demos/Text2Text_Demos.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zL8uiXTHIrHI"
      },
      "source": [
        "# [Text2Text](https://github.com/artitw/text2text): Crosslingual NLP/G toolkit\n",
        "\n",
        "## How Crosslingual Models Work (click to watch)\n",
        "[![Crosslingual Models](http://img.youtube.com/vi/caZLVcJqsqo/0.jpg)](https://youtu.be/caZLVcJqsqo \"Crosslingual Models\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R5p-YiGOJRLV",
        "outputId": "e1bc4e01-6b23-4273-d5d8-4faa7cd25486"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m75.3/75.3 kB\u001b[0m \u001b[31m1.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m219.1/219.1 kB\u001b[0m \u001b[31m11.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m104.3/104.3 MB\u001b[0m \u001b[31m6.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m17.6/17.6 MB\u001b[0m \u001b[31m38.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m35.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.8/5.8 MB\u001b[0m \u001b[31m66.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m224.5/224.5 kB\u001b[0m \u001b[31m8.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.8/7.8 MB\u001b[0m \u001b[31m89.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ],
      "source": [
        "%%bash\n",
        "pip install -qq -U text2text"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import text2text as t2t"
      ],
      "metadata": {
        "id": "6FIO1kNS1o9O"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "### Assistant\n",
        "# Free private open source alternative to commercial LLMs.\n",
        "# Commercial LLMs are costly, collect your data, impose quotas and rate limits that hinder development.\n",
        "# Run at no cost on Google Colab free tier, so you don't even need your own device.\n",
        "# For more examples, see https://colab.research.google.com/drive/1K6Kk80w9vjFZ7PL9dPRgVuOPuaWcY4ae\n",
        "# To add a knowledge base, see https://colab.research.google.com/drive/1hkNgpSmmUA-mzUibqz25xq-E8KYOLuVx?usp=sharing\n",
        "\n",
        "asst = t2t.Assistant()\n",
        "\n",
        "# Streaming example\n",
        "chat_history = [\n",
        "    {\"role\": \"user\",  \"content\": \"Hi\"},\n",
        "    {\"role\": \"assistant\", \"content\": \"Hello, how are you?\"},\n",
        "    {\"role\": \"user\", \"content\": \"What should I do today?\"}\n",
        "]\n",
        "\n",
        "result = asst.chat_completion(chat_history, stream=True) #{'role': 'assistant', 'content': '1. Make a list of things to be grateful for.\\n2. Go outside and take a walk in nature.\\n3. Practice mindfulness meditation.\\n4. Connect with a loved one or friend.\\n5. Do something kind for someone else.\\n6. Engage in a creative activity like drawing or writing.\\n7. Read an uplifting book or listen to motivational podcasts.'}\n",
        "for chunk in result:\n",
        "  print(chunk['message']['content'], end='', flush=True)"
      ],
      "metadata": {
        "id": "VPMdUSy9YYRl"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# clear memory for other models\n",
        "del assistant"
      ],
      "metadata": {
        "id": "ZqvizPpXyH5W"
      },
      "execution_count": null,
      "outputs": []
    },
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        },
        "id": "jiUl1ls51cuW",
        "outputId": "874350da-f1af-41fb-87b8-7a7f0d586fa7"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Better speed can be achieved with apex installed.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/272 [00:00<?, ?B/s]"
            ],
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        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)olve/main/vocab.json:   0%|          | 0.00/3.71M [00:00<?, ?B/s]"
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          "data": {
            "text/plain": [
              "Downloading (…)tencepiece.bpe.model:   0%|          | 0.00/2.42M [00:00<?, ?B/s]"
            ],
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)cial_tokens_map.json:   0%|          | 0.00/1.14k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "fff05a80388b44acaf7affcadbe6cc06"
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          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[['▁Hello', ',', '▁World', '!']]"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ],
      "source": [
        "### Tokenizer\n",
        "tokenizer = t2t.Tokenizer()\n",
        "tokenizer.transform([\"Hello, World!\"])\n",
        "#[['▁Hello', ',', '▁World', '!']]"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "del tokenizer"
      ],
      "metadata": {
        "id": "waqveLQk5b2R"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 83,
