feat: implement SparkPlug backend API integration for Gemini and Meshy

backend/package-lock.json

@@ -8,6 +8,8 @@
       "name": "titan3d-backend",
       "version": "1.0.0",
       "dependencies": {
+        "@google/generative-ai": "^0.24.1",
+        "axios": "^1.20.0",
         "bcrypt": "^5.1.1",
         "cors": "^2.8.5",
         "dotenv": "^17.4.2",
@@ -15,10 +17,20 @@
         "jsonwebtoken": "^9.0.2",
         "multer": "^1.4.5-lts.1",
         "nodemailer": "^9.0.5",
+        "pdf-parse": "^2.4.5",
         "pg": "^8.23.0",
         "uuid": "^9.0.1"
       }
     },
+    "node_modules/@google/generative-ai": {
+      "version": "0.24.1",
+      "resolved": "https://registry.npmjs.org/@google/generative-ai/-/generative-ai-0.24.1.tgz",
+      "integrity": "sha512-MqO+MLfM6kjxcKoy0p1wRzG3b4ZZXtPI+z2IE26UogS2Cm/XHO+7gGRBh6gcJsOiIVoH93UwKvW4HdgiOZCy9Q==",
+      "license": "Apache-2.0",
+      "engines": {
+        "node": ">=18.0.0"
+      }
+    },
     "node_modules/@mapbox/node-pre-gyp": {
       "version": "1.0.11",
       "resolved": "https://registry.npmjs.org/@mapbox/node-pre-gyp/-/node-pre-gyp-1.0.11.tgz",
@@ -39,6 +51,190 @@
         "node-pre-gyp": "bin/node-pre-gyp"
       }
     },
+    "node_modules/@napi-rs/canvas": {
+      "version": "0.1.80",
+      "resolved": "https://registry.npmjs.org/@napi-rs/canvas/-/canvas-0.1.80.tgz",
+      "integrity": "sha512-DxuT1ClnIPts1kQx8FBmkk4BQDTfI5kIzywAaMjQSXfNnra5UFU9PwurXrl+Je3bJ6BGsp/zmshVVFbCmyI+ww==",
+      "license": "MIT",
+      "workspaces": [
+        "e2e/*"
+      ],
+      "engines": {
+        "node": ">= 10"
+      },
+      "optionalDependencies": {
+        "@napi-rs/canvas-android-arm64": "0.1.80",
+        "@napi-rs/canvas-darwin-arm64": "0.1.80",
+        "@napi-rs/canvas-darwin-x64": "0.1.80",
+        "@napi-rs/canvas-linux-arm-gnueabihf": "0.1.80",
+        "@napi-rs/canvas-linux-arm64-gnu": "0.1.80",
+        "@napi-rs/canvas-linux-arm64-musl": "0.1.80",
+        "@napi-rs/canvas-linux-riscv64-gnu": "0.1.80",
+        "@napi-rs/canvas-linux-x64-gnu": "0.1.80",
+        "@napi-rs/canvas-linux-x64-musl": "0.1.80",
+        "@napi-rs/canvas-win32-x64-msvc": "0.1.80"
+      }
+    },
+    "node_modules/@napi-rs/canvas-android-arm64": {
+      "version": "0.1.80",
+      "resolved": "https://registry.npmjs.org/@napi-rs/canvas-android-arm64/-/canvas-android-arm64-0.1.80.tgz",
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+      "cpu": [
+        "arm64"
+      ],
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "android"
+      ],
+      "engines": {
+        "node": ">= 10"
+      }
+    },
+    "node_modules/@napi-rs/canvas-darwin-arm64": {
+      "version": "0.1.80",
+      "resolved": "https://registry.npmjs.org/@napi-rs/canvas-darwin-arm64/-/canvas-darwin-arm64-0.1.80.tgz",
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+      "cpu": [
+        "arm64"
+      ],
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "darwin"
+      ],
+      "engines": {
+        "node": ">= 10"
+      }
+    },
+    "node_modules/@napi-rs/canvas-darwin-x64": {
+      "version": "0.1.80",
+      "resolved": "https://registry.npmjs.org/@napi-rs/canvas-darwin-x64/-/canvas-darwin-x64-0.1.80.tgz",
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+      "cpu": [
+        "x64"
+      ],
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "darwin"
+      ],
+      "engines": {
+        "node": ">= 10"
+      }
+    },
