mirror of
https://github.com/jina-ai/node-DeepResearch.git
synced 2025-12-25 22:16:49 +08:00
fix oom issue
This commit is contained in:
parent
2b3004c80e
commit
1156990682
654
package-lock.json
generated
654
package-lock.json
generated
@ -11,7 +11,6 @@
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"@types/jsdom": "^21.1.7",
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"ai": "^4.1.26",
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"axios": "^1.7.9",
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@ -23,6 +22,7 @@
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"hjson": "^3.2.2",
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"jsdom": "^26.0.0",
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"node-fetch": "^3.3.2",
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"undici": "^7.3.0",
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"zod": "^3.22.4",
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"zod-to-json-schema": "^3.24.1"
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@ -896,6 +896,15 @@
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"node": ">=18"
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}
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@ -1045,6 +1054,381 @@
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"funding": {
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@ -3126,9 +3351,17 @@
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@ -3462,11 +3695,9 @@
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|
||||
"integrity": "sha512-eVRqCvVlZbuw3GrM63ovNSNAeA1K16kaR/LRY/92w0zxQ5/1YzwblUX652i4Xs9RwAGjW9d9y6X88t8OaAJfWQ=="
|
||||
},
|
||||
"node_modules/sisteransi": {
|
||||
"version": "1.0.5",
|
||||
"resolved": "https://registry.npmjs.org/sisteransi/-/sisteransi-1.0.5.tgz",
|
||||
@ -7969,6 +8251,12 @@
|
||||
}
|
||||
}
|
||||
},
|
||||
"node_modules/tslib": {
|
||||
"version": "2.8.1",
|
||||
"resolved": "https://registry.npmjs.org/tslib/-/tslib-2.8.1.tgz",
|
||||
"integrity": "sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w==",
|
||||
"optional": true
|
||||
},
|
||||
"node_modules/tunnel-agent": {
|
||||
"version": "0.6.0",
|
||||
"resolved": "https://registry.npmjs.org/tunnel-agent/-/tunnel-agent-0.6.0.tgz",
|
||||
|
||||
@ -28,7 +28,6 @@
|
||||
"dependencies": {
|
||||
"@ai-sdk/google": "^1.0.0",
|
||||
"@ai-sdk/openai": "^1.1.9",
|
||||
"@napi-rs/canvas": "^0.1.68",
|
||||
"@types/jsdom": "^21.1.7",
|
||||
"ai": "^4.1.26",
|
||||
"axios": "^1.7.9",
|
||||
@ -40,6 +39,7 @@
|
||||
"hjson": "^3.2.2",
|
||||
"jsdom": "^26.0.0",
|
||||
"node-fetch": "^3.3.2",
|
||||
"sharp": "^0.34.2",
|
||||
"undici": "^7.3.0",
|
||||
"zod": "^3.22.4",
|
||||
"zod-to-json-schema": "^3.24.1"
|
||||
|
||||
@ -1,10 +1,9 @@
|
||||
import canvas from '@napi-rs/canvas';
|
||||
import { getEmbeddings } from '../tools/embeddings';
|
||||
import { TokenTracker } from './token-tracker';
|
||||
import { ImageObject } from '../types';
|
||||
import { cosineSimilarity } from '../tools/cosine';
|
||||
import { logInfo, logError, logDebug, logWarning } from '../logging';
|
||||
export type { Canvas, Image } from '@napi-rs/canvas';
|
||||
import sharp from 'sharp';
|
||||
|
||||
export const downloadFile = async (uri: string) => {
|
||||
const resp = await fetch(uri);
|
||||
@ -16,13 +15,17 @@ export const downloadFile = async (uri: string) => {
|
||||
throw new Error('File too large');
|
||||
}
|
||||
const buff = await resp.arrayBuffer();
|
||||
const contentType = resp.headers.get('content-type');
|
||||
if (!contentType || !contentType.startsWith('image/')) {
|
||||
throw new Error(`Invalid content type ${contentType}, expected image/*`);
|
||||
}
|
||||
|
||||
return { buff, contentType: resp.headers.get('content-type') };
|
||||
return { buff, contentType };
|
||||
};
|
||||
|
||||
const _loadImage = async (input: string | Buffer) => {
|
||||
const loadImage = async (input: string | Buffer) => {
|
||||
let buff;
|
||||
let contentType;
|
||||
let contentType: string = '';
|
||||
|
||||
if (typeof input === 'string') {
|
||||
if (input.startsWith('data:')) {
|
||||
@ -51,71 +54,65 @@ const _loadImage = async (input: string | Buffer) => {
|
||||
throw new Error('Invalid input');
|
||||
}
|
||||
|
||||
const img = await canvas.loadImage(buff).catch((err) => {
|
||||
logError('Error loading image:', { error: err });
