Update app.py

app.py

@@ -1,144 +1,25 @@
-import gradio as gr
-import pandas as pd
-import json
-import os
-import re
-from PyPDF2 import PdfReader
-from collections import defaultdict
-
-# ========== TRANSCRIPT PARSING FUNCTIONS ==========
-def extract_courses_with_grade_levels(text):
-    grade_level_pattern = r"(Grade|Year)\s*[:]?\s*(\d+|Freshman|Sophomore|Junior|Senior)"
-    grade_match = re.search(grade_level_pattern, text, re.IGNORECASE)
-    current_grade_level = grade_match.group(2) if grade_match else "Unknown"
-
-    course_pattern = r"""
-        (?:^|\n)
-        (?: (Grade|Year)\s*[:]?\s*(\d+|Freshman|Sophomore|Junior|Senior)\s*[\n-]* )?
-        (
-            (?:[A-Z]{2,}\s?\d{3})
-            |
-            [A-Z][a-z]+(?:\s[A-Z][a-z]+)*
-        )
-        \s*
-        (?: [:\-]?\s* ([A-F][+-]?|\d{2,3}%)? )?
-    """
-
-    courses_by_grade = defaultdict(list)
-    current_grade = current_grade_level
-
-    for match in re.finditer(course_pattern, text, re.VERBOSE | re.MULTILINE):
-        grade_context, grade_level, course, grade = match.groups()
-
-        if grade_context:
-            current_grade = grade_level
-
-        if course:
-            course_info = {"course": course.strip()}
-            if grade:
-                course_info["grade"] = grade.strip()
-            courses_by_grade[current_grade].append(course_info)
-
-    return dict(courses_by_grade)
-
-def parse_transcript(file):
-    if file.name.endswith('.csv'):
-        df = pd.read_csv(file)
-    elif file.name.endswith('.xlsx'):
-        df = pd.read_excel(file)
-    elif file.name.endswith('.pdf'):
-        text = ''
-        reader = PdfReader(file)
-        for page in reader.pages:
-            page_text = page.extract_text()
-            if page_text:
-                text += page_text + '\n'
-
-        # Grade level extraction
-        grade_match = re.search(r'(Grade|Year)[\s:]*(\d+|Freshman|Sophomore|Junior|Senior)', text, re.IGNORECASE)
-        grade_level = grade_match.group(2) if grade_match else "Unknown"
-
-        # Enhanced GPA extraction
-        gpa_data = {'weighted': "N/A", 'unweighted': "N/A"}
-        gpa_patterns = [
-            r'Weighted GPA[\s:]*(\d\.\d{1,2})',
-            r'GPA \(Weighted\)[\s:]*(\d\.\d{1,2})',
-            r'Cumulative GPA \(Weighted\)[\s:]*(\d\.\d{1,2})',
-            r'Unweighted GPA[\s:]*(\d\.\d{1,2})',
-            r'GPA \(Unweighted\)[\s:]*(\d\.\d{1,2})',
-            r'Cumulative GPA \(Unweighted\)[\s:]*(\d\.\d{1,2})',
-            r'GPA[\s:]*(\d\.\d{1,2})'
-        ]
-        for pattern in gpa_patterns:
-            for match in re.finditer(pattern, text, re.IGNORECASE):
-                gpa_value = match.group(1)
-                if 'weighted' in pattern.lower():
-                    gpa_data['weighted'] = gpa_value
-                elif 'unweighted' in pattern.lower():
-                    gpa_data['unweighted'] = gpa_value
-                else:
-                    if gpa_data['unweighted'] == "N/A":
-                        gpa_data['unweighted'] = gpa_value
-                    if gpa_data['weighted'] == "N/A":
-                        gpa_data['weighted'] = gpa_value
-
-        courses_by_grade = extract_courses_with_grade_levels(text)
-
-        output_text = f"Grade Level: {grade_level}\n\n"
-        if gpa_data['weighted'] != "N/A" or gpa_data['unweighted'] != "N/A":
-            output_text += "GPA Information:\n"
-            if gpa_data['unweighted'] != "N/A":
-                output_text += f"- Unweighted GPA: {gpa_data['unweighted']}\n"
-            if gpa_data['weighted'] != "N/A":
-                output_text += f"- Weighted GPA: {gpa_data['weighted']}\n"
-        else:
-            output_text += "No GPA information found\n"
-
-        output_text += "\n(Courses not shown here)"
-
-        return output_text, {
-            "gpa": gpa_data,
-            "grade_level": grade_level,
-            "courses": courses_by_grade
-        }
-    else:
-        return "Unsupported file format", None
-
-    # For CSV/XLSX fallback
-    gpa = "N/A"
-    for col in ['GPA', 'Grade Point Average', 'Cumulative GPA']:
-        if col in df.columns:
-            gpa = df[col].iloc[0] if isinstance(df[col].iloc[0], (float, int)) else "N/A"
-            break
-
-    grade_level = "N/A"
-    for col in ['Grade Level', 'Grade', 'Class', 'Year']:
-        if col in df.columns:
-            grade_level = df[col].iloc[0]
-            break
-
-    courses = []
-    for col in ['Course', 'Subject', 'Course Name', 'Class']:
-        if col in df.columns:
-            courses = df[col].tolist()
-            break
-
-    output_text = f"Grade Level: {grade_level}\nGPA: {gpa}\n\nCourses:\n"
-    output_text += "\n".join(f"- {course}" for course in courses)
-
-    return output_text, {
-        "gpa": {"unweighted": gpa, "weighted": "N/A"},
-        "grade_level": grade_level,
-        "courses": courses
-    }
-
 # ========== 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 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 = [
@@ -146,7 +27,22 @@ learning_style_options = [
     ["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)"]
+    ["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 head (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):
@@ -168,228 +64,54 @@ def learning_style_quiz(*answers):
             scores["Kinesthetic"] += 1
     
