Update app.py

app.py

@@ -19,10 +19,11 @@ from pyabsa import (
 )
 from pyabsa import ABSAInstruction
 from pyabsa.utils.data_utils.dataset_manager import detect_infer_dataset
-
+import requests
 
 download_all_available_datasets()
 
+
 def get_atepc_example(dataset):
     task = TaskCodeOption.Aspect_Polarity_Classification
     dataset_file = detect_infer_dataset(atepc_dataset_items[dataset], task)
@@ -46,6 +47,7 @@ def get_atepc_example(dataset):
             )
         return sorted(set(lines), key=lines.index)
 
+
 def get_aste_example(dataset):
     task = TaskCodeOption.Aspect_Sentiment_Triplet_Extraction
     dataset_file = detect_infer_dataset(aste_dataset_items[dataset], task)
@@ -62,6 +64,7 @@ def get_aste_example(dataset):
             fin.close()
         return sorted(set(lines), key=lines.index)
 
+
 def get_acos_example(dataset):
     task = "ACOS"
     dataset_file = detect_infer_dataset(acos_dataset_items[dataset], task)
@@ -79,6 +82,7 @@ def get_acos_example(dataset):
         lines = [line.split("####")[0] for line in lines]
         return sorted(set(lines), key=lines.index)
 
+
 try:
     from pyabsa import AspectTermExtraction as ATEPC
 
@@ -99,16 +103,12 @@ except Exception as e:
 try:
     from pyabsa import AspectSentimentTripletExtraction as ASTE
 
-    aste_dataset_items = {
-        dataset.name: dataset for dataset in ASTE.ASTEDatasetList()
-    }
+    aste_dataset_items = {dataset.name: dataset for dataset in ASTE.ASTEDatasetList()}
     aste_dataset_dict = {
         dataset.name: get_aste_example(dataset.name)
         for dataset in ASTE.ASTEDatasetList()[:-1]
     }
-    triplet_extractor = ASTE.AspectSentimentTripletExtractor(
-        checkpoint="multilingual"
-    )
+    triplet_extractor = ASTE.AspectSentimentTripletExtractor(checkpoint="multilingual")
 except Exception as e:
     print(e)
     aste_dataset_items = {}
@@ -179,6 +179,44 @@ def perform_acos_inference(text, dataset):
     return result, text
 
 
+def run_demo(text, dataset, task):
+    try:
+        data = {
+            "text": text,
+            "dataset": dataset,
+            "task": task,
+        }
+        response = requests.post("https://pyabsa.pagekite.me/api/inference", json=data)
+        result = response.json()
+        print(response.json())
+        if task == "ATEPC":
+            return (
+                pd.DataFrame(
+                    {
+                        "aspect": result["aspect"],
+                        "sentiment": result["sentiment"],
+                        # 'probability': result[0]['probs'],
+                        "confidence": [round(x, 4) for x in result["confidence"]],
+                        "position": result["position"],
+                    }
+                ),
+                result["text"],
+            )
+        elif task == "ASTE":
+            return (
+                        pd.DataFrame(result["pred_triplets"]),
+                        pd.DataFrame(result["true_triplets"]),
+                        result["text"],
+                    )
+        elif task == "ACOS":
+            return pd.DataFrame(result["Quadruples"]), result["text"]
+
+    except Exception as e:
+        print(e)
+        print("Failed to connect to the server, running locally...")
+        return inference(text, dataset, task)
+
+
 def inference(text, dataset, task):
     if task == "ATEPC":
         return perform_atepc_inference(text, dataset)
@@ -220,8 +258,12 @@ if __name__ == "__main__":
                         acos_output_pred_df = gr.DataFrame(label="Predicted Triplets:")
 
                         acos_inference_button.click(
-                            fn=inference,
-                            inputs=[acos_input_sentence, acos_dataset_ids, gr.Text("ACOS")],
+                            fn=run_demo,
+                            inputs=[
+                                acos_input_sentence,
+                                acos_dataset_ids,
+                                gr.Text("ACOS", visible=False),
+                            ],
                             outputs=[acos_output_pred_df, acos_output_text],
                         )
         with gr.Row():
@@ -259,8 +301,12 @@ if __name__ == "__main__":
                             )
 
                             aste_inference_button.click(
-                                fn=inference,
-                                inputs=[aste_input_sentence, aste_dataset_ids, gr.Text("ASTE")],
+                                fn=run_demo,
+                                inputs=[
+                                    aste_input_sentence,
+                                    aste_dataset_ids,
+                                    gr.Text("ASTE", visible=False),
+                                ],
                                 outputs=[
                                     aste_output_pred_df,
                                     aste_output_true_df,
@@ -295,11 +341,11 @@ if __name__ == "__main__":
                             atepc_output_df = gr.DataFrame(label="Prediction Results:")
 
                             atepc_inference_button.click(
-                                fn=inference,
+                                fn=run_demo,
                                 inputs=[
                                     atepc_input_sentence,
                                     atepc_dataset_ids,
-                                    gr.Text("ATEPC"),
+                                    gr.Text("ATEPC", visible=False),
                                 ],
                                 outputs=[atepc_output_df, atepc_output_text],
                             )