Gradio_NER_App.ipynb

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  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "!pip install -q transformers"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "t3abZy8yE2Wn",
        "outputId": "7739a57d-af42-467d-b605-87b92fb3d2b2"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.9/7.9 MB\u001b[0m \u001b[31m41.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m302.0/302.0 kB\u001b[0m \u001b[31m26.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m295.0/295.0 kB\u001b[0m \u001b[31m22.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from transformers import pipeline"
      ],
      "metadata": {
        "id": "IM_T9i4wFFNL"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ner_pipeline = pipeline(\"ner\", model=\"RidaDogrul/multilingual-xlm-roberta-for-ner\")"
      ],
      "metadata": {
        "id": "ad5e-2FFFT00"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "text = \"I am Tim and I work at Google\""
      ],
      "metadata": {
        "id": "JW171HMbFsDE"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ner_pipeline(text)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lngXoZojF94V",
        "outputId": "8cad8895-e312-4c43-fbbc-a5739eb7e8a7"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'entity': 'B-PER',\n",
              "  'score': 0.82661855,\n",
              "  'index': 3,\n",
              "  'word': '▁Tim',\n",
              "  'start': 5,\n",
              "  'end': 8},\n",
              " {'entity': 'B-ORG',\n",
              "  'score': 0.947759,\n",
              "  'index': 8,\n",
              "  'word': '▁Google',\n",
              "  'start': 23,\n",
              "  'end': 29}]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "text_tr = \"Benim adım Ali ve Trendyol'da çalışıyorum\"\n",
        "ner_pipeline(text_tr)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8xhi_LK6GI-t",
        "outputId": "5435723e-2a29-42d8-daea-5fee50ee6623"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'entity': 'B-PER',\n",
              "  'score': 0.8826971,\n",
              "  'index': 3,\n",
              "  'word': '▁Ali',\n",
              "  'start': 11,\n",
              "  'end': 14},\n",
              " {'entity': 'B-ORG',\n",
              "  'score': 0.694531,\n",
              "  'index': 5,\n",
              "  'word': '▁Trend',\n",
              "  'start': 18,\n",
              "  'end': 23},\n",
              " {'entity': 'I-ORG',\n",
              "  'score': 0.7195995,\n",
              "  'index': 6,\n",
              "  'word': 'yol',\n",
              "  'start': 23,\n",
              "  'end': 26}]"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ner_pipeline(text_tr, aggregation_strategy = \"simple\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tBw4OEgYGnam",
        "outputId": "8dc4088b-c201-4fb4-e81e-73c3019bffe6"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'entity_group': 'PER',\n",
              "  'score': 0.8826971,\n",
              "  'word': 'Ali',\n",
              "  'start': 11,\n",
              "  'end': 14},\n",
              " {'entity_group': 'ORG',\n",
              "  'score': 0.7070652,\n",
              "  'word': 'Trendyol',\n",
              "  'start': 18,\n",
              "  'end': 26}]"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def ner(text):\n",
        "  output = ner_pipeline(text, aggregation_strategy=\"simple\")\n",
        "  return {\"text\": text, \"entities\": output}"
      ],
      "metadata": {
        "id": "kXppfMH5HEiO"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install -q gradio"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ieT_r9V2Ipul",
        "outputId": "c2f19a61-3aaf-4364-d761-d999dcea4602"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m15.4/15.4 MB\u001b[0m \u001b[31m71.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m92.9/92.9 kB\u001b[0m \u001b[31m10.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m302.7/302.7 kB\u001b[0m \u001b[31m28.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m129.9/129.9 kB\u001b[0m \u001b[31m13.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[?25h  Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "lida 0.0.10 requires kaleido, which is not installed.\n",
            "llmx 0.0.15a0 requires cohere, which is not installed.\n",
            "llmx 0.0.15a0 requires openai, which is not installed.\n",
            "llmx 0.0.15a0 requires tiktoken, which is not installed.\n",
            "tensorflow-probability 0.22.0 requires typing-extensions<4.6.0, but you have typing-extensions 4.8.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0m"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import gradio as gr"
      ],
      "metadata": {
        "id": "Ph2yOinCLBLc"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "examples = [\n",
        "    \"My name is Tim and I live in California\",\n",
        "    \"Ich arbeite bei Google in Berlin\",\n",
        "    \"Ali, Ankara'lı mı?\"\n",
        "]\n",
        "\n",
        "demo = gr.Interface(\n",
        "    ner,\n",
        "    gr.Textbox(placeholder=\"Enter sentence here...\"),\n",
        "    gr.HighlightedText(),\n",
        "    examples=examples\n",
        ")"
      ],
      "metadata": {
        "id": "HNvdK1c6L1LG"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "demo.launch(share=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 646
        },
        "id": "LYgxMSpiNfvP",
        "outputId": "2d76ca21-777c-4c2d-89be-e25ecfb57d78"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Rerunning server... use `close()` to stop if you need to change `launch()` parameters.\n",
            "----\n",
            "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
            "Running on public URL: https://6cd6d982fd3489a291.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
          ]
        },
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          "output_type": "display_data",
          "data": {
            "text/plain": [
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          "output_type": "execute_result",
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          "metadata": {},
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    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "qXIboWP5NpC-"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}