save changes

src/lib/pinterest.ts

@@ -36,6 +36,81 @@ export async function getPinUrlFromPinterest(keyword: string): Promise<string |
     }
 }
 
+export async function downloadImagesFromPinterestSearch(keyword: string, count: number): Promise<string[]> {
+    const browser = await puppeteer.launch({ headless: false });
+    const page = await browser.newPage();
+    await page.setUserAgent('Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36');
+    await page.setViewport({ width: 1920, height: 1080 });
+    try {
+        const searchUrl = `https://www.pinterest.com/search/pins/?q=${encodeURIComponent(keyword)}`;
+        await page.goto(searchUrl, { waitUntil: 'networkidle2' });
+
+        logger.info(`Scrolling 3 times...`);
+        for (let i = 0; i < 3; i++) {
+            await page.evaluate('window.scrollTo(0, document.body.scrollHeight)');
+            await new Promise(resolve => setTimeout(resolve, Math.random() * 1000 + 1000));
+        }
+
+        const imageUrls = await page.$$eval('img', (imgs) => {
+            const urls: string[] = imgs.map(img => {
+                const srcset = img.getAttribute('srcset') || '';
+                if (!srcset) return '';
+                const parts = srcset.split(',').map(p => p.trim());
+                for (const part of parts) {
+                    const m = part.match(/^(\S+)\s+4x$/);
+                    if (m && m[1]) return m[1];
+                }
+                const src = img.src || '';
+                if (src.includes('/originals/')) return src;
+                return '';
+            }).filter(s => !!s && s.includes('pinimg'));
+            // Remove duplicates
+            return [...new Set(urls)];
+        });
+
+        if (imageUrls.length === 0) {
+            logger.warn(`No 4x image URLs found for keyword "${keyword}"`);
+            return [];
+        }
+
+        // shuffle and pick up to `count` unique images
+        const shuffled = imageUrls.slice().sort(() => 0.5 - Math.random());
+        const chosen = shuffled.slice(0, Math.min(count, shuffled.length));
+
+        const outDir = path.join(process.cwd(), 'download');
+        await fs.mkdir(outDir, { recursive: true });
+
+        const results: string[] = [];
+        for (let i = 0; i < chosen.length; i++) {
+            const src = chosen[i];
+            try {
+                const imgPage = await browser.newPage();
+                const resp = await imgPage.goto(src, { timeout: 30000, waitUntil: 'networkidle2' });
+                if (!resp) {
+                    logger.warn(`Failed to fetch image ${src}`);
+                    await imgPage.close();
+                    continue;
+                }
+                const buffer = await resp.buffer();
+                const timestamp = Date.now();
+                const outPath = path.join(outDir, `${keyword.replace(/\s+/g, '_')}_${timestamp}_${i}.png`);
+                await fs.writeFile(outPath, buffer);
+                results.push(outPath);
+                await imgPage.close();
+            } catch (err) {
+                logger.error(`Failed to download image ${src}:`, err);
+            }
+        }
+        return results;
+
+    } catch (error) {
+        logger.error(`Error while downloading images for keyword "${keyword}":`, error);
+        return [];
+    } finally {
+        await browser.close();
+    }
+}
+
 
 // Download up to `count` images from a pin URL by opening the pin page and scro lling up to 5 times to trigger lazy loading
 // Returns an array of saved image paths (may be empty)

