app.py

from typing import Optional
from smolagents import CodeAgent, HfApiModel, tool
import os
import requests
import gradio as gr

# Define tool for fetching book recommendations
@tool
def get_book_recommendations(prompt: str) -> str:
    """Fetches book recommendations based on user prompt.
    Args:
        prompt: the user's query, e.g., "book about Mars"
    """
    print(f"Received prompt: {prompt}")
    api_key = os.getenv("GOOGLE_BOOKS_API_KEY")
    print(f"Using API Key: {api_key}")
    search_query = prompt
    
    url = f"https://www.googleapis.com/books/v1/volumes?q={search_query}&key={api_key}"
    print(f"Request URL: {url}")
    response = requests.get(url)
    print(f"API Response Status Code: {response.status_code}")
    
    if response.status_code == 200:
        books = parse_google_books_response(response.json())
        print(f"Parsed Books: {books}")
        top_books = books[:5]  # Get top 5 books
        return format_book_recommendations(top_books)
    else:
        return "Error fetching book recommendations."

def parse_google_books_response(json_content):
    books = []
    for item in json_content.get('items', []):
        volume_info = item.get('volumeInfo', {})
        title = volume_info.get('title', 'No title available')
        authors = ", ".join(volume_info.get('authors', ['No author available']))
        
        books.append({
            "title": title,
            "author": authors
        })
    return books

def format_book_recommendations(books):
    formatted_books = []
    for index, book in enumerate(books, start=1):
        formatted_books.append(f"{index}. {book['title']} by {book['author']}")
    return "\n".join(formatted_books)

# Create the AI agent
agent = CodeAgent(tools=[get_book_recommendations], model=HfApiModel(), additional_authorized_imports=["requests"])

# Define Gradio interface
def generate_recommendations(query: str) -> str:
    return agent.run(query)

description_md = """
Get top 5 book recommendations based on your query. Simply enter your query, and receive a list of books with their names, authors.
"""
# Create Gradio UI
iface = gr.Interface(
    fn=generate_recommendations,
    inputs=[
        gr.Textbox(lines=1, placeholder="Enter a query", label="Book Topic")
    ],
    outputs="text",
    title="Book Beacon",
    description=description_md
)

# Launch Gradio UI
iface.launch(share=True)