Update app.py

app.py

@@ -1,16 +1,16 @@
-# ========== STARTUP DEPENDENCY CHECK ==========
+# ========== DEPENDENCY MANAGEMENT ==========
 import sys
 import subprocess
 import importlib
 
-# List of required packages with their import names and pip names
+# List of required packages
 required_packages = {
-    'gradio': 'gradio',
+    'gradio': 'gradio>=3.0',
     'pandas': 'pandas',
     'PyPDF2': 'PyPDF2',
     'transformers': 'transformers',
     'pdfplumber': 'pdfplumber',
-    'typing_extensions': 'typing_extensions'  # Often needed for transformers
+    'typing_extensions': 'typing_extensions'
 }
 
 def check_and_install_packages():
@@ -24,20 +24,15 @@ def check_and_install_packages():
     if missing_packages:
         print(f"Missing packages: {', '.join(missing_packages)}")
         print("Attempting to install...")
-        
         try:
             subprocess.check_call([sys.executable, "-m", "pip", "install", *missing_packages])
-            print("Installation successful. Please restart the application.")
-            sys.exit(0)
+            print("Installation successful.")
         except subprocess.CalledProcessError as e:
             print(f"Failed to install packages. Error: {e}")
-            print("Please install them manually with:")
-            print(f"pip install {' '.join(missing_packages)}")
-            sys.exit(1)
 
 check_and_install_packages()
 
-# ========== MAIN IMPORTS (AFTER DEPENDENCY CHECK) ==========
+# ========== MAIN IMPORTS ==========
 import gradio as gr
 import pandas as pd
 import json
@@ -49,14 +44,650 @@ from transformers import pipeline
 from typing import List, Dict, Union
 import pdfplumber
 
-[... REST OF YOUR ORIGINAL CODE REMAINS EXACTLY THE SAME ...]
+# ========== TRANSCRIPT PARSING ==========
+class UniversalTranscriptParser:
+    def __init__(self):
+        self.patterns = {
+            'miami_dade': self._compile_miami_dade_patterns(),
+            'homeschool': self._compile_homeschool_patterns(),
+            'doral_academy': self._compile_doral_academy_patterns()
+        }
+        
+        self.grade_level_map = {
+            '09': '9th Grade', '10': '10th Grade', '11': '11th Grade', '12': '12th Grade',
+            '07': '7th Grade', '08': '8th Grade', 'MA': 'Middle School'
+        }
+    
+    def parse_transcript(self, text: str) -> Dict[str, Union[Dict, List[Dict]]]:
+        transcript_type = self._identify_transcript_type(text)
+        
+        if transcript_type == 'homeschool':
+            return self._parse_homeschool(text)
+        elif transcript_type == 'doral_academy':
+            return self._parse_doral_academy(text)
+        else:
+            return self._parse_miami_dade(text)
+    
+    def _identify_transcript_type(self, text: str) -> str:
+        if re.search(r'Sample OFFICIAL HIGH SCHOOL TRANSCRIPT', text):
+            return 'homeschool'
+        elif re.search(r'DORAL ACADEMY HIGH SCHOOL', text):
+            return 'doral_academy'
+        return 'miami_dade'
+    
+    def _parse_homeschool(self, text: str) -> Dict[str, Union[Dict, List[Dict]]]:
+        courses = []
+        current_grade = None
+        current_year = None
+        
+        student_info = {}
+        name_match = re.search(r'Student Name:\s*(.+)\s*SSN:', text)
+        if name_match:
+            student_info['name'] = name_match.group(1).strip()
+        
+        for line in text.split('\n'):
+            grade_match = re.match(r'^\|?\s*(\d+th Grade)\s*\|.*(\d{4}-\d{4})', line)
+            if grade_match:
+                current_grade = grade_match.group(1)
+                current_year = grade_match.group(2)
+                continue
+            
+            course_match = re.match(
+                r'^\|?\s*([^\|]+?)\s*\|\s*([A-Z][+*]?)\s*\|\s*([^\|]+)\s*\|\s*(\d+\.?\d*)\s*\|\s*(\d+)',
+                line
+            )
+            
+            if course_match and current_grade:
+                course_name = course_match.group(1).strip()
