Package 'kuzco'

chat ellmer helper (predates ellmer::chat)

Description

a minimal wrapper function to switch which provider is used for each llm_image* function when ellmer backend is selected, ollamar only supports ollama

Usage

chat_ellmer(provider = "ollama")

Arguments

provider

a provider, such as "ollama", or "claude", or "github"

Value

which ellmer function (provider) to use for kuzco llm_image_* when backend is ellmer

---

edit prompt

Description

edit a listed prompt installed with kuzco

Usage

edit_prompt(prompt)

Arguments

prompt

a prompt from list_prompts()

Value

a prompt markdown file to edit

Examples

## Not run: 
edit_prompt("system-prompt-alt-text.md")

## End(Not run)

---

shiny kuzco app

Description

a simple wrapper of kuzco to make computer vision for everyone. few-shot via frank hull and shiny assistant (https://gallery.shinyapps.io/assistant/)

Usage

kuzco_app()

Value

a shiny app instance as a playground for local llms

Examples

## Not run: 
kuzco_app()

## End(Not run)

---

list prompts

Description

list prompts installed with kuzco

Usage

list_prompts()

Value

a list of prompts stored within kuzco

Examples

list_prompts()

---

Image Alt Text using LLMs

Description

Image Alt Text using LLMs

Usage

llm_image_alt_text(
  llm_model = "qwen2.5vl",
  image = system.file("img/test_img.jpg", package = "kuzco"),
  backend = "ellmer",
  additional_prompt = "",
  provider = "ollama",
  language = "English",
  ...
)

Arguments

llm_model	a local LLM model either pulled from ollama or hosted
image	a local image path that has a jpeg, jpg, or png
backend	either 'ellmer' or 'ollamar', note that 'ollamar' suggests structured outputs while 'ellmer' enforces structured outputs
additional_prompt	text to append to the image prompt
provider	for backend = 'ollamar', provider is ignored. for backend = 'ellmer', provider refers to the ⁠ellmer::chat_*⁠ providers and can be used to switch from "ollama" to other providers such as "perplexity"
language	a language to guide the LLM model outputs
...	a pass through for other generate args and model args like temperature. set the temperature to 0 for more deterministic output

Value

a df with text

Examples

llm_image_alt_text(
 llm_model = "qwen2.5vl",
 image = system.file("img/test_img.jpg", package = "kuzco"),
 backend = 'ellmer',
 additional_prompt = "",
provider = "ollama",
language = "English"
)

---

Image Classification using LLMs

Description

Image Classification using LLMs

Usage

llm_image_classification(
  llm_model = "qwen2.5vl",
  image = system.file("img/test_img.jpg", package = "kuzco"),
  backend = "ellmer",
  additional_prompt = "",
  provider = "ollama",
  language = "English",
  ...
)

Arguments

llm_model	a local LLM model either pulled from ollama or hosted
image	a local image path that has a jpeg, jpg, or png
backend	either 'ollamar' or 'ellmer', note that 'ollamar' suggests structured outputs while 'ellmer' enforces structured outputs
additional_prompt	text to append to the image prompt
provider	for backend = 'ollamar', provider is ignored. for backend = 'ellmer', provider refers to the ⁠ellmer::chat_*⁠ providers and can be used to switch from "ollama" to other providers such as "perplexity"
language	a language to guide the LLM model outputs
...	a pass through for other generate args and model args like temperature

Value

a df with image_classification, primary_object, secondary_object, image_description, image_colors, image_proba_names, image_proba_values

Examples

llm_image_classification(
 llm_model = "qwen2.5vl",
 image = system.file("img/test_img.jpg", package = "kuzco"),
 backend = 'ellmer',
 additional_prompt = "",
provider = "ollama",
language = "English"
)

---

Customized Vision using LLMs

Description

Customized Vision using LLMs

Usage

llm_image_custom(
  llm_model = "qwen2.5vl",
  image = system.file("img/test_img.jpg", package = "kuzco"),
  backend = "ellmer",
  system_prompt = "You are a terse assistant in computer vision sentiment.",
  image_prompt = "return JSON describing image, do not include json or backticks",
  example_df = NULL,
  provider = "ollama",
  ...
)

Arguments

llm_model	a local LLM model either pulled from ollama or hosted
image	a local image path that has a jpeg, jpg, or png
backend	either 'ollamar' or 'ellmer'
system_prompt	overarching assistant description, please note that the LLM should be told to return as JSON while kuzco will handle the conversions to and from JSON
image_prompt	anything you want to really remind the llm about.
example_df	an example data.frame to show the llm what you want returned note this will be converted to JSON for the LLM.
provider	for backend = 'ollamar', provider is ignored. for backend = 'ellmer', provider refers to the ⁠ellmer::chat_*⁠ providers and can be used to switch from "ollama" to other providers such as "perplexity"
...	a pass through for other generate args and model args like temperature

