Update app.py

app.py

@@ -1,406 +1,171 @@
 import gradio as gr
 import pandas as pd
-import PyPDF2
 import json
+import os
 import re
+from PyPDF2 import PdfReader
+
+# ========== TRANSCRIPT PARSING FUNCTIONS ==========
 
-# Parse uploaded transcript file
 def parse_transcript(file):
     if file.name.endswith('.csv'):
-        df = pd.read_csv(file.name)
-    elif file.name.endswith(('.xls', '.xlsx')):
-        df = pd.read_excel(file.name)
+        df = pd.read_csv(file)
+    elif file.name.endswith('.xlsx'):
+        df = pd.read_excel(file)
     elif file.name.endswith('.pdf'):
-        reader = PyPDF2.PdfReader(file)
-        text = ""
+        text = ''
+        reader = PdfReader(file)
         for page in reader.pages:
-            text += page.extract_text() or ""
-        df = pd.DataFrame({'Transcript_Text': [text]})
+            text += page.extract_text() + '\n'
+        return extract_info_from_pdf(text)
     else:
-        raise ValueError("Unsupported file format. Use .csv, .xlsx, or .pdf")
-    return df
-
-# Extract student info
-def extract_transcript_info(df):
-    transcript_text = df['Transcript_Text'].iloc[0] if 'Transcript_Text' in df.columns else ''
-    info = {}
-    gpa_match = re.search(r'(GPA|Grade Point Average)[^\d]*(\d+\.\d+)', transcript_text, re.IGNORECASE)
-    if gpa_match:
-        info['GPA'] = gpa_match.group(2)
-    grade_match = re.search(r'Grade:?[\s]*(\d{1,2})', transcript_text, re.IGNORECASE)
-    if grade_match:
-        info['Grade_Level'] = grade_match.group(1)
-    courses = re.findall(r'(?i)\b([A-Z][a-zA-Z\s&/]+)\s+(\d{1,3})\b', transcript_text)
-    if courses:
-        info['Courses'] = list(set([c[0].strip() for c in courses]))
-    return info
-
-# Learning style questions - from educationplanner.org
-learning_style_questions = [
-    "When you are learning something new, you prefer to:",
-    "When you are at home, you like to:",
-    "When you spell a word, you remember it by:",
-    "When you read, you:",
-    "When you write, you:",
-    "When you listen to music, you:",
-    "When you work at solving a problem, you:",
-    "When you give someone directions, you:",
-    "When you are concentrating, you:",
-    "When you meet someone new, you remember them by:"
-]
-
-learning_style_answers = [
-    ["Watch someone do it", "Listen to someone explain it", "Read about it"],
-    ["Watch TV or play video games", "Listen to music or talk to people", "Read books or write stories"],
-    ["Seeing the word in your mind", "Saying the word out loud", "Writing the word down"],
-    ["See the action in your mind", "Hear the characters talk", "Focus on the written words"],
-    ["Use diagrams or doodles", "Talk about ideas", "Write detailed notes"],
-    ["Appreciate the rhythm and melodies", "Easily remember lyrics", "Analyze the lyrics"],
-    ["Visualize the solution", "Discuss the problem", "Write out the steps"],
-    ["Draw a map", "Give spoken directions", "Write directions"],
-    ["Picture things", "Say things out loud", "Write or read quietly"],
-    ["Remember faces", "Remember names or voices", "Remember what you wrote about them"]
-]
-
-style_count_map = {0: "visual", 1: "auditory", 2: "reading/writing"}
-
-def learning_style_quiz(*answers):
-    scores = {'visual': 0, 'auditory': 0, 'reading/writing': 0}
-
-    for i, ans in enumerate(answers):
-        if i < len(learning_style_answers):
-            options = learning_style_answers[i]
-            if ans in options:
-                index = options.index(ans)
-                style = style_count_map[index]
-                scores[style] += 1
-
-    max_score = max(scores.values())
-    best_styles = [style.capitalize() for style, score in scores.items() if score == max_score]
