llm-sentiment.md
In mall: Run Multiple Large Language Model Predictions Against a Table, or Vectors

Sentiment translates expected Spark SQL

Code
  llm_sentiment(df_spark, x)
Output
  <SQL>
  SELECT `df`.*, ai_analyze_sentiment(`x`) AS `.sentiment`
  FROM `df`

Sentiment on Ollama works

Code
  llm_vec_sentiment(vec_reviews)
Output
  [1] "positive" "negative" "neutral"

Code
  llm_vec_sentiment(vec_reviews, options = c("positive", "negative"))
Output
  [1] "positive" "negative" "negative"

Code
  llm_vec_sentiment(vec_reviews, options = c("positive", "negative"),
  additional_prompt = "Consider someone not sure as a positive comment.")
Output
  [1] "positive" "negative" "positive"

Code
  llm_sentiment(reviews, review)
Output
                                                                                review
  1                 This has been the best TV I've ever used. Great screen, and sound.
  2          I regret buying this laptop. It is too slow and the keyboard is too noisy
  3 Not sure how to feel about my new washing machine. Great color, but hard to figure
    .sentiment
  1   positive
  2   negative
  3    neutral

Code
  llm_sentiment(reviews, review, pred_name = "new")
Output
                                                                                review
  1                 This has been the best TV I've ever used. Great screen, and sound.
  2          I regret buying this laptop. It is too slow and the keyboard is too noisy
  3 Not sure how to feel about my new washing machine. Great color, but hard to figure
         new
  1 positive
  2 negative
  3  neutral