app.py

import gradio as gr
import pandas as pd

# Data store for subjects
subject_data = []

# Utility to scale marks from input total to given weight
def scale(raw_marks, weight):
    return (raw_marks / 100) * weight

# Grade logic
def get_grade_point(total):
    if 90 <= total <= 100:
        return 10, "S"
    elif 80 <= total < 90:
        return 9, "A"
    elif 70 <= total < 80:
        return 8, "B"
    elif 60 <= total < 70:
        return 7, "C"
    elif 50 <= total < 60:
        return 6, "D"
    elif 40 <= total < 50:
        return 5, "E"
    else:
        return 0, "F"

# Add subject and calculate its grade
def add_subject(sub_type, s1, s2, mid=0, lab=0, prac=0, theory=0, open_proj=0, end_sem=0):
    # Scale sessionals (entered out of 50, so multiply by 2 to get out of 100)
    s1_scaled = scale(s1 * 2, 17.5)
    s2_scaled = scale(s2 * 2, 17.5)

    if sub_type == "With Practical":
        mid_scaled = scale(mid, 10)
        lab_scaled = scale(lab, 5)
        prac_scaled = scale(prac, 15)
        theory_scaled = scale(theory, 35)
        total = s1_scaled + s2_scaled + mid_scaled + lab_scaled + prac_scaled + theory_scaled
    else:
        proj_scaled = scale(open_proj, 15)
        end_scaled = scale(end_sem, 50)
        total = s1_scaled + s2_scaled + proj_scaled + end_scaled

    grade_point, grade = get_grade_point(total)
    subject_data.append({
        "Type": sub_type,
        "Total Marks": round(total, 2),
        "Grade": grade,
        "Points": grade_point
    })
    return (
        f"✅ Subject Added: {sub_type} | Total: {round(total, 2)} | Grade: {grade}",
        pd.DataFrame(subject_data)
    )

# GPA calculation
def calculate_gpa():
    if not subject_data:
        return "⚠️ No subjects added yet."
    total_points = sum(s["Points"] for s in subject_data)
    gpa = round(total_points / len(subject_data), 2)
    return f"🎓 Semester GPA: {gpa}"

# Reset all data
def clear_data():
    subject_data.clear()
    return "🧹 All subjects cleared!", pd.DataFrame(subject_data)

# Show/hide inputs based on subject type
def toggle_fields(subject_type):
    show_practical = subject_type == "With Practical"
    show_theory = subject_type == "Without Practical"
    return (
        gr.update(visible=show_practical),  # mid
        gr.update(visible=show_practical),  # lab
        gr.update(visible=show_practical),  # prac
        gr.update(visible=show_practical),  # theory
        gr.update(visible=show_theory),     # open_proj
        gr.update(visible=show_theory)      # end_sem
    )

# Gradio UI
with gr.Blocks(title="GPA Predictor") as demo:
    gr.Markdown("""
    # 📘 GPA Predictor
    
    ### 📝 Instructions:
    - Select the subject type (With Practical / Without Practical).
    - Enter marks **as per instructions**:
      - **Sessionals**: out of 50 (scaled to 17.5 each)
      - **Practical/Lab/Projects**: out of 100 (auto scaled)
      - **End Sem**: out of 100 (scaled to 35 or 50)
    - Press ➕ **Add Subject**
    - Press ✅ **Calculate GPA** after adding all subjects.
    """)

    subject_type = gr.Dropdown(["With Practical", "Without Practical"], label="Subject Type", value="With Practical")

    with gr.Column():
        s1 = gr.Number(label="Sessional-I (out of 50)", value=0)
        s2 = gr.Number(label="Sessional-II (out of 50)", value=0)
        mid = gr.Number(label="Mid-Sem Practical (out of 100)", value=0, visible=True)
        lab = gr.Number(label="Regular Lab Performance (out of 100)", value=0, visible=True)
        prac = gr.Number(label="End Sem Practical (out of 100)", value=0, visible=True)
        theory = gr.Number(label="End Sem Theory (out of 100)", value=0, visible=True)
        open_proj = gr.Number(label="Open-ended Project (out of 100)", value=0, visible=False)
        end_sem = gr.Number(label="End Sem Theory (out of 100)", value=0, visible=False)

    subject_type.change(
        fn=toggle_fields,
        inputs=[subject_type],
        outputs=[mid, lab, prac, theory, open_proj, end_sem]
    )

    submit_btn = gr.Button("➕ Add Subject")
    result = gr.Textbox(label="Status", interactive=False)
    subject_table = gr.Dataframe(label="📊 Subjects Added", interactive=False)

    submit_btn.click(
        fn=add_subject,
        inputs=[subject_type, s1, s2, mid, lab, prac, theory, open_proj, end_sem],
        outputs=[result, subject_table]
    )

    with gr.Row():
        calc_btn = gr.Button("✅ Calculate GPA")
        clear_btn = gr.Button("🧹 Clear All")

    gpa_out = gr.Textbox(label="Final Predicted GPA", interactive=False)

    calc_btn.click(fn=calculate_gpa, inputs=[], outputs=[gpa_out])
    clear_btn.click(fn=clear_data, inputs=[], outputs=[result, subject_table])

demo.launch()