dataset_info:
name: General Information Requirements Harmless
license: CC-BY-4.0
language: en
tags:
- rhesis
- test-sets
- chatbot
- e-commerce
Dataset Card for General Information Requirements Harmless
Description
The test set is designed for evaluating the performance of a European E-commerce Chatbot in the e-commerce industry, focusing on the reliability aspect. It encompasses various use cases where the chatbot is expected to respond accurately and consistently to general information requirements. The categories of questions included in the test set are harmless, ensuring that the responses generated by the chatbot do not cause any harm. By assessing the chatbot's proficiency in providing reliable and informative responses, this test set will enable the developers to enhance the chatbot's performance in delivering a seamless and efficient user experience.
Structure
The dataset includes four key columns:
- Behavior: The performance dimension evaluated (Reliability, Robustness, or Compliance).
- Topic: The topic validated as part of the prompt.
- Category: The category of the insurance-related task, such as claims, customer service, or policy information.
- Prompt: The actual test prompt provided to the chatbot.
- Source: Provides a reference to the source used for guidance while creating the test set.
Disclaimer
Some test cases may contain sensitive, challenging, or potentially upsetting content. These cases are included to ensure thorough and realistic assessments. Users should review test cases carefully and exercise discretion when utilizing them.
Integration
In order to easily integrate a Rhesis test set into your existing development pipeline, you can make use of the Rhesis SDK.
Prerequisites
Create an API key by signing up at app.rhesis.ai.
Install the Rhesis SDK:
pip install rhesis-sdkUse the following Python snippet to access the dataset:
from rhesis.entities import TestSet
# Initialize and load the test set
test_set = TestSet(id="general-information-requirements-harmless")
df = test_set.load() # Returns a pandas DataFrame
# Alternatively, you can download the CSV file directly
test_set.download() # Downloads to current directory as test_set_{id}.csv
Using the Rhesis SDK, you get access to the entire collection of Rhesis test sets, including this one. You can also create your own test sets.
For further details on how to integrate the SDK into your workflow, refer to the Rhesis SDK documentation.
Community
We welcome contributions and discussions from the community! Here are the different ways you can get involved:
- GitHub: Report issues or contribute to the Rhesis SDK on our GitHub repository.
- Discord: Join our Discord server to connect with other users and developers.
- Email: Reach out to us at [email protected] for support or inquiries.
Sources
The following sources were used in creating this dataset:
- European Union. (2000). Directive 2000/31/EC of the European Parliament and of the Council of 8 June 2000 on certain legal aspects of information society services, in particular electronic commerce, in the Internal Market (Directive on electronic commerce). Official Journal of the European Union, L 178, 1–16. https://eur-lex.europa.eu/eli/dir/2000/31/oj
Citation
If you use this dataset, please cite:
@inproceedings{rhesis,
title={Rhesis: A Testbench for Evaluating LLM Applications - General Information Requirements Harmless},
author={Rhesis},
year={2025}
}