chore: update LLM Router configuration files and README for improved deployment instructions

- Added SPDX license headers to llm-router-values-override.yaml.
- Updated imageRegistry placeholder in llm-router-values-override.yaml for clarity.
- Revised README.md to reflect changes in directory structure and emphasize the need to update imageRegistry and imagePullSecrets.
- Adjusted paths in README.md for configuration file references to ensure accuracy.
- Modified router-config-dynamo.yaml to enhance model routing strategies and updated model names for better clarity.

Author: arunraman

examples/deployments/LLM Router/README.md

@@ -562,8 +562,8 @@ docker pull $DYNAMO_IMAGE
 ### Validate Configuration Files
 
 ```bash
-# Navigate to the customization directory
-cd customizations/LLM\ Router
+# Navigate to the deployment directory
+cd examples/deployments/LLM\ Router
 
 # Check that required files exist
 ls -la frontend.yaml agg.yaml disagg.yaml router-config-dynamo.yaml llm-router-values-override.yaml
@@ -704,7 +704,7 @@ kubectl create secret generic hf-token-secret \
   -n ${NAMESPACE}
 
 # 2. Navigate to your LLM Router directory (where agg.yaml/disagg.yaml are located)
-cd "customizations/LLM Router/"
+cd "examples/deployments/LLM Router/"
 ```
 
 #### Shared Frontend Deployment
@@ -884,9 +884,22 @@ kubectl get secrets -n llm-router
 git clone https://github.com/NVIDIA-AI-Blueprints/llm-router.git
 cd llm-router
 
-# 2. Use official NVIDIA LLM Router images (no building required)
-# Our values file is configured to use the official images from nvcr.io/nvidian/sae/
-# If you need custom images, build and push them to your registry:
+# 2. Configure Docker Registry (REQUIRED)
+# IMPORTANT: Update the imageRegistry in llm-router-values-override.yaml before deployment
+# The file contains a placeholder "YOUR_REGISTRY_HERE/" that MUST be replaced.
+
+# Edit the values file:
+nano ../examples/deployments/LLM\ Router/llm-router-values-override.yaml
+
+# Update line ~34: Replace "YOUR_REGISTRY_HERE/" with your actual registry:
+# Examples:
+# - "nvcr.io/nvidia/" (if you have access to NVIDIA's public registry)
+# - "your-company-registry.com/llm-router/" (for private registries)  
+# - "docker.io/your-username/" (for Docker Hub)
+
+# Also update imagePullSecrets name to match your registry credentials
+
+# If you need to build custom images, use:
 # docker build -t <your-registry>/router-server:latest -f src/router-server/router-server.dockerfile .
 # docker build -t <your-registry>/router-controller:latest -f src/router-controller/router-controller.dockerfile .
 # docker push <your-registry>/router-server:latest
@@ -896,7 +909,7 @@ cd llm-router
 # 3. Create router configuration ConfigMap using official External ConfigMap strategy
 # The official Helm chart now supports external ConfigMaps natively
 kubectl create configmap router-config-dynamo \
-  --from-file=config.yaml=router-config-dynamo.yaml \
+  --from-file=config.yaml=../examples/deployments/LLM\ Router/router-config-dynamo.yaml \
   --namespace=llm-router
 
 # 4. Prepare router models (download from NGC)
@@ -954,7 +967,7 @@ kubectl create secret generic llm-api-keys \
 cd deploy/helm/llm-router
 helm upgrade --install llm-router . \
   --namespace llm-router \
-  --values ../../../llm-router-values-override.yaml \
+  --values ../../../../examples/deployments/LLM\ Router/llm-router-values-override.yaml \
   --wait --timeout=10m
 
 # 6. Verify LLM Router deployment

examples/deployments/LLM Router/llm-router-values-override.yaml

@@ -1,13 +1,19 @@
+## 
+# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+##
+
 # LLM Router Helm Values for NVIDIA Dynamo Cloud Platform Integration
 # Based on official sample: https://github.com/NVIDIA-AI-Blueprints/llm-router/blob/main/deploy/helm/llm-router/values.override.yaml.sample
 # Uses official External ConfigMap strategy for custom configuration
 
 # Global configuration (following official sample structure)
+# NOTE: Update imageRegistry and imagePullSecrets before deployment (see README Step 6)
 global:
   storageClass: "standard"
-  imageRegistry: "nvcr.io/nvidian/sae/"
+  imageRegistry: "YOUR_REGISTRY_HERE/"  # REPLACE with your Docker registry
   imagePullSecrets:
-    - name: nvcr-secret
+    - name: nvcr-secret  # UPDATE to match your registry credentials
 