+                course_name = re.sub(r'^\|?\s*', '', course_name)
+                
+                courses.append({
+                    'name': course_name,
+                    'grade_level': current_grade,
+                    'school_year': current_year,
+                    'grade': course_match.group(2),
+                    'credit_type': course_match.group(3).strip(),
+                    'credits': float(course_match.group(4)),
+                    'quality_points': int(course_match.group(5)),
+                    'transcript_type': 'homeschool'
+                })
+        
+        gpa_data = {}
+        gpa_match = re.search(r'Cum\. GPA\s*\|\s*([\d\.]+)', text)
+        if gpa_match:
+            gpa_data['unweighted'] = gpa_match.group(1)
+            gpa_data['weighted'] = gpa_match.group(1)
+        
+        return {
+            'student_info': student_info,
+            'courses': {'All': courses},
+            'gpa': gpa_data,
+            'grade_level': current_grade.replace('th Grade', '') if current_grade else "Unknown"
+        }
+    
+    def _parse_doral_academy(self, text: str) -> Dict[str, Union[Dict, List[Dict]]]:
+        courses = []
+        student_info = {}
+        name_match = re.search(r'LEGAL NAME:\s*([^\n]+)', text)
+        if name_match:
+            student_info['name'] = name_match.group(1).strip()
+        
+        year_pattern = re.compile(r'YEAR:\s*(\d{4}-\d{4})\s*GRADE LEVEL:\s*(\d{2})', re.MULTILINE)
+        year_matches = year_pattern.finditer(text)
+        
+        grade_year_map = {}
+        for match in year_matches:
+            grade_year_map[match.group(2)] = match.group(1)
+        
+        course_pattern = re.compile(
+            r'(\d)\s+(\d{7})\s+([^\n]+?)\s+([A-Z]{2})\s+([A-Z])\s+([A-Z])\s+([A-Z])\s+(\d\.\d{2})\s+(\d\.\d{2})',
+            re.MULTILINE
+        )
+        
+        courses_by_grade = defaultdict(list)
+        for match in course_pattern.finditer(text):
+            grade_level_num = match.group(1)
+            grade_level = self.grade_level_map.get(grade_level_num, f"Grade {grade_level_num}")
+            school_year = grade_year_map.get(grade_level_num, "Unknown")
+            
+            course_info = {
+                'course_code': match.group(2),
+                'name': match.group(3).strip(),
+                'subject_area': match.group(4),
+                'grade': match.group(5),
+                'inclusion_status': match.group(6),
+                'credit_status': match.group(7),
+                'credits_attempted': float(match.group(8)),
+                'credits': float(match.group(9)),
+                'grade_level': grade_level,
+                'school_year': school_year,
+                'transcript_type': 'doral_academy'
+            }
+            
+            courses_by_grade[grade_level_num].append(course_info)
+        
+        gpa_data = {}
+        unweighted_match = re.search(r'Un-weighted GPA\s*([\d\.]+)', text)
+        weighted_match = re.search(r'Weighted GPA\s*([\d\.]+)', text)
+        
+        if unweighted_match:
+            gpa_data['unweighted'] = unweighted_match.group(1)
+        if weighted_match:
+            gpa_data['weighted'] = weighted_match.group(1)
+        
+        grade_level = "12" if re.search(r'GRADE LEVEL:\s*12', text) else "Unknown"
+        
+        return {
+            'student_info': student_info,
+            'courses': dict(courses_by_grade),
+            'gpa': gpa_data,
+            'grade_level': grade_level
+        }
+    
+    def _parse_miami_dade(self, text: str) -> Dict[str, Union[Dict, List[Dict]]]:
+        courses = []
+        courses_by_grade = defaultdict(list)
+        
+        student_info = {}
+        name_match = re.search(r'0783977 - ([^,]+),\s*([^\n]+)', text)
+        if name_match:
+            student_info['name'] = f"{name_match.group(2)} {name_match.group(1)}"
+        
+        course_pattern = re.compile(