+    "node_modules/@napi-rs/canvas-linux-arm-gnueabihf": {
+      "version": "0.1.80",
+      "resolved": "https://registry.npmjs.org/@napi-rs/canvas-linux-arm-gnueabihf/-/canvas-linux-arm-gnueabihf-0.1.80.tgz",
+      "integrity": "sha512-eyWz0ddBDQc7/JbAtY4OtZ5SpK8tR4JsCYEZjCE3dI8pqoWUC8oMwYSBGCYfsx2w47cQgQCgMVRVTFiiO38hHQ==",
+      "cpu": [
+        "arm"
+      ],
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "linux"
+      ],
+      "engines": {
+        "node": ">= 10"
+      }
+    },
+    "node_modules/@napi-rs/canvas-linux-arm64-gnu": {
+      "version": "0.1.80",
+      "resolved": "https://registry.npmjs.org/@napi-rs/canvas-linux-arm64-gnu/-/canvas-linux-arm64-gnu-0.1.80.tgz",
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+      "cpu": [
+        "arm64"
+      ],
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "linux"
+      ],
+      "engines": {
+        "node": ">= 10"
+      }
+    },
+    "node_modules/@napi-rs/canvas-linux-arm64-musl": {
+      "version": "0.1.80",
+      "resolved": "https://registry.npmjs.org/@napi-rs/canvas-linux-arm64-musl/-/canvas-linux-arm64-musl-0.1.80.tgz",
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+      "cpu": [
+        "arm64"
+      ],
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "linux"
+      ],
+      "engines": {
+        "node": ">= 10"
+      }
+    },
+    "node_modules/@napi-rs/canvas-linux-riscv64-gnu": {
+      "version": "0.1.80",
+      "resolved": "https://registry.npmjs.org/@napi-rs/canvas-linux-riscv64-gnu/-/canvas-linux-riscv64-gnu-0.1.80.tgz",
+      "integrity": "sha512-XTzR125w5ZMs0lJcxRlS1K3P5RaZ9RmUsPtd1uGt+EfDyYMu4c6SEROYsxyatbbu/2+lPe7MPHOO/0a0x7L/gw==",
+      "cpu": [
+        "riscv64"
+      ],
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "linux"
+      ],
+      "engines": {
+        "node": ">= 10"
+      }
+    },
+    "node_modules/@napi-rs/canvas-linux-x64-gnu": {
+      "version": "0.1.80",
+      "resolved": "https://registry.npmjs.org/@napi-rs/canvas-linux-x64-gnu/-/canvas-linux-x64-gnu-0.1.80.tgz",
+      "integrity": "sha512-BeXAmhKg1kX3UCrJsYbdQd3hIMDH/K6HnP/pG2LuITaXhXBiNdh//TVVVVCBbJzVQaV5gK/4ZOCMrQW9mvuTqA==",
+      "cpu": [
+        "x64"
+      ],
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "linux"
+      ],
+      "engines": {
+        "node": ">= 10"
+      }
+    },
+    "node_modules/@napi-rs/canvas-linux-x64-musl": {
+      "version": "0.1.80",
+      "resolved": "https://registry.npmjs.org/@napi-rs/canvas-linux-x64-musl/-/canvas-linux-x64-musl-0.1.80.tgz",
+      "integrity": "sha512-x0XvZWdHbkgdgucJsRxprX/4o4sEed7qo9rCQA9ugiS9qE2QvP0RIiEugtZhfLH3cyI+jIRFJHV4Fuz+1BHHMg==",
+      "cpu": [
+        "x64"
+      ],
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "linux"
+      ],
+      "engines": {
+        "node": ">= 10"
+      }
+    },
+    "node_modules/@napi-rs/canvas-win32-x64-msvc": {
+      "version": "0.1.80",
+      "resolved": "https://registry.npmjs.org/@napi-rs/canvas-win32-x64-msvc/-/canvas-win32-x64-msvc-0.1.80.tgz",
+      "integrity": "sha512-Z8jPsM6df5V8B1HrCHB05+bDiCxjE9QA//3YrkKIdVDEwn5RKaqOxCJDRJkl48cJbylcrJbW4HxZbTte8juuPg==",
+      "cpu": [
+        "x64"
+      ],
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "win32"
+      ],
+      "engines": {
+        "node": ">= 10"
+      }
+    },
     "node_modules/abbrev": {
       "version": "1.1.1",
       "resolved": "https://registry.npmjs.org/abbrev/-/abbrev-1.1.1.tgz",