 # Router Controller Configuration
 routerController:

examples/deployments/LLM Router/router-config-dynamo.yaml

@@ -41,99 +41,82 @@ policies:
   - name: "task_router"
     url: http://llm-router-router-server.llm-router.svc.cluster.local:8000/v2/models/task_router_ensemble/infer
     llms:
-      # === INTELLIGENT ROUTING STRATEGY ===
-      # Route to appropriate models based on task complexity
-      
-      # Simple tasks → Fast 8B model
-      - name: "Closed QA"
+      - name: Brainstorming
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
-        model: meta-llama/Llama-3.1-8B-Instruct
-      - name: Classification
+        model: meta-llama/Llama-3.1-70B-Instruct
+      - name: Chatbot
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
-        model: meta-llama/Llama-3.1-8B-Instruct
-      - name: Extraction
+        model: mistralai/Mixtral-8x22B-Instruct-v0.1
+      - name: Classification
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
         model: meta-llama/Llama-3.1-8B-Instruct
-      - name: Rewrite
+      - name: Closed QA
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
-        model: meta-llama/Llama-3.1-8B-Instruct
-      - name: Summarization
+        model: meta-llama/Llama-3.1-70B-Instruct
+      - name: Code Generation
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
-        model: meta-llama/Llama-3.1-8B-Instruct
-      - name: Unknown
+        model: meta-llama/Llama-3.1-70B-Instruct
+      - name: Extraction
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
         model: meta-llama/Llama-3.1-8B-Instruct
-        
-      # Complex tasks → Powerful 70B model
-      - name: Brainstorming
+      - name: Open QA
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
         model: meta-llama/Llama-3.1-70B-Instruct
-      - name: "Code Generation"
+      - name: Other
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
-        model: meta-llama/Llama-3.1-70B-Instruct
-      - name: "Open QA"
+        model: mistralai/Mixtral-8x22B-Instruct-v0.1
+      - name: Rewrite
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
-        model: meta-llama/Llama-3.1-70B-Instruct
-      - name: Other
+        model: meta-llama/Llama-3.1-8B-Instruct
+      - name: Summarization
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
-        model: mistralai/Mixtral-8x22B-Instruct-v0.1
-        
-      # Creative/Conversational tasks → Mixtral model
-      - name: Chatbot
+        model: meta-llama/Llama-3.1-70B-Instruct
+      - name: Text Generation
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
         model: mistralai/Mixtral-8x22B-Instruct-v0.1
-      - name: "Text Generation"
+      - name: Unknown
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
-        model: mistralai/Mixtral-8x22B-Instruct-v0.1
-
+        model: meta-llama/Llama-3.1-8B-Instruct
   - name: "complexity_router"
     url: http://llm-router-router-server.llm-router.svc.cluster.local:8000/v2/models/complexity_router_ensemble/infer
     llms:
-      # === INTELLIGENT COMPLEXITY ROUTING ===
-      # Route to appropriate models based on complexity level
-      
-      # Simple complexity → Fast 8B model
-      - name: "Contextual-Knowledge"
+      - name: Creativity
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
-        model: meta-llama/Llama-3.1-8B-Instruct
-      - name: "No-Label-Reason"
+        model: meta-llama/Llama-3.1-70B-Instruct
+      - name: Reasoning
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
-        model: meta-llama/Llama-3.1-8B-Instruct
-      - name: Constraint
+        model: meta-llama/Llama-3.1-70B-Instruct
+      - name: Contextual-Knowledge
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
         model: meta-llama/Llama-3.1-8B-Instruct
-        
-      # High complexity → Powerful 70B model
-      - name: Creativity
+      - name: Few-Shot
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
         model: meta-llama/Llama-3.1-70B-Instruct
-      - name: Reasoning
+      - name: Domain-Knowledge
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
-        model: meta-llama/Llama-3.1-70B-Instruct
-      - name: "Few-Shot"
+        model: mistralai/Mixtral-8x22B-Instruct-v0.1
+      - name: No-Label-Reason
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
-        model: meta-llama/Llama-3.1-70B-Instruct
-        
-      # Creative/Domain complexity → Mixtral model
-      - name: "Domain-Knowledge"
+        model: meta-llama/Llama-3.1-8B-Instruct
+      - name: Constraint
         api_base: ${DYNAMO_API_BASE}
         api_key: ${DYNAMO_API_KEY}
-        model: mistralai/Mixtral-8x22B-Instruct-v0.1 
+        model: meta-llama/Llama-3.1-8B-Instruct