Fix: Remove size parameter and improve error handling for dataset loading

app.py

@@ -1,120 +1,135 @@
 import gradio as gr
 import random
-import json
 from datasets import load_dataset
 
-try:
-    ds = load_dataset('Aiman1234/Interview-questions')
-    questions_data = ds['train']
-except:
-    questions_data = None
+questions_data = None
+
+def load_questions():
+    global questions_data
+    if questions_data is None:
+        try:
+            ds = load_dataset('Aiman1234/Interview-questions')
+            questions_data = ds['train']
+            return True
+        except Exception as e:
+            print(f"Error loading dataset: {e}")
+            return False
+    return True
 
 class InterviewBot:
     def __init__(self):
         self.current_question = None
         self.score = 0
         self.total_questions = 0
-        self.performance_notes = []
         self.answers_given = []
         
     def get_next_question(self, difficulty='Easy'):
-        if questions_data is None:
-            return "Dataset not available", "N/A", "N/A"
+        if not load_questions():
+            return "Failed to load questions. Please try again.", "N/A", "N/A"
         
-        filtered = [q for q in questions_data if q['level'] == difficulty]
-        if not filtered:
-            filtered = questions_data
+        try:
+            filtered = [q for q in questions_data if q['level'] == difficulty]
+            if not filtered:
+                filtered = list(questions_data)
+                
+            self.current_question = random.choice(filtered)
+            self.total_questions += 1
             
-        self.current_question = random.choice(filtered)
-        self.total_questions += 1
-        
-        return (
-            self.current_question['Questions'],
-            self.current_question['language'],
-            self.current_question['level']
-        )
+            return (
+                self.current_question['Questions'],
+                self.current_question['language'],
+                self.current_question['level']
+            )
+        except Exception as e:
+            return f"Error getting question: {str(e)}", "Error", "Error"
     
     def evaluate_answer(self, user_answer):
         if not self.current_question:
             return "Please get a question first!"
         
-        answer_length = len(user_answer.split())
-        correct_answer_length = len(self.current_question['Answers'].split())
-        
-        similarity = min(answer_length, correct_answer_length) / max(answer_length, correct_answer_length) if max(answer_length, correct_answer_length) > 0 else 0
-        
-        if similarity > 0.5:
-            feedback = f"Good effort! Your answer covers key points.\nExpected answer length: ~{correct_answer_length} words, Your answer: {answer_length} words"
-            self.score += 1
-        else:
-            feedback = f"Consider expanding your answer. Your response should be more detailed.\nExpected length: ~{correct_answer_length} words, Your answer: {answer_length} words"
-        
-        self.answers_given.append({
-            'question': self.current_question['Questions'],
-            'your_answer': user_answer,
-            'similarity': similarity,
-            'correct_answer': self.current_question['Answers']
-        })
-        
-        return feedback
+        try:
+            answer_length = len(user_answer.split())
+            correct_answer_length = len(self.current_question['Answers'].split())
+            
+            similarity = min(answer_length, correct_answer_length) / max(answer_length, correct_answer_length) if max(answer_length, correct_answer_length) > 0 else 0
+            
+            if similarity > 0.5:
+                feedback = f"Good effort! Your answer covers key points.\nExpected answer length: ~{correct_answer_length} words\nYour answer: {answer_length} words"
+                self.score += 1
+            else:
+                feedback = f"Consider expanding your answer. Your response should be more detailed.\nExpected length: ~{correct_answer_length} words\nYour answer: {answer_length} words"
+            
+            self.answers_given.append({
+                'question': self.current_question['Questions'],
+                'your_answer': user_answer,
+                'similarity': similarity
+            })
+            
+            return feedback
+        except Exception as e:
+            return f"Error evaluating answer: {str(e)}"
     
     def get_performance_analysis(self):
         if self.total_questions == 0:
             return "No questions answered yet!"
         