@@ -148,6 +344,24 @@
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       "license": "MIT"
     },
+    "node_modules/asynckit": {
+      "version": "0.4.0",
+      "resolved": "https://registry.npmjs.org/asynckit/-/asynckit-0.4.0.tgz",
+      "integrity": "sha512-Oei9OH4tRh0YqU3GxhX79dM/mwVgvbZJaSNaRk+bshkj0S5cfHcgYakreBjrHwatXKbz+IoIdYLxrKim2MjW0Q==",
+      "license": "MIT"
+    },
+    "node_modules/axios": {
+      "version": "1.20.0",
+      "resolved": "https://registry.npmjs.org/axios/-/axios-1.20.0.tgz",
+      "integrity": "sha512-r8aOh8j9cGKpgQAqpzrUHnSIc6a59Y3Xf/cv8sy1DrHCkZHzQGEuoq1tARk6qSyDdtQGSDgpb9kFlruzPvrgwg==",
+      "license": "MIT",
+      "dependencies": {
+        "follow-redirects": "^1.16.0",
+        "form-data": "^4.0.6",
+        "https-proxy-agent": "^5.0.1",
+        "proxy-from-env": "^2.1.0"
+      }
+    },
     "node_modules/balanced-match": {
       "version": "1.0.2",
       "resolved": "https://registry.npmjs.org/balanced-match/-/balanced-match-1.0.2.tgz",
@@ -281,6 +495,18 @@
         "color-support": "bin.js"
       }
     },
+    "node_modules/combined-stream": {
+      "version": "1.0.8",
+      "resolved": "https://registry.npmjs.org/combined-stream/-/combined-stream-1.0.8.tgz",
+      "integrity": "sha512-FQN4MRfuJeHf7cBbBMJFXhKSDq+2kAArBlmRBvcvFE5BB1HZKXtSFASDhdlz9zOYwxh8lDdnvmMOe/+5cdoEdg==",
+      "license": "MIT",
+      "dependencies": {
+        "delayed-stream": "~1.0.0"
+      },
+      "engines": {
+        "node": ">= 0.8"
+      }
+    },
     "node_modules/concat-map": {
       "version": "0.0.1",
       "resolved": "https://registry.npmjs.org/concat-map/-/concat-map-0.0.1.tgz",
@@ -376,6 +602,15 @@
         "ms": "2.0.0"
       }
     },
+    "node_modules/delayed-stream": {
+      "version": "1.0.0",
+      "resolved": "https://registry.npmjs.org/delayed-stream/-/delayed-stream-1.0.0.tgz",
+      "integrity": "sha512-ZySD7Nf91aLB0RxL4KGrKHBXl7Eds1DAmEdcoVawXnLD7SDhpNgtuII2aAkg7a7QS41jxPSZ17p4VdGnMHk3MQ==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=0.4.0"
+      }
+    },
     "node_modules/delegates": {
       "version": "1.0.0",
       "resolved": "https://registry.npmjs.org/delegates/-/delegates-1.0.0.tgz",
@@ -521,6 +756,21 @@
         "node": ">= 0.4"
       }
     },
+    "node_modules/es-set-tostringtag": {
+      "version": "2.1.0",
+      "resolved": "https://registry.npmjs.org/es-set-tostringtag/-/es-set-tostringtag-2.1.0.tgz",
+      "integrity": "sha512-j6vWzfrGVfyXxge+O0x5sh6cvxAog0a/4Rdd2K36zCMV5eJ+/+tOAngRO8cODMNWbVRdVlmGZQL2YS3yR8bIUA==",
+      "license": "MIT",
+      "dependencies": {
+        "es-errors": "^1.3.0",
+        "get-intrinsic": "^1.2.6",
+        "has-tostringtag": "^1.0.2",
+        "hasown": "^2.0.2"
+      },
+      "engines": {
+        "node": ">= 0.4"
+      }
+    },
     "node_modules/escape-html": {
       "version": "1.0.3",
       "resolved": "https://registry.npmjs.org/escape-html/-/escape-html-1.0.3.tgz",
@@ -600,6 +850,42 @@
         "node": ">= 0.8"
       }
     },
+    "node_modules/follow-redirects": {
+      "version": "1.16.0",
+      "resolved": "https://registry.npmjs.org/follow-redirects/-/follow-redirects-1.16.0.tgz",
+      "integrity": "sha512-y5rN/uOsadFT/JfYwhxRS5R7Qce+g3zG97+JrtFZlC9klX/W5hD7iiLzScI4nZqUS7DNUdhPgw4xI8W2LuXlUw==",
+      "funding": [
+        {
+          "type": "individual",
+          "url": "https://github.com/sponsors/RubenVerborgh"
+        }
+      ],
