DeepPavlov

• DeepPavlov is an open source framework for

  • chatbots and virtual assistants development

• DeepPavlov has comprehensive and flexible tools that let developers and NLP researchers:

  • create production ready conversational skills

  • complex multi-skill conversational assistants

  • Developed on top of the open source machine learning frameworks TensorFlow and Keras.

• Examples

Training the bot

• Installing

!pip install deeppavlov
!python -m deeppavlov install gobot_dstc2_minimal

• A policy module of the bot decides what action should be taken in the current dialogue state.
• The policy in our bot is implemented as a recurrent neural network (recurrency over user utterances) followed by a dense layer with softmax function on top.

Training data

[
  [
    {
      "speaker": 1,
      "text": "hi"
    },
    {
      "speaker": 2,
      "text": "Hello, what is the weather today?",
      "act": "welcome_msg"
    },
    {
      "speaker": 1,
      "text": "Quite sunny outside"
    },
    {
      "speaker": 2,
      "text": "Then you should cycle!",
      "act": "suggest_cycling"
    },
    {
      "speaker": 1,
      "text": "Thanks! Great idea"
    },
    {
      "speaker": 2,
      "text": "You are welcome! Bye!",
      "act": "good_bye"
    }
  ],
  [
    {
      "speaker": 1,
      "text": "hey, bot"
    },
    {
      "speaker": 2,
      "text": "Hello, what is the weather today?",
      "act": "welcome_msg"
    },
    {
      "speaker": 1,
      "text": "raining a lot"
    },
    {
      "speaker": 2,
      "text": "Then you should try hot chinese tea!",
      "act": "suggest_tea"
    },
    {
      "speaker": 1,
      "text": "nice. thank you"
    },
    {
      "speaker": 2,
      "text": "You are welcome! Bye!",
      "act": "good_bye"
    }
  ],
  [
    {
      "speaker": 1,
      "text": "good morning you!"
    },
    {
      "speaker": 2,
      "text": "Hello, what is the weather today?",
      "act": "welcome_msg"
    },
    {
      "speaker": 1,
      "text": "hot and a little bit cloudy i guess"
    },
    {
      "speaker": 2,
      "text": "Then you should cycle!",
      "act": "suggest_cycling"
    },
    {
      "speaker": 1,
      "text": "no, i dont have a bike"
    },
    {
      "speaker": 2,
      "text": "That's a pity! Next time maybe. Have a good day!",
      "act": "bad_bye"
    }
  ],
  [
    {
      "speaker": 1,
      "text": "hello beautiful!"
    },
    {
      "speaker": 2,
      "text": "Hello, what is the weather today?",
      "act": "welcome_msg"
    },
    {
      "speaker": 1,
      "text": "too much snow, dont want to go out"
    },
    {
      "speaker": 2,
      "text": "Then you should try hot chinese tea!",
      "act": "suggest_tea"
    },
    {
      "speaker": 1,
      "text": "no i am not into tea"
    },
    {
      "speaker": 2,
      "text": "That's a pity! Next time maybe. Have a good day!",
      "act": "bad_bye"
    }
  ],
  [
    {
      "speaker": 1,
      "text": "good evening"
    },
    {
      "speaker": 2,
      "text": "Hello, what is the weather today?",
      "act": "welcome_msg"
    },
    {
      "speaker": 1,
      "text": "mainly cloudy and gray"
    },
    {
      "speaker": 2,
      "text": "Then you should try hot chinese tea!",
      "act": "suggest_tea"
    },
    {
      "speaker": 1,
      "text": "that sounds good"
    },
    {
      "speaker": 2,
      "text": "You are welcome! Bye!",
      "act": "good_bye"
    }
  ],
  [
    {
      "speaker": 1,
      "text": "hey"
    },
    {
      "speaker": 2,
      "text": "Hello, what is the weather today?",
      "act": "welcome_msg"
    },
    {
      "speaker": 1,
      "text": "very dark and murky"
    },
    {
      "speaker": 2,
      "text": "Then you should try hot chinese tea!",
      "act": "suggest_tea"
    },
    {
      "speaker": 1,
      "text": "tea is not funny"
    },
    {
      "speaker": 2,
      "text": "That's a pity! Next time maybe. Have a good day!",
      "act": "bad_bye"
    }
  ],
  [
    {
      "speaker": 1,
      "text": "how you doing"
    },
    {
      "speaker": 2,
      "text": "Hello, what is the weather today?",
      "act": "welcome_msg"
    },
    {
      "speaker": 1,
      "text": "the weather is gorgeous!"
    },
    {
      "speaker": 2,
      "text": "Then you should cycle!",
      "act": "suggest_cycling"
    },
    {
      "speaker": 1,
      "text": "maybe you are right, i'll try that"
    },
    {
      "speaker": 2,
      "text": "You are welcome! Bye!",
      "act": "good_bye"
    }
  ],
  [
    {
      "speaker": 1,
      "text": "hii"
    },
    {
      "speaker": 2,
      "text": "Hello, what is the weather today?",
      "act": "welcome_msg"
    },
    {
      "speaker": 1,
      "text": "nice weather really"
    },
    {
      "speaker": 2,
      "text": "Then you should cycle!",
      "act": "suggest_cycling"
    },
    {
      "speaker": 1,
      "text": "i dont wanna do such stuff"
    },
    {
      "speaker": 2,
      "text": "That's a pity! Next time maybe. Have a good day!",
      "act": "bad_bye"
    }
  ]
]

Training the model

from deeppavlov import train_model

gobot_config['train']['batch_size'] = 4 # set batch size
gobot_config['train']['max_batches'] = 30 # maximum number of training batches
gobot_config['train']['val_every_n_batches'] = 30 # evaluate on full 'valid' split every 30 epochs
gobot_config['train']['log_every_n_batches'] = 5 # evaluate on full 'train' split every 5 batches

train_model(gobot_config)

Building the model

from deeppavlov import build_model
bot = build_model(gobot_config

Interacting with the bot

bot([[{"text": "good evening, bot"}]])

• response

[['Hello, what is the weather today?']]

bot([[{"text": "the weather is clooudy and gloooomy"}]])

• response

[['Then you should cycle!']]

Resetting the bot

bot.reset()

References

• DEEPPAVLOV
• How to build ‘Hello World!’ bot with DeepPavlov in 4 steps
• GloVe - Global Vectors for Word Representation