Developed by: Swagath Somanna
Submission: Project Samarth Internship Challenge
This project is a working prototype of an intelligent Q&A system that connects agricultural production data with climate indicators such as rainfall and temperature.
It helps policymakers, researchers, and farmers ask natural questions and instantly get data-backed insights.
The project is inspired by data.gov.in datasets from:
- Ministry of Agriculture & Farmers Welfare
- India Meteorological Department (IMD)
- Python 3.12
- Streamlit (for the front-end)
- Pandas (for data handling)
- Matplotlib (for visual insights)
- Natural language question parsing (states, crops, years)
- Integrated datasets for rainfall, temperature, and crop production
- Auto-generated graphs and summaries
- Transparent data citations (each answer mentions its source)
- Extensible for live API integration with government datasets
- Clone or download this project.
- Open a terminal in the project folder.
- Install dependencies:
pip install streamlit pandas matplotlib
- Run the app:
streamlit run app.py
- The app will open at http://localhost:8501.
- “Compare the average annual rainfall in Karnataka and Maharashtra for the last 3 years.”
- “List the top 3 crops produced in each state.”
- “Analyze the rice production trend in Karnataka and its correlation with temperature.”
Representative datasets are included for demo purposes, based on open government data:
- Rainfall data — IMD historical data (2015–2021)
- Crop production — Ministry of Agriculture
- Temperature trends — IMD climate records
- Direct API integration with live data.gov.in datasets
- Add district-level crop analysis
- Include soil and groundwater data for more accurate modeling