Update app.py

app.py

@@ -3,7 +3,7 @@ import requests
 from bs4 import BeautifulSoup
 import pandas as pd
 from transformers import pipeline
-import plotly.graph_objects as go
+import plotly.express as px
 from datetime import datetime, timedelta
 
 # Sentiment Analysis Model
@@ -64,25 +64,37 @@ def news_and_analysis(query):
     news_df['Sentiment'], news_df['Sentiment_Score'] = zip(*news_df['Title'].apply(analyze_sentiment))
     
     # Create sentiment plot
-    sentiment_fig = go.Figure(data=[go.Bar(
-        x=news_df['Time'],
-        y=news_df['Sentiment_Score'],
-        marker_color=news_df['Sentiment'].map({'positive': 'green', 'neutral': 'gray', 'negative': 'red'})
-    )])
-    sentiment_fig.update_layout(title='News Sentiment Over Time', xaxis_title='Time', yaxis_title='Sentiment Score')
+    sentiment_fig = px.bar(
+        news_df,
+        x='Time',
+        y='Sentiment_Score',
+        color='Sentiment',
+        color_discrete_map={'positive': 'green', 'neutral': 'gray', 'negative': 'red'},
+        title='News Sentiment Over Time',
+        labels={'Time': 'Publication Time', 'Sentiment_Score': 'Sentiment Score'}
+    )
     
     return news_df, sentiment_fig
 
 # Gradio interface
 with gr.Blocks() as demo:
-    gr.Markdown("#News Sentiment Analysis")
-    
-    topic = gr.Textbox(label="Enter a headline")
-    
-    analyze_btn = gr.Button(value="Analyze")
+    gr.Markdown(
+        """
+        # Financial News Sentiment Analysis
+        
+        Analyze the sentiment of news articles related to financial topics or companies. 
+        Enter a topic or company name to get started.
+        """
+    )
     
-    news_output = gr.DataFrame(label="News and Sentiment Analysis")
-    sentiment_plot = gr.Plot(label="Sentiment Analysis")
+    with gr.Row():
+        with gr.Column():
+            topic = gr.Textbox(label="Enter a financial topic or company name", placeholder="e.g., Apple Inc.")
+            analyze_btn = gr.Button(value="Analyze")
+        
+        with gr.Column():
+            news_output = gr.DataFrame(label="News and Sentiment Analysis")
+            sentiment_plot = gr.Plot(label="Sentiment Analysis")
     
     analyze_btn.click(
         news_and_analysis,
@@ -91,4 +103,4 @@ with gr.Blocks() as demo:
     )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()