Hackathon_registratin.ipynb

{
  "cells": [
    {
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      "execution_count": 3,
      "metadata": {
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          "height": 1000
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        "outputId": "f94c7636-a48d-44e6-c969-e4a88acae71f"
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        {
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          "name": "stdout",
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            "\u001b[?25hCollecting uvloop<0.15.0,>=0.5.3\n",
            "  Downloading uvloop-0.14.0-cp37-cp37m-manylinux2010_x86_64.whl (3.8 MB)\n",
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            "\u001b[?25hCollecting sanic<20.0.0,>=19.12.2\n",
            "  Downloading sanic-19.12.4-py3-none-any.whl (73 kB)\n",
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            "\u001b[?25hCollecting uvloop>=0.5.3\n",
            "  Downloading uvloop-0.16.0-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (3.8 MB)\n",
            "\u001b[K     |████████████████████████████████| 3.8 MB 37.8 MB/s \n",
            "\u001b[?25hCollecting sanic<20.0.0,>=19.12.2\n",
            "  Downloading sanic-19.12.3-py3-none-any.whl (72 kB)\n",
            "\u001b[K     |████████████████████████████████| 72 kB 1.2 MB/s \n",
            "\u001b[?25h  Downloading sanic-19.12.2-py3-none-any.whl (72 kB)\n",
            "\u001b[K     |████████████████████████████████| 72 kB 850 kB/s \n",
            "\u001b[?25hCollecting aiofiles>=0.3.0\n",
            "  Downloading aiofiles-0.8.0-py3-none-any.whl (13 kB)\n",
            "Collecting rfc3986<2,>=1.3\n",
            "  Downloading rfc3986-1.5.0-py2.py3-none-any.whl (31 kB)\n",
            "Collecting h11==0.8.*\n",
            "  Downloading h11-0.8.1-py2.py3-none-any.whl (55 kB)\n",
            "\u001b[K     |████████████████████████████████| 55 kB 3.9 MB/s \n",
            "\u001b[?25hCollecting hstspreload\n",
            "  Downloading hstspreload-2021.12.1-py3-none-any.whl (1.3 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.3 MB 37.5 MB/s \n",
            "\u001b[?25hCollecting h2==3.*\n",
            "  Downloading h2-3.2.0-py2.py3-none-any.whl (65 kB)\n",
            "\u001b[K     |████████████████████████████████| 65 kB 2.6 MB/s \n",
            "\u001b[?25hCollecting sniffio==1.*\n",
            "  Downloading sniffio-1.2.0-py3-none-any.whl (10 kB)\n",
            "Collecting hyperframe<6,>=5.2.0\n",
            "  Downloading hyperframe-5.2.0-py2.py3-none-any.whl (12 kB)\n",
            "Collecting hpack<4,>=3.0\n",
            "  Downloading hpack-3.0.0-py2.py3-none-any.whl (38 kB)\n",
            "Collecting sanic-plugins-framework>=0.9.0\n",
            "  Downloading Sanic_Plugins_Framework-0.9.5-py2.py3-none-any.whl (23 kB)\n",
            "Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.7/dist-packages (from scikit-learn<0.23,>=0.22->rasa==1.10.5) (1.1.0)\n",
            "Collecting python-crfsuite>=0.8.3\n",
            "  Downloading python_crfsuite-0.9.7-cp37-cp37m-manylinux1_x86_64.whl (743 kB)\n",
            "\u001b[K     |████████████████████████████████| 743 kB 45.8 MB/s \n",
            "\u001b[?25hRequirement already satisfied: tabulate in /usr/local/lib/python3.7/dist-packages (from sklearn-crfsuite<0.4,>=0.3->rasa==1.10.5) (0.8.9)\n",
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            "Collecting keras-applications>=1.0.8\n",
            "  Downloading Keras_Applications-1.0.8-py3-none-any.whl (50 kB)\n",
            "\u001b[K     |████████████████████████████████| 50 kB 6.6 MB/s \n",
            "\u001b[?25hRequirement already satisfied: wrapt>=1.11.1 in /usr/local/lib/python3.7/dist-packages (from tensorflow<2.2,>=2.1->rasa==1.10.5) (1.13.3)\n",
            "Requirement already satisfied: grpcio>=1.8.6 in /usr/local/lib/python3.7/dist-packages (from tensorflow<2.2,>=2.1->rasa==1.10.5) (1.43.0)\n",
            "Collecting gast==0.2.2\n",
            "  Downloading gast-0.2.2.tar.gz (10 kB)\n",
            "Collecting numpy<2.0,>=1.16\n",
            "  Downloading numpy-1.18.5-cp37-cp37m-manylinux1_x86_64.whl (20.1 MB)\n",
            "\u001b[K     |████████████████████████████████| 20.1 MB 36.9 MB/s \n",
            "\u001b[?25hRequirement already satisfied: wheel>=0.26 in /usr/local/lib/python3.7/dist-packages (from tensorflow<2.2,>=2.1->rasa==1.10.5) (0.37.1)\n",
            "Collecting h5py<=2.10.0\n",
            "  Downloading h5py-2.10.0-cp37-cp37m-manylinux1_x86_64.whl (2.9 MB)\n",
            "\u001b[K     |████████████████████████████████| 2.9 MB 22.7 MB/s \n",
            "\u001b[?25hCollecting keras-preprocessing==1.1.0\n",
            "  Downloading Keras_Preprocessing-1.1.0-py2.py3-none-any.whl (41 kB)\n",
            "\u001b[K     |████████████████████████████████| 41 kB 699 kB/s \n",
            "\u001b[?25hRequirement already satisfied: astor>=0.6.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow<2.2,>=2.1->rasa==1.10.5) (0.8.1)\n",
            "Requirement already satisfied: protobuf>=3.8.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow<2.2,>=2.1->rasa==1.10.5) (3.17.3)\n",
            "Requirement already satisfied: google-pasta>=0.1.6 in /usr/local/lib/python3.7/dist-packages (from tensorflow<2.2,>=2.1->rasa==1.10.5) (0.2.0)\n",
            "Collecting tensorboard<2.2.0,>=2.1.0\n",
            "  Downloading tensorboard-2.1.1-py3-none-any.whl (3.8 MB)\n",
            "\u001b[K     |████████████████████████████████| 3.8 MB 32.1 MB/s \n",
            "\u001b[?25hRequirement already satisfied: opt-einsum>=2.3.2 in /usr/local/lib/python3.7/dist-packages (from tensorflow<2.2,>=2.1->rasa==1.10.5) (3.3.0)\n",
            "Requirement already satisfied: google-auth<2,>=1.6.3 in /usr/local/lib/python3.7/dist-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow<2.2,>=2.1->rasa==1.10.5) (1.35.0)\n",
            "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.7/dist-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow<2.2,>=2.1->rasa==1.10.5) (3.3.6)\n",
            "Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in /usr/local/lib/python3.7/dist-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow<2.2,>=2.1->rasa==1.10.5) (0.4.6)\n",
