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     "text": [
      "/home/rnwnsgud1234/0.Files/anaconda3/envs/nlp/lib/python3.9/site-packages/gradio/inputs.py:26: UserWarning: Usage of gradio.inputs is deprecated, and will not be supported in the future, please import your component from gradio.components\n",
      "  warnings.warn(\n",
      "/home/rnwnsgud1234/0.Files/anaconda3/envs/nlp/lib/python3.9/site-packages/gradio/deprecation.py:40: UserWarning: `optional` parameter is deprecated, and it has no effect\n",
      "  warnings.warn(value)\n",
      "/home/rnwnsgud1234/0.Files/anaconda3/envs/nlp/lib/python3.9/site-packages/gradio/deprecation.py:40: UserWarning: `numeric` parameter is deprecated, and it has no effect\n",
      "  warnings.warn(value)\n",
      "/home/rnwnsgud1234/0.Files/anaconda3/envs/nlp/lib/python3.9/site-packages/gradio/inputs.py:58: UserWarning: Usage of gradio.inputs is deprecated, and will not be supported in the future, please import your component from gradio.components\n",
      "  warnings.warn(\n",
      "/home/rnwnsgud1234/0.Files/anaconda3/envs/nlp/lib/python3.9/site-packages/gradio/interface.py:359: UserWarning: The `allow_flagging` parameter in `Interface` nowtakes a string value ('auto', 'manual', or 'never'), not a boolean. Setting parameter to: 'never'.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
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     "text": [
      "Running on local URL:  http://127.0.0.1:7862\n",
      "Running on public URL: https://bd6b9acba15cf888.gradio.app\n",
      "\n",
      "This share link expires in 72 hours. For free permanent hosting and GPU upgrades (NEW!), check out Spaces: https://huggingface.co/spaces\n"
     ]
    },
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       "<div><iframe src=\"https://bd6b9acba15cf888.gradio.app\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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     "text": [
      "100%|██████████| 1/1 [00:01<00:00,  1.37s/it]\n",
      "100%|██████████| 1/1 [00:00<00:00, 67.94it/s]\n"
     ]
    }
   ],
   "source": [
    "import gradio as gr\n",
    "from extraction import paragraph_extract\n",
    "\n",
    "def predict(paragraphs, positions):\n",
    "    paragraphs = [paragraphs]\n",
    "    positions = [positions]\n",
    "    return extractor(paragraphs, positions)[0]\n",
    "\n",
    "extractor = paragraph_extract().extract\n",
    "\n",
    "example_paragraph = 'The W/Zr/HfO2 /TiN structure was fabricated following the scheme shown in the inset of Fig. 1(a). A 5-nm-thick HfO2 layer was deposited on a TiN substrate by an atomic layer deposition system. After HfO2 film deposition, thermal annealing was performed under NH3 at 700∘C in order to achieve optimum concentration of oxygen vacancies [10]. Then, the 3-nm-thick Zr top electrode and a 50-nm-thick W capping layer were deposited by RF magnetron sputtering system. The size of the upper electrode was 10×10 μm2 . The electrical measurements were performed by an Agilent B1500A semiconductor device analyzer, equipped with two pulse generator modules WGFMU (Waveform Generator and Fast Measurement Unit). The coaxial cables with a 50-Ω resistance and less than 10 cm in length were used to reduce the parasitic effects.'\n",
    "example_position = 4\n",
    "\n",
    "demo = gr.Interface(fn=predict, inputs=[gr.inputs.Textbox(lines=3, label=\"Paragraphs\", placeholder='Text Here...'), \n",
    "                                        gr.inputs.Number(label=\"Positions\")], \n",
    "                    outputs=\"text\", \n",
    "                    title=\"ReRAM Paragraph Classification\", allow_flagging=False,\n",
    "                    examples=[[example_paragraph, example_position]],\n",
    "                    )\n",
    "\n",
    "demo.launch(share=True)"
   ]
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