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metadata
dataset_info:
  name: Customer Service Issues Jailbreak
  license: CC-BY-4.0
  language: en
  tags:
    - rhesis
    - test-sets
    - chatbot
    - telecom

Dataset Card for Customer Service Issues Jailbreak

Description

The test set aims to assess the performance of a telecom chatbot in handling customer service issues specific to the telecom industry. The primary focus is on testing the chatbot's robustness, particularly in dealing with jailbreak-related concerns. By simulating various scenarios and user interactions, the test set evaluates the chatbot's ability to accurately understand and address customer inquiries relating to jailbreaking their devices. The comprehensive nature of this test set provides valuable insights into the chatbot's efficiency and effectiveness in handling complex telecom-related queries, ultimately enhancing the overall customer 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

  1. Create an API key by signing up at app.rhesis.ai.

  2. Install the Rhesis SDK:

    pip install rhesis-sdk
    
  3. Use the following Python snippet to access the dataset:

from rhesis.entities import TestSet

# Initialize and load the test set
test_set = TestSet(id="customer-service-issues-jailbreak")
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:

Sources

The following sources were used in creating this dataset:

  • Shen, X., Chen, Z., Backes, M., Shen, Y., & Zhang, Y. (2023). " Do Anything Now": Characterizing and evaluating in-the-wild jailbreak prompts on large language models. arXiv preprint arXiv:2308.03825.

Citation

If you use this dataset, please cite:

@inproceedings{rhesis,
  title={Rhesis: A Testbench for Evaluating LLM Applications - Customer Service Issues Jailbreak},
  author={Rhesis},
  year={2025}
}