successfully returning data on how the neural network performed

app.py

@@ -28,7 +28,6 @@ def not_valid(params: dict):
 @app.route("/", methods=["GET"])
 def index():
     params = request.json
-    print(params)
     error_message = not_valid(params=params)
     if error_message:
         return make_response(error_message, 400)
@@ -44,7 +43,7 @@ def index():
     return jsonify(model)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     app.run(
         debug=True,
     )

neural_network/neural_network.py

@@ -25,6 +25,7 @@ class NeuralNetwork:
         return self.compute_node(n1, self.w2, self.b2, self.activation_func)
 
     def set_loss_hist(self, loss_hist: list) -> None:
+        assert (isinstance(loss_hist, list))
         self.loss_history = loss_hist
 
     def eval(self, X_test, y_test) -> None:
@@ -35,18 +36,20 @@ class NeuralNetwork:
         return func(np.dot(arr, w) + b)
 
     @classmethod
-    def from_dict(cls, dct):
+    def from_dict(cls, dct) -> "NeuralNetwork":
         return cls(**dct)
 
-    def to_dict(self) -> dict:
+    def to_dict(self) -> dict[str, list | int | float | str]:
         return {
-            "w1": list(self.w1),
-            "w2": list(self.w2),
-            "b1": list(self.b1),
-            "b2": list(self.b2),
+            "w1": self.w1.tolist(),
+            "w2": self.w2.tolist(),
+            "b1": self.b1.tolist(),
+            "b2": self.b2.tolist(),
             "epochs": self.epochs,
             "learning_rate": self.learning_rate,
             "activation_func": self.activation_func.__name__,
             "func_prime": self.func_prime.__name__,
             "hidden_size": self.hidden_size,
+            "mse": self.mse,
+            "loss_history": self.loss_history,
         }