NVIDIA · pdmack · Jul 21, 2026 · Jul 21, 2026 · Jul 21, 2026
@@ -85,13 +85,13 @@ NVCF supports four workload types on the compute plane:
 
 Each component ships an `AGENTS.md` with detailed internals, data flows, and API contracts:
 
-- [`src/compute-plane-services/nvca/AGENTS.md`](../../src/compute-plane-services/nvca/AGENTS.md)
-- [`src/compute-plane-services/ess-agent/AGENTS.md`](../../src/compute-plane-services/ess-agent/AGENTS.md)
-- [`src/compute-plane-services/byoo-otel-collector/AGENTS.md`](../../src/compute-plane-services/byoo-otel-collector/AGENTS.md)
-- [`src/invocation-plane-services/http-invocation/AGENTS.md`](../../src/invocation-plane-services/http-invocation/AGENTS.md)
-- [`src/invocation-plane-services/grpc-proxy/AGENTS.md`](../../src/invocation-plane-services/grpc-proxy/AGENTS.md)
-- [`src/invocation-plane-services/llm-api-gateway/AGENTS.md`](../../src/invocation-plane-services/llm-api-gateway/AGENTS.md)
-- [`src/invocation-plane-services/ratelimiter/AGENTS.md`](../../src/invocation-plane-services/ratelimiter/AGENTS.md)
-- [`src/control-plane-services/nats-auth-callout/AGENTS.md`](../../src/control-plane-services/nats-auth-callout/AGENTS.md)
-- [`src/control-plane-services/function-autoscaler/AGENTS.md`](../../src/control-plane-services/function-autoscaler/AGENTS.md)
-- [`examples/AGENTS.md`](../../examples/AGENTS.md)
+- [src/compute-plane-services/nvca/AGENTS.md](https://github.com/NVIDIA/nvcf/blob/main/src/compute-plane-services/nvca/AGENTS.md)
+- [src/compute-plane-services/ess-agent/AGENTS.md](https://github.com/NVIDIA/nvcf/blob/main/src/compute-plane-services/ess-agent/AGENTS.md)
+- [src/compute-plane-services/byoo-otel-collector/AGENTS.md](https://github.com/NVIDIA/nvcf/blob/main/src/compute-plane-services/byoo-otel-collector/AGENTS.md)
+- [src/invocation-plane-services/http-invocation/AGENTS.md](https://github.com/NVIDIA/nvcf/blob/main/src/invocation-plane-services/http-invocation/AGENTS.md)
+- [src/invocation-plane-services/grpc-proxy/AGENTS.md](https://github.com/NVIDIA/nvcf/blob/main/src/invocation-plane-services/grpc-proxy/AGENTS.md)
+- [src/invocation-plane-services/llm-api-gateway/AGENTS.md](https://github.com/NVIDIA/nvcf/blob/main/src/invocation-plane-services/llm-api-gateway/AGENTS.md)
+- [src/invocation-plane-services/ratelimiter/AGENTS.md](https://github.com/NVIDIA/nvcf/blob/main/src/invocation-plane-services/ratelimiter/AGENTS.md)
+- [src/control-plane-services/nats-auth-callout/AGENTS.md](https://github.com/NVIDIA/nvcf/blob/main/src/control-plane-services/nats-auth-callout/AGENTS.md)
+- [src/control-plane-services/function-autoscaler/AGENTS.md](https://github.com/NVIDIA/nvcf/blob/main/src/control-plane-services/function-autoscaler/AGENTS.md)
+- [examples/AGENTS.md](https://github.com/NVIDIA/nvcf/blob/main/examples/AGENTS.md)
@@ -37,13 +37,13 @@ The `grpc_echo_sample` from the same repository shares the
 </Note>
 
 The source, build instructions, and registry push examples are in the
-[nv-cloud-function-helpers](https://github.com/NVIDIA/nv-cloud-function-helpers/tree/main/examples/function_samples/load_tester_supreme)
+[NVCF examples](https://github.com/NVIDIA/nvcf/tree/main/examples/function-samples/load-tester-supreme)
 repository. Build and push the image to whichever container registry your
 cluster has credentials for:
 
 ```bash
-git clone https://github.com/NVIDIA/nv-cloud-function-helpers.git
-cd nv-cloud-function-helpers/examples/function_samples/load_tester_supreme
+git clone https://github.com/NVIDIA/nvcf.git
+cd nvcf/examples/function-samples/load-tester-supreme
 
 # Build
 docker build --platform linux/amd64 -t load_tester_supreme .
@@ -115,8 +115,8 @@ The CLI saves the function and version IDs automatically. Run
 ## Clone the load test scripts
 
