Create app.py

app.py

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+# Import necessary libraries
+import streamlit as st
+import textrazor
+import matplotlib.pyplot as plt
+import pandas as pd
+import re
+
+# Set TextRazor API key using Streamlit Secrets
+textrazor.api_key = st.secrets["textrazer_api"]
+
+# Streamlit app title and input for URL
+st.title("TextRazor Entities Analysis")
+url_input = st.text_input("Enter URL to Analyze")
+
+# Check if URL is provided
+if url_input:
+    # Create TextRazor client and analyze URL
+    client = textrazor.TextRazor(extractors=["entities", "topics"])
+    response = client.analyze_url(url_input)
+
+    # Create dataframe and lists
+    df = pd.DataFrame(columns=['Entity ID', 'Entity Relevance', 'Entity Confidence', 'Entity Freebase'])
+    new_entityid = []
+    new_relevance = []
+    new_confidence = []
+    new_freebase = []
+
+    # Loop entities and append to list
+    for entity in response.entities():
+        entity_id = re.sub(r'\d+', '', entity.id)
+        new_entityid.append(entity_id)
+        new_relevance.append(entity.relevance_score)
+        new_confidence.append(entity.confidence_score)
+        new_freebase.append(entity.freebase_types)
+
+    # Assign columns values from lists to dataframe
+    df['Entity ID'] = new_entityid
+    df['Entity Relevance'] = new_relevance
+    df['Entity Confidence'] = new_confidence
+    df['Entity Freebase'] = new_freebase
+
+    # Save data to CSV
+    df.to_csv('textrazor_v1_entities.csv')
+
+    # Display dataframe
+    st.write("Top 25 Entities:")
+    st.write(df.head(25))
+
+    # Plot the top 10 entities
+    st.bar_chart(df['Entity ID'].value_counts().nlargest(10))
+
+    # Add labels and title to the chart
+    plt.xlabel('Entity')
+    plt.ylabel('Frequency')
+    plt.title('Top 10 Entities by frequency')
+
+    # Show the plot in Streamlit
+    st.pyplot(plt)
+else:
+    st.warning("Please enter a URL to analyze.")