Create app.py

app.py

@@ -0,0 +1,36 @@
+import gradio as gr
+import requests
+import os
+
+API_URL = "https://api-inference.huggingface.co/models/DISLab/SummLlama3.2-3B"
+
+def summarize(text):
+    headers = {"Authorization": f"Bearer {os.environ.get('HF_TOKEN')}"}
+    payload = {"inputs": text}
+    
+    try:
+        response = requests.post(API_URL, headers=headers, json=payload)
+        response.raise_for_status()
+        result = response.json()
+        
+        # Handle different response formats
+        if isinstance(result, list) and len(result) > 0:
+            return result[0].get('summary_text', result[0].get('generated_text', str(result[0])))
+        elif isinstance(result, dict):
+            return result.get('summary_text', result.get('generated_text', str(result)))
+        else:
+            return str(result)
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Create Gradio interface
+demo = gr.Interface(
+    fn=summarize,
+    inputs=gr.Textbox(lines=10, placeholder="Enter text to summarize..."),
+    outputs=gr.Textbox(label="Summary"),
+    title="SummLlama3.2-3B Summarization",
+    description="Test the DISLab/SummLlama3.2-3B model using Hugging Face Inference API"
+)
+
+if __name__ == "__main__":
+    demo.launch()