During the development of FREDS, our team encountered several challenges that required innovative solutions and persistent effort to overcome. These challenges are integral to the learning process and have contributed to our evolution.

1)Lack of Awareness on Awaiting Data Reception:- One significant challenge was understanding the importance of awaiting data reception when creating the interface to interact with the smart contract. Initially, we encountered null data from function calls to the smart contract, leading to confusion. This required several hours of investigation to identify the need for awaiting data before proceeding, ensuring smoother interactions with the smart contract.

2)Difficulty in Deploying Flask on a Server:- Deploying the Flask backend on a server proved to be another significant hurdle. Despite attempting various hosting platforms, we faced issues during the deployment process. This prompted us to set up the Flask server locally before running the frontend, allowing us to overcome the deployment challenges and continue the development process.

3)AI/ML Model Development Complexities:- Developing AI/ML models for content moderation introduced a range of challenges. Sourcing appropriate datasets for toxic and non-toxic comments, selecting models with a balance between speed and accuracy, and iteratively enhancing accuracy levels were complex tasks.

4)Another challenge we tackled was implementing a feature to sort posts in decreasing order of likes and effectively integrating APIs between the Flask server (housing the ML model) and the frontend.