From 9ec5c075f581e1a1e651990c15b861198669ab67 Mon Sep 17 00:00:00 2001
From: Naomi Pentrel <5212232+npentrel@users.noreply.github.com>
Date: Fri, 12 Sep 2025 14:09:01 +0200
Subject: [PATCH 1/3] DOCS-4341: Update run inference

---
 .../data-management/tensor-output.png         | Bin 0 -> 83773 bytes
 docs/data-ai/ai/run-inference.md              | 141 +++++++------
 .../reference/triggers-configuration.md       |  36 ++--
 .../run-inference.snippet.run-inference.go    | 177 ++++++++++++++++
 .../run-inference.snippet.run-inference.py    |  91 +++++++++
 ...sion-service.snippet.run-vision-service.go |  75 +++++++
 ...sion-service.snippet.run-vision-service.py |  43 ++++
 ...sion-service.snippet.run-vision-service.ts |  46 +++++
 .../examples/fleet-api/fleet-issue-1.go       |  88 ++++++++
 .../examples/fleet-api/fleet-issue-2.go       |  76 +++++++
 .../examples/fleet-api/fleet-issue-3.go       | 168 ++++++++++++++++
 .../examples/fleet-api/fleet-issue-4.go       | 168 ++++++++++++++++
 static/include/examples/go.mod                |  11 +
 static/include/examples/go.sum                |   7 +
 .../examples/run-inference/run-inference.go   | 189 ++++++++++++++++++
 .../examples/run-inference/run-inference.py   | 103 ++++++++++
 .../run-inference/run-vision-service.go       |  97 +++++++++
 .../run-inference/run-vision-service.py       |  63 ++++++
 .../run-inference/run-vision-service.ts       |  95 +++++++++
 19 files changed, 1591 insertions(+), 83 deletions(-)
 create mode 100644 assets/tutorials/data-management/tensor-output.png
 create mode 100644 static/include/examples-generated/run-inference.snippet.run-inference.go
 create mode 100644 static/include/examples-generated/run-inference.snippet.run-inference.py
 create mode 100644 static/include/examples-generated/run-vision-service.snippet.run-vision-service.go
 create mode 100644 static/include/examples-generated/run-vision-service.snippet.run-vision-service.py
 create mode 100644 static/include/examples-generated/run-vision-service.snippet.run-vision-service.ts
 create mode 100644 static/include/examples/fleet-api/fleet-issue-1.go
 create mode 100644 static/include/examples/fleet-api/fleet-issue-2.go
 create mode 100644 static/include/examples/fleet-api/fleet-issue-3.go
 create mode 100644 static/include/examples/fleet-api/fleet-issue-4.go
 create mode 100644 static/include/examples/run-inference/run-inference.go
 create mode 100644 static/include/examples/run-inference/run-inference.py
 create mode 100644 static/include/examples/run-inference/run-vision-service.go
 create mode 100644 static/include/examples/run-inference/run-vision-service.py
 create mode 100644 static/include/examples/run-inference/run-vision-service.ts

diff --git a/assets/tutorials/data-management/tensor-output.png b/assets/tutorials/data-management/tensor-output.png
new file mode 100644
index 0000000000000000000000000000000000000000..246814efe4069ff7ccd11009c7d4bfc99f075222
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diff --git a/docs/data-ai/ai/run-inference.md b/docs/data-ai/ai/run-inference.md
index 92cdbd5068..0bc9ab9483 100644
--- a/docs/data-ai/ai/run-inference.md
+++ b/docs/data-ai/ai/run-inference.md
@@ -15,100 +15,111 @@ aliases:
   - /ml/vision/segmentation/
   - /ml/vision/
   - /get-started/quickstarts/detect-people/
-description: "Run inference on a model with a vision service or an SDK."
+description: "Run machine learning inference locally on your robot or remotely in the cloud using vision services, ML model services, or SDKs."
+date: "2025-09-12"
 ---
 
 Inference is the process of generating output from a machine learning (ML) model.
-With Viam, you can run inference to generate the following kinds of output:
 
-- object detection (using bounding boxes)
-- classification (using tags)
-
-You can run inference locally on a Viam machine, or remotely in the Viam cloud.
+You can run inference [locally on a Viam machine](#machine-inference), or [remotely in the Viam cloud](#cloud-inference).
 
 ## Machine inference
 
-You can use `viam-server` to deploy and run ML models directly on your machines.
-
-You can run inference on your machine in the following ways:
-
-- with a vision service
-- manually in application logic with an SDK
+When you have [deployed an ML model](/data-ai/ai/deploy/) on your machine, you can run inference on your machine [directly with the ML model service](#using-an-ml-model-service-directly) or [using a vision service](#using-a-vision-service) that interprets the inferences.
 
 Entry-level devices such as the Raspberry Pi 4 can run small ML models, such as TensorFlow Lite (TFLite).
-More powerful hardware, including the Jetson Xavier or Raspberry Pi 5 with an AI HAT+, can process larger AI models, including TensorFlow and ONNX.
+More powerful hardware, including the Jetson Xavier or Raspberry Pi 5 with an AI HAT+, can process larger models, including TensorFlow and ONNX.
+If your hardware does not support the model you want to run, see [Cloud inference](#cloud-inference).
+
+### Using an ML model service directly
 
 {{< tabs >}}
-{{% tab name="Vision service" %}}
+{{% tab name="Web UI" %}}
 
-Vision services apply an ML model to a stream of images from a camera to generate bounding boxes or classifications.
+1. Visit your machine's **CONFIGURE** or **CONTROL** page.
+1. Expand the **TEST** area of the ML model service panel to view the tensor output.
 
-{{<resources_svc api="rdk:service:vision" type="vision">}}
+{{< imgproc src="/tutorials/data-management/tensor-output.png" alt="Example tensor output" resize="x1000" class="shadow imgzoom fill" >}}
+
+{{% /tab %}}
+{{% tab name="Python" %}}
+
+The following code passes an image to an ML model service, and uses the [`Infer`](/dev/reference/apis/services/ml/#infer) method to make inferences:
+
+{{< read-code-snippet file="/static/include/examples-generated/run-inference.snippet.run-inference.py" lang="py" class="line-numbers linkable-line-numbers" data-line="82-85" >}}
+
+{{% /tab %}}
+{{% tab name="Go" %}}
+
+The following code passes an image to an ML model service, and uses the [`Infer`](/dev/reference/apis/services/ml/#infer) method to make inferences:
+
+{{< read-code-snippet file="/static/include/examples-generated/run-inference.snippet.run-inference.go" lang="go" class="line-numbers linkable-line-numbers" data-line="166-171" >}}
+
+{{% /tab %}}
+{{< /tabs >}}
+
+### Using a vision service
+
+Vision services apply an ML model to a stream of images from a camera to:
 
-{{% alert title="Tip" color="tip" %}}
-Some vision services include their own ML models, and thus do not require a deployed ML model.
-If your vision service does not include an ML model, you must [deploy an ML model to your machine](/data-ai/ai/deploy/) to use that service.
-{{% /alert %}}
+- detect objects (using bounding boxes)
+- classify (using tags)
 
 To use a vision service:
 
-1. Visit your machine's **CONFIGURE** page.
+1. Navigate to your machine's **CONFIGURE** page.
 1. Click the **+** icon next to your main machine part and select **Component or service**.
-1. Type in the name of the service and select a vision service.
-1. If your vision service does not include an ML model, [deploy an ML model to your machine](/data-ai/ai/deploy/) to use that service.
-1. Configure the service based on your use case.
-1. To view the deployed vision service, use the live detection feed.
-   The feed shows an overlay of detected objects or classifications on top of a live camera feed.
-   On the **CONFIGURE** or **CONTROL** pages for your machine, expand the **Test** area of the service panel to view the feed.
+1. Select a vision service.
+1. Configure your vision service.
+   If your vision service does not include an ML model, you need to [deploy an ML model to your machine](/data-ai/ai/deploy/) and select it when configuring your vision service.
 
-   {{< imgproc src="/tutorials/data-management/blue-star.png" alt="Detected blue star" resize="x200" class="shadow" >}}
-   {{< imgproc src="/tutorials/filtered-camera-module/viam-figure-preview.png" alt="Detection of a viam figure with a confidence score of 0.97" resize="x200" class="shadow" >}}
+{{% expand "Click to search available vision services" %}}
 
-For instance, you could use [`viam:vision:mlmodel`](/operate/reference/services/vision/mlmodel/) with the `EfficientDet-COCO` ML model to detect a variety of objects, including people, bicycles, and apples, in a camera feed.
-
-Alternatively, you could use [`viam-soleng:vision:openalpr`](https://app.viam.com/module/viam-soleng/viamalpr) to detect license plates in images.
-Since this service includes its own ML model, there is no need to configure a separate ML model.
+{{<resources_svc api="rdk:service:vision" type="vision">}}
 
-After adding a vision service, you can use a vision service API method with a classifier or a detector to get inferences programmatically.
-For more information, see the APIs for [ML Model](/dev/reference/apis/services/ml/) and [Vision](/dev/reference/apis/services/vision/).
+{{% /expand%}}
 
-{{% /tab %}}
-{{% tab name="SDK" %}}
+{{% expand "Click to view example vision services" %}}
 
-With the Viam SDK, you can pass image data to an ML model service, read the output annotations, and react to output in your own code.
-Use the [`Infer`](/dev/reference/apis/services/ml/#infer) method of the ML Model API to make inferences.
+<!-- prettier-ignore -->
+| Example | Description |
+| ------- | ----------- |
+| Detect a variety of objects | Use the [`viam:vision:mlmodel`](/operate/reference/services/vision/mlmodel/) vision service with the `EfficientDet-COCO` ML model to detect a variety of objects, including people, bicycles, and apples, in a camera feed. |
+| Detect license plates | Use the [`viam-soleng:vision:openalpr`](https://app.viam.com/module/viam-soleng/viamalpr) vision service to detect license plates in images. This service includes its own ML model. |
 
-For example:
+{{% /expand%}}
 
 {{< tabs >}}
-{{% tab name="Python" %}}
+{{% tab name="Web UI" %}}
 
-```python {class="line-numbers linkable-line-numbers"}
-import numpy as np
+1. Visit your machine's **CONFIGURE** or **CONTROL** page.
+1. Expand the **TEST** area of the vision service panel.
 
-my_mlmodel = MLModelClient.from_robot(robot=machine, name="my_mlmodel_service")
+   The feed shows an overlay of detected objects or classifications on top of a live camera feed.
+
+   {{< imgproc src="/tutorials/data-management/blue-star.png" alt="Detected blue star" resize="x200" class="shadow" >}}
+   {{< imgproc src="/tutorials/filtered-camera-module/viam-figure-preview.png" alt="Detection of a viam figure with a confidence score of 0.97" resize="x200" class="shadow" >}}
 
-image_data = np.zeros((1, 384, 384, 3), dtype=np.uint8)
+{{% /tab %}}
+{{% tab name="Python" %}}
 
-# Create the input tensors dictionary
-input_tensors = {
-    "image": image_data
-}
+The following code passes an image from a camera to a vision service and uses the [`GetClassifications`](/dev/reference/apis/services/vision/#GetClassifications) method:
 
-output_tensors = await my_mlmodel.infer(input_tensors)
-```
+{{< read-code-snippet file="/static/include/examples-generated/run-vision-service.snippet.run-vision-service.py" lang="py" class="line-numbers linkable-line-numbers" data-line="36-37" >}}
 
 {{% /tab %}}
 {{% tab name="Go" %}}
 
-```go {class="line-numbers linkable-line-numbers"}
-input_tensors := ml.Tensors{"0": tensor.New(tensor.WithShape(1, 2, 3), tensor.WithBacking([]int{1, 2, 3, 4, 5, 6}))}
+The following code passes an image from a camera to a vision service and uses the [`GetClassifications`](/dev/reference/apis/services/vision/#GetClassifications) method:
 
-output_tensors, err := myMLModel.Infer(context.Background(), input_tensors)
-```
+{{< read-code-snippet file="/static/include/examples-generated/run-vision-service.snippet.run-vision-service.go" lang="go" class="line-numbers linkable-line-numbers" data-line="66-69" >}}
 
 {{% /tab %}}
-{{< /tabs >}}
+{{% tab name="TypeScript" %}}
+
+The following code passes an image from a camera to a vision service and uses the [`GetClassifications`](/dev/reference/apis/services/vision/#GetClassifications) method:
+
+{{< read-code-snippet file="/static/include/examples-generated/run-vision-service.snippet.run-vision-service.ts" lang="ts" class="line-numbers linkable-line-numbers" data-line="32-38" >}}
 
 {{% /tab %}}
 {{< /tabs >}}
@@ -116,19 +127,17 @@ output_tensors, err := myMLModel.Infer(context.Background(), input_tensors)
 ## Cloud inference
 
 Cloud inference enables you to run machine learning models in the Viam cloud, instead of on a local machine.
-Cloud inference often provides more computing power than edge devices, so you can benefit from:
+Cloud inference provides more computing power than edge devices, enabling you to run more computationally-intensive models or achieve faster inference times.
 
-- larger, more accurate models
-- faster inference times
+You can run cloud inference using any TensorFlow and TensorFlow Lite model in the Viam registry, including unlisted models owned by or shared with you.
 
-You can run cloud inference using any TensorFlow and TensorFlow Lite model in the Viam registry, including private models owned by or shared with your organization.
-
-To run cloud inference, you must pass
+To run cloud inference, you must pass the following:
 
 - the binary data ID and organization of the data you want to run inference on
 - the name, version, and organization of the model you want to use for inference
 
-The [`viam infer`](/dev/tools/cli/#infer) CLI command runs inference in the cloud on a piece of data using the specified ML model:
+You can obtain the binary data ID from the [**DATA** tab](https://app.viam.com/data/view) and the organization ID by running the CLI command `viam org list`.
+You can find the model information on the [**MODELS** tab](https://app.viam.com/models).
 
 ```sh {class="command-line" data-prompt="$" data-output="2-18"}
 viam infer --binary-data-id <binary-data-id> --model-name <model-name> --model-org-id <org-id-that-owns-model> --model-version "2025-04-14T16-38-25" --org-id <org-id-that-executes-inference>
@@ -151,5 +160,7 @@ Bounding Box Format: [x_min, y_min, x_max, y_max]
   No annotations.
 ```
 
-`infer` returns a list of detected classes or bounding boxes depending on the output of the ML model you specified, as well as a list of confidence values for those classes or boxes.
-This method returns bounding box output using proportional coordinates between 0 and 1, with the origin `(0, 0)` in the top left of the image and `(1, 1)` in the bottom right.
+The command returns a list of detected classes or bounding boxes depending on the output of the ML model you specified, as well as a list of confidence values for those classes or boxes.
+The bounding box output uses proportional coordinates between 0 and 1, with the origin `(0, 0)` in the top left of the image and `(1, 1)` in the bottom right.
+
+For more information, see [`viam infer`](/dev/tools/cli/#infer).
diff --git a/docs/data-ai/reference/triggers-configuration.md b/docs/data-ai/reference/triggers-configuration.md
index e69f6b2c83..e087e8bcf2 100644
--- a/docs/data-ai/reference/triggers-configuration.md
+++ b/docs/data-ai/reference/triggers-configuration.md
@@ -47,24 +47,24 @@ The following template demonstrates the structure of a JSON configuration for a
 The following template demonstrates the structure of a JSON configuration for a trigger that alerts when data syncs to the Viam cloud:
 
 ```json {class="line-numbers linkable-line-numbers"}
-  "triggers": [
-    {
-      "name": "<trigger name>",
-      "event": {
-        "type": "part_data_ingested",
-        "data_ingested": {
-          "data_types": ["binary", "tabular", "file", "unspecified"]
-        }
-      },
-      "notifications": [
-        {
-          "type": "<webhook|email>",
-          "value": "<webhook URL or email address>",
-          "seconds_between_notifications": <number of seconds>
-        }
-      ]
-    }
-  ]
+"triggers": [
+  {
+    "name": "<trigger name>",
+    "event": {
+      "type": "part_data_ingested",
+      "data_ingested": {
+        "data_types": ["binary", "tabular", "file", "unspecified"]
+      }
+    },
+    "notifications": [
+      {
+        "type": "<webhook|email>",
+        "value": "<webhook URL or email address>",
+        "seconds_between_notifications": <number of seconds>
+      }
+    ]
+  }
+]
 ```
 
 ### Conditional trigger template
diff --git a/static/include/examples-generated/run-inference.snippet.run-inference.go b/static/include/examples-generated/run-inference.snippet.run-inference.go
new file mode 100644
index 0000000000..9fe5c28070
--- /dev/null
+++ b/static/include/examples-generated/run-inference.snippet.run-inference.go
@@ -0,0 +1,177 @@
+package main
+
+import (
+	"bytes"
+	"context"
+	"fmt"
+	"image"
+	"image/jpeg"
+
+	"gorgonia.org/tensor"
+
+	"go.viam.com/rdk/logging"
+	"go.viam.com/rdk/ml"
+	"go.viam.com/rdk/robot/client"
+	"go.viam.com/rdk/components/camera"
+	"go.viam.com/rdk/services/mlmodel"
+	"go.viam.com/rdk/utils"
+	"go.viam.com/utils/rpc"
+)
+
+func main() {
+	apiKey := ""
+	apiKeyID := ""
+	machineAddress := ""
+	mlModelName := ""
+	cameraName := ""
+
+
+	logger := logging.NewDebugLogger("client")
+	ctx := context.Background()
+
+	machine, err := client.New(
+		context.Background(),
+		machineAddress,
+		logger,
+		client.WithDialOptions(rpc.WithEntityCredentials(
+			apiKeyID,
+			rpc.Credentials{
+				Type:    rpc.CredentialsTypeAPIKey,
+				Payload: apiKey,
+			})),
+	)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Capture image from camera
+	cam, err := camera.FromRobot(machine, cameraName)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	imageData, _, err := cam.Image(ctx, utils.MimeTypeJPEG, nil)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Decode the image data to get the actual image
+	img, err := jpeg.Decode(bytes.NewReader(imageData))
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Get ML model metadata to understand input requirements
+	mlModel, err := mlmodel.FromRobot(machine, mlModelName)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	metadata, err := mlModel.Metadata(ctx)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Get expected input shape and type from metadata
+	var expectedShape []int
+	var expectedDtype tensor.Dtype
+	var expectedName string
+
+	if len(metadata.Inputs) > 0 {
+		inputInfo := metadata.Inputs[0]
+		expectedShape = inputInfo.Shape
+		expectedName = inputInfo.Name
+
+		// Convert data type string to tensor.Dtype
+		switch inputInfo.DataType {
+		case "uint8":
+			expectedDtype = tensor.Uint8
+		case "float32":
+			expectedDtype = tensor.Float32
+		default:
+			expectedDtype = tensor.Float32 // Default to float32
+		}
+	} else {
+		logger.Fatal("No input info found in model metadata")
+	}
+
+	// Resize image to expected dimensions
+	bounds := img.Bounds()
+	width := bounds.Dx()
+	height := bounds.Dy()
+
+	// Extract expected dimensions
+	if len(expectedShape) != 4 || expectedShape[0] != 1 || expectedShape[3] != 3 {
+		logger.Fatal("Unexpected input shape format")
+	}
+
+	expectedHeight := expectedShape[1]
+	expectedWidth := expectedShape[2]
+
+	// Create a new image with the expected dimensions
+	resizedImg := image.NewRGBA(image.Rect(0, 0, expectedWidth, expectedHeight))
+
+	// Simple nearest neighbor resize
+	for y := 0; y < expectedHeight; y++ {
+		for x := 0; x < expectedWidth; x++ {
+			srcX := x * width / expectedWidth
+			srcY := y * height / expectedHeight
+			resizedImg.Set(x, y, img.At(srcX, srcY))
+		}
+	}
+
+	// Convert image to tensor data
+	tensorData := make([]float32, 1*expectedHeight*expectedWidth*3)
+	idx := 0
+
+	for y := 0; y < expectedHeight; y++ {
+		for x := 0; x < expectedWidth; x++ {
+			r, g, b, _ := resizedImg.At(x, y).RGBA()
+
+			// Convert from 16-bit to 8-bit and normalize to [0, 1] for float32
+			if expectedDtype == tensor.Float32 {
+				tensorData[idx] = float32(r>>8) / 255.0   // R
+				tensorData[idx+1] = float32(g>>8) / 255.0 // G
+				tensorData[idx+2] = float32(b>>8) / 255.0 // B
+			} else {
+				// For uint8, we need to create a uint8 slice
+				logger.Fatal("uint8 tensor creation not implemented in this example")
+			}
+			idx += 3
+		}
+	}
+
+	// Create input tensor
+	var inputTensor tensor.Tensor
+	if expectedDtype == tensor.Float32 {
+		inputTensor = tensor.New(
+			tensor.WithShape(1, expectedHeight, expectedWidth, 3),
+			tensor.WithBacking(tensorData),
+			tensor.Of(tensor.Float32),
+		)
+	} else {
+		logger.Fatal("Only float32 tensors are supported in this example")
+	}
+
+	// Convert tensor.Tensor to *tensor.Dense for ml.Tensors
+	denseTensor, ok := inputTensor.(*tensor.Dense)
+	if !ok {
+		logger.Fatal("Failed to convert inputTensor to *tensor.Dense")
+	}
+
+	inputTensors := ml.Tensors{
+		expectedName: denseTensor,
+	}
+
+	outputTensors, err := mlModel.Infer(ctx, inputTensors)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	fmt.Printf("Output tensors: %v\n", outputTensors)
+
+	err = machine.Close(ctx)
+	if err != nil {
+		logger.Fatal(err)
+	}
+}
diff --git a/static/include/examples-generated/run-inference.snippet.run-inference.py b/static/include/examples-generated/run-inference.snippet.run-inference.py
new file mode 100644
index 0000000000..bccf0a8b60
--- /dev/null
+++ b/static/include/examples-generated/run-inference.snippet.run-inference.py
@@ -0,0 +1,91 @@
+import asyncio
+import numpy as np
+
+from PIL import Image
+from viam.components.camera import Camera
+from viam.media.utils.pil import viam_to_pil_image
+from viam.robot.client import RobotClient
+from viam.services.mlmodel import MLModelClient
+
+# Configuration constants – replace with your actual values
+API_KEY = ""  # API key, find or create in your organization settings
+API_KEY_ID = ""  # API key ID, find or create in your organization settings
+MACHINE_ADDRESS = ""  # the address of the machine you want to capture images from
+ML_MODEL_NAME = ""  # the name of the ML model you want to use
+CAMERA_NAME = ""  # the name of the camera you want to capture images from
+
+
+async def connect_machine() -> RobotClient:
+    """Establish a connection to the robot using the robot address."""
+    machine_opts = RobotClient.Options.with_api_key(
+        api_key=API_KEY,
+        api_key_id=API_KEY_ID
+    )
+    return await RobotClient.at_address(MACHINE_ADDRESS, machine_opts)
+
+async def main() -> int:
+    machine = await connect_machine()
+
+    camera = Camera.from_robot(machine, CAMERA_NAME)
+    ml_model = MLModelClient.from_robot(machine, ML_MODEL_NAME)
+
+    # Get ML model metadata to understand input requirements
+    metadata = await ml_model.metadata()
+
+    # Capture image
+    image_frame = await camera.get_image()
+
+    # Convert ViamImage to PIL Image first
+    pil_image = viam_to_pil_image(image_frame)
+    # Convert PIL Image to numpy array
+    image_array = np.array(pil_image)
+
+    # Get expected input shape from metadata
+    expected_shape = list(metadata.input_info[0].shape)
+    expected_dtype = metadata.input_info[0].data_type
+    expected_name = metadata.input_info[0].name
+
+    if not expected_shape:
+        print("No input info found for 'image'")
+        return 1
+
+    if len(expected_shape) == 4 and expected_shape[0] == 1 and expected_shape[3] == 3:
+        expected_height = expected_shape[1]
+        expected_width = expected_shape[2]
+
+        # Resize to expected dimensions
+        if image_array.shape[:2] != (expected_height, expected_width):
+            pil_image_resized = pil_image.resize((expected_width, expected_height))
+            image_array = np.array(pil_image_resized)
+    else:
+        print(f"Unexpected input shape format.")
+        return 1
+
+    # Add batch dimension and ensure correct shape
+    image_data = np.expand_dims(image_array, axis=0)
+
+    # Ensure the data type matches expected type
+    if expected_dtype == "uint8":
+        image_data = image_data.astype(np.uint8)
+    elif expected_dtype == "float32":
+        # Convert to float32 and normalize to [0, 1] range
+        image_data = image_data.astype(np.float32) / 255.0
+    else:
+        # Default to float32 with normalization
+        image_data = image_data.astype(np.float32) / 255.0
+
+    # Create the input tensors dictionary
+    input_tensors = {
+        expected_name: image_data
+    }
+
+    output_tensors = await ml_model.infer(input_tensors)
+    print(f"Output tensors:")
+    for key, value in output_tensors.items():
+        print(f"{key}: shape={value.shape}, dtype={value.dtype}")
+
+    await machine.close()
+    return 0
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/static/include/examples-generated/run-vision-service.snippet.run-vision-service.go b/static/include/examples-generated/run-vision-service.snippet.run-vision-service.go
new file mode 100644
index 0000000000..58e321d716
--- /dev/null
+++ b/static/include/examples-generated/run-vision-service.snippet.run-vision-service.go
@@ -0,0 +1,75 @@
+package main
+
+import (
+	"context"
+	"fmt"
+	"image/jpeg"
+	"bytes"
+
+	"go.viam.com/rdk/logging"
+	"go.viam.com/rdk/robot/client"
+	"go.viam.com/rdk/services/vision"
+	"go.viam.com/rdk/components/camera"
+	"go.viam.com/rdk/utils"
+	"go.viam.com/utils/rpc"
+)
+
+func main() {
+	apiKey := ""
+	apiKeyID := ""
+	machineAddress := ""
+	classifierName := ""
+	cameraName := ""
+
+
+	logger := logging.NewDebugLogger("client")
+	ctx := context.Background()
+
+	machine, err := client.New(
+		context.Background(),
+		machineAddress,
+		logger,
+		client.WithDialOptions(rpc.WithEntityCredentials(
+			apiKeyID,
+			rpc.Credentials{
+				Type:    rpc.CredentialsTypeAPIKey,
+				Payload: apiKey,
+			})),
+	)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Capture image from camera
+	cam, err := camera.FromRobot(machine, cameraName)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	imageData, _, err := cam.Image(ctx, utils.MimeTypeJPEG, nil)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Convert binary data to image.Image
+	img, err := jpeg.Decode(bytes.NewReader(imageData))
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Get classifications using the image
+	classifier, err := vision.FromRobot(machine, classifierName)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	classifications, err := classifier.Classifications(ctx, img, 2, nil)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	err = machine.Close(ctx)
+	if err != nil {
+		logger.Fatal(err)
+	}
+}
diff --git a/static/include/examples-generated/run-vision-service.snippet.run-vision-service.py b/static/include/examples-generated/run-vision-service.snippet.run-vision-service.py
new file mode 100644
index 0000000000..6d367a2d1a
--- /dev/null
+++ b/static/include/examples-generated/run-vision-service.snippet.run-vision-service.py
@@ -0,0 +1,43 @@
+import asyncio
+import numpy as np
+
+from PIL import Image
+from viam.components.camera import Camera
+from viam.media.utils.pil import viam_to_pil_image
+from viam.robot.client import RobotClient
+from viam.services.vision import VisionClient
+
+# Configuration constants – replace with your actual values
+API_KEY = ""  # API key, find or create in your organization settings
+API_KEY_ID = ""  # API key ID, find or create in your organization settings
+MACHINE_ADDRESS = ""  # the address of the machine you want to capture images from
+CLASSIFIER_NAME = ""  # the name of the classifier you want to use
+CAMERA_NAME = ""  # the name of the camera you want to capture images from
+
+
+async def connect_machine() -> RobotClient:
+    """Establish a connection to the robot using the robot address."""
+    machine_opts = RobotClient.Options.with_api_key(
+        api_key=API_KEY,
+        api_key_id=API_KEY_ID
+    )
+    return await RobotClient.at_address(MACHINE_ADDRESS, machine_opts)
+
+async def main() -> int:
+    machine = await connect_machine()
+
+    camera = Camera.from_robot(machine, CAMERA_NAME)
+    classifier = VisionClient.from_robot(machine, CLASSIFIER_NAME)
+
+    # Capture image
+    image_frame = await camera.get_image(mime_type="image/jpeg")
+
+    # Get tags using the ViamImage (not the PIL image)
+    tags = await classifier.get_classifications(
+        image=image_frame, image_format="image/jpeg", count=2)
+
+    await machine.close()
+    return 0
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/static/include/examples-generated/run-vision-service.snippet.run-vision-service.ts b/static/include/examples-generated/run-vision-service.snippet.run-vision-service.ts
new file mode 100644
index 0000000000..98b7f98857
--- /dev/null
+++ b/static/include/examples-generated/run-vision-service.snippet.run-vision-service.ts
@@ -0,0 +1,46 @@
+import { createRobotClient, RobotClient, VisionClient, CameraClient } from "@viamrobotics/sdk";
+
+// Configuration constants – replace with your actual values
+let API_KEY = "";  // API key, find or create in your organization settings
+let API_KEY_ID = "";  // API key ID, find or create in your organization settings
+let MACHINE_ADDRESS = "";  // the address of the machine you want to capture images from
+let CLASSIFIER_NAME = "";  // the name of the classifier you want to use
+let CAMERA_NAME = "";  // the name of the camera you want to capture images from
+
+async function connectMachine(): Promise<RobotClient> {
+    // Establish a connection to the robot using the machine address
+    return await createRobotClient({
+        host: MACHINE_ADDRESS,
+        credentials: {
+          type: 'api-key',
+          payload: API_KEY,
+          authEntity: API_KEY_ID,
+        },
+        signalingAddress: 'https://app.viam.com:443',
+      });
+}
+
+async function main(): Promise<number> {
+    const machine = await connectMachine();
+    const camera = new CameraClient(machine, CAMERA_NAME);
+    const classifier = new VisionClient(machine, CLASSIFIER_NAME);
+
+    // Capture image
+    const imageFrame = await camera.getImage();
+
+    // Get tags using the image
+    const tags = await classifier.getClassifications(
+        imageFrame,
+        imageFrame.width ?? 0,
+        imageFrame.height ?? 0,
+        imageFrame.mimeType ?? "",
+        2
+    );
+
+    return 0;
+}
+
+main().catch((error) => {
+    console.error("Script failed:", error);
+    process.exit(1);
+});
diff --git a/static/include/examples/fleet-api/fleet-issue-1.go b/static/include/examples/fleet-api/fleet-issue-1.go
new file mode 100644
index 0000000000..2cbd55efd2
--- /dev/null
+++ b/static/include/examples/fleet-api/fleet-issue-1.go
@@ -0,0 +1,88 @@
+package main
+
+import (
+	"context"
+	"fmt"
+	"os"
+
+	"go.viam.com/rdk/app"
+	"go.viam.com/rdk/logging"
+)
+
+// Configuration constants – replace with your actual values
+var (
+	API_KEY     = "" // API key, find or create in your organization settings
+	API_KEY_ID  = "" // API key ID, find or create in your organization settings
+	ORG_ID      = "" // Organization ID, find or create in your organization settings
+)
+
+func main() {
+	ORG_ID = os.Getenv("TEST_ORG_ID")
+	API_KEY = os.Getenv("VIAM_API_KEY")
+	API_KEY_ID = os.Getenv("VIAM_API_KEY_ID")
+    logger := logging.NewDebugLogger("client")
+	ctx := context.Background()
+
+	// Make a ViamClient
+	viamClient, err := app.CreateViamClientWithAPIKey(
+		ctx, app.Options{}, API_KEY, API_KEY_ID, logger)
+	if err != nil {
+		logger.Fatal(err)
+	}
+	defer viamClient.Close()
+
+	// Instantiate an AppClient called "cloud"
+	// to run fleet management API methods on
+	cloud := viamClient.AppClient()
+
+    //  ISSUE 1: CREATE & DELETE REGISTRY ITEM
+
+	// Create registry item
+	err = cloud.CreateRegistryItem(ctx, ORG_ID, "new-registry-item-12", app.PackageTypeMLModel)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Get number of registry items
+    registryItems, err := cloud.ListRegistryItems(
+		ctx,
+		&ORG_ID,
+		[]app.PackageType{app.PackageTypeMLModel},
+		[]app.Visibility{app.VisibilityPrivate, app.VisibilityPublic},
+		[]string{"linux/any"},
+		[]app.RegistryItemStatus{app.RegistryItemStatusPublished},
+		&app.ListRegistryItemsOptions{})
+	if err != nil {
+		logger.Fatal(err)
+	}
+	numRegistryItems := len(registryItems)
+	fmt.Println("Number of registry items:", numRegistryItems)
+    if numRegistryItems <= 0 {
+		logger.Fatal("Expected > 0 registry items")
+	}
+
+	// DOES NOT SEEM TO DELETE THE REGISTRY ITEM
+	// Delete registry item
+	err = cloud.DeleteRegistryItem(ctx, "docs-test:new-registry-item-12")
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Get number of registry items
+    registryItems, err = cloud.ListRegistryItems(
+		ctx,
+		&ORG_ID,
+		[]app.PackageType{app.PackageTypeMLModel},
+		[]app.Visibility{app.VisibilityPrivate, app.VisibilityPublic},
+		[]string{"linux/any"},
+		[]app.RegistryItemStatus{app.RegistryItemStatusPublished},
+		&app.ListRegistryItemsOptions{})
+	if err != nil {
+		logger.Fatal(err)
+	}
+	fmt.Println("Number of registry items:", len(registryItems))
+	if numRegistryItems - 1 != len(registryItems) {
+		logger.Fatal("Expected 1 fewer registry item after deletion")
+	}
+
+}
diff --git a/static/include/examples/fleet-api/fleet-issue-2.go b/static/include/examples/fleet-api/fleet-issue-2.go
new file mode 100644
index 0000000000..c12eb0558f
--- /dev/null
+++ b/static/include/examples/fleet-api/fleet-issue-2.go
@@ -0,0 +1,76 @@
+package main
+
+import (
+	"context"
+	"fmt"
+	"os"
+
+	"go.viam.com/rdk/app"
+	"go.viam.com/rdk/logging"
+)
+
+// Configuration constants – replace with your actual values
+var (
+	API_KEY     = "" // API key, find or create in your organization settings
+	API_KEY_ID  = "" // API key ID, find or create in your organization settings
+	ORG_ID      = "" // Organization ID, find or create in your organization settings
+	LOCATION_ID = "" // Location ID, find or create in your organization settings
+)
+
+func main() {
+	// :remove-start:
+	ORG_ID = os.Getenv("TEST_ORG_ID")
+	API_KEY = os.Getenv("VIAM_API_KEY")
+	API_KEY_ID = os.Getenv("VIAM_API_KEY_ID")
+	LOCATION_ID = "pg5q3j3h95"
+	// :remove-end:
+    logger := logging.NewDebugLogger("client")
+	ctx := context.Background()
+
+	// Make a ViamClient
+	viamClient, err := app.CreateViamClientWithAPIKey(
+		ctx, app.Options{}, API_KEY, API_KEY_ID, logger)
+	if err != nil {
+		logger.Fatal(err)
+	}
+	defer viamClient.Close()
+
+	// Instantiate an AppClient called "cloud"
+	// to run fleet management API methods on
+	cloud := viamClient.AppClient()
+
+	//  ISSUE 2: Add role
+	// User ID: d3bcb264-1a60-406b-8a79-9e43da4f3c9d
+	// 2025-09-02T10:31:21.526Z	ERROR	client	fleet-api/fleet-issues.go:113	rpc error: code = InvalidArgument desc = requestID=9806ca33a0007d462e545f16a7cc0ec0: provided invalid authorization id 'location_owner' for resource type 'location' and authorization type 'owner'
+
+	memberList, _, err := cloud.ListOrganizationMembers(ctx, ORG_ID)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Add role
+	userID := memberList[1].UserID
+	fmt.Println("User ID:", userID)
+
+	err = cloud.AddRole(
+		ctx,
+		ORG_ID,
+		userID,
+		app.AuthRoleOwner,
+		app.AuthResourceTypeLocation,
+		LOCATION_ID,
+	)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Change role
+    fmt.Printf(userID)
+	err = cloud.ChangeRole(ctx, &app.Authorization{}, ORG_ID, userID, app.AuthRoleOwner, app.AuthResourceTypeOrganization, ORG_ID)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// d3bcb264-1a60-406b-8a79-9e43da4f3c9d2025-09-02T10:33:43.956Z	ERROR	client	fleet-api/fleet-issues.go:122	rpc error: code = InvalidArgument desc = requestID=df8a74809aad4dfd156a7c2bad698d23: missing required 'identity_id'
+
+}
diff --git a/static/include/examples/fleet-api/fleet-issue-3.go b/static/include/examples/fleet-api/fleet-issue-3.go
new file mode 100644
index 0000000000..1bda39812b
--- /dev/null
+++ b/static/include/examples/fleet-api/fleet-issue-3.go
@@ -0,0 +1,168 @@
+package main
+
+import (
+	"context"
+	"fmt"
+	"os"
+
+	"go.viam.com/rdk/app"
+	"go.viam.com/rdk/logging"
+)
+
+// Configuration constants – replace with your actual values
+var (
+	API_KEY     = "" // API key, find or create in your organization settings
+	API_KEY_ID  = "" // API key ID, find or create in your organization settings
+	ORG_ID      = "" // Organization ID, find or create in your organization settings
+	EMAIL_ADDRESS = "" // Email address of the user to get the user id for
+	LOCATION_ID = "" // Location ID, find or create in your organization settings
+)
+
+func main() {
+	// :remove-start:
+	ORG_ID = os.Getenv("TEST_ORG_ID")
+	API_KEY = os.Getenv("VIAM_API_KEY")
+	API_KEY_ID = os.Getenv("VIAM_API_KEY_ID")
+	LOCATION_ID = "pg5q3j3h95"
+	// :remove-end:
+    logger := logging.NewDebugLogger("client")
+	ctx := context.Background()
+
+	// Make a ViamClient
+	viamClient, err := app.CreateViamClientWithAPIKey(
+		ctx, app.Options{}, API_KEY, API_KEY_ID, logger)
+	if err != nil {
+		logger.Fatal(err)
+	}
+	defer viamClient.Close()
+
+	// Instantiate an AppClient called "cloud"
+	// to run fleet management API methods on
+	cloud := viamClient.AppClient()
+
+    //  ISSUE 1: CREATE & DELETE REGISTRY ITEM
+
+	// // Create registry item
+	// err = cloud.CreateRegistryItem(ctx, ORG_ID, "new-registry-item-12", app.PackageTypeMLModel)
+	// if err != nil {
+	// 	logger.Fatal(err)
+	// }
+
+	// // Get number of registry items
+    // registryItems, err := cloud.ListRegistryItems(
+	// 	ctx,
+	// 	&ORG_ID,
+	// 	[]app.PackageType{app.PackageTypeMLModel},
+	// 	[]app.Visibility{app.VisibilityPrivate, app.VisibilityPublic},
+	// 	[]string{"linux/any"},
+	// 	[]app.RegistryItemStatus{app.RegistryItemStatusPublished},
+	// 	&app.ListRegistryItemsOptions{})
+	// if err != nil {
+	// 	logger.Fatal(err)
+	// }
+	// numRegistryItems := len(registryItems)
+	// fmt.Println("Number of registry items:", numRegistryItems)
+    // if numRegistryItems <= 0 {
+	// 	logger.Fatal("Expected > 0 registry items")
+	// }
+
+	// // DOES NOT SEEM TO DELETE THE REGISTRY ITEM
+	// // Delete registry item
+	// err = cloud.DeleteRegistryItem(ctx, "docs-test:new-registry-item-12")
+	// if err != nil {
+	// 	logger.Fatal(err)
+	// }
+
+	// // Get number of registry items
+    // registryItems, err = cloud.ListRegistryItems(
+	// 	ctx,
+	// 	&ORG_ID,
+	// 	[]app.PackageType{app.PackageTypeMLModel},
+	// 	[]app.Visibility{app.VisibilityPrivate, app.VisibilityPublic},
+	// 	[]string{"linux/any"},
+	// 	[]app.RegistryItemStatus{app.RegistryItemStatusPublished},
+	// 	&app.ListRegistryItemsOptions{})
+	// if err != nil {
+	// 	logger.Fatal(err)
+	// }
+	// fmt.Println("Number of registry items:", len(registryItems))
+	// if numRegistryItems - 1 != len(registryItems) {
+	// 	logger.Fatal("Expected 1 fewer registry item after deletion")
+	// }
+
+	//  ISSUE 2: Add role
+	// User ID: d3bcb264-1a60-406b-8a79-9e43da4f3c9d
+	// 2025-09-02T10:31:21.526Z	ERROR	client	fleet-api/fleet-issues.go:113	rpc error: code = InvalidArgument desc = requestID=9806ca33a0007d462e545f16a7cc0ec0: provided invalid authorization id 'location_owner' for resource type 'location' and authorization type 'owner'
+
+	memberList, _, err := cloud.ListOrganizationMembers(ctx, ORG_ID)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Add role
+	userID := memberList[1].UserID
+	fmt.Println("User ID:", userID)
+
+	// err = cloud.AddRole(
+	// 	ctx,
+	// 	ORG_ID,
+	// 	userID,
+	// 	app.AuthRoleOwner,
+	// 	app.AuthResourceTypeLocation,
+	// 	LOCATION_ID,
+	// )
+	// if err != nil {
+	// 	logger.Fatal(err)
+	// }
+
+	// Change role
+    fmt.Printf(userID)
+	// err = cloud.ChangeRole(ctx, &app.Authorization{}, ORG_ID, userID, app.AuthRoleOwner, app.AuthResourceTypeOrganization, ORG_ID)
+	// if err != nil {
+	// 	logger.Fatal(err)
+	// }
+
+	// d3bcb264-1a60-406b-8a79-9e43da4f3c9d2025-09-02T10:33:43.956Z	ERROR	client	fleet-api/fleet-issues.go:122	rpc error: code = InvalidArgument desc = requestID=df8a74809aad4dfd156a7c2bad698d23: missing required 'identity_id'
+
+	//  ISSUE 3: It seems we can't create keys because we can't create APIKeyAuthorization structs
+
+	// Create API key
+	// Since APIKeyAuthorization has unexported fields, we can't construct it directly
+	// apiKey, apiKeyID, err := cloud.CreateKey(ctx, ORG_ID, []app.APIKeyAuthorization{{
+	// 	Role: app.AuthRoleOwner,
+	// 	ResourceType: app.AuthResourceTypeLocation,
+	// 	ResourceID: LOCATION_ID,
+	// }}, "mytestkey")
+	// if err != nil {
+	// 	logger.Fatal(err)
+	// }
+	// if apiKey == "" {
+	// 	logger.Fatal("API key should not be empty")
+	// }
+	// if apiKeyID == "" {
+	// 	logger.Fatal("API key ID should not be empty")
+	// }
+
+	//  ISSUE 4: RenameKey does not return the key ID
+	apiKeyID2, apiKey2, err := cloud.CreateKeyFromExistingKeyAuthorizations(ctx, newAPIKeyID)
+	if err != nil {
+		logger.Fatal(err)
+	}
+	if apiKey2 == "" {
+		logger.Fatal("API key 2 should not be empty")
+	}
+	if apiKeyID2 == "" {
+		logger.Fatal("API key ID 2 should not be empty")
+	}
+	fmt.Printf("API key id 2: %+v\n", apiKeyID2)
+
+	apiKeyID3, apiKeyName3, err := cloud.RenameKey(ctx, apiKeyID2, "mytestkey2newName")
+	if err != nil {
+		logger.Fatal(err)
+	}
+	if apiKeyName3 != "mytestkey2newName" {
+		logger.Fatal("API key 3 should be renamed")
+	}
+	fmt.Printf("API key id 3: %+v\n", apiKeyID3)
+
+}
diff --git a/static/include/examples/fleet-api/fleet-issue-4.go b/static/include/examples/fleet-api/fleet-issue-4.go
new file mode 100644
index 0000000000..1bda39812b
--- /dev/null
+++ b/static/include/examples/fleet-api/fleet-issue-4.go
@@ -0,0 +1,168 @@
+package main
+
+import (
+	"context"
+	"fmt"
+	"os"
+
+	"go.viam.com/rdk/app"
+	"go.viam.com/rdk/logging"
+)
+
+// Configuration constants – replace with your actual values
+var (
+	API_KEY     = "" // API key, find or create in your organization settings
+	API_KEY_ID  = "" // API key ID, find or create in your organization settings
+	ORG_ID      = "" // Organization ID, find or create in your organization settings
+	EMAIL_ADDRESS = "" // Email address of the user to get the user id for
+	LOCATION_ID = "" // Location ID, find or create in your organization settings
+)
+
+func main() {
+	// :remove-start:
+	ORG_ID = os.Getenv("TEST_ORG_ID")
+	API_KEY = os.Getenv("VIAM_API_KEY")
+	API_KEY_ID = os.Getenv("VIAM_API_KEY_ID")
+	LOCATION_ID = "pg5q3j3h95"
+	// :remove-end:
+    logger := logging.NewDebugLogger("client")
+	ctx := context.Background()
+
+	// Make a ViamClient
+	viamClient, err := app.CreateViamClientWithAPIKey(
+		ctx, app.Options{}, API_KEY, API_KEY_ID, logger)
+	if err != nil {
+		logger.Fatal(err)
+	}
+	defer viamClient.Close()
+
+	// Instantiate an AppClient called "cloud"
+	// to run fleet management API methods on
+	cloud := viamClient.AppClient()
+
+    //  ISSUE 1: CREATE & DELETE REGISTRY ITEM
+
+	// // Create registry item
+	// err = cloud.CreateRegistryItem(ctx, ORG_ID, "new-registry-item-12", app.PackageTypeMLModel)
+	// if err != nil {
+	// 	logger.Fatal(err)
+	// }
+
+	// // Get number of registry items
+    // registryItems, err := cloud.ListRegistryItems(
+	// 	ctx,
+	// 	&ORG_ID,
+	// 	[]app.PackageType{app.PackageTypeMLModel},
+	// 	[]app.Visibility{app.VisibilityPrivate, app.VisibilityPublic},
+	// 	[]string{"linux/any"},
+	// 	[]app.RegistryItemStatus{app.RegistryItemStatusPublished},
+	// 	&app.ListRegistryItemsOptions{})
+	// if err != nil {
+	// 	logger.Fatal(err)
+	// }
+	// numRegistryItems := len(registryItems)
+	// fmt.Println("Number of registry items:", numRegistryItems)
+    // if numRegistryItems <= 0 {
+	// 	logger.Fatal("Expected > 0 registry items")
+	// }
+
+	// // DOES NOT SEEM TO DELETE THE REGISTRY ITEM
+	// // Delete registry item
+	// err = cloud.DeleteRegistryItem(ctx, "docs-test:new-registry-item-12")
+	// if err != nil {
+	// 	logger.Fatal(err)
+	// }
+
+	// // Get number of registry items
+    // registryItems, err = cloud.ListRegistryItems(
+	// 	ctx,
+	// 	&ORG_ID,
+	// 	[]app.PackageType{app.PackageTypeMLModel},
+	// 	[]app.Visibility{app.VisibilityPrivate, app.VisibilityPublic},
+	// 	[]string{"linux/any"},
+	// 	[]app.RegistryItemStatus{app.RegistryItemStatusPublished},
+	// 	&app.ListRegistryItemsOptions{})
+	// if err != nil {
+	// 	logger.Fatal(err)
+	// }
+	// fmt.Println("Number of registry items:", len(registryItems))
+	// if numRegistryItems - 1 != len(registryItems) {
+	// 	logger.Fatal("Expected 1 fewer registry item after deletion")
+	// }
+
+	//  ISSUE 2: Add role
+	// User ID: d3bcb264-1a60-406b-8a79-9e43da4f3c9d
+	// 2025-09-02T10:31:21.526Z	ERROR	client	fleet-api/fleet-issues.go:113	rpc error: code = InvalidArgument desc = requestID=9806ca33a0007d462e545f16a7cc0ec0: provided invalid authorization id 'location_owner' for resource type 'location' and authorization type 'owner'
+
+	memberList, _, err := cloud.ListOrganizationMembers(ctx, ORG_ID)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Add role
+	userID := memberList[1].UserID
+	fmt.Println("User ID:", userID)
+
+	// err = cloud.AddRole(
+	// 	ctx,
+	// 	ORG_ID,
+	// 	userID,
+	// 	app.AuthRoleOwner,
+	// 	app.AuthResourceTypeLocation,
+	// 	LOCATION_ID,
+	// )
+	// if err != nil {
+	// 	logger.Fatal(err)
+	// }
+
+	// Change role
+    fmt.Printf(userID)
+	// err = cloud.ChangeRole(ctx, &app.Authorization{}, ORG_ID, userID, app.AuthRoleOwner, app.AuthResourceTypeOrganization, ORG_ID)
+	// if err != nil {
+	// 	logger.Fatal(err)
+	// }
+
+	// d3bcb264-1a60-406b-8a79-9e43da4f3c9d2025-09-02T10:33:43.956Z	ERROR	client	fleet-api/fleet-issues.go:122	rpc error: code = InvalidArgument desc = requestID=df8a74809aad4dfd156a7c2bad698d23: missing required 'identity_id'
+
+	//  ISSUE 3: It seems we can't create keys because we can't create APIKeyAuthorization structs
+
+	// Create API key
+	// Since APIKeyAuthorization has unexported fields, we can't construct it directly
+	// apiKey, apiKeyID, err := cloud.CreateKey(ctx, ORG_ID, []app.APIKeyAuthorization{{
+	// 	Role: app.AuthRoleOwner,
+	// 	ResourceType: app.AuthResourceTypeLocation,
+	// 	ResourceID: LOCATION_ID,
+	// }}, "mytestkey")
+	// if err != nil {
+	// 	logger.Fatal(err)
+	// }
+	// if apiKey == "" {
+	// 	logger.Fatal("API key should not be empty")
+	// }
+	// if apiKeyID == "" {
+	// 	logger.Fatal("API key ID should not be empty")
+	// }
+
+	//  ISSUE 4: RenameKey does not return the key ID
+	apiKeyID2, apiKey2, err := cloud.CreateKeyFromExistingKeyAuthorizations(ctx, newAPIKeyID)
+	if err != nil {
+		logger.Fatal(err)
+	}
+	if apiKey2 == "" {
+		logger.Fatal("API key 2 should not be empty")
+	}
+	if apiKeyID2 == "" {
+		logger.Fatal("API key ID 2 should not be empty")
+	}
+	fmt.Printf("API key id 2: %+v\n", apiKeyID2)
+
+	apiKeyID3, apiKeyName3, err := cloud.RenameKey(ctx, apiKeyID2, "mytestkey2newName")
+	if err != nil {
+		logger.Fatal(err)
+	}
+	if apiKeyName3 != "mytestkey2newName" {
+		logger.Fatal("API key 3 should be renamed")
+	}
+	fmt.Printf("API key id 3: %+v\n", apiKeyID3)
+
+}
diff --git a/static/include/examples/go.mod b/static/include/examples/go.mod
index 21ab063a30..400d67071f 100644
--- a/static/include/examples/go.mod
+++ b/static/include/examples/go.mod
@@ -6,6 +6,7 @@ require (
 	github.com/golang/geo v0.0.0-20230421003525-6adc56603217
 	go.viam.com/rdk v0.91.0
 	go.viam.com/utils v0.1.164
+	gorgonia.org/tensor v0.9.24
 )
 
 require (
@@ -21,6 +22,7 @@ require (
 	git.sr.ht/~sbinet/gg v0.6.0 // indirect
 	github.com/a8m/envsubst v1.4.2 // indirect
 	github.com/ajstarks/svgo v0.0.0-20211024235047-1546f124cd8b // indirect
+	github.com/apache/arrow/go/arrow v0.0.0-20201229220542-30ce2eb5d4dc // indirect
 	github.com/aybabtme/uniplot v0.0.0-20151203143629-039c559e5e7e // indirect
 	github.com/benbjohnson/clock v1.3.5 // indirect
 	github.com/bep/debounce v1.2.1 // indirect
@@ -31,6 +33,8 @@ require (
 	github.com/cenkalti/backoff v2.2.1+incompatible // indirect
 	github.com/cenkalti/backoff/v4 v4.3.0 // indirect
 	github.com/chenzhekl/goply v0.0.0-20190930133256-258c2381defd // indirect
+	github.com/chewxy/hm v1.0.0 // indirect
+	github.com/chewxy/math32 v1.0.8 // indirect
 	github.com/cloudwego/base64x v0.1.5 // indirect
 	github.com/davecgh/go-spew v1.1.1 // indirect
 	github.com/decred/dcrd/dcrec/secp256k1/v4 v4.2.0 // indirect
@@ -52,12 +56,14 @@ require (
 	github.com/go-logr/stdr v1.2.2 // indirect
 	github.com/go-viper/mapstructure/v2 v2.4.0 // indirect
 	github.com/goccy/go-json v0.10.2 // indirect
+	github.com/gogo/protobuf v1.3.2 // indirect
 	github.com/golang-jwt/jwt/v4 v4.5.2 // indirect
 	github.com/golang/freetype v0.0.0-20170609003504-e2365dfdc4a0 // indirect
 	github.com/golang/groupcache v0.0.0-20210331224755-41bb18bfe9da // indirect
 	github.com/golang/protobuf v1.5.4 // indirect
 	github.com/golang/snappy v0.0.4 // indirect
 	github.com/gonuts/binary v0.2.0 // indirect
+	github.com/google/flatbuffers v2.0.6+incompatible // indirect
 	github.com/google/go-cmp v0.7.0 // indirect
 	github.com/google/s2a-go v0.1.8 // indirect
 	github.com/google/uuid v1.6.0 // indirect
@@ -125,6 +131,7 @@ require (
 	github.com/xdg-go/scram v1.1.2 // indirect
 	github.com/xdg-go/stringprep v1.0.4 // indirect
 	github.com/xfmoulet/qoi v0.2.0 // indirect
+	github.com/xtgo/set v1.0.0 // indirect
 	github.com/youmark/pkcs8 v0.0.0-20240726163527-a2c0da244d78 // indirect
 	github.com/zhuyie/golzf v0.0.0-20161112031142-8387b0307ade // indirect
 	github.com/zitadel/oidc/v3 v3.37.0 // indirect
@@ -144,6 +151,7 @@ require (
 	go.uber.org/zap v1.27.0 // indirect
 	go.viam.com/api v0.1.475 // indirect
 	go.viam.com/test v1.2.4 // indirect
+	go4.org/unsafe/assume-no-moving-gc v0.0.0-20230525183740-e7c30c78aeb2 // indirect
 	golang.org/x/arch v0.19.0 // indirect
 	golang.org/x/crypto v0.41.0 // indirect
 	golang.org/x/exp v0.0.0-20241009180824-f66d83c29e7c // indirect
@@ -156,6 +164,7 @@ require (
 	golang.org/x/text v0.28.0 // indirect
 	golang.org/x/time v0.6.0 // indirect
 	golang.org/x/tools v0.35.0 // indirect
+	golang.org/x/xerrors v0.0.0-20220907171357-04be3eba64a2 // indirect
 	gonum.org/v1/gonum v0.16.0 // indirect
 	gonum.org/v1/plot v0.15.2 // indirect
 	google.golang.org/api v0.196.0 // indirect
@@ -166,5 +175,7 @@ require (
 	google.golang.org/protobuf v1.36.8 // indirect
 	gopkg.in/natefinch/lumberjack.v2 v2.2.1 // indirect
 	gopkg.in/yaml.v3 v3.0.1 // indirect
+	gorgonia.org/vecf32 v0.9.0 // indirect
+	gorgonia.org/vecf64 v0.9.0 // indirect
 	nhooyr.io/websocket v1.8.7 // indirect
 )
diff --git a/static/include/examples/go.sum b/static/include/examples/go.sum
index 185e91cedd..2567260a78 100644
--- a/static/include/examples/go.sum
+++ b/static/include/examples/go.sum
@@ -138,6 +138,7 @@ github.com/chenzhekl/goply v0.0.0-20190930133256-258c2381defd h1:S0onsSZ3RawTrm4
 github.com/chenzhekl/goply v0.0.0-20190930133256-258c2381defd/go.mod h1:P2dOeu3SNXtjA5VOH7tF0AnGm/eYrst9YA89b36c35I=
 github.com/chewxy/hm v1.0.0 h1:zy/TSv3LV2nD3dwUEQL2VhXeoXbb9QkpmdRAVUFiA6k=
 github.com/chewxy/hm v1.0.0/go.mod h1:qg9YI4q6Fkj/whwHR1D+bOGeF7SniIP40VweVepLjg0=
+github.com/chewxy/math32 v1.0.0/go.mod h1:Miac6hA1ohdDUTagnvJy/q+aNnEk16qWUdb8ZVhvCN0=
 github.com/chewxy/math32 v1.0.8 h1:fU5E4Ec4Z+5RtRAi3TovSxUjQPkgRh+HbP7tKB2OFbM=
 github.com/chewxy/math32 v1.0.8/go.mod h1:dOB2rcuFrCn6UHrze36WSLVPKtzPMRAQvBvUwkSsLqs=
 github.com/chzyer/logex v1.1.10/go.mod h1:+Ywpsq7O8HXn0nuIou7OrIPyXbp3wmkHB+jjWRnGsAI=
@@ -365,6 +366,7 @@ github.com/gonuts/binary v0.2.0 h1:caITwMWAoQWlL0RNvv2lTU/AHqAJlVuu6nZmNgfbKW4=
 github.com/gonuts/binary v0.2.0/go.mod h1:kM+CtBrCGDSKdv8WXTuCUsw+loiy8f/QEI8YCCC0M/E=
 github.com/google/btree v0.0.0-20180813153112-4030bb1f1f0c/go.mod h1:lNA+9X1NB3Zf8V7Ke586lFgjr2dZNuvo3lPJSGZ5JPQ=
 github.com/google/btree v1.0.0/go.mod h1:lNA+9X1NB3Zf8V7Ke586lFgjr2dZNuvo3lPJSGZ5JPQ=
+github.com/google/flatbuffers v1.11.0/go.mod h1:1AeVuKshWv4vARoZatz6mlQ0JxURH0Kv5+zNeJKJCa8=
 github.com/google/flatbuffers v2.0.6+incompatible h1:XHFReMv7nFFusa+CEokzWbzaYocKXI6C7hdU5Kgh9Lw=
 github.com/google/flatbuffers v2.0.6+incompatible/go.mod h1:1AeVuKshWv4vARoZatz6mlQ0JxURH0Kv5+zNeJKJCa8=
 github.com/google/go-cmp v0.2.0/go.mod h1:oXzfMopK8JAjlY9xF4vHSVASa0yLyX7SntLO5aqRK0M=
@@ -844,6 +846,7 @@ github.com/stretchr/objx v0.4.0/go.mod h1:YvHI0jy2hoMjB+UWwv71VJQ9isScKT/TqJzVSS
 github.com/stretchr/objx v0.5.0/go.mod h1:Yh+to48EsGEfYuaHDzXPcE3xhTkx73EhmCGUpEOglKo=
 github.com/stretchr/objx v0.5.2/go.mod h1:FRsXN1f5AsAjCGJKqEizvkpNtU+EGNCLh3NxZ/8L+MA=
 github.com/stretchr/testify v1.1.4/go.mod h1:a8OnRcib4nhh0OaRAV+Yts87kKdq0PP7pXfy6kDkUVs=
+github.com/stretchr/testify v1.2.0/go.mod h1:a8OnRcib4nhh0OaRAV+Yts87kKdq0PP7pXfy6kDkUVs=
 github.com/stretchr/testify v1.2.2/go.mod h1:a8OnRcib4nhh0OaRAV+Yts87kKdq0PP7pXfy6kDkUVs=
 github.com/stretchr/testify v1.3.0/go.mod h1:M5WIy9Dh21IEIfnGCwXGc5bZfKNJtfHm1UVUgZn+9EI=
 github.com/stretchr/testify v1.4.0/go.mod h1:j7eGeouHqKxXV5pUuKE4zz7dFj8WfuZ+81PSLYec5m4=
@@ -1090,6 +1093,7 @@ golang.org/x/net v0.0.0-20200520004742-59133d7f0dd7/go.mod h1:qpuaurCH72eLCgpAm/
 golang.org/x/net v0.0.0-20200602114024-627f9648deb9/go.mod h1:qpuaurCH72eLCgpAm/N6yyVIVM9cpaDIP3A8BGJEC5A=
 golang.org/x/net v0.0.0-20200625001655-4c5254603344/go.mod h1:/O7V0waA8r7cgGh81Ro3o1hOxt32SMVPicZroKQ2sZA=
 golang.org/x/net v0.0.0-20200822124328-c89045814202/go.mod h1:/O7V0waA8r7cgGh81Ro3o1hOxt32SMVPicZroKQ2sZA=
+golang.org/x/net v0.0.0-20200904194848-62affa334b73/go.mod h1:/O7V0waA8r7cgGh81Ro3o1hOxt32SMVPicZroKQ2sZA=
 golang.org/x/net v0.0.0-20201021035429-f5854403a974/go.mod h1:sp8m0HH+o8qH0wwXwYZr8TS3Oi6o0r6Gce1SSxlDquU=
 golang.org/x/net v0.0.0-20201110031124-69a78807bb2b/go.mod h1:sp8m0HH+o8qH0wwXwYZr8TS3Oi6o0r6Gce1SSxlDquU=
 golang.org/x/net v0.0.0-20201202161906-c7110b5ffcbb/go.mod h1:sp8m0HH+o8qH0wwXwYZr8TS3Oi6o0r6Gce1SSxlDquU=
@@ -1168,6 +1172,7 @@ golang.org/x/sys v0.0.0-20200519105757-fe76b779f299/go.mod h1:h1NjWce9XRLGQEsW7w
 golang.org/x/sys v0.0.0-20200602225109-6fdc65e7d980/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
 golang.org/x/sys v0.0.0-20200615200032-f1bc736245b1/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
 golang.org/x/sys v0.0.0-20200625212154-ddb9806d33ae/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
+golang.org/x/sys v0.0.0-20200909081042-eff7692f9009/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
 golang.org/x/sys v0.0.0-20200930185726-fdedc70b468f/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
 golang.org/x/sys v0.0.0-20201024232916-9f70ab9862d5/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
 golang.org/x/sys v0.0.0-20201119102817-f84b799fce68/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
@@ -1354,6 +1359,7 @@ google.golang.org/genproto v0.0.0-20200331122359-1ee6d9798940/go.mod h1:55QSHmfG
 google.golang.org/genproto v0.0.0-20200423170343-7949de9c1215/go.mod h1:55QSHmfGQM9UVYDPBsyGGes0y52j32PQ3BqQfXhyH3c=
 google.golang.org/genproto v0.0.0-20200513103714-09dca8ec2884/go.mod h1:55QSHmfGQM9UVYDPBsyGGes0y52j32PQ3BqQfXhyH3c=
 google.golang.org/genproto v0.0.0-20200526211855-cb27e3aa2013/go.mod h1:NbSheEEYHJ7i3ixzK3sjbqSGDJWnxyFXZblF3eUsNvo=
+google.golang.org/genproto v0.0.0-20200911024640-645f7a48b24f/go.mod h1:FWY/as6DDZQgahTzZj3fqbO1CbirC29ZNUFHwi0/+no=
 google.golang.org/genproto v0.0.0-20210126160654-44e461bb6506/go.mod h1:FWY/as6DDZQgahTzZj3fqbO1CbirC29ZNUFHwi0/+no=
 google.golang.org/genproto v0.0.0-20240903143218-8af14fe29dc1 h1:BulPr26Jqjnd4eYDVe+YvyR7Yc2vJGkO5/0UxD0/jZU=
 google.golang.org/genproto v0.0.0-20240903143218-8af14fe29dc1/go.mod h1:hL97c3SYopEHblzpxRL4lSs523++l8DYxGM1FQiYmb4=
@@ -1383,6 +1389,7 @@ google.golang.org/grpc v1.36.0/go.mod h1:qjiiYl8FncCW8feJPdyg3v6XW24KsRHe+dy9BAG
 google.golang.org/grpc v1.44.0/go.mod h1:k+4IHHFw41K8+bbowsex27ge2rCb65oeWqe4jJ590SU=
 google.golang.org/grpc v1.75.0 h1:+TW+dqTd2Biwe6KKfhE5JpiYIBWq865PhKGSXiivqt4=
 google.golang.org/grpc v1.75.0/go.mod h1:JtPAzKiq4v1xcAB2hydNlWI2RnF85XXcV0mhKXr2ecQ=
+google.golang.org/grpc/cmd/protoc-gen-go-grpc v0.0.0-20200910201057-6591123024b3/go.mod h1:6Kw0yEErY5E/yWrBtf03jp27GLLJujG4z/JK95pnjjw=
 google.golang.org/protobuf v0.0.0-20200109180630-ec00e32a8dfd/go.mod h1:DFci5gLYBciE7Vtevhsrf46CRTquxDuWsQurQQe4oz8=
 google.golang.org/protobuf v0.0.0-20200221191635-4d8936d0db64/go.mod h1:kwYJMbMJ01Woi6D6+Kah6886xMZcty6N08ah7+eCXa0=
 google.golang.org/protobuf v0.0.0-20200228230310-ab0ca4ff8a60/go.mod h1:cfTl7dwQJ+fmap5saPgwCLgHXTUD7jkjRqWcaiX5VyM=
diff --git a/static/include/examples/run-inference/run-inference.go b/static/include/examples/run-inference/run-inference.go
new file mode 100644
index 0000000000..22d65f794c
--- /dev/null
+++ b/static/include/examples/run-inference/run-inference.go
@@ -0,0 +1,189 @@
+// :snippet-start: run-inference
+package main
+
+import (
+	"bytes"
+	"context"
+	"fmt"
+	"image"
+	"image/jpeg"
+
+	"gorgonia.org/tensor"
+	// :remove-start:
+	"os"
+	// :remove-end:
+
+	"go.viam.com/rdk/logging"
+	"go.viam.com/rdk/ml"
+	"go.viam.com/rdk/robot/client"
+	"go.viam.com/rdk/components/camera"
+	"go.viam.com/rdk/services/mlmodel"
+	"go.viam.com/rdk/utils"
+	"go.viam.com/utils/rpc"
+)
+
+func main() {
+	apiKey := ""
+	apiKeyID := ""
+	machineAddress := ""
+	mlModelName := ""
+	cameraName := ""
+
+	// :remove-start:
+	apiKey = os.Getenv("VIAM_API_KEY")
+	apiKeyID = os.Getenv("VIAM_API_KEY_ID")
+	machineAddress = "auto-machine-main.pg5q3j3h95.viam.cloud"
+	cameraName = "camera-1"
+	mlModelName = "mlmodel-1"
+	// :remove-end:
+
+	logger := logging.NewDebugLogger("client")
+	ctx := context.Background()
+
+	machine, err := client.New(
+		context.Background(),
+		machineAddress,
+		logger,
+		client.WithDialOptions(rpc.WithEntityCredentials(
+			apiKeyID,
+			rpc.Credentials{
+				Type:    rpc.CredentialsTypeAPIKey,
+				Payload: apiKey,
+			})),
+	)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Capture image from camera
+	cam, err := camera.FromRobot(machine, cameraName)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	imageData, _, err := cam.Image(ctx, utils.MimeTypeJPEG, nil)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Decode the image data to get the actual image
+	img, err := jpeg.Decode(bytes.NewReader(imageData))
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Get ML model metadata to understand input requirements
+	mlModel, err := mlmodel.FromRobot(machine, mlModelName)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	metadata, err := mlModel.Metadata(ctx)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Get expected input shape and type from metadata
+	var expectedShape []int
+	var expectedDtype tensor.Dtype
+	var expectedName string
+
+	if len(metadata.Inputs) > 0 {
+		inputInfo := metadata.Inputs[0]
+		expectedShape = inputInfo.Shape
+		expectedName = inputInfo.Name
+
+		// Convert data type string to tensor.Dtype
+		switch inputInfo.DataType {
+		case "uint8":
+			expectedDtype = tensor.Uint8
+		case "float32":
+			expectedDtype = tensor.Float32
+		default:
+			expectedDtype = tensor.Float32 // Default to float32
+		}
+	} else {
+		logger.Fatal("No input info found in model metadata")
+	}
+
+	// Resize image to expected dimensions
+	bounds := img.Bounds()
+	width := bounds.Dx()
+	height := bounds.Dy()
+
+	// Extract expected dimensions
+	if len(expectedShape) != 4 || expectedShape[0] != 1 || expectedShape[3] != 3 {
+		logger.Fatal("Unexpected input shape format")
+	}
+
+	expectedHeight := expectedShape[1]
+	expectedWidth := expectedShape[2]
+
+	// Create a new image with the expected dimensions
+	resizedImg := image.NewRGBA(image.Rect(0, 0, expectedWidth, expectedHeight))
+
+	// Simple nearest neighbor resize
+	for y := 0; y < expectedHeight; y++ {
+		for x := 0; x < expectedWidth; x++ {
+			srcX := x * width / expectedWidth
+			srcY := y * height / expectedHeight
+			resizedImg.Set(x, y, img.At(srcX, srcY))
+		}
+	}
+
+	// Convert image to tensor data
+	tensorData := make([]float32, 1*expectedHeight*expectedWidth*3)
+	idx := 0
+
+	for y := 0; y < expectedHeight; y++ {
+		for x := 0; x < expectedWidth; x++ {
+			r, g, b, _ := resizedImg.At(x, y).RGBA()
+
+			// Convert from 16-bit to 8-bit and normalize to [0, 1] for float32
+			if expectedDtype == tensor.Float32 {
+				tensorData[idx] = float32(r>>8) / 255.0   // R
+				tensorData[idx+1] = float32(g>>8) / 255.0 // G
+				tensorData[idx+2] = float32(b>>8) / 255.0 // B
+			} else {
+				// For uint8, we need to create a uint8 slice
+				logger.Fatal("uint8 tensor creation not implemented in this example")
+			}
+			idx += 3
+		}
+	}
+
+	// Create input tensor
+	var inputTensor tensor.Tensor
+	if expectedDtype == tensor.Float32 {
+		inputTensor = tensor.New(
+			tensor.WithShape(1, expectedHeight, expectedWidth, 3),
+			tensor.WithBacking(tensorData),
+			tensor.Of(tensor.Float32),
+		)
+	} else {
+		logger.Fatal("Only float32 tensors are supported in this example")
+	}
+
+	// Convert tensor.Tensor to *tensor.Dense for ml.Tensors
+	denseTensor, ok := inputTensor.(*tensor.Dense)
+	if !ok {
+		logger.Fatal("Failed to convert inputTensor to *tensor.Dense")
+	}
+
+	inputTensors := ml.Tensors{
+		expectedName: denseTensor,
+	}
+
+	outputTensors, err := mlModel.Infer(ctx, inputTensors)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	fmt.Printf("Output tensors: %v\n", outputTensors)
+
+	err = machine.Close(ctx)
+	if err != nil {
+		logger.Fatal(err)
+	}
+}
+// :snippet-end:
\ No newline at end of file
diff --git a/static/include/examples/run-inference/run-inference.py b/static/include/examples/run-inference/run-inference.py
new file mode 100644
index 0000000000..b45202b6f1
--- /dev/null
+++ b/static/include/examples/run-inference/run-inference.py
@@ -0,0 +1,103 @@
+# :snippet-start: run-inference
+import asyncio
+# :remove-start:
+import os
+# :remove-end:
+import numpy as np
+
+from PIL import Image
+from viam.components.camera import Camera
+from viam.media.utils.pil import viam_to_pil_image
+from viam.robot.client import RobotClient
+from viam.services.mlmodel import MLModelClient
+
+# Configuration constants – replace with your actual values
+API_KEY = ""  # API key, find or create in your organization settings
+API_KEY_ID = ""  # API key ID, find or create in your organization settings
+MACHINE_ADDRESS = ""  # the address of the machine you want to capture images from
+ML_MODEL_NAME = ""  # the name of the ML model you want to use
+CAMERA_NAME = ""  # the name of the camera you want to capture images from
+
+# :remove-start:
+API_KEY = os.environ["VIAM_API_KEY"]
+API_KEY_ID = os.environ["VIAM_API_KEY_ID"]
+MACHINE_ADDRESS = "auto-machine-main.pg5q3j3h95.viam.cloud"
+CAMERA_NAME = "camera-1"
+ML_MODEL_NAME = "mlmodel-1"
+# :remove-end:
+
+async def connect_machine() -> RobotClient:
+    """Establish a connection to the robot using the robot address."""
+    machine_opts = RobotClient.Options.with_api_key(
+        api_key=API_KEY,
+        api_key_id=API_KEY_ID
+    )
+    return await RobotClient.at_address(MACHINE_ADDRESS, machine_opts)
+
+async def main() -> int:
+    machine = await connect_machine()
+
+    camera = Camera.from_robot(machine, CAMERA_NAME)
+    ml_model = MLModelClient.from_robot(machine, ML_MODEL_NAME)
+
+    # Get ML model metadata to understand input requirements
+    metadata = await ml_model.metadata()
+
+    # Capture image
+    image_frame = await camera.get_image()
+
+    # Convert ViamImage to PIL Image first
+    pil_image = viam_to_pil_image(image_frame)
+    # Convert PIL Image to numpy array
+    image_array = np.array(pil_image)
+
+    # Get expected input shape from metadata
+    expected_shape = list(metadata.input_info[0].shape)
+    expected_dtype = metadata.input_info[0].data_type
+    expected_name = metadata.input_info[0].name
+
+    if not expected_shape:
+        print("No input info found for 'image'")
+        return 1
+
+    if len(expected_shape) == 4 and expected_shape[0] == 1 and expected_shape[3] == 3:
+        expected_height = expected_shape[1]
+        expected_width = expected_shape[2]
+
+        # Resize to expected dimensions
+        if image_array.shape[:2] != (expected_height, expected_width):
+            pil_image_resized = pil_image.resize((expected_width, expected_height))
+            image_array = np.array(pil_image_resized)
+    else:
+        print(f"Unexpected input shape format.")
+        return 1
+
+    # Add batch dimension and ensure correct shape
+    image_data = np.expand_dims(image_array, axis=0)
+
+    # Ensure the data type matches expected type
+    if expected_dtype == "uint8":
+        image_data = image_data.astype(np.uint8)
+    elif expected_dtype == "float32":
+        # Convert to float32 and normalize to [0, 1] range
+        image_data = image_data.astype(np.float32) / 255.0
+    else:
+        # Default to float32 with normalization
+        image_data = image_data.astype(np.float32) / 255.0
+
+    # Create the input tensors dictionary
+    input_tensors = {
+        expected_name: image_data
+    }
+
+    output_tensors = await ml_model.infer(input_tensors)
+    print(f"Output tensors:")
+    for key, value in output_tensors.items():
+        print(f"{key}: shape={value.shape}, dtype={value.dtype}")
+
+    await machine.close()
+    return 0
+
+if __name__ == "__main__":
+    asyncio.run(main())
+# :snippet-end:
\ No newline at end of file
diff --git a/static/include/examples/run-inference/run-vision-service.go b/static/include/examples/run-inference/run-vision-service.go
new file mode 100644
index 0000000000..13473e6259
--- /dev/null
+++ b/static/include/examples/run-inference/run-vision-service.go
@@ -0,0 +1,97 @@
+// :snippet-start: run-vision-service
+package main
+
+import (
+	"context"
+	"fmt"
+	"image/jpeg"
+	"bytes"
+	// :remove-start:
+	"os"
+	// :remove-end:
+
+	"go.viam.com/rdk/logging"
+	"go.viam.com/rdk/robot/client"
+	"go.viam.com/rdk/services/vision"
+	"go.viam.com/rdk/components/camera"
+	"go.viam.com/rdk/utils"
+	"go.viam.com/utils/rpc"
+)
+
+func main() {
+	apiKey := ""
+	apiKeyID := ""
+	machineAddress := ""
+	classifierName := ""
+	cameraName := ""
+
+	// :remove-start:
+	apiKey = os.Getenv("VIAM_API_KEY")
+	apiKeyID = os.Getenv("VIAM_API_KEY_ID")
+	machineAddress = "auto-machine-main.pg5q3j3h95.viam.cloud"
+	cameraName = "camera-1"
+	classifierName = "classifier-1"
+	// :remove-end:
+
+	logger := logging.NewDebugLogger("client")
+	ctx := context.Background()
+
+	machine, err := client.New(
+		context.Background(),
+		machineAddress,
+		logger,
+		client.WithDialOptions(rpc.WithEntityCredentials(
+			apiKeyID,
+			rpc.Credentials{
+				Type:    rpc.CredentialsTypeAPIKey,
+				Payload: apiKey,
+			})),
+	)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Capture image from camera
+	cam, err := camera.FromRobot(machine, cameraName)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	imageData, _, err := cam.Image(ctx, utils.MimeTypeJPEG, nil)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Convert binary data to image.Image
+	img, err := jpeg.Decode(bytes.NewReader(imageData))
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// Get classifications using the image
+	classifier, err := vision.FromRobot(machine, classifierName)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	classifications, err := classifier.Classifications(ctx, img, 2, nil)
+	if err != nil {
+		logger.Fatal(err)
+	}
+
+	// :remove-start:
+	if len(classifications) == 0 {
+		fmt.Println("No tags found")
+		return
+	} else {
+		for _, classification := range classifications {
+			fmt.Printf("Found tag: %s\n", classification.Label())
+		}
+	}
+	// :remove-end:
+	err = machine.Close(ctx)
+	if err != nil {
+		logger.Fatal(err)
+	}
+}
+// :snippet-end:
\ No newline at end of file
diff --git a/static/include/examples/run-inference/run-vision-service.py b/static/include/examples/run-inference/run-vision-service.py
new file mode 100644
index 0000000000..47794a3a44
--- /dev/null
+++ b/static/include/examples/run-inference/run-vision-service.py
@@ -0,0 +1,63 @@
+# :snippet-start: run-vision-service
+import asyncio
+# :remove-start:
+import os
+# :remove-end:
+import numpy as np
+
+from PIL import Image
+from viam.components.camera import Camera
+from viam.media.utils.pil import viam_to_pil_image
+from viam.robot.client import RobotClient
+from viam.services.vision import VisionClient
+
+# Configuration constants – replace with your actual values
+API_KEY = ""  # API key, find or create in your organization settings
+API_KEY_ID = ""  # API key ID, find or create in your organization settings
+MACHINE_ADDRESS = ""  # the address of the machine you want to capture images from
+CLASSIFIER_NAME = ""  # the name of the classifier you want to use
+CAMERA_NAME = ""  # the name of the camera you want to capture images from
+
+# :remove-start:
+API_KEY = os.environ["VIAM_API_KEY"]
+API_KEY_ID = os.environ["VIAM_API_KEY_ID"]
+MACHINE_ADDRESS = "auto-machine-main.pg5q3j3h95.viam.cloud"
+CAMERA_NAME = "camera-1"
+CLASSIFIER_NAME = "classifier-1"
+# :remove-end:
+
+async def connect_machine() -> RobotClient:
+    """Establish a connection to the robot using the robot address."""
+    machine_opts = RobotClient.Options.with_api_key(
+        api_key=API_KEY,
+        api_key_id=API_KEY_ID
+    )
+    return await RobotClient.at_address(MACHINE_ADDRESS, machine_opts)
+
+async def main() -> int:
+    machine = await connect_machine()
+
+    camera = Camera.from_robot(machine, CAMERA_NAME)
+    classifier = VisionClient.from_robot(machine, CLASSIFIER_NAME)
+
+    # Capture image
+    image_frame = await camera.get_image(mime_type="image/jpeg")
+
+    # Get tags using the ViamImage (not the PIL image)
+    tags = await classifier.get_classifications(
+        image=image_frame, image_format="image/jpeg", count=2)
+
+    # :remove-start:
+    if not len(tags):
+        print("No tags found")
+        return 1
+    else:
+        for tag in tags:
+            print(f"Found tag: {tag.class_name}")
+    # :remove-end:
+    await machine.close()
+    return 0
+
+if __name__ == "__main__":
+    asyncio.run(main())
+# :snippet-end:
\ No newline at end of file
diff --git a/static/include/examples/run-inference/run-vision-service.ts b/static/include/examples/run-inference/run-vision-service.ts
new file mode 100644
index 0000000000..358426226d
--- /dev/null
+++ b/static/include/examples/run-inference/run-vision-service.ts
@@ -0,0 +1,95 @@
+// :snippet-start: run-vision-service
+import { createRobotClient, RobotClient, VisionClient, CameraClient } from "@viamrobotics/sdk";
+// :remove-start:
+import pkg from "@koush/wrtc";
+const {
+    RTCPeerConnection,
+    RTCSessionDescription,
+    RTCIceCandidate,
+    MediaStream,
+    MediaStreamTrack
+} = pkg;
+
+// Set up global WebRTC classes
+global.RTCPeerConnection = RTCPeerConnection;
+global.RTCSessionDescription = RTCSessionDescription;
+global.RTCIceCandidate = RTCIceCandidate;
+global.MediaStream = MediaStream;
+global.MediaStreamTrack = MediaStreamTrack;
+// :remove-end:
+
+// Configuration constants – replace with your actual values
+let API_KEY = "";  // API key, find or create in your organization settings
+let API_KEY_ID = "";  // API key ID, find or create in your organization settings
+let MACHINE_ADDRESS = "";  // the address of the machine you want to capture images from
+let CLASSIFIER_NAME = "";  // the name of the classifier you want to use
+let CAMERA_NAME = "";  // the name of the camera you want to capture images from
+// :remove-start:
+API_KEY = process.env.VIAM_API_KEY || "";
+API_KEY_ID = process.env.VIAM_API_KEY_ID || "";
+MACHINE_ADDRESS = "auto-machine-main.pg5q3j3h95.viam.cloud";
+CAMERA_NAME = "camera-1";
+CLASSIFIER_NAME = "classifier-1";
+// :remove-end:
+
+async function connectMachine(): Promise<RobotClient> {
+    // Establish a connection to the robot using the machine address
+    return await createRobotClient({
+        host: MACHINE_ADDRESS,
+        credentials: {
+          type: 'api-key',
+          payload: API_KEY,
+          authEntity: API_KEY_ID,
+        },
+        signalingAddress: 'https://app.viam.com:443',
+      });
+}
+
+async function main(): Promise<number> {
+    const machine = await connectMachine();
+    const camera = new CameraClient(machine, CAMERA_NAME);
+    const classifier = new VisionClient(machine, CLASSIFIER_NAME);
+
+    // Capture image
+    const imageFrame = await camera.getImage();
+
+    // Get tags using the image
+    const tags = await classifier.getClassifications(
+        imageFrame,
+        imageFrame.width ?? 0,
+        imageFrame.height ?? 0,
+        imageFrame.mimeType ?? "",
+        2
+    );
+
+    // :remove-start:
+    if (tags.length === 0) {
+        console.log("No tags found");
+        return 1;
+    } else {
+        for (const tag of tags) {
+            console.log(`Found tag: ${tag.className}`);
+        }
+    }
+
+    // Force exit after cleanup
+    process.exit(0);
+    // :remove-end:
+    return 0;
+}
+
+// :remove-start:
+// Run the script with timeout
+const timeout = setTimeout(() => {
+    console.log("Script timed out, forcing exit");
+    process.exit(1);
+}, 20000); // 10 second timeout
+// :remove-end:
+main().catch((error) => {
+    // :remove-start:
+    clearTimeout(timeout);
+    // :remove-end:
+    console.error("Script failed:", error);
+    process.exit(1);
+});
+// :snippet-end:
\ No newline at end of file

From 582c9cc1463a6951f94677b1fb6bbff05d4c9966 Mon Sep 17 00:00:00 2001
From: Naomi Pentrel <5212232+npentrel@users.noreply.github.com>
Date: Fri, 12 Sep 2025 14:21:31 +0200
Subject: [PATCH 2/3] Fix links

---
 docs/data-ai/ai/run-inference.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/docs/data-ai/ai/run-inference.md b/docs/data-ai/ai/run-inference.md
index 0bc9ab9483..c0e13020e0 100644
--- a/docs/data-ai/ai/run-inference.md
+++ b/docs/data-ai/ai/run-inference.md
@@ -103,21 +103,21 @@ To use a vision service:
 {{% /tab %}}
 {{% tab name="Python" %}}
 
-The following code passes an image from a camera to a vision service and uses the [`GetClassifications`](/dev/reference/apis/services/vision/#GetClassifications) method:
+The following code passes an image from a camera to a vision service and uses the [`GetClassifications`](/dev/reference/apis/services/vision/#getclassifications) method:
 
 {{< read-code-snippet file="/static/include/examples-generated/run-vision-service.snippet.run-vision-service.py" lang="py" class="line-numbers linkable-line-numbers" data-line="36-37" >}}
 
 {{% /tab %}}
 {{% tab name="Go" %}}
 
-The following code passes an image from a camera to a vision service and uses the [`GetClassifications`](/dev/reference/apis/services/vision/#GetClassifications) method:
+The following code passes an image from a camera to a vision service and uses the [`GetClassifications`](/dev/reference/apis/services/vision/#getclassifications) method:
 
 {{< read-code-snippet file="/static/include/examples-generated/run-vision-service.snippet.run-vision-service.go" lang="go" class="line-numbers linkable-line-numbers" data-line="66-69" >}}
 
 {{% /tab %}}
 {{% tab name="TypeScript" %}}
 
-The following code passes an image from a camera to a vision service and uses the [`GetClassifications`](/dev/reference/apis/services/vision/#GetClassifications) method:
+The following code passes an image from a camera to a vision service and uses the [`GetClassifications`](/dev/reference/apis/services/vision/#getclassifications) method:
 
 {{< read-code-snippet file="/static/include/examples-generated/run-vision-service.snippet.run-vision-service.ts" lang="ts" class="line-numbers linkable-line-numbers" data-line="32-38" >}}
 

From 4b58fa0c5ab3cec06fc8f2be0061f53ad228894f Mon Sep 17 00:00:00 2001
From: Naomi Pentrel <5212232+npentrel@users.noreply.github.com>
Date: Fri, 19 Sep 2025 08:06:07 +0200
Subject: [PATCH 3/3] Improve

---
 docs/data-ai/ai/run-inference.md | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/docs/data-ai/ai/run-inference.md b/docs/data-ai/ai/run-inference.md
index c0e13020e0..a5e9a047a8 100644
--- a/docs/data-ai/ai/run-inference.md
+++ b/docs/data-ai/ai/run-inference.md
@@ -60,7 +60,8 @@ The following code passes an image to an ML model service, and uses the [`Infer`
 
 ### Using a vision service
 
-Vision services apply an ML model to a stream of images from a camera to:
+There are a range of vision services that interpret images.
+Some vision services apply an ML model to a stream of images from a camera to:
 
 - detect objects (using bounding boxes)
 - classify (using tags)
@@ -70,6 +71,7 @@ To use a vision service:
 1. Navigate to your machine's **CONFIGURE** page.
 1. Click the **+** icon next to your main machine part and select **Component or service**.
 1. Select a vision service.
+   For more information on the vision service, see its entry in the [Viam registry](https://app.viam.com/registry).
 1. Configure your vision service.
    If your vision service does not include an ML model, you need to [deploy an ML model to your machine](/data-ai/ai/deploy/) and select it when configuring your vision service.