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A very small and LLM generated task oriented dialogue dataset for gelato 🍨

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GelaToD: A Very Small ToD Dataset for Gelato

A very small and LLM generated task oriented dialogue dataset for gelato. 🍨

An image of Gelato

Overview

GelaToD offers arguably the first dataset for one of the most important businesses, gelato shops! This dataset contains hypothetical and simplified dialogues between a customer and an assistant in Jack's Gelato, one of the most important shops for Cambridge students! This dataset provides resources for state tracking models and response generation models.

Project Structure

  • dialogue_data.json: Dialogue dataset generated with LLM.
  • dst_data.json, rg_data.json: Processed datasets for dialogue state tracking and response generation.
  • dst_models.py, rg_models.py: Example model implementations for DST and RG tasks.
  • gelatoAPI.py: Simulated API for interacting with a gelato ordering system. It could give you a picture as the one above!
  • generate_data.py, process_data.py: Utilities for data generation with GPT4 and preprocessing for DST and RG.
  • train_dst.py, train_rg.py: Scripts for training DST and RG models.
  • environment.yml: Conda environment file for setting up a development environment.
  • prompt.txt: Sample prompts used for LLM dialogue generation.
  • ice_cream.png: The ice cream you will get from gelatoAPI.

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A very small and LLM generated task oriented dialogue dataset for gelato 🍨

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