-
-    return ", ".join(best_styles)
-
-# PanoramaEd categories and multiple choice questions
-get_to_know_categories = {
-    "All About Me": [
-        ("What's your favorite way to spend a day off?", []),
-        ("If you could only eat one food for the rest of your life, what would it be?", []),
-        ("Do you have any pets? If so, what are their names?", []),
-        ("If you could travel anywhere in the world, where would you go?", []),
-        ("What's your favorite holiday or tradition?", []),
-        ("What are some of your favorite movies or shows?", []),
-        ("Do you have a favorite book or book series? Why?", []),
-        ("Who is a character from a show, book, or movie that you relate to? Why?", []),
-        ("If you could be any fictional character, who would you be and why?", [])
-    ],
-    "Hopes and Dreams": [
-        ("What do you want to be when you grow up?", []),
-        ("What's something you hope to achieve this year?", []),
-        ("If you could change the world in one way, what would you do?", []),
-        ("What are you most proud of?", []),
-        ("What's a big dream you have for your future?", [])
-    ],
-    "School Life": [
-        ("What's your favorite subject in school?", []),
-        ("What's something that makes learning easier for you?", []),
-        ("Do you prefer working alone or in groups?", []),
-        ("What helps you feel confident in class?", []),
-        ("What's something you're good at in school?", [])
-    ],
-    "Relationships": [
-        ("Who do you look up to and why?", []),
-        ("Who is someone that makes you feel safe and supported?", []),
-        ("Do you have a best friend? What do you like to do together?", []),
-        ("What's one thing you wish people knew about you?", []),
-        ("What's something kind you've done for someone else?", [])
-    ]
-}
-
-# Generators for output summaries
-def generate_learning_plan(info):
-    level = info.get("Grade_Level", "unknown")
-    courses = info.get("Courses", [])
-    gpa = info.get("GPA", "N/A")
-    return f"""
-📘 **Personalized Learning Plan**
-- Grade Level: {level}
-- GPA: {gpa}
-- Suggested Focus Areas: {', '.join(courses[:3]) if courses else 'N/A'}
-- Goals: Strengthen key subjects, explore interests, and build study habits.
-"""
-
-def generate_learning_style_summary(style):
-    return f"""
-🧠 **Learning Style Summary**
-You are a **{style}** learner. That means you learn best through {"visual aids like charts and images" if "Visual" in style else "listening and verbal instruction" if "Auditory" in style else "reading and writing-based methods"}.
-"""
-
-def generate_motivation_section(responses):
-    hopes = [ans for q, ans in responses.items() if "hope" in q.lower() or "dream" in q.lower()]
-    return f"""
-💡 **Motivational Summary**
-Your dreams are powerful: {'; '.join(hopes) if hopes else 'You are filled with potential!'}. 
-Believe in yourself and keep moving forward.
-"""
-
-# Save all answers into profile
-def save_profile(file, *inputs):
-    if not file:
-        return "⚠️ Please upload your transcript."
-
-    quiz_answers = inputs[:len(learning_style_questions)]
-    if any(ans is None for ans in quiz_answers):
-        return "⚠️ Please answer all the learning style questions."
-
-    blog_checkbox = inputs[len(learning_style_questions)]
-    blog_text = inputs[len(learning_style_questions)+1]
-    category_answers = inputs[len(learning_style_questions)+2:]
-
-    if any(ans.strip() == "" for ans in category_answers):
-        return "⚠️ Please complete all 'Get to Know You' sections before saving."
+        return "Unsupported file format", None
 
