privykurura1/Zimbabwe-agri-advisor

# Offline AI Farming Advisor for Zimbabwe An offline, on-device AI advisor that helps Zimbabwean farmers diagnose livestock diseases and get crop guidance by Natural Region — no internet, no cloud, running entirely on an 8GB laptop. Built for the Africa Deep Tech Challenge 2026 — Agriculture domain. ## What it does - **Livestock disease triage** — describe symptoms, get a likely diagnosis, reasoning, and clear next steps (cattle tick-borne diseases, poultry disease) - **Crop advisory** — pest identification and planting-window guidance tuned to Zimbabwe's Natural Regions (I–V) Every answer is grounded in a locally-stored knowledge base (`corpus_livestock_crops.md`), retrieved at inference time — not just the model's general training data. ## How it works - **Model:** Qwen2.5-3B-Instruct, GGUF Q4_K_M quantization - **Runtime:** llama.cpp, CPU-only - **Retrieval:** TF-IDF-based RAG over the local corpus (`rag.py`) ## Quick start ```bash bash download_model.sh python rag.py "your farming question here" ``` See `REPORT.md` for full technical details, design decisions, and benchmarks.