Update app.py

app.py

@@ -9,16 +9,6 @@ entity_types_to_show = [
 ]
 selected_types = st.multiselect('Select entity types to show:', entity_types_to_show)
 
-def sample_analyze_entities(text_content, selected_types):
-    # Existing code for setting up credentials and client...
-
-    # Create an empty list to hold the results
-    entities_list = []
-
-    for entity in response.entities:
-        entity_type_name = language_v1.Entity.Type(entity.type_).name
-        if entity_type_name in selected_types:
-
 # Header and intro
 st.title("Google Cloud NLP Entity Analyzer")
 st.write("## Introduction to the Knowledge Graph API")
@@ -54,51 +44,10 @@ def sample_analyze_entities(text_content, your_query=""):
     entities_list = []
 
     for entity in response.entities:
-        # Create a dictionary to hold individual entity details
-        entity_details = {
-            "Name": entity.name,
-            "Type": language_v1.Entity.Type(entity.type_).name,
-            "Salience Score": entity.salience,
-            "Metadata": [],
-            "Mentions": []
-        }
-
-        for metadata_name, metadata_value in entity.metadata.items():
-            entity_details["Metadata"].append({metadata_name: metadata_value})
-
-        for mention in entity.mentions:
-            entity_details["Mentions"].append({
-                "Text": mention.text.content,
-                "Type": language_v1.EntityMention.Type(mention.type_).name
-            })
-
-        # Append the dictionary to the list
-        entities_list.append(entity_details)
-
-    # Streamlit UI
-    if your_query:
-        st.write(f"### We found {len(entities_list)} results for your query of **{your_query}**")
-    else:
-        st.write("### We found results for your query")
-
-    st.write("----")
-
-    for i, entity in enumerate(entities_list):
-        st.write(f"Relevance Score: {entity.get('Salience Score', 'N/A')} \t {i+1} of {len(entities_list)}")
-        
-        # Display all key-value pairs in the entity dictionary
-        for key, value in entity.items():
-            if value:
-                st.write(f"**{key}:**")
-                if isinstance(value, (list, dict)):
-                    st.json(value)
-                else:
-                    st.write(value)
-        
-        st.write("----")
-
-
-    st.write(f"### Language of the text: {response.language}")
+        entity_type_name = language_v1.Entity.Type(entity.type_).name
+        if entity_type_name in selected_types:
+            # Rest of your code to handle each entity
+            # ...
 
 # User input for text analysis
 user_input = st.text_area("Enter text to analyze")