Integrate a model for language analysis to interpret people's mood. To this end, ChatGPT can analyze text/video to identify feelings in terms of emotions such as joy, sadness, anger, fear, surprise, disgust (as alternative could identify polarity such as positive, negative, neutral), as well as calculate the magnitude of emotions (by assigning a numerical value to them). In this way, the result of Sentiment Analysis can be used together with other integrations to:
- Suggest activities based on mood
- Suggest music playlists
- Adjust the tone of Assist's responses
- Suggest the most appropriate recipe (e.g., comfort food vs. processed food)
- Choose the type of TV program to watch
- Combine different inputs together, e.g. with wearable devices for heart rate monitoring or hours slept at night for cross-analysis
- Create emotional profiles and identify recurring patterns
The model is composed by:
- sensors
- automation
- lovelace card
In order to create the sensors, you would need:
- OpenAI API key
- Variable integration (refer to: https://github.com/snarky-snark/home-assistant-variables)
The model analyzes three different data inputs:
- Text
- Video, and you would need:
- LLM Vision integration
- A configured camera
- Conversation, and you would need:
- OpenAI Conversation integration
- A configured Assist instance