Given angles $0<\theta_{ij}<\pi$ for $1\leq i<j\leq k$, what conditions are there on the angles to ensure that there exists $k$ unit vector $v_i\in \mathbb R^k$ so that the angle between $v_i$ and $v_j$ is $\theta_{ij}$?
There are clearly problems when $\theta_{12},\theta_{13},\theta_{23}$ are all close to $\pi$. What if I can ensure, for a given $\epsilon>0$ that $|\theta_{ij}-\frac{\pi}2|<\epsilon?$
Intuitively, this is true for $k=3$ and the angles close to $\frac{\pi}2$. We can easily pick $v_1,v_2$ and the locus of points for $v_3$ meeting the angle requirement with $v_1$ is a near-great circle in the unit sphere. With $v_2$, the same. And these two near-great circles are near-perpendicular. We need them to intersect for $v_3$ to be found.
But I can’t prove it, and my intuition for $k>3$ spheres is negligible.
This is a possible solution for this question. (In fact, I only need $k>3$ to complete that question - I’ve got an entirely different solution for $k=3$ in that question.)
I think a minimum necessary condition is, for all distinct $i,j,k$: $$\theta_{ij}+\theta_{jk}\geq \theta_{ik}.\tag 1$$ (Here we need $\theta_{ij}=\theta_{ji}$ for $i>j$ to include all the correct cases in (1).)
Also, probably: $$\theta_{ij}+\theta_{jk}+\theta_{ik}\leq 2\pi\tag 2$$
It seems like, when $k=3$, (1) and (2) should be enough.

$\def\vec{\boldsymbol}\def\v{\vec{v}}\def\x{\vec{x}}\def\R{\mathbb{R}}\def\Ω{{\mit Ω}}\def\<{\langle}\def\>{\rangle}\DeclareMathOperator{\diag}{diag}$On the one hand, if there exists such $\v_1, \cdots, \v_n$, define $V = [\v_1, \cdots, \v_n] \in \R^{n × n}$, then$$ V^T V = \begin{bmatrix} \<\v_1, \v_1\> & \cdots & \<\v_1, \v_n\>\\ \vdots & \ddots & \vdots\\ \<\v_n, \v_1\> & \cdots & \<\v_n, \v_n\> \end{bmatrix} = \begin{bmatrix} 1 & \cos θ_{1, 2} & \cdots & \cos θ_{1, n}\\ \cos θ_{2, 1} & 1 & \ddots & \cos θ_{2, n}\\ \vdots & \ddots & \ddots & \vdots\\ \cos θ_{n, 1} & \cos θ_{n, 2} & \cdots & 1 \end{bmatrix} =: A $$ is a positive semidefinite matrix.
On the other hand, if $A \geqslant 0$, then there exists an orthogonal matrix $\Ω$ and $D = \diag(λ_1, \cdots, λ_n)$ such that $λ_1, \cdots, λ_n \geqslant 0$ and $A = \Ω^T D\Ω$. Take $V = \sqrt{D}\Ω$ and $\v_k$ as the $k$-th column of $V$, then such $\v_k$'s satisfies $\dfrac{\v_i · \v_j}{\|\v_i\| \|\v_j\|} = \cos θ_{i, j}$ for any $i ≠ j$. (When $A > 0$, $V$ can also be computed by Cholesky decomposition.) Therefore the given condition is equivalent to $A \geqslant 0$.
Now, an easy-to-check condition to ensure $A \geqslant 0$ is\begin{gather*} \sum_{\substack{1 \leqslant j \leqslant n\\j ≠ i}} |\cos θ_{i, j}| \leqslant 1.\quad \forall 1 \leqslant i \leqslant n \tag{1} \end{gather*} In fact, when (1) is true, for any $\vec{x} \in \R^n$,\begin{gather*} \x^T A \x = \sum_{k = 1}^n x_k^2 + 2 \sum_{i < j} \cos θ_{i, j} x_i x_j\\ \geqslant \sum_{k = 1}^n x_k^2 - \sum_{i < j} |\cos θ_{i, j}| (x_i^2 + x_j^2) = \sum_{i = 1}^n \biggl( 1 - \sum_{\substack{1 \leqslant j \leqslant n\\j ≠ i}} |\cos θ_{i, j}| \biggr) x_i^2 \geqslant 0. \end{gather*} An even simpler condition implied by (1) is\begin{gather*} \max_{1 \leqslant i < j \leqslant n} |\cos θ_{i, j}| \leqslant \frac{1}{n - 1}, \tag{2} \end{gather*} or\begin{gather*} \max_{1 \leqslant i < j \leqslant n} \left| θ_{i, j} -\frac{π}{2} \right| \leqslant \arcsin\frac{1}{n - 1}. \tag{2$'$} \end{gather*}