+            r'([A-Z]-[A-Za-z\s&]+)\s*\|\s*(\d{4}-\d{4})\s*\|\s*(\d{2})\s*\|\s*([A-Z0-9]+)\s*\|\s*([^\|]+)\s*\|\s*([^\|]+)\s*\|\s*([^\|]+)\s*\|\s*([A-Z]?)\s*\|\s*([A-Z]?)\s*\|\s*([^\|]+)',
+            re.MULTILINE
+        )
+        
+        for match in course_pattern.finditer(text):
+            grade_level = self.grade_level_map.get(match.group(3), match.group(3))
+            credits = match.group(10).strip()
+            
+            course_info = {
+                'requirement_category': match.group(1).strip(),
+                'school_year': match.group(2),
+                'grade_level': grade_level if isinstance(grade_level, str) else f"Grade {match.group(3)}",
+                'course_code': match.group(4).strip(),
+                'name': match.group(5).strip(),
+                'term': match.group(6).strip(),
+                'district_number': match.group(7).strip(),
+                'grade': match.group(8),
+                'inclusion_status': match.group(9),
+                'credits': 0.0 if 'inProgress' in credits else float(credits.replace(' ', '')),
+                'transcript_type': 'miami_dade'
+            }
+            
+            courses_by_grade[match.group(3)].append(course_info)
+        
+        gpa_data = {
+            'weighted': extract_gpa(text, 'Weighted GPA'),
+            'unweighted': extract_gpa(text, 'Un-weighted GPA')
+        }
+        
+        grade_level = re.search(r'Current Grade:\s*(\d+)', text).group(1) if re.search(r'Current Grade:\s*(\d+)', text) else "Unknown"
+        
+        return {
+            'student_info': student_info,
+            'courses': dict(courses_by_grade),
+            'gpa': gpa_data,
+            'grade_level': grade_level
+        }
+
+    def _compile_miami_dade_patterns(self):
+        return {
+            'student': re.compile(r'Current Grade:\s*(\d+).*YOG\s*(\d{4})'),
+            'course': re.compile(
+                r'([A-Z]-[A-Za-z\s&]+)\s*\|\s*(\d{4}-\d{4})\s*\|\s*(\d{2})\s*\|\s*([A-Z0-9]+)\s*\|\s*([^\|]+)\s*\|\s*([^\|]+)\s*\|\s*([^\|]+)\s*\|\s*([A-Z]?)\s*\|\s*([A-Z]?)\s*\|\s*([^\|]+)',
+                re.MULTILINE
+            )
+        }
+
+    def _compile_homeschool_patterns(self):
+        return {
+            'student': re.compile(r'Student Name:\s*(.+)\s*SSN:'),
+            'course': re.compile(
+                r'^\|?\s*([^\|]+?)\s*\|\s*([A-Z][+*]?)\s*\|\s*([^\|]+)\s*\|\s*(\d+\.?\d*)\s*\|\s*(\d+)'
+            )
+        }
+
+    def _compile_doral_academy_patterns(self):
+        return {
+            'student': re.compile(r'LEGAL NAME:\s*([^\n]+)'),
+            'course': re.compile(
+                r'(\d)\s+(\d{7})\s+([^\n]+?)\s+([A-Z]{2})\s+([A-Z])\s+([A-Z])\s+([A-Z])\s+(\d\.\d{2})\s+(\d\.\d{2})',
+                re.MULTILINE
+            )
+        }
+
+def extract_gpa(text, gpa_type):
+    pattern = rf'{gpa_type}\s*([\d\.]+)'
+    match = re.search(pattern, text)
+    return match.group(1) if match else "N/A"
+
+def parse_transcript(file):
+    parser = UniversalTranscriptParser()
+    
+    if file.name.endswith('.pdf'):
+        text = ''
+        with pdfplumber.open(file.name) as pdf:
+            for page in pdf.pages:
+                text += page.extract_text() or '' + '\n'
+        
+        parsed_data = parser.parse_transcript(text)
+        
+        output_text = f"Student Transcript Summary\n{'='*40}\n"
+        
+        if 'student_info' in parsed_data and 'name' in parsed_data['student_info']:
+            output_text += f"Student: {parsed_data['student_info']['name']}\n"
+        
+        output_text += f"Current Grade Level: {parsed_data.get('grade_level', 'Unknown')}\n"
+        
+        if 'gpa' in parsed_data:
+            gpa = parsed_data['gpa']
+            output_text += f"Weighted GPA: {gpa.get('weighted', 'N/A')}\n"
+            output_text += f"Unweighted GPA: {gpa.get('unweighted', 'N/A')}\n\n"
+        
+        output_text += "Course History:\n{'='*40}\n"
+        
+        if 'courses' in parsed_data:
+            courses_by_grade = parsed_data['courses']
