some fixes

Author: penelopeysm

src/model.jl

@@ -807,12 +807,12 @@ samples from the prior.
 """
 (model::Model)() = model(Random.default_rng())
 function (model::Model)(
-    rng::AbstractRNG,
+    rng::Random.AbstractRNG,
     varinfo::AbstractVarInfo=VarInfo(),
     sampler::AbstractSampler=SampleFromPrior(),
 )
     spl_ctx = SamplingContext(rng, sampler, DefaultContext())
-    return evaluate!!(model, varinfo, spl_ctx)
+    return first(evaluate!!(model, varinfo, spl_ctx))
 end
 
 """
@@ -833,12 +833,15 @@ evaluation by wrapping the model's context in a `SamplingContext`.
 
 Returns a tuple of the model's return value, plus the updated `varinfo` object.
 """
-function sample!!(rng::AbstractRNG, model::Model, varinfo::AbstractVarInfo)
+function sample!!(rng::Random.AbstractRNG, model::Model, varinfo::AbstractVarInfo)
     sampling_model = contextualize(
         model, SamplingContext(rng, SampleFromPrior(), model.context)
     )
     return evaluate!!(sampling_model, varinfo)
 end
+function sample!!(model::Model, varinfo::AbstractVarInfo)
+    return sample!!(Random.default_rng(), model, varinfo)
+end
 
 """
     evaluate!!(model::Model, varinfo)
@@ -978,7 +981,6 @@ Return the arguments and keyword arguments to be passed to the evaluator of the
             # speeding up computation. See docs for `maybe_invlink_before_eval!!`
             # for more information.
             maybe_invlink_before_eval!!(varinfo, model),
-            context_new,
             $(unwrap_args...),
         )
         kwargs = model.defaults
@@ -1014,15 +1016,7 @@ Base.nameof(model::Model{<:Function}) = nameof(model.f)
 Generate a sample of type `T` from the prior distribution of the `model`.
 """
 function Base.rand(rng::Random.AbstractRNG, ::Type{T}, model::Model) where {T}
-    x = last(
-        evaluate!!(
-            model,
-            SimpleVarInfo{Float64}(OrderedDict()),
-            # NOTE: Use `leafcontext` here so we a) avoid overriding the leaf context of `model`,
-            # and b) avoid double-stacking the parent contexts.
-            SamplingContext(rng, SampleFromPrior(), leafcontext(model.context)),
-        ),
-    )
+    x = last(sample!!(model, SimpleVarInfo{Float64}(OrderedDict())))
     return values_as(x, T)
 end
 
@@ -1187,7 +1181,7 @@ function Distributions.loglikelihood(model::Model, chain::AbstractMCMC.AbstractC
 end
 
 """
-    predict([rng::AbstractRNG,] model::Model, chain::AbstractVector{<:AbstractVarInfo})
+    predict([rng::Random.AbstractRNG,] model::Model, chain::AbstractVector{<:AbstractVarInfo})
 
 Generate samples from the posterior predictive distribution by evaluating `model` at each set
 of parameter values provided in `chain`. The number of posterior predictive samples matches