examples/trippy_rasa_tutorial.ipynb

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    "colab": {
      "name": "Copy of TRIPPY_RASA_TINY",
      "provenance": [],
      "collapsed_sections": []
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    "kernelspec": {
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  "cells": [
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      "cell_type": "markdown",
      "metadata": {
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      "source": [
        "### You can also run the notebook in [COLAB](https://colab.research.google.com/github/deepmipt/DeepPavlov/blob/master/examples/trippy_rasa_tutorial.ipynb)."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mKHBh1lcCwzx"
      },
      "source": [
        "## Rasa 2.X with TripPy\n",
        "\n",
        "This is a tiny demo to show you how you can build a goal oriented bot in DeepPavlov leveraging the RASA format and the TripPy model in ~<10 lines of code!\n",
        "\n",
        "So without further ado, let's go!"
      ]
    },
    {
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          "height": 1000
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        "outputId": "6eebfd60-77f6-4a31-e64f-fc7fbf8d6e53"
      },
      "source": [
        "!git clone -b rulebased_gobot_trippy https://github.com/Muennighoff/DeepPavlov\n",
        "%cd DeepPavlov\n",
        "!pip install -r requirements.txt"
      ],
      "execution_count": null,
      "outputs": [
        {
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          "text": [
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            "\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",
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          ],
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        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "numpy",
                  "pandas",
                  "pytz"
                ]
              }
            }
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          "metadata": {
            "tags": []
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      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hm3VCqMNJAOD"
      },
      "source": [
        "STORIES_PATH=\"stories.yml\"\n",
        "NLU_PATH=\"nlu.yml\"\n",
        "DOMAIN_PATH=\"domain.yml\""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SNC-jU9pED8p"
      },
      "source": [
        "### `Stories.yml`"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "edx8nWiSk5RV",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cb38ee9c-87d8-44df-ae58-288569a6db24"
      },
      "source": [
        "%%writefile {STORIES_PATH}\n",
        "\n",
        "stories:\n",
        "- story: bla bla\n",
        "  steps:\n",
        "  - intent: user_hey\n",
        "  - action: system_hey\n",
        "  - intent: user_howru\n",
        "  - action: system_fine\n",
        "  - intent: user_bye\n",
        "  - action: system_bye\n",
        "- story: heybye\n",
        "  steps:\n",
        "  - intent: user_hey\n",
        "  - action: system_hey\n",
        "  - intent: user_bye\n",
        "  - action: system_bye\n",
        "- story: howru\n",
        "  steps:\n",
        "  - intent: user_howru\n",
        "  - action: system_fine\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Writing stories.yml\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KXQdDMrql5VE"
      },
      "source": [
        "!cp {STORIES_PATH} stories-trn.yml\n",
        "!cp {STORIES_PATH} stories-tst.yml \n",
        "!cp {STORIES_PATH} stories-val.yml"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KXVajIbEFKbC"
      },
      "source": [
        "### `NLU.yml`"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tpXxp5Tlk-cS",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "11eba142-37fa-4044-d515-b1946814f4d8"
      },
      "source": [
        "%%writefile {NLU_PATH}\n",
        "version: \"2.0\"\n",
        "dp_version: \"2.0\"\n",
        "\n",
        "nlu:\n",
        "  # regex intent\n",
        "  - regex: user_hey\n",
        "    examples: |\n",
        "      - hey\n",
        "      - (hello|hi)\n",
        "\n",
        "  - intent: user_howru\n",
        "    examples: |\n",
        "      - how are you\n",
        "      - how u doin?\n",
        "  \n",
        "  # DeepPavlov IntentCatcher examples\n",
        "  - intent: user_bye\n",
        "    examples: | \n",
        "      - farewell\n",
        "    regex_examples: |\n",
        "      - (((good)|(bye-)){0,1}bye)|(see you (later){0,1})\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Writing nlu.yml\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HhinLEavFNH9"
      },
      "source": [
        "###`Domain.yml`"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1k_L_-PVk-td",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f5d9bc44-58e4-428a-ceda-87fd5bcaa182"
      },
      "source": [
        "%%writefile {DOMAIN_PATH}\n",
        "actions:\n",
        "- system_fine\n",
        "- system_hey\n",
        "- system_bye\n",
        "\n",
        "intents:\n",
        "- user_hey\n",
        "- user_bye\n",
        "- user_howru\n",
        "\n",
        "responses:\n",
        "  system_fine:\n",
        "  - text: im fine\n",
        "  system_hey:\n",
        "  - text: hey you!\n",
        "  system_bye:\n",
