Update app.py

app.py

@@ -2,6 +2,23 @@ import json
 import streamlit as st
 from google.oauth2 import service_account
 from google.cloud import language_v1
+import urllib.parse
+import urllib.request
+
+# Function to query Google's Knowledge Graph API
+def query_knowledge_graph(entity_id):
+    service_url = 'https://kgsearch.googleapis.com/v1/entities:search'
+    params = {
+        'ids': entity_id,
+        'limit': 1,
+        'indent': True,
+        'key': st.secrets["kg_api"],
+    }
+    url = service_url + '?' + urllib.parse.urlencode(params)
+    response = json.loads(urllib.request.urlopen(url).read())
+    for element in response['itemListElement']:
+        st.write(f"Knowledge Graph name: {element['result']['name']}")
+        st.write(f"Knowledge Graph score: {element['resultScore']}")
 
 # Function to count entities with 'mid' that contains '/g/' or '/m/' in their metadata
 def count_entities(entities):
@@ -26,7 +43,7 @@ st.sidebar.markdown("""
 # Header and intro
 st.title("Google Cloud NLP Entity Analyzer")
 st.write("This tool analyzes text to identify entities such as people, locations, organizations, and events")
-st.write("Entity salience scores are always relative to the analysed text. In natural language processing, a salience score is always a prediction of what a human would consider to be the most important entities in the same text.")
+st.write("Entity salience scores are always relative to the analysed text.")
 
 def sample_analyze_entities(text_content):
     service_account_info = json.loads(st.secrets["google_nlp"])
@@ -58,8 +75,7 @@ def sample_analyze_entities(text_content):
             
             if 'mid' in entity.metadata and ('/g/' in entity.metadata['mid'] or '/m/' in entity.metadata['mid']):
                 entity_id = entity.metadata['mid']
-                ahref_link = f"https://kgsearch.googleapis.com/v1/entities:search?ids={entity_id}&key=credentials&limit=1&indent=True"
-                st.markdown(f'<a href="{ahref_link}" target="_blank">Google Entity Link</a>', unsafe_allow_html=True)
+                query_knowledge_graph(entity_id)
 
         if entity.mentions:
             st.write("Mentions:")