app.py

import pandas as pd
import gradio as gr
from Search_Engine.SmartSearchEngine import search_courses
# Load the DataFrame with embeddings
df = pd.read_pickle('output/courses_with_embeddings.pkl')

# Define the search function to be used in the Gradio interface
def gradio_search(query):
    results = search_courses(query, top_n=5)
    return results.to_dict(orient='records')

# Create a Gradio interface
iface = gr.Interface(
    fn=gradio_search,
    inputs=gr.Textbox(lines=2, placeholder="Enter your search query here..."),
    outputs=gr.JSON(label="Search Results"),
    title="Smart Course Search Tool",
    description="Search for the most relevant courses on Analytics Vidhya"
)

# Launch the Gradio interface
iface.launch(share=True)