Update app.py

app.py

@@ -1,21 +1,26 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load the Hugging Face model for keyword/keyphrase extraction
-extractor = pipeline("text2text-generation", model="ml6team/keyphrase-extraction-distilbert-inspec")
+# Load a ready-made keyword extraction / summarization model
+extractor = pipeline("summarization", model="pszemraj/keyword-extraction-distilbart-cnn-12-6")
 
 def extract_keywords(text):
     if not text.strip():
         return "⚠️ Please enter some text."
-    result = extractor(text, max_length=64, clean_up_tokenization_spaces=True)
-    return result[0]['generated_text']
+    try:
+        result = extractor(text, max_length=64, min_length=5, do_sample=False)
+        keywords = result[0]['summary_text']
+        return f"🧠 **Extracted Keywords:**\n\n{keywords}"
+    except Exception as e:
+        return f"❌ Error: {str(e)}"
 
 demo = gr.Interface(
     fn=extract_keywords,
-    inputs=gr.Textbox(lines=6, placeholder="Enter medical or general text here..."),
-    outputs="text",
-    title="🔍 Keyword Extraction",
-    description="Extract key phrases and keywords using a Hugging Face Transformer model."
+    inputs=gr.Textbox(label="📝 Enter text here", lines=6, placeholder="Paste medical or general text..."),
+    outputs=gr.Markdown(label="📊 Keywords"),
+    title="🔍 Keyword Extractor (Hugging Face Model)",
+    description="A lightweight keyword extraction tool using a fine-tuned DistilBART model.",
+    theme="soft"
 )
 
 if __name__ == "__main__":