Update app.py

app.py

@@ -1,47 +1,60 @@
 import gradio as gr
 from transformers import pipeline
+import numpy as np
 
-# Initialize a sentiment analysis pipeline
+# Initialize models
 sentiment_analyzer = pipeline("sentiment-analysis")
+text_generator = pipeline("text-generation", model="gpt2")
 
 def analyze_sentiment(text):
-    if not text.strip():
-        return "Please enter some text to analyze"
-    
     result = sentiment_analyzer(text)[0]
     return {
-        "Sentiment": result["label"],
-        "Confidence": f"{result['score']*100:.1f}%"
+        "text": text,
+        "sentiment": result["label"],
+        "confidence": f"{result['score']*100:.1f}%"
     }
 
-# Create the Gradio interface
-with gr.Blocks(title="Sentiment Analysis App") as demo:
-    gr.Markdown("# 🎭 Text Sentiment Analysis")
-    gr.Markdown("Enter some text and I'll analyze its sentiment using a Hugging Face model.")
-    
-    with gr.Row():
-        with gr.Column():
-            text_input = gr.Textbox(label="Your Text", placeholder="Type something here...")
-            analyze_btn = gr.Button("Analyze Sentiment")
-        with gr.Column():
-            json_output = gr.JSON(label="Analysis Results")
-    
-    # Additional examples
-    gr.Examples(
-        examples=[
-            "I love this product! It's amazing!",
-            "I'm really disappointed with the service.",
-            "The weather is nice today."
-        ],
-        inputs=text_input
-    )
+def generate_text(prompt, length=50):
+    generated = text_generator(prompt, max_length=length, num_return_sequences=1)
+    return generated[0]["generated_text"]
+
+with gr.Blocks(title="Multi-Function NLP App", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("""
+    # 🚀 Advanced NLP Playground
+    *Powered by Hugging Face Transformers*
+    """)
     
-    analyze_btn.click(
-        fn=analyze_sentiment,
-        inputs=text_input,
-        outputs=json_output
-    )
+    with gr.Tab("Sentiment Analysis"):
+        with gr.Row():
+            with gr.Column():
+                sentiment_input = gr.Textbox(label="Input Text", placeholder="Enter text to analyze...")
+                sentiment_button = gr.Button("Analyze")
+            with gr.Column():
+                sentiment_output = gr.JSON(label="Results")
+        
+        sentiment_examples = gr.Examples(
+            examples=[
+                "I'm absolutely thrilled with this service!",
+                "The product didn't meet my expectations.",
+                "It's okay, nothing special."
+            ],
+            inputs=sentiment_input
+        )
+        sentiment_button.click(analyze_sentiment, inputs=sentiment_input, outputs=sentiment_output)
+
+    with gr.Tab("Text Generation"):
+        with gr.Row():
+            with gr.Column():
+                gen_input = gr.Textbox(label="Prompt", placeholder="Start typing your idea...")
+                gen_slider = gr.Slider(20, 100, value=50, label="Output Length")
+                gen_button = gr.Button("Generate")
+            with gr.Column():
+                gen_output = gr.Textbox(label="Generated Text", lines=5)
+        
+        gen_button.click(generate_text, inputs=[gen_input, gen_slider], outputs=gen_output)
+
+    gr.Markdown("---")
+    gr.HTML("<center>Built with ❤️ using Gradio and Hugging Face</center>")
 
-# Launch the app
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(share=True)