chore: update gradio and add error message when wrong order execution

app.py

@@ -71,7 +71,8 @@ def keygen():
 
 
 def encode_quantize_encrypt(text, user_id):
-    assert user_id != [], "Please, wait for the creation of FHE keys before trying to encrypt."
+    if not user_id:
+        raise gr.Error("You need to generate FHE keys first.")
 
     fhe_api = FHEModelClient("sentiment_fhe_model/deployment", f".fhe_keys/{user_id}")
     fhe_api.load()
@@ -102,10 +103,14 @@ def encode_quantize_encrypt(text, user_id):
 
 
 def run_fhe(user_id):
-    assert user_id != [], "Please, wait for the creation of FHE keys before trying to predict."
+    encoded_data_path = Path(f"tmp/tmp_encrypted_quantized_encoding_{user_id}.npy")
+    if not user_id:
+        raise gr.Error("You need to generate FHE keys first.")
+    if not encoded_data_path.is_file():
+        raise gr.Error("No encrypted data was found. Encrypt the data before trying to predict.")
 
     # Read encrypted_quantized_encoding from the file
-    encrypted_quantized_encoding = numpy.load(f"tmp/tmp_encrypted_quantized_encoding_{user_id}.npy")
+    encrypted_quantized_encoding = numpy.load(encoded_data_path)
 
     # Read evaluation_key from the file
     evaluation_key = numpy.load(f"tmp/tmp_evaluation_key_{user_id}.npy")
@@ -132,10 +137,14 @@ def run_fhe(user_id):
 
 
 def decrypt_prediction(user_id):
-    assert user_id != [], "Please, wait for the creation of FHE keys before trying to decrypt."
+    encoded_data_path = Path(f"tmp/tmp_encrypted_prediction_{user_id}.npy")
+    if not user_id:
+        raise gr.Error("You need to generate FHE keys first.")
+    if not encoded_data_path.is_file():
+        raise gr.Error("No encrypted prediction was found. Run the prediction over the encrypted data first.")
 
     # Read encrypted_prediction from the file
-    encrypted_prediction = numpy.load(f"tmp/tmp_encrypted_prediction_{user_id}.npy").tobytes()
+    encrypted_prediction = numpy.load(encoded_data_path).tobytes()
 
     fhe_api = FHEModelClient("sentiment_fhe_model/deployment", f".fhe_keys/{user_id}")
     fhe_api.load()

requirements.txt

@@ -1,5 +1,5 @@
 concrete-ml==0.4.0
-gradio==3.1.0
+gradio==3.10.0
 pandas==1.4.3
 uvicorn==0.18.2
 transformers==4.20.1