diff --git a/src/backend/langflow/api/v1/endpoints.py b/src/backend/langflow/api/v1/endpoints.py
index e38906fbf..e99fb723f 100644
--- a/src/backend/langflow/api/v1/endpoints.py
+++ b/src/backend/langflow/api/v1/endpoints.py
@@ -1,9 +1,10 @@
 from langflow.database.models.flow import Flow
-from langflow.processing.process import process_graph_cached
+from langflow.processing.process import process_graph_cached, process_tweaks
 from langflow.utils.logger import logger
 from importlib.metadata import version
 
 from fastapi import APIRouter, Depends, HTTPException
+from fastapi.security import HTTPBearer
 
 from langflow.api.v1.schemas import (
     PredictRequest,
@@ -17,23 +18,40 @@ from sqlmodel import Session
 # build router
 router = APIRouter(tags=["Base"])
 
+security = HTTPBearer()
+
+
+def get_flow_from_token(
+    bearer: HTTPBearer = Depends(security), session: Session = Depends(get_session)
+) -> str:
+    # Extract the token, which is the flow_id in this case
+    flow_id = bearer.credentials
+    # Check if the flow_id exists in the database
+    flow = session.get(Flow, flow_id)
+    if flow is None:
+        raise HTTPException(status_code=401, detail="Invalid token")
+    return flow
+
 
 @router.get("/all")
 def get_all():
     return build_langchain_types_dict()
 
 
-@router.post("/predict/{flow_id}", status_code=200, response_model=PredictResponse)
+@router.post("/predict", response_model=PredictResponse)
 async def get_load(
     predict_request: PredictRequest,
-    flow_id: str,
-    session: Session = Depends(get_session),
+    flow: Flow = Depends(get_flow_from_token),
 ):
+    """
+    Endpoint to process a message using the flow passed in the bearer token.
+    """
+
     try:
-        flow_obj = session.get(Flow, flow_id)
-        if flow_obj is None:
-            raise ValueError(f"Flow {flow_id} not found")
-        graph_data = flow_obj.data
+        graph_data = flow.data
+        if predict_request.tweaks:
+            graph_data = process_tweaks(graph_data, predict_request.tweaks)
+
         response = process_graph_cached(graph_data, predict_request.message)
         return PredictResponse(
             result=response.get("result", ""),