Update app.py

app.py

@@ -3,13 +3,29 @@ from google.oauth2 import service_account
 from google.cloud import language_v1
 import streamlit as st
 
+# Header and intro
+st.write("## Introduction to the Knowledge Graph API")
+st.write("---")
+st.write("""
+The Google Knowledge Graph API reveals entity information related to a keyword, that Google knows about.
+This information can be very useful for SEO – discovering related topics and what Google believes is relevant.
+It can also help when trying to claim/win a Knowledge Graph box on search results.
+The API requires a high level of technical understanding, so this tool creates a simple public interface, with the ability to export data into spreadsheets.
+""")
+
 def sample_analyze_entities(text_content):
+    # Parse the JSON string to a dictionary
     service_account_info = json.loads(st.secrets["google_nlp"])
+
+    # Create credentials
     credentials = service_account.Credentials.from_service_account_info(
         service_account_info, scopes=["https://www.googleapis.com/auth/cloud-platform"]
     )
+
+    # Initialize the LanguageServiceClient with the credentials
     client = language_v1.LanguageServiceClient(credentials=credentials)
 
+    # NLP analysis
     type_ = language_v1.Document.Type.PLAIN_TEXT
     language = "en"
     document = {"content": text_content, "type_": type_, "language": language}
@@ -48,21 +64,19 @@ def sample_analyze_entities(text_content):
         st.write(f"**Name**: {entity['Name']}")
         st.write(f"**Type**: {entity['Type']}")
         st.write(f"**Salience Score**: {entity['Salience Score']}")
-        
+
         if entity["Metadata"]:
             st.write("**Metadata**: ")
             st.json(entity["Metadata"])
-        
+
         if entity["Mentions"]:
             st.write("**Mentions**: ")
             st.json(entity["Mentions"])
 
 
-st.title('Google Cloud NLP Entity Analyzer')
-user_input = st.text_area("Enter text to analyze", "Your text goes here")
+    st.write(f"### Language of the text: {response.language}")
 
-if st.button('Analyze'):
-    if user_input:
-        sample_analyze_entities(user_input)
-    else:
-        st.write("Please enter some text to analyze.")
+# User input for text analysis
+user_input = st.text_area("Enter text to analyze")
+if st.button("Analyze"):
+    sample_analyze_entities(user_input)