            "Requirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.7/dist-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow<2.2,>=2.1->rasa==1.10.5) (1.0.1)\n",
            "Requirement already satisfied: cachetools<5.0,>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from google-auth<2,>=1.6.3->tensorboard<2.2.0,>=2.1.0->tensorflow<2.2,>=2.1->rasa==1.10.5) (4.2.4)\n",
            "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.7/dist-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.2.0,>=2.1.0->tensorflow<2.2,>=2.1->rasa==1.10.5) (1.3.1)\n",
            "Requirement already satisfied: typing-extensions>=3.6.4 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->jsonpickle<1.5,>=1.3->rasa==1.10.5) (3.10.0.2)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->jsonpickle<1.5,>=1.3->rasa==1.10.5) (3.7.0)\n",
            "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.7/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.2.0,>=2.1.0->tensorflow<2.2,>=2.1->rasa==1.10.5) (3.2.0)\n",
            "Requirement already satisfied: pysocks in /usr/local/lib/python3.7/dist-packages (from twilio<6.27,>=6.26->rasa==1.10.5) (1.7.1)\n",
            "Requirement already satisfied: future in /usr/local/lib/python3.7/dist-packages (from webexteamssdk<1.4.0,>=1.1.1->rasa==1.10.5) (0.16.0)\n",
            "Collecting requests-toolbelt\n",
            "  Downloading requests_toolbelt-0.9.1-py2.py3-none-any.whl (54 kB)\n",
            "\u001b[K     |████████████████████████████████| 54 kB 2.5 MB/s \n",
            "\u001b[?25hRequirement already satisfied: cffi>=1.12 in /usr/local/lib/python3.7/dist-packages (from cryptography->python-telegram-bot<13.0,>=11.1->rasa==1.10.5) (1.15.0)\n",
            "Requirement already satisfied: pycparser in /usr/local/lib/python3.7/dist-packages (from cffi>=1.12->cryptography->python-telegram-bot<13.0,>=11.1->rasa==1.10.5) (2.21)\n",
            "Building wheels for collected packages: absl-py, mattermostwrapper, sanic-jwt, gast, webexteamssdk\n",
            "  Building wheel for absl-py (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for absl-py: filename=absl_py-0.9.0-py3-none-any.whl size=121939 sha256=9a716fe0df7c4962cb4ef9af908558eaeece2d15cef1df912bdeff15d462daee\n",
            "  Stored in directory: /root/.cache/pip/wheels/cc/af/1a/498a24d0730ef484019e007bb9e8cef3ac00311a672c049a3e\n",
            "  Building wheel for mattermostwrapper (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for mattermostwrapper: filename=mattermostwrapper-2.2-py3-none-any.whl size=2465 sha256=eecf9ac1043a4c1b62bc13e2535a16bbfaae2468e394ed0eeee3491dc882edb5\n",
            "  Stored in directory: /root/.cache/pip/wheels/b9/70/77/6c3f3c9a6f096f765d0767b21e73598d66c3b79cb7b09b62ad\n",
            "  Building wheel for sanic-jwt (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for sanic-jwt: filename=sanic_jwt-1.4.1-py3-none-any.whl size=21613 sha256=c464220bbdd050d7e26bfd729eb1b590d0e6bef813ac0c890b8c4e3405e3ff59\n",
            "  Stored in directory: /root/.cache/pip/wheels/26/df/b1/f72efce63fe6e26b2bae666e1cae88c68c38d718dafb9183b0\n",
            "  Building wheel for gast (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for gast: filename=gast-0.2.2-py3-none-any.whl size=7554 sha256=a7c86d801048516088b28df37138805354f73177cb5089dcfd3ad6b4591d2ebb\n",
            "  Stored in directory: /root/.cache/pip/wheels/21/7f/02/420f32a803f7d0967b48dd823da3f558c5166991bfd204eef3\n",
            "  Building wheel for webexteamssdk (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for webexteamssdk: filename=webexteamssdk-1.3-py3-none-any.whl size=99579 sha256=bb28ee9bded7c746fe71d3552f257e3fe29be864092d0e4e484c1dc9bb481e0a\n",
            "  Stored in directory: /root/.cache/pip/wheels/08/88/4d/7fe6eec20e0658e8ad6edd9969d27114280780d7f4ef42e436\n",
            "Successfully built absl-py mattermostwrapper sanic-jwt gast webexteamssdk\n",
            "Installing collected packages: urllib3, hyperframe, hpack, sniffio, rfc3986, hstspreload, h2, h11, websockets, uvloop, ujson, numpy, multidict, httpx, httptools, aiofiles, sanic, jmespath, h5py, absl-py, yarl, tensorflow-estimator, tensorboard, sanic-plugins-framework, pytz, keras-preprocessing, keras-applications, humanfriendly, gast, botocore, attrs, async-timeout, tqdm, tensorflow, sanic-cors, s3transfer, ruamel.yaml.clib, requests-toolbelt, python-engineio, python-crfsuite, pymongo, PyJWT, prompt-toolkit, dnspython, cryptography, coloredlogs, aiohttp, webexteamssdk, twilio, terminaltables, tensorflow-probability, tensorflow-hub, tensorflow-addons, SQLAlchemy, slackclient, sklearn-crfsuite, scikit-learn, sanic-jwt, ruamel.yaml, rocketchat-API, regex, redis, rasa-sdk, questionary, python-telegram-bot, python-socketio, pykwalify, pydot, psycopg2-binary, pika, packaging, networkx, mattermostwrapper, kafka-python, jsonschema, jsonpickle, gevent, fbmessenger, colorhash, colorclass, boto3, async-generator, apscheduler, rasa\n",
            "  Attempting uninstall: urllib3\n",
            "    Found existing installation: urllib3 1.24.3\n",
            "    Uninstalling urllib3-1.24.3:\n",
            "      Successfully uninstalled urllib3-1.24.3\n",
            "  Attempting uninstall: numpy\n",
            "    Found existing installation: numpy 1.19.5\n",
            "    Uninstalling numpy-1.19.5:\n",
            "      Successfully uninstalled numpy-1.19.5\n",
            "  Attempting uninstall: h5py\n",
            "    Found existing installation: h5py 3.1.0\n",
            "    Uninstalling h5py-3.1.0:\n",
            "      Successfully uninstalled h5py-3.1.0\n",
            "  Attempting uninstall: absl-py\n",
            "    Found existing installation: absl-py 1.0.0\n",
            "    Uninstalling absl-py-1.0.0:\n",
            "      Successfully uninstalled absl-py-1.0.0\n",
            "  Attempting uninstall: tensorflow-estimator\n",
            "    Found existing installation: tensorflow-estimator 2.7.0\n",
            "    Uninstalling tensorflow-estimator-2.7.0:\n",
            "      Successfully uninstalled tensorflow-estimator-2.7.0\n",
            "  Attempting uninstall: tensorboard\n",
            "    Found existing installation: tensorboard 2.7.0\n",
            "    Uninstalling tensorboard-2.7.0:\n",
            "      Successfully uninstalled tensorboard-2.7.0\n",
            "  Attempting uninstall: pytz\n",
