Test

.github/workflows/run-htmltest.yml

@@ -5,10 +5,11 @@
 # https://github.com/wjdp/htmltest
 #
 name: run-htmltest-external
-on:
-  schedule:
-    # 10am UTC on weekdays
-    - cron: '0 10 * * 1,2,3,4,5'
+on: pull_request
+# on:
+  # schedule:
+  #   # 10am UTC on weekdays
+  #   - cron: '0 10 * * 1,2,3,4,5'
 jobs:
   htmltest:
     runs-on: ubuntu-large
@@ -60,13 +61,6 @@ jobs:
           issuetype: Bug
           summary: Broken link detected
           description: For more info see https://github.com/viamrobotics/docs/actions/runs/{{ env.GITHUB_RUN_ID }}.
-      - name: Log created issue
+      - name: Log created Jira issue
+        if: failure()
         run: echo "Issue ${{ steps.create.outputs.issue }} was created"
-
-            - name: Create issue about failure
-              if: failure()
-              uses: JasonEtco/[email protected]
-              env:
-                GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-              with:
-                filename: .github/failed-action-issue-template.md

docs/tutorials/projects/guardian.md

@@ -245,7 +245,7 @@ Then test the components on the [machine's Control tab](/fleet/machines/#control
 ## Detect persons and pets
 
 For the guardian to be able to detect living beings, you will use a machine learning model from the Viam registry called [`EfficientDet-COCO`](https://app.viam.com/ml-model/viam-labs/EfficientDet-COCO).
-The model can detect a variety of things which you can see in <file>[labels.txt](https://github.com/viam-labs/devrel-demos/raw/main/Light%20up%20bot/labels.txt)</file> file.
+The model can detect a variety of things which you can see in <file>[labels.txt](https://githubsss.com/viam-labs/devrel-demos/raw/main/Light%20up%20bot/labels.txt)</file> file.
 
 You can also [train your own custom model](/ml/train-model/) based on images from your robot but the provided Machine Learning model is a good one to start with.