src/product/generate_image.ts

@@ -0,0 +1,88 @@
+import * as fs from 'fs/promises';
+import * as path from 'path';
+import dotenv from 'dotenv';
+import { readJsonToPng, embedJsonToPng } from '../lib/util';
+import { convertImage } from '../lib/image-converter';
+
+dotenv.config();
+
+const inputDir = './generated/prompts';
+const outputDir = './generated/image';
+
+const COMFY_BASE_URL = process.env.SERVER2_COMFY_BASE_URL!;
+const COMFY_OUTPUT_DIR = process.env.SERVER2_COMFY_OUTPUT_DIR!;
+
+interface PngMetadata {
+    prompts: {
+        imagePrompt: string;
+        videoPrompt: string;
+    }[];
+}
+
+async function main() {
+    await fs.mkdir(outputDir, { recursive: true });
+
+    const files = await fs.readdir(inputDir);
+    let generatedImageIndex = 0;
+
+    for (const file of files) {
+        if (path.extname(file).toLowerCase() !== '.png') {
+            continue;
+        }
+
+        const inputFile = path.join(inputDir, file);
+        const metadata = await readJsonToPng(inputFile) as PngMetadata;
+
+        if (metadata && metadata.prompts && Array.isArray(metadata.prompts)) {
+            console.log(`Processing ${file} with ${metadata.prompts.length} prompt pairs.`);
+
+            const inputfolderFullpath = COMFY_OUTPUT_DIR.replace("output", "input");
+            await fs.copyFile(inputFile, path.join(inputfolderFullpath, file));
+
+            for (const promptPair of metadata.prompts) {
+                const { imagePrompt, videoPrompt } = promptPair;
+                const newFileName = `cleaned_prompt_generated_${generatedImageIndex}.png`;
+                generatedImageIndex++;
+                const outputPath = path.join(outputDir, newFileName);
+
+                try {
+                    await fs.access(outputPath);
+                    console.log(`File ${newFileName} already exists, skipping.`);
+                    continue;
+                } catch (error) {
+                    // File does not exist, proceed with generation
+                }
+
+                console.log(`Generating image for prompt: "${imagePrompt}"`);
+
+                try {
+                    const generatedFilePath = await convertImage(
+                        imagePrompt,
+                        file, // Using the same image for both inputs as per interpretation
+                        COMFY_BASE_URL,
+                        COMFY_OUTPUT_DIR
+                    );
+
+                    // The convertImage function saves the file in a generic location.
+                    // We need to move it to the correct location with the correct name.
+                    await fs.rename(generatedFilePath, outputPath);
+
+                    const newMetadata = {
+                        imagePrompt: imagePrompt,
+                        videoPrompt: videoPrompt
+                    };
+
+                    await embedJsonToPng(outputPath, newMetadata);
+
+                    console.log(`Successfully generated and saved ${newFileName} with metadata.`);
+                } catch (error) {
+                    console.error(`Error generating image for prompt "${imagePrompt}":`, error);
+                }
+            }
+        } else {
+            console.log(`Skipping ${file}, no valid prompts metadata found.`);
+        }
+    }
+}
+
+main().catch(console.error);

src/product/generate_prompt.ts

@@ -1,7 +1,10 @@
 import * as fs from 'fs';
 import * as path from 'path';
 import { callLMStudioAPIWithFile, callLmstudio } from '../lib/lmstudio';
-import { embedJsonToPng, readJsonToPng } from '../lib/util';
+import { embedJsonToPng } from '../lib/util';
+import { downloadImagesFromPinterestSearch } from '../lib/pinterest';
+import { logger } from '../lib/logger';
+import sharp from 'sharp';
 
 const INPUT_DIR = path.join(process.cwd(), 'input');
 const OUTPUT_DIR = path.join(process.cwd(), 'generated', 'prompts');
@@ -10,148 +13,91 @@ if (!fs.existsSync(OUTPUT_DIR)) {
     fs.mkdirSync(OUTPUT_DIR, { recursive: true });
 }
 
-async function generatePromptsForImage(imagePath: string) {
+async function generatePromptsForImage(imagePath: string, index: number) {
-    const outputFilePath = path.join(OUTPUT_DIR, path.basename(imagePath));
+    const outputFilePath = path.join(OUTPUT_DIR, `cleaned_prompt_${index}.png`);
+    logger.info(`Processing image: ${path.basename(imagePath)} -> ${path.basename(outputFilePath)}`);
 
-    // Check if the output file already exists and has valid metadata
-    if (fs.existsSync(outputFilePath)) {
     try {
-            const existingMetadata = await readJsonToPng(outputFilePath);
+        // Step 1: Detect main object and generate colors from the input image
-            if (existingMetadata && existingMetadata.imagePrompts && existingMetadata.videoPrompt) {
+        const colorGenerationPrompt = `
-                console.log(`Skipping already processed image: ${path.basename(imagePath)}`);
+You are a creative assistant. Analyze the provided image.
-                return;
+Identify the main subject product ( not a product name).
-            }
+Then, list exactly five colors related to this subject:
-        } catch (error) {
+- Two colors that are common for this object.
-            // File exists but is invalid or has no metadata, so we'll overwrite it.
+- Two colors that are uncommon but plausible.
-            console.log(`Output file for ${path.basename(imagePath)} exists but is invalid. Regenerating...`);
+- One color that is completely crazy or surreal for this object.
-        }
-    }
 
