The Cornbelt AI Agronomy Query Router is a lightweight classification model designed to analyze farmer queries and determine how they should be processed by an agricultural AI assistant.
The model acts as a routing layer for a Retrieval-Augmented Generation (RAG) system by identifying:
whether a query is agriculture-related
which crop the query concerns
agronomic topic categories
whether additional context such as weather or location may be required
This allows an AI system to efficiently determine which knowledge sources and tools should be used to answer the question.
The model was trained using MiniLM, a compact transformer architecture optimized for fast inference.
Intended Use
This model is intended to support agronomy-focused AI systems by performing query understanding and routing before deeper reasoning or retrieval occurs.
