update

src/interface.jl

@@ -83,8 +83,6 @@ function decisionMaker(a::T1, state::T2) where {T1<:agent, T2<:AbstractDict}
   # (trajectories)
   # """
 
-
-  #[WORKING] 
   _prompt = 
   """
   You are a helpful sommelier working for a wine store. 

src/mcts.jl

@@ -135,12 +135,13 @@ function expand(a::T1, node::MCTSNode, state::T2, decisionMaker::Function, state
   # sampling action from decisionMaker
   for sample in 1:n
     thought = decisionMaker(a, state)
-    error("--> expand")
+    
     newState = transition(node.state, action)  #[] Implement your transition function
     if newState ∉ keys(node.children)
         node.children[newState] = MCTSNode(newState, 0, 0.0, Dict{T, MCTSNode}())
     end
   end
+  error("--> expand")
 end
 
 """