-    if blog_checkbox and blog_text.strip() == "":
-        return "⚠️ You checked the blog option but didn't write anything. Please write your mini blog or uncheck the option."
+    courses = df['Course'].tolist() if 'Course' in df.columns else []
+    grades = df['Grade'].tolist() if 'Grade' in df.columns else []
+    gpa = df['GPA'].mean() if 'GPA' in df.columns else "N/A"
 
-    df = parse_transcript(file)
-    transcript_info = extract_transcript_info(df)
-    learning_type = learning_style_quiz(*quiz_answers)
-
-    question_texts = [q for cat in get_to_know_categories.values() for q, _ in cat]
-    responses = dict(zip(question_texts, category_answers))
-
-    profile = {
-        "transcript": df.to_dict(orient='records'),
-        "transcript_info": transcript_info,
-        "learning_style": learning_type,
-        "get_to_know_answers": responses,
-        "blog": blog_text if blog_checkbox else "[User chose to skip this section]"
+    course_info = "\n".join([f"{c}: {g}" for c, g in zip(courses, grades)])
+    return f"Transcript Parsed:\n\n{course_info}\n\nGPA: {gpa}", {
+        "courses": courses,
+        "grades": grades,
+        "gpa": gpa
     }
 
-    summary = {
-        "Learning_Plan": generate_learning_plan(transcript_info),
-        "Style_Summary": generate_learning_style_summary(learning_type),
-        "Motivation": generate_motivation_section(responses)
+def extract_info_from_pdf(text):
+    course_lines = re.findall(r"([A-Za-z &]+):\s*([A-F][+-]?)", text)
+    gpa_match = re.search(r"GPA[:\s]+(\d\.\d+)", text)
+    courses = [course.strip() for course, _ in course_lines]
+    grades = [grade for _, grade in course_lines]
+    gpa = float(gpa_match.group(1)) if gpa_match else "N/A"
+
+    course_info = "\n".join([f"{c}: {g}" for c, g in zip(courses, grades)])
+    return f"Transcript Parsed (PDF):\n\n{course_info}\n\nGPA: {gpa}", {
+        "courses": courses,
+        "grades": grades,
+        "gpa": gpa
     }
 
-    with open("student_profile.json", "w") as f:
-        json.dump(profile, f, indent=4)
-
-    with open("student_summary.md", "w") as f:
-        f.write(summary["Learning_Plan"] + '\n' + summary["Style_Summary"] + '\n' + summary["Motivation"])
-
-    return f"✅ Profile saved! Your learning style is: {learning_type}"
-
-# Build Gradio UI
-with gr.Blocks() as demo:
-    gr.Markdown("## 🎓 Personalized AI Student Assistant")
-
-    with gr.Row():
-        file = gr.File(label="📄 Upload Your Transcript (.csv, .xlsx, .pdf)")
-
-    with gr.Column():
-        gr.Markdown("### 🧠 Learning Style Discovery")
-        quiz_components = []
-        for i, (question, options) in enumerate(zip(learning_style_questions, learning_style_answers)):
-            quiz_components.append(gr.Radio(
-                choices=options,
-                label=f"{i+1}. {question}"
-            ))
+# ========== LEARNING STYLE QUIZ FUNCTION ==========
 
