diff --git a/src/backend/langflow/cache/__init__.py b/src/backend/langflow/cache/__init__.py
index f7aac380b..583d5ac6d 100644
--- a/src/backend/langflow/cache/__init__.py
+++ b/src/backend/langflow/cache/__init__.py
@@ -1 +1 @@
-from langflow.cache.base import add_pandas, add_image, get  # noqa
+from langflow.cache.manager import cache_manager  # noqa
diff --git a/src/backend/langflow/cache/base.py b/src/backend/langflow/cache/base.py
index 9dd5c1780..ba250da6b 100644
--- a/src/backend/langflow/cache/base.py
+++ b/src/backend/langflow/cache/base.py
@@ -152,33 +152,3 @@ def load_cache(hash_val):
         with cache_path.open("rb") as cache_file:
             return dill.load(cache_file)
     return None
-
-
-def add_pandas(name: str, obj: Any):
-    if isinstance(obj, (pd.DataFrame, pd.Series)):
-        CACHE[name] = {"obj": obj, "type": "pandas"}
-    else:
-        raise ValueError("Object is not a pandas DataFrame or Series")
-
-
-def add_image(name: str, obj: Any):
-    if isinstance(obj, Image.Image):
-        CACHE[name] = {"obj": obj, "type": "image"}
-    else:
-        raise ValueError("Object is not a PIL Image")
-
-
-def get(name: str):
-    return CACHE.get(name, {}).get("obj", None)
-
-
-# get last added item
-def get_last():
-    obj_dict = list(CACHE.values())[-1]
-    if obj_dict["type"] == "pandas":
-        # return a csv string
-        return obj_dict["obj"].to_csv()
-    elif obj_dict["type"] == "image":
-        # return a base64 encoded string
-        return base64.b64encode(obj_dict["obj"].tobytes()).decode("utf-8")
-    return obj_dict["obj"]
diff --git a/src/backend/langflow/cache/manager.py b/src/backend/langflow/cache/manager.py
new file mode 100644
index 000000000..ba34a3a8d
--- /dev/null
+++ b/src/backend/langflow/cache/manager.py
@@ -0,0 +1,126 @@
+from contextlib import contextmanager
+from typing import Any, Awaitable, Callable, List
+from PIL import Image
+import pandas as pd
+
+
+class Subject:
+    """Base class for implementing the observer pattern."""
+
+    def __init__(self):
+        self.observers: List[Callable[[], None]] = []
+
+    def attach(self, observer: Callable[[], None]):
+        """Attach an observer to the subject."""
+        self.observers.append(observer)
+
+    def detach(self, observer: Callable[[], None]):
+        """Detach an observer from the subject."""
+        self.observers.remove(observer)
+
+    def notify(self):
+        """Notify all observers about an event."""
+        for observer in self.observers:
+            if observer is None:
+                continue
+            observer()
+
+
+class AsyncSubject:
+    """Base class for implementing the async observer pattern."""
+
+    def __init__(self):
+        self.observers: List[Callable[[], Awaitable]] = []
+
+    def attach(self, observer: Callable[[], Awaitable]):
+        """Attach an observer to the subject."""
+        self.observers.append(observer)
+
+    def detach(self, observer: Callable[[], Awaitable]):
+        """Detach an observer from the subject."""
+        self.observers.remove(observer)
+
+    async def notify(self):
+        """Notify all observers about an event."""
+        for observer in self.observers:
+            if observer is None:
+                continue
+            await observer()
+
+
+class CacheManager(Subject):
+    """Manages cache for different clients and notifies observers on changes."""
+
+    def __init__(self):
+        super().__init__()
+        self.CACHE = {}
+        self.current_client_id = None
+
+    @contextmanager
+    def set_client_id(self, client_id: str):
+        """
+        Context manager to set the current client_id and associated cache.
+
+        Args:
+            client_id (str): The client identifier.
+        """
+        previous_client_id = self.current_client_id
+        self.current_client_id = client_id
+        self.current_cache = self.CACHE.setdefault(client_id, {})
+        try:
+            yield
+        finally:
+            self.current_client_id = previous_client_id
+            self.current_cache = self.CACHE.get(self.current_client_id, {})
+
+    def add_pandas(self, name: str, obj: Any):
+        """
+        Add a pandas DataFrame or Series to the current client's cache.
+
+        Args:
+            name (str): The cache key.
+            obj (Any): The pandas DataFrame or Series object.
+        """
+        if isinstance(obj, (pd.DataFrame, pd.Series)):
+            self.current_cache[name] = {"obj": obj, "type": "pandas"}
+            self.notify()
+        else:
+            raise ValueError("Object is not a pandas DataFrame or Series")
+
+    def add_image(self, name: str, obj: Any):
+        """
+        Add a PIL Image to the current client's cache.
+
+        Args:
+            name (str): The cache key.
+            obj (Any): The PIL Image object.
+        """
+        if isinstance(obj, Image.Image):
+            self.current_cache[name] = {"obj": obj, "type": "image"}
+            self.notify()
+        else:
+            raise ValueError("Object is not a PIL Image")
+
+    def get(self, name: str):
+        """
+        Get an object from the current client's cache.
+
+        Args:
+            name (str): The cache key.
+
+        Returns:
+            The cached object associated with the given cache key.
+        """
+        return self.current_cache[name]
+
+    def get_last(self):
+        """
+        Get the last added item in the current client's cache.
+
+        Returns:
+            The last added item in the cache.
+        """
+        return list(self.current_cache.values())[-1]
+
+
+cache_manager = CacheManager()