## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----providers----------------------------------------------------------------
library(dicomtk)

# 1. Local Ollama (100% private, runs on your machine)
ollama_llm <- dicom_llm(
  provider = "ollama",
  model = "llava:13b",
  base_url = "http://localhost:11434"
)
ollama_llm

# 2. OpenAI or any OpenAI-compatible API endpoint
openai_llm <- dicom_llm(
  provider = "openai",
  model = "gpt-4o",
  base_url = "https://api.openai.com/v1"
)

# 3. Anthropic Claude
claude_llm <- dicom_llm(
  provider = "anthropic",
  model = "claude-sonnet-4-20250514"
)

# 4. Deterministic offline provider (for reproducible pipelines without network access)
offline_llm <- dicom_llm("offline")

## ----ai-tasks-----------------------------------------------------------------
dcm_file <- system.file("extdata", "example.dcm", package = "dicomtk")

# Natural-language study metadata summary
dicom_summarize(dcm_file, llm = offline_llm)

# Vision + quantitative pixel analysis
dicom_describe_image(dcm_file, llm = offline_llm)

# Generate a structured radiology report and export as a DICOM Structured Report (.dcm)
sr_out <- tempfile(fileext = ".dcm")
report_tbl <- dicom_report(dcm_file, llm = offline_llm, save_sr_path = sr_out)
report_tbl

# Read back the generated DICOM Structured Report
read_dicom_sr(sr_out)

## ----nl-query-----------------------------------------------------------------
dicom_ask(dcm_file, "What are the image dimensions and photometric interpretation?", llm = offline_llm)

# Look up standard DICOM tags with natural language
dicom_tag_lookup("What tag stores window center?", llm = offline_llm)