{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d55eb3ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import base64\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "77b23cd8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# API endpoint\n",
    "BASE_URL = \"http://127.0.0.1:7960\"\n",
    "\n",
    "def generate_no_preview(image_base64: str):\n",
    "    \"\"\"Generate 3D model from a single base64-encoded image without previews.\n",
    "    \n",
    "    Args:\n",
    "        image_base64: Base64 string of the image (without 'data:image/...' prefix)\n",
    "    \"\"\"\n",
    "    try:\n",
    "        # Set generation parameters\n",
    "        params = {\n",
    "            'image_base64': image_base64,\n",
    "            'seed': 42,\n",
    "            'ss_guidance_strength': 7.5,\n",
    "            'ss_sampling_steps': 30,\n",
    "            'slat_guidance_strength': 7.5,\n",
    "            'slat_sampling_steps': 30,\n",
    "            'mesh_simplify_ratio': 0.95,\n",
    "            'texture_size': 1024,\n",
    "            'output_format': 'glb'\n",
    "        }\n",
    "        \n",
    "        # Start generation\n",
    "        print(\"Starting generation...\")\n",
    "        response = requests.post(f\"{BASE_URL}/generate_no_preview\", data=params)\n",
    "        print(\"Response status:\", response.status_code)\n",
    "        response.raise_for_status()\n",
    "        \n",
    "        # Poll status until complete\n",
    "        while True:\n",
    "            status = requests.get(f\"{BASE_URL}/status\").json()\n",
    "            print(f\"Progress: {status['progress']}%\")\n",
    "            \n",
    "            if status['status'] == 'COMPLETE':\n",
    "                break\n",
    "            elif status['status'] == 'FAILED':\n",
    "                raise Exception(f\"Generation failed: {status['message']}\")\n",
    "            \n",
    "            time.sleep(1)\n",
    "        \n",
    "        # Download the model\n",
    "        print(\"Downloading model...\")\n",
    "        response = requests.get(f\"{BASE_URL}/download/model\")\n",
    "        response.raise_for_status()\n",
    "        print(\"Model downloaded.\")\n",
    "        \n",
    "        return response.content\n",
    "        \n",
    "    except Exception as e:\n",
    "        print(f\"Error: {str(e)}\")\n",
    "        return None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "eb122295",
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_model(image_path, output_path):\n",
    "    with open(image_path, 'rb') as image_file:\n",
    "        image_data = image_file.read()\n",
    "\n",
    "    base64_encoded = base64.b64encode(image_data).decode('utf-8')\n",
    "    model = generate_no_preview(base64_encoded)\n",
    "    \n",
    "    with open(output_path, 'wb') as f:\n",
    "        f.write(model)\n",
    "    print(f\"Model saved to {output_path}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2ce7dfdf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting generation...\n",
      "Response status: 200\n",
      "Progress: 100%\n",
      "Downloading model...\n",
      "Model downloaded.\n",
      "Model saved to test_resources/style_test_3_model.glb\n"
     ]
    }
   ],
   "source": [
    "\n",
    "image_path = 'test_resources/style_test_3.jpg'\n",
    "output_path = \"test_resources/style_test_3_model.glb\"\n",
    "\n",
    "generate_model(image_path, output_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a1224d13",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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