feat: 1. using cache storage store image data; 2. get base64image before chat to api #5013

This commit is contained in:
lloydzhou 2024-07-19 13:50:10 +08:00
parent afa1a4303b
commit 287fa0a39c
9 changed files with 164 additions and 14 deletions

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@ -21,7 +21,7 @@ import {
} from "@fortaine/fetch-event-source";
import { prettyObject } from "@/app/utils/format";
import { getClientConfig } from "@/app/config/client";
import { getMessageTextContent, isVisionModel } from "@/app/utils";
import { getMessageTextContent } from "@/app/utils";
export interface OpenAIListModelResponse {
object: string;

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@ -12,6 +12,7 @@ import {
import Locale from "../../locales";
import { prettyObject } from "@/app/utils/format";
import { getMessageTextContent, isVisionModel } from "@/app/utils";
import { preProcessImageContent } from "@/app/utils/chat";
import { cloudflareAIGatewayUrl } from "@/app/utils/cloudflare";
export type MultiBlockContent = {
@ -93,7 +94,12 @@ export class ClaudeApi implements LLMApi {
},
};
const messages = [...options.messages];
// try get base64image from local cache image_url
const messages = [];
for (const v of options.messages) {
const content = await preProcessImageContent(v.content);
messages.push({ role: v.role, content });
}
const keys = ["system", "user"];
@ -135,6 +141,7 @@ export class ClaudeApi implements LLMApi {
content: content
.filter((v) => v.image_url || v.text)
.map(({ type, text, image_url }) => {
console.log("process message", type, text, image_url);
if (type === "text") {
return {
type,

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@ -14,6 +14,7 @@ import {
getMessageImages,
isVisionModel,
} from "@/app/utils";
import { preProcessImageContent } from "@/app/utils/chat";
export class GeminiProApi implements LLMApi {
path(path: string): string {
@ -56,7 +57,14 @@ export class GeminiProApi implements LLMApi {
async chat(options: ChatOptions): Promise<void> {
const apiClient = this;
let multimodal = false;
const messages = options.messages.map((v) => {
// try get base64image from local cache image_url
const _messages = [];
for (const v of options.messages) {
const content = await preProcessImageContent(v.content);
_messages.push({ role: v.role, content });
}
const messages = _messages.map((v) => {
let parts: any[] = [{ text: getMessageTextContent(v) }];
if (isVisionModel(options.config.model)) {
const images = getMessageImages(v);

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@ -11,6 +11,7 @@ import {
} from "@/app/constant";
import { useAccessStore, useAppConfig, useChatStore } from "@/app/store";
import { collectModelsWithDefaultModel } from "@/app/utils/model";
import { preProcessImageContent } from "@/app/utils/chat";
import { cloudflareAIGatewayUrl } from "@/app/utils/cloudflare";
import {
@ -105,10 +106,13 @@ export class ChatGPTApi implements LLMApi {
async chat(options: ChatOptions) {
const visionModel = isVisionModel(options.config.model);
const messages = options.messages.map((v) => ({
role: v.role,
content: visionModel ? v.content : getMessageTextContent(v),
}));
const messages = [];
for (const v of options.messages) {
const content = visionModel
? await preProcessImageContent(v.content)
: getMessageTextContent(v);
messages.push({ role: v.role, content });
}
const modelConfig = {
...useAppConfig.getState().modelConfig,

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@ -61,7 +61,7 @@ import {
isVisionModel,
} from "../utils";
import { compressImage } from "@/app/utils/chat";
import { uploadImage as uploadImageRemote } from "@/app/utils/chat";
import dynamic from "next/dynamic";
@ -1167,7 +1167,7 @@ function _Chat() {
...(await new Promise<string[]>((res, rej) => {
setUploading(true);
const imagesData: string[] = [];
compressImage(file, 256 * 1024)
uploadImageRemote(file)
.then((dataUrl) => {
imagesData.push(dataUrl);
setUploading(false);
@ -1209,7 +1209,7 @@ function _Chat() {
const imagesData: string[] = [];
for (let i = 0; i < files.length; i++) {
const file = event.target.files[i];
compressImage(file, 256 * 1024)
uploadImageRemote(file)
.then((dataUrl) => {
imagesData.push(dataUrl);
if (

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@ -21,6 +21,9 @@ export const BYTEDANCE_BASE_URL = "https://ark.cn-beijing.volces.com";
export const ALIBABA_BASE_URL = "https://dashscope.aliyuncs.com/api/";
export const CACHE_URL_PREFIX = "/api/cache";
export const UPLOAD_URL = `${CACHE_URL_PREFIX}/upload`;
export enum Path {
Home = "/",
Chat = "/chat",
@ -239,7 +242,7 @@ const baiduModels = [
"ernie-speed-128k",
"ernie-speed-8k",
"ernie-lite-8k",
"ernie-tiny-8k"
"ernie-tiny-8k",
];
const bytedanceModels = [