        "  - text: bye!"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Writing domain.yml\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "t8NleRtjSap8",
        "outputId": "cf7e0e31-58d9-4b57-b2f1-bbcbc96eda9d"
      },
      "source": [
        "%%writefile deeppavlov/configs/go_bot/trippy_md_yaml_minimal.json\n",
        "{\n",
        "    \"dataset_reader\": {\n",
        "      \"class_name\": \"md_yaml_dialogs_reader\",\n",
        "      \"data_path\": \"{DATA_PATH}\",\n",
        "      \"fmt\": \"yml\"\n",
        "    },\n",
        "    \"dataset_iterator\": {\n",
        "      \"class_name\": \"md_yaml_dialogs_iterator\"\n",
        "    },\n",
        "    \"chainer\": {\n",
        "      \"in\": [\"x\"],\n",
        "      \"in_y\": [\"y\"],\n",
        "      \"out\": [\"y_predicted\"],\n",
        "      \"pipe\": [\n",
        "        {\n",
        "            \"class_name\": \"trippy\",\n",
        "            \"in\": [\"x\"],\n",
        "            \"in_y\": [\"y\"],\n",
        "            \"out\": [\"y_predicted\"],\n",
        "            \"load_path\": \"{MODEL_PATH}/model\",\n",
        "            \"save_path\": \"{MODEL_PATH}/model\",\n",
        "            \"pretrained_bert\": \"bert-base-uncased\",\n",
        "            \"max_seq_length\": 180,\n",
        "            \"debug\": false,\n",
        "            \"database\": null,\n",
        "            \"nlg_manager\": {\n",
        "                \"class_name\": \"gobot_json_nlg_manager\",\n",
        "                \"data_path\": \"{DATA_PATH}\",\n",
        "                \"dataset_reader_class\": \"md_yaml_dialogs_reader\",\n",
        "                \"actions2slots_path\": \"{DATA_PATH}/dstc2-actions2slots.json\",\n",
        "                \"api_call_action\": null\n",
        "            },\n",
        "            \"api_call_action\": null,\n",
        "            \"optimizer_parameters\": {\"lr\": 1e-5, \"eps\": 1e-6}\n",
        "        }\n",
        "      ]\n",
        "    },\n",
        "    \"train\": {\n",
        "        \"batch_size\": 32,\n",
        "        \"max_batches\": 600,\n",
        "    \n",
        "        \"metrics\": [\"per_item_dialog_accuracy\"],\n",
        "        \"validation_patience\": 10,\n",
        "        \"val_every_n_batches\": 15,\n",
        "        \"val_every_n_epochs\": -1,\n",
        "    \n",
        "        \"log_every_n_batches\": 15,\n",
        "        \"log_on_k_batches\": 10,\n",
        "    \n",
        "        \"validate_first\": true,\n",
        "    \n",
        "        \"show_examples\": false,\n",
        "        \"evaluation_targets\": [\n",
        "          \"valid\",\n",
        "          \"test\"\n",
        "        ]\n",
        "      },\n",
        "    \"metadata\": {\n",
        "      \"variables\": {\n",
        "        \"ROOT_PATH\": \"~/.deeppavlov\",\n",
        "        \"CONFIGS_PATH\": \"{DEEPPAVLOV_PATH}/configs\",\n",
        "        \"DOWNLOADS_PATH\": \"{ROOT_PATH}/downloads\",\n",
        "        \"DATA_PATH\": \".\",\n",
        "        \"MODELS_PATH\": \"{ROOT_PATH}/models\",\n",
        "        \"MODEL_PATH\": \".\"\n",
        "      }\n",
        "    }\n",
        "  }\n",
        "  "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Overwriting deeppavlov/configs/go_bot/trippy_md_yaml_minimal.json\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U6_XCLkoVHZk",
        "outputId": "0df75327-cfde-4835-adf4-7915b28f928c"
      },
      "source": [
        "!python -m deeppavlov install deeppavlov/configs/go_bot/trippy_md_yaml_minimal.json"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting transformers==2.9.1\n",
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            "Successfully installed sentencepiece-0.1.96 tokenizers-0.7.0 transformers-2.9.1\n",
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          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "25d1YaLzSami"
      },
      "source": [
        "from deeppavlov import configs\n",
        "from deeppavlov.core.common.file import read_json\n",
        "\n",
        "gobot_config = read_json(configs.go_bot.trippy_md_yaml_minimal)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2_-oecu8Sajn"
      },
      "source": [
        "from deeppavlov import train_model\n",
        "\n",
        "train_model(gobot_config, download=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ARGukrcQSahZ"
      },
      "source": [
        "from deeppavlov import build_model\n",
        "bot = build_model(gobot_config)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7h3R_oB3Saek",
        "outputId": "9e389b6d-e71f-4d7c-bf91-b65b137ca61a"
      },
      "source": [
        "bot.reset()\n",
        "bot([\"hello\"])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[['hey you!']]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eFe3ZWbGSabt",
        "outputId": "115cd9f7-96cc-4236-d415-949c7e82c20c"
      },
      "source": [
        "bot([\"how r u?\"])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[['im fine']]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c7Jsh8HtSaY6",
        "outputId": "c3ede16c-d621-4ef3-fb28-9864035d7f1a"
      },
      "source": [
        "bot([\"ok goodbye\"])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[['bye!']]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    }
  ]
}