blazingbunny commited on
Commit
a95b8e3
·
1 Parent(s): 0a35ca9

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +12 -5
app.py CHANGED
@@ -26,7 +26,7 @@ st.sidebar.markdown("""
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  # Header and intro
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  st.title("Google Cloud NLP Entity Analyzer")
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  st.write("This tool analyzes text to identify entities such as people, locations, organizations, and events")
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- 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. A number of textual features contribute to the salience score.")
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  def sample_analyze_entities(text_content):
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  service_account_info = json.loads(st.secrets["google_nlp"])
@@ -51,18 +51,25 @@ def sample_analyze_entities(text_content):
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  st.write(f"Name: {entity.name}")
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  st.write(f"Type: {language_v1.Entity.Type(entity.type_).name}")
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  st.write(f"Salience Score: {entity.salience}")
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-
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  if entity.metadata:
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  st.write("Metadata:")
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  st.write(entity.metadata)
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-
 
 
 
 
 
 
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  if entity.mentions:
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  st.write("Mentions:")
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- st.write(entity.mentions)
 
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  st.write("---")
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  # User input for text analysis
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- user_input = st.text_area("Enter text to analyze", max_chars=10000)
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  if st.button("Analyze"):
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  if user_input:
 
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  # Header and intro
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  st.title("Google Cloud NLP Entity Analyzer")
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  st.write("This tool analyzes text to identify entities such as people, locations, organizations, and events")
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+ 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.")
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  def sample_analyze_entities(text_content):
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  service_account_info = json.loads(st.secrets["google_nlp"])
 
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  st.write(f"Name: {entity.name}")
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  st.write(f"Type: {language_v1.Entity.Type(entity.type_).name}")
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  st.write(f"Salience Score: {entity.salience}")
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+
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  if entity.metadata:
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  st.write("Metadata:")
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  st.write(entity.metadata)
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+
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+ if 'mid' in entity.metadata and ('/g/' in entity.metadata['mid'] or '/m/' in entity.metadata['mid']):
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+ entity_id = entity.metadata['mid']
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+ ahref_link = f"https://kgsearch.googleapis.com/v1/entities:search?ids={entity_id}&key={st.secrets['google_nlp']}&limit=1&indent=True"
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+ st.markdown(f'<a href="{ahref_link}" target="_blank">Google Entity Link</a>', unsafe_allow_html=True)
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+
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+
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  if entity.mentions:
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  st.write("Mentions:")
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+ st.write(', '.join([mention.text.content for mention in entity.mentions]))
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+
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  st.write("---")
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  # User input for text analysis
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+ user_input = st.text_area("Enter text to analyze", max_chars=5000)
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  if st.button("Analyze"):
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  if user_input: