multilingual-support

    library(kuzco)
    test_img <- file.path(system.file(package = "kuzco"), "img/test_img.jpg")

### multilingual support

Some models are capable of returning outputs in multiple languages. As a result, it became necessary to include a language specification to ensure certain models responded in English. Once this step was in place, switching the output language for specific computer vision tasks became straightforward & easy to implement.

#### English Results

    llm_image_classification(
      llm_model = "qwen2.5vl",
      image = test_img,
      backend = 'ellmer',
      provider = 'ollama',
      language = 'English'
      )

    #>   image_classification primary_object secondary_object
    #> 1  Portrait of a puppy          puppy
    #>                                                                                                          image_description
    #> 1 A close-up portrait of a puppy with black and white fur is the main subject, with a red plaid blanket in the background.
    #>                                              image_colors image_proba_names
    #> 1 ["#000000", "#FFFFFF", "#FF0000", "#0000FF", "#A52A2A"]
    #>              image_proba_values
    #> 1 [0.6, 0.15, 0.08, 0.07, 0.02]

#### Spanish Results

    llm_image_classification(
      llm_model = "qwen2.5vl",
      image = test_img,
      backend = 'ellmer',
      provider = 'ollama',
      language = 'Spanish'
      )

    #>   image_classification primary_object secondary_object
    #> 1              perrito        perrito            pañal
    #>                                                                                                                                                                                   image_description
    #> 1 Un adorable perrito de color negro y blanco está echado en la cama. El perrito está mirando directamente a la cámara. Se ven texturas sutiles en el pelaje y un fondo de colcha de cuadros rojos.
    #>                                    image_colors image_proba_names
    #> 1 [#000000, #FFFFFF, #D60000, #FF0000, #0000FF]           perrito
    #>       image_proba_values
    #> 1 :[0.8,0.0,0.0,0.0,0.0]

#### German Results

    llm_image_classification(
      llm_model = "qwen2.5vl",
      image = test_img,
      backend = 'ellmer',
      provider = 'ollama',
      language = 'German'
      )

    #>   image_classification primary_object secondary_object
    #> 1         Kinderbetten           Hund
    #>                                                           image_description
    #> 1 Der Bildinhalt zeigt einen Hund, der in der Nähe eines Kinderbetts liegt.
    #>                                                  image_colors
    #> 1 [⌘A87, ⌘AADE, ⌘545417, ⌘545417, ⌘AADE, ⌘A87, ⌘38182A, ⌘A87]
    #>                                                       image_proba_names
    #> 1 Hund, Bett, Tier, Kind, Hundebett, Tiergesicht, Fell, Haar, Tieraugen
    #>                                            image_proba_values
    #> 1 [0.42, 0.106, 0.08, 0.075, 0.045, 0.035, 0.034, 0.09, 0.07]

#### Chinese Results

    llm_image_classification(
      llm_model = "qwen2.5vl",
      image = test_img,
      backend = 'ellmer',
      provider = 'ollama',
      language = 'Mandarin Chinese'
      )

    #>   image_classification primary_object secondary_object
    #> 1         pet portrait          puppy
    #>                                                  image_description
    #> 1 这是一张黑白相间的小狗的特写照片，它有着独特的眼睛和湿润的鼻子。
    #>                                              image_colors image_proba_names
    #> 1 ["#990000", "#0000FF", "#FFC0CB", "#000000", "#FFFFFF"]                 [
    #>   image_proba_values
    #> 1                  [