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HexaBot: Your Local Place Finding Companion

💡 Inspiration

The inspiration for HexaBot came from a personal experience that many can relate to - spending an entire day searching for a bank. This frustrating experience highlighted the need for a more streamlined, chat-based approach to finding nearby locations. I wanted to create something that would make this process as simple as asking a friend, "Where's the nearest bank?"

🚀 What I Learned

Throughout this project, I gained valuable experience in several areas:

• Understanding and implementing conversation flows in chatbots
• Basic Docker containerization for development environments
• Flutter app development with a focus on chat interfaces
• Integration with location-based APIs
• Working with open-source mapping solutions

🛠️ How I Built It

The development journey started with exploring the Hello plugin as a foundation. From there, I:

1. Experimented with Chat Mechanics: I spent time understanding the underlying mechanisms of chatbot interactions, gradually building up from basic responses to more complex conversations.

2. Data Source Research: After getting the chat interface working, I needed reliable location data. This led me to OpenStreetMap, an incredible open-source mapping project that aligned perfectly with my love for open-source solutions.

3. API Integration: The real breakthrough came when I discovered Overpass API, a powerful tool built on top of OpenStreetMap. This API provided exactly what I needed - the ability to search for nearby amenities and locations with precise geographical data.

4. Implementation: I combined these elements into a cohesive system:

   • Flutter-based chat interface
   • Location services integration
   • OpenStreetMap for base mapping
   • Overpass API for nearby place discovery
   • Firebase for data persistence

🤔 Challenges Faced

Building HexaBot came with its share of challenges:

1. Understanding Chat Flows: Initially, creating natural conversation flows was tricky. I had to carefully design the interaction patterns to feel intuitive and helpful.

2. API Integration: Working with multiple APIs (location services, Overpass, etc.) required careful handling of asynchronous operations and error cases.

3. Data Processing: Converting raw location data into user-friendly information needed several iterations to get right.

4. UI/UX Design: Balancing the chat interface with map displays while keeping the experience smooth and intuitive took considerable experimentation.

5. Link Between the app and the plugin: This was the hardest part of the journey, i had to learn how to make channels from the existing slack channel, and tried my best to imitate it, but with no results, so i had to implement a little part of the workflow directly inside the app for demonstrations.

💝 Open Source Love

One of the most rewarding aspects of this project was working with open-source technologies. OpenStreetMap and Overpass API not only provided the functionality I needed but also aligned with my values of using and supporting open-source projects. This experience reinforced my belief in the power of open-source collaboration and community-driven development.

Built With

• flutter
• typescript