update

src/interface.jl

@@ -174,23 +174,59 @@ function decisionMaker(a::T)::Dict{Symbol, Any} where {T<:agent}
   # {"thought"
   # """
 
+  # systemmsg = 
+  # """
+  #   You are a helpful sommelier working for a wine store. 
+  #   Your task is to help the user choose the best wine that match the user preferences from your inventory.
+  #   You are also eager to improve your helpfulness.
+    
+  #   You must follow the following guidelines:
+  #   - Get to know how much the user willing to spend
+  #   - Get to know type of wine the user is looking for e.g. red, white, sparkling, rose, dessert, fortified
+  #   - Get to know what occasion the user is buying wine for
+  #   - Get to know what characteristics of wine the user is looking for e.g. tannin, sweetness, intensity, acidity
+  #   - Get to know what food the user will have with wine
+
+  #   At each round of conversation, the user will give you the current situation:
+  #   Context: ...
+  #   Your earlier conversation with the user: ...
+
+  #   You should then respond to the user with interleaving Thought, Plan, Action and Observation:
+  #   - thought: 
+  #       1) State your reasoning about the current situation.
+  #   - plan: Based on the current situation, what would you do to complete the task? Be specific.
+  #   - action (Must be aligned with your plan): Can be one of the following functions:
+  #       1) CHATBOX[text], which you can use to talk with the user. "text" is in verbal English. 
+  #       2) WINESTOCK[query], which you can use to find info about wine in your inventory. "query" is a search term in verbal English.
+  #   - observation: result of the action.
+
+  #   You should only respond in format as described below:
+  #   thought: ...
+  #   plan: ...
+  #   action_name: ...
+  #   action_input: ...
+  #   observation: ...
+
+  #   Let's begin!
+  # """
+
   systemmsg = 
   """
     You are a helpful sommelier working for a wine store. 
     Your task is to help the user choose the best wine that match the user preferences from your inventory.
     You are also eager to improve your helpfulness.
 
-    You must follow the following guidelines:
+    At each round of conversation, the user will give you the current situation:
+    Context: ...
+    Your earlier conversation with the user: ...
+
+    You should follow the following guidelines:
     - Get to know how much the user willing to spend
     - Get to know type of wine the user is looking for e.g. red, white, sparkling, rose, dessert, fortified
     - Get to know what occasion the user is buying wine for
     - Get to know what characteristics of wine the user is looking for e.g. tannin, sweetness, intensity, acidity
     - Get to know what food the user will have with wine
 
-    At each round of conversation, the user will give you the current situation:
-    Context: ...
-    Your earlier conversation with the user: ...
-
     You should then respond to the user with interleaving Thought, Plan, Action and Observation:
     - thought: 
         1) State your reasoning about the current situation.
@@ -213,7 +249,7 @@ function decisionMaker(a::T)::Dict{Symbol, Any} where {T<:agent}
   usermsg =
   """
   Context: None
-  Your earlier conversation with the user: $(chatHistoryToString(a))
+  Your earlier conversation with the user: $(vectorOfDictToText(a.chathistory))
   """
 
   _prompt = 
@@ -902,10 +938,11 @@ function conversation(a::T, userinput::Dict) where {T<:agent}
     # add usermsg to a.chathistory
     addNewMessage(a, "user", userinput[:text])
 
-    thought = think(a)
+    think(a)
 
     # thought will be added to chat model via context
-    chatresponse = generatechat(a, thought)
+    chatresponse = generatechat(a)
+    addNewMessage(a, "assistant", chatresponse)
 
     return chatresponse
   end
@@ -1024,8 +1061,12 @@ function think(a::T) where {T<:agent}
   isterminal::Bool = haskey(response, :isterminal) ? response[:isterminal] : false
   errormsg::Union{AbstractString, Nothing} = haskey(response, :errormsg) ? response[:errormsg] : nothing
   success::Bool = haskey(response, :success) ? response[:success] : false
-  a.shortmem
+
-  return result
+  if actionname == "CHATBOX"
+    a.memory[:chatbox] = result
+  else  
+    push!(a.memory[:shortmem], Dict(Symbol(actionname)=> result))
+  end
 end
 
