AirDialogue

AirDialogue is a benchmark dataset for goal-oriented dialogue generation research. This python library contains a collection of tookits that come with the dataset.

AirDialogue paper
AirDialogue dataset
Reference implementation: AirDialogue Model

Prerequisites

General

python (verified on 2.7.16)
wget

Python Packages

tensorflow (tested on 1.14.0)
tqdm
nltk
flask (for visualization)

Install

To install the pre-build version from pip, use

pip install airdialogue

To install the bleeding edge from github, use

python setup.py install

Quick Start

Scoring

The official scoring function evaluates the predictive results for a trained model and compare it to the AirDialogue dataset.

airdialogue score --true_data PATH_TO_DATA_FILE --true_kb PATH_TO_KB_FILE

Context Generation

Context generator generates a valid context-action pair without conversatoin history.

airdialogue contextgen \
    --output_data PATH_TO_OUTPUT_DATA_FILE \
    --output_kb PATH_TO_OUTPUT_KB_FILE \
    --num_samples 100

Preprocessing

AirDialogue proprocess tookie tokenizes dialogue. Preprocess on AirDialogue data requires 50GB of ram to work. Parameter job_type is a set of 5 bits separted by |, which reqpresents train|eval|infer|sp-train|sp-eval. Parameter input_type can be either context for context only data or dialogue for dialogue data with full history.

airdialogue prepro \
  --data_file PATH_TO_DATA_FILE \
  --kb_file PATH_TO_KB_FILE \
  --output_dir "./data/airdialogue/" \
  --output_prefix 'train' --job_type '0|0|0|1|0' --input_type context

Simulator

Simulator is built on top of context generator that provides not only a context-action pair but also a full conversation history generated by two templated chatbot agents.

airdialogue sim \
    --output_data PATH_TO_OUTPUT_DATA_FILE \
    --output_kb PATH_TO_OUTPUT_KB_FILE \
    --num_samples 100

Visualization

Visualization tool displays the content of the raw json file.

airdialogue vis --data_path ./data/airdialogue/json/

JACKHAHA363/airdialogue