This project aims to provide a solution for quantitatively estimating the damage caused by "hallucinations" in large language models. It implements an insurance mechanism that afford redress for the damage caused by hallucinations, helping users to address this phenomenon effectively.

• Quantitative estimation of hallucination-induced damage
• Compensation for hallucination-induced damage
• Easy integration with large language models
• User-friendly interface for managing insurance claims

Please follow the instructions here to use it.

Step 1: Call interface (https://mock.apifox.com/m1/3993944-0-default/get_public_key) to obtain the public key

Step 2: Perform RSA calculation based on public key and take a significant bit every 2 bits. Don't worry about data security, as no one can access your real content after doing so, so your data is secure.

Step 3: Use the result of the second step as the body of HTTP to call interface ( https://mock.apifox.com/m1/3993944-0-default/purchase_insurance_for_content) to insure the content generated by GPT

Step 3: Call interface (https://mock.apifox.com/m1/3993944-0-default/claimant) to claim compensation

Our insurance mechanism is designed to identify and measure the impact of hallucinations in language models. It uses advanced algorithms to analyze the output of the models, detect hallucinations, and estimate their potential damage.

By contributing to this project, you can help improve the reliability of large language models and make a positive impact in addressing the hallucinations phenomenon. Your contributions can help develop more effective insurance mechanisms and compensation systems.

This project is licensed under the MIT License. Please see the license file for more information.

For any questions or feedback, please contact us at [email protected].