update
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@@ -118,7 +118,7 @@ function decisionMaker(a::T1, state::T2)::String where {T1<:agent, T2<:AbstractD
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"Thought_2": "reasoning",
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...
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"Thought_n": "reasoning",
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"Action_1": {"action": "action to take", "input": "Action input"},
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"Action_1": {"name": "action to take", "input": "Action input"},
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"Observation_1": "result of the action"
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}
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@@ -128,13 +128,13 @@ function decisionMaker(a::T1, state::T2)::String where {T1<:agent, T2<:AbstractD
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"Thought_1": "I have many cars in my inventory suitable for several usage scenarios.",
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"Thought_2": "It would be better if I knew what the user intends to do with his car.",
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"Thought_3": "I will ask the user what is the intended usecase",
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"Action_1": {"action": "chatbox", "input": "What will you use it for?"}
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"Action_1": {"name": "chatbox", "input": "What will you use it for?"}
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}
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{
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"Question": "I'm looking for a sedan.",
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"Thought_1": "I have many types of sedans in my inventory, each with diverse features.",
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"Thought_2": "It would be easier to make a recommendation if I knew what feature the user is looking for. I should ask the user.",
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"Action_1": {"action": "chatbox", "input": "Do you have any specific feature in mind?"}
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"Action_1": {"name": "chatbox", "input": "Do you have any specific feature in mind?"}
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}
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$reflect
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@@ -311,7 +311,7 @@ function conversation(a::T, userinput::Dict) where {T<:agent}
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:storeinfo=> deepcopy(a.keywordinfo[:storeinfo]),
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:thoughtHistory=> Dict{Symbol, Any}( # contain question, thought_1, action_1, observation_1, thought_2, ...
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:question=> userinput[:text],
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:Question=> userinput[:text],
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)
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)
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bestplan = runMCTS(a, initialState, decisionMaker, stateValueEstimator, reflector,
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