TagIt is a mobile application built using SwiftUI and Firebase for sharing grocery deals and user reviews. This README provides comprehensive documentation for developers working with the TagIt codebase.

• Deal Posting: Users can post deals including product name, description, price, location, and photos.
• User Reviews: Users can submit reviews for products, including star ratings and text reviews with optional photos.
• Barcode Scanning: Integrated barcode scanning to easily add product details and reviews.
• User Authentication: Secure user accounts managed by Firebase Authentication.
• User Profiles: User profiles include display name, avatar image, and ranking points.
• Ranking System: User rankings based on deal postings, upvotes, and comments.
• Search Functionality: Algolia-powered search for deals based on product names and locations.
• Location Services: Displays deals near the user's current location (requires location permission).
• Saving Deals: Users can save deals to their profile for later viewing.
• Comments & Voting: Upvote/downvote functionality for both deals and comments.

• SwiftUI: For the user interface.
• Firebase: For backend services (Firestore, Authentication, Storage).
• Algolia: For search functionality.
• Core Location: For location-based services.
• PhotosUI: For image selection from the photo library.
• AVFoundation: For barcode scanning.

• Xcode 14 or later.
• A Firebase project set up with necessary services (Firestore, Authentication, Storage). Obtain your GoogleService-Info.plist file, and add it to the Xcode project.
• An Algolia account and API Key, configured in Info.plist added to the Xcode project. The Algolia index "search_deals" must be created. Update Info.plist and .env with your Algolia API Key and App ID.
• CocoaPods (for dependency management - though appears to now use Swift Package Manager).

1. Clone the repository:

   git clone <repository_url>

2. Install dependencies:

   • Swift Package Manager: Open the project in Xcode and let Xcode manage the dependencies. You should be prompted to add the dependencies. Ensure you have the required Firebase and Algolia packages added.

3. Configure Firebase:

   • Download your GoogleService-Info.plist file from your Firebase project settings and place it in the TagIt directory.
   • Add the file to your Xcode project.

4. Configure Algolia:

   • Create an Algolia index named "search_deals".
   • Replace placeholders in TagIt/Info.plist with your Algolia App ID and API Key.
   • Update .env file with GEMINI_API_KEY if using a Gemini API Key

5. Run the project: Open TagIt.xcodeproj in Xcode and run the application on a simulator or device.

The NewDealView allows users to create new deals. The process involves filling out fields for product name, description, price, location and uploading an image.

The BarcodeScannerView utilizes the device's camera to scan barcodes. Upon successful scanning, the barcode value will be sent to the next view for review submission.

The SearchView allows users to search for deals. The search uses Algolia for quick searching by product name or location.

The project is organized into the following directories:

• TagIt: Contains the main source code, models, services, view models, and views.

  • Assets.xcassets: Contains the application assets (images, color sets).
  • Extensions: Contains Swift extensions for helper functions.
  • Models: Contains data models (e.g., Deal, UserProfile).
  • Other: Contains helper functions (Utils, LocationManager).
  • Preview Content: Contains assets for preview.
  • Services: Contains classes for interacting with Firebase and Algolia (e.g., AuthService, DealService, FirestoreService, ImageService, ReviewService, SearchService, StoreService, UserService, VoteService).
  • ViewModels: Contains view models (e.g., HomeViewModel, LoginViewModel).
  • Views: Contains the user interface components and views.
  • .env: Contains environment variables (Algolia API Key).

• TagIt.xcodeproj: Xcode project files.

• dummy_data.json: Contains dummy data for testing. This is populated by set_dummy.py and cleaned up by delete_dummy.py.
• delete_dummy.py: Deletes dummy data and associated images from Firestore and Storage. Requires Firebase Admin SDK and a service account key file.
• dummy_data.json: Contains dummy data for initializing or testing the database.
• firestore_export.py: Exports Firestore data to a JSON file.
• nuke_db.py: Deletes all data (deals, users, reviews, etc.) from Firestore and storage. Use with extreme caution!
• set_dummy.py: Populates the Firestore database with dummy data from dummy_data.json, creates dummy users and handles image uploads to Storage.

Before running any of the Python scripts, ensure you've installed the Firebase Admin SDK: pip install firebase-admin and have a valid service account key file (e.g., tagit-39035-firebase-adminsdk-hugo8-9c33455468.json) in the scripts directory. The set_dummy.py script relies on image URLs and will download those images as part of its execution.

Angi Shi, Chenghou Si, Mahbub Prutik Iftekhar, Mingyang Li, Mu He, Peter Tran, Sipeng He