 ```bash
-git clone https://github.com/NVIDIA/nv-cloud-function-helpers.git
-cd nv-cloud-function-helpers/examples/load-tests
+git clone https://github.com/NVIDIA/nvcf.git
+cd nvcf/examples/load-tests
 ```
 
 ## Install k6

@@ -29,13 +29,13 @@ for high-throughput benchmarking and includes:
 - Built-in OpenTelemetry tracing
 
 The source, build instructions, and registry push examples are in the
-[nv-cloud-function-helpers](https://github.com/NVIDIA/nv-cloud-function-helpers/tree/main/examples/function_samples/load_tester_supreme)
+[NVCF examples](https://github.com/NVIDIA/nvcf/tree/main/examples/function-samples/load-tester-supreme)
 repository. Build and push the image to whichever container registry your
 cluster has credentials for:
 
 ```bash
-git clone https://github.com/NVIDIA/nv-cloud-function-helpers.git
-cd nv-cloud-function-helpers/examples/function_samples/load_tester_supreme
+git clone https://github.com/NVIDIA/nvcf.git
+cd nvcf/examples/function-samples/load-tester-supreme
 
 # Build
 docker build --platform linux/amd64 -t load_tester_supreme .
@@ -100,8 +100,8 @@ k3d, Docker Desktop) it is typically `localhost` or `127.0.0.1`.
 ## Clone the load test scripts
 
 ```bash
-git clone https://github.com/NVIDIA/nv-cloud-function-helpers.git
-cd nv-cloud-function-helpers/examples/load-tests
+git clone https://github.com/NVIDIA/nvcf.git
+cd nvcf/examples/load-tests
 ```
 
 ## Install k6

@@ -32,13 +32,13 @@ for high-throughput benchmarking and includes:
 - Built-in OpenTelemetry tracing
 
 The source, build instructions, and registry push examples are in the
-[nv-cloud-function-helpers](https://github.com/NVIDIA/nv-cloud-function-helpers/tree/main/examples/function_samples/load_tester_supreme)
+[NVCF examples](https://github.com/NVIDIA/nvcf/tree/main/examples/function-samples/load-tester-supreme)
 repository. Build and push the image to whichever container registry your
 cluster has credentials for:
 
 ```bash
-git clone https://github.com/NVIDIA/nv-cloud-function-helpers.git
-cd nv-cloud-function-helpers/examples/function_samples/load_tester_supreme
+git clone https://github.com/NVIDIA/nvcf.git
+cd nvcf/examples/function-samples/load-tester-supreme
 
 # Build (multi-arch)
 docker buildx build --platform linux/amd64,linux/arm64 -t load_tester_supreme .
@@ -162,7 +162,7 @@ you want a steady, predictable load.
 
 <Note>
 The latest version of this script is maintained in the
-[nv-cloud-function-helpers](https://github.com/NVIDIA/nv-cloud-function-helpers)
+[NVCF examples](https://github.com/NVIDIA/nvcf/tree/main/examples)
 repository.
 
 </Note>

@@ -21,7 +21,7 @@ The cluster agent and operator emit Prometheus-style metrics. The following metr
 | nvca_cluster_group | The NVCA cluster group |
 | nvca_version | The NVCA version |
 
-Cluster maintainers can scrape the available metrics. See a full example of how to do this with an OpenTelemetry Collector in the cluster [here](https://github.com/NVIDIA/nv-cloud-function-helpers/tree/main/examples/cluster_monitoring_sample).
+Cluster maintainers can scrape the available metrics. See a full example of how to do this with an OpenTelemetry Collector in the cluster [cluster monitoring example](https://github.com/NVIDIA/nvcf/tree/main/examples/cluster-monitoring-sample).
 
 Use the following examples of a PodMonitor for NVCA Operator and ServiceMonitor for NVCA for reference:
 

@@ -344,7 +344,7 @@ Or use the `--debug` flag or `NVCF_DEBUG=true` environment variable per-command.
 ```
 
 <Note>
-For immediate testing, you can use `load_tester_supreme` from `nvcf-onprem` (see [self-hosted-artifact-manifest](./manifest.md)), which supports the `{"message": "hello world"}` request body above. For more function samples, see the [nv-cloud-function-helpers](https://github.com/NVIDIA/nv-cloud-function-helpers) repository and [function-creation](./function-creation.md) for function creation documentation.
+For immediate testing, you can use `load_tester_supreme` from `nvcf-onprem` (see [self-hosted-artifact-manifest](./manifest.md)), which supports the `{"message": "hello world"}` request body above. For more function samples, see the [NVCF examples](https://github.com/NVIDIA/nvcf/tree/main/examples) repository and [function-creation](./function-creation.md) for function creation documentation.
 
 </Note>
 

@@ -21,7 +21,7 @@ The cluster agent and operator emit Prometheus-style metrics. The following metr
 | nvca_cluster_group | The NVCA cluster group           |
 | nvca_version       | The NVCA version                 |
 
-Cluster maintainers can scrape the available metrics. See a full example of how to do this with an OpenTelemetry Collector in the cluster [here](https://github.com/NVIDIA/nv-cloud-function-helpers/tree/main/examples/cluster_monitoring_sample).
+Cluster maintainers can scrape the available metrics. See a full example of how to do this with an OpenTelemetry Collector in the cluster [cluster monitoring example](https://github.com/NVIDIA/nvcf/tree/main/examples/cluster-monitoring-sample).
 
 Use the following examples of a PodMonitor for NVCA Operator and ServiceMonitor for NVCA for reference:
 

@@ -4,9 +4,9 @@ Container-based functions require building and pushing a Cloud Functions compati
 
 ## Resources
 
-- Example containers can be found [in the examples repository](https://github.com/NVIDIA/nv-cloud-function-helpers/tree/main/examples).
+- Example containers can be found [in the examples directory](https://github.com/NVIDIA/nvcf/tree/main/examples).
 
-- The repository also contains [helper functions](https://github.com/NVIDIA/nv-cloud-function-helpers/blob/main/helper_library/nv_cloud_function_helpers/nvcf_container/helpers.py) that are useful when authoring your container, including:
+- The repository also contains [helper functions](https://github.com/NVIDIA/nvcf/blob/main/src/libraries/python/nv-cloud-function-helpers/nv_cloud_function_helpers/nvcf_container/helpers.py) that are useful when authoring your container, including:
 
   - Helpers that parse Cloud Functions-specific parameters on invocation
   - Helpers that can be used to instrument your container with Cloud Functions compatible logs
@@ -43,7 +43,7 @@ Cloud Functions also expects the following directories in the container to remai
 
 ## Composing a FastAPI Container
 
-It's possible to use any container with Cloud Functions as long as it implements a server with the above endpoints. The below is an example of a FastAPI-based container compatible with Cloud Functions. Clone the [FastAPI echo example](https://github.com/NVIDIA/nv-cloud-function-helpers/tree/main/examples/function_samples/fastapi_echo_sample).
+It's possible to use any container with Cloud Functions as long as it implements a server with the above endpoints. The below is an example of a FastAPI-based container compatible with Cloud Functions. Clone the [FastAPI echo example](https://github.com/NVIDIA/nvcf/tree/main/examples/function-samples/fastapi-echo-sample).
 
 ### Create the "requirements.txt" File
 
@@ -289,7 +289,7 @@ Create the function via the NVCF API. In this example, we defined the inference
 
 ### Additional Examples
 
-See more examples of containers that are Cloud Functions compatible [in the function samples directory](https://github.com/NVIDIA/nv-cloud-function-helpers/tree/main/examples/function_samples/).
+See more examples of containers that are Cloud Functions compatible [in the function samples directory](https://github.com/NVIDIA/nvcf/tree/main/examples/function-samples/).
 
 ## Creating gRPC-based Functions
 
@@ -300,7 +300,7 @@ Cloud Functions supports function invocation via gRPC. During function creation,
 - The function container must implement a gRPC port, endpoint and health check. The health check is expected to be served by the gRPC inference port, there is no need to define a separate health endpoint path.
 
   - See [gRPC health checking](https://grpc.io/docs/guides/health-checking/).
-  - See an [example container](https://github.com/NVIDIA/nv-cloud-function-helpers/blob/main/examples/function_samples/grpc_echo_sample/grpc_echo_server.py) with a gRPC server that is Cloud Functions compatible.
+  - See an [example container](https://github.com/NVIDIA/nvcf/blob/main/examples/function-samples/grpc-echo-sample/grpc_echo_server.py) with a gRPC server that is Cloud Functions compatible.
 
 ### gRPC Function Creation via API
 

@@ -48,7 +48,7 @@ For LLM functions, see [LLM Gateway](./llm-gateway.md#function-configuration) fo
 
 The following is a reference of available variables via the headers of the invocation message (auto-populated by Cloud Functions), accessible within the container.
 
-For examples of how to extract and use some of these variables, see [NVCF Container Helper Functions](https://github.com/NVIDIA/nv-cloud-function-helpers/tree/main).
+For examples of how to extract and use some of these variables, see [NVCF Container Helper Functions](https://github.com/NVIDIA/nvcf/tree/main/src/libraries/python/nv-cloud-function-helpers).
 
 | Name                         | Description                                             |
 | ---------------------------- | ------------------------------------------------------- |

@@ -41,7 +41,7 @@ All Pod specs in your helm chart will be updated with pull secrets at runtime, s
 
 **Example Creation via API**
 
-Please see our [sample helm chart used](https://github.com/NVIDIA/nv-cloud-function-helpers/tree/main/examples/function_samples/helmchart_samples/inference_test_sample) in this example for reference.
+Please see our [sample helm chart used](https://github.com/NVIDIA/nvcf/tree/main/examples/function-samples/helmchart-samples/inference-test-sample) in this example for reference.
 
 Below is an example function creation API call creating a helm-based function:
 
@@ -72,7 +72,7 @@ For gRPC-based functions, set `"inferenceURL" : "/gRPC"`. This signals to Cloud
 To create a multi-node helm deployment, you need to use the following format for the `instanceType`:
 `<CSP>.GPU.<GPU_NAME>_<number of gpus per node>x[.x<number of nodes>]`. For example, `DGXC.GPU.L40S_1x` is a single L40S instance while `ON-PREM.GPU.B200_8x.x2` is two full nodes of 8-way B200.
 
-A sample helm chart for a multi-node deployment can be found [in the multi-node helm example](https://github.com/NVIDIA/nv-cloud-function-helpers/tree/main/examples/function_samples/helmchart_samples/multi_node_helm_function_test/).
+A sample helm chart for a multi-node deployment can be found [in the multi-node helm example](https://github.com/NVIDIA/nvcf/tree/main/examples/function-samples/helmchart-samples/multi-node-helm-function-test/).
 
 ## Limitations
 

@@ -191,7 +191,7 @@ Environment configuration files define how NVCF is deployed in your specific env
 Set `HELMFILE_ENV` to your environment name and copy the base configuration.
 The filename must match `HELMFILE_ENV` because Helmfile uses it to select the
 environment file. The template below shows the values to configure for Amazon
-EKS ([cp-env-eks-example.yaml](samples/configs/cp-env-eks-example.yaml)).
+EKS ([cp-env-eks-example.yaml](https://raw.githubusercontent.com/NVIDIA/nvcf/main/docs/user/samples/configs/cp-env-eks-example.yaml)).
 
 ```bash
 cd path/to/nvcf-self-managed-stack
@@ -586,7 +586,7 @@ These credentials will then be used for function deployments. Note that if the r
 Copy the secrets template using the same `HELMFILE_ENV` value from Step 2. The
 filename must match `HELMFILE_ENV` because Helmfile loads the corresponding
 secrets file. The example below shows the required structure
-([example-secrets.yaml](samples/configs/cp-example-secrets.yaml)). You must
+([example-secrets.yaml](https://raw.githubusercontent.com/NVIDIA/nvcf/main/docs/user/samples/configs/cp-example-secrets.yaml)). You must
 replace all instances of `REPLACE_WITH_BASE64_DOCKER_CREDENTIAL` with your
 actual base64-encoded registry credentials.
 
@@ -731,7 +731,7 @@ registry.
 If your `image` registry is private and your cluster nodes do not have built-in credential helpers, you must create Kubernetes `docker-registry` secrets in each NVCF namespace and configure the helmfile to reference them.
 
 1. Create the pull secret in each NVCF namespace
-   ([create-nvcr-pull-secrets.sh](samples/scripts/create-nvcr-pull-secrets.sh)):
+   ([create-nvcr-pull-secrets.sh](https://raw.githubusercontent.com/NVIDIA/nvcf/main/docs/user/samples/scripts/create-nvcr-pull-secrets.sh)):
 
