diff --git a/docs/my-website/docs/caching/caching.md b/docs/my-website/docs/caching/caching.md
index 2147def37aa..1fa9611dd49 100644
--- a/docs/my-website/docs/caching/caching.md
+++ b/docs/my-website/docs/caching/caching.md
@@ -1,6 +1,6 @@
 # LiteLLM - Caching
 
-## LiteLLM Caches `completion()` and `embedding()` calls when switched on
+## Caching `completion()` and `embedding()` calls when switched on
 
 liteLLM implements exact match caching and supports the following Caching:
 * In-Memory Caching [Default]
@@ -8,8 +8,8 @@ liteLLM implements exact match caching and supports the following Caching:
 * Redic Caching Hosted
 * GPTCache 
 
-## Usage
-1. Caching - cache
+## Quick Start Usage - Completion
+Caching - cache
 Keys in the cache are `model`, the following example will lead to a cache hit
 ```python
 import litellm
@@ -23,3 +23,64 @@ response2 = completion(model="gpt-3.5-turbo", messages=[{"role": "user", "conten
 
 # response1 == response2, response 1 is cached
 ```
+
+## Using Redis Cache with LiteLLM
+### Pre-requisites
+Install redis
+```
+pip install redis
+```
+For the hosted version you can setup your own Redis DB here: https://app.redislabs.com/
+### Usage
+```python
+import litellm
+from litellm import completion
+from litellm.caching import Cache
+litellm.cache = Cache(type="redis", host=<host>, port=<port>, password=<password>)
+
+# Make completion calls
+response1 = completion(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Tell me a joke."}])
+response2 = completion(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Tell me a joke."}])
+
+# response1 == response2, response 1 is cached
+```
+
+## Caching with Streaming 
+LiteLLM can cache your streamed responses for you
+
+### Usage
+```python
+import litellm
+from litellm import completion
+from litellm.caching import Cache
+litellm.cache = Cache()
+
+# Make completion calls
+response1 = completion(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Tell me a joke."}], stream=True)
+for chunk in response1:
+    print(chunk)
+response2 = completion(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Tell me a joke."}], stream=True)
+for chunk in response2:
+    print(chunk)
+```
+
+## Usage - Embedding()
+1. Caching - cache
+Keys in the cache are `model`, the following example will lead to a cache hit
+```python
+import time
+import litellm
+from litellm import completion
+from litellm.caching import Cache
+litellm.cache = Cache()
+
+start_time = time.time()
+embedding1 = embedding(model="text-embedding-ada-002", input=["hello from litellm"*5])
+end_time = time.time()
+print(f"Embedding 1 response time: {end_time - start_time} seconds")
+
+start_time = time.time()
+embedding2 = embedding(model="text-embedding-ada-002", input=["hello from litellm"*5])
+end_time = time.time()
+print(f"Embedding 2 response time: {end_time - start_time} seconds")
+```
\ No newline at end of file