update after API breaking change

app.py

@@ -1,11 +1,10 @@
 import copy
-import pandas as pd
 from typing import Optional
 
+import pandas as pd
 import requests
 import streamlit as st
 
-
 http_session = requests.Session()
 
 LOCAL_DB = False
@@ -20,7 +19,7 @@ PREDICTION_URL = ROBOTOFF_BASE_URL + "/predict/category"
 
 @st.cache_data
 def get_predictions(barcode: str, threshold: Optional[float] = None):
-    data = {"barcode": barcode, "predictors": ["neural"]}
+    data = {"barcode": barcode}
     if threshold is not None:
         data["threshold"] = threshold
 
@@ -28,6 +27,7 @@ def get_predictions(barcode: str, threshold: Optional[float] = None):
     r.raise_for_status()
     return r.json()["neural"]
 
+
 def display_predictions(
     barcode: str,
     threshold: Optional[float] = None,
@@ -40,20 +40,17 @@ def display_predictions(
             debug = response["debug"]
         response.pop("debug")
     st.write(pd.DataFrame(response["predictions"]))
-    
+
     if debug is not None:
         st.markdown("**Debug information**")
         st.write(debug)
 
 
-
 st.sidebar.title("Category Prediction Demo")
 query_params = st.experimental_get_query_params()
 
 default_barcode = query_params["barcode"][0] if "barcode" in query_params else ""
-barcode = st.sidebar.text_input(
-    "Product barcode", default_barcode
-)
+barcode = st.sidebar.text_input("Product barcode", default_barcode)
 threshold = st.sidebar.number_input("Threshold", format="%f", value=0.5) or None
 
 if barcode: