## Inspiration and Beginning

The journey of developing our food transparency app began with a simple yet powerful idea: to empower consumers with the knowledge they need to make informed decisions about the food they buy and consume. Inspired by the vision of Open Food Facts, we were driven by the belief that everyone should have access to transparent information about the products they consume daily. This vision resonated deeply with our team, igniting a passion to contribute to a more transparent and sustainable food system.

## What it does

Health Receipt is a revolutionary app designed to provide consumers with comprehensive information about the food products they purchase. Its core functionalities include:

1. **OCR-Based Receipt Scanning**: Using optical character recognition (OCR) technology, Health Receipt scans grocery store receipts to extract detailed information about the food items listed.
2. **Nutrition Information**: The app retrieves nutrition facts for each scanned product, including calorie count, macronutrient breakdown, and ingredient list.
3. **Eco-Scores and Packaging Information**: Health Receipt evaluates the environmental impact of each product by analyzing packaging materials and carbon footprint, providing users with eco-scores to guide sustainable purchasing decisions.
4. **Allergen Warnings**: The app identifies potential allergens present in scanned products, helping users with dietary restrictions make safe choices.
5. **Recipe Creation**: Health Receipt offers a unique feature that allows users to generate recipes based on the ingredients scanned from their receipts, promoting creative and healthy meal planning.

## How we built it

1. **Typescript**: We chose TypeScript for its strong typing system and scalability, enabling us to write cleaner and more maintainable code.
2. [Bun](https://bun.sh/): The backend of Health Receipt is powered by Bun, providing a fast and efficient server environment for processing user requests and handling data.
3. **npm**: We utilized npm, the package manager for JavaScript, to integrate various libraries and dependencies into our project, streamlining development and ensuring compatibility.
4. [Convex](https://www.convex.dev/): Leveraging the Convex framework, we implemented features such as text search, server functions, and real-time updates, enhancing the performance and functionality of our app's backend.
5. [Google Vision API](https://cloud.google.com/vision?hl=en): For OCR functionality, we integrated the Google Vision API, which enabled us to extract text data from grocery store receipts with high accuracy and reliability.
6. [Together AI](https://www.together.ai/): Collaborating with Together AI, we incorporated innovative features like recipe creation into Health Receipt, enriching the user experience and adding value to the app.

## Challenges we ran into

Throughout the hackathon, we encountered numerous challenges that tested our perseverance and problem-solving skills. From overcoming technical hurdles to refining user interfaces for optimal usability, each obstacle presented an opportunity for growth and innovation. One of our significant challenges was ensuring the accuracy and reliability of OCR data extraction, requiring meticulous fine-tuning and validation processes.

With each hurdle overcame, we emerged stronger and more resilient, fueled by our passion for catalyzing positive change in the food industry.

## Accomplishments that we're proud of

Our integration with the Open Food Facts database has enabled us to contribute to the broader movement for food transparency. By leveraging this vast repository of product data, we're facilitating greater transparency and accountability within the food industry.

## What we learned

Through the development of Health Receipt, we gained invaluable insights into the importance of teamwork and collaboration. Our team dynamics played a crucial role in driving the project forward, with each member contributing their unique strengths and expertise. We learned to leverage individual strengths to overcome challenges and capitalize on opportunities, fostering a supportive and cohesive working environment. Additionally, we became more attuned to recognizing and addressing our team's weaknesses, embracing a culture of continuous improvement and open communication. Ultimately, our journey with Health Receipt reinforced the significance of teamwork in achieving shared goals and delivering impactful solutions to real-world problems.
## Inspiration

The world today has changed significantly because of COVID 19, with the increased prominence of food delivery services. We decided to get people back into the kitchen to cook for themselves again. Additionally, everyone has a lot of groceries that they never get around to eating because they don't know what to make. We wanted to make a service that would make it easier than ever to cook based on what you already have.

## What it does

Recognizes food ingredients through pictures taken on a smartphone, to build a catalog of ingredients lying around the house. These ingredients are then processed into delicious recipes that you can make at home. Common ingredients and the location of users are also stored to help reduce waste from local grocery stores through better demographic data.

## How we built it

We used to express and Node for the backend and react native for the front end. To process the images we used the Google Vision API to detect the ingredients. The final list of ingredients was then sent to the Spoonacular API to find recipes that best match the ingredients at hand. Finally, we used CockroachDB to store the locational and ingredient data of users, so they can be used for data analysis in the future.

