update

src/interface.jl

@@ -51,7 +51,7 @@ julia>
 
 # TODO
   [] update docstring
-  [x] implement the function
+  [PENDING] implement the function
   [] implement RAG to pull similar experience
   [] use iterative prompting to ensure JSON format
 
@@ -143,8 +143,8 @@ function decisionMaker(a::T1, state::T2) where {T1<:agent, T2<:AbstractDict}
     )
   )
 
-  thought = GeneralUtils.sendReceiveMqttMsg(outgoingMsg)
+  result = GeneralUtils.sendReceiveMqttMsg(outgoingMsg)
-
+  thought = result[:response][:text]
   return thought
 end
 
@@ -288,7 +288,7 @@ end
 function conversation(a::T, userinput::Dict) where {T<:agent}
   """
   [] update document
-  [x] MCTS() for planning
+  [PENDING] MCTS() for planning
   """
   # "newtopic" command to delete chat history
   if userinput[:text] == "newtopic"

src/mcts.jl

@@ -15,9 +15,8 @@ using ..type
 
 """ a node for MCTS search tree
 
-  Arguments\n
+# Arguments
-  -----
+  - `state::T`
-    state::T
     a state of a game. Can be a Dict or something else. 
     For example:
     state = Dict(
@@ -31,27 +30,23 @@ using ..type
         ...
       )  
     )
-    visits::Integer 
+  - `visits::Integer `
     number of time the game visits this state
-    stateValue::Float64
+  - `stateValue::Float64`
     state value
 
-  Return\n
+# Return
-  -----
 
-  Example\n
+# Example
-  -----
+```jldoctest
-  ```jldoctest
+julia> 
-  julia> 
+```
-  ```
 
-  TODO\n
+# TODO
-  -----
   [] update docstring
-    [DONE] implement the function
+  [x] implement the function
 
-  Signature\n
+# Signature
-  -----
 """
 struct MCTSNode{T<:AbstractDict}
   state::T
@@ -62,28 +57,23 @@ end
 
 """ Select a node based on UCT score
 
-  Arguments\n
+# Arguments
-  -----
+  - `node::MCTSNode`
-    node::MCTSNode
     mcts node
-    w::Float64
+  - `w::Float64`
     exploration weight
-  Return\n
+# Return
-  -----
 
-  Example\n
+# Example
-  -----
+```jldoctest
-  ```jldoctest
+julia> 
-  julia> 
+```
-  ```
 
-  TODO\n
+# TODO
-  -----
   [] update docstring
   [DONE] check childNode.total_reward w/ LATS paper. Which value total_reward representing 
 
-  Signature\n
+# Signature
-  -----
 """
 function select(node::MCTSNode, w::Float64)
     max_uct = -Inf
@@ -103,31 +93,26 @@ end
 
 """ Expand selected node 
 
-  Arguments\n
+# Arguments
-  -----
+  - `node::MCTSNode`
-    node::MCTSNode
     MCTS node
-    state::T
+  - `state::T`
     a state of a game. Can be a Dict or something else.
-    decisionMaker::Function
+  - `decisionMaker::Function`
     
   
-  Return\n
+# Return
-  -----
 
-  Example\n
+# Example
-  -----
+```jldoctest
-  ```jldoctest
+julia> 
-  julia> 
+```
-  ```
 
-  TODO\n
+# TODO
-  -----
+  - [] update docstring
-    [] update docstring
+  - [WORKING] implement the function
-    [x] implement the function
 
-  Signature\n
+# Signature
-  -----
 """
 function expand(a::T1, node::MCTSNode, state::T2, decisionMaker::Function, stateValueEstimator::Function;
                 n::Integer=3) where {T1<:agent, T2<:AbstractDict}
@@ -149,26 +134,21 @@ end
 
 """
 
-  Arguments\n
+# Arguments
-  -----
   
-  Return\n
+# Return
-  -----
 
-  Example\n
+# Example
-  -----
+```jldoctest
-  ```jldoctest
+julia> 
-  julia> 
+```
-  ```
 
-  TODO\n
+# TODO
-  -----
+  - [] update docstring
-    [] update docstring
+  - [] implement the function
-    [] implement the function
+  - [] reward only comes at terminal state
-    [] reward only comes at terminal state
 
