mirror of
https://github.com/velocitatem/raccoon.git
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60 lines
2.3 KiB
Markdown
60 lines
2.3 KiB
Markdown
<table style="border-collapse: collapse; border: none; margin: auto;">
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<tr>
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<td style="border: none;"><img src="./logo1.png" alt="logo"></td>
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<td style="border: none; vertical-align: middle;"><h1>Raccoon</h1></td>
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</tr>
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</table>
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Quick links:
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+ [Examples](./examples/README.md)
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+ [Splendidbing](./splendidbing.md)
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---
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Using LLMs for a project is great, but not if it ends up costing you a lot because a malicious prompt gets in.
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# Prompt Stress-Test
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Are you concerned about the security of your AI-powered application or model? Worried that it might be vulnerable to attacks such as cross-site scripting? If so, the Prompt Stress-Test is just what you need!
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## What is the Prompt Stress-Test?
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The Prompt Stress-Test is a tool designed to evaluate prompts for AI models and applications. By subjecting your prompts to rigorous testing, it helps you identify potential vulnerabilities and prevent attacks.
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### Prevention 🚧
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The best way to prevent cross-site scripting attacks is by using an allow list of acceptable input types. The Prompt Stress-Test uses this same approach to ensure that all inputs are safe and secure.
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Other ways to create good prompts include understanding prompt design principles which can be found in our [Prompt Engineering Guide](https://github.com/dair-ai/Prompt-Engineering-Guide).
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## How does it work?
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To use the Prompt Stress-Test, simply follow these steps:
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1. Configure `run.py` with your evaluation method.
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2. Run `cps.py`.
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3. Check results.
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It's that simple!
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## Demonstration
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Don't believe us? Try out our demo! After cloning this repository, navigate into the root directory, run `npm i`, and create a configuration file called `config.json` with your OpenAI API key inside like so:
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```json
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{
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"key": "OPENAI KEY"
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}
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```
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Then start the server by running `node server.js`. Finally, run `python3 cps.py` in another terminal window and watch as we stress-test your chosen prompt(s)!
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## Other Resources
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For more information on how to improve prompt performance and security in general, check out these other resources:
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* [Google Forms LLM](https://github.com/velocitatem/FormsAI)
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* [Bing Chat Prompt](https://gitlab.com/-/snippets/2498990)
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And if you have any contributions or feedback for us, please don't hesitate to make a pull request!
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