Reproducibility and Data Version Control for LangChain and LLM/OpenAI Models

Explore reproducibility and data version control for LangChain and LLM/OpenAI models in this 58-minute conference talk by Amit Kesarwani, Director of Solutions Engineering at Treeverse. Dive into the world of Large Language Models (LLMs) and Foundation Models, understanding their recent surge in popularity and usefulness. Learn about the unique challenges of working with Foundation Models compared to traditional machine learning approaches, including techniques like Fine Tuning, Prompt Engineering, and Retrieval Augmented Generation. Discover how LangChain simplifies the complexity of working with LLMs through its comprehensive library of open-source components. Address the growing challenges of managing and controlling large datasets, as well as achieving reproducibility in LLM applications. Gain insights into lakeFS, an open-source scalable data version control system, and its integration with LangChain through an official document loader. Understand how this combination allows for efficient management of vast amounts of data in any format, enabling branching, committing, and traversing history without data duplication.