app.py

import gradio as gr
import pickle
import pandas as pd
from sentence_transformers import SentenceTransformer
from sklearn.metrics.pairwise import cosine_similarity

# Load model and data
with open("course_emb.pkl", "rb") as f:
    course_emb = pickle.load(f)

df = pd.read_excel("analytics_vidhya_courses_Final.xlsx")
model = SentenceTransformer('all-MiniLM-L6-v2')

def search_courses(query, top_n=5):
    if not query.strip():
        return "Please enter a search query."
    
    query_embedding = model.encode([query])
    similarities = cosine_similarity(query_embedding, course_emb)
    top_n_idx = similarities[0].argsort()[-top_n:][::-1]
    
    results = []
    for idx in top_n_idx:
        course = df.iloc[idx]
        results.append({
            "title": course["Course Title"],
            "description": course["Course Description"],
            "similarity": float(similarities[0][idx])
        })
    return results

def gradio_interface(query):
    results = search_courses(query)
    if isinstance(results, str):
        return results
    
    # Format results as HTML for better presentation
    html_output = "<div style='font-family: Arial, sans-serif;'>"
    
    for i, course in enumerate(results, 1):
        relevance = int(course['similarity'] * 100)
        html_output += f"""
        <div style='background: white; padding: 15px; margin: 10px 0; border-radius: 10px; box-shadow: 0 2px 4px rgba(0,0,0,0.1);'>
            <h3 style='color: #2c3e50; margin: 0 0 10px 0;'>#{i}. {course['title']}</h3>
            <div style='color: #7f8c8d; font-size: 0.9em; margin-bottom: 8px;'>Relevance: {relevance}%</div>
            <p style='color: #34495e; margin: 0; line-height: 1.5;'>{course['description']}</p>
        </div>
        """
    
    html_output += "</div>"
    return html_output

# Create Gradio interface with improved styling
css = """
.gradio-container {
    font-family: 'Arial', sans-serif;
}
"""

with gr.Blocks(css=css) as iface:
    gr.Markdown(
        """
        # 🎓 EduPath Explorer
        Discover your ideal learning path! Simply describe what you want to learn, and let our AI find the perfect courses for you.
        """
    )
    
    with gr.Row():
        query_input = gr.Textbox(
            label="Describe Your Learning Goals",
            placeholder="e.g., 'data visualization fundamentals' or 'deep learning with practical projects'",
            scale=4
        )
    
    with gr.Row():
        search_button = gr.Button("🎯 Find My Courses", variant="primary")
    
    with gr.Row():
        output = gr.HTML(label="Recommended Courses")
    
    search_button.click(
        fn=gradio_interface,
        inputs=query_input,
        outputs=output,
    )
    
    gr.Markdown(
        """
        ### 💡 Search Tips:
        - Mention your current expertise level
        - Include specific technologies or tools
        - Describe your end goals
        - Add preferred learning style (hands-on, theoretical, etc.)
        """
    )

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