## Challenges we ran into

* Working with Android is much more challenging than expected.
* Filtering food words for the image recognition suggestion.
* Team members having multiple time zones.
* Understanding and formatting inputs and outputs of APIs used

## Accomplishments that we're proud of

* We have an awesome-looking UI prototype to demonstrate our vision with our app.
* We were able to build our app with tools that we are unfamiliar with prior to the hackathon.
* We have a functional app apk that's ready to demonstrate to everyone at the hackathon.
* We were able to create something collaboratively in a team of people each with a drastically different skill set.

## What we learned

* Spoonacular API
* React Native
* Google Vision API
* CockroachDB

## What's next for Foodeck

* Implement personalized recipe suggestions using machine learning techniques. ( Including health and personal preferences )
* Learn user behavior of a certain region and make more localized recipe recommendations for each region.
* Implement an optional login system for increased personalization that can be transferred through d
* Extend to multi-platform, allowing users to sync the profile throughout different devices.
Integrate with grocery delivery services such as instacart, uber eats.
## Inspiration

Food is a basic human need. As someone who often finds themselves wandering the aisles of Target, I know firsthand how easy it is to get lost among the countless products and displays. The experience can quickly become overwhelming, leading to forgotten items and a less-than-efficient shopping trip. This project was born from the desire to transform that chaos into a seamless shopping experience. We aim to create a tool that not only helps users stay organized with their grocery lists but also guides them through the store in a way that makes shopping enjoyable and stress-free.

## What it does

**TAShopping** is a smart grocery list app that records your grocery list in an intuitive user interface and generates a personalized route in **(almost)** any Target location across the United States. Users can easily add items to their lists, and the app will optimize their shopping journey by mapping out the most efficient path through the store.

## How we built it

* **Data Aggregation:** We utilized `Selenium` for web scraping, gathering product information and store layouts from Target's website.
* **Object Storage:** `Amazon S3` was used for storing images and other static files related to the products.
* **User Data Storage:** User preferences and grocery lists are securely stored using `Google Firebase`.
* **Backend Compute:** The backend is powered by `AWS Lambda`, allowing for serverless computing that scales with demand.
* **Data Categorization:** User items are classified with `Google Gemini`
* **API:** `AWS API Endpoint` provides a reliable way to interact with the backend services and handle requests from the front end.
* **Webapp:** The web application is developed using `Reflex`, providing a responsive and modern interface for users.
* **iPhone App:** The iPhone application is built with `Swift`, ensuring a seamless experience for iOS users.

## Challenges we ran into

* **Data Aggregation:** Encountered challenges with the rigidity of `Selenium` for scraping dynamic content and navigating web page structures.
* **Object Storage:** N/A (No significant issues reported)
* **User Data Storage:** N/A (No significant issues reported)
* **Backend Compute:** Faced long compute times; resolved this by breaking the Lambda function into smaller, more manageable pieces for quicker processing.
* **Backend Compute:** Dockerized various builds to ensure compatibility with the AWS Linux environment and streamline deployment.
* **API:** Managed the complexities of dealing with and securing credentials to ensure safe API access.
* **Webapp:** Struggled with a lack of documentation for `Reflex`, along with complicated Python dependencies that slowed development.
* **iPhone App:** N/A (No significant issues reported)

## Accomplishments that we're proud of

* Successfully delivered a finished product with a relatively good user experience that has received positive feedback.
* Achieved support for hundreds of Target stores across the United States, enabling a wide range of users to benefit from the app.

## What we learned

>
> We learned a lot about:
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> * **Gemini:** Gained insights into effective data aggregation and user interface design.
> * **AWS:** Improved our understanding of cloud computing and serverless architecture with AWS Lambda.
> * **Docker:** Mastered the process of containerization for development and deployment, ensuring consistency across environments.
> * **Reflex:** Overcame challenges related to the framework, gaining hands-on experience with Python web development.
> * **Firebase:** Understood user authentication and real-time database capabilities through Google Firebase.
> * **User Experience (UX) Design:** Emphasized the importance of intuitive navigation and clear presentation of information in app design.
> * **Version Control:** Enhanced our collaboration skills and code management practices using Git.
>
>
>

## What's next for TAShopping

>
> There are many exciting features on the horizon, including:
>
>
> * **Google SSO for web app user data:** Implementing Single Sign-On functionality to simplify user authentication.
> * **Better UX for grocery list manipulation:** Improving the user interface for adding, removing, and organizing items on grocery lists.
> * **More stores:** Expanding support to additional retailers, including Walmart and Home Depot, to broaden our user base and shopping capabilities.
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