+      "license": "MIT",
+      "engines": {
+        "node": ">=4.0"
+      },
+      "peerDependenciesMeta": {
+        "debug": {
+          "optional": true
+        }
+      }
+    },
+    "node_modules/form-data": {
+      "version": "4.0.6",
+      "resolved": "https://registry.npmjs.org/form-data/-/form-data-4.0.6.tgz",
+      "integrity": "sha512-vKatAh4SlVfgbv+YtmhiRjhEMJsYpsG1Y2rMQtR+SVSbytsSD1YGzDIcrAJmdFec88u/+VoGmxnl+80gL1tRCQ==",
+      "license": "MIT",
+      "dependencies": {
+        "asynckit": "^0.4.0",
+        "combined-stream": "^1.0.8",
+        "es-set-tostringtag": "^2.1.0",
+        "hasown": "^2.0.4",
+        "mime-types": "^2.1.35"
+      },
+      "engines": {
+        "node": ">= 6"
+      }
+    },
     "node_modules/forwarded": {
       "version": "0.2.0",
       "resolved": "https://registry.npmjs.org/forwarded/-/forwarded-0.2.0.tgz",
@@ -748,6 +1034,21 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/has-tostringtag": {
+      "version": "1.0.2",
+      "resolved": "https://registry.npmjs.org/has-tostringtag/-/has-tostringtag-1.0.2.tgz",
+      "integrity": "sha512-NqADB8VjPFLM2V0VvHUewwwsw0ZWBaIdgo+ieHtK3hasLz4qeCRjYcqfB6AQrBggRKppKF8L52/VqdVsO47Dlw==",
+      "license": "MIT",
+      "dependencies": {
+        "has-symbols": "^1.0.3"
+      },
+      "engines": {
+        "node": ">= 0.4"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/ljharb"
+      }
+    },
     "node_modules/has-unicode": {
       "version": "2.0.1",
       "resolved": "https://registry.npmjs.org/has-unicode/-/has-unicode-2.0.1.tgz",
@@ -1280,6 +1581,38 @@
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       "license": "MIT"
     },
+    "node_modules/pdf-parse": {
+      "version": "2.4.5",
+      "resolved": "https://registry.npmjs.org/pdf-parse/-/pdf-parse-2.4.5.tgz",
+      "integrity": "sha512-mHU89HGh7v+4u2ubfnevJ03lmPgQ5WU4CxAVmTSh/sxVTEDYd1er/dKS/A6vg77NX47KTEoihq8jZBLr8Cxuwg==",
+      "license": "Apache-2.0",
+      "dependencies": {
+        "@napi-rs/canvas": "0.1.80",
+        "pdfjs-dist": "5.4.296"
+      },
+      "bin": {
+        "pdf-parse": "bin/cli.mjs"
+      },
+      "engines": {
+        "node": ">=20.16.0 <21 || >=22.3.0"
+      },
+      "funding": {
+        "type": "github",
+        "url": "https://github.com/sponsors/mehmet-kozan"
+      }
+    },
+    "node_modules/pdfjs-dist": {
+      "version": "5.4.296",
+      "resolved": "https://registry.npmjs.org/pdfjs-dist/-/pdfjs-dist-5.4.296.tgz",
+      "integrity": "sha512-DlOzet0HO7OEnmUmB6wWGJrrdvbyJKftI1bhMitK7O2N8W2gc757yyYBbINy9IDafXAV9wmKr9t7xsTaNKRG5Q==",
+      "license": "Apache-2.0",
+      "engines": {
+        "node": ">=20.16.0 || >=22.3.0"
+      },
+      "optionalDependencies": {
+        "@napi-rs/canvas": "^0.1.80"
+      }
+    },
     "node_modules/pg": {
       "version": "8.23.0",
       "resolved": "https://registry.npmjs.org/pg/-/pg-8.23.0.tgz",
@@ -1427,6 +1760,15 @@
         "node": ">= 0.10"
       }
     },
+    "node_modules/proxy-from-env": {
+      "version": "2.1.0",
+      "resolved": "https://registry.npmjs.org/proxy-from-env/-/proxy-from-env-2.1.0.tgz",
+      "integrity": "sha512-cJ+oHTW1VAEa8cJslgmUZrc+sjRKgAKl3Zyse6+PV38hZe/V6Z14TbCuXcan9F9ghlz4QrFr2c92TNF82UkYHA==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=10"
+      }
+    },
     "node_modules/qs": {
       "version": "6.15.3",
       "resolved": "https://registry.npmjs.org/qs/-/qs-6.15.3.tgz",

