import gradio as gr
import pandas as pd
from course_search import CourseSearchSystem

# Initialize the search system
df = pd.read_csv('course_data.csv')
search_system = CourseSearchSystem()
search_system.load_and_prepare_data(df)

def search_courses(query: str, num_results: int) -> str:
    """Search function for Gradio interface"""
    if not query.strip():
        return "Please enter a search query to find relevant courses!"
    
    return search_system.search_courses(query, top_k=num_results)

# Create Gradio interface
with gr.Blocks(title="Analytics Vidhya Free Course Search") as iface:
    gr.Markdown("""
    # 📚 Analytics Vidhya Free Course Search
    Find the perfect free course from Analytics Vidhya's collection using natural language search.
    Simply describe what you're looking for!
    """)
    
    with gr.Row():
        with gr.Column():
            query_input = gr.Textbox(
                label="What would you like to learn?",
                placeholder="E.g., 'machine learning for beginners' or 'computer vision projects'",
                lines=2
            )
            num_results = gr.Slider(
                minimum=1,
                maximum=10,
                value=3,
                step=1,
                label="Number of results to show"
            )
            search_button = gr.Button("🔍 Search Courses", variant="primary")
        
    output = gr.Markdown(label="Search Results")
    
    search_button.click(
        fn=search_courses,
        inputs=[query_input, num_results],
        outputs=output
    )
    
    gr.Markdown("""
    ---
    Made with ❤️ using Sentence Transformers and Gradio
    """)

if __name__ == "__main__":
    iface.launch()