update

src/interface.jl

@@ -588,7 +588,7 @@ function conversation(a::agentReflex, usermsg::String; attemptlimit::Int=3)
   if a.thinkingmode == :no_thinking
     a.earlierConversation = conversationSummary(a)  #TODO should be long conversation before use summary because it leaves out details
     _ = addNewMessage(a, "user", usermsg)
-    prompt = chat_mistral_openorca(a, usermsg)  #TODO rewrite this function
+    prompt = chat_mistral_openorca(a, usermsg)
     @show prompt
     respond = sendReceivePrompt(a, prompt)
     respond = split(respond, "<|im_end|>")[1]
@@ -604,6 +604,8 @@ end
 
 
 function work(a::agentReflex, usermsg::String)
+  respond = nothing
+
   if a.thinkingmode == :new_thinking
     a.earlierConversation = conversationSummary(a)
     _ = addNewMessage(a, "user", usermsg)
@@ -618,44 +620,65 @@ function work(a::agentReflex, usermsg::String)
   while true  # Work loop
     # plan
     a.attempt += 1
-    if a.attempt <= a.attemptlimit
-
-    else  # attempt limit reached
-
-    end
     @show a.attempt
     @show usermsg
-    logmsg = "user: $usermsg\n"
-    a.memory[:shortterm] *= logmsg
+    if a.attempt <= a.attemptlimit
+      logmsg = "user: $usermsg\n"
+      a.memory[:shortterm] *= logmsg
 
-    toolname = nothing
-    toolinput = nothing
-    prompt = planner_mistral_openorca(a, usermsg)
-    @show prompt
-    respond = sendReceivePrompt(a, prompt)
-    plan = split(respond, "<|im_end|>")[1]
-    plan = split(plan, "Response:")[1]
-    _plan = replace(plan, "Plan:"=>"Plan $(a.attempt):")
-    logmsg = "assistant: $_plan\n"
-    a.memory[:shortterm] *= logmsg
-    actorstate, msgToUser = actor(a, plan)
-    #WORKING
-    if actorstate == "chatbox"
-      return msgToUser
-    elseif actorstate == "all steps done"
-      error(">>>>>>>>>> ", a.memory[:shortterm])
-      # evaluationGuideline = writeEvaluationGuideline(a, )
-      break
-    else
-      error("undefied condition, actorstate $actorstate $(@__LINE__)")
+      toolname = nothing
+      toolinput = nothing
+      prompt = planner_mistral_openorca(a, usermsg)
+      @show prompt
+      respond = sendReceivePrompt(a, prompt)
+      plan = split(respond, "<|im_end|>")[1]
+      plan = split(plan, "Response:")[1]
+      _plan = replace(plan, "Plan:"=>"Plan $(a.attempt):")
+      logmsg = "assistant: $_plan\n"
+      a.memory[:shortterm] *= logmsg
+      actorstate, msgToUser = actor(a, plan)
+
+      if actorstate == "chatbox"
+        respond = msgToUser
+        break
+      elseif actorstate == "all steps done"
+        println("all steps done")
+        #WORKING give answer to the question
+        respond = formulateRespond()
+
+        #TODO evaluate. if score < 8/10 try again.
+        headerToDetect = ["user:", "assistant:", ]
+        headers = detectCharacters(a.memory[:shortterm], headerToDetect)
+        chunkedtext = chunktext(a.memory[:shortterm], headers)
+        stimulus = chunkedtext["user:"]
+        guideline = writeEvaluationGuideline(a, stimulus)
+        score = grading(a, guideline, a.memory[:shortterm])
+        @show score
+        if score >= 8 # good enough answer
+          @show a.memory[:shortterm]
+          a.memory[:shortterm] = ""
+          a.thoughtlog = ""
+          respond = msgToUser
+          break
+        else  # self evaluate and reflect then try again
+          report = analyze(a, a.memory[:shortterm])
+          @show report
+          lesson = selfReflext(a, report)
+          @show lesson
+          error(">>>>>>>>>>")
+        end
+      else
+        error("undefied condition, actorstate $actorstate $(@__LINE__)")
+        break
+      end
+    else  #TODO attempt limit reached, force AI to answer
+      error("attempt limit reach")
       break
     end
-
-
-    
-
-    
   end
+
+  # good enough answer
+  return  respond
 end
 
 
@@ -678,10 +701,11 @@ end
 """
 function actor(a::agentReflex, plan::T) where {T<:AbstractString}
   actorState = nothing
+  msgToUser = nothing
+
   @show plan
   totalsteps = checkTotalStepInPlan(a, plan)
   
-  msgToUser = nothing
   a.step = 0
   while true  # Actor loop
     a.step += 1
@@ -713,22 +737,21 @@ function actor(a::agentReflex, plan::T) where {T<:AbstractString}
         _ = addNewMessage(a, "assistant", respond)
         msgToUser = respond
         actorState = toolname
-        error("actor done 0")
         break
       else  # function call
         f = a.tools[Symbol(toolname)][:func]
-        result = f(toolinput)
-        result = "\nObs $(a.step): $result\n"
-        a.memory[:shortterm] *= result
+        result = f(a, toolinput)
+        _result = "\nObs $(a.step): $result\n"
+        a.memory[:shortterm] *= _result
+        msgToUser = result
       end
     else  #TODO finish all steps
       actorState = "all steps done"
       msgToUser = nothing
-      error("actor done 2")
       break
     end
   end
-  error("actor done 3")
+
   return actorState, msgToUser
 end
 
@@ -830,7 +853,10 @@ function grading(a, guideline::T, shorttermMemory::T)  where {T<:AbstractString}
   """
 
   respond = sendReceivePrompt(a, prompt)
-  score = parse(Int, respond[end-4:end-3])
+  println("grading = ", respond)
+  _score = split(respond[end-5:end], "/")[1]
+  _score = split(_score, " ")[end]
+  score = parse(Int, _score)
   return score
 end
 
@@ -941,8 +967,11 @@ function selfReflext(a, report::T) where {T<:AbstractString}
 end
 
 
-
-
+""" 
+""" #WORKING
+function formulateRespond(a, shorttermMemory::T)  where {T<:AbstractString}
+  
+end