Update app.py

app.py

@@ -1,5 +1,7 @@
 import gradio as gr
 from transformers import pipeline
+import json
+from datetime import datetime
 
 model = pipeline("token-classification", model="benchaffe/Bert-RAdam-Large", aggregation_strategy="simple")
 
@@ -13,18 +15,31 @@ def to_serializable(obj):
     else:
         return str(obj)
 
-def predict(text):
-    result = model(text)
+def log_interaction(input_text, prediction):
+    log_entry = {
+        "timestamp": datetime.now().isoformat(),
+        "input": input_text,
+        "prediction": to_serializable(prediction)
+    }
     with open("log.jsonl", "a") as f:
-        import json
-        from datetime import datetime
-        log_entry = {
-          "timestamp": datetime.now().isoformat(),
-          "input": text,
-          "prediction": to_serializable(result)
-        }
         f.write(json.dumps(log_entry) + "\n")
+
+def predict(text):
+    result = model(text)
+    log_interaction(text, result)
     return result
 
-interface = gr.Interface(fn=predict, inputs="text", outputs="json", title="Abbreviation Detector")
-interface.launch()
+with gr.Blocks() as demo:
+    gr.Markdown("## Biomedical Abbreviation Identifier")
+    
+    with gr.Row():
+        input_box = gr.Textbox(label="Enter biomedical text")
+        output_box = gr.JSON(label="Model Prediction")
+    
+    run_button = gr.Button("Submit")
+    run_button.click(fn=predict, inputs=input_box, outputs=output_box)
+    
+    gr.Markdown("### Download Interaction Logs")
+    gr.File(label="Download Logs", value="log.jsonl")
+
+demo.launch()