Dive into the future of software testing with AI-driven QA systems using Multi-Agent Retrieval-Augmented Generation (RAG). This session will demonstrate how to design and implement multi-agent systems that collaborate to automate UI testing, identify bugs, and adapt dynamically to application updates.
We’ll explore step-by-step methods for:
1)Integrating RAG techniques to retrieve and utilize relevant data for adaptive testing. 2)Building Python-based pipelines using libraries like PyTest, Selenium, and LangChain for seamless automation. 3)Automating bug detection with enhanced accuracy using machine learning models. 4)Optimizing test coverage with agents that learn and adapt to application changes.
This presentation is perfect for Python developers, QA testers, and engineers seeking practical approaches to enhance their testing workflows, reduce manual intervention, and ensure robust application performance in evolving software environments.