 
@@ -1049,27 +1090,22 @@ julia>
 
 # Signature
 """
-function generatechat(a::T1, input::T2) where {T1<:agent, T2<:AbstractString}
+function generatechat(a::T) where {T<:agent}
   systemmsg = 
   """
   You are a helpful sommelier working for a wine store. 
   Your task is to help the user choose the best wine that match the user preferences from your inventory.
-  You are also eager to improve your helpfulness.
 
-  You must follow the following guidelines:
+  At each round of conversation, the user will give you the current situation:
-  - Get to know how much the user willing to spend
-  - Get to know type of wine the user is looking for e.g. red, white, sparkling, rose, dessert, fortified
-  - Get to know what occasion the user is buying wine for
-  - Get to know what characteristics of wine the user is looking for e.g. tannin, sweetness, intensity, acidity
-  - Get to know what food the user will have with wine
-
-  At each round of conversation, the user will give you:
   Context: ...
   Your thoughts: Your current thinking in your mind
   Your earlier conversation with the user: ...
 
+  You must follow the following guidelines (if the user interrupts, prioritize the user):
+  - Do not recommend specific wine before you checked your inventory.
+
   You should then respond to the user with:
-  - chat: what do you want to say to the user
+  - chat: what do you want to say to the user based on the current situation
 
   You should only respond in format as described below:
   chat: ...
@@ -1077,11 +1113,13 @@ function generatechat(a::T1, input::T2) where {T1<:agent, T2<:AbstractString}
   Let's begin!
   """
 
+  context = length(a.memory[:shortmem]) > 0 ? vectorOfDictToText(a.memory[:shortmem], withkey=false) : "None"
+
   usermsg =
   """
-  Context: None
+  Context: $context
-  Your thoughts: $input
+  Your earlier conversation with the user: $(vectorOfDictToText(a.chathistory))
-  Your earlier conversation with the user: $(chatHistoryToString(a))
+  Your thoughts: $(a.memory[:chatbox])
   """
 
   _prompt = 
@@ -1099,31 +1137,31 @@ function generatechat(a::T1, input::T2) where {T1<:agent, T2<:AbstractString}
 
   for attempt in 1:5
     try
-      response = text2textInstructLLM(prompt)
+      response = a.text2textInstructLLM(prompt)
       responsedict = GeneralUtils.textToDict(response,
             ["chat"], 
             rightmarker=":", symbolkey=true)
 
-      # check if dict has all required value
+      for i ∈ [:chat]
-      evaluationtext::AbstractString = responsedict[:evaluation]
+        if length(JSON3.write(responsedict[i])) == 0
-      responsedict[:score] = parse(Int, responsedict[:score]) # convert string "5" into integer 5
+          error("$i is empty ", @__LINE__)
-      score::Integer = responsedict[:score]
+        end
-      accepted_as_answer::AbstractString = responsedict[:accepted_as_answer]
-      suggestion::AbstractString = responsedict[:suggestion]
-
-      # add to state here instead to in transition() because the latter causes julia extension crash (a bug in julia extension)
-      state[:evaluation] = responsedict[:evaluation] 
-      state[:evaluationscore] = responsedict[:score] 
-      state[:accepted_as_answer] = responsedict[:accepted_as_answer]
-      state[:suggestion] = responsedict[:suggestion]
-
-      # mark as terminal state when the answer is achieved
-      if accepted_as_answer == "Yes"
-        state[:isterminal] = true
-        state[:reward] = 1
       end
 
