India Street Food Guide: A Local Food Recommendation App Built with Kiro
This project shows how I built a simple street food guide for India using Kiro, focusing on local food, real areas, and offline data without using any external APIs.
Overview
India has one of the richest street food cultures in the world. Every city has its own famous food, and at the same time you can also find food from other states in that city. Most food apps feel generic and do not capture this local feeling.
In this project, I built India Street Food Guide, a simple web app that suggests street food based on a user’s city and food craving. The app is built using only HTML, CSS, and JavaScript, and it uses Kiro to handle local logic in a clear and controlled way.
GitHub repository:
https://github.com/PayalKumari10/Street-Food-Guide-app.git
https://github.com/PayalKumari10/Street-Food-Guide-app.git
What the App Does
The app asks the user two things:
- City name (optional)
- What they are craving or their mood
Based on this input, the app shows:
- Food name
- Area or landmark
- A short reason explaining why this food is suggested
For example:
- Vada Pav from CST Station in Mumbai
- Fuchka from New Market in Kolkata
- Litti Chokha from Gandhi Maidan in Patna
If the user input is unclear, the app safely suggests popular street foods from different cities.
How I Used Kiro
Kiro was used as a local-aware agent. Instead of letting it guess, I gave it a clear local dataset and strict rules.
The dataset contains:
- Major Indian cities
- Each city’s famous street foods
- Popular foods from other states that are also available in that city
- Real areas and simple reasons
Kiro follows these rules:
- Use only the local dataset
- Do not invent food or locations
- Prefer city-based food if a city is provided
- Fall back to popular Indian street food if input is unclear
This keeps the output realistic and consistent.
Why This Project Matters
Street food is deeply local. A good recommendation should feel like advice from someone who knows the city. This project shows that even without APIs or complex systems, we can build meaningful local experiences if the context is designed properly.
Tech Stack
- HTML for structure
- CSS for mobile-friendly design
- JavaScript for logic
- Kiro for local decision-making
No external libraries or APIs were used.
Conclusion
India Street Food Guide is a small but practical project that focuses on local culture and simplicity. Through this project, I learned how important clear context and rules are when working with AI agents like Kiro.
This project was built as part of the Kiro Hero Challenge Week 5.
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