Large language models (LLM) are rapidly growing, and numerous applications have emerged. Many of these applications deal with a quick change in data and business requirements, which may cause a problem in the system.
Having an end-to-end machine learning pipeline could be a great choice to avoid these issues in the future. I would like to share Ray framework with Vertex AI for LLM development, fine-tuning, deployment, and monitoring by utilizing LLMOps principles to improve application performance and help organizations create better LLM apps.