separate the output parameter out from the base parameter which handl…

…es the component trace, and make the backward engine with only eval mode and without output a parameter

adalflow/adalflow/core/generator.py

@@ -21,7 +21,12 @@
 from adalflow.core.base_data_class import DataClass
 
 
-from adalflow.optim.parameter import Parameter, GradientContext, Gradient
+from adalflow.optim.parameter import (
+    Parameter,
+    GradientContext,
+    Gradient,
+    OutputParameter,
+)
 from adalflow.optim.types import ParameterType
 
 from adalflow.core.prompt_builder import Prompt
@@ -523,7 +528,7 @@ def forward(
             if output and not output.error
             else f"Error: {output.error}, raw_response: {output.raw_response}"
         )
-        response: Parameter = Parameter(
+        response: Parameter = OutputParameter(
             data=param_data,
             name=self.name + "_output",
             role_desc=f"Output from (llm) {self.name}",
@@ -740,6 +745,11 @@ def _backward_through_one_predecessor(
             gradient_output: GeneratorOutput = backward_engine(
                 prompt_kwargs=backward_engine_prompt_kwargs
             )
+            if not isinstance(gradient_output, GeneratorOutput):
+                raise ValueError(
+                    f"Generator: Backward Engine should return a GeneratorOutput. Got {gradient_output} instead."
+                )
+
         # USE this to trace each node's input and output, all nodes can be visualized
         log.info(
             f"Generator Backward Engine Prompt: {backward_engine.get_prompt( **backward_engine_prompt_kwargs)}"
@@ -748,9 +758,6 @@ def _backward_through_one_predecessor(
             gradient_output.data
             or backward_engine.failure_message_to_optimizer(gradient_output)
         )
-        log.info(
-            f"Generator Gradient value: {gradient_value}, raw response: {gradient_output.raw_response}"
-        )
         # TODO: make it a debug feature
         var_gradient = Gradient(
             data=gradient_value,
@@ -947,7 +954,11 @@ class BackwardEngine(Generator):  # it is a generator with defaule template
 
     __doc__ = """The backward engine is a Generator with a default template for the backward pass.
 
-    If you want to customize the template, you can create your own backward engine"""
+    If you want to customize the template, you can create your own backward engine.
+
+    Yet, we will forever keep the training mode to False for the backward engine.
+    This is achieved by making forward the same as call.
+    """
 
     def __init__(self, **kwargs):
         if kwargs is None:
@@ -965,6 +976,10 @@ def call(self, **kwargs) -> GeneratorOutputType:
             raise ValueError(f"Error in the backward engine: {output.error}")
         return output
 
+    def forward(self, **kwargs):
+        r"""Forward pass for the backward engine."""
+        return self.call(**kwargs)
+
     @staticmethod
     def failure_message_to_optimizer(
         gradient_response: GeneratorOutput,

adalflow/adalflow/optim/grad_component.py

@@ -64,7 +64,7 @@ def forward(self, *args, **kwargs) -> "Parameter":
         3. Return the parameter object.
         """
 
-        from adalflow.optim.parameter import Parameter
+        from adalflow.optim.parameter import Parameter, OutputParameter
 
         log.debug(
             f"Forwarding through {self.name} with args: {args} and kwargs: {kwargs}"
@@ -122,7 +122,7 @@ def forward(self, *args, **kwargs) -> "Parameter":
 
         # 4. Create a Parameter object to trace the forward pass
         input_args.update(kwargs)
-        response = Parameter(
+        response = OutputParameter(
             data=call_response,
             name=self.name + "_output",
             role_desc=self.name + " response",

adalflow/adalflow/optim/loss_component.py

@@ -1,6 +1,7 @@
 """Base class for Autograd Components that can be called and backpropagated through."""
 
 from typing import TYPE_CHECKING
+import uuid
 
 if TYPE_CHECKING:
     from adalflow.core.generator import BackwardEngine
@@ -27,10 +28,12 @@ class LossComponent(Component):
     """
     backward_engine: "BackwardEngine"
     _component_type = "loss"
+    id = None
 
     def __init__(self, *args, **kwargs):
         super().__init__()
         super().__setattr__("backward_engine", None)
+        super().__setattr__("id", str(uuid.uuid4()))
 
     def __call__(self, *args, **kwargs):
         return self.forward(*args, **kwargs)