backend/package.json

@@ -7,6 +7,8 @@
     "start": "node server.js"
   },
   "dependencies": {
+    "@google/generative-ai": "^0.24.1",
+    "axios": "^1.20.0",
     "bcrypt": "^5.1.1",
     "cors": "^2.8.5",
     "dotenv": "^17.4.2",
@@ -14,6 +16,7 @@
     "jsonwebtoken": "^9.0.2",
     "multer": "^1.4.5-lts.1",
     "nodemailer": "^9.0.5",
+    "pdf-parse": "^2.4.5",
     "pg": "^8.23.0",
     "uuid": "^9.0.1"
   }

backend/server.js

@@ -7,6 +7,9 @@ const { v4: uuidv4 } = require('uuid');
 const multer = require('multer');
 const path = require('path');
 const fs = require('fs');
+const pdfParse = require('pdf-parse');
+const { GoogleGenerativeAI } = require('@google/generative-ai');
+const axios = require('axios');
 
 const { db, run, get, all } = require('./database');
 const { sendMail } = require('./mail');
@@ -305,6 +308,176 @@ app.post('/api/upload/complete', authenticate, (req, res) => {
   }
 });
 
+// ==========================================
+// SPARK PLUG WORKFLOW APIS
+// ==========================================
+
+const getKeysFromProfile = async (userId) => {
+  const profile = await get('SELECT api_keys FROM profiles WHERE id = ?', [userId]);
+  if (profile && profile.api_keys) {
+    try {
+      return JSON.parse(profile.api_keys);
+    } catch(e) {}
+  }
+  return {};
+};
+
+// 1. Extract PDF (Gemini)
+app.post('/api/sparkplug/extract', authenticate, upload.single('file'), async (req, res) => {
+  if (!req.file) return res.status(400).json({ error: 'No file uploaded' });
+  
+  try {
+    const keys = await getKeysFromProfile(req.user.id);
+    const geminiKey = keys.GEMINI_API_KEY;
+    if (!geminiKey) return res.status(400).json({ error: 'Gemini API key missing' });
+
+    // Parse PDF
+    const dataBuffer = fs.readFileSync(req.file.path);
+    const pdfData = await pdfParse(dataBuffer);
+    const textContent = pdfData.text;
+
+    // Call Gemini to extract prompt
+    const genAI = new GoogleGenerativeAI(geminiKey);
+    const model = genAI.getGenerativeModel({ model: "gemini-1.5-flash" });
+
+    const prompt = `
+      You are an expert product designer. Read the following text from a product spec PDF and create a highly detailed, concise visual design prompt for an image generation AI.
+      Focus on the object's shape, color, materials, packaging details, and label content. Do not include background details.
+      
+      TEXT:
+      ${textContent.substring(0, 30000)} // Limit to avoid context length issues if massive
+    `;
+
+    const result = await model.generateContent(prompt);
+    const response = await result.response;
+    const extractedPrompt = response.text();
+
+    res.json({ prompt: extractedPrompt });
+  } catch (err) {
+    res.status(500).json({ error: err.message });
+  } finally {
+    if (req.file) {
+      fs.unlinkSync(req.file.path); // cleanup uploaded PDF
+    }
+  }
+});
+
+// 2. Generate Images (Nano Banana / Gemini Imagen)
+app.post('/api/sparkplug/generate-images', authenticate, async (req, res) => {
+  const { prompt } = req.body;
+  if (!prompt) return res.status(400).json({ error: 'No prompt provided' });
+
+  try {
+    const keys = await getKeysFromProfile(req.user.id);
+    const apiKey = keys.NANO_BANANA_API_KEY || keys.GEMINI_API_KEY;
+    if (!apiKey) return res.status(400).json({ error: 'Nano Banana (Gemini) API key missing' });
+
+    // We will use axios to call the Gemini Imagen REST API
+    const baseUrl = 'https://generativelanguage.googleapis.com/v1beta/models/imagen-3.0-generate-001:predict';
+    
+    const views = ['Front view', 'Back view', 'Left side view', 'Right side view'];
+    const imageUrls = [];
