Add regression equation and R2 to plot in Julia

I have the following scatter plot with smoothed regression line:

using Plots
using DataFrames
using GLM

df = DataFrame(x = collect(1:7), y = collect(1:7)+rand(7))

scatter(df.x, df.y, smooth = :true, label = "data")
xlabel!("x")
ylabel!("y")

Output:

And the regression model:

model = lm(@formula(y ~ x), df)
StatsModels.TableRegressionModel{LinearModel{GLM.LmResp{Vector{Float64}}, GLM.DensePredChol{Float64, LinearAlgebra.CholeskyPivoted{Float64, Matrix{Float64}, Vector{Int64}}}}, Matrix{Float64}}

y ~ 1 + x

Coefficients:
─────────────────────────────────────────────────────────────────────────
                Coef.  Std. Error      t  Pr(>|t|)   Lower 95%  Upper 95%
─────────────────────────────────────────────────────────────────────────
(Intercept)  0.469577   0.21843     2.15    0.0843  -0.0919156    1.03107
x            1.03064    0.0488424  21.10    <1e-05   0.905083     1.15619
─────────────────────────────────────────────────────────────────────────

I would like to add the regression equation (y=ax+b) and the R squared coefficient to this plot. So I was wondering if anyone knows how to add the equation and coefficients of a regression fit to a plot in Julia?

using the LaTeXStrings.jl:

annotate!(
  4,
  7,
  latexstring(
    "y = $(round(coef(model)[2], digits = 2))x + $(round(coef(model)[1], digits = 2))"
  )
)

annotate!(
  4,
  6.5,
  latexstring("r^2 = $(round(r2(model), digits = 2))")
)