Update inference_server.py

inference_server.py

@@ -16,8 +16,13 @@ model.eval()
 # Load the BERT tokenizer
 tokenizer = transformers.BertTokenizer.from_pretrained('bert-base-cased')
 def predict(input_text: str):
-    # Add the new input string to the set of strings
-    strings.add(input_text)
+    # Add the new input string to the file
+    with open('strings.txt','a') as f:
+        f.write(input_text + '\n')
+        
+    # Read all the strings from the file
+    with open('strings.txt', 'r') as f:
+        strings = set(f.read().splitlines())
     # Convert the input strings to input tensors for the BERT LM
     input_tensors = tokenizer.batch_encode_plus(list(strings), max_length=512,
                                                                                     pad_to_max_length=True, return_tensors='pt')