app.py

import json
import streamlit as st
from google.oauth2 import service_account
from google.cloud import language_v1

# Adding checkbox options for entity types
entity_types_to_show = [
    "UNKNOWN", "PERSON", "LOCATION", "ORGANIZATION", "EVENT", "WORK_OF_ART", "CONSUMER_GOOD", "OTHER"
]
selected_types = st.multiselect('Select entity types to show:', entity_types_to_show)

# Header and intro
st.title("Google Cloud NLP Entity Analyzer")
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, your_query=""):
    # 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}
    encoding_type = language_v1.EncodingType.UTF8

    response = client.analyze_entities(request={"document": document, "encoding_type": encoding_type})

    # 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:
            # Rest of your code to handle each entity
            # ...

# User input for text analysis
user_input = st.text_area("Enter text to analyze")
your_query = st.text_input("Enter your query (optional)")

if st.button("Analyze"):
    sample_analyze_entities(user_input, your_query)