| --- |
| language: en |
| license: apache-2.0 |
| pipeline_tag: text-classification |
| library_name: transformers |
| tags: |
| - agriculture |
| - agronomy |
| - query-classification |
| - farming |
| - corn |
| - soybeans |
| - rag |
| - routing |
| --- |
| |
| # Cornbelt AI Agronomy Query Router (MiniLM) |
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| ## Overview |
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| 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. |
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| The model acts as a **routing layer** for a Retrieval-Augmented Generation (RAG) system by identifying: |
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| - 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 |
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| This allows an AI system to efficiently determine which knowledge sources and tools should be used to answer the question. |
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| The model was trained using **MiniLM**, a compact transformer architecture optimized for fast inference. |
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| --- |
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| ## Intended Use |
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| This model is intended to support agronomy-focused AI systems by performing **query understanding and routing** before deeper reasoning or retrieval occurs. |
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| Example use cases include: |
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| - agronomy chat assistants |
| - agricultural decision support systems |
| - RAG pipelines for extension publications |
| - crop management advisory tools |
| - agronomy knowledge search systems |
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| Typical pipeline usage: |
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