Update app.py

app.py

@@ -1,13 +1,27 @@
+# Install dependencies (if needed)
+# !pip install gradio pandas scikit-learn
+
 import pandas as pd
 import gradio as gr
 from sklearn.feature_extraction.text import TfidfVectorizer
 from sklearn.metrics.pairwise import cosine_similarity
 
 # Load dataset
-df = pd.read_csv('mcq_dataset.csv')
+df = pd.read_csv("mcq_dataset.csv")
+
+# Clean domain/subdomain for consistent matching
+df['domain'] = df['domain'].astype(str).str.strip().str.lower()
+df['subdomain'] = df['subdomain'].astype(str).str.strip()
 
-# Core logic to retrieve top MCQs
+# Function to get top N MCQs using cosine similarity
 def get_top_mcqs(user_input, domain, subdomain, top_n=10):
+    if not domain or not subdomain:
+        return pd.DataFrame()
+
+    # Normalize input for comparison
+    domain = domain.strip().lower()
+    subdomain = subdomain.strip()
+
     filtered_df = df[(df['domain'] == domain) & (df['subdomain'] == subdomain)]
 
     if filtered_df.empty:
@@ -27,47 +41,52 @@ def get_top_mcqs(user_input, domain, subdomain, top_n=10):
 
     return top_questions.reset_index(drop=True)
 
-# Interactive quiz logic
+# Quiz execution logic
 def run_quiz(domain, subdomain, keyword_input):
-    try:
-        mcq_df = get_top_mcqs(keyword_input, domain, subdomain)
-
-        if mcq_df.empty:
-            return "⚠️ No questions found for the selected domain/subdomain."
-
-        quiz_output = ""
-        for i, row in mcq_df.iterrows():
-            quiz_output += f"Q{i+1}: {row['question']}\n"
-            quiz_output += f"A. {row['option1']}\n"
-            quiz_output += f"B. {row['option2']}\n"
-            quiz_output += f"C. {row['option3']}\n"
-            quiz_output += f"D. {row['option4']}\n"
-            quiz_output += f"(Correct Answer: {row['correct_answer']})\n\n"
-
-        return quiz_output
-    except Exception as e:
-        return f"❌ Runtime Error: {str(e)}"
-
-# Function to update subdomain choices
+    mcq_df = get_top_mcqs(keyword_input, domain, subdomain)
+
+    if mcq_df.empty:
+        return "⚠️ No questions found for the selected domain/subdomain."
+
+    quiz_output = ""
+    for i, row in mcq_df.iterrows():
+        quiz_output += f"Q{i+1}: {row['question']}\n"
+        quiz_output += f"A. {row['option1']}\n"
+        quiz_output += f"B. {row['option2']}\n"
+        quiz_output += f"C. {row['option3']}\n"
+        quiz_output += f"D. {row['option4']}\n"
+        quiz_output += f"(✅ Correct Answer: {row['correct_answer']})\n\n"
+
+    return quiz_output
+
+# Update subdomains dynamically
 def update_subdomains(domain):
-    subdomains = df[df["domain"] == domain]["subdomain"].dropna().astype(str).unique().tolist()
-    return gr.Dropdown.update(choices=sorted(subdomains))
+    if not domain:
+        return gr.Dropdown.update(choices=[], value=None)
+
+    domain = domain.strip().lower()
+    subdomains = df[df["domain"] == domain]["subdomain"].dropna().unique().tolist()
+    
+    if not subdomains:
+        subdomains = ["No Subdomains Available"]
+
+    return gr.Dropdown.update(choices=sorted(subdomains), value=subdomains[0])
 
 # Gradio UI
 with gr.Blocks() as demo:
     gr.Markdown("## 🧠 Domain-Based MCQ Quiz System")
 
     with gr.Row():
-        domain_dropdown = gr.Dropdown(label="Select Domain", choices=sorted(df['domain'].dropna().unique().tolist()))
-        subdomain_dropdown = gr.Dropdown(label="Select Subdomain", choices=[])
+        domain_dropdown = gr.Dropdown(label="Select Domain", choices=sorted(df['domain'].unique().tolist()))
+        subdomain_dropdown = gr.Dropdown(label="Select Subdomain")
 
     domain_dropdown.change(fn=update_subdomains, inputs=domain_dropdown, outputs=subdomain_dropdown)
 
     keyword_input = gr.Textbox(label="Enter keywords or topic")
     quiz_button = gr.Button("Get Top MCQs")
-    quiz_output = gr.Textbox(label="Quiz Questions", lines=20, interactive=False)
+    quiz_output = gr.Textbox(label="Quiz Questions", lines=20)
 
     quiz_button.click(fn=run_quiz, inputs=[domain_dropdown, subdomain_dropdown, keyword_input], outputs=quiz_output)
 
-# Launch the app
+# Launch app
 demo.launch()