
|
||||
|
||||
return [
|
||||
messages
|
||||
.map(({ name = '', role, content }) => {
|
||||
return `<|im_start|>${name || role}${roleSep}${content}<|im_end|>`;
|
||||
})
|
||||
.join(msgSep),
|
||||
`<|im_start|>assistant${roleSep}`
|
||||
].join(msgSep);
|
||||
}
|
||||
function text2TokensLen(encoder: Tiktoken, inputText: string) {
|
||||
const encoding = encoder.encode(inputText, 'all');
|
||||
const segments: { text: string; tokens: { id: number; idx: number }[] }[] = [];
|
||||
|
||||
let byteAcc: number[] = [];
|
||||
let tokenAcc: { id: number; idx: number }[] = [];
|
||||
let inputGraphemes = graphemer.splitGraphemes(inputText);
|
||||
|
||||
for (let idx = 0; idx < encoding.length; idx++) {
|
||||
const token = encoding[idx]!;
|
||||
byteAcc.push(...encoder.decode_single_token_bytes(token));
|
||||
tokenAcc.push({ id: token, idx });
|
||||
|
||||
const segmentText = textDecoder.decode(new Uint8Array(byteAcc));
|
||||
const graphemes = graphemer.splitGraphemes(segmentText);
|
||||
|
||||
if (graphemes.every((item, idx) => inputGraphemes[idx] === item)) {
|
||||
segments.push({ text: segmentText, tokens: tokenAcc });
|
||||
|
||||
byteAcc = [];
|
||||
tokenAcc = [];
|
||||
inputGraphemes = inputGraphemes.slice(graphemes.length);
|
||||
}
|
||||
}
|
||||
|
||||
return segments.reduce((memo, i) => memo + i.tokens.length, 0) ?? 0;
|
||||
}
|
||||
|
||||
const adaptMessages = adaptChatItem_openAI({ messages });
|
||||
|
||||
return text2TokensLen(getOpenAiEncMap()[model], getChatGPTEncodingText(adaptMessages, model));
|
||||
}
|
||||
|
||||
export const openAiSliceTextByToken = ({
|
||||
model = 'gpt-3.5-turbo',
|
||||
text,
|
||||
length
|
||||
}: {
|
||||
model: `${OpenAiChatEnum}`;
|
||||
text: string;
|
||||
length: number;
|
||||
}) => {
|
||||
const enc = getOpenAiEncMap()[model];
|
||||
const encodeText = enc.encode(text);
|
||||
const decoder = new TextDecoder();
|
||||
return decoder.decode(enc.decode(encodeText.slice(0, length)));
|
||||
};
|
||||
135
client/src/utils/tools.ts
Normal file
135
client/src/utils/tools.ts
Normal file
@@ -0,0 +1,135 @@
|
||||
import crypto from 'crypto';
|
||||
import { useToast } from '@/hooks/useToast';
|
||||
import dayjs from 'dayjs';
|
||||
|
||||
/**
|
||||
* copy text data
|
||||
*/
|
||||
export const useCopyData = () => {
|
||||
const { toast } = useToast();
|
||||
|
||||
return {
|
||||
copyData: async (data: string, title: string = '复制成功') => {
|
||||
try {
|
||||
if (navigator.clipboard) {
|
||||
await navigator.clipboard.writeText(data);
|
||||
} else {
|
||||
throw new Error('');
|
||||
}
|
||||
} catch (error) {
|
||||
const textarea = document.createElement('textarea');
|
||||
textarea.value = data;
|
||||
document.body.appendChild(textarea);
|
||||
textarea.select();
|
||||
document.execCommand('copy');
|
||||
document.body.removeChild(textarea);
|
||||
}
|
||||
|
||||
toast({
|
||||
title,
|
||||
status: 'success',
|
||||
duration: 1000
|
||||
});
|
||||
}
|
||||
};
|
||||
};
|
||||
|
||||
/**
|
||||
* 密码加密
|
||||
*/
|
||||
export const createHashPassword = (text: string) => {
|
||||
const hash = crypto.createHash('sha256').update(text).digest('hex');
