added title

app.py

@@ -29,7 +29,7 @@ def plot_efficient_frontier_and_max_sharpe(mu, S):
     ef_max_sharpe.max_sharpe(risk_free_rate=0.02)
     ret_tangent, std_tangent, _ = ef_max_sharpe.portfolio_performance()
     ax.scatter(std_tangent, ret_tangent, marker="*", s=100, c="r", label="Max Sharpe")
-    # Generate random portfolios
+    # Generate random portfolios with random weights
     n_samples = 1000
     w = np.random.dirichlet(np.ones(ef.n_assets), n_samples)
     rets = w.dot(ef.expected_returns)
@@ -104,7 +104,7 @@ with gr.Blocks() as app:
         btn = gr.Button("Get Optimized Portfolio")
        
     with gr.Row():
-        gr.Markdown("Optimizied Portfolio Metrics")
+        gr.HTML("<h3>Optimizied Portfolio Metrics</h3>")
         
     with gr.Row():
         expected_annual_return = gr.Text(label="Expected Annual Return")

app.py.bak

@@ -10,9 +10,7 @@ import numpy as np
 import pandas as pd
 import plotly.express as px
 import matplotlib.pyplot as plt
-import seaborn as sns
 from datetime import datetime
-from io import BytesIO
 import datetime
 
 def plot_cum_returns(data, title):