            "    Found existing installation: pytz 2018.9\n",
            "    Uninstalling pytz-2018.9:\n",
            "      Successfully uninstalled pytz-2018.9\n",
            "  Attempting uninstall: keras-preprocessing\n",
            "    Found existing installation: Keras-Preprocessing 1.1.2\n",
            "    Uninstalling Keras-Preprocessing-1.1.2:\n",
            "      Successfully uninstalled Keras-Preprocessing-1.1.2\n",
            "  Attempting uninstall: gast\n",
            "    Found existing installation: gast 0.4.0\n",
            "    Uninstalling gast-0.4.0:\n",
            "      Successfully uninstalled gast-0.4.0\n",
            "  Attempting uninstall: attrs\n",
            "    Found existing installation: attrs 21.4.0\n",
            "    Uninstalling attrs-21.4.0:\n",
            "      Successfully uninstalled attrs-21.4.0\n",
            "  Attempting uninstall: tqdm\n",
            "    Found existing installation: tqdm 4.62.3\n",
            "    Uninstalling tqdm-4.62.3:\n",
            "      Successfully uninstalled tqdm-4.62.3\n",
            "  Attempting uninstall: tensorflow\n",
            "    Found existing installation: tensorflow 2.7.0\n",
            "    Uninstalling tensorflow-2.7.0:\n",
            "      Successfully uninstalled tensorflow-2.7.0\n",
            "  Attempting uninstall: pymongo\n",
            "    Found existing installation: pymongo 4.0.1\n",
            "    Uninstalling pymongo-4.0.1:\n",
            "      Successfully uninstalled pymongo-4.0.1\n",
            "  Attempting uninstall: prompt-toolkit\n",
            "    Found existing installation: prompt-toolkit 1.0.18\n",
            "    Uninstalling prompt-toolkit-1.0.18:\n",
            "      Successfully uninstalled prompt-toolkit-1.0.18\n",
            "  Attempting uninstall: tensorflow-probability\n",
            "    Found existing installation: tensorflow-probability 0.15.0\n",
            "    Uninstalling tensorflow-probability-0.15.0:\n",
            "      Successfully uninstalled tensorflow-probability-0.15.0\n",
            "  Attempting uninstall: tensorflow-hub\n",
            "    Found existing installation: tensorflow-hub 0.12.0\n",
            "    Uninstalling tensorflow-hub-0.12.0:\n",
            "      Successfully uninstalled tensorflow-hub-0.12.0\n",
            "  Attempting uninstall: SQLAlchemy\n",
            "    Found existing installation: SQLAlchemy 1.4.31\n",
            "    Uninstalling SQLAlchemy-1.4.31:\n",
            "      Successfully uninstalled SQLAlchemy-1.4.31\n",
            "  Attempting uninstall: scikit-learn\n",
            "    Found existing installation: scikit-learn 1.0.2\n",
            "    Uninstalling scikit-learn-1.0.2:\n",
            "      Successfully uninstalled scikit-learn-1.0.2\n",
            "  Attempting uninstall: regex\n",
            "    Found existing installation: regex 2019.12.20\n",
            "    Uninstalling regex-2019.12.20:\n",
            "      Successfully uninstalled regex-2019.12.20\n",
            "  Attempting uninstall: pydot\n",
            "    Found existing installation: pydot 1.3.0\n",
            "    Uninstalling pydot-1.3.0:\n",
            "      Successfully uninstalled pydot-1.3.0\n",
            "  Attempting uninstall: packaging\n",
            "    Found existing installation: packaging 21.3\n",
            "    Uninstalling packaging-21.3:\n",
            "      Successfully uninstalled packaging-21.3\n",
            "  Attempting uninstall: networkx\n",
            "    Found existing installation: networkx 2.6.3\n",
            "    Uninstalling networkx-2.6.3:\n",
            "      Successfully uninstalled networkx-2.6.3\n",
            "  Attempting uninstall: jsonschema\n",
            "    Found existing installation: jsonschema 4.3.3\n",
            "    Uninstalling jsonschema-4.3.3:\n",
            "      Successfully uninstalled jsonschema-4.3.3\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",
            "panel 0.12.1 requires tqdm>=4.48.0, but you have tqdm 4.45.0 which is incompatible.\n",
            "nbclient 0.5.10 requires jupyter-client>=6.1.5, but you have jupyter-client 5.3.5 which is incompatible.\n",
            "jupyter-console 5.2.0 requires prompt-toolkit<2.0.0,>=1.0.0, but you have prompt-toolkit 2.0.10 which is incompatible.\n",
            "ipython 5.5.0 requires prompt-toolkit<2.0.0,>=1.0.4, but you have prompt-toolkit 2.0.10 which is incompatible.\n",
            "imbalanced-learn 0.8.1 requires scikit-learn>=0.24, but you have scikit-learn 0.22.2.post1 which is incompatible.\n",
            "datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\n",
            "albumentations 0.1.12 requires imgaug<0.2.7,>=0.2.5, but you have imgaug 0.2.9 which is incompatible.\u001b[0m\n",
            "Successfully installed PyJWT-1.7.1 SQLAlchemy-1.3.24 absl-py-0.9.0 aiofiles-0.8.0 aiohttp-3.6.3 apscheduler-3.6.3 async-generator-1.10 async-timeout-3.0.1 attrs-19.3.0 boto3-1.20.49 botocore-1.23.49 colorclass-2.2.2 coloredlogs-10.0 colorhash-1.0.4 cryptography-36.0.1 dnspython-1.16.0 fbmessenger-6.0.0 gast-0.2.2 gevent-1.5.0 h11-0.8.1 h2-3.2.0 h5py-2.10.0 hpack-3.0.0 hstspreload-2021.12.1 httptools-0.3.0 httpx-0.9.3 humanfriendly-10.0 hyperframe-5.2.0 jmespath-0.10.0 jsonpickle-1.4.2 jsonschema-3.2.0 kafka-python-1.4.7 keras-applications-1.0.8 keras-preprocessing-1.1.0 mattermostwrapper-2.2 multidict-4.7.6 networkx-2.4 numpy-1.18.5 packaging-20.9 pika-1.1.0 prompt-toolkit-2.0.10 psycopg2-binary-2.8.6 pydot-1.4.2 pykwalify-1.7.0 pymongo-3.8.0 python-crfsuite-0.9.7 python-engineio-3.12.1 python-socketio-4.5.1 python-telegram-bot-12.8 pytz-2019.3 questionary-1.5.2 rasa-1.10.5 rasa-sdk-1.10.3 redis-3.5.3 regex-2020.6.8 requests-toolbelt-0.9.1 rfc3986-1.5.0 rocketchat-API-1.3.1 ruamel.yaml-0.16.13 ruamel.yaml.clib-0.2.6 s3transfer-0.5.1 sanic-19.12.2 sanic-cors-0.10.0.post3 sanic-jwt-1.4.1 sanic-plugins-framework-0.9.5 scikit-learn-0.22.2.post1 sklearn-crfsuite-0.3.6 slackclient-2.9.3 sniffio-1.2.0 tensorboard-2.1.1 tensorflow-2.1.4 tensorflow-addons-0.7.1 tensorflow-estimator-2.1.0 tensorflow-hub-0.8.0 tensorflow-probability-0.9.0 terminaltables-3.1.10 tqdm-4.45.0 twilio-6.26.3 ujson-2.0.3 urllib3-1.25.11 uvloop-0.16.0 webexteamssdk-1.3 websockets-8.1 yarl-1.5.1\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "numpy",
