Update app.py

app.py

@@ -1,25 +1,144 @@
+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'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:"
+    "When you meet new people, you remember them by:"
 ]
 
 learning_style_options = [
@@ -27,22 +146,7 @@ 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)"],
-    ["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)"]
+    ["Their face (Visual)", "Their name (Auditory)", "What you talked about (Reading/Writing)", "What you did together (Kinesthetic)"]
 ]
 
 def learning_style_quiz(*answers):
@@ -64,54 +168,228 @@ def learning_style_quiz(*answers):
             scores["Kinesthetic"] += 1
     
     max_score = max(scores.values())
-    total_questions = len(learning_style_questions)
+    dominant_styles = [style for style, score in scores.items() if score == max_score]
     
-    # Calculate percentages
-    percentages = {style: (score/total_questions)*100 for style, score in scores.items()}
+    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
     
-    # Sort styles by score (descending)
-    sorted_styles = sorted(scores.items(), key=lambda x: x[1], reverse=True)
+    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
+    }
     
-    # 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"
+    data = {
+        "name": name,
+        "age": age,
+        "interests": interests,
+        "transcript": transcript,
+        "learning_style": learning_style,
+        "favorites": favorites,
+        "blog": blog
+    }
     
-    result += "\n"
+    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."
     
-    # Determine primary and secondary styles
-    primary_styles = [style for style, score in scores.items() if score == max_score]
+    # 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", "")
     
-    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:
-        result += f"You have multiple strong learning styles: {', '.join(primary_styles)}\n\n"
-        result += "You may benefit from combining different learning approaches.\n"
+    # Common responses
+    greetings = ["hi", "hello", "hey"]
+    study_help = ["study", "learn", "prepare", "exam"]
+    grade_help = ["grade", "gpa", "score"]
+    interest_help = ["interest", "hobby", "passion"]
+    
+    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
     
-    return result
+    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!")
+    
+    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()