          "referenced_widgets": [
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        "id": "kcTKpC5wS7Xs",
        "outputId": "be30573c-4193-42b9-faf2-ebbb01ddc926"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading:   0%|          | 0.00/1.94G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
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          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0.0125036 , 0.00377429, 0.01060265, ..., 0.03131489, 0.04224026,\n",
              "        0.0292194 ]], dtype=float32)"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ],
      "source": [
        "vectorizer = t2t.Vectorizer()\n",
        "vectorizer.transform([\"Hello, World!\"]) #array([[0.18745188, 0.05658336, 0.15895301, ..., 0.46946704, 0.6332584 , 0.43805206]], dtype=float32)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "del vectorizer"
      ],
      "metadata": {
        "id": "0VQxBw9d5dBt"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NtbMwkhTS9ID",
        "outputId": "a3891f46-2016-4d7a-9dcf-e514dbf02709"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'▁Hello': 0.5, ',': 0.5, '▁World': 0.5, '!': 0.5}]"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ],
      "source": [
        "tfidfer = t2t.Tfidfer()\n",
        "tfidfer.transform([\"Hello, World!\"]) #[{'!': 0.5, ',': 0.5, '▁Hello': 0.5, '▁World': 0.5}]"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "del tfidfer"
      ],
      "metadata": {
        "id": "aO5HsCqD5eFj"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PZd0nkVVnsYU",
        "outputId": "995417bf-4b0f-40dc-a2db-8a61d033b453"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'▁Hello': 0.3068528194400547,\n",
              "  ',': 0.3068528194400547,\n",
              "  '▁World': 0.3068528194400547,\n",
              "  '!': 0.3068528194400547}]"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ],
      "source": [
        "bm25er = t2t.Bm25er()\n",
        "bm25er.transform([\"Hello, World!\"]) #[{'!': 0.5, ',': 0.5, '▁Hello': 0.5, '▁World': 0.5}]"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "del bm25er"
      ],
      "metadata": {
        "id": "2rilrjim5e9G"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "### Index for information retrieval\n",
        "# [STF-IDF Demo] https://colab.research.google.com/drive/1RaWj5SqWvyC2SsCTGg8IAVcl9G5hOB50?usp=sharing\n",
        "\n",
        "index = t2t.Indexer().transform([\n",
        "  \"Let's go hiking tomorrow, let's go!\",\n",
        "  \"안녕하세요.\",\n",
        "  \"돼지꿈을 꾸세요~~\",\n",
        "])\n",
        "\n",
        "index.retrieve([\"돼지\"], k=1) #[['\"돼지꿈을 꾸세요~~\"']]\n",
        "\n",
        "# Add documents incrementing on ids if none specified\n",
        "index.add([\"Hello, World! 你好,世界!\"])\n",
        "\n",
        "# Remove by ids\n",
        "index.remove([2]) #Removes \"안녕하세요.\"\n",
        "\n",
        "# Retrieve k results per query sorted by distance\n",
        "index.retrieve([\"你好, World\"], k=3)\n",
        "\n",
        "# To learn more, see [STF-IDF](https://arxiv.org/abs/2209.14281)."
      ],
      "metadata": {
        "id": "jWTF88R46-au",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a42f2a44-f169-4058-823e-e71bb4235f21"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Creating index with 128104 dimensions.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([[0.7752551],\n",
              "        [0.8452994],\n",
              "        [0.4347524]], dtype=float32), array([[102],\n",
              "        [101],\n",
              "        [100]]))"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "del index"
      ],
      "metadata": {
        "id": "UDkgd_Iw5f-f"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ceb_OD6-S_Lx",
        "outputId": "7eebc6a0-dccf-410b-d58f-6e98e35badf7"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/transformers/generation/utils.py:1387: UserWarning: Neither `max_length` nor `max_new_tokens` has been set, `max_length` will default to 200 (`self.config.max_length`). Controlling `max_length` via the config is deprecated and `max_length` will be removed from the config in v5 of Transformers -- we recommend using `max_new_tokens` to control the maximum length of the generation.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['你好,世界!']"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ],
      "source": [
        "translator = t2t.Translator()\n",
        "translator.transform([\"Hello, World!\"], src_lang=\"en\", tgt_lang=\"zh\") #['你好,世界!']"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "del translator"
      ],
      "metadata": {
        "id": "2yC0S6bx5lmi"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "I9CDJUZ0TCVj",
