Update app.py

app.py

@@ -3,39 +3,23 @@ from google.cloud import language_v1
 from google.oauth2 import service_account
 import json
 
-
-# Load Google Cloud credentials
-credentials = service_account.Credentials.from_service_account_file(json.loads(st.secrets["GOOGLE_APPLICATION_CREDENTIALS"]))
-
 def print_result(annotations):
-    # Overall Sentiment
     score = annotations.document_sentiment.score
     magnitude = annotations.document_sentiment.magnitude
-    st.write("**Overall Sentiment:**")
-    st.write(f"  * Score: {score}")
-    st.write(f"  * Magnitude: {magnitude}")
 
-    # Sentence-Level Sentiment
-    st.write("**Sentence-Level Sentiment:**")
     for index, sentence in enumerate(annotations.sentences):
-        sentence_text = sentence.text.content
         sentence_sentiment = sentence.sentiment.score
-        st.write(f"Sentence {index}: {sentence_text}")
-        st.write(f"  * Sentiment score: {sentence_sentiment}")
-
-    # Entity-Level Sentiment (If Applicable)
-    if annotations.entities:
-        st.write("**Entity-Level Sentiment:**")
-        for entity in annotations.entities:
-            st.write(f"Entity: {entity.name} ({entity.type})") 
-            st.write(f"  * Sentiment Score: {entity.sentiment.score}")
-            st.write(f"  * Magnitude: {entity.sentiment.magnitude}")
-            st.write(f"  * Salience: {entity.salience}")
-
-def analyze_sentiment(texts, credentials):
+        st.write(f"Sentence {index} has a sentiment score of {sentence_sentiment}")
+
+    st.write(f"Overall Sentiment: score of {score} with magnitude of {magnitude}")
+
+def analyze_sentiment(texts):
+    # Load credentials directly from secrets (load as JSON)
+    credentials_info = json.loads(st.secrets["GOOGLE_APPLICATION_CREDENTIALS"])
+    credentials = service_account.Credentials.from_service_account_info(credentials_info)
+
     client = language_v1.LanguageServiceClient(credentials=credentials)
 
-    # Include options for entity analysis
     document = language_v1.Document(content=texts, type_=language_v1.Document.Type.PLAIN_TEXT)
     annotations = client.analyze_sentiment(request={"document": document})
 
@@ -48,7 +32,7 @@ text_input = st.text_area("Text to analyze", height=200)
 
 if st.button("Analyze Sentiment"):
     if text_input:
-        annotations = analyze_sentiment(text_input, credentials)  
+        annotations = analyze_sentiment(text_input) 
         print_result(annotations)
     else:
         st.warning("Please enter some text.")