# Deploy lm glm
#
# This is the base function of jaqpot named 'deploy.on.jaqpot'
# which deploys a model on 'Jaqpot'.
#
#' deploy.on.jaqpot takes as input a trained model, it uploads it
#' after some prompt questions and returns a model id
#'
#' Suports lm from base
#' @param model
# source('login.jaqpot.R', local = TRUE)
deploy.lm.glm.jaqpot <- function(object){
basep <- readline("Base path of jaqpot *etc: https://api.jaqpot.org/ : ")
token <- login.jaqpot(basep)
checkfeatures <- array( names(coef(object)));
if(checkfeatures[1] %in% "(Intercept)"){
independentFeaturesfm <- checkfeatures[!checkfeatures %in% "(Intercept)"]
}else{
independentFeaturesfm <- checkfeatures
}
title <- readline("Title of the model: ")
discription <- readline("Discription of the model:")
if(library_check == 1){
libabry_in <- "base"
}
predicts <- readline("Actual name of the predicted feature: ")
model <- serialize(list(MODEL=object),connection=NULL)
tojson <- list(rawModel=model,runtime="R-lm-glm", implementedWith="lm or a glm in r",pmmlModel=NULL,independentFeatures=independentFeaturesfm,
predictedFeatures=predicts, dependentFeatures=predicts, title=title, description=discription, algorithm="lm or a glm in r")
json <- toJSON(tojson)
bearer = paste("Bearer", token, sep=" ")
res = POST(basep, path="jaqpot/services/model",
add_headers(Authorization=bearer),
accept_json(),
content_type("application/json"),
body = json, encode = "json")
code <- status_code(res)
if(status_code(res) == 200 ){
resp <- content(res, "text")
respon <- fromJSON(resp)
response <- paste("Model created. The id is: ", respon$modelId, ". Please visit: https://app.jaqpot.org/ to complete ", sep=" ")
response
}else{
code
}
}
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