|
||||
return hash;
|
||||
};
|
||||
|
||||
/**
|
||||
* 对象转成 query 字符串
|
||||
*/
|
||||
export const Obj2Query = (obj: Record<string, string | number>) => {
|
||||
const queryParams = new URLSearchParams();
|
||||
for (const key in obj) {
|
||||
queryParams.append(key, `${obj[key]}`);
|
||||
}
|
||||
return queryParams.toString();
|
||||
};
|
||||
|
||||
/**
|
||||
* 格式化时间成聊天格式
|
||||
*/
|
||||
export const formatTimeToChatTime = (time: Date) => {
|
||||
const now = dayjs();
|
||||
const target = dayjs(time);
|
||||
|
||||
// 如果传入时间小于60秒，返回刚刚
|
||||
if (now.diff(target, 'second') < 60) {
|
||||
return '刚刚';
|
||||
}
|
||||
|
||||
// 如果时间是今天，展示几时:几秒
|
||||
if (now.isSame(target, 'day')) {
|
||||
return target.format('HH:mm');
|
||||
}
|
||||
|
||||
// 如果是昨天，展示昨天
|
||||
if (now.subtract(1, 'day').isSame(target, 'day')) {
|
||||
return '昨天';
|
||||
}
|
||||
|
||||
// 如果是前天，展示前天
|
||||
if (now.subtract(2, 'day').isSame(target, 'day')) {
|
||||
return '前天';
|
||||
}
|
||||
|
||||
// 如果是今年，展示某月某日
|
||||
if (now.isSame(target, 'year')) {
|
||||
return target.format('M月D日');
|
||||
}
|
||||
|
||||
// 如果是更久之前，展示某年某月某日
|
||||
return target.format('YYYY/M/D');
|
||||
};
|
||||
|
||||
export const hasVoiceApi = typeof window !== 'undefined' && 'speechSynthesis' in window;
|
||||
/**
|
||||
* voice broadcast
|
||||
*/
|
||||
export const voiceBroadcast = ({ text }: { text: string }) => {
|
||||
window.speechSynthesis?.cancel();
|
||||
const msg = new SpeechSynthesisUtterance(text);
|
||||
const voices = window.speechSynthesis?.getVoices?.(); // 获取语言包
|
||||
const voice = voices.find((item) => {
|
||||
return item.name === 'Microsoft Yaoyao - Chinese (Simplified, PRC)';
|
||||
});
|
||||
if (voice) {
|
||||
msg.voice = voice;
|
||||
}
|
||||
|
||||
window.speechSynthesis?.speak(msg);
|
||||
|
||||
msg.onerror = (e) => {
|
||||
console.log(e);
|
||||
};
|
||||
|
||||
return {
|
||||
cancel: () => window.speechSynthesis?.cancel()
|
||||
};
|
||||
};
|
||||
|
||||
export const formatLinkText = (text: string) => {
|
||||
const httpReg =
|
||||
/(http|https|ftp):\/\/[\w\-_]+(\.[\w\-_]+)+([\w\-\.,@?^=%&:/~\+#]*[\w\-\@?^=%&/~\+#])?/gi;
|
||||
return text.replace(httpReg, ` $& `);
|
||||
};
|
||||
|
||||
export const getErrText = (err: any, def = '') => {
|
||||
const msg = typeof err === 'string' ? err : err?.message || def || '';
|
||||
msg && console.log('error =>', msg);
|
||||
return msg;
|
||||
};
|
||||
|
||||
export const delay = (ms: number) =>
|
||||
new Promise((resolve) => {
|
||||
setTimeout(() => {
|
||||
resolve('');
|
||||
}, ms);
|
||||
});
|
||||
17
client/src/utils/user.ts
Normal file
17
client/src/utils/user.ts
Normal file
@@ -0,0 +1,17 @@
|
||||
import { PRICE_SCALE } from '@/constants/common';
|
||||
import { loginOut } from '@/api/user';
|
||||
|
||||
export const clearCookie = () => {
|
||||
try {
|
||||
loginOut();
|
||||
} catch (error) {
|
||||
error;
|
||||
}
|
||||
};
|
||||
|
||||
/**
|
||||
* 把数据库读取到的price，转化成元
|
||||
*/
|
||||
export const formatPrice = (val = 0, multiple = 1) => {
|
||||
return Number(((val / PRICE_SCALE) * multiple).toFixed(10));
|
||||
};
|
||||
Reference in New Issue
Block a user