diff --git a/src/backend/langflow/interface/run.py b/src/backend/langflow/interface/run.py
index 48ba918a8..bab211c2a 100644
--- a/src/backend/langflow/interface/run.py
+++ b/src/backend/langflow/interface/run.py
@@ -67,40 +67,6 @@ def build_langchain_object(data_graph):
     return graph.build()
 
 
-def process_graph(data_graph: Dict[str, Any]):
-    """
-    Process graph by extracting input variables and replacing ZeroShotPrompt
-    with PromptTemplate,then run the graph and return the result and thought.
-    """
-    # Load langchain object
-    logger.debug("Loading langchain object")
-    message = data_graph.pop("message", "")
-    is_first_message = len(data_graph.get("chatHistory", [])) == 0
-    computed_hash, langchain_object = load_langchain_object(
-        data_graph, is_first_message
-    )
-    logger.debug("Loaded langchain object")
-
-    if langchain_object is None:
-        # Raise user facing error
-        raise ValueError(
-            "There was an error loading the langchain_object. Please, check all the nodes and try again."
-        )
-
-    # Generate result and thought
-    logger.debug("Generating result and thought")
-    result, thought = get_result_and_steps(langchain_object, message)
-    logger.debug("Generated result and thought")
-
-    # Save langchain_object to cache
-    # We have to save it here because if the
-    # memory is updated we need to keep the new values
-    logger.debug("Saving langchain object to cache")
-    # save_cache(computed_hash, langchain_object, is_first_message)
-    logger.debug("Saved langchain object to cache")
-    return {"result": str(result), "thought": thought.strip()}
-
-
 def process_graph_cached(data_graph: Dict[str, Any], message: str):
     """
     Process graph by extracting input variables and replacing ZeroShotPrompt
diff --git a/tests/test_graph.py b/tests/test_graph.py
index 73c05099f..a0f5945fc 100644
--- a/tests/test_graph.py
+++ b/tests/test_graph.py
@@ -14,7 +14,7 @@ from langflow.graph.nodes import (
     ToolNode,
     WrapperNode,
 )
-from langflow.interface.run import get_result_and_steps
+from langflow.interface.run import get_result_and_thought
 from langflow.utils.payload import get_root_node
 
 # Test cases for the graph module
@@ -335,7 +335,7 @@ def test_get_result_and_thought(basic_graph):
     # now build again and check if FakeListLLM was used
 
     # Get the result and thought
-    result, thought = get_result_and_steps(langchain_object, message)
+    result, thought = get_result_and_thought(langchain_object, message)
     # The result should be a str
     assert isinstance(result, str)
     # The thought should be a Thought