+            
+            def grade_sort_key(grade):
+                try:
+                    num = int(re.search(r'\d+', grade).group())
+                    return num
+                except (AttributeError, ValueError):
+                    return float('inf')
+            
+            grades_sorted = sorted(courses_by_grade.keys(), key=grade_sort_key)
+            
+            for grade in grades_sorted:
+                output_text += f"\nGrade {grade}:\n{'-'*30}\n"
+                for course in courses_by_grade[grade]:
+                    output_text += f"- {course.get('name', 'Unnamed Course')}"
+                    if 'grade' in course and course['grade']:
+                        output_text += f" (Grade: {course['grade']})"
+                    if 'credits' in course:
+                        output_text += f" | Credits: {course['credits']}"
+                    if 'school_year' in course:
+                        output_text += f" | Year: {course['school_year']}"
+                    output_text += "\n"
+        
+        return output_text, parsed_data
+    else:
+        return "Unsupported file format (PDF only for transcript parsing)", None
+
+def transcript_display(transcript_dict):
+    if not transcript_dict or "courses" not in transcript_dict:
+        return "No course information available"
+    
+    display = "### Detailed Course History\n"
+    courses_by_grade = transcript_dict["courses"]
+    
+    if isinstance(courses_by_grade, dict):
+        def grade_sort_key(grade):
+            try:
+                num = int(re.search(r'\d+', grade).group())
+                return num
+            except (AttributeError, ValueError):
+                return float('inf')
+        
+        grades_sorted = sorted(courses_by_grade.keys(), key=grade_sort_key)
+        
+        for grade in grades_sorted:
+            display += f"\n**Grade {grade}**\n"
+            for course in courses_by_grade[grade]:
+                display += f"- {course.get('name', 'Unnamed Course')}"
+                if 'grade' in course and course['grade']:
+                    display += f" (Grade: {course['grade']})"
+                if 'credits' in course:
+                    display += f" | Credits: {course['credits']}"
+                if 'school_year' in course:
+                    display += f" | Year: {course['school_year']}"
+                display += "\n"
+    
+    if 'gpa' in transcript_dict:
+        gpa = transcript_dict['gpa']
+        display += "\n**GPA Information**\n"
+        display += f"- Unweighted: {gpa.get('unweighted', 'N/A')}\n"
+        display += f"- Weighted: {gpa.get('weighted', 'N/A')}\n"
+    
+    return display
+
+# ========== LEARNING STYLE QUIZ ==========
+learning_style_questions = [
+    "When you study for a test, you prefer to:",
+    "When you need directions to a new place, you prefer:",
+    "When you learn a new skill, you prefer to:",
+    "When you're trying to concentrate, you:",
+    "When you meet new people, you remember them by:",
+    "When you're assembling furniture or a gadget, you:",
+    "When choosing a restaurant, you rely most on:",
+    "When you're in a waiting room, you typically:",
+    "When giving someone instructions, you tend to:",
+    "When you're trying to recall information, you:",
+    "When you're at a museum or exhibit, you:",
+    "When you're learning a new language, you prefer:",
+    "When you're taking notes in class, you:",
+    "When you're explaining something complex, you:",
+    "When you're at a party, you enjoy:",
+    "When you're trying to remember a phone number, you:",
+    "When you're relaxing, you prefer to:",
+    "When you're learning to use new software, you:",
+    "When you're giving a presentation, you rely on:",
+    "When you're solving a difficult problem, you:"
+]
+
+learning_style_options = [
+    ["Read the textbook (Reading/Writing)", "Listen to lectures (Auditory)", "Use diagrams/charts (Visual)", "Practice problems (Kinesthetic)"],