        "outputId": "05ef3087-874e-49c6-f8d5-d2cd85b3dbb0"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Hello the world!',\n",
              " 'My brother and sister!',\n",
              " 'Welcome to the world!',\n",
              " 'Hello, the world',\n",
              " '“No to the world”',\n",
              " 'It is clearly!',\n",
              " 'Welcome to the light!',\n",
              " 'Hello to the world!',\n",
              " 'Hello to the world!',\n",
              " 'Hello, it’s a good thing!',\n",
              " 'Congratulations to all!',\n",
              " 'Hello to the world!',\n",
              " 'Hello to the world!',\n",
              " 'Good Morning, the World',\n",
              " 'Welcome to the World!',\n",
              " 'Hello the world!',\n",
              " 'Hello the world!',\n",
              " 'Good morning to the world!',\n",
              " 'Hello, World!',\n",
              " 'Hello the world!',\n",
              " 'Fortunately the world!',\n",
              " 'Hello to the world!',\n",
              " 'We do it!',\n",
              " 'Welcome to the world!',\n",
              " 'Hello to the world!',\n",
              " 'Go to the world!',\n",
              " 'Member of the Board of Directors of the Board of Directors of the Board of Directors of the Board of Directors',\n",
              " 'The world.',\n",
              " 'Hello to the world!',\n",
              " 'and it is!',\n",
              " 'Hello, for the world!',\n",
              " 'Hello to the world!',\n",
              " 'Hello to the world!',\n",
              " 'Hello to the world!',\n",
              " 'Hello to the world!',\n",
              " 'Hello to the world!',\n",
              " 'Welcome to the world!',\n",
              " 'Congratulations to the world!',\n",
              " 'Hello to the World!',\n",
              " 'Around the world!',\n",
              " 'Well and well!',\n",
              " 'Hello to the world!',\n",
              " 'Hello to the world!',\n",
              " 'Congratulations to you!',\n",
              " 'Go to the world!',\n",
              " 'I am I am I am!',\n",
              " 'and the air!',\n",
              " 'and it is the one!',\n",
              " 'Hello the world!',\n",
              " 'Hello the world!',\n",
              " 'Hello, movie!',\n",
              " 'Moko!',\n",
              " 'Home » World!',\n",
              " 'Hello and the world!',\n",
              " 'Hello the world!',\n",
              " 'You are here in the world!',\n",
              " 'Hello to the world!',\n",
              " 'Hello the world!',\n",
              " 'The latest!',\n",
              " 'Hello to the world!',\n",
              " 'Welcome to the world!',\n",
              " 'The house!',\n",
              " 'Hello to the world!',\n",
              " 'Hello the world!',\n",
              " 'Hello the world!',\n",
              " 'Smooth!',\n",
              " 'Hello to the world!',\n",
              " 'It is the truth, it is the truth, it is the truth, it is the truth, it is the truth, it is the truth, it is the truth, it is the truth, it is the truth, it is the truth, it is the truth.',\n",
              " 'Hello, Europe!',\n",
              " 'Hello the world!',\n",
              " 'in the world!',\n",
              " 'Hello to the world!',\n",
              " 'Good day to the world!',\n",
              " 'Hello to the world!',\n",
              " 'Hello to the world!',\n",
              " 'Congratulations to the world!',\n",
              " 'Good Morning World!',\n",
              " 'Hello to the world!',\n",
              " 'Aaaaaaaaa',\n",
              " 'Hello to the world!',\n",
              " 'Welcome to the world!',\n",
              " 'Issues',\n",
              " 'In the words of the',\n",
              " 'Hello the world!',\n",
              " 'Hello to the world!',\n",
              " 'Hello to the world!',\n",
              " 'Hello world!',\n",
              " 'Hello to the world!',\n",
              " 'The name!',\n",
              " 'Hello the world!',\n",
              " 'I am in the world!',\n",
              " 'Hello to the world!',\n",
              " 'Hello O’Y’Y’Y!',\n",
              " 'Hello to the world!',\n",
              " 'Wish!',\n",
              " 'First of all!',\n",
              " 'Hello to the world!',\n",
              " 'It is there!',\n",
              " 'Hello the world!',\n",
              " 'First of all!']"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ],
      "source": [
        "### Variation\n",
        "# Useful for augmenting training data\n",
        "variator = t2t.Variator()\n",
        "variator.transform([\"Hello, World!\"], src_lang=\"en\") #['Hello the world!', 'Welcome to the world.', 'Hello to the world!',..."