-    category_inputs = []
-    for category, questions in get_to_know_categories.items():
-        gr.Markdown(f"### 📘 {category}")
-        for q_text, _ in questions:
-            category_inputs.append(gr.Textbox(label=q_text))
-
-    blog_checkbox = gr.Checkbox(label="📝 I'd like to write a mini blog about myself")
-    blog_text = gr.Textbox(lines=5, label="✍️ Mini Blog", visible=False)
-
-    blog_checkbox.change(fn=lambda x: gr.update(visible=x), inputs=blog_checkbox, outputs=blog_text
-
-    submit = gr.Button("🗕️ Save My Profile")
-    output = gr.Textbox(label="Status")
-
-    submit.click(fn=save_profile,
-                 inputs=[file, *quiz_components, blog_checkbox, blog_text, *category_inputs],
-                 outputs=[output])
-
-    # Assistant component functions
-    def load_student_profile():
-        try:
-            with open("student_profile.json", "r") as f:
-                return json.load(f)
-        except FileNotFoundError:
-            return None
-
-    def generate_study_tips(learning_style):
-        tips = {
-            "Visual": [
-                "Use color-coding in your notes",
-                "Create mind maps or diagrams",
-                "Watch educational videos",
-                "Use flashcards with images",
-                "Draw pictures to represent concepts"
-            ],
-            "Auditory": [
-                "Record lectures and listen to them",
-                "Explain concepts out loud to yourself",
-                "Participate in study groups",
-                "Use mnemonic devices with rhymes",
-                "Listen to educational podcasts"
-            ],
-            "Reading/writing": [
-                "Rewrite your notes in your own words",
-                "Create detailed outlines",
-                "Write summaries of what you learn",
-                "Read textbooks and articles",
-                "Keep a learning journal"
-            ]
-        }
-        return tips.get(learning_style.split(", ")[0], [])
-
-    def generate_subject_specific_advice(courses):
-        advice = {
-            "Math": [
-                "Practice problems daily",
-                "Focus on understanding concepts, not just memorization",
-                "Show all your work step-by-step",
-                "Relate math to real-world applications"
-            ],
-            "Science": [
-                "Conduct simple experiments at home",
-                "Create concept maps of scientific processes",
-                "Relate concepts to everyday phenomena",
-                "Watch science documentaries"
-            ],
-            "English": [
-                "Read diverse genres of literature",
-                "Keep a vocabulary journal",
-                "Practice writing in different styles",
-                "Analyze author's techniques"
-            ],
-            "History": [
-                "Create timelines of events",
-                "Connect historical events to current affairs",
-                "Watch historical films (and fact-check them)",
-                "Debate different historical perspectives"
-            ]
-        }
-        
-        default_advice = [
-            "Break study sessions into 25-minute chunks",
-            "Review material regularly, not just before tests",
-            "Connect new information to what you already know",
-            "Teach the material to someone else"
-        ]
-        
-        course_advice = []
-        for course in courses:
-            for subject in advice:
-                if subject.lower() in course.lower():
-                    course_advice.extend(advice[subject])
-        
-        return course_advice if course_advice else default_advice
-
-    def generate_personalized_message(responses):
-        hobbies = [ans for q, ans in responses.items() if "favorite way to spend" in q.lower()]
-        goals = [ans for q, ans in responses.items() if "want to be when" in q.lower() or "hope to achieve" in q.lower()]
-        
-        messages = []
-        if hobbies:
-            messages.append(f"I see you enjoy {hobbies[0].lower()}. Let's find ways to connect that to your learning!")
-        if goals:
-            messages.append(f"Your goal to {goals[0].lower()} is inspiring! Here's how we can work toward that:")
-        return "\n".join(messages) if messages else "I'm excited to help you achieve your learning goals!"
-
-    def assistant_response(message, history):
-        profile = load_student_profile()
-        if not profile:
-            return "Please complete and save your profile first using the previous tabs."
-        
-        # Get profile data
-        learning_style = profile["learning_style"]
-        courses = profile["transcript_info"].get("Courses", [])
-        responses = profile["get_to_know_answers"]
-        
-        # Generate personalized content
-        study_tips = generate_study_tips(learning_style)
-        subject_advice = generate_subject_specific_advice(courses)
-        personal_message = generate_personalized_message(responses)
-        
-        # Common responses
-        if "help" in message.lower() or "support" in message.lower():
-            return f"""
-{personal_message}
-
-Here's how I can help:
-1. Provide study tips matching your {learning_style} learning style
-2. Offer subject-specific advice for {', '.join(courses[:3]) if courses else 'your courses'}
-3. Answer questions about your learning plan
-4. Help you stay motivated
-
-What would you like to focus on today?
-"""
-        elif "tip" in message.lower() or "advice" in message.lower():
-            return f"""
-📚 **Personalized Study Advice**
-
-🎨 For your {learning_style} learning style:
-{'\n'.join(f'- {tip}' for tip in study_tips)}
+def learning_style_quiz(*answers):
+    visual = answers.count("I remember something better when I see it written down.")
+    auditory = answers.count("I remember best by listening to a lecture or a recording.")
+    reading = answers.count("I remember best by reading information on my own.")
+
+    styles = {"Visual": visual, "Auditory": auditory, "Reading/Writing": reading}
+    top_styles = [k for k, v in styles.items() if v == max(styles.values())]
+    result = ", ".join(top_styles)
+    return result
+
+# ========== SAVE STUDENT PROFILE FUNCTION ==========
+
+def save_profile(name, age, interests, transcript, learning_style, favorites, blog):
+    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)
 