+    ["Look at a map (Visual)", "Have someone tell you (Auditory)", "Write down directions (Reading/Writing)", "Try walking/driving there (Kinesthetic)"],
+    ["Read instructions (Reading/Writing)", "Have someone show you (Visual)", "Listen to explanations (Auditory)", "Try it yourself (Kinesthetic)"],
+    ["Need quiet (Reading/Writing)", "Need background noise (Auditory)", "Need to move around (Kinesthetic)", "Need visual stimulation (Visual)"],
+    ["Their face (Visual)", "Their name (Auditory)", "What you talked about (Reading/Writing)", "What you did together (Kinesthetic)"],
+    ["Read the instructions carefully (Reading/Writing)", "Look at the diagrams (Visual)", "Ask someone to explain (Auditory)", "Start putting pieces together (Kinesthetic)"],
+    ["Online photos of the food (Visual)", "Recommendations from friends (Auditory)", "Reading the menu online (Reading/Writing)", "Remembering how it felt to eat there (Kinesthetic)"],
+    ["Read magazines (Reading/Writing)", "Listen to music (Auditory)", "Watch TV (Visual)", "Fidget or move around (Kinesthetic)"],
+    ["Write them down (Reading/Writing)", "Explain verbally (Auditory)", "Demonstrate (Visual)", "Guide them physically (Kinesthetic)"],
+    ["See written words in your mind (Visual)", "Hear the information in your head (Auditory)", "Write it down to remember (Reading/Writing)", "Associate it with physical actions (Kinesthetic)"],
+    ["Read all the descriptions (Reading/Writing)", "Listen to audio guides (Auditory)", "Look at the displays (Visual)", "Touch interactive exhibits (Kinesthetic)"],
+    ["Study grammar rules (Reading/Writing)", "Listen to native speakers (Auditory)", "Use flashcards with images (Visual)", "Practice conversations (Kinesthetic)"],
+    ["Write detailed paragraphs (Reading/Writing)", "Record the lecture (Auditory)", "Draw diagrams and charts (Visual)", "Doodle while listening (Kinesthetic)"],
+    ["Write detailed steps (Reading/Writing)", "Explain verbally with examples (Auditory)", "Draw diagrams (Visual)", "Use physical objects to demonstrate (Kinesthetic)"],
+    ["Conversations with people (Auditory)", "Watching others or the environment (Visual)", "Writing notes or texting (Reading/Writing)", "Dancing or physical activities (Kinesthetic)"],
+    ["See the numbers in your mind (Visual)", "Say them aloud (Auditory)", "Write them down (Reading/Writing)", "Dial them on a keypad (Kinesthetic)"],
+    ["Read a book (Reading/Writing)", "Listen to music (Auditory)", "Watch TV/movies (Visual)", "Do something physical (Kinesthetic)"],
+    ["Read the manual (Reading/Writing)", "Ask someone to show you (Visual)", "Call tech support (Auditory)", "Experiment with the software (Kinesthetic)"],
+    ["Detailed notes (Reading/Writing)", "Verbal explanations (Auditory)", "Visual slides (Visual)", "Physical demonstrations (Kinesthetic)"],
+    ["Write out possible solutions (Reading/Writing)", "Talk through it with someone (Auditory)", "Draw diagrams (Visual)", "Build a model or prototype (Kinesthetic)"]
+]
+
+def learning_style_quiz(*answers):
+    scores = {
+        "Visual": 0,
+        "Auditory": 0,
+        "Reading/Writing": 0,
+        "Kinesthetic": 0
+    }
+    
+    for i, answer in enumerate(answers):
+        if answer == learning_style_options[i][0]:
+            scores["Reading/Writing"] += 1
+        elif answer == learning_style_options[i][1]:
+            scores["Auditory"] += 1
+        elif answer == learning_style_options[i][2]:
+            scores["Visual"] += 1
+        elif answer == learning_style_options[i][3]:
+            scores["Kinesthetic"] += 1
+    
+    max_score = max(scores.values())
+    total_questions = len(learning_style_questions)
+    
+    percentages = {style: (score/total_questions)*100 for style, score in scores.items()}
+    
+    sorted_styles = sorted(scores.items(), key=lambda x: x[1], reverse=True)
+    
+    result = "Your Learning Style Results:\n\n"
+    for style, score in sorted_styles:
+        result += f"{style}: {score}/{total_questions} ({percentages[style]:.1f}%)\n"
+    
+    result += "\n"
+    
+    primary_styles = [style for style, score in scores.items() if score == max_score]
+    
+    if len(primary_styles) == 1:
+        result += f"Your primary learning style is: {primary_styles[0]}\n\n"
+        if primary_styles[0] == "Visual":
+            result += "Tips for Visual Learners:\n"
+            result += "- Use color coding in your notes\n"
+            result += "- Create mind maps and diagrams\n"
+            result += "- Watch educational videos\n"
+            result += "- Use flashcards with images\n"
+        elif primary_styles[0] == "Auditory":
+            result += "Tips for Auditory Learners:\n"
+            result += "- Record lectures and listen to them\n"
+            result += "- Participate in study groups\n"
+            result += "- Explain concepts out loud to yourself\n"
+            result += "- Use rhymes or songs to remember information\n"
+        elif primary_styles[0] == "Reading/Writing":
+            result += "Tips for Reading/Writing Learners:\n"
+            result += "- Write detailed notes\n"
+            result += "- Create summaries in your own words\n"
+            result += "- Read textbooks and articles\n"
+            result += "- Make lists to organize information\n"
+        else:
+            result += "Tips for Kinesthetic Learners:\n"
+            result += "- Use hands-on activities\n"
+            result += "- Take frequent movement breaks\n"
+            result += "- Create physical models\n"
+            result += "- Associate information with physical actions\n"
+    else:
+        result += f"You have multiple strong learning styles: {', '.join(primary_styles)}\n\n"
+        result += "You may benefit from combining different learning approaches.\n"
+    
+    return result
+
+# ========== SAVE STUDENT PROFILE ==========
+def save_profile(name, age, interests, transcript, learning_style, 
+                movie, movie_reason, show, show_reason, 
+                book, book_reason, character, character_reason, blog):
+    age = int(age) if age else 0
+    
+    favorites = {
+        "movie": movie,
+        "movie_reason": movie_reason,
+        "show": show,
+        "show_reason": show_reason,
+        "book": book,
+        "book_reason": book_reason,
+        "character": character,
+        "character_reason": character_reason
+    }
+    
+    data = {
+        "name": name,
+        "age": age,
+        "interests": interests,
+        "transcript": transcript,
+        "learning_style": learning_style,
+        "favorites": favorites,
+        "blog": blog
+    }
+    
+    os.makedirs("student_profiles", exist_ok=True)
+    json_path = os.path.join("student_profiles", f"{name.replace(' ', '_')}_profile.json")
+    with open(json_path, "w") as f:
+        json.dump(data, f, indent=2)
+
+    markdown_summary = f"""### Student Profile: {name}
+**Age:** {age}  
+**Interests:** {interests}  
+**Learning Style:** {learning_style}  
+#### Transcript:
+{transcript_display(transcript)}
+#### Favorites:
+- Movie: {favorites['movie']} ({favorites['movie_reason']})
+- Show: {favorites['show']} ({favorites['show_reason']})
+- Book: {favorites['book']} ({favorites['book_reason']})
+- Character: {favorites['character']} ({favorites['character_reason']})
+#### Blog:
+{blog if blog else "_No blog provided_"}
+"""
+    return markdown_summary
+
+# ========== AI TEACHING ASSISTANT ==========
+def load_profile():
+    if not os.path.exists("student_profiles"):
+        return {}
+    files = [f for f in os.listdir("student_profiles") if f.endswith('.json')]
+    if files:
+        with open(os.path.join("student_profiles", files[0]), "r") as f:
+            return json.load(f)
+    return {}
+
+def generate_response(message, history):
+    profile = load_profile()
+    if not profile:
+        return "Please complete and save your profile first using the previous tabs."