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@ -1,4 +1,5 @@
import heic2any from "heic2any";
import { CACHE_URL_PREFIX, UPLOAD_URL } from "@/app/constant";
// import heic2any from "heic2any";
export function compressImage(file: File, maxSize: number): Promise<string> {
return new Promise((resolve, reject) => {
@ -40,6 +41,7 @@ export function compressImage(file: File, maxSize: number): Promise<string> {
reader.onerror = reject;
if (file.type.includes("heic")) {
const heic2any = require("heic2any");
heic2any({ blob: file, toType: "image/jpeg" })
.then((blob) => {
reader.readAsDataURL(blob as Blob);
@ -52,3 +54,78 @@ export function compressImage(file: File, maxSize: number): Promise<string> {
reader.readAsDataURL(file);
});
}
export async function preProcessImageContent(
content: RequestMessage["content"],
) {
if (typeof content === "string") {
return content;
}
const result = [];
for (const part of content) {
if (part?.type == "image_url" && part?.image_url?.url) {
const url = await cacheImageToBase64Image(part?.image_url?.url);
result.push({ type: part.type, image_url: { url } });
} else {
result.push({ ...part });
}
}
return result;
}
const imageCaches = {};
export function cacheImageToBase64Image(imageUrl: string) {
if (imageUrl.includes(CACHE_URL_PREFIX)) {
if (!imageCaches[imageUrl]) {
const reader = new FileReader();
return fetch(imageUrl, {
method: "GET",
mode: "cors",
credentials: "include",
})
.then((res) => res.blob())
.then(
(blob) => (imageCaches[imageUrl] = compressImage(blob, 256 * 1024)),
); // compressImage
}
return Promise.resolve(imageCaches[imageUrl]);
}
return imageUrl;
}
export function base64Image2Blob(base64Data: string, contentType: string) {
const byteCharacters = atob(base64Data);
const byteNumbers = new Array(byteCharacters.length);
for (let i = 0; i < byteCharacters.length; i++) {
byteNumbers[i] = byteCharacters.charCodeAt(i);
}
const byteArray = new Uint8Array(byteNumbers);
return new Blob([byteArray], { type: contentType });
}
export function uploadImage(file: File): Promise<string> {
const body = new FormData();
body.append("file", file);
return fetch(UPLOAD_URL, {
method: "post",
body,
mode: "cors",
credentials: "include",
})
.then((res) => res.json())
.then((res) => {
console.log("res", res);
if (res?.code == 0 && res?.data) {
return res?.data;
}
throw Error(`upload Error: ${res?.msg}`);
});
}
export function removeImage(imageUrl: string) {
return fetch(imageUrl, {
method: "DELETE",
mode: "cors",
credentials: "include",
});
}

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@ -1,10 +1,13 @@
const CHATGPT_NEXT_WEB_CACHE = "chatgpt-next-web-cache";
const CHATGPT_NEXT_WEB_FILE_CACHE = "chatgpt-next-web-file";
let a="useandom-26T198340PX75pxJACKVERYMINDBUSHWOLF_GQZbfghjklqvwyzrict";let nanoid=(e=21)=>{let t="",r=crypto.getRandomValues(new Uint8Array(e));for(let n=0;n<e;n++)t+=a[63&r[n]];return t};
self.addEventListener("activate", function (event) {
console.log("ServiceWorker activated.");
});
self.addEventListener("install", function (event) {
self.skipWaiting(); // enable new version
event.waitUntil(
caches.open(CHATGPT_NEXT_WEB_CACHE).then(function (cache) {
return cache.addAll([]);
@ -12,4 +15,45 @@ self.addEventListener("install", function (event) {
);
});
self.addEventListener("fetch", (e) => {});
async function upload(request, url) {
const formData = await request.formData()
const file = formData.getAll('file')[0]
let ext = file.name.split('.').pop()
if (ext === 'blob') {
ext = file.type.split('/').pop()
}
const fileUrl = `${url.origin}/api/cache/${nanoid()}.${ext}`
// console.debug('file', file, fileUrl, request)
const cache = await caches.open(CHATGPT_NEXT_WEB_FILE_CACHE)
await cache.put(new Request(fileUrl), new Response(file, {
headers: {
'content-type': file.type,
'content-length': file.size,
'cache-control': 'no-cache', // file already store in disk
'server': 'ServiceWorker',
}
}))
return Response.json({ code: 0, data: fileUrl })
}
async function remove(request, url) {
const cache = await caches.open(CHATGPT_NEXT_WEB_FILE_CACHE)
const res = await cache.delete(request.url)
return Response.json({ code: 0 })
}
self.addEventListener("fetch", (e) => {
const url = new URL(e.request.url);
if (/^\/api\/cache/.test(url.pathname)) {
if ('GET' == e.request.method) {
e.respondWith(caches.match(e.request))
}
if ('POST' == e.request.method) {
e.respondWith(upload(e.request, url))
}
if ('DELETE' == e.request.method) {
e.respondWith(remove(e.request, url))
}
}
});

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@ -2,8 +2,15 @@ if ('serviceWorker' in navigator) {
window.addEventListener('load', function () {
navigator.serviceWorker.register('/serviceWorker.js').then(function (registration) {
console.log('ServiceWorker registration successful with scope: ', registration.scope);
registration.update().then(res => {
console.log('ServiceWorker registration update: ', res);
});
}, function (err) {
console.error('ServiceWorker registration failed: ', err);
});
navigator.serviceWorker.addEventListener('controllerchange', function() {
console.log('ServiceWorker controllerchange ');
window.location.reload(true);
});
});
}
}