+
+    // Run parallel generation for all 4 views
+    const promises = views.map(async (view, index) => {
+      const fullPrompt = `${prompt}. ${view}, isolated on a pure white background, studio lighting.`;
+      
+      const payload = {
+        instances: [
+          {
+            prompt: fullPrompt
+          }
+        ],
+        parameters: {
+          sampleCount: 1,
+          outputOptions: { mimeType: 'image/png' }
+        }
+      };
+
+      const response = await axios.post(`${baseUrl}?key=${apiKey}`, payload, {
+        headers: { 'Content-Type': 'application/json' }
+      });
+
+      const base64Image = response.data.predictions[0].bytesBase64Encoded;
+      const buffer = Buffer.from(base64Image, 'base64');
+      
+      const filename = `sparkplug-${req.user.id}-${Date.now()}-${index}.png`;
+      const filepath = path.join(uploadsDir, filename);
+      fs.writeFileSync(filepath, buffer);
+      
+      return `/uploads/${filename}`;
+    });
+
+    const generatedUrls = await Promise.all(promises);
+    res.json({ images: generatedUrls });
+  } catch (err) {
+    // Gemini HTTP errors usually have response.data.error
+    const errorMsg = err.response?.data?.error?.message || err.message;
+    res.status(500).json({ error: errorMsg });
+  }
+});
+
+// 3. Generate 3D (Meshy)
+app.post('/api/sparkplug/generate-3d', authenticate, async (req, res) => {
+  const { imageUrls } = req.body;
+  if (!imageUrls || imageUrls.length === 0) return res.status(400).json({ error: 'No images provided' });
+
+  try {
+    const keys = await getKeysFromProfile(req.user.id);
+    const meshyKey = keys.MESHY_API_KEY;
+    if (!meshyKey) return res.status(400).json({ error: 'Meshy API key missing' });
+
+    // Assuming imageUrls are local paths like /uploads/...
+    // Meshy requires base64 Data URIs if the images are not publicly accessible URLs.
+    // Our local URLs are not publicly accessible to Meshy's servers! We MUST convert to base64.
+    
+    const base64Images = imageUrls.map(url => {
+      // Extract filename from URL
+      const filename = url.replace('/uploads/', '');
+      const filepath = path.join(uploadsDir, filename);
+      const buffer = fs.readFileSync(filepath);
+      return `data:image/png;base64,${buffer.toString('base64')}`;
+    });
+
+    const response = await axios.post('https://api.meshy.ai/openapi/v1/multi-image-to-3d', {
+      image_urls: base64Images,
+      enable_pbr: true
+    }, {
+      headers: {
+        'Authorization': `Bearer ${meshyKey}`,
+        'Content-Type': 'application/json'
+      }
+    });
+
+    res.json({ taskId: response.data.result });
+  } catch (err) {
+    const errorMsg = err.response?.data?.message || err.message;
+    res.status(500).json({ error: errorMsg });
+  }
+});
+
+// 4. Check 3D Status (Meshy)
+app.get('/api/sparkplug/status-3d/:taskId', authenticate, async (req, res) => {
+  const { taskId } = req.params;
+  
+  try {
+    const keys = await getKeysFromProfile(req.user.id);
+    const meshyKey = keys.MESHY_API_KEY;
+    if (!meshyKey) return res.status(400).json({ error: 'Meshy API key missing' });
+
+    const response = await axios.get(`https://api.meshy.ai/openapi/v1/multi-image-to-3d/${taskId}`, {
+      headers: {
+        'Authorization': `Bearer ${meshyKey}`
+      }
+    });
+
+    res.json(response.data);
+  } catch (err) {
+    const errorMsg = err.response?.data?.message || err.message;
+    res.status(500).json({ error: errorMsg });
+  }
+});
+
 const PORT = process.env.PORT || 3005;
 app.listen(PORT, () => {
   console.log(`Backend server running on port ${PORT}`);

