I want to prove the conditionnal Jensen's inequality. Let $(\Omega, \mathcal H, \mathbb P)$ be a probability space, $\mathcal G \subset \mathcal H$ a sub sigma algebra, $\varphi : \mathbb R \longrightarrow \mathbb R$ convex and $X \in L^1(\mathcal H)$. Then the Jensen inequality is $$ \mathbb E [\varphi(X) | \mathcal G] \geq \varphi(\mathbb E [X | \mathcal G]). $$
For the proof the classical argument is that by basic properties of convex functions, forall $x \in \mathbb R$, $$ \tag{1}\varphi(x) = \sup_{(a,b) \in E_\varphi} ax+b = \sup_{(a,b) \in E_\varphi \cap \mathbb Q^2} ax+b $$ where $$ E_\varphi = \{ (a,b) \in \mathbb R^2 : \forall x \in \mathbb R ~~~\varphi(x) \geq ax+b \}. $$ The second equality of $(1)$ is false when $\varphi$ is affine with irrational growth ratio and I don't understand why we would need $(a,b)$ to vary in a countable set. This is how I proceed from the first equality of $(1)$ :
Fix $(a,b) \in E_\varphi$, forall $x \in \mathbb R$ we have $\varphi(x) \geq ax+b$ so $\varphi(X) \geq aX+b$. Taking the conditionnal expectation, which is non negative and linear, yields $$ \mathbb E [\varphi(X) | \mathcal G] \geq a \mathbb E [X | \mathcal G] + b. $$ Now taking the supremum of the left hand side on $(a,b)$ and using the first equality of $(1)$ yields the result. Is my proof correct?