update

src/interface.jl

@@ -644,7 +644,8 @@ function work(a::agentReflex, usermsg::String)
       elseif actorstate == "all steps done"
         println("all steps done")
         #WORKING give answer to the question
-        respond = formulateRespond()
+        respond = formulateRespond(a, a.memory[:shortterm])
+        a.memory[:shortterm] *= "Respond: $respond\n"
 
         #TODO evaluate. if score < 8/10 try again.
         headerToDetect = ["user:", "assistant:", ]
@@ -652,13 +653,13 @@ function work(a::agentReflex, usermsg::String)
         chunkedtext = chunktext(a.memory[:shortterm], headers)
         stimulus = chunkedtext["user:"]
         guideline = writeEvaluationGuideline(a, stimulus)
-        score = grading(a, guideline, a.memory[:shortterm])
+        @show guideline
+        score = grading(a, guideline, respond)
         @show score
         if score >= 8 # good enough answer
           @show a.memory[:shortterm]
-          a.memory[:shortterm] = ""
-          a.thoughtlog = ""
-          respond = msgToUser
+          # a.memory[:shortterm] = ""
+          # a.thoughtlog = ""
           break
         else  # self evaluate and reflect then try again
           report = analyze(a, a.memory[:shortterm])
@@ -831,7 +832,7 @@ julia> score = grading(agent, guideline, shorttermMemory)
 2
 ```
 """
-function grading(a, guideline::T, shorttermMemory::T)  where {T<:AbstractString}
+function grading(a, guideline::T, text::T)  where {T<:AbstractString}
   prompt =
   """
     <|im_start|>system
@@ -839,21 +840,21 @@ function grading(a, guideline::T, shorttermMemory::T)  where {T<:AbstractString}
     chatbox: Useful for when you need to ask a customer for more context. Input should be a conversation to customer.
     wikisearch: Useful for when you need to search an encyclopedia Input is keywords and not a question.
 
-    Evaluation guideline:
     $guideline
 
-    Your work:
-    $shorttermMemory
+    Your respond: $text
 
     You job are:
-    1. Evaluate your work using the evaluation guideline.
-    2. Give yourself a score out of 10 for your work. 
-      Use the following format to answer: Score {}/10.
+    1. Evaluate your respond using the evaluation guideline and an example respond.
+    2. Give yourself a score out of 10 for your respond. 
+
+    Use the following format to answer: 
+    {Evaluation} Score {}/10.
     <|im_end|>
   """
-
+  println("prompt 11 ", prompt)
   respond = sendReceivePrompt(a, prompt)
-  println("grading = ", respond)
+  println("grading respond 11 = $respond")
   _score = split(respond[end-5:end], "/")[1]
   _score = split(_score, " ")[end]
   score = parse(Int, _score)
@@ -967,10 +968,59 @@ function selfReflext(a, report::T) where {T<:AbstractString}
 end
 
 
-""" 
-""" #WORKING
+""" Formulate a respond from work for user's stimulus.
+
+Args:
+  a, one of ChatAgent's agent.
+
+Return:
+  A respond for user's stimulus.
+
+# Example
+
+```jldoctest
+julia> using ChatAgent, CommUtils
+julia> agent = ChatAgent.agentReflex("Jene")
+julia> shorttermMemory = 
+        "
+        user: What's AMD latest product?
+        assistant:   Plan 1: To provide the user with information about AMD's latest product, I will search for the most recent product release from AMD.
+          1. Search for \"AMD latest product\" using wikisearch tool.
+          2. Identify the most recent product release mentioned in the search results.
+          3. Provide the user with the name of the latest product.
+          
+          Thought 1: The user wants to know about the latest AMD products, so I should use the wikisearch tool to find information on this topic.
+          Act 1: wikisearch
+          ActInput 1: \"AMD latest product\"
+          Obs 1: No info available."
+julia> report = formulateRespond(agent, shorttermMemory)
+```
+"""
 function formulateRespond(a, shorttermMemory::T)  where {T<:AbstractString}
-  
+  prompt =
+  """
+    <|im_start|>system
+    You have access to the following tools:
+    chatbox: Useful for when you need to ask a customer for more context. Input should be a conversation to customer.
+    wikisearch: Useful for when you need to search an encyclopedia Input is keywords and not a question.
+
+    Symbol:
+    Stimulus: the input user gives to you and you must respond
+    Plan: a plan
+    Thought: your thought
+    Act: the action you took
+    ActInput: the input to the action
+    Obs: the result of the action
+
+    Your work:
+    $shorttermMemory
+    
+    From your work, formulate a respond for user's stimulus.
+    <|im_end|>
+  """
+
+  respond = sendReceivePrompt(a, prompt)
+  return respond
 end
 
 

src/type.jl

@@ -95,7 +95,7 @@ function agentReflex(
     :planner=> 
       """Use the following format:
       Stimulus: the input user gives to you and you must respond
-      Plan: first you should always think about the stimulus and the info you have thoroughly then extract and devise a step by step plan to respond (pay attention to correct numeral calculation and commonsense).
+      Plan: first you should always think about the stimulus and the info you have thoroughly then extract and devise a step by step plan to prepare a respond (pay attention to correct numeral calculation and commonsense).
       """,
     :actor=> 
       """Use the following format:

src/utils.jl

@@ -28,7 +28,7 @@ function makeSummary(a::T1, input::T2) where {T1<:agent, T2<:AbstractString}
     <|im_start|>assistant
   
   """
-  prompt = replace(prompt, "{input}" => usermsg)
+  prompt = replace(prompt, "{input}" => input)
   result = sendReceivePrompt(a, prompt)
   result = GeneralUtils.getStringBetweenCharacters(result, "{", "}")
   if result == "yes"