import gradio as gr
import pandas as pd
import io
import plotly.express as px
import plotly.graph_objects as go

# Define admin credentials
ADMIN_EMAIL = "admin@gmail.com"
ADMIN_PASSWORD = "123456"

# Variable to store uploaded grades file in memory
grades_df = None

# Admin login function
def admin_login(email, password):
    if email == ADMIN_EMAIL and password == ADMIN_PASSWORD:
        return (True, "", "Logged in successfully.", True)
    else:
        return (False, "", "Invalid credentials.", False)

def intern_login(email):
    return (True, "", f"Welcome {email}. You can now view your grades.", True)

# Admin upload function
def admin_upload(file):
    global grades_df
    if file is not None:
        grades_df = pd.read_excel(io.BytesIO(file.read()))
        return "File uploaded and processed successfully."
    else:
        return "Please upload a valid Excel file."

# Function to generate performance analysis charts
def performance_analysis():
    if grades_df is not None:
        # Ensure 'Created At' is datetime
        grades_df['Created At'] = pd.to_datetime(grades_df['Created At'])
        grades_df['Date'] = grades_df['Created At'].dt.date

        # Group by date and calculate sum of grades
        daily_performance = grades_df.groupby('Date')['Grade'].sum().reset_index()

        # Line chart for daily performance
        line_chart = px.line(daily_performance, x='Date', y='Grade', title='Daily Performance (Total Grades)')
        
        # Histogram of grades
        histogram = px.histogram(grades_df, x='Grade', nbins=20, title='Grade Distribution')

        # Box plot for grade statistics
        box_plot = px.box(grades_df, y='Grade', title='Grade Statistics')

        # Create a summary table
        summary_stats = grades_df['Grade'].describe().reset_index()
        summary_table = go.Figure(data=[go.Table(
            header=dict(values=['Statistic', 'Value']),
            cells=dict(values=[summary_stats['index'], summary_stats['Grade']])
        )])
        
        return line_chart, histogram, box_plot, summary_table
    else:
        return None, None, None, None

# Create the Gradio interface
with gr.Blocks() as demo:
    with gr.Tab("Admin Login"):
        admin_email = gr.Textbox(label="Admin Email")
        admin_password = gr.Textbox(label="Admin Password", type="password")
        admin_login_button = gr.Button("Login")
        admin_login_output = gr.Textbox(label="Admin Output")
        admin_file = gr.File(label="Upload Grades Excel File", visible=False)
        admin_submit = gr.Button("Submit", visible=False)
        admin_file_output = gr.Textbox(label="File Upload Output", visible=False)
        
        admin_charts = gr.Plot(visible=False)
        admin_histogram = gr.Plot(visible=False)
        admin_box_plot = gr.Plot(visible=False)
        admin_summary_table = gr.Plot(visible=False)

        admin_login_button.click(
            admin_login,
            inputs=[admin_email, admin_password],
            outputs=[admin_login_output, admin_file, admin_submit, admin_file_output],
            show_progress=False,
        )
        admin_submit.click(
            admin_upload,
            inputs=[admin_file],
            outputs=admin_file_output,
        )
        admin_submit.click(
            performance_analysis,
            outputs=[admin_charts, admin_histogram, admin_box_plot, admin_summary_table],
        )
    
    with gr.Tab("Intern Login"):
        intern_email = gr.Textbox(label="Intern Email")
        intern_login_button = gr.Button("Login")
        intern_login_output = gr.Textbox(label="Intern Output")
        intern_submit = gr.Button("View Grades", visible=False)
        intern_output = gr.Textbox(label="Grade Analysis", visible=False)

        intern_login_button.click(
            intern_login,
            inputs=[intern_email],
            outputs=[intern_login_output, intern_submit, intern_output],
            show_progress=False,
        )
        intern_submit.click(
            intern_view,
            inputs=[intern_email],
            outputs=intern_output,
        )

# Launch the app
demo.launch()