-    console.log(`Processing image: ${imagePath}`);
-
-    // Step 1: Get main subject and sub-objects
-    const firstPrompt = `
-You are a creative director for unique product video generation.
-
-Read the given photo carefully.
-
-Identify and write the main subject (the most important object in the photo).
-Propose 20 possible sub-objects that could appear around the main subject in a video scene.
-Sub-objects are only suggestions.
-They should be stylish, cool, or complementary items that enhance the main subject.
-Keep each sub-object as a short noun phrase (no long explanations).
-Do not repeat similar items.
 Output strictly in this JSON format:
-
+{
-{result:{
+  "result": {
-"main-subject": "the identified main object",
+    "main_object": "the identified noun",
-"sub-object": [
+    "colors": [
-"first proposal",
+      "color1",
-"second proposal",
+      "color2",
-...
+      "color3",
-"twentieth proposal"
+      "color4",
-]
+      "color5"
-}}
-`;
-
-    try {
-        const firstApiResponse = await callLMStudioAPIWithFile(imagePath, firstPrompt);
-        const firstApiResult = firstApiResponse.result;
-        const mainSubject = firstApiResult['main-subject'];
-        const subObjects = firstApiResult['sub-object'];
-
-        if (!mainSubject || !Array.isArray(subObjects) || subObjects.length < 3) {
-            console.error('Invalid response from the first API call for image:', imagePath);
-            return;
-        }
-
-        // Step 2: Pick 3 random sub-objects
-        const selectedSubObjects = subObjects.sort(() => 0.5 - Math.random()).slice(0, 3);
-
-        // Step 3: Generate background proposals
-        const secondPrompt = `
-You are a senior creative director for product photography and video.
-Follow the instructions carefully.
-
-Task:
-1. Extract the main subject from Figure 1.
-2. Use the three selected sub-objects provided.
-3. Generate exactly five background prompt suggestions.
-
-SUB1: ${selectedSubObjects[0]}
-SUB2: ${selectedSubObjects[1]}
-SUB3: ${selectedSubObjects[2]}
-
-Requirements for background prompts:
-- All five suggestions must be written in English.
-- Every suggestion must begin with the phrase: "Extract the object from Figure 1 and generate a new image."
-- After that phrase, always instruct to place the three sub-objects in the scene.
-  Example: "and include Pink silk scarf, Pearl necklace, Pink lipstick in the scene."
-- Each suggestion must also describe:
-  - Background color (must always include pink)
-  - Lighting (direction, mood, intensity)
-  - Style or design elements (minimal, futuristic, luxury, natural, abstract, etc.)
-- Try to describe detail for each sugegstion. > 50 words.
-- Suggestions must be visually distinct.
-- Each suggestion must use a completely different background color palette while still incorporating pink.
-- Do not mention brand names or logos.
-
-Special condition:
-- In the new image, always place a pink silk scarf.
-- The background color must always be pink.
-
-Output strictly in JSON format:
-
-{result:{
-  "main-subject": "${mainSubject}",
-  "selected-sub-objects": ["${selectedSubObjects[0]}","${selectedSubObjects[1]}","${selectedSubObjects[2]}"],
-  "background-proposals": [
-    "Extract the object from Figure1 and generate a new image,{be creative and generate scene with ${selectedSubObjects[0]},${selectedSubObjects[1]},${selectedSubObjects[2]} }",
-    "Extract the object from Figure1 and generate a new image,{be creative and generate scene with ${selectedSubObjects[0]},${selectedSubObjects[1]},${selectedSubObjects[2]} }",
-    "Extract the object from Figure1 and generate a new image,{be creative and generate scene with ${selectedSubObjects[0]},${selectedSubObjects[1]},${selectedSubObjects[2]} }",
-    "Extract the object from Figure1 and generate a new image,{be creative and generate scene with ${selectedSubObjects[0]},${selectedSubObjects[1]},${selectedSubObjects[2]} }",
-    "Extract the object from Figure1 and generate a new image,{be creative and generate scene with ${selectedSubObjects[0]},${selectedSubObjects[1]},${selectedSubObjects[2]} }"
     ]
-    }}
+  }
+}
 `;
+        const colorResponse = await callLMStudioAPIWithFile(imagePath, colorGenerationPrompt);
+        const { main_object, colors } = colorResponse.result;
 
