genai_pic.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "aabe5c20",
   "metadata": {},
   "outputs": [
    {
     "ename": "RetryError",
     "evalue": "Deadline of 60.0s exceeded while calling target function, last exception: 503 failed to connect to all addresses; last error: UNAVAILABLE: ipv4:172.217.160.106:443: Failed to connect to remote host: FD shutdown",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31m_InactiveRpcError\u001b[0m                         Traceback (most recent call last)",
      "File \u001b[0;32m~/Virtualenvs/heracles/lib/python3.10/site-packages/google/api_core/grpc_helpers.py:79\u001b[0m, in \u001b[0;36m_wrap_unary_errors.<locals>.error_remapped_callable\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     78\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 79\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mcallable_\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     80\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m grpc\u001b[38;5;241m.\u001b[39mRpcError \u001b[38;5;28;01mas\u001b[39;00m exc:\n",
      "File \u001b[0;32m~/Virtualenvs/heracles/lib/python3.10/site-packages/grpc/_channel.py:1160\u001b[0m, in \u001b[0;36m_UnaryUnaryMultiCallable.__call__\u001b[0;34m(self, request, timeout, metadata, credentials, wait_for_ready, compression)\u001b[0m\n\u001b[1;32m   1154\u001b[0m (\n\u001b[1;32m   1155\u001b[0m     state,\n\u001b[1;32m   1156\u001b[0m     call,\n\u001b[1;32m   1157\u001b[0m ) \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_blocking(\n\u001b[1;32m   1158\u001b[0m     request, timeout, metadata, credentials, wait_for_ready, compression\n\u001b[1;32m   1159\u001b[0m )\n\u001b[0;32m-> 1160\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_end_unary_response_blocking\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstate\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcall\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/Virtualenvs/heracles/lib/python3.10/site-packages/grpc/_channel.py:1003\u001b[0m, in \u001b[0;36m_end_unary_response_blocking\u001b[0;34m(state, call, with_call, deadline)\u001b[0m\n\u001b[1;32m   1002\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1003\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m _InactiveRpcError(state)\n",
      "\u001b[0;31m_InactiveRpcError\u001b[0m: <_InactiveRpcError of RPC that terminated with:\n\tstatus = StatusCode.UNAVAILABLE\n\tdetails = \"failed to connect to all addresses; last error: UNAVAILABLE: ipv4:172.217.160.106:443: Failed to connect to remote host: FD shutdown\"\n\tdebug_error_string = \"UNKNOWN:Error received from peer  {grpc_message:\"failed to connect to all addresses; last error: UNAVAILABLE: ipv4:172.217.160.106:443: Failed to connect to remote host: FD shutdown\", grpc_status:14, created_time:\"2024-03-15T08:05:14.179397+08:00\"}\"\n>",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mServiceUnavailable\u001b[0m                        Traceback (most recent call last)",
      "File \u001b[0;32m~/Virtualenvs/heracles/lib/python3.10/site-packages/google/api_core/retry.py:207\u001b[0m, in \u001b[0;36mretry_target\u001b[0;34m(target, predicate, sleep_generator, timeout, on_error, **kwargs)\u001b[0m\n\u001b[1;32m    206\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 207\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[43mtarget\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    208\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m inspect\u001b[38;5;241m.\u001b[39misawaitable(result):\n",
      "File \u001b[0;32m~/Virtualenvs/heracles/lib/python3.10/site-packages/google/api_core/timeout.py:120\u001b[0m, in \u001b[0;36mTimeToDeadlineTimeout.__call__.<locals>.func_with_timeout\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    118\u001b[0m     kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtimeout\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mmax\u001b[39m(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_timeout \u001b[38;5;241m-\u001b[39m time_since_first_attempt)\n\u001b[0;32m--> 120\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/Virtualenvs/heracles/lib/python3.10/site-packages/google/api_core/grpc_helpers.py:81\u001b[0m, in \u001b[0;36m_wrap_unary_errors.<locals>.error_remapped_callable\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     80\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m grpc\u001b[38;5;241m.\u001b[39mRpcError \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[0;32m---> 81\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m exceptions\u001b[38;5;241m.\u001b[39mfrom_grpc_error(exc) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mexc\u001b[39;00m\n",