src/lib/api.ts

@@ -192,5 +192,57 @@ export const api = {
       if (!res.ok) throw new Error(data.error);
       return data.url;
     }
+  },
+
+  // ==========================================
+  // SPARK PLUG APIS
+  // ==========================================
+  
+  extractPDF: async (file: File) => {
+    const formData = new FormData();
+    formData.append('file', file);
+    
+    const res = await fetch(`${API_URL}/sparkplug/extract`, {
+      method: 'POST',
+      headers: {
+        'Authorization': `Bearer ${localStorage.getItem('auth_token')}`
+      },
+      body: formData
+    });
+    const data = await res.json();
+    if (!res.ok) throw new Error(data.error);
+    return data.prompt;
+  },
+
+  generateImages: async (prompt: string) => {
+    const res = await fetch(`${API_URL}/sparkplug/generate-images`, {
+      method: 'POST',
+      headers: getHeaders(),
+      body: JSON.stringify({ prompt })
+    });
+    const data = await res.json();
+    if (!res.ok) throw new Error(data.error);
+    return data.images; // Array of 4 image URLs
+  },
+
+  generate3D: async (imageUrls: string[]) => {
+    const res = await fetch(`${API_URL}/sparkplug/generate-3d`, {
+      method: 'POST',
+      headers: getHeaders(),
+      body: JSON.stringify({ imageUrls })
+    });
+    const data = await res.json();
+    if (!res.ok) throw new Error(data.error);
+    return data.taskId;
+  },
+
+  get3DStatus: async (taskId: string) => {
+    const res = await fetch(`${API_URL}/sparkplug/status-3d/${taskId}`, {
+      method: 'GET',
+      headers: getHeaders()
+    });
+    const data = await res.json();
+    if (!res.ok) throw new Error(data.error);
+    return data; // { status: "SUCCEEDED"|"PENDING", model_urls: { glb: "..." }, ... }
   }
 };

src/pages/SparkPlug.tsx

@@ -27,6 +27,7 @@ export default function SparkPlug() {
 
   // Step 4: 3D Model
   const [modelProgress, setModelProgress] = useState(0);
+  const [generatedGlbUrl, setGeneratedGlbUrl] = useState<string | null>(null);
 
   const handleFileUpload = async (e: React.ChangeEvent<HTMLInputElement>) => {
     if (e.target.files && e.target.files[0]) {
@@ -49,17 +50,14 @@ export default function SparkPlug() {
         setIsLoading(false);
         return;
       }
-      
+      // Call our backend endpoint to parse PDF and query Gemini
-      // We would normally send the PDF to the backend or use Gemini SDK directly here.
+      const prompt = await api.extractPDF(pdfFile);
-      // Mocking the extraction for now based on the Indica Shampoo PDF context:
+      setExtractedPrompt(prompt);
-      await new Promise(r => setTimeout(r, 2000));
-      
-      setExtractedPrompt("Product: Indica Easy Herbal Shield Colour Shampoo\nType: Sachet/Packet\nColor Palette: Green, White\nKey Elements: Woman with black hair, Amla & Aloe illustration, 10 Minutes Herbal Care text.\n\nDescription: A glossy green rectangular sachet with vivid branding and product imagery for an herbal hair colour shampoo.");
       
