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Fadzai-Ryan-Mboma/zimbabwe-crop-rag

Domaine:

agriculture

Type de record:

software
Créateur:
Fad
Hôte:
# Zimbabwe 6-Crop RAG System Agricultural variety selection AND in-season diagnostic advisory system for Zimbabwe farmers. Covers maize, tomatoes, tobacco, cotton, groundnuts, and sorghum. ## What It Does ✅ **Pre-Planting**: Variety selection, region matching, ROI calculations ✅ **In-Season Diagnostics**: Disease identification, pest management, nutrient deficiency diagnosis ✅ **Growth Stage Advice**: What to do at each stage of crop development ## Quick Start (5 Steps) ```bash # 1. Clone and setup cd zimbabwe-crop-rag python -m venv venv source venv/bin/activate # Windows: venv\Scripts\activate pip install -r requirements.txt # 2. Configure API keys cp .env.example .env # Edit .env with your API keys (see SETUP.md for details) # 3. Collect data python data_collection/run_collection.py # 4. Process and load to vector database python data_processing/populate_db.py # 5. Start the server python interface/app.py ``` ## Example Queries **Variety Selection:** - "Best maize variety for Region III with 600mm rainfall" - "Drought tolerant groundnuts for Region V" **Disease Diagnosis:** - "At 6 weeks, my tobacco leaves have yellow spots and stalks are getting weak" - "Gray rectangular spots on my maize leaves" **Pest Identification:** - "Found caterpillars eating my maize leaves" - "White flies on my tomatoes" **Growth Stage Advice:** - "When should I top my tobacco?" - "What should I do for maize at 6 weeks?" ## Features - **6 Crops Covered**: Maize, tomatoes, tobacco, cotton, groundnuts, sorghum - **300+ Varieties**: From Seed Co, Bayer, CIMMYT, ICRISAT, and more - **In-Season Diagnostics**: Disease, pest, and nutrient deficiency identification - **Zimbabwe-Specific**: Natural Region mapping, local prices, local products - **WhatsApp Interface**: Twilio integration with Shona/English support - **Confidence Scoring**: Transparent data quality indicators - **Economic Optimizer**: ROI calculations, budget alternatives ## Data Quality by Crop | Crop | Varieti …

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