Value

a customized return based on example_df for custom control

Examples

llm_image_custom(
 llm_model = "qwen2.5vl",
 image = system.file("img/test_img.jpg", package = "kuzco"),
 backend = "ellmer",
 system_prompt = "You are a terse assistant in computer vision sentiment.",
 image_prompt = "return JSON describing image, do not include json or backticks",
 example_df = NULL,
 provider = "ollama"
)

---

Image OCR for Text Extraction using LLMs

Description

Image OCR for Text Extraction using LLMs

Usage

llm_image_extract_text(
  llm_model = "qwen2.5vl",
  image = system.file("img/text_img.jpg", package = "kuzco"),
  backend = "ellmer",
  additional_prompt = "",
  provider = "ollama",
  language = "English",
  ...
)

Arguments

llm_model	a local LLM model either pulled from ollama or hosted
image	a local image path that has a jpeg, jpg, or png
backend	either 'ellmer' or 'ollamar', note that 'ollamar' suggests structured outputs while 'ellmer' enforces structured outputs
additional_prompt	text to append to the image prompt
provider	for backend = 'ollamar', provider is ignored. for backend = 'ellmer', provider refers to the ⁠ellmer::chat_*⁠ providers and can be used to switch from "ollama" to other providers such as "perplexity"
language	a language to guide the LLM model outputs
...	a pass through for other generate args and model args like temperature. set the temperature to 0 for more deterministic output

Value

a df with text and a confidence score

Examples

llm_image_extract_text(
 llm_model = "qwen2.5vl",
 image = system.file("img/test_img.jpg", package = "kuzco"),
 backend = 'ellmer',
 additional_prompt = "",
provider = "ollama",
language = "English"
)

---

Image Recognition using LLMs

Description

Image Recognition using LLMs

Usage

llm_image_recognition(
  llm_model = "qwen2.5vl",
  image = system.file("img/test_img.jpg", package = "kuzco"),
  recognize_object = "face",
  backend = "ellmer",
  additional_prompt = "",
  provider = "ollama",
  language = "English",
  ...
)

Arguments

llm_model	a local LLM model either pulled from ollama or hosted
image	a local image path that has a jpeg, jpg, or png
recognize_object	an item you want to LLM to look for
backend	either 'ollamar' or 'ellmer', note that 'ollamar' suggests structured outputs while 'ellmer' enforces structured outputs
additional_prompt	text to append to the image prompt
provider	for backend = 'ollamar', provider is ignored. for backend = 'ellmer', provider refers to the ⁠ellmer::chat_*⁠ providers and can be used to switch from "ollama" to other providers such as "perplexity"
language	a language to guide the LLM model outputs
...	a pass through for other generate args and model args like temperature. set the temperature to 0 for more deterministic output

Value

a df with object_recognized, object_count, object_description, object_location

Examples

llm_image_recognition(
 llm_model = "qwen2.5vl",
 image = system.file("img/test_img.jpg", package = "kuzco"),
	recognize_object = "nose",
 backend = 'ellmer',
 additional_prompt = "",
provider = "ollama",
language = "English"
)

---

Image Sentiment using LLMs

Description

Image Sentiment using LLMs

Usage

llm_image_sentiment(
  llm_model = "qwen2.5vl",
  image = system.file("img/test_img.jpg", package = "kuzco"),
  backend = "ellmer",
  additional_prompt = "",
  provider = "ollama",
  language = "English",
  ...
)

Arguments

llm_model	a local LLM model either pulled from ollama or hosted
image	a local image path that has a jpeg, jpg, or png
backend	either 'ollamar' or 'ellmer', note that 'ollamar' suggests structured outputs while 'ellmer' enforces structured outputs
additional_prompt	text to append to the image prompt
provider	for backend = 'ollamar', provider is ignored. for backend = 'ellmer', provider refers to the ⁠ellmer::chat_*⁠ providers and can be used to switch from "ollama" to other providers such as "perplexity"
language	a language to guide the LLM model outputs
...	a pass through for other generate args and model args like temperature. set the temperature to 0 for more deterministic output

Value

a df with image_sentiment, image_score, sentiment_description, image_keywords

Examples

llm_image_sentiment(
 llm_model = "qwen2.5vl",
 image = system.file("img/test_img.jpg", package = "kuzco"),
 backend = 'ellmer',
 additional_prompt = "",
provider = "ollama",
language = "English"
)

---

View Images quickly and easily

Description

View Images quickly and easily

Usage

view_image(image = system.file("img/test_img.jpg", package = "kuzco"))

Arguments

image

an image to view

Value

a plot of the image in a Plots pane

Examples

view_image(image = system.file("img/test_img.jpg", package = "kuzco"))

---

view llm results as a tidy great table

Description

view llm results as a tidy great table

Usage

view_llm_results(llm_results)

Arguments

llm_results

results from one of the llm_image_* functions

Value

a great table to view the results neatly

Examples

## Not run: 
view_llm_results(llm_image_alt_text())

## End(Not run)

---