Update app.py

app.py

@@ -24,28 +24,22 @@ def parse_transcript(file):
 def extract_transcript_info(df):
     transcript_text = df['Transcript_Text'].iloc[0] if 'Transcript_Text' in df.columns else ''
     info = {}
-
-    # GPA extraction
-    gpa_matches = re.findall(r'(weighted|unweighted)?\s*GPA[:\s-]*([0-4]\.?\d{0,2})', transcript_text, re.IGNORECASE)
-    for gpa_type, gpa_value in gpa_matches:
-        key = f"{gpa_type.strip().capitalize() if gpa_type else 'GPA'}"
-        info[key] = gpa_value
-
-    # Grade Level
-    grade_match = re.search(r'Grade:?\s*(\d{1,2})', transcript_text, re.IGNORECASE)
+    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)
+    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]
+    grade_match = re.search(r'Grade:?[\s]*(\d{1,2})', transcript_text, re.IGNORECASE)
     if grade_match:
         info['Grade_Level'] = grade_match.group(1)
-
-    # Full Name
-    name_match = re.search(r'(Student Name|Name):?\s*([A-Z][a-z]+\s+[A-Z][a-z]+)', transcript_text)
-    if name_match:
-        info['Full_Name'] = name_match.group(2)
-
-    # Courses
     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
@@ -93,6 +87,7 @@ def learning_style_quiz(*answers):
 
     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?", []),
@@ -131,7 +126,7 @@ get_to_know_categories = {
 def generate_learning_plan(info):
     level = info.get("Grade_Level", "unknown")
     courses = info.get("Courses", [])
-    gpa = info.get("GPA", info.get("Unweighted", "N/A"))
+    gpa = info.get("GPA", info.get("Unweighted_GPA", "N/A"))
     return f"""
 📘 **Personalized Learning Plan**
 - Grade Level: {level}
@@ -154,63 +149,58 @@ Your dreams are powerful: {'; '.join(hopes) if hopes else 'You are filled with p
 Believe in yourself and keep moving forward.
 """
 
-def show_basic_info():
-    with open("student_profile.json") as f:
-        profile = json.load(f)
-        info = profile["transcript_info"]
-        name = info.get("Full_Name", "Name not found")
-        grade = info.get("Grade_Level", "N/A")
-        gpa = info.get("GPA", info.get("Unweighted", "N/A"))
-        weighted = info.get("Weighted", "Not provided")
-        return f"👤 Name: {name}\n🎓 Grade Level: {grade}\n📊 GPA: {gpa}\n📈 Weighted GPA: {weighted}"
-
 def save_profile(file, *inputs):
-    if not file:
-        return gr.Textbox.update(value="⚠️ Please upload your transcript."), gr.Textbox.update(visible=False)
+    try:
+        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 gr.Textbox.update(value="⚠️ Please answer all the learning style questions."), gr.Textbox.update(visible=False)
+        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 gr.Textbox.update(value="⚠️ Please complete all 'Get to Know You' sections before saving."), gr.Textbox.update(visible=False)
+        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 gr.Textbox.update(value="⚠️ You checked the blog option but didn’t write anything. Please write your mini blog or uncheck the option."), gr.Textbox.update(visible=False)
+        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"])
 
-    return gr.Textbox.update(value="✅ Profile saved!"), gr.Textbox.update(value=show_basic_info(), visible=True)
+        return f"✅ Profile saved! Your learning style is: {learning_type}"
+    
+    except Exception as e:
+        return f"❌ Error: {str(e)}"
 
+# Build Gradio UI
 with gr.Blocks() as demo:
     gr.Markdown("## 🎓 Personalized AI Student Assistant")
 
@@ -234,15 +224,15 @@ with gr.Blocks() as demo:
 
     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")
-    status_output = gr.Textbox(label="Status")
-    user_info_output = gr.Textbox(label="👤 Your Info", visible=False)
+    output = gr.Textbox(label="Status")
 
     submit.click(fn=save_profile,
                  inputs=[file, *quiz_components, blog_checkbox, blog_text, *category_inputs],
-                 outputs=[status_output, user_info_output])
+                 outputs=[output])
 
 if __name__ == '__main__':
-    demo.launch()
+    demo.launch()