Update app.py

app.py

@@ -24,16 +24,9 @@ def parse_transcript(file):
 def extract_transcript_info(df):
     transcript_text = df['Transcript_Text'].iloc[0] if 'Transcript_Text' in df.columns else ''
     info = {}
-    name_match = re.search(r"Name[:\s]+([A-Z][a-z]+\s[A-Z][a-z]+)", transcript_text)
-    if name_match:
-        info['Name'] = name_match.group(1)
-    gpa_match = re.findall(r'(GPA|Grade Point Average)[^\d]*(\d+\.\d+)', transcript_text, re.IGNORECASE)
+    gpa_match = re.search(r'(GPA|Grade Point Average)[^\d]*(\d+\.\d+)', transcript_text, re.IGNORECASE)
     if gpa_match:
-        if len(gpa_match) == 1:
-            info['GPA'] = gpa_match[0][1]
-        elif len(gpa_match) >= 2:
-            info['Unweighted_GPA'] = gpa_match[0][1]
-            info['Weighted_GPA'] = gpa_match[1][1]
+        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)
@@ -42,7 +35,7 @@ def extract_transcript_info(df):
         info['Courses'] = list(set([c[0].strip() for c in courses]))
     return info
 
-# Learning style questions
+# 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:",
@@ -87,58 +80,116 @@ def learning_style_quiz(*answers):
 
     return ", ".join(best_styles)
 
-# Save profile function
+# 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):
-    try:
-        if not file:
-            return "⚠️ Please upload your transcript."
+    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."
+    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:]
+    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 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."
+    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)
+    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))
+    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]"
-        }
+    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)
-        }
+    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_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"])
+    with open("student_summary.md", "w") as f:
+        f.write(summary["Learning_Plan"] + '\n' + summary["Style_Summary"] + '\n' + summary["Motivation"])
 
-        # Reset the inputs and clear the fields
-        return f"✅ Profile saved! Your learning style is: {learning_type}", *[gr.update(value="") for _ in inputs] + [gr.update(value=None) for _ in inputs]
-
-    except Exception as e:
-        return f"❌ Error: {str(e)}"
+    return f"✅ Profile saved! Your learning style is: {learning_type}", *[gr.update(value="") for _ in inputs] + [gr.update(value=None) for _ in inputs]
 
 # Build Gradio UI
 with gr.Blocks() as demo: