DOCS-1070: Pt6: Update builder UI instructions (#1877)

docs/components/power-sensor/fake.md

@@ -18,7 +18,7 @@ Configure a `fake` power sensor to integrate into your robot:
 {{% tab name="Config Builder" %}}
 
 Navigate to the **Config** tab of your robot's page in [the Viam app](https://app.viam.com).
-Click on the **Components** subtab and navigate to the **Create component** menu.
+Click on the **Components** subtab and click **Create component** in the lower-left corner.
 Select the type `power_sensor`, then select the `fake` model.
 Name your sensor, and click **Create**.
 

docs/components/power-sensor/ina219.md

@@ -17,7 +17,7 @@ Configure an `INA219` power sensor to integrate into your robot:
 {{% tab name="Config Builder" %}}
 
 Navigate to the **Config** tab of your robot's page in [the Viam app](https://app.viam.com).
-Click on the **Components** subtab and navigate to the **Create component** menu.
+Click on the **Components** subtab and click **Create component** in the lower-left corner.
 Select the type `power_sensor`, then select the `ina219` model.
 Name your sensor, and click **Create**.
 

docs/components/power-sensor/ina226.md

@@ -15,7 +15,7 @@ Configure an `INA226` power sensor to integrate into your robot:
 {{% tab name="Config Builder" %}}
 
 Navigate to the **Config** tab of your robot's page in [the Viam app](https://app.viam.com).
-Click on the **Components** subtab and navigate to the **Create component** menu.
+Click on the **Components** subtab and click **Create component** in the lower-left corner.
 Select the type `power_sensor`, then select the `ina226` model.
 Name your sensor, and click **Create**.
 

docs/components/power-sensor/renogy.md

@@ -16,7 +16,7 @@ Configure a `renogy` sensor to integrate a [Renogy battery temperature sensor](h
 {{% tab name="Config Builder" %}}
 
 Navigate to the **Config** tab of your robot's page in [the Viam app](https://app.viam.com).
-Click on the **Components** subtab and navigate to the **Create component** menu.
+Click on the **Components** subtab and click **Create component** in the lower-left corner.
 Select the type `power_sensor`, then select the `renogy` model.
 Name your sensor, and click **Create**.
 

docs/extend/modular-resources/configure.md

@@ -59,7 +59,7 @@ You can also find [the module itself](#configure-a-module-from-the-viam-registry
 
 If the module requires you to configure specific **Attributes**, click the **URL** link in the [module's configuration pane](#configure-a-module-from-the-viam-registry) to view the specific attribute requirements on the module's GitHub page.
 
-To delete a module added from the Viam registry, click the trash can icon in the upper-right corner of the module configuration pane in the **Components** tab.
+To delete a module added from the Viam registry, click the trash can icon in the upper-right corner of the module configuration pane in the **Modules** subtab of the robot's **Config** tab.
 Deleting a module _does not_ delete any configured modular resources it provides.
 
 ### Add a modular service from the Viam registry

docs/tutorials/get-started/lazy-susan.md

@@ -363,7 +363,7 @@ Connect the wood to your motor and decorate it as you wish to make your Lazy Sus
 This is not where your Lazy Susan project has to end - here are some ideas for adding more components to this project:
 
 - An [input controller component](/components/input-controller/) so you can turn and stop the Lazy Susan with a gamepad.
-- A [camera component](/components/camera/) and a [ML model](/services/ml/) that recognizes your friends' faces and stops the Lazy Susan precisely where they can reach their favorite food, or takes their photo as it rotates, so you all can have candid memories.
+- A [camera component](/components/camera/) and an [ML model](/services/ml/) that recognizes your friends' faces and stops the Lazy Susan precisely where they can reach their favorite food, or takes their photo as it rotates, so you all can have candid memories.
 - A [sensor component](/components/sensor/), so your Lazy Susan only spins when it detects movement around it.
 
 Or you can head over to our [Tutorials](/tutorials/) page and try one of our other tutorials to continue building robots.

docs/tutorials/projects/pet-treat-dispenser.md

@@ -292,26 +292,30 @@ Go ahead and select all the tags you would like to include in your model and cli
 
 ### Deploy your model to your robot
 
-Once the model has finished training, deploy it by adding a [ML model service](/services/ml/#tabset-servicesml-1-1):
-
-1. To deploy a new model onto your robot, navigate to the robot page on the Viam app, and in the **Config** tab, select **Services**.
-1. Create a new service, select **ML Model** as the **Type**, and name it `puppymodel`.
-   Select `tflite_cpu` as the **Model**.
+Once the model has finished training, deploy it by adding an [ML model service](/services/ml/#tabset-servicesml-1-1) to your robot:
 
+1. Navigate to the robot page on the Viam app.
+   Click to the **Config** tab, then select the **Services** subtab.
+1. Click **Create service** in the lower-left corner.
+1. Select `ML Model` as the type, and select `TFLite CPU` as the model.
+1. Enter `puppymodel` as the name, then click **Create**.
 1. To configure your service and deploy a model onto your robot, select **Deploy Model On Robot** for the **Deployment** field.
 1. Select your trained model (`puppymodel`) as your desired **Model**.
 
 ### Use the vision service to detect your pet
 
 To detect your pet with your machine learning model, you need to add a [vision service](/services/vision/) that uses the model and a [transform camera](/components/camera/transform/) that applies the vision service to an existing camera stream and specifies a confidence threshold:
 
-1. Create a new **Service** and select **Vision**, and `mlmodel` as the Type.
+1. From the **Services** subtab, click **Create service** in the lower-left corner.
+1. Select `Vision` as the type and `ML Model` as the model.
+1. Enter a name for your ML model service and click **Create**.
 1. Select the model you previously created in the drop down menu.
 
    ![The vision service panel with the puppymodel selected.](/tutorials/pet-treat-dispenser/app-service-vision.png)
 
-1. Navigate to the **Components** tab and scroll to the **Create Component** menu.
-1. Create a [transform camera](/components/camera/transform/) with the name `classifier_cam`, the type `camera` and the model `transform`.
+1. Navigate to the **Components** subtab and click **Create component** in the lower-left corner.
+1. Create a [transform camera](/components/camera/transform/) by selecting type `camera` and model `transform`.
+1. Enter `classifier_cam` as the name for your camera, then click **Create**.
 1. Replace the JSON attributes with the following object which specifies the camera source for the transform cam and also defines a pipeline that adds the `classifier` you created.
 
    ```js
@@ -338,7 +342,7 @@ To detect your pet with your machine learning model, you need to add a [vision s
 With your robot configured, you can now add a program to your robot that controls the pet feeder when executed, using the [Viam SDK](/program/apis/) in the language of your choice.
 This tutorial uses Python.
 
-### Set up your python environment
+### Set up your Python environment
 
 Open your terminal and `ssh` into your Pi.
 Run the following command to install the Python package manager onto your Pi:
@@ -549,7 +553,7 @@ Take your smart pet feeder to the next level!
 You could try one of the following:
 
 - Add speakers and record your voice so that the pet feeder can play a message to your pet each time it dispenses a treat.
-- Train a [ML model](/services/ml/) to recognize when your pet performs a trick, and withhold the treat until a specific trick is detected.
+- Train an [ML model](/services/ml/) to recognize when your pet performs a trick, and withhold the treat until a specific trick is detected.
 - Add a button that your pet must press to access the treat.
   If you add several treat types, you might include a different color button for each treat type, allowing your pet to choose.
 - If you have multiple pets, you could configure different treats for each pet by training the ML model on each pet, and dispensing different treats depending on the pet recognized.

docs/tutorials/services/try-viam-color-detection.md

@@ -123,15 +123,12 @@ Note that the detector does not detect black, perfect greys (greys where the red
 Viam [camera](/components/camera/) components can be [physical](/components/camera/webcam/) like the one already configured on the rover, or virtual.
 A virtual camera transforms the output from a physical camera.
 
-To view output from the color detector overlaid on images from a physical camera, you need to configure a [transform camera](/components/camera/transform/).
+To view output from the color detector overlaid on images from a physical camera, you need to configure a [transform camera](/components/camera/transform/):
 
-Navigate to the **Components** tab in the Viam app and scroll to the **Create Component** section.
-To create a [transform camera](/components/camera/transform/):
-
-1. Enter a name for **Name**, for example `detectionCam`.
-2. Select `camera` as the **Type**.
-3. Select `transform` as the **Model**.
-4. Click **Create Component**.
+1. Click **Create component** in the lower-left corner of the **Components** subtab.
+2. Select `camera` as the type.
+3. Select `transform` as the model.
+4. Name your transform camera (for example, `detectionCam`) and click **Create**.
 
 ![The Viam app showing the Create Component panel populated with a camera component. The name is detectionCam, the type is camera, and the model is transform.](/tutorials/try-viam-color-detection/create-component-pane.png)