                  "packaging",
                  "prompt_toolkit",
                  "pytz"
                ]
              }
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "!pip install rasa==1.10.5"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_E6RG7zr4d-e",
        "outputId": "973249a5-6570-4b1c-f203-04868679a8b9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting en_core_web_sm==2.2.5\n",
            "  Downloading https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-2.2.5/en_core_web_sm-2.2.5.tar.gz (12.0 MB)\n",
            "\u001b[K     |████████████████████████████████| 12.0 MB 5.4 MB/s \n",
            "\u001b[?25hRequirement already satisfied: spacy>=2.2.2 in /usr/local/lib/python3.7/dist-packages (from en_core_web_sm==2.2.5) (2.2.4)\n",
            "Requirement already satisfied: wasabi<1.1.0,>=0.4.0 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->en_core_web_sm==2.2.5) (0.9.0)\n",
            "Requirement already satisfied: requests<3.0.0,>=2.13.0 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->en_core_web_sm==2.2.5) (2.23.0)\n",
            "Requirement already satisfied: tqdm<5.0.0,>=4.38.0 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->en_core_web_sm==2.2.5) (4.62.3)\n",
            "Requirement already satisfied: numpy>=1.15.0 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->en_core_web_sm==2.2.5) (1.19.5)\n",
            "Requirement already satisfied: preshed<3.1.0,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->en_core_web_sm==2.2.5) (3.0.6)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->en_core_web_sm==2.2.5) (57.4.0)\n",
            "Requirement already satisfied: thinc==7.4.0 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->en_core_web_sm==2.2.5) (7.4.0)\n",
            "Requirement already satisfied: cymem<2.1.0,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->en_core_web_sm==2.2.5) (2.0.6)\n",
            "Requirement already satisfied: murmurhash<1.1.0,>=0.28.0 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->en_core_web_sm==2.2.5) (1.0.6)\n",
            "Requirement already satisfied: plac<1.2.0,>=0.9.6 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->en_core_web_sm==2.2.5) (1.1.3)\n",
            "Requirement already satisfied: blis<0.5.0,>=0.4.0 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->en_core_web_sm==2.2.5) (0.4.1)\n",
            "Requirement already satisfied: catalogue<1.1.0,>=0.0.7 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->en_core_web_sm==2.2.5) (1.0.0)\n",
            "Requirement already satisfied: srsly<1.1.0,>=1.0.2 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->en_core_web_sm==2.2.5) (1.0.5)\n",
            "Requirement already satisfied: importlib-metadata>=0.20 in /usr/local/lib/python3.7/dist-packages (from catalogue<1.1.0,>=0.0.7->spacy>=2.2.2->en_core_web_sm==2.2.5) (4.10.1)\n",
            "Requirement already satisfied: typing-extensions>=3.6.4 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata>=0.20->catalogue<1.1.0,>=0.0.7->spacy>=2.2.2->en_core_web_sm==2.2.5) (3.10.0.2)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata>=0.20->catalogue<1.1.0,>=0.0.7->spacy>=2.2.2->en_core_web_sm==2.2.5) (3.7.0)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.13.0->spacy>=2.2.2->en_core_web_sm==2.2.5) (2021.10.8)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.13.0->spacy>=2.2.2->en_core_web_sm==2.2.5) (2.10)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.13.0->spacy>=2.2.2->en_core_web_sm==2.2.5) (1.24.3)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.13.0->spacy>=2.2.2->en_core_web_sm==2.2.5) (3.0.4)\n",
            "\u001b[38;5;2m✔ Download and installation successful\u001b[0m\n",
            "You can now load the model via spacy.load('en_core_web_sm')\n",
            "\u001b[38;5;2m✔ Linking successful\u001b[0m\n",
            "/usr/local/lib/python3.7/dist-packages/en_core_web_sm -->\n",
            "/usr/local/lib/python3.7/dist-packages/spacy/data/en\n",
            "You can now load the model via spacy.load('en')\n"
          ]
        }
      ],
      "source": [
        "!python -m spacy download en"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZWFJYPDi4hR6",
        "outputId": "a1d453fc-73a7-44e1-e786-38a6e13abc52"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting nest_asyncio==1.3.3\n",
            "  Downloading nest_asyncio-1.3.3-py3-none-any.whl (4.7 kB)\n",
            "Installing collected packages: nest-asyncio\n",
            "  Attempting uninstall: nest-asyncio\n",
            "    Found existing installation: nest-asyncio 1.5.4\n",
            "    Uninstalling nest-asyncio-1.5.4:\n",
            "      Successfully uninstalled nest-asyncio-1.5.4\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",
            "nbclient 0.5.10 requires jupyter-client>=6.1.5, but you have jupyter-client 5.3.5 which is incompatible.\u001b[0m\n",
            "Successfully installed nest-asyncio-1.3.3\n"
          ]
        }
      ],
      "source": [
        "!pip install nest_asyncio==1.3.3"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yCngBlYp4kc_",
        "outputId": "1e866a48-e2ce-40b5-e559-8c47af0b79b2"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "event loop ready\n"
          ]
        }
      ],
      "source": [
        "import os\n",
        "import rasa\n",
        "import nest_asyncio\n",
        "\n",
        "nest_asyncio.apply()\n",
        "\n",
        "print(\"event loop ready\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "zy4H6hWv4l-D"
      },
      "outputs": [],
      "source": [
        "from rasa.cli.scaffold import create_initial_project"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "3UNYbtz-4n2-"
      },
      "outputs": [],
      "source": [
        "project = 'test_project'\n",
        "create_initial_project(project)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AWwGWOIk4q-x",
        "outputId": "edc50d92-8473-484a-b996-9466618b1ec6"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['__pycache__', '__init__.py', 'tests', 'endpoints.yml', 'config.yml', 'credentials.yml', 'actions.py', 'domain.yml', 'data']\n"
          ]
        }
      ],
      "source": [
        "os.chdir(project)\n",
        "print(os.listdir(\".\"))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BFFYeIXW4tFn",
