Government Data, Chatbot, Accessibility
AgriQuery
Accessible Agricultural Commodity Price Chatbot
AgriQuery makes daily mandi price information easier to access for farmers, traders, students, and screen-reader users.
Status: Completed
Problem
Government market price data can be difficult to find and interpret. Users may not know the official commodity names or how to search large datasets.
Solution
The application accepts natural-language queries, handles common commodity names and synonyms, fetches official data, and returns relevant price information in a simple interface.
Architecture
- Express serves the chatbot interface.
- Scheduled data import keeps local records current.
- Natural-language matching maps user input to commodity data.
- Database queries return market records quickly.
Technologies
Node.js
Express
EJS
SQLite3
Government APIs
JavaScript
Automation
Responsive Web Design
Accessibility Review
- Semantic HTML and labeled form controls.
- Keyboard-friendly chatbot workflow.
- Clear status and error messaging for screen readers.
Challenges
- Handling inconsistent commodity names.
- Normalizing government API data.
- Balancing fuzzy matching with reliable results.
Skills Demonstrated
- Government API integration
- Backend development
- Database design
- Automation
- Accessibility engineering
Outcome
AgriQuery shows how public data can become a practical, accessible conversational tool.
Future Improvements
- Add more Indian languages.
- Add historical price trends.
- Improve location-aware market suggestions.
