Update app.py

app.py

@@ -1 +1,49 @@
-st.write(st.secrets["GOOGLE_APPLICATION_CREDENTIALS"])
+import streamlit as st
+from google.cloud import language_v1
+from google.oauth2 import service_account
+import json
+
+# Load credentials from Hugging Face Secrets
+def load_credentials():
+    credentials_info = json.loads(st.secrets["GOOGLE_APPLICATION_CREDENTIALS"])
+    return service_account.Credentials.from_service_account_info(credentials_info)
+
+# Create a Language Service client with the provided credentials
+def get_language_client():
+    credentials = load_credentials()
+    return language_v1.LanguageServiceClient(credentials=credentials)
+
+# Perform sentiment analysis on the input text
+def analyze_sentiment(texts):
+    client = get_language_client()
+    document = language_v1.Document(content=texts, type_=language_v1.Document.Type.PLAIN_TEXT)
+    return client.analyze_sentiment(request={"document": document})
+
+# Display sentiment analysis results
+def display_sentiment_results(annotations):
+    score = annotations.document_sentiment.score
+    magnitude = annotations.document_sentiment.magnitude
+
+    for index, sentence in enumerate(annotations.sentences):
+        sentence_sentiment = sentence.sentiment.score
+        st.write(f"Sentence {index} has a sentiment score of {sentence_sentiment}")
+
+    st.write(f"Overall Sentiment: score of {score} with magnitude of {magnitude}")
+
+# Main function to run the app
+def main():
+    st.title("Sentiment Analysis App")
+    st.write("Enter some text to analyze its sentiment:")
+
+    text_input = st.text_area("Text to analyze", height=200)
+
+    if st.button("Analyze Sentiment"):
+        if text_input:
+            annotations = analyze_sentiment(text_input)
+            display_sentiment_results(annotations)
+        else:
+            st.warning("Please enter some text.")
+
+# Run the app
+if __name__ == "__main__":
+    main()