     max_score = max(scores.values())
-    dominant_styles = [style for style, score in scores.items() if score == max_score]
+    total_questions = len(learning_style_questions)
     
-    if len(dominant_styles) == 1:
-        return f"Your primary learning style is: {dominant_styles[0]}"
-    else:
-        return f"You have multiple strong learning styles: {', '.join(dominant_styles)}"
-
-# ========== SAVE STUDENT PROFILE FUNCTION ==========
-def save_profile(name, age, interests, transcript, learning_style, movie, movie_reason, show, show_reason, book, book_reason, character, character_reason, blog):
-    # Convert age to int if it's a numpy number (from gradio Number input)
-    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
-
-def transcript_display(transcript_dict):
-    if not transcript_dict:
-        return "No transcript uploaded."
-    if isinstance(transcript_dict, dict) and "courses" in transcript_dict:
-        if isinstance(transcript_dict["courses"], dict):
-            display = ""
-            for grade_level, courses in transcript_dict["courses"].items():
-                display += f"\n**Grade {grade_level}**\n"
-                for course in courses:
-                    display += f"- {course['course']}"
-                    if 'grade' in course:
-                        display += f" (Grade: {course['grade']})"
-                    display += "\n"
-            return display
-        elif isinstance(transcript_dict["courses"], list):
-            return "\n".join([f"- {course}" for course in transcript_dict["courses"]])
-    return "No course information available"
-
-# ========== 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."
+    # Calculate percentages
+    percentages = {style: (score/total_questions)*100 for style, score in scores.items()}
     
-    # Get profile data
-    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", "")
+    # Sort styles by score (descending)
+    sorted_styles = sorted(scores.items(), key=lambda x: x[1], reverse=True)
     
-    # Common responses
-    greetings = ["hi", "hello", "hey"]
-    study_help = ["study", "learn", "prepare", "exam"]
-    grade_help = ["grade", "gpa", "score"]
-    interest_help = ["interest", "hobby", "passion"]
+    # Prepare detailed results
+    result = "Your Learning Style Results:\n\n"
+    for style, score in sorted_styles:
+        result += f"{style}: {score}/{total_questions} ({percentages[style]:.1f}%)\n"
     
-    if any(greet in message.lower() for greet in greetings):
-        return f"Hello {profile.get('name', 'there')}! How can I help you today?"
+    result += "\n"
     
-    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 "help" in message.lower():
-        return ("I can help with:\n"
-               "- Study tips based on your learning style\n"
-               "- GPA and grade information\n"
-               "- General academic advice\n\n"
-               "Try asking about study strategies or your grades!")
+    # Determine primary and secondary styles
+    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"
+        # Add personalized tips based on primary style
+        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:  # Kinesthetic
+            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:
-        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"):
-        transcript_file = gr.File(label="Upload your transcript (CSV, Excel, or PDF)")
-        transcript_output = gr.Textbox(label="Transcript Output")
-        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")
-        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="Learning Style Result")
-        gr.Button("Submit Quiz").click(
-            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
-        )
-
-    # AI Teaching Assistant Tab
-    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?",
-                "Help me with study strategies",
-                "How can I improve my grades?"
-            ]
-        )
-
-if __name__ == "__main__":
-    app.launch()
+        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