-📖 Subject-specific tips:
-{'\n'.join(f'- {advice}' for advice in subject_advice)}
-"""
-        elif "plan" in message.lower() or "schedule" in message.lower():
-            return """
-📅 **Suggested Study Schedule**
-- Morning (30 min): Review previous material
-- Afternoon (45 min): Practice new concepts
-- Evening (20 min): Quick recap
-- Weekend: Longer project work
+    markdown_summary = f"""### Student Profile: {name}
 
-Remember to take breaks every 25-30 minutes!
-"""
-        elif "motiv" in message.lower():
-            return f"""
-💪 **Motivation Boost**
-{personal_message}
+**Age:** {age}  
+**Interests:** {interests}  
+**Learning Style:** {learning_style}  
 
-Remember:
-- Progress is more important than perfection
-- Small steps add up to big achievements
-- Your {learning_style} learning style is your superpower!
-"""
-        else:
-            return f"""
-{personal_message}
+#### Transcript:
+{transcript_display(transcript)}
 
-I'm your personalized learning assistant! Here are things I can help with:
-- Study tips and techniques
-- Learning plan advice
-- Motivation and encouragement
-- Answering questions about your progress
+#### 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']})
 
-Try asking about:
-- "How should I study for my classes?"
-- "What's the best way to learn based on my style?"
-- "Can you help me make a study plan?"
+#### Blog:
+{blog if blog else "_No blog provided_"}
 """
-
-    # Add assistant tab to the interface
-    with gr.Tab("🤖 AI Teaching Assistant"):
-        gr.Markdown("## 🎓 Your Personalized Learning Assistant")
-        gr.Markdown("Chat with your AI assistant to get personalized learning support based on your profile.")
-        chatbot = gr.ChatInterface(
-            assistant_response,
-            examples=[
-                "How should I study based on my learning style?",
-                "Give me study tips for my courses",
-                "Help me make a study plan",
-                "I need motivation"
-            ]
-        )
-
-if __name__ == '__main__':
-    demo.launch()
+    return markdown_summary
+
+def transcript_display(transcript_dict):
+    if not transcript_dict:
+        return "No transcript uploaded."
+    return "\n".join([f"{c}: {g}" for c, g in zip(transcript_dict["courses"], transcript_dict["grades"])] + [f"GPA: {transcript_dict['gpa']}"])
+
+# ========== 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"):
+        q1 = gr.Radio(choices=[
+            "I remember something better when I see it written down.",
+            "I remember best by listening to a lecture or a recording.",
+            "I remember best by reading information on my own."
+        ], label="1. How do you best remember information?")
+        q2 = gr.Radio(choices=q1.choices, label="2. What’s your preferred study method?")
+        q3 = gr.Radio(choices=q1.choices, label="3. What helps you understand new topics?")
+        q4 = gr.Radio(choices=q1.choices, label="4. How do you prefer to take notes?")
+        q5 = gr.Radio(choices=q1.choices, label="5. When you visualize concepts, what helps most?")
+        learning_output = gr.Textbox(label="Learning Style Result")
+        gr.Button("Submit Quiz").click(learning_style_quiz, inputs=[q1, q2, q3, q4, q5], 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?")
+        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(fn=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")
+        
+        def gather_and_save(name, age, interests, movie, movie_reason, show, show_reason,
+                            book, book_reason, character, character_reason, blog, transcript, learning_style):
+            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,
+            }
+            return save_profile(name, age, interests, transcript, learning_style, favorites, blog)
+
+        save_btn.click(fn=gather_and_save, 
+                       inputs=[name, age, interests, movie, movie_reason, show, show_reason,
+                               book, book_reason, character, character_reason, blog_text,
+                               transcript_data, learning_output],
+                       outputs=output_summary)
+
+app.launch()
+
+   
+
+    
+