 ```bash
 export NGC_API_KEY="<your-ngc-api-key>"

@@ -295,7 +295,7 @@ Dashboards are provided in native Grafana JSON format for [file-provisioning](ht
 Load dashboards into Grafana by placing them in `/etc/grafana/provisioning/dashboards/` on startup.
 
 Published dashboards will be available in the
-[nv-cloud-function-helpers](https://github.com/NVIDIA/nv-cloud-function-helpers) public GitHub repository.
+[NVCF examples](https://github.com/NVIDIA/nvcf/tree/main/examples) public GitHub repository.
 
 ## Troubleshooting
 

@@ -1090,7 +1090,7 @@ echo "=============================================="
 
 ```
 
-[force-cleanup-nvcf.sh](samples/scripts/force-cleanup-nvcf.sh)
+[force-cleanup-nvcf.sh](https://raw.githubusercontent.com/NVIDIA/nvcf/main/docs/user/samples/scripts/force-cleanup-nvcf.sh)
 
 **Usage:**
 

@@ -274,7 +274,7 @@ Or use the `--debug` flag or `NVCF_DEBUG=true` environment variable per-command.
 ```
 
 <Note>
-For immediate testing, you can use `load_tester_supreme` from `nvcf-onprem` (see [self-hosted-artifact-manifest](./manifest.md)), which supports the `{"message": "hello world"}` request body above. For more function samples, see the [nv-cloud-function-helpers](https://github.com/NVIDIA/nv-cloud-function-helpers) repository and [function-creation](./function-creation.md) for function creation documentation.
+For immediate testing, you can use `load_tester_supreme` from `nvcf-onprem` (see [self-hosted-artifact-manifest](./manifest.md)), which supports the `{"message": "hello world"}` request body above. For more function samples, see the [NVCF examples](https://github.com/NVIDIA/nvcf/tree/main/examples) repository and [function-creation](./function-creation.md) for function creation documentation.
 
 </Note>
 

@@ -21,7 +21,7 @@ The cluster agent and operator emit Prometheus-style metrics. The following metr
 | nvca_cluster_group | The NVCA cluster group           |
 | nvca_version       | The NVCA version                 |
 
-Cluster maintainers can scrape the available metrics. See a full example of how to do this with an OpenTelemetry Collector in the cluster [here](https://github.com/NVIDIA/nv-cloud-function-helpers/tree/main/examples/cluster_monitoring_sample).
+Cluster maintainers can scrape the available metrics. See a full example of how to do this with an OpenTelemetry Collector in the cluster [cluster monitoring example](https://github.com/NVIDIA/nvcf/tree/main/examples/cluster-monitoring-sample).
 
 Use the following examples of a PodMonitor for NVCA Operator and ServiceMonitor for NVCA for reference:
-Original file line number
+Diff line change
@@ Expand Up @@
     ```
     <Note>
-    For immediate testing, you can use `load_tester_supreme` from `nvcf-onprem` (see [self-hosted-artifact-manifest](./manifest.md)), which supports the `{"message": "hello world"}` request body above. For more function samples, see the [nv-cloud-function-helpers](https://github.com/NVIDIA/nv-cloud-function-helpers) repository and [function-creation](./function-creation.md) for function creation documentation.
+    For immediate testing, you can use `load_tester_supreme` from `nvcf-onprem` (see [self-hosted-artifact-manifest](./manifest.md)), which supports the `{"message": "hello world"}` request body above. For more function samples, see the [NVCF examples](https://github.com/NVIDIA/nvcf/tree/main/examples) repository and [function-creation](./function-creation.md) for function creation documentation.
     </Note>
@@ Expand Down @@