|
||||
return undefined;
|
||||
});
|
||||
if (buff.length > 20 * 1024 * 1024) {
|
||||
throw new Error('Image too large');
|
||||
}
|
||||
|
||||
return img;
|
||||
return {
|
||||
buff,
|
||||
contentType,
|
||||
};
|
||||
}
|
||||
|
||||
export const loadImage = async (uri: string | Buffer) => {
|
||||
try {
|
||||
const theImage = await _loadImage(uri);
|
||||
const ImageTypes = ['png', 'jpeg', 'jpg', 'webp', 'avif', 'tiff', 'gif', 'svg', 'bmp', 'heif', 'jxl', 'jp2', 'ppm', 'raw', 'exr', 'fits', 'rad'];
|
||||
|
||||
return theImage;
|
||||
} catch (err: any) {
|
||||
if (err?.message?.includes('Unsupported image type') || err?.message?.includes('unsupported')) {
|
||||
throw new Error(`Unknown image format for ${uri.slice(0, 128)}`);
|
||||
export const fitImageToSquareBox = async (imageBuffer: Buffer, contentType: string, size: number = 1024) => {
|
||||
if (!imageBuffer || imageBuffer.length === 0) {
|
||||
throw new Error('Invalid image buffer');
|
||||
}
|
||||
|
||||
const metadata = await sharp(imageBuffer).metadata();
|
||||
if (!metadata.width || !metadata.height || metadata.width < 256 || metadata.height < 256) {
|
||||
throw new Error('Image must be at least 256x256 pixels');
|
||||
}
|
||||
|
||||
let width = metadata.width;
|
||||
let height = metadata.height;
|
||||
const targetSize = size;
|
||||
const imageType = contentType.split('/')[1];
|
||||
if (!ImageTypes.includes(imageType)) {
|
||||
throw new Error(`Unsupported image type: ${imageType}`);
|
||||
}
|
||||
|
||||
if (width > targetSize || height > targetSize) {
|
||||
const aspectRatio = width / height;
|
||||
|
||||
if (aspectRatio > 1) {
|
||||
width = targetSize;
|
||||
height = Math.round(targetSize / aspectRatio);
|
||||
} else {
|
||||
height = targetSize;
|
||||
width = Math.round(targetSize * aspectRatio);
|
||||
}
|
||||
throw err;
|
||||
}
|
||||
}
|
||||
|
||||
// 调整图片大小
|
||||
const resizedImageBuffer = await sharp(imageBuffer)
|
||||
.resize(width, height, {
|
||||
fit: 'inside',
|
||||
withoutEnlargement: true
|
||||
})
|
||||
.toFormat(imageType as any)
|
||||
.toBuffer();
|
||||
|
||||
export const fitImageToSquareBox = (image: canvas.Image | canvas.Canvas, size: number = 1024) => {
|
||||
if (image.width <= size && image.height <= size) {
|
||||
const canvasInstance = canvas.createCanvas(image.width, image.height);
|
||||
const ctx = canvasInstance.getContext('2d');
|
||||
ctx.drawImage(image, 0, 0, image.width, image.height, 0, 0, canvasInstance.width, canvasInstance.height);
|
||||
|
||||
return canvasInstance;
|
||||
}
|
||||
|
||||
const aspectRatio = image.width / image.height;
|
||||
|
||||
const resizedWidth = Math.round(aspectRatio > 1 ? size : size * aspectRatio);
|
||||
const resizedHeight = Math.round(aspectRatio > 1 ? size / aspectRatio : size);
|
||||
|
||||
const canvasInstance = canvas.createCanvas(resizedWidth, resizedHeight);
|
||||
const ctx = canvasInstance.getContext('2d');
|
||||
ctx.drawImage(image, 0, 0, image.width, image.height, 0, 0, resizedWidth, resizedHeight);
|
||||
|
||||
return canvasInstance;
|
||||
}
|
||||
|
||||
|
||||
export const canvasToDataUrl = (canvas: canvas.Canvas, mimeType?: 'image/png' | 'image/jpeg') => {
|
||||
return canvas.toDataURLAsync((mimeType || 'image/png') as 'image/png');
|
||||
}
|
||||
|
||||
export const canvasToBuffer = (canvas: canvas.Canvas, mimeType?: 'image/png' | 'image/jpeg') => {
|
||||
return canvas.toBuffer((mimeType || 'image/png') as 'image/png');
|
||||
return resizedImageBuffer.toString('base64');
|
||||
}
|
||||
|
||||
export const processImage = async (url: string, tracker: TokenTracker): Promise<ImageObject | undefined> => {
|
||||
try {
|
||||
const img = await loadImage(url);
|
||||
if (!img) {
|
||||
return;
|
||||
}
|
||||
const { buff, contentType } = await loadImage(url);
|
||||
const base64Data = await fitImageToSquareBox(buff, contentType, 256);
|
||||
|
||||
// Check if the image is smaller than 256x256
|
||||
if (img.width < 256 || img.height < 256) {
|
||||
return;
|
||||
}
|
||||
|
||||
const canvas = fitImageToSquareBox(img, 256);
|
||||
const base64Data = (await canvasToDataUrl(canvas)).split(',')[1];
|
||||
|
||||
const { embeddings } = await getEmbeddings([{ image: base64Data }], tracker, {
|
||||
dimensions: 512,
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user