blob: 2aa7137477a359a092aaef2a8c88d771ffdc199c [file] [log] [blame]
# Helper function to find README.md file in current or parent directories
find_readme_path <- function() {
readme_paths <- c("Readme.md", "../Readme.md", "../../Readme.md")
for (path in readme_paths) {
if (file.exists(path)) {
return(path)
}
}
return(NULL)
}
# Helper function to read README content
read_readme_content <- function() {
readme_path <- find_readme_path()
if (is.null(readme_path)) {
return(NULL)
}
readme_content <- readLines(readme_path)
paste(readme_content, collapse = "\n")
}
# Helper function to call OpenAI API
call_openai_api <- function(prompt, max_tokens = 500, temperature = 0.1) {
library(httr2)
library(jsonlite)
tryCatch({
response <- request("https://api.openai.com/v1/chat/completions") |>
req_headers(
"Authorization" = paste("Bearer", Sys.getenv("OPENAI_API_KEY")),
"Content-Type" = "application/json"
) |>
req_body_json(list(
model = "gpt-4.1-mini",
messages = list(
list(role = "user", content = prompt)
),
max_tokens = max_tokens,
temperature = temperature
)) |>
req_retry(max_tries = 3) |>
req_perform()
# Parse the response
result <- response |> resp_body_json()
result$choices[[1]]$message$content
}, error = function(e) {
if (grepl("429", as.character(e))) {
skip("OpenAI API rate limit exceeded - please try again later or check your API key/credits")
} else if (grepl("401", as.character(e))) {
skip("OpenAI API authentication failed - please check your OPENAI_API_KEY")
} else {
stop(paste("OpenAI API error:", as.character(e)))
}
})
}
# KorAP URL for testing
KORAP_URL <- "https://korap.ids-mannheim.de/instance/wiki"
# Helper function to create README-guided prompt
create_readme_prompt <- function(task_description, specific_task) {
readme_text <- read_readme_content()
if (is.null(readme_text)) {
stop("README.md not found")
}
paste0(
"You are an expert R programmer. Based on the following README documentation for the RKorAPClient package, ",
task_description, "\n\n",
"IMPORTANT: Use the KorAP URL '", KORAP_URL, "' as the KorAPUrl parameter in KorAPConnection.\n\n",
"README Documentation:\n",
readme_text,
"\n\nTask: ", specific_task,
"\n\nProvide only the R code without explanations."
)
}
# Helper function to extract R code from markdown code blocks
extract_r_code <- function(response_text) {
# Remove markdown code blocks if present
code <- gsub("```[rR]?\\n?", "", response_text)
code <- gsub("```\\n?$", "", code)
# Remove leading/trailing whitespace
trimws(code)
}
test_that("GPT-4.1 mini can solve frequency query task with README guidance", {
skip_if_not(nzchar(Sys.getenv("OPENAI_API_KEY")), "OPENAI_API_KEY not set")
skip_if_not(!is.null(find_readme_path()), "Readme.md not found in current or parent directories")
# Create the prompt with README context and task
prompt <- create_readme_prompt(
"write R code to perform a frequency query for the word 'Deutschland' across multiple years (2010-2015). The code should use the RKorAPClient package and return a data frame with year and frequency columns.",
"Write R code to query frequency of 'Deutschland' from 2010-2015 using RKorAPClient."
)
# Call OpenAI API
generated_response <- call_openai_api(prompt, max_tokens = 500)
generated_code <- extract_r_code(generated_response)
# Basic checks on the generated code
expect_true(grepl("KorAPConnection", generated_code), "Generated code should include KorAPConnection")
expect_true(grepl("frequencyQuery", generated_code), "Generated code should include frequencyQuery")
expect_true(grepl("Deutschland", generated_code), "Generated code should include the search term 'Deutschland'")
expect_true(grepl("201[0-5]", generated_code), "Generated code should include years 2010-2015")
expect_true(grepl(KORAP_URL, generated_code, fixed = TRUE), "Generated code should include the specified KorAP URL")
# Check that the generated code contains essential RKorAPClient patterns
expect_true(grepl("\\|>", generated_code) || grepl("%>%", generated_code),
"Generated code should use pipe operators")
# Optional: Try to parse the generated code to check for syntax errors
parsed_successfully <- tryCatch({
parse(text = generated_code)
TRUE
}, error = function(e) {
FALSE
})
expect_true(parsed_successfully, "Generated code should be syntactically valid R code")
# Print the generated code for manual inspection
cat("Generated code:\n", generated_code, "\n")
})
test_that("GPT-4.1 mini can solve collocation analysis task with README guidance", {
skip_if_not(nzchar(Sys.getenv("OPENAI_API_KEY")), "OPENAI_API_KEY not set")
skip_if_not(!is.null(find_readme_path()), "Readme.md not found in current or parent directories")
# Create the prompt for collocation analysis
prompt <- create_readme_prompt(
"write R code to perform a collocation analysis for the word 'setzen' (looking for light verb constructions). The code should use the RKorAPClient package's collocationAnalysis function.",
"Write R code to perform collocation analysis for 'setzen' using RKorAPClient."
)
# Call OpenAI API
generated_response <- call_openai_api(prompt, max_tokens = 500)
generated_code <- extract_r_code(generated_response)
# Basic checks on the generated code
expect_true(grepl("KorAPConnection", generated_code), "Generated code should include KorAPConnection")
expect_true(grepl("collocationAnalysis", generated_code), "Generated code should include collocationAnalysis")
expect_true(grepl("setzen", generated_code), "Generated code should include the search term 'setzen'")
expect_true(grepl("auth", generated_code), "Generated code should include auth() for collocation analysis")
expect_true(grepl(KORAP_URL, generated_code, fixed = TRUE), "Generated code should include the specified KorAP URL")
# Check for collocation analysis parameters
expect_true(grepl("leftContextSize|rightContextSize", generated_code),
"Generated code should include context size parameters")
# Print the generated code for manual inspection
cat("Generated collocation analysis code:\n", generated_code, "\n")
})
test_that("GPT-4.1 mini can solve corpus query task with README guidance", {
skip_if_not(nzchar(Sys.getenv("OPENAI_API_KEY")), "OPENAI_API_KEY not set")
skip_if_not(!is.null(find_readme_path()), "Readme.md not found in current or parent directories")
# Create the prompt for corpus query
prompt <- create_readme_prompt(
"write R code to perform a simple corpus query for 'Hello world' and fetch all results. The code should use the RKorAPClient package.",
"Write R code to query 'Hello world' and fetch all results using RKorAPClient."
)
# Call OpenAI API
generated_response <- call_openai_api(prompt, max_tokens = 300)
generated_code <- extract_r_code(generated_response)
# Basic checks on the generated code
expect_true(grepl("KorAPConnection", generated_code), "Generated code should include KorAPConnection")
expect_true(grepl("corpusQuery", generated_code), "Generated code should include corpusQuery")
expect_true(grepl("Hello world", generated_code), "Generated code should include the search term 'Hello world'")
expect_true(grepl("fetchAll", generated_code), "Generated code should include fetchAll")
expect_true(grepl(KORAP_URL, generated_code, fixed = TRUE), "Generated code should include the specified KorAP URL")
# Check that the generated code follows the README example pattern
expect_true(grepl("\\|>", generated_code) || grepl("%>%", generated_code),
"Generated code should use pipe operators")
# Print the generated code for manual inspection
cat("Generated corpus query code:\n", generated_code, "\n")
})