        "outputId": "0bd682a1-30e5-4928-c3f6-111e2ce599e8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "config.yml data/ domain.yml models/\n"
          ]
        }
      ],
      "source": [
        "config = \"config.yml\"\n",
        "training_files = \"data/\"\n",
        "domain = 'domain.yml'\n",
        "output = 'models/'\n",
        "\n",
        "print(config, training_files, domain, output)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NHfynViZ4uBK",
        "outputId": "7eb46b5c-8d0b-46c4-bf04-90828187834d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[94mTraining Core model...\u001b[0m\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processed Story Blocks: 100%|██████████| 5/5 [00:00<00:00, 248.72it/s, # trackers=1]\n",
            "Processed Story Blocks: 100%|██████████| 5/5 [00:00<00:00, 214.63it/s, # trackers=5]\n",
            "Processed Story Blocks: 100%|██████████| 5/5 [00:00<00:00, 127.71it/s, # trackers=20]\n",
            "Processed Story Blocks: 100%|██████████| 5/5 [00:00<00:00, 131.51it/s, # trackers=24]\n",
            "Processed trackers: 100%|██████████| 5/5 [00:00<00:00, 84.31it/s, # actions=16]\n",
            "Processed actions: 16it [00:00, 413.22it/s, # examples=16]\n",
            "Processed trackers: 100%|██████████| 231/231 [00:06<00:00, 38.22it/s, # actions=126]\n",
            "Epochs:   0%|          | 0/100 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/rasa/utils/tensorflow/model_data.py:386: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray\n",
            "  final_data[k].append(np.concatenate(np.array(v)))\n",
            "Epochs: 100%|██████████| 100/100 [00:18<00:00,  5.46it/s, t_loss=0.152, loss=0.080, acc=1.000]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[94mCore model training completed.\u001b[0m\n",
            "\u001b[94mTraining NLU model...\u001b[0m\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\u001b[93m/usr/local/lib/python3.7/dist-packages/rasa/utils/common.py:363: UserWarning: You specified 'DIET' to train entities, but no entities are present in the training data. Skip training of entities.\n",
            "Epochs:   0%|          | 0/100 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/rasa/utils/tensorflow/model_data.py:386: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray\n",
            "  final_data[k].append(np.concatenate(np.array(v)))\n",
            "Epochs: 100%|██████████| 100/100 [00:08<00:00, 11.33it/s, t_loss=1.541, i_loss=0.158, i_acc=1.000]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[94mNLU model training completed.\u001b[0m\n",
            "\u001b[92mYour Rasa model is trained and saved at '/content/test_project/models/20220205-150955.tar.gz'.\u001b[0m\n",
            "models/20220205-150955.tar.gz\n"
          ]
        }
      ],
      "source": [
        "model_path = rasa.train(domain, config, [training_files], output)\n",
        "print(model_path) "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "7Sjxqzot5SUV",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7bc7b66d-fcfe-494f-fca3-9792b4b3c51e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Your bot is ready to talk! Type your messages here or send '/stop'.\n",
            "/stop\n"
          ]
        }
      ],
      "source": [
        "from rasa.jupyter import chat\n",
        "\n",
        "endpoints = 'endpoints.yml'\n",
        "\n",
        "chat(model_path, endpoints)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "MtawRGvP5bbX",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3e66b683-06d5-4c02-c253-33d2a7d447ed"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Overwriting data/nlu.md\n"
          ]
        }
      ],
      "source": [
        "%%writefile data/nlu.md\n",
        "\n",
        "## intent:f_name\n",
        "- my name is [SAIF UDDIN](name)\n",
        "- [RAJ KUMAR](name)\n",
        "- [BALAJI](name)\n",
        "- name is [AKASH MALHOTRA](name)\n",
        "- i am [MUSKAN SHARMA](name)\n",
        "- [KIRAN RAO](name)\n",
        "- [JUHI PAREKH](name)\n",
        "- [ATUL SHARMA](name)\n",
        "\n",
        "## intent:user_id\n",
        "- [saife245](usr_id)\n",
        "- my user id is [raj23](usr_id)\n",
        "- [sam_001](usr_id) \n",
        "- [mus_02](usr_id)\n",
        "- [02_mus](usr_id)\n",
        "- [su_1996](usr_id)\n",
        "\n",
        "## intent:number\n",
        "- my mobile number is [9076543210](mob)\n",
        "- number is [8907654321](mob)\n",
        "- [789065434](mob)\n",
        "- [907654398](mob)\n",
        "- [789654123](mob) is my number\n",
        "\n",
        "## intent:email_id\n",
        "- [sai34@gmail.com](email)\n",
        "- my email id is [shruti45@yahoo.com](email)\n",
        "- [ramy.45@gmail.com](email)\n",
        "- [srk_23@hotmail.com](email)\n",
        "- [sanju09@rediffmail.com](email)\n",
        "\n",
        "## intent:greet\n",
        "- hey\n",
        "- hello\n",
        "- hi\n",
        "- good morning\n",
        "- good evening\n",
        "- hey there\n",
        "\n",
        "## intent:goodbye\n",
        "- bye\n",
        "- goodbye\n",
        "- see you around\n",
        "- see you later\n",
        "\n",
        "## intent:affirm\n",
        "- yes\n",
        "- indeed\n",
        "- of course\n",
        "- that sounds good\n",
        "- correct\n",
        "\n",
        "## intent:deny\n",
        "- no\n",
        "- never\n",
        "- I don't think so\n",
        "- don't like that\n",
        "- no way\n",
        "- not really\n",
        "\n",
        "## intent:mood_great\n",
        "- perfect\n",
        "- very good\n",
        "- great\n",
        "- amazing\n",
        "- wonderful\n",
        "- I am feeling very good\n",
        "- I am great\n",
        "- I'm good\n",
        "\n",
        "## intent:mood_unhappy\n",
        "- sad\n",
        "- very sad\n",
        "- unhappy\n",
        "- bad\n",
        "- very bad\n",
        "- awful\n",
        "- terrible\n",
        "- not very good\n",
        "- extremely sad\n",
        "- so sad\n",
        "\n",
        "## intent:bot_challenge\n",
        "- are you a bot?\n",
        "- are you a human?\n",
        "- am I talking to a bot?\n",
