diff --git a/src/interface.jl b/src/interface.jl
index 7a57a6f..9d5a159 100755
--- a/src/interface.jl
+++ b/src/interface.jl
@@ -451,13 +451,13 @@ function selfAwareness(a::agentReflex)
       </Your keyword memory>
       <Your job> 
       Use the following format strictly:
-      Info extraction: repeat all keywords from the latest observed result thoroughly
-      Info mapping: based on extracted info, explicitly state what each keyword could match which keyword memory's key
+      Info extraction: repeat all important info from the latest observed result thoroughly
+      Info mapping: based on extracted info, explicitly state what each info could match which keyword memory's key
       Info matching: using JSON format, what key in my memory matches which info
       </Your job>
       <Example>
       <Your earlier work>
-      The user wants to buy an electric SUV car.
+      The user wants to buy an electric SUV car under 20000 dollars.
       </Your earlier work>
       <Your keyword memory>
       {"car type": null, "color": null, "financing": null}
@@ -477,13 +477,17 @@ function selfAwareness(a::agentReflex)
                                   stopword=["/n/n", "END", "End", "Obs", "<|", "</"])
   response = split(response, "<|")[1]
   response = split(response, "</")[1]
+  response = "Info extraction:" * response
 
+  println("")
   @show selfaware_1 = response
 
   #WORKING
-  headerToDetect = ["Info extraction:", "Info matching:",]
+  headerToDetect = ["Info extraction:", "Info mapping:", "Info matching:", "Actinput"]
   headers = detectCharacters(response, headerToDetect)
-  chunkedtext = chunktext(response, headers)
+
+  # headers[1:2] is for when LLM generate more than a paire of "Info extraction" and "Info matching", discard the rest
+  chunkedtext = chunktext(response, headers[1:3]) 
   println("")
   _infomatch = chunkedtext["Info matching:"]
   _infomatch = GeneralUtils.getStringBetweenCharacters(_infomatch, '{', '}', endCharLocation="next")
@@ -527,6 +531,7 @@ function selfAwareness(a::agentReflex)
   # response = split(response, "</")[1]
 
   response = "What I know about user:" * JSON3.write(a.memory[:keyword])         # * response
+  println("")
   @show selfaware_2 = response
 
 
@@ -590,12 +595,13 @@ function actor_mistral_openorca(a::agentReflex, selfaware=nothing)
   end
 
   thought = "Thought: you should always think about what to do according to the plan (pay attention to correct numeral calculation and commonsense and do one thing at a time.)"
+  startword = "Thought:"
   if selfaware !== nothing
-    
     thought = 
-    "Self-awareness: $(JSON3.write(a.memory[:keyword]))
-    Thought: To think about your next step, reflect on your self-awareness and prioritize what you need to improve first (null) then consult your plan. (P.S. 1) let's think a single step. 2) pay attention to correct numeral calculation and commonsense.)
+    "Self-awareness: readout all info (key and value) you know and not know about the user one by one
+    Thought: based on your self-awareness, focus on what you need to improve first then follow your plan to decide what to do next. (P.S. 1) let's think a single step. 2) pay attention to correct numeral calculation and commonsense.)
     "
+    startword = "Self-awareness:"
   end
                         # your should request the missing information first before making a decision
   aboutYourself =
@@ -616,6 +622,8 @@ function actor_mistral_openorca(a::agentReflex, selfaware=nothing)
     winestocksearchresult = "\n"
   end
 
+  #WORKING I need a llm json read function
+
   prompt = 
   """
     <|system|>
@@ -628,7 +636,9 @@ function actor_mistral_openorca(a::agentReflex, selfaware=nothing)
       <Your plan>
       $(a.memory[:shortterm]["Plan 1:"])
       </Your plan>
-
+      <What I know about the user>
+      $(JSON3.write(a.memory[:keyword]))
+      </What I know about the user>
       <Your job> 
       Use the following format:
       $thought
@@ -637,14 +647,21 @@ function actor_mistral_openorca(a::agentReflex, selfaware=nothing)
       Obs: observed result of the action
       </Your job>
       <Example>
+      <What I know about the user>
+      {"car type": "SUV", "engine type": "electric motor", "price": "20k dollar", "color": null, "financing method": null}
+      </What I know about the user>
+      "Self-awareness:
+        - The user wants an electric SUV car
+        - The user budget is 20k dollars
+        - I don't know about the car color yet 
+        - I don't knoe about financing method yet
       Thought: based on self-awareness, I think he also need to know whether there are any charging station near by his house. I should search the internet to get this info.
       Act: internetsearch
       Actinput: {\"internetsearch\": \"EV charging station near Bangkok\"}
       </Example>
     </s>
     <|assistant|>
-    $work
-    "Thought: "
+    $startword
   """
 
   prompt = replace(prompt, "{toolnames}" => toolnames)
@@ -656,24 +673,22 @@ function actor_mistral_openorca(a::agentReflex, selfaware=nothing)
   chunkedtext = nothing
   latestTask = nothing
 
-  tempcounter = 0.2
-  seed = nothing
   while true  # while Thought or Act is empty, run actor again
-    # tempcounter += 0.2
-    @show tempcounter
+
     response = sendReceivePrompt(a, prompt, max_tokens=1024, temperature=0.4, timeout=300,
                                 stopword=["Thought:", "Obs:", "<|system|>", "</s>", "<|end|>"],
-                                seed=seed)
+                                seed=rand(1000000:2000000))
+    println("")
+    @show actor_raw = response
+
     response = splittext(response, ["/n/n", "END", "End","obs", "Obs", "<|im_end|>"])
     response = split(response, "<|")[1]
     response = split(response, "</")[1]
-    response = split(response, "Thought:")[end]
+    # response = split(response, "Thought:")[end]
     
     latestTask = shortMemLatestTask(a.memory[:shortterm]) +1
 
-    if occursin("Thought", response) == false
-      response = "Thought:" * response
-    end
+    response = startword * response
 
     headerToDetect = ["Plan:", "Self-awareness:", "Thought:", 
                       "Act:", "Actinput:", "Obs:", 
@@ -690,7 +705,7 @@ function actor_mistral_openorca(a::agentReflex, selfaware=nothing)
     response = replace(response, "actinput:"=>"Actinput:")
 
     println("")
-    @show response
+    @show actor_response = response
 
     headerToDetect = ["Plan $(a.attempt):",
                       "Self-awareness $latestTask:", 
diff --git a/src/type.jl b/src/type.jl
index 93df93f..12d8e6f 100644
--- a/src/type.jl
+++ b/src/type.jl
@@ -151,14 +151,13 @@ function agentReflex(
     :sommelier => 
       """
         Request the user’s input for the following info initially, and use alternative sources of information only if they are unable to provide it:
-          - occasion
+          - wine price range: ask the user
+          - wine type (Rose, White, Red, Rose, Sparkling, Dessert)  
           - food type that will be served with wine
-          - wine type (Rose, White, Red, Rose, Sparkling, Dessert)
           - wine sweetness level (dry to very sweet)
           - wine intensity level (light to full bodied)
           - wine tannin level (low to high)
           - wine acidity level (low to high)
-          - wine price range: ask the user
           - wines we have in stock (use winestock tool)
       """
   ),