      "\u001b[0;31mServiceUnavailable\u001b[0m: 503 failed to connect to all addresses; last error: UNAVAILABLE: ipv4:172.217.160.106:443: Failed to connect to remote host: FD shutdown",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mRetryError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[0;32mIn [1], line 18\u001b[0m\n\u001b[1;32m     15\u001b[0m ax\u001b[38;5;241m.\u001b[39mimshow(img)\n\u001b[1;32m     17\u001b[0m model \u001b[38;5;241m=\u001b[39m genai\u001b[38;5;241m.\u001b[39mGenerativeModel(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mgemini-pro-vision\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m---> 18\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgenerate_content\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimg\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     20\u001b[0m \u001b[38;5;28mprint\u001b[39m(response\u001b[38;5;241m.\u001b[39mtext)\n",
      "File \u001b[0;32m~/Virtualenvs/heracles/lib/python3.10/site-packages/google/generativeai/generative_models.py:243\u001b[0m, in \u001b[0;36mGenerativeModel.generate_content\u001b[0;34m(self, contents, generation_config, safety_settings, stream, **kwargs)\u001b[0m\n\u001b[1;32m    241\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m generation_types\u001b[38;5;241m.\u001b[39mGenerateContentResponse\u001b[38;5;241m.\u001b[39mfrom_iterator(iterator)\n\u001b[1;32m    242\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 243\u001b[0m     response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_client\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgenerate_content\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    244\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m generation_types\u001b[38;5;241m.\u001b[39mGenerateContentResponse\u001b[38;5;241m.\u001b[39mfrom_response(response)\n",
      "File \u001b[0;32m~/Virtualenvs/heracles/lib/python3.10/site-packages/google/ai/generativelanguage_v1beta/services/generative_service/client.py:566\u001b[0m, in \u001b[0;36mGenerativeServiceClient.generate_content\u001b[0;34m(self, request, model, contents, retry, timeout, metadata)\u001b[0m\n\u001b[1;32m    561\u001b[0m metadata \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mtuple\u001b[39m(metadata) \u001b[38;5;241m+\u001b[39m (\n\u001b[1;32m    562\u001b[0m     gapic_v1\u001b[38;5;241m.\u001b[39mrouting_header\u001b[38;5;241m.\u001b[39mto_grpc_metadata(((\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmodel\u001b[39m\u001b[38;5;124m\"\u001b[39m, request\u001b[38;5;241m.\u001b[39mmodel),)),\n\u001b[1;32m    563\u001b[0m )\n\u001b[1;32m    565\u001b[0m \u001b[38;5;66;03m# Send the request.\u001b[39;00m\n\u001b[0;32m--> 566\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[43mrpc\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    567\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    568\u001b[0m \u001b[43m    \u001b[49m\u001b[43mretry\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mretry\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    569\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    570\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmetadata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmetadata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    571\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    573\u001b[0m \u001b[38;5;66;03m# Done; return the response.\u001b[39;00m\n\u001b[1;32m    574\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m response\n",
      "File \u001b[0;32m~/Virtualenvs/heracles/lib/python3.10/site-packages/google/api_core/gapic_v1/method.py:131\u001b[0m, in \u001b[0;36m_GapicCallable.__call__\u001b[0;34m(self, timeout, retry, compression, *args, **kwargs)\u001b[0m\n\u001b[1;32m    128\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compression \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    129\u001b[0m     kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcompression\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m compression\n\u001b[0;32m--> 131\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mwrapped_func\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/Virtualenvs/heracles/lib/python3.10/site-packages/google/api_core/retry.py:372\u001b[0m, in \u001b[0;36mRetry.