        "- am I talking to a human?\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "6Dcnv5K85cuB",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8b20a523-6e44-45b6-bfa0-5b5bed5a846c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Overwriting domain.yml\n"
          ]
        }
      ],
      "source": [
        "%%writefile domain.yml\n",
        "\n",
        "intents:\n",
        "  - greet\n",
        "  - goodbye\n",
        "  - affirm\n",
        "  - deny\n",
        "  - mood_great\n",
        "  - mood_unhappy\n",
        "  - bot_challenge\n",
        "  - f_name\n",
        "  - user_id\n",
        "  - number\n",
        "  - email_id\n",
        "\n",
        "slots:\n",
        "  name:\n",
        "    type: unfeaturized\n",
        "  usr_id:\n",
        "    type: unfeaturized\n",
        "  mob:\n",
        "    type: unfeaturized\n",
        "  email:\n",
        "    type: unfeaturized\n",
        "\n",
        "forms:\n",
        "  - form_hack\n",
        "\n",
        "actions:\n",
        "  - action_reset_all_slots\n",
        "  \n",
        "responses:\n",
        "  utter_greet:\n",
        "  - text: \"Welcome to the Rasa Hackathon! For Registration Provide necessary Information.\"\n",
        "\n",
        "  utter_ask_name:\n",
        "  - text: \"Enter your Name(in caps): \"\n",
        "\n",
        "  utter_ask_usr_id:\n",
        "  - text: \"Enter Unique User I'd for yourself: \"\n",
        "\n",
        "  utter_ask_mob:\n",
        "  - text: \"Enter your Mobile number: \"\n",
        "\n",
        "  utter_ask_email:\n",
        "  - text: \" Enter Your email I'd: \"\n",
        "\n",
        "  utter_end_response:\n",
        "  - text: \"See you in Hackathon...\"\n",
        "\n",
        "  utter_cheer_up:\n",
        "  - text: \"Here is something to cheer you up:\"\n",
        "    image: \"https://i.imgur.com/nGF1K8f.jpg\"\n",
        "\n",
        "  utter_did_that_help:\n",
        "  - text: \"Did that help you?\"\n",
        "\n",
        "  utter_happy:\n",
        "  - text: \"Great, carry on!\"\n",
        "\n",
        "  utter_goodbye:\n",
        "  - text: \"Bye\"\n",
        "\n",
        "  utter_iamabot:\n",
        "  - text: \"I am a bot, powered by Rasa.\"\n",
        "\n",
        "entities:\n",
        "  - name\n",
        "  - usr_id\n",
        "  - mob\n",
        "  - email\n",
        "\n",
        "session_config:\n",
        "  session_expiration_time: 60\n",
        "  carry_over_slots_to_new_session: true\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "id": "LpBm98815gIU",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4d46a9b3-8392-4259-aeec-dfead6ab4779"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Overwriting data/stories.md\n"
          ]
        }
      ],
      "source": [
        "%%writefile data/stories.md\n",
        "    \n",
        "## hackathon\n",
        "* greet\n",
        "  - utter_greet\n",
        "  - action_reset_all_slots\n",
        "  - form_hack\n",
        "  - form{\"name\": \"form_hack\"}\n",
        "  - form{\"name\": null}\n",
        "  - utter_end_response\n",
        "  \n",
        "## happy path\n",
        "* greet\n",
        "  - utter_greet\n",
        "* mood_great\n",
        "  - utter_happy\n",
        "\n",
        "## sad path 1\n",
        "* greet\n",
        "  - utter_greet\n",
        "* mood_unhappy\n",
        "  - utter_cheer_up\n",
        "  - utter_did_that_help\n",
        "* affirm\n",
        "  - utter_happy\n",
        "\n",
        "## sad path 2\n",
        "* greet\n",
        "  - utter_greet\n",
        "* mood_unhappy\n",
        "  - utter_cheer_up\n",
        "  - utter_did_that_help\n",
        "* deny\n",
        "  - utter_goodbye\n",
        "\n",
        "## say goodbye\n",
        "* goodbye\n",
        "  - utter_goodbye\n",
        "\n",
        "## bot challenge\n",
        "* bot_challenge\n",
        "  - utter_iamabot\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "id": "H0pzjKaMRxSB",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "02f0d613-25b9-4932-a96c-bde39182a6e0"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Overwriting actions.py\n"
          ]
        }
      ],
      "source": [
        "%%writefile actions.py\n",
        "# This files contains your custom actions which can be used to run\n",
        "# custom Python code.\n",
        "#\n",
        "# See this guide on how to implement these action:\n",
        "# https://rasa.com/docs/rasa/core/actions/#custom-actions/\n",
        "\n",
        "\n",
        "# This is a simple example for a custom action which utters \"Hello World!\"\n",
        "import os\n",
        "import pandas as pd\n",
        "\n",
        "from typing import Any, Text, Dict, List\n",
        "from rasa_sdk.forms import FormAction\n",
        "from rasa_sdk import Action, Tracker\n",
        "from rasa_sdk.executor import CollectingDispatcher\n",
        "from rasa_sdk.events import AllSlotsReset\n",
        "\n",
        "\n",
        "class ActionResetAllSlots(Action):\n",
        "\n",
        "    def name(self) -> Text:\n",
        "        return \"action_reset_all_slots\"\n",
        "\n",
        "    def run(self, dispatcher: CollectingDispatcher,\n",
        "            tracker: Tracker,\n",
        "            domain: Dict[Text, Any]):\n",
        "\n",
        "        return [AllSlotsReset()]\n",
        "\n",
        "\n",
        "class ActionHackathon(FormAction):\n",
        "\n",
        "    def name(self) -> Text:\n",
        "        return \"form_hack\"\n",
        "\n",
        "    @staticmethod\n",
        "    def required_slots(tracker: Tracker) -> List[Text]:\n",
        "\n",
        "      return ['name', 'usr_id', 'mob', 'email']\n",
        "\n",
        "    def submit(self, dispatcher: CollectingDispatcher,\n",
        "            tracker: Tracker,\n",
        "            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:\n",
        "\n",
        "        name = tracker.get_slot(\"name\")\n",
        "        usr_id = tracker.get_slot(\"usr_id\")\n",
        "        mob = tracker.get_slot(\"mob\")\n",
        "        email = tracker.get_slot(\"email\")\n",
        "\n",
        "        if not os.path.isfile('participant.csv'):\n",
        "          df = pd.DataFrame(columns=(\"Name\", \"User Id\", \"Mobile\", \"Email\"))\n",
        "          df.to_csv('participant.csv', index=False)\n",
