Delete app.py

app.py

@@ -1,98 +0,0 @@
-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)