Expert Support case study: Bolstering a RAG app with LLM-as-a-Judge

This is a guest blog post authored by Digital Green. Digital green is participating in a CGIAR-led collaboration to bring agricultural support to smallholder farmers.

There are an estimated 500 million smallholder farmers globally: they play a critical role in global food security. Timely access to accurate information is essential for these farmers to make informed decisions and improve their yields.

An “agricultural extension service” offers technical advice on agriculture to farmers, and also supplies them with the necessary inputs and services to support their agricultural production.
Agriculture extension agents are 300K in India alone, they provide necessary information about improved agriculture practice and help in decision making for the smallholder farmers.

But although their number is impressive, extension workers are not in large enough numbers to cope with all the demand: they interact with farmers at typically in the ratio of 1:1000. Reaching the agriculture extension workers and farmers through partnership and technology remains the key.

Enter project GAIA, a collaborative initiative pioneered by CGIAR.
It brought together Hugging Face as mentor through the Expert Support program, and Digital Green as project partner.

GAIA has a lofty goal to bring years of agriculture knowledge in the form of research papers meticulously maintained in GARDIAN portal in the hands of the farmers. There are close to 46000 research papers and reports that have agricultural knowledge globally carried over multiple decades across different crops.

Digital Green immediately saw the potential of developing intelligent chatbots powered by Retrieval-Augmented Generation (RAG) on approved, curated information. Thus they decided to develop Farmer.chat, a chatbot that leverages the capabilities of large language models (LLMs) to deliver personalized and reliable agricultural advice to the farmers and front line extension workers.

Let’s take a look at how they tackled this challenge!