+    
+    learning_style = profile.get("learning_style", "")
+    grade_level = profile.get("transcript", {}).get("grade_level", "unknown")
+    gpa = profile.get("transcript", {}).get("gpa", {})
+    interests = profile.get("interests", "")
+    courses = profile.get("transcript", {}).get("courses", {})
+    
+    greetings = ["hi", "hello", "hey"]
+    study_help = ["study", "learn", "prepare", "exam"]
+    grade_help = ["grade", "gpa", "score"]
+    interest_help = ["interest", "hobby", "passion"]
+    course_help = ["courses", "classes", "transcript", "schedule"]
+    
+    if any(greet in message.lower() for greet in greetings):
+        return f"Hello {profile.get('name', 'there')}! How can I help you today?"
+    
+    elif any(word in message.lower() for word in study_help):
+        if "Visual" in learning_style:
+            response = ("Based on your visual learning style, I recommend:\n"
+                       "- Creating mind maps or diagrams\n"
+                       "- Using color-coded notes\n"
+                       "- Watching educational videos")
+        elif "Auditory" in learning_style:
+            response = ("Based on your auditory learning style, I recommend:\n"
+                       "- Recording lectures and listening to them\n"
+                       "- Participating in study groups\n"
+                       "- Explaining concepts out loud")
+        elif "Reading/Writing" in learning_style:
+            response = ("Based on your reading/writing learning style, I recommend:\n"
+                       "- Writing detailed notes\n"
+                       "- Creating summaries in your own words\n"
+                       "- Reading textbooks and articles")
+        elif "Kinesthetic" in learning_style:
+            response = ("Based on your kinesthetic learning style, I recommend:\n"
+                       "- Hands-on practice\n"
+                       "- Creating physical models\n"
+                       "- Taking frequent movement breaks")
+        else:
+            response = ("Here are some general study tips:\n"
+                       "- Break study sessions into 25-minute chunks\n"
+                       "- Review material regularly\n"
+                       "- Teach concepts to someone else")
+        
+        return response
+    
+    elif any(word in message.lower() for word in grade_help):
+        return (f"Your GPA information:\n"
+               f"- Unweighted: {gpa.get('unweighted', 'N/A')}\n"
+               f"- Weighted: {gpa.get('weighted', 'N/A')}\n\n"
+               "To improve your grades, try:\n"
+               "- Setting specific goals\n"
+               "- Meeting with teachers\n"
+               "- Developing a study schedule")
+    
+    elif any(word in message.lower() for word in interest_help):
+        return (f"I see you're interested in: {interests}\n\n"
+               "You might want to:\n"
+               "- Find clubs or activities related to these interests\n"
+               "- Explore career paths that align with them")
+    
+    elif any(word in message.lower() for word in course_help):
+        response = "Here's a summary of your courses:\n"
+        if isinstance(courses, dict):
+            def grade_sort_key(grade):
+                try:
+                    num = int(re.search(r'\d+', grade).group())
+                    return num
+                except (AttributeError, ValueError):
+                    return float('inf')
+            
+            grades_sorted = sorted(courses.keys(), key=grade_sort_key)
+            
+            for grade in grades_sorted:
+                response += f"\nGrade {grade}:\n"
+                for course in courses[grade]:
+                    response += f"- {course.get('name', 'Unnamed Course')}"
+                    if 'grade' in course:
+                        response += f" (Grade: {course['grade']})"
+                    response += "\n"
+        else:
+            response += "No detailed course information available."
