feat(JAQPOT-361): support jaqpot metadata (#33)

src/handlers/predict_sklearn.py

@@ -6,7 +6,7 @@
 
 def sklearn_post_handler(request: PredictionRequestPydantic):
     model = model_decoder.decode(request.model["rawModel"])
-    data_entry_all, JaqpotInternalId = json_to_predreq.decode(request)
+    data_entry_all, jaqpot_row_ids = json_to_predreq.decode(request)
     prediction = predict_onnx(model, data_entry_all, request)
     task = request.model["task"].lower()
     if task == "binary_classification" or task == "multiclass_classification":
@@ -15,26 +15,26 @@ def sklearn_post_handler(request: PredictionRequestPydantic):
         probabilities = [None for _ in range(len(prediction))]
 
     final_all = []
-    for jaqpot_id in JaqpotInternalId:
+    for jaqpot_row_id in jaqpot_row_ids:
         if len(request.model["dependentFeatures"]) == 1:
             prediction = prediction.reshape(-1, 1)
-        jaqpot_id = int(jaqpot_id)
+        jaqpot_row_id = int(jaqpot_row_id)
         results = {
-            feature["key"]: int(prediction[jaqpot_id, i])
+            feature["key"]: int(prediction[jaqpot_row_id, i])
             if isinstance(
-                prediction[jaqpot_id, i], (np.int16, np.int32, np.int64, np.longlong)
+                prediction[jaqpot_row_id, i], (np.int16, np.int32, np.int64, np.longlong)
             )
-            else float(prediction[jaqpot_id, i])
+            else float(prediction[jaqpot_row_id, i])
             if isinstance(
-                prediction[jaqpot_id, i], (np.float16, np.float32, np.float64)
+                prediction[jaqpot_row_id, i], (np.float16, np.float32, np.float64)
             )
-            else prediction[jaqpot_id, i]
+            else prediction[jaqpot_row_id, i]
             for i, feature in enumerate(request.model["dependentFeatures"])
         }
-        results["jaqpotInternalId"] = jaqpot_id
         results["jaqpotInternalMetadata"] = {
             "AD": None,
-            "Probabilities": probabilities[jaqpot_id],
+            "probabilities": probabilities[jaqpot_row_id],
+            "jaqpotRowId": jaqpot_row_id
         }
         final_all.append(results)
 

src/helpers/json_to_predreq.py

@@ -5,9 +5,9 @@
 
 def decode(request):
     df = pd.DataFrame(request.dataset["input"])
-    jaqpot_Internal_Id = []
+    jaqpot_row_ids = []
     for i in range(len(df)):
-        jaqpot_Internal_Id.append(df.iloc[i]["jaqpotInternalId"])
+        jaqpot_row_ids.append(df.iloc[i]["jaqpotRowId"])
     independent_features = request.model["independentFeatures"]
     smiles_cols = [
         feature["key"]
@@ -36,4 +36,4 @@ def decode(request):
         task=request.model["task"].lower(),
         featurizer=featurizers,
     )
-    return dataset, jaqpot_Internal_Id
+    return dataset, jaqpot_row_ids