diff --git a/litellm/caching.py b/litellm/caching.py
index 923a3031b..7c04bab72 100644
--- a/litellm/caching.py
+++ b/litellm/caching.py
@@ -1,4 +1,5 @@
 import litellm
+import time
 def get_prompt(*args, **kwargs):
     # make this safe checks, it should not throw any exceptions
     if len(args) > 1:
@@ -30,9 +31,9 @@ class InMemoryCache():
         self.cache_dict = {}
 
     def set_cache(self, key, value):
-        print("in set cache for inmem")
+        #print("in set cache for inmem")
         self.cache_dict[key] = value
-        print(self.cache_dict)
+        #print(self.cache_dict)
 
     def get_cache(self, key):
         #print("in get cache for inmem")
@@ -65,11 +66,23 @@ class Cache():
             return None
         return cache_key
 
+    def generate_streaming_content(self, content):
+        chunk_size = 5  # Adjust the chunk size as needed
+        for i in range(0, len(content), chunk_size):
+            yield {'choices': [{'delta': {'role': 'assistant', 'content': content[i:i+chunk_size]}}]}
+            time.sleep(0.02)
+    
     def get_cache(self, *args, **kwargs):
         try:  # never block execution
             cache_key = self.get_cache_key(*args, **kwargs)
             if cache_key is not None:
-                return self.cache.get_cache(cache_key)
+                cached_result = self.cache.get_cache(cache_key)
+                if cached_result != None and 'stream' in kwargs and kwargs['stream'] == True:
+                    # if streaming is true and we got a cache hit, return a generator
+                    #print("cache hit and stream=True")
+                    #print(cached_result)
+                    return self.generate_streaming_content(cached_result["choices"][0]['message']['content'])
+                return cached_result
         except:
             return None
 
diff --git a/litellm/tests/test_caching.py b/litellm/tests/test_caching.py
index 949ae0c26..580c6d86b 100644
--- a/litellm/tests/test_caching.py
+++ b/litellm/tests/test_caching.py
@@ -152,35 +152,32 @@ def test_embedding_caching():
 # test_embedding_caching()
 
 
-# # test caching with streaming
-# messages = [{"role": "user", "content": "hello gm who are u"}]
-# def test_caching_v2_stream():
-#     try:
-#         litellm.cache = Cache()
-#         # litellm.token="ishaan@berri.ai"
-#         response1 = completion(model="gpt-3.5-turbo", messages=messages, stream=True)
-#         for chunk in response1:
-#             # 
-#             pass
-#             # print("chunk")
-#             pass
-#             # response1_id = chunk['id']
+# test caching with streaming
+messages = [{"role": "user", "content": "tell me a story in 2 sentences"}]
+def test_caching_v2_stream():
+    try:
+        litellm.cache = Cache()
+        # litellm.token="ishaan@berri.ai"
+        response1 = completion(model="gpt-3.5-turbo", messages=messages, stream=True)
+        result_string = ""
+        for chunk in response1:
+            print(chunk)
+            result_string+=chunk['choices'][0]['delta']['content']
+            # response1_id = chunk['id']
 
-#         # response2 = completion(model="gpt-3.5-turbo", messages=messages, stream=True)
-#         # for chunk in response2:
-#         #     #print(chunk)
-#         #     response2_id = chunk['id']
-       
-#         # print(f"response1: {response1}")
-#         # print(f"response2: {response2}")
-#         # litellm.cache = None # disable cache
-#         # if response2_id != response1_id:
-#         #     print(f"response1: {response1_id}")
-#         #     print(f"response2: {response2_id}")
-#         #     pytest.fail(f"Error occurred: {e}")
-#     except Exception as e:
-#         print(f"error occurred: {traceback.format_exc()}")
-#         pytest.fail(f"Error occurred: {e}")
+        result2_string=""
+        response2 = completion(model="gpt-3.5-turbo", messages=messages, stream=True)
+        for chunk in response2:
+            print(chunk)
+            result2_string+=chunk['choices'][0]['delta']['content']
+        if result_string != result2_string:
+            print(result_string)
+            print(result2_string)
+            pytest.fail(f"Error occurred: Caching with streaming failed, strings diff")
+
+    except Exception as e:
+        print(f"error occurred: {traceback.format_exc()}")
+        pytest.fail(f"Error occurred: {e}")
 
 # test_caching_v2_stream()
 
diff --git a/litellm/utils.py b/litellm/utils.py
index 26b37b694..c41610f5c 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -70,7 +70,7 @@ last_fetched_at_keys = None
 
 
 class Message(OpenAIObject):
-    def __init__(self, content=" ", role="assistant", **params):
+    def __init__(self, content="default", role="assistant", **params):
         super(Message, self).__init__(**params)
         self.content = content
         self.role = role
@@ -287,24 +287,18 @@ class Logging:
                         )
                     if callback == "cache":
                         try:
-                            #print("in cache callback2", self.stream)
-                            #print(original_response)
-                            #print(self.model_call_details)
-                            
-                            if litellm.cache != None:
+                            if litellm.cache != None and self.model_call_details.get('optional_params', {}).get('stream', False) == True:
                                 if self.litellm_params["stream_response"] == None:
                                     self.litellm_params["stream_response"] = ModelResponse()
                                 else:
                                     #self.litellm_call_id["stream_response"]["id"] = self.litellm_params["litellm_call_id"]
-                                    self.litellm_params["stream_response"]["choices"][0]["message"]["content"] += original_response
-                                #print("cache is not none")
-                                # convert original_response to format of Model Object
-                                # Set the model
+                                    if self.litellm_params["stream_response"]["choices"][0]["message"]["content"] == "default":
+                                        self.litellm_params["stream_response"]["choices"][0]["message"]["content"] = original_response # handle first try
+                                    else:
+                                        self.litellm_params["stream_response"]["choices"][0]["message"]["content"] += original_response
                                 litellm.cache.add_cache(self.litellm_params["stream_response"], **self.model_call_details)
-                            #print(self.litellm_params["stream_response"])
                         except Exception as e:
-                            print("got exception")
-                            print(e)
+                           pass
                 except:
                     print_verbose(
                         f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while post-call logging with integrations {traceback.format_exc()}"