VibeReads

Have you ever felt your mood deserves the perfect story? Whether it’s a warm mystery or a bold quest, VibeReads matches your vibe with personalized picks and a fun quiz to find your next read!

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Inspiration

VibeReads was born from the universal experience of picking up a book that just doesn’t feel right at the moment. As book lovers, we often wondered, What if there was a way to find books that perfectly align with how we feel right now? Whether you’re seeking comfort during tough times, a burst of joy, or a quiet space for reflection, we realized there was no platform that could help connect emotions to the right stories.
This sparked the idea for VibeReads — a platform that combines the power of AI and literature to provide an emotionally attuned book discovery experience. The project was inspired by the notion that books are more than just words on a page; they are companions that can uplift, inspire, and heal based on our emotional needs.

What it does

VibeReads is a one-of-a-kind platform that creates a bridge between your feelings and the books you read. It does this through a series of innovative features:
Mood Analysis with Gemini Prompt API: When you visit VibeReads, the first step is sharing a brief description of your current mood. It might be as simple as “nostalgic” , “happy” or “overwhelmed.” Using the advanced Gemini Prompt API, the platform processes your input and detects the emotions behind your words. Whether you’re feeling calm, excited, or introspective, the AI tailors its recommendations to reflect your state of mind.
Personalized Book Recommendations: Once your mood is identified, VibeReads uses the Gemini API’s suggestions as a foundation to curate a list of books that match your emotions. To ensure that you get meaningful results, the platform integrates with the Google Books API, fetching detailed book metadata like author, description, genre, and even captivating cover images. The result? A list of books you’ll want to dive into immediately, each resonating with your current emotional journey.
Interactive AI-Powered Book Quiz: Beyond recommendations, VibeReads offers a fun and educational way to engage with literature through an AI-powered quiz. Whether you’re testing your knowledge of genres, authors, or famous works, the quiz—also powered by Gemini AI—adds an interactive layer that keeps users entertained while subtly introducing them to more books that match their interests.

How we built it

Frontend and User Interface: The front end, developed using React, was designed to be intuitive and visually engaging. Special care was taken to create a smooth user flow, from describing your mood to browsing recommendations.
Backend and API Integration: The backend, powered by Node.js, acts as the brain of the platform. It integrates with the Gemini Prompt API to process mood input and fetch mood-specific book suggestions. To enhance these recommendations, the backend then connects to the Google Books API, which provides accurate and detailed book data.
AI for Quiz and Mood Analysis: The Gemini Prompt API plays a dual role: analyzing user emotions and generating dynamic quiz questions. This gave us a chance to explore how AI could personalize user experiences in both recommendation and engagement.

Challenges we ran into

Incomplete Data from APIs: The Gemini API, while excellent at sentiment analysis, didn’t provide all the book details we needed, such as cover images or publisher information. To address this, we integrated the Google Books API as a secondary source, ensuring users get complete and visually appealing recommendations.
Balancing Accuracy and Simplicity: Analyzing emotions can be complex, and we wanted the mood submission process to feel natural without overwhelming users. Refining the user input process to work seamlessly with the Gemini API took some trial and error.

Accomplishments that we're proud of

We’re proud of creating a personalized book recommendation system powered by mood analysis. The AI-based quiz adds a fun, interactive element, and the integration with real book data is seamless.

What we learned

We learned how to integrate external APIs effectively and how to build a web app that can analyze text and emotions. We also gained experience in handling user input and tailoring recommendations.

What's next for VibeReads

Next, we plan to enhance the mood analysis model, add more quiz categories, and improve book recommendation algorithms. We also aim to expand the app to include user reviews and community-based suggestions.

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