__call__.<locals>.retry_wrapped_func\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    368\u001b[0m target \u001b[38;5;241m=\u001b[39m functools\u001b[38;5;241m.\u001b[39mpartial(func, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m    369\u001b[0m sleep_generator \u001b[38;5;241m=\u001b[39m exponential_sleep_generator(\n\u001b[1;32m    370\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_initial, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_maximum, multiplier\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_multiplier\n\u001b[1;32m    371\u001b[0m )\n\u001b[0;32m--> 372\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mretry_target\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    373\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtarget\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    374\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_predicate\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    375\u001b[0m \u001b[43m    \u001b[49m\u001b[43msleep_generator\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    376\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_timeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    377\u001b[0m \u001b[43m    \u001b[49m\u001b[43mon_error\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mon_error\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    378\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/Virtualenvs/heracles/lib/python3.10/site-packages/google/api_core/retry.py:226\u001b[0m, in \u001b[0;36mretry_target\u001b[0;34m(target, predicate, sleep_generator, timeout, on_error, **kwargs)\u001b[0m\n\u001b[1;32m    222\u001b[0m     next_attempt_time \u001b[38;5;241m=\u001b[39m datetime_helpers\u001b[38;5;241m.\u001b[39mutcnow() \u001b[38;5;241m+\u001b[39m datetime\u001b[38;5;241m.\u001b[39mtimedelta(\n\u001b[1;32m    223\u001b[0m         seconds\u001b[38;5;241m=\u001b[39msleep\n\u001b[1;32m    224\u001b[0m     )\n\u001b[1;32m    225\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m deadline \u001b[38;5;241m<\u001b[39m next_attempt_time:\n\u001b[0;32m--> 226\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m exceptions\u001b[38;5;241m.\u001b[39mRetryError(\n\u001b[1;32m    227\u001b[0m             \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDeadline of \u001b[39m\u001b[38;5;132;01m{:.1f}\u001b[39;00m\u001b[38;5;124ms exceeded while calling target function\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\n\u001b[1;32m    228\u001b[0m                 timeout\n\u001b[1;32m    229\u001b[0m             ),\n\u001b[1;32m    230\u001b[0m             last_exc,\n\u001b[1;32m    231\u001b[0m         ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlast_exc\u001b[39;00m\n\u001b[1;32m    233\u001b[0m _LOGGER\u001b[38;5;241m.\u001b[39mdebug(\n\u001b[1;32m    234\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRetrying due to \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m, sleeping \u001b[39m\u001b[38;5;132;01m{:.1f}\u001b[39;00m\u001b[38;5;124ms ...\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(last_exc, sleep)\n\u001b[1;32m    235\u001b[0m )\n\u001b[1;32m    236\u001b[0m time\u001b[38;5;241m.\u001b[39msleep(sleep)\n",
      "\u001b[0;31mRetryError\u001b[0m: Deadline of 60.0s exceeded while calling target function, last exception: 503 failed to connect to all addresses; last error: UNAVAILABLE: ipv4:172.217.160.106:443: Failed to connect to remote host: FD shutdown"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import google.generativeai as genai\n",
    "import os\n",
    "from dotenv import load_dotenv\n",
    "import PIL.Image\n",
    "from IPython import display\n",
    "from matplotlib_inline import backend_inline\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "load_dotenv()\n",
    "genai.configure(api_key=os.environ.get(\"GOOGLE_API_KEY\"))\n",
    "\n",
    "img = PIL.Image.open('/Users/huangchong/Downloads/JPEG image-4799-88CD-07-0.jpeg')\n",
    "\n",
    "_, ax  = plt.subplots(1,1,figsize=(10,2))\n",
    "ax.imshow(img)\n",
    "\n",
    "model = genai.GenerativeModel('gemini-pro-vision')\n",
    "response = model.generate_content(img)\n",
    "\n",
    "print(response.text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "16b64bbb",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}