Programmer Taps AI to Tame Sprawling Digital Book Collection
TORONTO – A local programmer has developed a novel approach to a uniquely 21st-century problem: how to bring order to a sprawling personal library of several thousand e-book files. By integrating Google's Gemini AI, he has created a system to automatically retrieve the genre and synopsis for each title, transforming a disorganized collection into a meticulously cataloged digital library.
The project began with the challenge of files named with inconsistent author and title information. Using the epub-metadata library for Python, the developer first built a tool to reliably extract the title from each file. The next step was to enrich this basic data. "I wanted to be able to use AI and Google to get the genre and synopsis," he stated, outlining his goal.
To accomplish this, he turned to Google's AI Studio to acquire an API key, granting his script access to the powerful Gemini Pro model. In a proof-of-concept script, he demonstrated how the AI could be queried with a book's title to return structured metadata. The system is designed for a streamlined workflow; the Python script securely accesses the API key from an environment variable, a standard practice for managing credentials in software development.
This innovative solution showcases the growing accessibility of advanced artificial intelligence, allowing individuals to build powerful, custom tools to manage personal data and automate complex organizational tasks. The programmer's initial tests have proven successful, paving the way for the full-scale cataloging of his extensive collection.
Title: the emperors new mind
"""
Google Books API Integration Script
This script uses Google's Gemini AI API to retrieve genre and synopsis information
for books based on their titles. It constructs a query using the book title and
the Google Books URL format, then uses the Gemini AI model to generate a response
with genre and synopsis information.
Requirements:
- Google Gemini API key set as environment variable 'GEMINI_API_KEY'
- google-generativeai package installed
Usage:
python test_google_book_api.py
(The script will prompt for a book title)
"""
import pprint # For pretty-printing the API response
from google import genai # Google's Generative AI library
# The client gets the API key from the environment variable `GEMINI_API_KEY`.
# Google Books URL format: https://www.google.ca/books/edition/title
def aibook(title):
"""
Query the Gemini AI model for book genre and synopsis information.
This function creates a Gemini AI client, constructs a prompt with the book title
and desired output format, then returns the generated text response.
Args:
title (str): The title of the book to query
Returns:
str: The formatted response text containing genre and synopsis information
Example output format:
Genre: Fiction, Science Fiction, Dystopian
Synopsis: A story about...
"""
# Initialize the Gemini AI client
client = genai.Client()
# Generate content using the Gemini model with a formatted prompt
response = client.models.generate_content(
model="gemini-2.5-flash", # Using the Gemini 2.5 Flash model for fast responses
contents=f"""
book url https://www.google.ca/books/edition/{title}/
provide the genre and synopsis of the book
use the format
line 1 Genre: genre1, genre2, etc
line 2 Synopsys: the synopsys
"""
)
# Return the text portion of the response
return response.text
# Execute only if run as a script, not when imported as a module
if __name__ == "__main__":
# Prompt the user for a book title, pass it to the aibook function,
# and pretty-print the results
pprint.pp(aibook(input('Title: ')))
