diff --git a/garak b/garak
new file mode 160000
index 000000000..a4e29f929
--- /dev/null
+++ b/garak
@@ -0,0 +1 @@
+Subproject commit a4e29f929a0247682d2bc82a615d7c9eb6a6936f
diff --git a/nemoguardrails/integrations/langchain/runnable_rails.py b/nemoguardrails/integrations/langchain/runnable_rails.py
index 1eb282848..961f8af4f 100644
--- a/nemoguardrails/integrations/langchain/runnable_rails.py
+++ b/nemoguardrails/integrations/langchain/runnable_rails.py
@@ -15,7 +15,7 @@
 
 from __future__ import annotations
 
-from typing import Any, List, Optional
+from typing import Any, List, Literal, Optional
 
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
@@ -41,6 +41,7 @@ def __init__(
         input_key: str = "input",
         output_key: str = "output",
         verbose: bool = False,
+        consistent_output_format: Literal["preserve", "always_dict", "always_string"] = "preserve",
     ) -> None:
         self.llm = llm
         self.passthrough = passthrough
@@ -48,7 +49,10 @@ def __init__(
         self.passthrough_user_input_key = input_key
         self.passthrough_bot_output_key = output_key
         self.verbose = verbose
+        self.consistent_output_format = consistent_output_format
         self.config: Optional[RunnableConfig] = None
+        self._current_config: Optional[RunnableConfig] = None
+        self._current_kwargs: dict = {}
 
         # We override the config passthrough.
         config.passthrough = passthrough
@@ -74,7 +78,10 @@ async def passthrough_fn(context: dict, events: List[dict]):
             # First, we fetch the input from the context
             _input = context.get("passthrough_input")
             async_wrapped_invoke = async_wrap(self.passthrough_runnable.invoke)
-            _output = await async_wrapped_invoke(_input, self.config, **self.kwargs)
+            
+            # Pass the config and kwargs that were captured in the invoke method
+            # This ensures that callbacks (like Langfuse tracing) are properly propagated
+            _output = await async_wrapped_invoke(_input, self._current_config, **self._current_kwargs)
 
             # If the output is a string, we consider it to be the output text
             if isinstance(_output, str):
@@ -86,6 +93,36 @@ async def passthrough_fn(context: dict, events: List[dict]):
 
         self.rails.llm_generation_actions.passthrough_fn = passthrough_fn
 
+    def _format_output_consistently(self, output: Any, input_type: Any) -> Any:
+        """Format output according to consistent_output_format setting."""
+        if self.consistent_output_format == "preserve":
+            return output
+        elif self.consistent_output_format == "always_dict":
+            if isinstance(output, str):
+                return {self.passthrough_bot_output_key: output}
+            elif isinstance(output, dict):
+                return output
+            else:
+                return {self.passthrough_bot_output_key: str(output)}
+        elif self.consistent_output_format == "always_string":
+            if isinstance(output, dict):
+                # Try to extract string from dict
+                if self.passthrough_bot_output_key in output:
+                    return output[self.passthrough_bot_output_key]
+                elif "content" in output:
+                    return output["content"]
+                elif "output" in output:
+                    return output["output"]
+                else:
+                    # Return the first string value found or convert to string
+                    for value in output.values():
+                        if isinstance(value, str):
+                            return value
+                    return str(output)
+            else:
+                return str(output)
+        return output
+
     def __or__(self, other):
         if isinstance(other, BaseLanguageModel):
             self.llm = other
@@ -188,8 +225,12 @@ def invoke(
     ) -> Output:
         """Invoke this runnable synchronously."""
         input_messages = self._transform_input_to_rails_format(input)
+        # Store config and kwargs for use in passthrough function
+        # This ensures callbacks are properly passed to the underlying runnable
         self.config = config
         self.kwargs = kwargs
+        self._current_config = config
+        self._current_kwargs = kwargs
         res = self.rails.generate(
             messages=input_messages, options=GenerationOptions(output_vars=True)
         )
@@ -222,20 +263,25 @@ def invoke(
             elif isinstance(passthrough_output, dict):
                 passthrough_output[self.passthrough_bot_output_key] = bot_message
 
