Ask a question to a chatbot — ai

The question is sent to the chatbot server, and the answer is returned. The default chatbot server is ollama running locally, and the default model is codestral:latest. It was also tested with mistral:7b-instruct-v0.2-q6_K for an even smaller model.

ai_ask(
  question,
  context = NULL,
  max_tokens = getOption("SciViews.chatbot.max_tokens",
    Sys.getenv("SCIVIEWS_CHATBOT_MAX_TOKENS", 1000L)),
  lang = getOption("data.io_lang", "en"),
  url = getOption("SciViews.chatbot.url", Sys.getenv("SCIVIEWS_CHATBOT_URL",
    "http://localhost:11434/api/chat")),
  model = getOption("SciViews.chatbot.model", Sys.getenv("SCIVIEWS_CHATBOT_MODEL",
    "codestral:latest")),
  api_key = Sys.getenv("CONNECT_API_KEY", ""),
  verbose = FALSE
)

ai_explain_term(term, lang = getOption("data.io_lang", "en"), ...)

ai_explain_function(
  fun,
  package = NULL,
  lang = getOption("data.io_lang", "en"),
  ...
)

ai_explain_code(code, lang = getOption("data.io_lang", "en"), ...)

ai_explain_error(
  code = NULL,
  error = NULL,
  lang = getOption("data.io_lang", "en"),
  ...
)

Arguments

question: A character string with the question to ask.
context: An R object used as context (usually a data frame). This is not used yet, but it should be implemented in the future.
max_tokens: The maximum number of tokens to return in the answer. By default, it is 1000.
lang: The language to use for the answer. Default is "en". You can also use "fr" for instance.
url: The URL of the chatbot server. Default is http://localhost:11434/api/chat
model: The LLM (large language model) to use. Default is codestral. Make sure you complies to its license (see https://mistral.ai/news/mistral-ai-non-production-license-mnpl/), or switch to another model that better suits your requirements.
api_key: The API key to use for connecting to the chatbot server (optional, see your server administrator).
verbose: Should more information be printed? FALSE by default.
term: The term to describe.
...: Further arguments passed to ai_ask().
fun: The R function to explain.
package: The R package that provides the function.
code: A small chunk of R code to explain.
error: The error message that R returns.

Value

The answer is returned invisibly. The function is used for its side-effect of displaying the chatbot help page with the question, answer and examples

Examples

if (FALSE) { # \dontrun{


# Basic questions
ai_ask("Who are you?")
ai_ask("What is a chatbot?")
ai_ask("Qui es-tu ?")
ai_ask("Qu'est-ce que R ?")
ai_ask("Qu'est-ce que RStudio ?")
ai_ask("What is GitHub?")
ai_ask("Qu'est-ce que le R Markdown ?")
ai_ask("What is data science?")

# Inappropriate questions
ai_ask("Qu'est ce qu'un Acanthurus sp ?")
ai_ask("Raconte-moi une bonne blague.")
ai_ask("Va te faire voir !")

# Now, more complex questions
ai_ask("Comment filtrer un data frame en R?")
ai_ask("Write R code to filter a data frame.")
ai_ask("Que fait AIC()? Donne un exemple.")
ai_ask("Qu'est ce que l'hétéroscédasticite et comment la détecter dans une ANOVA à un facteur ?")
ai_ask("How to determine which model is better using an ANOVA for nested linear models?")

# Explain terms
ai_explain_term("True positive")
ai_explain_term("percentile", lang = "fr")
ai_explain_term("git push")
ai_explain_term("Quarto", lang = "fr")
ai_explain_term("boite à moustaches") # Language mismatch
ai_explain_term("boites à moustaches parallèles", lang = "fr")

# Explain R functions
ai_explain_function("mean")
ai_explain_function("fmean", lang = "fr")
ai_explain_function("collapse::fmean", lang = "fr")
ai_explain_function("glm", package = "stats", lang = "fr")
ai_explain_function("replace_na", "tidyr", lang = "fr") # collapse::replace_na() used instead!
try(ai_explain_function("nonexistingfunction")) # Error
try(ai_explain_function("apropos", package = "stats")) # Wrong package
try(ai_explain_function("apropos", package = "unknownpkg")) # Unknown package

# Explain R code
ai_explain_code("y <- c(1, 5, 7, NA, -Inf, 8)")
ai_explain_code(r"-[
mtcars |>
  filter(cyl == 4) |>
  summarise(mean_hp = mean(hp), median_disp = median(disp))]-")
ai_explain_code(r"-[
  mtcars %>.%
    sfilter(., cyl == 4) %>.%
    ssummarise(., mean_hp = fmean(hp), median_disp = fmedian(disp))
]-")
ai_explain_code(r"-[
  chart(data = trees, Volume ~ Girth) +
    geom_point() +
    geom_smooth()
]-")
ai_explain_error(error = "longer object length is not a multiple of shorter object length")
ai_explain_error(error = "Error: object 'mydata' not found")
ai_explain_error(error = "Error in lenght(1:10) : could not find function \"lenght\"", lang = "fr")
ai_explain_error(code = r"-[y <- c(1, 5, 7, NA, -Inf, 8, )]-", lang = "fr")
ai_explain_error(code = r"-[trees %>.% filter(Girth > 10))]-", lang = "fr")
ai_explain_error(code = r"-[
urchin <- read("urchin", package = "data.io")
  ]-", error = r"-[
Error in read("urchin", package = "data.io") :
  dataset 'urchin' not found in package 'data.io'
  ]-", lang = "fr")
} # }