Update app.py

app.py

@@ -16,25 +16,42 @@ def load_model(model_name):
     return model, tokenizer
 
 
-def inference(prompt):
+def inference(prompt_inputs):
+
     model_name = "Unggi/feedback_prize_kor"
 
     model, tokenizer = load_model(
         model_name = model_name
     )
 
-    inputs = tokenizer(
-        prompt, 
-        return_tensors="pt"
-        )
+    # prompt 구두점 단위로 분리하기
+    prompt_list = prompt_inputs.split('.|!|?')
+
+    class_id_list = []
+
+    for prompt in prompt_list:
+        inputs = tokenizer(
+            prompt, 
+            return_tensors="pt"
+            )
+    
+        with torch.no_grad():
+            logits = model(**inputs).logits
+    
+        predicted_class_id = logits.argmax().item()
+        class_id = model.config.id2label[predicted_class_id]
+
+        class_id_list.append(class_id)
+
+    outputs = []
+
+    for p, c_id in zip(prompt_list, class_id_list):
 
-    with torch.no_grad():
-        logits = model(**inputs).logits
+        outputs.append(p + '\t' + c_id)
 
-    predicted_class_id = logits.argmax().item()
-    class_id = model.config.id2label[predicted_class_id]
+    outputs = outputs.join('\n')
 
-    return class_id
+    return outputs
 
 demo = gr.Interface(
     fn=inference,