-        accuracy = (self.score / self.total_questions) * 100
-        
-        analysis = f"""
-        === PERFORMANCE ANALYSIS ===
-        
-        Total Questions: {self.total_questions}
-        Correct Answers: {self.score}
-        Accuracy: {accuracy:.1f}%
-        
-        STRENGTHS:
-        - You completed {self.total_questions} interview questions
-        - Your accuracy rate is {accuracy:.1f}%
-        
-        AREAS FOR IMPROVEMENT:
-        - Focus on providing detailed and structured answers
-        - Practice technical concepts and definitions
-        - Improve answer articulation and clarity
-        
-        RECOMMENDATIONS:
-        1. Review the expected answers for failed questions
-        2. Practice similar questions in your weak areas
-        3. Work on concise but comprehensive responses
-        4. Practice explaining complex concepts simply
-        """
-        
-        return analysis
+        try:
+            accuracy = (self.score / self.total_questions) * 100
+            
+            analysis = f"""
+PERFORMANCE ANALYSIS
+{'='*50}
+Total Questions Attempted: {self.total_questions}
+Correct Answers: {self.score}
+Accuracy Rate: {accuracy:.1f}%
+
+STRENGTHS:
+- Successfully completed {self.total_questions} interview questions
+- Current accuracy rate: {accuracy:.1f}%
+
+AREAS FOR IMPROVEMENT:
+- Focus on providing detailed and structured answers
+- Practice technical concepts and definitions
+- Improve answer clarity and completeness
+
+RECOMMENDATIONS:
+1. Review the expected answers for failed questions
+2. Practice similar questions in weak areas
+3. Work on concise but comprehensive responses
+4. Practice explaining complex concepts clearly
+"""
+            return analysis
+        except Exception as e:
+            return f"Error generating analysis: {str(e)}"
 
 bot = InterviewBot()
 
 def start_interview(difficulty):
-    question, language, level = bot.get_next_question(difficulty)
-    return f"Question ({language} - {level}): {question}"
+    try:
+        question, language, level = bot.get_next_question(difficulty)
+        return f"Question ({language} - {level}):\n{question}"
+    except Exception as e:
+        return f"Error: {str(e)}"
 
 def submit_answer(answer_text):
     if not answer_text.strip():
         return "Please provide an answer!"
-    evaluation = bot.evaluate_answer(answer_text)
-    return evaluation
+    return bot.evaluate_answer(answer_text)
 
 def show_analysis():
     return bot.get_performance_analysis()
 
 with gr.Blocks(title="AI Job Interview Bot - Computer Science") as demo:
     gr.Markdown("""
-    # AI Job Interview Bot for Computer Science
-    
-    Practice technical interview questions with AI-powered feedback!
-    
-    **Features:**
-    - 496+ real interview questions
-    - Multiple difficulty levels
-    - Performance analysis and feedback
-    - Identified strengths and weaknesses
+# AI Job Interview Bot for Computer Science
+
+Practice technical interview questions with AI-powered feedback!
+
+**Features:**
+- 496+ real interview questions
+- Multiple difficulty levels (Easy, Medium, Hard)
+- Real-time AI feedback on your answers
+- Performance analysis and recommendations
     """)
     
     with gr.Row():
@@ -132,7 +147,7 @@ with gr.Blocks(title="AI Job Interview Bot - Computer Science") as demo:
             question_display = gr.Textbox(
                 label="Question",
                 interactive=False,
-                lines=4
+                lines=5
             )
     
     with gr.Row():
@@ -155,11 +170,12 @@ with gr.Blocks(title="AI Job Interview Bot - Computer Science") as demo:
     
     with gr.Row():
         analysis_btn = gr.Button("Show Performance Analysis", variant="secondary")
-        analysis_display = gr.Textbox(
-            label="Performance Analysis",
-            interactive=False,
-            lines=15
-        )
+        
+    analysis_display = gr.Textbox(
+        label="Performance Analysis",
+        interactive=False,
+        lines=15
+    )
     
     start_btn.click(
         fn=start_interview,