Update app.py

app.py

@@ -1,14 +1,28 @@
 import gradio as gr
-from textblob import TextBlob
-
-# Define the sentiment analysis function
-def analyze_sentiment(text):
-	blob = TextBlob(text)
-	polarity = blob.sentiment.polarity
-	subjectivity = blob.sentiment.subjectivity
-	sentiment = "POSITIVE" if polarity >= 0 else "NEGATIVE"
-	return f"Sentiment: {sentiment}\nPolarity: {polarity:.2f}\nSubjectivity: {subjectivity:.2%}"
-
-# Create a Gradio interface
-iface = gr.Interface(fn=analyze_sentiment, inputs="text", outputs="text")
-iface.launch()
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+
+# Load the GPT-2 model and tokenizer
+model_name = "gpt2"
+model = GPT2LMHeadModel.from_pretrained(model_name)
+tokenizer = GPT2Tokenizer.from_pretrained(model_name)
+
+# Define the sentence completion function
+def complete_sentence(sentence):
+	input_ids = tokenizer.encode(sentence, return_tensors="pt")
+	output = model.generate(input_ids, max_length=50, num_return_sequences=1)
+	completed_sentence = tokenizer.decode(output[0], skip_special_tokens=True)
+	return completed_sentence
+
+# Create the Gradio interface
+iface = gr.Interface(
+	fn=complete_sentence,
+	inputs="text",
+	outputs="text",
+	title="Sentence Completion",
+	description="Enter a sentence to complete",
+	example="I love to"
+)
+
+# Launch the Gradio interface
+if __name__ == "__main__":
+	iface.launch()