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "del variator"
      ],
      "metadata": {
        "id": "mpBWByHl5qXd"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8V3geqhhTFdc",
        "outputId": "469f6048-f4fd-4102-8501-256af6e06de2"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[2]"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ],
      "source": [
        "### Levenshtein Sub-word Edit Distance\n",
        "measurer = t2t.Measurer()\n",
        "measurer.transform([\"Hello, World! [SEP] Hello, what?\"]) #[2]\n",
        "measurer.transform([\n",
        "  \"Hello, World! [SEP] Hello, what?\",\n",
        "  \"안녕하세요. [SEP] 돼지꿈을 꾸세요~~\"\n",
        "], metric=\"levenshtein_distance\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "del measurer"
      ],
      "metadata": {
        "id": "JwSC9eNx5rVm"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "server = t2t.Server(host='0.0.0.0', port=80)\n",
        "\n",
        "import time\n",
        "time.sleep(1)"
      ],
      "metadata": {
        "id": "hv72aPlE5ww1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9cf4a32e-9e6d-4253-e72a-46b46df0e79b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Creating index with 128104 dimensions.\n",
            "Serving at http://172.28.0.12/\n",
            " * Serving Flask app \"text2text.server\" (lazy loading)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<text2text.server.Server at 0x7f2cad2988e0>"
            ]
          },
          "metadata": {},
          "execution_count": 14
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " * Environment: production\n",
            "\u001b[31m   WARNING: This is a development server. Do not use it in a production deployment.\u001b[0m\n",
            "\u001b[2m   Use a production WSGI server instead.\u001b[0m\n",
            " * Debug mode: off\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import socket\n",
        "import requests\n",
        "\n",
        "address = socket.gethostbyname(socket.getfqdn(socket.gethostname()))\n",
        "url = f\"http://{address}\"\n",
        "transformer = \"Translator\"\n",
        "payload = {\n",
        "  \"input_lines\": [\"hello\", \"world\"],\n",
        "  \"src_lang\": \"en\",\n",
        "  \"tgt_lang\": \"ko\",\n",
        "}\n",
        "r = requests.post(f\"{url}/{transformer}\", json=payload)\n",
        "print(r.json())\n",
        "r = requests.post(f\"{url}/Indexer/add\", json=payload)\n",
        "print(r.json())\n",
        "r = requests.post(f\"{url}/Indexer/size\", json=payload)\n",
        "print(r.json())\n",
        "r = requests.post(f\"{url}/Indexer/search\", json=payload)\n",
        "print(r.json())\n",
        "r = requests.post(f\"{url}/Indexer/retrieve\", json=payload)\n",
        "print(r.json())\n",
        "payload[\"ids\"] = [0,1]\n",
        "r = requests.post(f\"{url}/Indexer/remove\", json=payload)\n",
        "print(r.json())"
      ],
      "metadata": {
        "id": "KsMirskN5xcG",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "36a5281c-b679-48dd-c431-065695e305f8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:werkzeug: * Running on http://0.0.0.0:80/ (Press CTRL+C to quit)\n",
            "INFO:werkzeug:172.28.0.12 - - [15/Dec/2022 17:29:39] \"\u001b[37mPOST /translate HTTP/1.1\u001b[0m\" 200 -\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'result': ['안녕하세요', '세계']}\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:werkzeug:172.28.0.12 - - [15/Dec/2022 17:29:40] \"\u001b[37mPOST /index/add HTTP/1.1\u001b[0m\" 200 -\n",
            "INFO:werkzeug:172.28.0.12 - - [15/Dec/2022 17:29:40] \"\u001b[37mPOST /index/size HTTP/1.1\u001b[0m\" 200 -\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'result': 'index/add performed'}\n",
            "{'result': 2}\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:werkzeug:172.28.0.12 - - [15/Dec/2022 17:29:41] \"\u001b[37mPOST /index/search HTTP/1.1\u001b[0m\" 200 -\n",
            "INFO:werkzeug:172.28.0.12 - - [15/Dec/2022 17:29:41] \"\u001b[37mPOST /index/remove HTTP/1.1\u001b[0m\" 200 -\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'result': [[[0.0, 2.0, 3.4028234663852886e+38], [0.0, 2.0, 3.4028234663852886e+38]], [[1.0, 2.0, -1.0], [2.0, 1.0, -1.0]]]}\n",