        "\n",
        "        data = pd.read_csv(\"participant.csv\")\n",
        "\n",
        "        if usr_id in data[\"User Id\"].values:\n",
        "          mess1 = \"User Id is already in Database.\"\n",
        "          mess2 = \"EEither you already registered for Rasa Hackathon.\"\n",
        "          mess3 = \"Or try with different user id.\"\n",
        "          message = mess1 + '\\n' + mess2 + '\\n' + mess3\n",
        "        else:\n",
        "          details = {\"Name\": [name], \"User Id\": [usr_id], \"Mobile\": [mob], \"Email\": [email]}\n",
        "          df = pd.DataFrame(details)\n",
        "          df.to_csv(\"participant.csv\", mode='a', index=False, header=False)\n",
        "\n",
        "          mess1 = \"Registeration Successful for Rasa Hackathon!!!\"\n",
        "          mess2 = \"Thanks for your information! You well get the further details of Hackathon on email.\"\n",
        "          message = mess1 + '\\n' + mess2\n",
        "\n",
        "        dispatcher.utter_message(text=message)\n",
        "\n",
        "        return []"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "id": "7WjYzcBNZT4W",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3ea4c7fe-d533-44fd-9716-e1b984384bfc"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processed Story Blocks: 100%|██████████| 6/6 [00:00<00:00, 289.81it/s, # trackers=1]\n",
            "Processed Story Blocks: 100%|██████████| 6/6 [00:00<00:00, 182.25it/s, # trackers=6]\n",
            "Processed Story Blocks:   0%|          | 0/6 [00:00<?, ?it/s, # trackers=24]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[94mTraining Core model...\u001b[0m\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processed Story Blocks: 100%|██████████| 6/6 [00:00<00:00, 93.46it/s, # trackers=24]\n",
            "Processed Story Blocks: 100%|██████████| 6/6 [00:00<00:00, 93.44it/s, # trackers=17]\n",
            "Processed trackers: 100%|██████████| 6/6 [00:00<00:00, 85.83it/s, # actions=20]\n",
            "Processed actions: 20it [00:00, 414.94it/s, # examples=18]\n",
            "Processed trackers: 100%|██████████| 302/302 [00:08<00:00, 36.93it/s, # actions=182]\n",
            "Epochs:   0%|          | 0/100 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/rasa/utils/tensorflow/model_data.py:386: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray\n",
            "  final_data[k].append(np.concatenate(np.array(v)))\n",
            "Epochs: 100%|██████████| 100/100 [00:25<00:00,  3.99it/s, t_loss=1.763, loss=1.664, acc=0.916]\n",
            "Processed trackers: 100%|██████████| 6/6 [00:00<00:00, 85.20it/s, # actions=20]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[94mCore model training completed.\u001b[0m\n",
            "\u001b[94mTraining NLU model...\u001b[0m\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/rasa/nlu/classifiers/diet_classifier.py:595: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray\n",
            "  for tag_name, tag_ids in tag_name_to_tag_ids.items()\n",
            "Epochs:   0%|          | 0/100 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/rasa/utils/tensorflow/model_data.py:386: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray\n",
            "  final_data[k].append(np.concatenate(np.array(v)))\n",
            "Epochs: 100%|██████████| 100/100 [00:12<00:00,  7.84it/s, t_loss=2.027, i_loss=0.223, entity_loss=0.029, i_acc=1.000, entity_f1=0.921]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[94mNLU model training completed.\u001b[0m\n",
            "\u001b[92mYour Rasa model is trained and saved at '/content/test_project/models/20220205-151519.tar.gz'.\u001b[0m\n",
            "models/20220205-151519.tar.gz\n"
          ]
        }
      ],
      "source": [
        "model_path = rasa.train(domain, config, [training_files], output)\n",
        "print(model_path)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!rasa run actions & rasa shell"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gAWqM3NlXCvc",
        "outputId": "04ead0f9-d049-45a3-de96-66edce220e39"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2022-02-05 15:31:23 \u001b[1;30mINFO    \u001b[0m \u001b[34mrasa_sdk.endpoint\u001b[0m  - Starting action endpoint server...\n",
            "2022-02-05 15:31:23 \u001b[1;30mINFO    \u001b[0m \u001b[34mrasa_sdk.executor\u001b[0m  - Registered function for 'action_reset_all_slots'.\n",
            "2022-02-05 15:31:23 \u001b[1;30mINFO    \u001b[0m \u001b[34mrasa_sdk.executor\u001b[0m  - Registered function for 'form_hack'.\n",
            "2022-02-05 15:31:23 \u001b[1;30mINFO    \u001b[0m \u001b[34mrasa_sdk.endpoint\u001b[0m  - Action endpoint is up and running on http://localhost:5055\n",
            "2022-02-05 15:31:23 \u001b[1;30mINFO    \u001b[0m \u001b[34mroot\u001b[0m  - Generating grammar tables from /usr/lib/python3.7/lib2to3/Grammar.txt\n",
            "2022-02-05 15:31:24 \u001b[1;30mINFO    \u001b[0m \u001b[34mroot\u001b[0m  - Generating grammar tables from /usr/lib/python3.7/lib2to3/PatternGrammar.txt\n",
            "2022-02-05 15:31:24 \u001b[1;30mINFO    \u001b[0m \u001b[34mroot\u001b[0m  - Connecting to channel 'cmdline' which was specified by the '--connector' argument. Any other channels will be ignored. To connect to all given channels, omit the '--connector' argument.\n",
            "2022-02-05 15:31:24 \u001b[1;30mINFO    \u001b[0m \u001b[34mroot\u001b[0m  - Starting Rasa server on http://localhost:5005\n",
            "2022-02-05 15:31:34 \u001b[1;30mINFO    \u001b[0m \u001b[34mroot\u001b[0m  - Rasa server is up and running.\n",
            "\u001b[92mBot loaded. Type a message and press enter (use '/stop' to exit): \u001b[0m\n",
            "\u001b[15C\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[15D\u001b[J\u001b[0m\u001b[?7h\u001b[?2004l\u001b[?1lWARNING: your terminal doesn't support cursor position requests (CPR).\n",
            "\u001b[0m\n",
            "\u001b[J\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[?2004l\u001b[94mWelcome to the Rasa Hackathon! For Registration Provide necessary Information.\u001b[0m\n",
            "\u001b[94mEnter your Name(in caps):\u001b[0m\n",
            "\u001b[15C\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[15D\u001b[J\u001b[0m\u001b[?7h\u001b[?2004l\u001b[?1lWARNING: your terminal doesn't support cursor position requests (CPR).\n",
