How to directly label regression lines within plot frame (without a legend)?

Question

Data and Previous Content

This question is a continuation of a previous question with the same data but with a slight tweak.

Question

Same as before, this is the example I am looking to achieve, with the part I want now highlighted in green:

Instead of coloring a specific regression line, now I want to add a direct label to the plot window like above. I know that by faceting the data, we can achieve this with a legend, coloring the lines, etc. We can even manually add an annotation by selecting the x and y coordinates with annotate or geom_text.

But I want something that doesn't require a legend or manually figuring out where the exact geom coordinates are. Is there a way to simply add the label to a regression line within the plot window similar to other aes functions? This is the base plot I have so far, with the label now removed and regression lines colored:

ggplot(slack.work,
       aes(x=Coffee_Cups,
           y=Mins_Work,
           color=Month_Name))+
  geom_point(alpha = .4)+
  geom_smooth(method = "lm",
              se = F)+
  scale_colour_viridis_d()+
  theme_bw()+
  labs(title = "Coffee Cups x Minutes of Productivity",
       subtitle = "Pearson r = .30, p < .001",
       x="Cups of Coffee",
       y="Minutes of Work",
       color="Month")+
  theme(plot.title = element_text(face = "bold",
                                  size = 15,
                                  family = "mono"),
        plot.subtitle = element_text(face = "italic"),
        legend.position = "none")

Currently, it looks like this:

But I would like for it to look something like this:

Answer 1

Adapting this answer to your case you could achieve your desired result by using stat="smooth" via geom_text or ggrepel::geom_text_repel. The tricky part is to get only one label for which I use an ifelse inside after_stat:

library(ggplot2)

# Levels of Month_Name. 
# Needed to get the month names.
# When using after_stat only get the level number via `group`
levels_month <- levels(factor(slack.work$Month_Name))

ggplot(
  slack.work,
  aes(
    x = Coffee_Cups,
    y = Mins_Work,
    group = Month_Name,
    color = Month_Name == "January"
  )
) +
  geom_point(alpha = .4) +
  geom_smooth(
    data = ~subset(.x, !Month_Name == "January"),
    method = "lm",
    se = F
  ) +
  geom_smooth(
    data = ~subset(.x, Month_Name == "January"),
    method = "lm",
    se = F
  ) +
  ggrepel::geom_text_repel(aes(label = after_stat(ifelse(x %in% range(x)[1], levels_month[group], NA_character_))), 
                            stat = "smooth", method = "lm",
                            nudge_x = -.5, direction = "y") +
  scale_x_continuous(expand = expansion(add = c(.5, 0), mult =.05)) +
  scale_colour_manual(values = c("TRUE" = "steelblue", "FALSE" = "grey65")) +
  annotate("text",
           x = 3,
           y = 800,
           label = "January had the strongest effect on productivity.",
           size = 4,
           color = "steelblue"
  ) +
  theme_bw() +
  labs(
    title = "Coffee Cups x Minutes of Productivity",
    subtitle = "Pearson r = .30, p < .001",
    x = "Cups of Coffee",
    y = "Minutes of Work",
    color = "Month"
  ) +
  theme(
    plot.title = element_text(
      face = "bold",
      size = 15,
      family = "mono"
    ),
    plot.subtitle = element_text(face = "italic")
  ) +
  guides(color = "none")

EDIT To get rid of the segments connecting the line and the label you could add min.segment.length = Inf to geom_text_repel:

... +
ggrepel::geom_text_repel(aes(label = after_stat(ifelse(x %in% range(x)[1], levels_month[group], NA_character_))), 
                            stat = "smooth", method = "lm", min.segment.length = Inf,
                            nudge_x = -.5, direction = "y") +
...