Creating a KM curve function

I am trying to make a KM curve function, however, I am not sure where I am going wrong.

library(tidyverse)library(ggplot)library(survival)library(survminer)km_curve <- function(df, tm, ev, predictor) {            surv_object <- Surv(time = df$tm, event = df$ev)            fit1 <- survfit(surv_object ~ predictor, data = df)            ggsurvplot(fit1, data = df, pval = TRUE, xlab = "Months")            }

I also tried this

km_curve <- function(df, tm, ev, predictor) {            surv_object <- Surv(time = df[,tm], event = df[,ev])            fit1 <- survfit(surv_object ~ predictor, data = df)            ggsurvplot(fit1, data = df, pval = TRUE, xlab = "Months")            }             km_curve(df = first_primaries,                       tm = pfs_time_months,                       ev = pfs_fail.x,                       predictor = risk)

I have also tried

   km_curve <- function(df, tm, ev, predictor) {               tim <- df %>%                       select(tm)               even <- df %>%                       select(ev)               surv_object <- Surv(time = tim, event = even)               fit1 <- survfit(surv_object ~ predictor, data = df)               ggsurvplot(fit1, data = df, pval = TRUE, xlab = "Months")             }         km_curve(df = first_primaries,                   tm = pfs_time_months,                   ev = pfs_fail.x,                   predictor = risk)

It keeps giving me error messages that pf_time_months not found. Even though it is a column in my data frame I specify.