            "\u001b[0m\n",
            "\u001b[J\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[?2004l\u001b[94mEnter Unique User I'd for yourself:\u001b[0m\n",
            "\u001b[15C\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[15D\u001b[J\u001b[0m\u001b[?7h\u001b[?2004l\u001b[?1lWARNING: your terminal doesn't support cursor position requests (CPR).\n",
            "\u001b[0m\n",
            "\u001b[J\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[?2004l\u001b[94mEnter your Mobile number:\u001b[0m\n",
            "\u001b[15C\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[15D\u001b[J\u001b[0m\u001b[?7h\u001b[?2004l\u001b[?1lWARNING: your terminal doesn't support cursor position requests (CPR).\n",
            "\u001b[0m\n",
            "\u001b[J\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[?2004l\u001b[94mEnter Your email I'd:\u001b[0m\n",
            "\u001b[15C\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[15D\u001b[J\u001b[0m\u001b[?7h\u001b[?2004l\u001b[?1lWARNING: your terminal doesn't support cursor position requests (CPR).\n",
            "\u001b[0m\n",
            "\u001b[J\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[?2004l\u001b[94mRegisteration Successful for Rasa Hackathon!!!\n",
            "Thanks for your information! You well get the further details of Hackathon on email.\u001b[0m\n",
            "\u001b[94mSee you in Hackathon...\u001b[0m\n",
            "\u001b[15C\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[15D\u001b[J\u001b[0m\u001b[?7h\u001b[?2004l\u001b[?1lWARNING: your terminal doesn't support cursor position requests (CPR).\n",
            "\u001b[0m\n",
            "\u001b[J\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[?2004l\u001b[94mWelcome to the Rasa Hackathon! For Registration Provide necessary Information.\u001b[0m\n",
            "\u001b[94mEnter your Name(in caps):\u001b[0m\n",
            "\u001b[15C\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[15D\u001b[J\u001b[0m\u001b[?7h\u001b[?2004l\u001b[?1lWARNING: your terminal doesn't support cursor position requests (CPR).\n",
            "\u001b[0m\n",
            "\u001b[J\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[?2004l\u001b[94mEnter Unique User I'd for yourself:\u001b[0m\n",
            "\u001b[15C\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[15D\u001b[J\u001b[0m\u001b[?7h\u001b[?2004l\u001b[?1lWARNING: your terminal doesn't support cursor position requests (CPR).\n",
            "\u001b[0m\n",
            "\u001b[J\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[?2004l\u001b[94mEnter your Mobile number:\u001b[0m\n",
            "\u001b[15C\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[15D\u001b[J\u001b[0m\u001b[?7h\u001b[?2004l\u001b[?1lWARNING: your terminal doesn't support cursor position requests (CPR).\n",
            "\u001b[0m\n",
            "\u001b[J\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[?2004l\u001b[94mEnter Your email I'd:\u001b[0m\n",
            "\u001b[15C\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[15D\u001b[J\u001b[0m\u001b[?7h\u001b[?2004l\u001b[?1lWARNING: your terminal doesn't support cursor position requests (CPR).\n",
            "\u001b[0m\n",
            "\u001b[J\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[?2004l\u001b[94mRegisteration Successful for Rasa Hackathon!!!\n",
            "Thanks for your information! You well get the further details of Hackathon on email.\u001b[0m\n",
            "\u001b[94mSee you in Hackathon...\u001b[0m\n",
            "\u001b[15C\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[15D\u001b[J\u001b[0m\u001b[?7h\u001b[?2004l\u001b[?1lWARNING: your terminal doesn't support cursor position requests (CPR).\n",
            "\u001b[0m\n",
            "\u001b[J\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[?2004l\u001b[94mWelcome to the Rasa Hackathon! For Registration Provide necessary Information.\u001b[0m\n",
            "\u001b[94mEnter your Name(in caps):\u001b[0m\n",
            "\u001b[15C\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[15D\u001b[J\u001b[0m\u001b[?7h\u001b[?2004l\u001b[?1lWARNING: your terminal doesn't support cursor position requests (CPR).\n",
            "\u001b[0m\n",
            "\u001b[J\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[?2004l\u001b[94mEnter Unique User I'd for yourself:\u001b[0m\n",
            "\u001b[15C\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[15D\u001b[J\u001b[0m\u001b[?7h\u001b[?2004l\u001b[?1lWARNING: your terminal doesn't support cursor position requests (CPR).\n",
            "\u001b[0m\n",
            "\u001b[J\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[?2004l\u001b[94mEnter your Mobile number:\u001b[0m\n",
            "\u001b[15C\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[15D\u001b[J\u001b[0m\u001b[?7h\u001b[?2004l\u001b[?1lWARNING: your terminal doesn't support cursor position requests (CPR).\n",
            "\u001b[0m\n",
            "\u001b[J\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[?2004l\u001b[94mEnter Your email I'd:\u001b[0m\n",
            "\u001b[15C\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[15D\u001b[J\u001b[0m\u001b[?7h\u001b[?2004l\u001b[?1lWARNING: your terminal doesn't support cursor position requests (CPR).\n",
            "\u001b[0m\n",
            "\u001b[J\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[?2004l\u001b[94mRegisteration Successful for Rasa Hackathon!!!\n",
            "Thanks for your information! You well get the further details of Hackathon on email.\u001b[0m\n",
            "\u001b[94mSee you in Hackathon...\u001b[0m\n",
            "\u001b[15C\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[15D\u001b[J\u001b[0m\u001b[?7h\u001b[?2004l\u001b[?1lWARNING: your terminal doesn't support cursor position requests (CPR).\n",
            "\u001b[0m\n",
            "\u001b[J\u001b[?7h\u001b[0m\u001b[?12l\u001b[?25h\u001b[?2004l2022-02-05 15:37:40 \u001b[1;30mINFO    \u001b[0m \u001b[34mroot\u001b[0m  - Killing Sanic server now.\n"
          ]
        }
      ]
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [],
      "name": "Rasa_Form.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "nbformat": 4,
  "nbformat_minor": 0
}