docs/3_inference/ATEPC_flask_demo.ipynb

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   "cell_type": "markdown",
   "source": [
    "# Aspect Term Extraction and Sentiment Classification"
   ],
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  },
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   "cell_type": "markdown",
   "source": [
    "## Flask Server"
   ],
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   "source": [
    "!pip install pyabsa\n",
    "!pip install flask"
   ],
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   "execution_count": 1,
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     "text": [
      "C:\\Users\\chuan\\miniconda3\\lib\\site-packages\\torch\\utils\\tensorboard\\__init__.py:4: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.\n",
      "  if not hasattr(tensorboard, \"__version__\") or LooseVersion(\n"
     ]
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    {
     "name": "stdout",
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     "text": [
      "[2023-03-12 18:53:59] (2.1.6) \u001B[31mPyABSA(2.1.6): \n",
      "[New Feature] Aspect Sentiment Triplet Extraction from v2.1.0 test version (https://github.com/yangheng95/PyABSA/tree/v2/examples-v2/aspect_sentiment_triplet_extration)\n",
      "\n",
      "If you find any problems, please report them on GitHub. Thanks!\n",
      "The v2.x versions are not compatible with Google Colab. Please downgrade to 1.16.27.\n",
      "\u001B[0m\n",
      " * Serving Flask app '__main__'\n",
      " * Debug mode: on\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\chuan\\miniconda3\\lib\\multiprocessing\\pool.py:268: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=1>\n",
      "  _warn(f\"unclosed running multiprocessing pool {self!r}\",\n",
      "ResourceWarning: Enable tracemalloc to get the object allocation traceback\n",
      "C:\\Users\\chuan\\miniconda3\\lib\\site-packages\\werkzeug\\serving.py:718: ResourceWarning: unclosed <socket.socket fd=5952, family=AddressFamily.AF_INET, type=SocketKind.SOCK_STREAM, proto=0>\n",
      "  self.socket = socket.fromfd(fd, address_family, socket.SOCK_STREAM)\n",
      "ResourceWarning: Enable tracemalloc to get the object allocation traceback\n",
      "WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.\n",
      " * Running on http://127.0.0.1:5000\n",
      "Press CTRL+C to quit\n",
      " * Restarting with stat\n"
     ]
    },
    {
     "ename": "SystemExit",
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      "An exception has occurred, use %tb to see the full traceback.\n",
      "\u001B[1;31mSystemExit\u001B[0m\u001B[1;31m:\u001B[0m 1\n"
     ]
    },
    {
     "name": "stderr",
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     "text": [
      "C:\\Users\\chuan\\miniconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py:3468: UserWarning: To exit: use 'exit', 'quit', or Ctrl-D.\n",
      "  warn(\"To exit: use 'exit', 'quit', or Ctrl-D.\", stacklevel=1)\n"
     ]
    }
   ],
   "source": [
    "from flask import Flask, request, jsonify\n",
    "from pyabsa import AspectTermExtraction as ATEPC\n",
    "\n",
    "app = Flask(__name__)\n",
    "\n",
    "\n",
    "@app.route(\"/predict\", methods=[\"POST\"])\n",
    "def predict():\n",
    "    # Load the model\n",
    "    triplet_extractor = ATEPC.AspectExtractor(\"multilingual\")\n",
    "\n",
    "    # Get the text from the request\n",
    "    data = request.get_json(force=True)\n",
    "    text = data[\"text\"]\n",
    "\n",
    "    # Predict\n",
    "    result = triplet_extractor.predict(text)\n",
    "\n",
    "    return jsonify(result)\n",
    "\n",
    "\n",
    "app.run(port=5000, debug=True)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "## API Request"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"Triplets\": [\n",
      "    {\n",
      "      \"Aspect\": \"food\",\n",
      "      \"Opinion\": \"good,\",\n",
      "      \"Polarity\": \"Positive\"\n",
      "    },\n",
      "    {\n",
      "      \"Aspect\": \"food\",\n",
      "      \"Opinion\": \"bad.\",\n",
      "      \"Polarity\": \"Negative\"\n",
      "    },\n",
      "    {\n",
      "      \"Aspect\": \"service\",\n",
      "      \"Opinion\": \"good,\",\n",
      "      \"Polarity\": \"Positive\"\n",
      "    },\n",
      "    {\n",
      "      \"Aspect\": \"service\",\n",
      "      \"Opinion\": \"bad.\",\n",
      "      \"Polarity\": \"Negative\"\n",
      "    }\n",
      "  ],\n",
      "  \"True Triplets\": [],\n",
      "  \"sentence\": \"The food is good, but the service is bad.\",\n",
      "  \"sentence_id\": 0\n",
      "}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import requests\n",
    "import json\n",
    "\n",
    "url = \"http://localhost:5000/predict\"\n",
    "data = {\"text\": \"The food is good, but the service is bad.\"}\n",
    "headers = {\"Content-type\": \"application/json\", \"Accept\": \"text/plain\"}\n",
    "r = requests.post(url, data=json.dumps(data), headers=headers)\n",
    "print(r.text)"
   ],
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