-  Signature\n
+# Signature
-  -----
 """
 function simulate(state::T, max_depth::Int) where {T<:AbstractDict}
     total_reward = 0.0
@@ -186,25 +166,20 @@ end
 
 """
 
-  Arguments\n
+# Arguments
-  -----
   
-  Return\n
+# Return
-  -----
 
-  Example\n
+# Example
-  -----
+```jldoctest
-  ```jldoctest
+julia> 
-  julia> 
+```
-  ```
 
-  TODO\n
+# TODO
-  -----
+  - [] update docstring
-    [] update docstring
+  - [] implement the function
-    [] implement the function
 
-  Signature\n
+# Signature
-  -----
 """
 function backpropagate(node::MCTSNode, reward::Float64)
     node.visits += 1
@@ -219,79 +194,61 @@ end
 
 """
 
-  Arguments\n
+# Arguments
-  -----
   
-  Return\n
+# Return
-  -----
 
-  Example\n
+# Example
-  -----
+```jldoctest
-  ```jldoctest
+julia> 
-  julia> 
+```
-  ```
 
-  TODO\n
+# TODO
-  -----
+  - [] update docstring
-    [] update docstring
+  - [] implement the function
-    [] implement the function
 
-  Signature\n
+# Signature
-  -----
 """
 function transition(state, action)
 
 end
 
-""" Check whether a node is a leaf node of a tree
+"""
 
-  Arguments\n
+# Arguments
-  -----
-    node::MCTSNode
-      node of a tree
   
-  Return\n
+# Return
-  -----
-    result::Bool
-      true if the node is a leaf node of a tree otherwise false
 
-  Example\n
+# Example
-  -----
+```jldoctest
-  ```jldoctest
+julia> 
-  julia> using 
+```
-  ```
 
-  TODO\n
+# TODO
-  -----
+  - [] update docstring
-    [] update docstring
+  - [x] implement the function
 
-  Signature\n
+# Signature
-  -----
 """
 isleaf(node::MCTSNode)::Bool = isempty(node.children)
 
 
 """
 
-  Arguments\n
+# Arguments
-  -----
   
-  Return\n
+# Return
-  -----
 
-  Example\n
+# Example
-  -----
+```jldoctest
-  ```jldoctest
+julia> 
-  julia> 
+```
-  ```
 
-  TODO\n
+# TODO
-  -----
+  - [] update docstring
-    [] update docstring
+  - [] implement the function
-    [] implement the function
 
-  Signature\n
+# Signature
-  -----
 """
 function executeLLMFunction()
 
@@ -303,42 +260,37 @@ end
 # ------------------------------------------------------------------------------------------------ #
 """ Search the best action to take for a given state and task 
 
-  Arguments\n
+# Arguments
-  -----
+  - `a::agent`
-    a::agent
     one of Yiem's agents
+  - `initial state`
     initial state
-      initial state
+  - `decisionMaker::Function`
-    decisionMaker::Function
     decide what action to take
-    stateValueEstimator::Function
+  - `stateValueEstimator::Function`
     assess the value of the state
-    reflector::Function
+  - `reflector::Function`
     generate lesson from trajectory and reward
-    isterminal::Function
+  - `isterminal::Function`
     determine whether a given state is a terminal state
-    n::Integer
+  - `n::Integer`
     how many times action will be sampled from decisionMaker 
-    w::Float64
+  - `w::Float64`
     exploration weight
   
-  Return\n
+# Return
-  -----
+  - `plan::Vector{Dict}`
-    plan::Vector{Dict}
     best plan
 
-  Example\n
+# Example
-  -----
+```jldoctest
-  ```jldoctest
+julia> 
-  julia> 
+```
-  ```
 
-  TODO\n
+# TODO
-  -----
   [] update docstring
 
-  Signature\n
+# Signature
-  -----
 """
 function runMCTS(
   a::T1, 

src/util.jl

@@ -293,7 +293,7 @@ end
   TODO\n
   -----
     [] update docstring
-    [WORKING] implement the function
+    [PENDING] implement the function
 
   Signature\n
   -----
@@ -332,7 +332,7 @@ end
   TODO\n
   -----
     [] update docstring
-    [WORKING] implement the function
+    [TESTING] implement the function
 
   Signature\n
   -----

test/runtest.jl

@@ -100,10 +100,6 @@ response = YiemAgent.conversation(a, Dict(:text=> "Hello, I would like a get a b
 
 
 
-
-
-
-