TUS is a domain-independent user simulator with transformers for task-oriented dialogue systems. It is based on the ConvLab-2 framework. Therefore, you should follow their instruction to install the package.

Introduction

Our model is a domain-independent user simulator, which means it is not based on any domain-dependent freatures and the output representation is also domain-independent. Therefore, it can easily adapt to a new domain, without additional feature engineering and model retraining.

The code of TUS is in convlab2/policy/tus and a rule-based DST of user is also created in convlab2/dst/rule/multiwoz/dst.py based on the rule-based DST in convlab2/dst/rule/multiwoz/dst.py.

How to run the model

Train the user simulator

python3 convlab2/policy/tus/multiwoz/train.py --user_config convlab2/policy/tus/multiwoz/exp/default.json

One default configuration is placed in convlab2/policy/tus/multiwoz/exp/default.json. They can be modified based on your requirements. For example, the output directory can be specified in the configuration (model_dir).

Train a dialogue policy with TUS

You can use it as a normal user simulator by PipelineAgent. For example,

import json
from convlab2.dialog_agent.agent import PipelineAgent
from convlab2.dst.rule.multiwoz.usr_dst import UserRuleDST
from convlab2.policy.tus.multiwoz.TUS import UserPolicy

user_config_file = "convlab2/policy/tus/multiwoz/exp/default.json"
dst_usr = UserRuleDST()
user_config = json.load(open(user_config_file))
policy_usr = UserPolicy(user_config)
simulator = PipelineAgent(None, dst_usr, policy_usr, None, 'user')

License

Apache License 2.0