How neeraja2303/ai-powered-weather-agent works
AgriAid is a Streamlit farm-advisory app: a user enters location and field conditions, then receives a yield estimate, weather details, soil advice, a crop recommendation, and optimization tips. The app directly invokes each advisory module; the crop recommendation is also passed to the tips function. The repository includes model-training code and data/artifact files, but their shown paths do not match the paths used by the code, so their runtime wiring is uncertain. The README describes a weather assistant, while the sampled app implements broader crop and farm advice.
Main entry points: app.py Streamlit App · weather_agent.py Weather Lookup · optimization_agent.py Optimization Tips · yield_predictor.py Yield Prediction
Components 11
Farm Advisor Interface
- Streamlit App
app.py
Farm Advice
- Weather Lookup
weather_agent.py - Soil Advice
soil_health_agent.py - Crop Recommendation
crop_advisor.py - Optimization Tips
optimization_agent.py
Yield Modeling
- Yield Prediction
yield_predictor.py - Model Training Script
train_model.py - Crop Yield Data
crop_yield_data.csv - Trained Model Artifact
trained_model.pkl
Other components
- Farmer
- OpenWeatherMap
Connections 10
- Farmer → Streamlit App: enters conditions
app.py - Streamlit App → Yield Prediction: requests estimate
app.py - Streamlit App → Weather Lookup: requests forecast
app.py - Streamlit App → Soil Advice: requests advice
app.py - Streamlit App → Crop Recommendation: requests crop
app.py - Streamlit App → Optimization Tips: requests tips
app.py - Streamlit App → Optimization Tips: passes crop
app.py - Weather Lookup → OpenWeatherMap: fetches conditions
weather_agent.py - Model Training Script → Trained Model Artifact: saves model
- Crop Yield Data → Yield Prediction: may train from