Explore a comprehensive 19-minute conference talk from Conf42 Prompt Engineering 2024 that delves into the critical aspects of testing Large Language Model (LLM) powered applications. Learn from real-world examples, including the Microsoft Tay Bot case study, to understand the challenges and risks associated with deploying LLMs in production environments. Master essential testing methodologies, security considerations around prompt injection, and strategies for handling non-deterministic behaviors and inaccuracies inherent to language models. Discover how to build robust test systems, implement various testing types, and utilize key metrics for LLM evaluation. Gain insights into advanced testing approaches like adversarial testing and auto evaluation, while exploring available open-source tools for effective LLM testing.
Testing LLM-Powered Applications - Best Practices and Evaluation Methods
Overview
Syllabus
Introduction and Welcome
The Challenges of LLM-Powered Applications
Case Study: Microsoft's Tay Bot
The Risks of LLMs in Real-World Applications
Testing LLM-Powered Applications
Security Concerns and Prompt Injection
Non-Determinism and Inaccuracy in LLMs
Building a Robust Test System
Types of Testing for LLMs
Metrics for Evaluating LLMs
Adversarial Testing and Auto Evaluation
Open Source Tools for LLM Testing
Conclusion and Final Thoughts
Taught by
Conf42
