Create app.py

app.py

@@ -0,0 +1,29 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load your fine-tuned SpanBERT ADR model (replace with your actual model name)
+ner_pipeline = pipeline(
+    "token-classification",
+    model="hazarri/fine_tuned_spanbert",  # make sure this matches your uploaded model repo name
+    aggregation_strategy="simple"
+)
+
+def extract_adrs(text):
+    results = ner_pipeline(text)
+    if not results:
+        return "No ADR entities found."
+    
+    formatted = []
+    for r in results:
+        formatted.append(f"{r['word']} ({r['entity_group']}, score={r['score']:.2f})")
+    return "\n".join(formatted)
+
+demo = gr.Interface(
+    fn=extract_adrs,
+    inputs=gr.Textbox(lines=5, placeholder="Enter a medical review..."),
+    outputs="text",
+    title="SpanBERT ADR Extraction API",
+    description="Extracts adverse drug reactions (ADRs) from patient reviews using a fine-tuned SpanBERT model."
+)
+
+demo.launch()