Project Title: Co-op Project - Pricing Calculator App

This project is a Python-based web application that I developed at Drone Cleaning Company that I joined as a Co-op Innternship placement.

Note: I got the permission to post the following system architecture and web app application.

Key Features:

1. Secure User Authentication: Restricts access to authorized users via a robust login system using Firebase and GCP Identity Platform.¹
2. Data Entry and Real-time Calculation: Enables efficient data input with intuitive forms and provides instant feedback through real-time calculation updates, enhancing user experience and productivity.²
3. Integrated Location Services: Utilizes Google Maps API for seamless address geocoding, location search, and interactive map visualization, enhancing user experience with location-based data.³
4. Automated Data Verification: Implements robust data validation to ensure accuracy and consistency, generates Google Sheets based on user demand, supports seamless verified data upload to Cloud SQL for persistent storage.⁴
5. Interactive Data Exploration & Dashboards: Provides intuitive dashboards on the homepage and a dedicated dashboard page, enabling users to select attributes, and input queries for data retrieval and analysis, monitor cleaning project completion, facilitate quick review for each cleaning project.⁵
6. Seamless Database Update: Allows users to efficiently update database records with a user-friendly interface and built-in data validation, ensuring data accuracy and integrity while providing real-time feedback on update status.⁶
7. Feedback System with Notion: Streamlines user feedback collection by integrating with Notion API, allowing users to submit feedback and optional screenshots directly to a designated Notion page, facilitating efficient issue tracking and web app improvement.⁷
8. AI-Powered Source Code Exploration: Leverages Google Gemini LLM and a FAISS vector database, providing Retrieval Augmented Generation(RAG) system through a user-friendly chat interface to understand web application source codes.⁸

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Technologies Used:

• Frontend: Dash/Plotly (React.js base)
• Backend: Python (Flask)
• Cloud Platform: Google Cloud Platform (GCP)
• Database: GCP's Cloud SQL(PostgreSQL)
• Loging: Firebase & GCP's Identity Platform
• Version Control: Git (GitHub)
• Additional API Services:
  • Notion API
  • Google Drive/Sheet/Map API

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Architecture Overview:

For a detailed visual representation of the system's workflow and interactions, refer to the diagrams provided in the docs/architectures/ folder or check the links on footnotes.

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Contact:

• Emails:
  • rarino@myseneca.ca
  • ranarino0611ca@gmail.com
• LinkedIn: https://www.linkedin.com/in/ran-arino-25253022b/

Footnotes

1. More details about the authentication process can be found in Login.png. ↩

2. The real-time calculation feature significantly improves user experience by providing immediate feedback. DataEntry.png ↩

3. Google Maps API enables seamless integration of location-based services, enhancing the app's functionality. GoogleMap.png ↩

4. Automated data verification ensures data accuracy and consistency, a crucial aspect of the application. DataVerify.png ↩

5. The interactive dashboards provide users with powerful tools for data exploration and analysis. Dashboard.png ↩

6. Seamless database updates streamline data management and ensure data integrity. DBUpdate.png ↩

7. The Notion API integration facilitates efficient feedback collection and issue tracking. Feedback.png ↩

8. The RAG system led by Google Gemini and FIASS vector DB boosts the understanding of source codes. CodingRAG.png ↩