            "{'result': 'index/remove performed'}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "del server"
      ],
      "metadata": {
        "id": "PHqmOon-5wwU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "F0RWWWrM83ov",
        "outputId": "400db902-d3d3-4922-d300-b6c0020094a1"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'af': 'Afrikaans',\n",
              " 'am': 'Amharic',\n",
              " 'ar': 'Arabic',\n",
              " 'ast': 'Asturian',\n",
              " 'az': 'Azerbaijani',\n",
              " 'ba': 'Bashkir',\n",
              " 'be': 'Belarusian',\n",
              " 'bg': 'Bulgarian',\n",
              " 'bn': 'Bengali',\n",
              " 'br': 'Breton',\n",
              " 'bs': 'Bosnian',\n",
              " 'ca': 'Catalan_Valencian',\n",
              " 'ceb': 'Cebuano',\n",
              " 'cs': 'Czech',\n",
              " 'cy': 'Welsh',\n",
              " 'da': 'Danish',\n",
              " 'de': 'German',\n",
              " 'el': 'Greeek',\n",
              " 'en': 'English',\n",
              " 'es': 'Spanish',\n",
              " 'et': 'Estonian',\n",
              " 'fa': 'Persian',\n",
              " 'ff': 'Fulah',\n",
              " 'fi': 'Finnish',\n",
              " 'fr': 'French',\n",
              " 'fy': 'Western_Frisian',\n",
              " 'ga': 'Irish',\n",
              " 'gd': 'Gaelic_Scottish_Gaelic',\n",
              " 'gl': 'Galician',\n",
              " 'gu': 'Gujarati',\n",
              " 'ha': 'Hausa',\n",
              " 'he': 'Hebrew',\n",
              " 'hi': 'Hindi',\n",
              " 'hr': 'Croatian',\n",
              " 'ht': 'Haitian_Haitian_Creole',\n",
              " 'hu': 'Hungarian',\n",
              " 'hy': 'Armenian',\n",
              " 'id': 'Indonesian',\n",
              " 'ig': 'Igbo',\n",
              " 'ilo': 'Iloko',\n",
              " 'is': 'Icelandic',\n",
              " 'it': 'Italian',\n",
              " 'ja': 'Japanese',\n",
              " 'jv': 'Javanese',\n",
              " 'ka': 'Georgian',\n",
              " 'kk': 'Kazakh',\n",
              " 'km': 'Central_Khmer',\n",
              " 'kn': 'Kannada',\n",
              " 'ko': 'Korean',\n",
              " 'lb': 'Luxembourgish_Letzeburgesch',\n",
              " 'lg': 'Ganda',\n",
              " 'ln': 'Lingala',\n",
              " 'lo': 'Lao',\n",
              " 'lt': 'Lithuanian',\n",
              " 'lv': 'Latvian',\n",
              " 'mg': 'Malagasy',\n",
              " 'mk': 'Macedonian',\n",
              " 'ml': 'Malayalam',\n",
              " 'mn': 'Mongolian',\n",
              " 'mr': 'Marathi',\n",
              " 'ms': 'Malay',\n",
              " 'my': 'Burmese',\n",
              " 'ne': 'Nepali',\n",
              " 'nl': 'Dutch_Flemish',\n",
              " 'no': 'Norwegian',\n",
              " 'ns': 'Northern_Sotho',\n",
              " 'oc': 'Occitan',\n",
              " 'or': 'Oriya',\n",
              " 'pa': 'Panjabi_Punjabi',\n",
              " 'pl': 'Polish',\n",
              " 'ps': 'Pushto_Pashto',\n",
              " 'pt': 'Portuguese',\n",
              " 'ro': 'Romanian_Moldavian_Moldovan',\n",
              " 'ru': 'Russian',\n",
              " 'sd': 'Sindhi',\n",
              " 'si': 'Sinhala_Sinhalese',\n",
              " 'sk': 'Slovak',\n",
              " 'sl': 'Slovenian',\n",
              " 'so': 'Somali',\n",
              " 'sq': 'Albanian',\n",
              " 'sr': 'Serbian',\n",
              " 'ss': 'Swati',\n",
              " 'su': 'Sundanese',\n",
              " 'sv': 'Swedish',\n",
              " 'sw': 'Swahili',\n",
              " 'ta': 'Tamil',\n",
              " 'th': 'Thai',\n",
              " 'tl': 'Tagalog',\n",
              " 'tn': 'Tswana',\n",
              " 'tr': 'Turkish',\n",
              " 'uk': 'Ukrainian',\n",
              " 'ur': 'Urdu',\n",
              " 'uz': 'Uzbek',\n",
              " 'vi': 'Vietnamese',\n",
              " 'wo': 'Wolof',\n",
              " 'xh': 'Xhosa',\n",
              " 'yi': 'Yiddish',\n",
              " 'yo': 'Yoruba',\n",
              " 'zh': 'Chinese',\n",
              " 'zu': 'Zulu'}"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ],
      "source": [
        "### Languages Available\n",
        "t2t.Transformer.LANGUAGES"
      ]
    }
  ],
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