kuzco-sentiment
Analyze the sentiment or mood conveyed by an image using a local vision language
model, exposed as an ellmer tool by the kuzco R
package.
When to use
The user wants the emotional tone of an image: cheerful, somber, threatening,
calm. Useful for content moderation triage, marketing asset selection, or photo
curation. For factual descriptions of image contents, use kuzco-classification.
Setup
library(kuzco)
library(ellmer)
chat <- chat_ollama(model = "qwen2.5vl")
chat$register_tool(tool_llm_image_sentiment())
Tool arguments (LLM-controlled)
image (required): local file path to a jpeg, jpg, or png image.
additional_prompt (optional): extra instructions, e.g. "consider cultural context".
language (optional): output language, e.g. "English".
Result
Compact JSON text with image_sentiment, image_score, sentiment_description,
and image_keywords. Lead with the sentiment label and score, then the description.
Present sentiment as the model's reading, not as ground truth.
Example
User: "What mood does img/sunset.jpg convey?"
- Call
kuzco_image_sentiment with image = "img/sunset.jpg".
- Report the sentiment, score, and description.