-      return responsedict[:score]
+      # check if there are more than 1 key per categories
+      for i ∈ [:chat]
+        matchkeys = GeneralUtils.findMatchingDictKey(responsedict, i)
+        if length(matchkeys) > 1
+          error("generatechat has more than one key per categories")
+        end
+      end
+
+      result = responsedict[:chat]
+
+      #[WORKING] delete chat
+      a.memory[:chatbox] = ""
+
+      return result
     catch e
       io = IOBuffer()
       showerror(io, e)
@@ -1134,7 +1172,7 @@ function generatechat(a::T1, input::T2) where {T1<:agent, T2<:AbstractString}
       println("")
     end
   end
-  error("evaluator failed to generate an evaluation")
+  error("generatechat failed to generate an evaluation")
 
 
 

src/type.jl

@@ -93,7 +93,7 @@ mutable struct sommelier <: agent
 
   """
   chathistory::Vector{Dict{Symbol, Any}}
-  shortmem::Dict{Symbol, Any}
+  memory::Dict{Symbol, Any}
 
   # communication function
   text2textInstructLLM::Function
@@ -105,7 +105,7 @@ function sommelier(
   name::String= "Assistant",
   id::String= string(uuid4()),
   maxHistoryMsg::Integer= 20,
-  chathistory::Vector{Dict{Symbol, Any}} = Vector{Dict{Symbol, Any}}(),
+  chathistory::Vector{Dict{Symbol, String}} = Vector{Dict{Symbol, String}}(),
   )
 
   tools = Dict( # update input format
@@ -127,13 +127,18 @@ function sommelier(
       # ),
     )
 
+  memory = Dict{Symbol, Any}(
+              :chatbox=> "",
+              :shortmem=> Vector{Dict{Symbol, String}}()
+            )
+
   newAgent = sommelier(
     name,
     id,
     tools,
     maxHistoryMsg,
     chathistory,
-    Dict{Symbol, Any}(),
+    memory,
     text2textInstructLLM,
     )
   

src/util.jl

@@ -1,6 +1,6 @@
 module util
 
-export clearhistory, addNewMessage, chatHistoryToString
+export clearhistory, addNewMessage, vectorOfDictToText
 
 using UUIDs, Dates, DataStructures, HTTP, MQTTClient, JSON3
 using GeneralUtils
@@ -113,15 +113,43 @@ function addNewMessage(a::T1, name::String, text::T2;
 end
 
 
-function chatHistoryToString(a)
+"""
-  chatHistoryStr = ""
+
-  for i in a.chathistory
+# Arguments
-    name = i[:name]
+  - `v::Integer`
-    text = i[:text]
+    dummy variable
-    chatHistoryStr *= "$name> $text"
+    
+# Return
+
+# Example
+```jldoctest
+julia> 
+```
+
+# TODO
+  - [] update docstring
+  - [x] implement the function
+
+# Signature
+"""
+function vectorOfDictToText(vecd::Vector; withkey=true)
+  text = ""
+
+  if withkey
+    for d in vecd
+      name = d[:name]
+      _text = d[:text]
+      text *= "$name> $_text \n"
+    end
+  else
+    for d in vecd
+      for (k, v) in d
+        text *= "$v \n"
+      end
+    end
   end
 
-  return chatHistoryStr
+  return text
 end
 
 
@@ -131,9 +159,6 @@ end
 
 
 
-
-
-
 # """ Convert a single chat dictionary into LLM model instruct format.
 
 # # Llama 3 instruct format example

test/runtest.jl

@@ -67,11 +67,11 @@ end
 response = YiemAgent.conversation(a, Dict(:text=> "Hello, I would like a get a bottle of wine."))
 println("---> YiemAgent: ", response)
 
-response = YiemAgent.conversation(a, Dict(:text=> "I'm having a graduation party this evening. I'll pay at most 30 bucks.",
+response = YiemAgent.conversation(a, Dict(:text=> "I'm having a graduation party this evening. I'll pay at most 30 bucks."))
-                                          :select=> nothing,
+response = YiemAgent.conversation(a, Dict(:text=> "What type of wine do you recommend for a celebration?"))
-                                          :reward=> 0,
+
-                                          :isterminal=> false,
+
-                                ) )
+
 println("---> YiemAgent: ", response)