import streamlit as st
from google.cloud import language_v1
import os

# Your existing function (replace this part with your actual code)
def sample_analyze_entities(text_content):
    st.write("Debug: Entered sample_analyze_entities")
    try:
        client = language_v1.LanguageServiceClient()

        type_ = language_v1.Document.Type.PLAIN_TEXT
        language = "en"
        document = {"content": text_content, "type_": type_, "language": language}
        encoding_type = language_v1.EncodingType.UTF8

        st.write("Debug: Making API call...")
        
        response = client.analyze_entities(request={"document": document, "encoding_type": encoding_type})

        st.write("Debug: API call completed.")
        
        for entity in response.entities:
            st.write(f"Entity: {entity.name}, Type: {language_v1.Entity.Type(entity.type_).name}, Salience: {entity.salience}")
    except Exception as e:
        st.write(f"Debug: An error occurred: {e}")

# Streamlit UI
st.title('Google Cloud NLP Entity Analyzer')
user_input = st.text_area('Enter text to analyze', '')

if st.button('Analyze'):
    st.write("Debug: Analyze button clicked")
    if user_input:
        st.write(f"Debug: User input received: {user_input}")
        sample_analyze_entities(user_input)