1.2.1

• Added Dark Mode

1.1.2

• Fix issue where event deletion task was consuming large amounts of memory

1.1.1

https://kleypot.com/last-watch-ai-v1-1-released/

This is the first stable release of version 1.x, which contains a ton of new features and improvements over the previous 0.x versions. Please refer to the release notes for the last few beta releases to see what has changed.

• 1.1.0-beta release
• 1.0.0-beta release
• 0.10.0-beta release

If you are upgrading from an older version (before 1.0.0), please refer to the release notes for v1.0.0 for upgrade instructions. There are some breaking changes to be aware of. TL;DR -- the .env file has grown a lot and you should start fresh using the provided example file.

1.1.0-beta

• Add image thumbnails to detection events page
• Streamline docker-compose file and example configs
• Update documentation
• Improve image compression
• Enabled automatic retries for automations
• Improved error logging for automations

1.0.0-beta

Last Watch AI 1.0.0

This is a major release which may contain breaking changes. Please check the special instructions below if you are upgrading from a 0.* release.

Summary of Changes

1.0.0 is focused mainly on performance and stability. There are breaking changes to the file watcher and the webhook.

In previous versions, the watch folder was mounted into the web application. The watcher scanned for changes and notified the main application when a new file was available, and the web app would read the file directly from the mounted volume. Many users experienced performance issues as the size of the watch folder increased over time, with the file watcher process often using up a ton of CPU to monitor the folder for changes.

In 1.0.0, the watch folder is no longer mounted into the web application. Instead of just notifying the existence of a new file, the watcher now posts the full image data to the webhook, and the web server saves its own copy of the image file. After posting the image, the watcher will delete the image from the watch folder. This keeps the watch folder clean, which has a dramatic impact on performance. The web server also compresses its copies of the images to save space (optional), and it automatically deletes old images according to your data retention period.

1.0.0 also includes the performance improvements for the worker queue originally introduced in version 0.10.0. Instead of processing every job with the same priority, now the webhooks, AI detection, automations, and image compression jobs are sent into either high, medium, or low priority queues to make sure important jobs are processed first. Automations can now be set up as "High Priority" if you need real-time performance (e.g. if you want to trigger a recording in Blue Iris as soon as an object is detected). Non-priority automations go into the low priority queue by default.

Upgrading from previous release

If you prefer to install from the zipped releases, follow the upgrade guide here

If you are upgrading from source, there are a few extra steps to be aware of. In addition to the normal upgrade steps, there are some new steps for updating your .env file and removing the old mounted directory.

1. Stop the containers first, as usual

cd /path/to/last-watch-ai
sudo docker-compose down

2. Pull the latest code from master, or a release tag

git checkout master
git pull

3. Update your .env file. There are several new variables added, so back up your old file and replace it with the new one. Edit the new file to apply your settings.

cp .env .env.old
cp .env.example .env
nano .env

4. Rebuild the code, as usual

sudo docker-compose run --rm composer install --optimize-autoloader --no-dev &&
sudo docker-compose run --rm artisan route:cache &&
sudo docker-compose run --rm artisan migrate --force &&
sudo docker-compose run --rm npm install --verbose &&
sudo docker-compose run --rm npm rebuild &&
sudo docker-compose run --rm npm run prod --verbose

5. Important: remove the events folder before bringing up the containers. This is the old mount point for the watch folder, which will be replaced with a new public images folder. If you don't delete this, the web server will throw permissions errors.

sudo rm -rf src/storage/app/public/events/

6. Bring up the containers

sudo docker-compose up -d --build site

7. Recommended: clean up your watch folder by deleting all of the images or moving them into another folder. Keeping the watch folder clean will help with performance.

Breaking Changes

Once you get the containers back up and running, there is one breaking change to be aware of. Now that the web server owns the image files, all of your previous events will be missing their respective images. In the Detection Events page, you will see that all of your old events no longer show an image name.

Testing

Version 1.0.0 has been tested and confirmed working in Debian Linux, Windows 10, Windows Server 2019.

0.10.1-beta

• Fixes an issue in 0.10.0 where webhook jobs were not queued properly

0.10.0-beta

• Implement high and low priority queues for automations. High priority automations will be run ahead of other queued jobs. This is useful for minimizing latency in automations. For example, if you trigger video recording, you would want the trigger to happen as soon as possible.

• Add ability to delete automations. Deleting an automation will automatically remove all of its subscribers.

0.9.0

Added new env variables:

• APP_DEBUG - set to true to expose application errors in the web UI
• DEEPSTACK_BASE_URL - change deepstack endpoint when hosting deepstack separately from Last Watch

Detection Event UI improvements:

• Added a badge to show the total number of AI predictions from deepstack
• Clicking the aforementioned badge will highlight the predictions in the image preview pane
• When predictions are highlighted, buttons appear below the image preview pane to solo each prediction

0.8.0

• Add support for Mqtt automations
• Create substitution variables for web request automations
• Add API method to temporarily disable a profile for a number of minutes

0.8.0-alpha

• Add support for Mqtt automations
• Create substitution variables for web request automations