-        const secondApiResponse = await callLMStudioAPIWithFile(imagePath, secondPrompt);
+        if (!main_object || !Array.isArray(colors) || colors.length !== 5) {
-        const secondApiResult = secondApiResponse.result;
+            logger.error(`Failed to get a valid main object and color list for ${imagePath}.`);
-        const backgroundProposals = secondApiResult['background-proposals'];
-
-        if (!Array.isArray(backgroundProposals) || backgroundProposals.length !== 5) {
-            console.error('Invalid response from the second API call for image:', imagePath);
             return;
         }
 
-        // Step 4: Translate proposals to Chinese
+        logger.info(`Main object: "${main_object}", Colors: ${colors.join(', ')}`);
-        const translatedProposals: string[] = [];
-        for (const proposal of backgroundProposals) {
-            const translationPrompt = `Translate the following English text to Chinese. Return only the translated text.
 
-Text: "${proposal}"
+        const prompts: { imagePrompt: string, videoPrompt: string }[] = [];
+        const themes = ["special", "unique", "beautiful", "crazy", "funny"];
 
-Return the result in this format:
+        // Step 2: Iterate through each color
-{"result":""}
+        for (const color of colors) {
-`;
+            const randomTheme = themes[Math.floor(Math.random() * themes.length)];
-            const translationResponse = await callLmstudio(translationPrompt);
+            const pinterestQuery = `${main_object} product photo ${color} background ${randomTheme}`;
-            const translatedResult = translationResponse.result;
+            logger.info(`Searching Pinterest for: "${pinterestQuery}"`);
-            translatedProposals.push(translationResponse.result);
+
+            // Step 3: Get an image from Pinterest
+            const downloadedImages = await downloadImagesFromPinterestSearch(pinterestQuery, 1);
+            if (downloadedImages.length === 0) {
+                logger.warn(`Could not find an image on Pinterest for query: "${pinterestQuery}"`);
+                continue;
             }
+            const pinterestImagePath = downloadedImages[0];
+            logger.info(`Downloaded Pinterest image: ${pinterestImagePath}`);
 
-        // Step 5: Generate video prompt
+            // Step 4: Generate a detailed prompt from the Pinterest image
+            const imagePromptRequest = `
+You are an expert in generating descriptive prompts for image generation models.
+Analyze the provided image and describe it in a single, detailed paragraph.
+Focus on style, mood, lighting, color palette, sub-objects, and composition.
+Do not mention the main object itself. The prompt should be about the scene.
+
+Output strictly in this JSON format:
+{
+  "result": "your generated prompt here"
+}
+`;
+            const imagePromptResponse = await callLMStudioAPIWithFile(pinterestImagePath, imagePromptRequest);
+            const imagePrompt = imagePromptResponse.result;
+
+            if (imagePrompt) {
+                logger.info(`Generated image prompt for color ${color}: "${imagePrompt}"`);
+
+                // Step 5: Generate a matching video prompt
                 const videoPromptRequest = `
 You are a creative director for a short, stylish video ad.
 Based on the provided image and the following scene description, generate an attractive video prompt.
 
-Main Subject: ${mainSubject}
+Main Subject: ${main_object}
-Sub-Objects: ${selectedSubObjects.join(', ')}
+Scene Description: ${imagePrompt}
-Scene Description: ${backgroundProposals[0]}
 
 The video prompt should:
-- Be in English.
+- Be in English and approximately 50 words.
-- Be approximately 50 words.
+- Describe one clear action involving the main subject.
-- Describe one clear action involving the main subject and sub-objects.
 - Include one specific camera movement (e.g., slow zoom in, orbiting shot, push-in, pull-out).
 - Be dynamic and visually appealing.
 
@@ -160,27 +106,41 @@ Output strictly in this JSON format:
   "result": "your generated video prompt here"
 }
 `;
-        const videoPromptResponse = await callLMStudioAPIWithFile(imagePath, videoPromptRequest);
+                const videoPromptResponse = await callLMStudioAPIWithFile(pinterestImagePath, videoPromptRequest);
                 const videoPrompt = videoPromptResponse.result;
 
