update

src/interface.jl

@@ -35,32 +35,27 @@ using ..type, ..util, ..llmfunction, ..mcts
 
 """ Think and choose action
 
-  Arguments\n
+# Arguments
-  -----
+  `a::T1`
-    a::T1
     one of Yiem's agent
-    state::T2
+  `state::T2`
     a game state
   
-  Return\n
+# Return
-  -----
+  `thought::Dict`
-    thought::Dict
 
-  Example\n
+# Example
-  -----
 ```jldoctest
 julia> 
 ```
 
-  TODO\n
+# TODO
-  -----
   [] update docstring
   [x] implement the function
   [] implement RAG to pull similar experience
   [] use iterative prompting to ensure JSON format
 
-  Signature\n
+# Signature
-  -----
 """
 function decisionMaker(a::T1, state::T2) where {T1<:agent, T2<:AbstractDict}
   customerinfo = 

src/mcts.jl

@@ -134,14 +134,17 @@ function expand(a::T1, node::MCTSNode, state::T2, decisionMaker::Function, state
 
   # sampling action from decisionMaker
   for sample in 1:n
-    thought = decisionMaker(a, state)
+    thoughtJstr = decisionMaker(a, state)
+    thoughtDict = copy(JSON3.read(thoughtJstr)) 
+    latestActionKey = GeneralUtils.findHighestIndexKey(thoughtDict, "Action")
 
+    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
 
 """