Update app.py

app.py

@@ -1,25 +1,29 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load a ready-made keyword extraction / summarization model
-extractor = pipeline("summarization", model="pszemraj/keyword-extraction-distilbart-cnn-12-6")
+# ✅ Publicly available summarization model
+extractor = pipeline("summarization", model="facebook/bart-large-cnn")
 
 def extract_keywords(text):
     if not text.strip():
         return "⚠️ Please enter some text."
     try:
-        result = extractor(text, max_length=64, min_length=5, do_sample=False)
+        result = extractor(text, max_length=40, min_length=5, do_sample=False)
         keywords = result[0]['summary_text']
-        return f"🧠 **Extracted Keywords:**\n\n{keywords}"
+        return f"🧠 **Extracted Keywords (Approx):**\n\n{keywords}"
     except Exception as e:
         return f"❌ Error: {str(e)}"
 
 demo = gr.Interface(
     fn=extract_keywords,
-    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.",
+    inputs=gr.Textbox(
+        label="📝 Enter Text",
+        placeholder="Paste your text here...",
+        lines=6
+    ),
+    outputs=gr.Markdown(label="📊 Extracted Keywords"),
+    title="🔍 Keyword Extractor (using BART)",
+    description="A quick and lightweight keyword extractor built using `facebook/bart-large-cnn` summarization model.",
     theme="soft"
 )