docs: Adjust the path to examples

README.md

@@ -68,12 +68,13 @@ pip install "ai-dynamo[all]"
 
 ### Building the Dynamo Base Image
 
-Although not needed for local development, deploying your Dynamo pipelines to Kubernetes will require you to build and push a Dynamo base image to your container registry. You can use any container registry of your choice, such as:
+Although not needed for local development, deploying your Dynamo pipelines to Kubernetes will require you to use a Dynamo base image to your container registry. You can use any container registry of your choice, such as:
 - Docker Hub (docker.io)
 - NVIDIA NGC Container Registry (nvcr.io)
 - Any private registry
 
-Here's how to build it:
+We publish our images in nvcr.io and you can use them.
+Alternatively you could build and push an image from source:
 
 ```bash
 ./container/build.sh
@@ -83,8 +84,10 @@ docker push <your-registry>/dynamo-base:latest-vllm
 ```
 
 Notes about builds for specific frameworks:
-- For specific details on the `--framework vllm` build, see [here](examples/vllm/README.md).
-- For specific details on the `--framework tensorrtllm` build, see [here](examples/tensorrt_llm/README.md).
+- For specific details on the `--framework vllm` build [read about the VLLM backend](components/backends/vllm/README.md)
+.
+- For specific details on the `--framework tensorrtllm` build, see [Read about the TensorRT-LLM backend](components/backends/trtllm/README.md)
+.
 
 Note about AWS environments:
 - If deploying Dynamo in AWS, make sure to build the container with EFA support using the `--make-efa` flag.
@@ -197,8 +200,6 @@ pip install .
 cd ../../../
 pip install ".[all]"
 
-# To test
-docker compose -f deploy/metrics/docker-compose.yml up -d
-cd examples/llm
-dynamo serve graphs.agg:Frontend -f configs/agg.yaml
+Follow the [Quickstart Guide](docs/guides/dynamo_deploy/quickstart.md)
+
 ```

components/backends/vllm/deploy/disagg.yaml

@@ -80,7 +80,7 @@ spec:
           image: nvcr.io/nvidian/nim-llm-dev/vllm_v1-runtime:dep-216.4
           workingDir: /workspace/components/backends/vllm
           args:
-            - "python3 components/main.py --model Qwen/Qwen3-0.6B --enforce-eager 2>&1 | tee /tmp/vllm.log"
+            - "python3 -m dynamo.vllm --model Qwen/Qwen3-0.6B --enforce-eager 2>&1 | tee /tmp/vllm.log"
     VllmPrefillWorker:
       dynamoNamespace: vllm-v1-disagg
       envFromSecret: hf-token-secret
@@ -119,4 +119,4 @@ spec:
           image: nvcr.io/nvidian/nim-llm-dev/vllm_v1-runtime:dep-216.4
           workingDir: /workspace/components/backends/vllm
           args:
-            - "python3 components/main.py --model Qwen/Qwen3-0.6B --enforce-eager --is-prefill-worker 2>&1 | tee /tmp/vllm.log"
+            - "python3 -m dynamo.vllm --model Qwen/Qwen3-0.6B --enforce-eager --is-prefill-worker 2>&1 | tee /tmp/vllm.log"

components/backends/vllm/deploy/disagg_planner.yaml

@@ -119,4 +119,4 @@ spec:
           image: nvcr.io/nvidian/nim-llm-dev/vllm_v1-runtime:dep-216.4
           workingDir: /workspace/components/backends/vllm
           args:
-            - "python3 components/main.py --model Qwen/Qwen3-0.6B --enforce-eager --is-prefill-worker 2>&1 | tee /tmp/vllm.log"
+            - "python3 -m dynamo.vllm --model Qwen/Qwen3-0.6B --enforce-eager --is-prefill-worker 2>&1 | tee /tmp/vllm.log"

deploy/helm/README.md

@@ -29,8 +29,10 @@ This approach allows you to install Dynamo directly using a DynamoGraphDeploymen
 
 ### Basic Installation
 
+Here is how you would install a VLLM inference backend example.
+
 ```bash
-helm upgrade --install dynamo-graph ./deploy/helm/chart -n dynamo-cloud -f ./examples/vllm/deploy/agg.yaml
+helm upgrade --install dynamo-graph ./deploy/helm/chart -n dynamo-cloud -f ./components/backends/vllm/deploy/agg.yaml
 ```
 
 ### Customizable Properties
@@ -39,7 +41,7 @@ You can override the default configuration by setting the following properties:
 
 ```bash
 helm upgrade --install dynamo-graph ./deploy/helm/chart -n dynamo-cloud \
-  -f ./examples/vllm/deploy/agg.yaml \
+  -f ./components/backends/vllm/deploy/agg.yaml \
   --set "imagePullSecrets[0].name=docker-secret-1" \
   --set etcdAddr="my-etcd-service:2379" \
   --set natsAddr="nats://my-nats-service:4222"

deploy/inference-gateway/example/README.md

@@ -16,11 +16,7 @@ This guide provides instructions for setting up the Inference Gateway with Dynam
 [See Quickstart Guide](../../../docs/guides/dynamo_deploy/quickstart.md) to install Dynamo Cloud.
 
 
-2. **Launch Dynamo Deployments**
-
-[See VLLM Example](../../../examples/vllm/README.md)
-
-3. **Deploy Inference Gateway**
+2. **Deploy Inference Gateway**
 
 First, deploy an inference gateway service. In this example, we'll install `kgateway` based gateway implementation.
 
@@ -54,7 +50,7 @@ kubectl get gateway inference-gateway
 # inference-gateway   kgateway             True         1m
 ```
 
-4. **Apply Dynamo-specific manifests**
+3. **Apply Dynamo-specific manifests**
 
 The Inference Gateway is configured through the `inference-gateway-resources.yaml` file.
 

docs/examples/README.md

@@ -2,7 +2,7 @@
 
 ## Serving examples locally
 
-TODO: Follow individual examples to serve models locally.
+Follow individual examples under components/backends/ to serve models locally.
 
 
 ## Deploying Examples to Kubernetes
@@ -38,7 +38,7 @@ export NAMESPACE=<your-namespace> # the namespace you used to deploy Dynamo clou
 Deploying an example consists of the simple `kubectl apply -f ... -n ${NAMESPACE}` command. For example:
 
 ```bash
-kubectl apply -f  examples/vllm/deploy/agg.yaml -n ${NAMESPACE}
+kubectl apply -f  components/backends/vllm/deploy/agg.yaml -n ${NAMESPACE}
 ```
 
 You can use `kubectl get dynamoGraphDeployment -n ${NAMESPACE}` to view your deployment.

docs/get_started.md

@@ -167,7 +167,7 @@ docker compose -f deploy/docker-compose.yml up -d
 
 ### Start Dynamo LLM Serving Components
 
-[Explore the VLLM Example](../examples/vllm/README.md)
+[Explore the VLLM Example](../components/backends/vllm/README.md)
 
 
 ## Local Development

docs/guides/dynamo_deploy/quickstart.md

@@ -187,19 +187,6 @@ We provide a script to uninstall CRDs should you need a clean start.
 
 ## Explore Examples
 
-Pick your deployment destination.
-
-If local
-
-```bash
-export DYNAMO_CLOUD=http://localhost:8080
-```
-
-If kubernetes
-```bash
-export DYNAMO_CLOUD=https://dynamo-cloud.nvidia.com
-```
-
 If deploying to Kubernetes, create a Kubernetes secret containing your sensitive values if needed:
 
 ```bash