BookKeeperAI

Overview

BookKeeperAI is a state-of-the-art application designed to mimic the behavior of a librarian using artificial intelligence. The app leverages LangChain, LangGraph, and Azure OpenAI's GPT-4 (o-mini model) to provide users with an interactive and intelligent library management experience. The app is hosted on a Gradio interface for an easy-to-use and visually appealing interface.

Key Features

• Search Books: Users can query the library dataset to search for books by title, category, or other attributes.
• Rent Books: Users can rent books directly through the interface. The app checks the availability of the book before completing the rental process.
• Markdown Responses: Search results are displayed in an elegant markdown table format for better readability.

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Tech Stack

1. LangChain LangChain serves as the core framework for building conversational AI agents. It provides the tools and structure to integrate language models, tools, and memory into a single seamless application.

2. LangGraph LangGraph is used to design and manage the application flow, ensuring a modular and scalable architecture for the AI librarian.

3. Azure OpenAI GPT-4 o-mini The AI model behind the app is the powerful Azure OpenAI GPT-4 (o-mini model). This model enables advanced natural language understanding and generation, making interactions with the AI librarian intuitive and human-like.

4. Gradio Gradio is used to create the user interface for the app. It provides a web-based platform where users can interact with the librarian, search books, and manage rentals.

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Prerequisites

Before you can run this project, ensure you have the following installed on your system:

• Docker
• Docker Compose You will also need an Azure OpenAI API Key and a valid library dataset to set up the application.

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Getting Started Follow the steps below to set up and run the project:

1. Clone the Repository

git clone git@github.com:nubufi/BookKeeperAI.git
cd BookKeeperAI

2. Set Up Environment Variables

Create a .env file in the root of the project based on the keys provided in the .env-example file.

3. Start the Application

Run the following command to start the application using Docker Compose:

docker-compose up

This will build the Docker image, start the container, and host the Gradio interface on http://localhost:9000.

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Usage Instructions

1. Access the Gradio Interface: Open your web browser and navigate to http://localhost:9000.

2. Search for Books:

• Enter a query to search for books. For example:
  • "Show me all fantasy books."
  • "Find books with the title 'Harry Potter'."
• Rent a Book:
  • Once a book is selected, the librarian checks its availability. If available, the book can be rented directly.

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API Integration

The app uses the following APIs:

1. Azure OpenAI API:

• Handles language model interactions.
• Requires an API key and endpoint configured in the .env file.

2. Database (SQLite):

• Manages the library dataset, including books, rentals, and customers.
• Queries are handled dynamically by LangChain tools.

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Known Issues & Limitations

• Book Availability: The app assumes each book is a single-copy entity. Multi-copy support is not currently implemented.
• Model Latency: The response time depends on the Azure OpenAI API and may vary.

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Future Enhancements

• Add support for creating new customers.
• Extend the librarian's functionality to recommend books based on user preferences.
• Implement user authentication for a personalized library experience.

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License

This project is licensed under the MIT License.

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Enjoy your AI-powered library experience! 📚