fixed pydantic error

Author: Shakiran-Nannyombi

.github/workflows/ci.yml

@@ -12,7 +12,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: [3.11]
+        python-version: [3.11, 3.12, 3.13]
 
     steps:
       - name: Checkout

backend/api/routers/predict.py

@@ -45,8 +45,9 @@ async def predict_caloric_needs(
         raise HTTPException(status_code=500, detail="Model loader not initialized")
 
     try:
-        # Convert Pydantic model to dict
-        input_dict = input_data.dict()
+        # Convert Pydantic model to dict (use model_dump for Pydantic v2)
+        # `model_dump` is the v2 replacement for `.dict()` and returns a dict.
+        input_dict = input_data.model_dump()
 
         # Make prediction
         result = model_loader.predict(input_dict, model_preference=model)
@@ -89,7 +90,7 @@ async def batch_predict(
 
     for input_data in batch_input.inputs:
         try:
-            input_dict = input_data.dict()
+            input_dict = input_data.model_dump()
             result = model_loader.predict(input_dict, model_preference=model_pref)
             results.append(result)
 

backend/tests/test_loader_and_api.py

@@ -9,18 +9,19 @@
 from fastapi.testclient import TestClient
 
 
-def make_dummy_model(pred_value=123.45, feature_names=None):
-    class DummyModel:
-        def __init__(self, v, cols=None):
-            self._v = v
-            if cols is not None:
-                # mimic scikit-learn attribute
-                self.feature_names_in_ = cols
+class DummyModel:
+    def __init__(self, v, cols=None):
+        self._v = v
+        if cols is not None:
+            # mimic scikit-learn attribute
+            self.feature_names_in_ = cols
+
+    def predict(self, X):
+        # return array-like
+        return [self._v] * len(X)
 
-        def predict(self, X):
-            # return array-like
-            return [self._v] * len(X)
 
+def make_dummy_model(pred_value=123.45, feature_names=None):
     return DummyModel(pred_value, feature_names)