Data Analyzer

Update sensors using AI

Image to sensor

Introduction

data_analyzer updates a sensor based in image input. (Added in v1.3.1)

For example you could create a sensor to monitor how many cars are parked, monitor your 3D print quality or the license plate of the car in your driveway.

Use helpers to create virtual sensors!

Supported sensors

• number and input_number

• text and input_text

• select and input_select

• input_boolean

Action Reference

Action Reference

service: llmvision.data_analyzer
data:
  provider: 01J99F4T99PA1XGQ4CTQS3CP8H  # Select in UI dropdown
  model: gpt-4o-mini
  message: What is the car's license plate?
  sensor_entity: input_text.last_license_plate
  image_entity: 
    - image.garage_car
  image_file: |-
    /config/www/weather_chart.jpg
  max_tokens: 5 # A low value is recommended
  target_width: 1280
  temperature: 0.1 # Recommeded for accuracy
  include_filename: true # Include image/camera name in request

The provider id will not be the same for you. Switch to UI mode and select one of your configurations. If you don't see any, you need to set up at least one provider!

For all available models see: Choosing the right model

Paramter Reference

Parameter	Required	Description	Default
provider	Yes	The AI provider configuration
model	No	Model used for processing the image(s).
message	Yes	The prompt to send along with the image(s).
use_memory	No	Use information stored in memory to provide additional context. Memory must be set up.	false
sensor_entity	Yes	The sensor to update
image_file	No*	The path to the image file(s). Each path must be on a new line.
image_entity	No*	An alternative to image_file for providing image input.
include_filename	Yes	Whether to include the filename in the request.	false
target_width	No	Width to downscale the image to before encoding.	1280
max_tokens	Yes	The maximum number of response tokens to generate.	100
temperature	Yes	Randomness of the output.	0.5