BookWise

BookWise is a comprehensive library management system app built with Next.js for tracking book states.

Core Features

• Add Books: Add new books with details like title, author, and ISBN.
• Update Status: Easily update a book's borrowing status between 'Available', 'Checked Out', and 'Archived'.
• Assign Borrowers: Assign books to borrowers when they are checked out.
• Search & Filter: A powerful search for finding books by title and filtering by their current status.
• AI-Powered Suggestions: Get recommendations for related books based on a book's title, powered by GenAI.

This project is a demonstration of a modern, full-stack web application using Next.js, TypeScript, and Tailwind CSS, featuring server components, server actions, and AI integration.

Project Structure

Here's an overview of the key directories and files in this project:

• /src/app: Contains the core Next.js application, including pages and API routes.
• /src/components: Reusable React components used throughout the application.
• /src/ai: Houses the Genkit AI flows and configuration.
• /src/services: Modules for interacting with external services like Firebase.
• /src/lib: Utility functions and type definitions.
• /firebase.json: Configuration for Firebase services.
• /genkit.ts: Configuration for the Genkit AI framework.

Firebase Integration

This project uses Firebase to handle backend services, including:

• Firestore: A NoSQL document database for storing book information, user data, and application state.
• Firebase Authentication: Manages user sign-up and login, providing a secure way to handle user accounts.
• Cloud Storage for Firebase: Used to store book cover images generated by the AI.
• Cloud Functions for Firebase: The onBookWriteCreateEmbedding function is a key part of the AI-powered features, generating embeddings from book notes.

Getting Started with Genkit

Genkit is an open-source framework that helps you build, deploy, and monitor production-ready AI-powered features. It provides tools for defining AI flows, managing prompts, and integrating with models like Google's Gemini.

Genkit AI Flows

The application leverages Genkit to create AI-powered flows that enhance the user experience. These flows are defined in the /src/ai/flows directory.

generateBookCover

• Purpose: Generates a unique book cover image based on the book's title and author.
• Genkit Features:
  • ai.defineFlow: Defines the flow, making it available for invocation.
  • ai.generate: Calls the image generation model with a specific prompt.
• Trigger: Manually triggered by the user from the book details page.
• Input: title, author, bookId.
• Output: The public URL of the generated book cover image in Firebase Storage.

populateBookData

• Purpose: Automatically populates book data (author and ISBN) based on the book's title.
• Genkit Features:
  • ai.definePrompt: Creates a reusable prompt template for extracting structured data.
  • ai.defineFlow: Wraps the prompt in a flow.
• Trigger: When a user adds a new book.
• Input: title.
• Output: An object containing the title, author, and isbn.

suggestRelatedBooks

• Purpose: Suggests a list of related books based on the current book's title.
• Genkit Features:
  • ai.definePrompt: Creates a prompt for generating a list of suggestions.
  • ai.defineFlow: Exposes the prompt as a flow.
• Trigger: Manually triggered by the user.
• Input: title.
• Output: A list of related book titles.

talkWithGemini

• Purpose: Enables a conversational experience, allowing users to chat about a book.
• Genkit Features:
  • ai.defineFlow: Manages the chat history and context.
  • ai.generate: Generates a conversational response.
• Trigger: User initiates a chat from the book details page.
• Input: Chat history and book object.
• Output: A conversational response from the AI.

Firebase Functions

The project includes a key Cloud Function for Firebase that integrates with the AI capabilities.

onBookWriteCreateEmbedding

• Purpose: This function automatically generates a vector embedding for a book's notes whenever the notes are added or updated in Firestore.
• Trigger: The function is triggered by onWrite events on documents in the /users/{userId}/books/{bookId} collection. For example, a real document path could be /users/123/books/456.
• Details: When a book's notes field is modified, the function uses a Genkit embedder to create a 768-dimensional vector embedding of the notes. This embedding is then stored in the embedding field of the same document, enabling vector-based similarity searches.

Deployed Application

You can access the deployed application here: https://studio--bookwise-7k4b9.us-central1.hosted.app