docs(routing.md): add calling via proxy tutorial to router docs

docs/my-website/docs/routing.md

@@ -274,7 +274,7 @@ print(response)
 </TabItem>
 <TabItem value="usage-based-v2" label="Rate-Limit Aware v2 (ASYNC)">
 
-**NEW**
+**🎉 NEW**
 
 This is an async implementation of usage-based-routing.
 
@@ -286,6 +286,8 @@ If you pass in the deployment's tpm/rpm limits, this will also check against tha
 
 For Azure, your RPM = TPM/6. 
 
+<Tabs>
+<TabItem value="sdk" label="sdk">
 
 ```python
 from litellm import Router 
@@ -333,6 +335,59 @@ response = await router.acompletion(model="gpt-3.5-turbo",
 
 print(response)
 ```
+</TabItem>
+<TabItem value="proxy" label="proxy">
+
+**1. Set strategy in config**
+
+```yaml
+model_list:
+	- model_name: gpt-3.5-turbo # model alias 
+	  litellm_params: # params for litellm completion/embedding call 
+		model: azure/chatgpt-v-2 # actual model name
+		api_key: os.environ/AZURE_API_KEY
+		api_version: os.environ/AZURE_API_VERSION
+		api_base: os.environ/AZURE_API_BASE
+      tpm: 100000
+	  rpm: 10000
+	- model_name: gpt-3.5-turbo 
+	  litellm_params: # params for litellm completion/embedding call 
+		model: gpt-3.5-turbo 
+		api_key: os.getenv(OPENAI_API_KEY)
+      tpm: 100000
+	  rpm: 1000
+
+router_settings:
+  routing_strategy: usage-based-routing-v2 # 👈 KEY CHANGE
+  redis_host: <your-redis-host>
+  redis_password: <your-redis-password>
+  redis_port: <your-redis-port>
+  enable_pre_call_check: true
+
+general_settings:
+  master_key: sk-1234
+```
+
+**2. Start proxy**
+
+```bash
+litellm --config /path/to/config.yaml
+```
+
+**3. Test it!**
+
+```bash
+curl --location 'http://localhost:4000/v1/chat/completions' \
+--header 'Content-Type: application/json' \
+--header 'Authorization: Bearer sk-1234' \
+--data '{
+    "model": "gpt-3.5-turbo", 
+    "messages": [{"role": "user", "content": "Hey, how's it going?"}]
+}'
+```
+
+</TabItem>
+</Tabs>
 
 
 </TabItem>