app.py

import gradio as gr
import pandas as pd
import PyPDF2
import json
import re

# 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)
    elif file.name.endswith('.pdf'):
        reader = PyPDF2.PdfReader(file)
        text = ""
        for page in reader.pages:
            text += page.extract_text() or ""
        df = pd.DataFrame({'Transcript_Text': [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."

    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."

    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]"
    }

    summary = {
        "Learning_Plan": generate_learning_plan(transcript_info),
        "Style_Summary": generate_learning_style_summary(learning_type),
        "Motivation": generate_motivation_section(responses)
    }

    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}"
            ))

    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)}

📖 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

Remember to take breaks every 25-30 minutes!
"""
    elif "motiv" in message.lower():
        return f"""
💪 **Motivation Boost**
{personal_message}

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}

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

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?"
"""

# 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()