LangChain for Life Sciences and Healthcare

Chapter 5. Building Personal Assistants

While working as a research scientist in a chemistry lab, most of my work was far from what is seen in movies: there was much more routine and less action. The questions that real scientists bump into daily may take enormous time and effort to solve. Generative AI can’t replace humans, but it can augment human capabilities to accelerate the pace of scientific discovery. Even with future AI developments, there’s an argument that AI would augment rather than replace humans in science. The creativity, intuition, and cross-disciplinary insights that humans bring to scientific discovery may remain valuable. Powered by LLMs, generative AI applications can help with topic explanation, parse vast scientific literature, extract insights, identify patterns, generate hypotheses, even run calculations and simulations, and much more. Generative AI is already used by researchers to create clear and concise reports, presentation materials, and parts of research papers, ensuring their findings are communicated accurately and effectively.

Chapters 6 through 9 cover using LangChain in the fields of biology, chemistry, drug discovery, and healthcare. This chapter discusses building personal assistants to help with research and development.

Building Assistants with Chains

Chapter 3 discussed how to use chains in LangChain. In LangChain, a chain is a powerful concept that allows you to combine multiple operations and steps into a cohesive pipeline. Such sequences ...