save current changes

.env

@@ -0,0 +1,2 @@
+LLM_BASE_URL=http://192.168.1.117:1234/
+LOG_LEVEL=INFO

.gitignore

@@ -17,3 +17,6 @@
 npm-debug.log*
 yarn-debug.log*
 yarn-error.log*
+
+# Downloaded images
+/download/

package.json

@@ -12,7 +12,11 @@
     "author": "",
     "license": "ISC",
     "devDependencies": {
-        "typescript": "^5.0.0",
-        "@types/node": "^20.0.0"
+        "@types/node": "^20.0.0",
+        "typescript": "^5.0.0"
+    },
+    "dependencies": {
+        "dotenv": "^17.2.1",
+        "puppeteer": "^24.16.2"
     }
 }

src/index.ts

@@ -1 +1,29 @@
-console.log("Hello, TypeScript! 2");
+import { downloadPinterestImages } from './lib/downloader';
+import { describeImage } from './lib/image-describer';
+import { logger, setLogLevel, LogLevel } from './lib/logger';
+
+(async () => {
+    const keyword = 'cyberpunk city';
+    const numberOfPages = 1;
+    const imagePaths = await downloadPinterestImages(keyword, numberOfPages);
+    logger.info('Downloaded images:', imagePaths);
+
+    for (const imagePath of imagePaths) {
+        try {
+            const llmResponseJSON = await describeImage(imagePath,
+                `Describe this image as a prompt for an image generation model.
+                Prompt should be in 200 words.
+                Output should be in this format
+                ---
+                {
+                    "prompt":""
+                }
+                ---
+                `);
+            const prompt = llmResponseJSON.prompt;
+            logger.info(`Description for ${imagePath}:`, prompt);
+        } catch (error) {
+            logger.error(`Failed to describe ${imagePath}:`, error);
+        }
+    }
+})();

src/lib/downloader.ts

@@ -0,0 +1,85 @@
+import puppeteer from 'puppeteer';
+import fs from 'fs';
+import path from 'path';
+import { logger } from './logger';
+
+const downloadPath = path.resolve(__dirname, '../../download');
+
+if (!fs.existsSync(downloadPath)) {
+    fs.mkdirSync(downloadPath, { recursive: true });
+}
+
+async function downloadImage(url: string, filepath: string) {
+    const response = await fetch(url);
+    const buffer = await response.arrayBuffer();
+    fs.writeFileSync(filepath, Buffer.from(buffer));
+}
+
+export async function downloadPinterestImages(keyword: string, numberOfPages: number): Promise<string[]> {
+    const browser = await puppeteer.launch({ headless: true });
+    const page = await browser.newPage();
+    await page.setUserAgent('Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36');
+    await page.setViewport({ width: 1280, height: 800 });
+
+    const encodedKeyword = encodeURIComponent(keyword);
+    await page.goto(`https://www.pinterest.com/search/pins/?q=${encodedKeyword}`, { waitUntil: 'networkidle2' });
+
+    logger.debug('Searching for:', keyword);
+
+    let imageCount = 0;
+    const downloadedUrls = new Set<string>();
+    const downloadedImagePaths: string[] = [];
+
+    for (let i = 0; i < numberOfPages; i++) {
+        logger.debug(`Scraping page ${i + 1}...`);
+        try {
+            const imageUrls = await page.evaluate(() => {
+                const images = Array.from(document.querySelectorAll('img[src*="i.pinimg.com"]'));
+                const urls = images.map(img => {
+                    const srcset = (img as HTMLImageElement).srcset;
+                    if (srcset) {
+                        const sources = srcset.split(',').map(s => s.trim());
+                        const source4x = sources.find(s => s.endsWith(' 4x'));
+                        if (source4x) {
+                            return source4x.split(' ')[0];
+                        }
+                    }
+                    return null;
+                });
+                return urls.filter((url): url is string => url !== null);
+            });
+
+            for (const url of imageUrls) {
+                if (!downloadedUrls.has(url)) {
+                    downloadedUrls.add(url);
+                    const extension = path.extname(new URL(url).pathname) || '.jpg';
+                    const filename = `${keyword.replace(/ /g, '_')}_${imageCount++}${extension}`;
+                    const filepath = path.join(downloadPath, filename);
+                    logger.debug(`Downloading ${url} to ${filepath}`);
+                    await downloadImage(url, filepath);
+                    downloadedImagePaths.push(filepath);
+                }
+            }
+
+            const previousHeight = await page.evaluate('document.body.scrollHeight');
+            await page.evaluate('window.scrollTo(0, document.body.scrollHeight)');
+
+            try {
+                await page.waitForFunction(`document.body.scrollHeight > ${previousHeight}`, { timeout: 10000 });
+            } catch (e) {
+                logger.debug('No more content to load.');
+                break;
+            }
+
+            await new Promise(resolve => setTimeout(resolve, 1000)); // Small delay for images to render
+        } catch (error) {
+            logger.error(`An error occurred while scraping page ${i + 1}:`, error);
+            logger.debug('Stopping the scraping process due to an error.');
+            break;
+        }
+    }
+
+    await browser.close();
+    logger.debug('Done.');
+    return downloadedImagePaths;
+}