-            return passthrough_output
+            return self._format_output_consistently(passthrough_output, type(input))
         else:
             if isinstance(input, ChatPromptValue):
-                return AIMessage(content=result["content"])
+                output = AIMessage(content=result["content"])
+                return self._format_output_consistently(output, type(input))
             elif isinstance(input, StringPromptValue):
                 if isinstance(result, dict):
-                    return result["content"]
+                    output = result["content"]
                 else:
-                    return result
+                    output = result
+                return self._format_output_consistently(output, type(input))
             elif isinstance(input, dict):
                 user_input = input["input"]
                 if isinstance(user_input, str):
-                    return {"output": result["content"]}
+                    output = {"output": result["content"]}
                 elif isinstance(user_input, list):
-                    return {"output": result}
+                    output = {"output": result}
+                else:
+                    output = {"output": result["content"]}
+                return self._format_output_consistently(output, type(input))
             else:
                 raise ValueError(f"Unexpected input type: {type(input)}")
diff --git a/tests/test_runnable_rails.py b/tests/test_runnable_rails.py
index 10b33c056..453cb685e 100644
--- a/tests/test_runnable_rails.py
+++ b/tests/test_runnable_rails.py
@@ -658,3 +658,124 @@ def log(x):
     print(result)
     assert "LOL" not in result["output"]
     assert "can't respond" in result["output"]
+
+
+def test_runnable_config_callback_passthrough():
+    """Test that RunnableConfig with callbacks is properly passed to passthrough runnable."""
+    config_received = []
+    
+    class CallbackTestRunnable(Runnable):
+        def invoke(self, input: Input, config: Optional[RunnableConfig] = None) -> Output:
+            # Capture the config to verify callbacks were passed
+            config_received.append(config)
+            return {"output": "Test response"}
+    
+    # Create a mock callback for testing
+    mock_callbacks = ["mock_callback"]
+    test_config = RunnableConfig(callbacks=mock_callbacks)
+    
+    rails_config = RailsConfig.from_content(config={"models": []})
+    runnable_with_rails = RunnableRails(
+        rails_config, passthrough=True, runnable=CallbackTestRunnable()
+    )
+    
+    # Invoke with the config containing callbacks
+    result = runnable_with_rails.invoke("test input", config=test_config)
+    
+    # Verify that the config with callbacks was passed through
+    assert len(config_received) == 1
+    assert config_received[0] is not None
+    assert config_received[0].get("callbacks") == mock_callbacks
+    assert result == {"output": "Test response"}
+
+
+def test_consistent_output_format_preserve():
+    """Test that preserve mode maintains original inconsistent behavior."""
+    config = RailsConfig.from_content(config={"models": []})
+    
+    # Test normal passthrough (should return string)
+    runnable_with_rails = RunnableRails(
+        config, passthrough=True, runnable=MockRunnable2(), 
+        consistent_output_format="preserve"
+    )
+    result = runnable_with_rails.invoke("test input")
+    assert result == "PARIS!!"  # String format preserved
+    
+    
+def test_consistent_output_format_always_dict():
+    """Test that always_dict mode forces dictionary format."""
+    config = RailsConfig.from_content(config={"models": []})
+    
+    # Test with string output - should be converted to dict
+    runnable_with_rails = RunnableRails(
+        config, passthrough=True, runnable=MockRunnable2(),
+        consistent_output_format="always_dict"
+    )
+    result = runnable_with_rails.invoke("test input")
+    assert result == {"output": "PARIS!!"}  # Converted to dict
+    
+    # Test with dict output - should remain dict
+    runnable_with_rails2 = RunnableRails(
+        config, passthrough=True, runnable=MockRunnable(),
+        consistent_output_format="always_dict"
+    )
+    result2 = runnable_with_rails2.invoke("test input")
+    assert result2 == {"output": "PARIS!!"}  # Already dict format
+
+
+def test_consistent_output_format_always_string():
+    """Test that always_string mode forces string format when possible."""
+    config = RailsConfig.from_content(config={"models": []})
+    
+    # Test with dict output - should be converted to string
+    runnable_with_rails = RunnableRails(
+        config, passthrough=True, runnable=MockRunnable(),
+        consistent_output_format="always_string"
+    )
+    result = runnable_with_rails.invoke("test input")
+    assert result == "PARIS!!"  # Extracted from dict
+    
+    # Test with string output - should remain string
+    runnable_with_rails2 = RunnableRails(
+        config, passthrough=True, runnable=MockRunnable2(),
+        consistent_output_format="always_string" 
+    )
+    result2 = runnable_with_rails2.invoke("test input")
+    assert result2 == "PARIS!!"  # Already string
+
+
+def test_consistent_output_format_with_rails_blocking():
+    """Test consistent format when rails block the input/output."""
+    llm = FakeLLM(responses=["  ask off topic question", "  ask off topic question"])
+    config = RailsConfig.from_content(
+        config={"models": []},
+        colang_content="""
+            define user ask off topic question
+              "Can you help me cook something?"
+
+            define flow
+              user ask off topic question
+              bot refuse to respond
+
+            define bot refuse to respond
+              "I'm sorry, I can't help with that."
+            """,
+    )
+
+    # Test with always_string - even when rails trigger, should return string
+    runnable_with_rails = RunnableRails(
+        config, llm=llm, passthrough=True, runnable=MockRunnable(),
+        consistent_output_format="always_string"
+    )
+    result = runnable_with_rails.invoke("This is an off topic question")
+    assert isinstance(result, str)
+    assert result == "I'm sorry, I can't help with that."
+    
+    # Test with always_dict - should return dict format
+    runnable_with_rails2 = RunnableRails(
+        config, llm=llm, passthrough=True, runnable=MockRunnable(),
+        consistent_output_format="always_dict"
+    )
+    result2 = runnable_with_rails2.invoke("This is an off topic question")
+    assert isinstance(result2, dict)
+    assert result2 == {"output": "I'm sorry, I can't help with that."}