reez-code/vunaguide-frontend

AI-Powered Crop Doctor for Smallholder Farmers in Kenya 🇰🇪 # 📱 VunaGuide Frontend AI-Powered Crop Doctor for Smallholder Farmers in Kenya 🇰🇪 View Backend Repository · Report Bug --- ## 📚 Project Deliverables Quick links to the Capstone Project submission materials: | Document | Link | | -------------------------- | -------------------------------------------------------------------------------------------------------------------------- | | 📄 **Project Proposal** | View Google Doc | | 🎥 **Demo Video** | Watch on Drive | | 📽️ **Presentation Slides** | View Google Slides | --- ## 📑 Table of Contents - Overview - Key Features - Tech Stack - Setup Guide - How to Use - Project Structure - License --- ## 📖 Overview VunaGuide bridges the gap between expert agronomy and smallholder farmers. This mobile-first web application provides an intuitive interface for farmers to: - **Diagnose Crop Diseases**: Instantly identify issues like Maize Lethal Necrosis or Tomato Blight using computer vision. - **Get Localized Advice**: Receive actionable, locally relevant treatment plans (e.g., specific Kenyan fungicides or organic remedies). - **Chat with an Expert**: Ask questions about planting seasons, market prices, and soil health, powered by real-time Google Search grounding. Built for the **Unstacked Labs / Google AI Hackathon**, this frontend is optimized for performance in low-bandwidth environments common in rural Africa. --- ## ✨ Key Features ### 📸 Visual Diagnosis (Computer Vision) - **Native Camera Integration**: Seamlessly captures photos directly from the device camera. - **Smart Analysis**: Uploads images to the backend Agent for instant disease identification. - **Actionable Results**: Displays clear, color-coded cards showing the disease name, confidence score, and a step-by-step treatment plan. - **Safety First**: Prominently display …