+        return response
+    
+    elif "help" in message.lower():
+        return ("I can help with:\n"
+               "- Study tips based on your learning style\n"
+               "- GPA and grade information\n"
+               "- Course history and schedules\n"
+               "- General academic advice\n\n"
+               "Try asking about study strategies or your grades!")
+    
+    else:
+        return ("I'm your personalized teaching assistant. "
+               "I can help with study tips, grade information, and academic advice. "
+               "Try asking about how to study for your classes!")
+
+# ========== GRADIO INTERFACE ==========
+with gr.Blocks() as app:
+    with gr.Tab("Step 1: Upload Transcript"):
+        gr.Markdown("### Upload your transcript (PDF recommended)")
+        transcript_file = gr.File(label="Transcript file", file_types=[".pdf"])
+        transcript_output = gr.Textbox(label="Transcript Results", lines=20)
+        transcript_data = gr.State()
+        transcript_file.change(
+            fn=parse_transcript,
+            inputs=transcript_file,
+            outputs=[transcript_output, transcript_data]
+        )
+
+    with gr.Tab("Step 2: Learning Style Quiz"):
+        gr.Markdown("### Learning Style Quiz (20 Questions)")
+        quiz_components = []
+        for i, (question, options) in enumerate(zip(learning_style_questions, learning_style_options)):
+            quiz_components.append(gr.Radio(options, label=f"{i+1}. {question}"))
+        
+        learning_output = gr.Textbox(label="Your Learning Style", lines=15)
+        gr.Button("Submit Quiz").click(
+            fn=learning_style_quiz,
+            inputs=quiz_components,
+            outputs=learning_output
+        )
+
+    with gr.Tab("Step 3: Personal Questions"):
+        name = gr.Textbox(label="What's your name?")
+        age = gr.Number(label="How old are you?", precision=0)
+        interests = gr.Textbox(label="What are your interests?")
+        movie = gr.Textbox(label="Favorite movie?")
+        movie_reason = gr.Textbox(label="Why do you like that movie?")
+        show = gr.Textbox(label="Favorite TV show?")
+        show_reason = gr.Textbox(label="Why do you like that show?")
+        book = gr.Textbox(label="Favorite book?")
+        book_reason = gr.Textbox(label="Why do you like that book?")
+        character = gr.Textbox(label="Favorite character?")
+        character_reason = gr.Textbox(label="Why do you like that character?")
+        blog_checkbox = gr.Checkbox(label="Do you want to write a blog?", value=False)
+        blog_text = gr.Textbox(label="Write your blog here", visible=False, lines=5)
+        blog_checkbox.change(lambda x: gr.update(visible=x), inputs=blog_checkbox, outputs=blog_text)
+
+    with gr.Tab("Step 4: Save & Review"):
+        output_summary = gr.Markdown()
+        save_btn = gr.Button("Save Profile")
+        save_btn.click(
+            fn=save_profile,
+            inputs=[name, age, interests, transcript_data, learning_output,
+                   movie, movie_reason, show, show_reason,
+                   book, book_reason, character, character_reason, blog_text],
+            outputs=output_summary
+        )
+
+    with gr.Tab("🤖 AI Teaching Assistant"):
+        gr.Markdown("## Your Personalized Learning Assistant")
+        chatbot = gr.ChatInterface(
+            fn=generate_response,
+            examples=[
+                "How should I study for my next test?",
+                "What's my GPA information?",
+                "Show me my course history",
+                "How can I improve my grades?"
+            ]
+        )
 
+# ========== RUN APPLICATION ==========
 if __name__ == "__main__":
-    # Check if running in a notebook environment
-    try:
-        from IPython import get_ipython
-        if 'IPKernelApp' not in get_ipython().config:
-            app.launch()
-    except:
-        app.launch()
-        
+    app.launch()