-        if (!videoPrompt) {
+                if (videoPrompt) {
-            console.error('Failed to generate video prompt for image:', imagePath);
+                    logger.info(`Generated video prompt for color ${color}: "${videoPrompt}"`);
+                    prompts.push({ imagePrompt, videoPrompt });
+                } else {
+                    logger.warn(`Failed to generate a video prompt for ${pinterestImagePath}`);
+                }
+            } else {
+                logger.warn(`Failed to generate an image prompt for ${pinterestImagePath}`);
+            }
+        }
+
+        if (prompts.length === 0) {
+            logger.error(`No prompt pairs were generated for ${imagePath}. Aborting.`);
             return;
         }
 
-        // Step 6: Embed all prompts into PNG metadata
+        // Step 6: Embed all prompts into the original image and save to the new location
         const metadata = {
-            imagePrompts: translatedProposals,
+            prompts: prompts
-            videoPrompt: videoPrompt
         };
 
-        fs.copyFileSync(imagePath, outputFilePath);
+        // Convert original image to a valid PNG at the output path before embedding
+        await sharp(imagePath)
+            .toFormat('png')
+            .toFile(outputFilePath);
+
         await embedJsonToPng(outputFilePath, metadata);
 
-        console.log(`Successfully generated prompts and saved to ${outputFilePath}`);
+        logger.info(`Successfully generated prompts and saved metadata to ${outputFilePath}`);
 
     } catch (error) {
-        console.error(`Failed to process image ${imagePath}:`, error);
+        logger.error(`An error occurred while processing ${imagePath}:`, error);
     }
 }
 
@@ -194,9 +154,10 @@ async function main() {
             return;
         }
 
-        for (const imageFile of imageFiles) {
+        for (let i = 0; i < imageFiles.length; i++) {
+            const imageFile = imageFiles[i];
             const imagePath = path.join(INPUT_DIR, imageFile);
-            await generatePromptsForImage(imagePath);
+            await generatePromptsForImage(imagePath, i);
         }
 
         console.log('All images processed.');

src/product/generate_video.ts

@@ -0,0 +1,74 @@
+import * as fs from 'fs/promises';
+import * as path from 'path';
+import dotenv from 'dotenv';
+import { readJsonToPng } from '../lib/util';
+import { generateVideo } from '../lib/video-generator';
+
+dotenv.config();
+
+const inputDir = './input';
+const outputDir = './generated/video';
+
+const COMFY_BASE_URL = process.env.SERVER2_COMFY_BASE_URL!;
+const COMFY_OUTPUT_DIR = process.env.SERVER2_COMFY_OUTPUT_DIR!;
+
+
+interface PngMetadata {
+    imagePrompt: string;
+    videoPrompt: string;
+}
+
+async function main() {
+    await fs.mkdir(outputDir, { recursive: true });
+
+    const files = await fs.readdir(inputDir);
+    const pngFiles = files.filter(file => path.extname(file).toLowerCase() === '.png');
+
+    for (let i = 0; i < pngFiles.length; i++) {
+        const file = pngFiles[i];
+
+        const inputFile = path.join(inputDir, file);
+        const metadata = await readJsonToPng(inputFile) as PngMetadata;
+
+        if (metadata && metadata.videoPrompt) {
+            console.log(`Processing ${file} for video generation.`);
+
+            const originalFileName = path.parse(file).name;
+            const nameParts = originalFileName.split('_');
+            const promptIndex = nameParts[nameParts.length - 1];
+            const newFileName = `product_${i}_${promptIndex}.mp4`;
+            const outputPath = path.join(outputDir, newFileName);
+
+            try {
+                await fs.access(outputPath);
+                console.log(`File ${newFileName} already exists, skipping.`);
+                continue;
+            } catch (error) {
+                // File does not exist, proceed with generation
+            }
+
+            console.log(`Generating video for prompt: "${metadata.videoPrompt}"`);
+
+            const inputfolderFullpath = COMFY_OUTPUT_DIR.replace("output", "input");
+            await fs.copyFile(inputFile, path.join(inputfolderFullpath, file));
+
+            try {
+                await generateVideo(
+                    metadata.videoPrompt,
+                    file,
+                    newFileName,
+                    COMFY_BASE_URL,
+                    COMFY_OUTPUT_DIR
+                );
+
+                console.log(`Successfully generated and saved ${newFileName}`);
+            } catch (error) {
+                console.error(`Error generating video for ${file}:`, error);
+            }
+        } else {
+            console.log(`Skipping ${file}, no valid videoPrompt metadata found.`);
+        }
+    }
+}
+
+main().catch(console.error);