       setCurrentStep(2);
-    } catch (err) {
+    } catch (err: any) {
       console.error(err);
-      alert("Failed to process PDF.");
+      alert(`Failed to process PDF: ${err.message || 'Unknown error'}`);
     } finally {
       setIsLoading(false);
     }
@@ -80,22 +78,18 @@ export default function SparkPlug() {
         setIsLoading(false);
         return;
       }
-
+      // Call our backend endpoint which queries Gemini Imagen
-      // Mocking the image generation with Nano Banana
+      const images = await api.generateImages(extractedPrompt);
-      await new Promise(r => setTimeout(r, 3000));
       
-      // Placeholder images for the 4 views (front, back, left, right)
+      if (images && images.length === 4) {
-      setGeneratedImages([
+        setGeneratedImages(images);
-        "https://images.unsplash.com/photo-1629198688000-71f23e745b6e?w=400&q=80", // front
+        setCurrentStep(3);
-        "https://images.unsplash.com/photo-1629198725848-18e55e975cc3?w=400&q=80", // back
+      } else {
-        "https://images.unsplash.com/photo-1629198725838-511bb7405234?w=400&q=80", // left
+        throw new Error("Failed to generate exactly 4 images.");
-        "https://images.unsplash.com/photo-1629198688000-71f23e745b6e?w=400&q=80", // right
+      }
-      ]);
+    } catch (err: any) {
-      
-      setCurrentStep(3);
-    } catch (err) {
       console.error(err);
-      alert("Failed to generate image.");
+      alert(`Failed to generate images: ${err.message || 'Unknown error'}`);
     } finally {
       setIsLoading(false);
     }
@@ -116,17 +110,39 @@ export default function SparkPlug() {
         setIsLoading(false);
         return;
       }
-
+      // Call backend to start Meshy task
-      // Simulate Meshy generation
+      const taskId = await api.generate3D(generatedImages);
-      for (let i = 1; i <= 10; i++) {
+      
-        await new Promise(r => setTimeout(r, 500));
+      // Poll Meshy status
-        setModelProgress(i * 10);
+      let isDone = false;
+      let attempts = 0;
+      while (!isDone && attempts < 60) { // Max 5 mins (60 * 5s)
+        attempts++;
+        await new Promise(resolve => setTimeout(resolve, 5000));
+        
+        const statusData = await api.get3DStatus(taskId);
+        const { status, progress, model_urls, task_error } = statusData;
+        
+        if (progress) {
+          setModelProgress(progress);
+        }
+        
+        if (status === 'SUCCEEDED') {
+          setGeneratedGlbUrl(model_urls.glb);
+          isDone = true;
+          setCurrentStep(4);
+        } else if (status === 'FAILED') {
+          throw new Error(`Meshy generation failed: ${task_error?.message || 'Unknown error'}`);
+        }
       }
       
-      setCurrentStep(4);
+      if (!isDone) {
-    } catch (err) {
+        throw new Error("Meshy task timed out after 5 minutes.");
+      }
+      
+    } catch (err: any) {
       console.error(err);
-      alert("Failed to generate 3D model.");
+      alert(`Failed to generate 3D model: ${err.message || 'Unknown error'}`);
     } finally {
       setIsLoading(false);
     }
@@ -136,8 +152,9 @@ export default function SparkPlug() {
     setLoadingMessage('Saving project to your workspace...');
     setIsLoading(true);
     try {
-      // Mock generated GLB URL from Meshy
+      if (!generatedGlbUrl) {
-      const mockGlbUrl = "https://raw.githubusercontent.com/KhronosGroup/glTF-Sample-Models/master/2.0/BoxTextured/glTF-Binary/BoxTextured.glb";
+        throw new Error("No GLB URL available to save.");
+      }
       
       // Create project and save with model injected into scene_data
       const res = await api.saveProject({
@@ -152,7 +169,7 @@ export default function SparkPlug() {
               position: [0, 0, 0],
               rotation: [0, 0, 0],
               scale: [1, 1, 1],
-              url: mockGlbUrl
+              url: generatedGlbUrl
             }
           ]
         }