update

src/ChatAgent.jl

@@ -22,11 +22,11 @@ module ChatAgent
   
 #------------------------------------------------------------------------------------------------100
   
-  """ version 0.0.1
+  """ version 0.0.5
       Todo:
-          [] add chat mechanism
+          [WORKING] add formulateUserRespond to AI tools
   
-      Change from version: 0.0.0
+      Change from version: 0.0.4
           - 
   
   """

src/interface.jl

@@ -3,7 +3,7 @@ module interface
 
 export agentReact, agentReflex,
         addNewMessage, clearMessage, removeLatestMsg, conversation, writeEvaluationGuideline,
-        grading, analyze, selfReflext, actor_mistral_openorca2
+        grading, analyze, selfReflext, actor_mistral_openorca2, formulateUserRespond
 
 using JSON3, DataStructures, Dates, UUIDs, HTTP
 using CommUtils, GeneralUtils
@@ -246,7 +246,7 @@ function chat_mistral_openorca(a::agentReflex, usermsg::String)
   return prompt
 end
 
-#WORKING mark only attemp, step
+
 function planner_mistral_openorca(a::agentReflex)
   """
     general prompt format:
@@ -299,7 +299,7 @@ function planner_mistral_openorca(a::agentReflex)
       - occasion
       - user's personal taste of wine
       - wine price range
-      - temperature at the serving location
+      - ambient temperature at the serving location
       - wines we have in stock
       You job is to provide a personalized recommendation of up to two wines based on the user's info above, and you describe the benefits of each wine in detail.
   """
@@ -380,17 +380,7 @@ function actor_mistral_openorca(a::agentReflex)
   prompt = replace(prompt, "{thinkingFormat}" => a.thinkingFormat[:actor])
   prompt = replace(prompt, "{step}" => a.step)
   
-
-  s = ""
-  for (k, v) in a.memory[:shortterm]
-    if k ∉ ["user:", "Plan 1:"]
-      s1 = "$k $v"
-      s *= s1
-      if s[end] != "\n"
-        s *= "\n"
-      end
-    end
-  end
+  s = shortMemoryToString(a.memory[:shortterm], ["user:", "Plan 1:"])
   prompt = replace(prompt, "{shorttermMemory}" => s)
 
   toolnames = ""
@@ -419,6 +409,8 @@ function actor_mistral_openorca(a::agentReflex)
   return prompt
 end
 
+
+
 """
   Chat with llm.
   
@@ -685,16 +677,16 @@ function work(a::agentReflex, usermsg::String)
         a.newplan = false
       end
       
+      # enter actor loop
       actorstate, msgToUser = actor(a)
 
       if actorstate == "chatbox"
         respond = msgToUser
         break
-      elseif actorstate == "all steps done" #WORKING add canceled during plan
+      elseif actorstate == "all steps done" ||  actorstate == "formulateUserRespond"
         println("all steps done")
 
         respond = formulateUserRespond(a)
-        error("10")
         
         a.memory[:shortterm]["Respond $mark_plan:"] = respond
         a.memory[:log]["Respond $mark:"] = respond
@@ -710,7 +702,7 @@ function work(a::agentReflex, usermsg::String)
           a.memory[:log] = OrderedDict{String, Any}()
           break
         else  # self evaluate and reflect then try again
-          analysis = analyze(a, a.memory[:shortterm])
+          analysis = analyze(a)
           @show analysis
           error(12)
           lessonwithcontext = selfReflext(a, analysis)
@@ -830,6 +822,9 @@ function actor(a::agentReflex)
         msgToUser = respond
         actorState = toolname
         break
+      elseif toolname == "formulateUserRespond"
+        actorState = "formulateUserRespond"
+        break
       else  # function call
         f = a.tools[Symbol(toolname)][:func]
         toolresult = f(a, toolinput)
@@ -948,7 +943,10 @@ function grading(a, guideline::T, text::T)  where {T<:AbstractString}
     {Evaluation} Score {}/10.
     <|im_end|>
   """
-  println("prompt 11 ", prompt)
+  println("")
+  prompt_grading = prompt
+  @show prompt_grading
+
   respond = sendReceivePrompt(a, prompt)
   println("grading respond 11 = $respond")
   _score = split(respond[end-5:end], "/")[1]
@@ -985,8 +983,7 @@ julia> report = analyze(agent, shorttermMemory)
 ```
 """
 function analyze(a)
-  
-
+  shorttermMemory = shortMemoryToString(a.memory[:shortterm], ["user:"])
   prompt =
   """
     <|im_start|>system
@@ -1092,12 +1089,7 @@ julia> report = formulateRespond(agent, shorttermMemory)
 function formulateUserRespond(a)
   stimulus = a.memory[:shortterm]["user:"]
 
-  work = ""
-  for (k, v) in a.memory[:shortterm]
-    if k ∉ ["user:",]
-      work *= "$k, $v\n"
-    end
-  end
+  work = shortMemoryToString(a.memory[:shortterm], ["user:"])
 
   prompt =
   """

src/utils.jl

@@ -3,7 +3,7 @@ module utils
 export makeSummary, sendReceivePrompt, chunktext, extractStepFromPlan, checkTotalStepInPlan,
         detectCharacters, findDetectedCharacter, extract_number, toolNameBeingCalled,
         chooseThinkingMode, conversationSummary, checkReasonableness, replaceHeaders,
-        addShortMem!, splittext
+        addShortMem!, splittext, shortMemoryToString
 
 using UUIDs, Dates, DataStructures
 using CommUtils, GeneralUtils
@@ -619,16 +619,43 @@ function replaceHeaders(text::T, headers, step::Int) where {T<:AbstractString}
 end
 
 
+""" Convert short term memory into 1 continous string.
 
+Args:
+  shortMemory = a short memory of a ChatAgent's agent
+  skiplist = a list of keys in memory you want to skip
 
+Return:
+  a short term memory in 1 countinuous string
 
+# Example
+```jldoctest
+julia> shortMemory = OrderedDict(
+                                "Thought" => "I like it.",
+                                "Act" => "chatbox",
+                                "ActInput" => "I get this one.",
+                              )
 
+julia> headers = ["user:"]
+julia> shortMemoryToString(shortMemory, headers)
+```
+"""
+function shortMemoryToString(shortMemory::OrderedDict, 
+          skiplist::Union{Array{String}, Array{Symbol}})
+  s = ""
+  for (k, v) in shortMemory
+    if k ∉ skiplist
+      s1 = "$k $v"
+      s *= s1
 
-
-
-
-
-
+      # ensure a newline seperate each sentences
+      if s[end] != "\n"
+        s *= "\n"
+      end
+    end
+  end
+  return s
+end