src/lib/image-describer.ts

@@ -0,0 +1,66 @@
+import fs from 'fs';
+import path from 'path';
+import dotenv from 'dotenv';
+import { logger } from './logger';
+
+dotenv.config();
+
+const LLM_BASE_URL = process.env.LLM_BASE_URL;
+
+async function describeImage(imagePath: string, prompt: string): Promise<any> {
+    if (!LLM_BASE_URL) {
+        throw new Error('LLM_BASE_URL is not defined in the .env file');
+    }
+
+    const imageBuffer = fs.readFileSync(imagePath);
+    const base64Image = imageBuffer.toString('base64');
+
+    for (let i = 0; i < 10; i++) {
+        let llmResponse = "";
+
+        try {
+            const requestUrl = new URL('v1/chat/completions', LLM_BASE_URL);
+            const response = await fetch(requestUrl, {
+                method: 'POST',
+                headers: {
+                    'Content-Type': 'application/json',
+                },
+                body: JSON.stringify({
+                    model: 'local-model',
+                    messages: [
+                        {
+                            role: 'user',
+                            content: [
+                                { type: 'image_url', image_url: { url: `data:image/jpeg;base64,${base64Image}` } },
+                                { type: 'text', text: prompt },
+                            ],
+                        },
+                    ],
+                    temperature: 0.7,
+                }),
+            });
+
+            const data = await response.json();
+            if (data.choices && data.choices.length > 0) {
+                const content = data.choices[0].message.content;
+                llmResponse = content;
+                const jsonMatch = content.match(/\{[\s\S]*\}/);
+                if (jsonMatch) {
+                    return JSON.parse(jsonMatch[0]);
+                }
+            } else {
+                logger.error('Unexpected API response:', data);
+            }
+        } catch (error) {
+            logger.error(`Attempt ${i + 1} failed:`, error);
+            if (error instanceof TypeError && error.message.includes('fetch failed')) {
+                logger.error('Could not connect to the LM Studio server. Please ensure the server is running and accessible at the specified LLM_BASE_URL.');
+            }
+            logger.debug(`LLM response: ${llmResponse}`)
+        }
+    }
+
+    throw new Error('Failed to describe image after 10 attempts');
+}
+
+export { describeImage };

src/lib/logger.ts

@@ -0,0 +1,60 @@
+import dotenv from 'dotenv';
+
+dotenv.config();
+
+export enum LogLevel {
+    NONE = 0,
+    ERROR = 1,
+    WARN = 2,
+    INFO = 3,
+    DEBUG = 4,
+}
+
+const getLogLevelFromString = (level: string | undefined): LogLevel => {
+    if (!level) {
+        return LogLevel.INFO;
+    }
+    switch (level.toUpperCase()) {
+        case 'NONE':
+            return LogLevel.NONE;
+        case 'ERROR':
+            return LogLevel.ERROR;
+        case 'WARN':
+            return LogLevel.WARN;
+        case 'INFO':
+            return LogLevel.INFO;
+        case 'DEBUG':
+            return LogLevel.DEBUG;
+        default:
+            return LogLevel.INFO;
+    }
+};
+
+let currentLogLevel: LogLevel = getLogLevelFromString(process.env.LOG_LEVEL);
+
+export function setLogLevel(level: LogLevel) {
+    currentLogLevel = level;
+}
+
+export const logger = {
+    error: (...args: any[]) => {
+        if (currentLogLevel >= LogLevel.ERROR) {
+            console.error(...args);
+        }
+    },
+    warn: (...args: any[]) => {
+        if (currentLogLevel >= LogLevel.WARN) {
+            console.warn(...args);
+        }
+    },
+    info: (...args: any[]) => {
+        if (currentLogLevel >= LogLevel.INFO) {
+            console.info(...args);
+        }
+    },
+    debug: (...args: any[]) => {
+        if (currentLogLevel >= LogLevel.DEBUG) {
+            console.debug(...args);
+        }
+    },
+};