License Apache 2.0 Python 3.6 tensorflow 1.4

Sequence-To-Sequence Dialogue Bot for goal-oriented task

Dialogue agent is able to handle multi-domain data. The model is end-to-end differentiable and does not need to explicitly model dialogue state or belief trackers.

We also used a new Stanford NLP Group released dataset of 3,031 dialogues [2] that are grounded through underlying knowledge bases and span three distinct tasks in the in-car personal assistant space: calendar scheduling, weather information retrieval, and point-of-interest navigation.

Here is a simple example of interaction with a trained dialogue bot (can be downloaded with deeppavlov/download.py):

x_text:: Where's the nearest parking garage?
>> the nearest is dish parking at dish_parking_address. is that okay?
x_text:: Yes, please set directions via a route that avoids all heavy traffic if possible.
>> it looks like there is a road block being reported on the route but i will still find the quickest route to dish_parking_address.
x_text:: Thanks so much for your help.
>> you're welcome. have a good day. end_of_dialogue

x_text:: Will it be warm in Camarillo over the next 2 days?
>> no, it's not gon na be warm in camarillo over the next 2 days
x_text:: Thank you car!
>> you're welcome! end_of_dialogue

x_text:: What day is my lab appointment, and who all will be there?
>> your lab appointment is on lab_appointment_date at lab_appointment_time with lab_appointment_party.
x_text:: Thanks!
>> you're welcome.

Usage

Requirements

To use a seq2seq_go_bot model you should have a pretrained goal-oriented bot model

Config parameters:

Usage example

from deeppavlov.core.commands.infer import build_model_from_config
from deeppavlov.core.common.file import read_json

CONFIG_PATH = 'path/to/config.json'
model = build_model_from_config(read_json(CONFIG_PATH))

utterance = ""
while utterance != 'exit':
    print(">> " + model([utterance])[0])
    utterance = input(':: ')
cd deeppavlov
python3 deep.py interact path/to/config.json

References

[1] A New Multi-Turn, Multi-Domain, Task-Oriented Dialogue Dataset

[2] Mihail Eric, Lakshmi Krishnan, Francois Charette, and Christopher D. Manning, Key-Value Retrieval Networks for Task-Oriented Dialogue – 2017