Update app.py

app.py

@@ -14,7 +14,7 @@ sentiment_analysis = pipeline("sentiment-analysis", model=model, tokenizer=token
 st.title("GPT-2 Movie Sentiment Analysis")
 
 # Input text for sentiment analysis
-input_text = st.text_area("Enter movie sentiment:", "")
+input_text = st.text_area("Enter movie review:", "")
 
 # Choose analysis type
 analysis_type = st.radio("Select analysis type:", ["Zero-shot", "One-shot", "Few-shot"])
@@ -22,18 +22,23 @@ analysis_type = st.radio("Select analysis type:", ["Zero-shot", "One-shot", "Few
 if st.button("Analyze Sentiment"):
     # Perform sentiment analysis based on the selected type
     if analysis_type == "Zero-shot":
+        prompt = "Label the text as either 'positive', 'negative', or 'mixed' related to a movie:"
+        input_text = prompt + "\n\n" + input_text
         results = sentiment_analysis(input_text)
     elif analysis_type == "One-shot":
-        # Use the input text as the single example
-        results = sentiment_analysis(f"This movie is about {input_text}")
+        prompt = "Label the sentence as either 'positive', 'negative', or 'mixed' related to a movie:\n\n" \
+                 "Sentence: This movie exceeded my expectations.\nLabel: positive"
+        input_text = prompt + " " + input_text
+        results = sentiment_analysis(input_text)
     elif analysis_type == "Few-shot":
-        # Use multiple examples for few-shot analysis
         examples = [
-            f"This movie sets an example of bad ethics. {input_text}",
-            f"I loved this movie. {input_text}",
-            f"The movie is neither good nor bad. {input_text}"
+            "Sentence: The cinematography in this movie is outstanding.\nLabel: positive",
+            "Sentence: I didn't enjoy the plot twists in the movie.\nLabel: negative",
+            "Sentence: The acting was great, but the pacing felt off.\nLabel: mixed",
+            "Sentence: This movie didn't live up to the hype.\nLabel: negative",
         ]
-        input_text = " ".join(examples)
+        prompt = "Label the sentences as either 'positive', 'negative', or 'mixed' related to a movie:\n\n" + "\n".join(examples)
+        input_text = prompt + "\n\n" + input_text
         results = sentiment_analysis(input_text)
 
     # Display results