update

src/interface.jl

@@ -320,21 +320,57 @@ function reflector()
   """
   You are an advanced reasoning agent that can improve based on self refection. 
   You will be given the information related to the previous help you've done for a user.
-
+  You were unsuccessful in helping the user either because you guessed the wrong answer with Finish[answer], or you used up your set number of reasoning steps.
-
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-  You were unsuccessful in helping the user either because you guessed the wrong answer with Finish[<answer>], or you used up your set number of reasoning steps.
-
-
-
   In a few sentences, Diagnose a possible reason for failure and devise a new, concise, high level plan that aims to mitigate the same failure. 
   Use complete sentences.  
   
   Here are some examples:
   Previous Trial:
+  {
+    "question": "Hello, I would like a get a bottle of wine", 
+    "thought_1": "A customer wants to buy a bottle of wine. Before making a recommendation, I need to know more about their preferences.", 
+    "action_1": {"name": "chatbox", "input": "What is the occasion for which you're buying this wine?"},
+    "observation_1": "We are holding a wedding party",
+
+    "thought_2": "A wedding party, that's a great occasion! The customer might be looking for a celebratory drink. Let me ask some more questions to narrow down the options.",
+    "action_2": {"name": "chatbox", "input": "What type of food will you be serving at the wedding?"},
+    "observation_2": "It will be Thai dishes.", 
+
+    "thought_3": "With Thai food, I should recommend a wine that complements its spicy and savory flavors. And since it's a celebratory occasion, the customer might prefer a full-bodied wine.",
+    "action_3": {"name": "chatbox", "input": "What is your budget for this bottle of wine?"},
+    "observation_3": "I would spend up to 50 bucks.",
+
+    "thought_4": "Now that I have some more information, it's time to narrow down the options.", 
+    "action_4": {"name": "winestock", "input": "red wine with full body, pairs well with spicy food, budget \$50"},
+    "observation_4": "I found the following wines in our stock: \n{\n  1: El Enemigo Cabernet Franc 2019\n2: Tantara Chardonnay 2017\n\n}\n", 
+
+    "thought_5": "Now that I have a list of potential wines, I need to know more about the customer's taste preferences.",
+    "action_5": {"name": "chatbox", "input": "What type of wine characteristics are you looking for? (e.g. t.e.g. tannin level, sweetness, intensity, acidity)"},
+    "observation_5": "I like full-bodied Red wine with low tannin.", 
+
+    "thought_6": "Now that I have more information about the customer's preferences, it's time to make a recommendation.",
+    "action_6": {"name": "recommendbox", "input": "El Enemigo Cabernet Franc 2019"},
+    "observation_6": "I don't like the one you recommend. I want dry wine."
+  }
+  Reflection: I searched one of the prime ministers involved in the signing, then attemted to answer right away. I should have searched each of the prime ministers, then looked up 'death' on each of their pages in order to get more information before answering.
+
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+
   Question: The Rome Protocols were signed by three Prime Ministers one of which was assassinated as part of what?
   Thought 1: I need to search Rome Protocols, find the three Prime Ministers, then find what they were assassinated as part of.
   Action 1: Search[Rome Protocols]
@@ -386,6 +422,52 @@ function reflector()
   Previous trial:
   {trajectory}Reflection:
   """
+
+  # apply LLM specific instruct format
+  externalService = a.config[:externalservice][:text2textinstruct]
+  llminfo = externalService[:llminfo]
+  prompt = 
+  if llminfo[:name] == "llama3instruct"
+    formatLLMtext_llama3instruct("system", _prompt)
+  else
+    error("llm model name is not defied yet $(@__LINE__)")
+  end
+
+  msgMeta = GeneralUtils.generate_msgMeta(
+    a.config[:externalservice][:text2textinstruct][:mqtttopic],
+    senderName= "progressValueEstimator",
+    senderId= a.id,
+    receiverName= "text2textinstruct",
+    mqttBroker= a.config[:mqttServerInfo][:broker],
+    mqttBrokerPort= a.config[:mqttServerInfo][:port],
+  )
+
+  outgoingMsg = Dict(
+    :msgMeta=> msgMeta,
+    :payload=> Dict(
+      :text=> prompt,
+      :kwargs=> Dict(
+        :max_tokens=> 512,
+        :stop=> ["<|eot_id|>"],
+        )
+      )
+    )
+
+  _response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg)
+  _thoughtJsonStr = _response[:response][:text]
+
+  # expectedJsonExample =
+  # """
+  # Here is an expected JSON format:
+  # {"evaluation": "...", "score": "..."}
+  # """
+  # resultJsonStr = jsoncorrection(a, _thoughtJsonStr, expectedJsonExample)
+  # resultDict = copy(JSON3.read(resultJsonStr)) 
+
+  # return resultDict[:evaluation], resultDict[:score]
+
+
+  return _thoughtJsonStr
 end
 
 

test/test_1.jl

@@ -137,7 +137,7 @@ result = GeneralUtils.sendMqttMsg(outgoingMsg)
 outgoingMsg = Dict(
   :msgMeta=> msgMeta,
   :payload=> Dict(
-    :text=> "Yep.",
+    :text=> "I don't have any thing specific",
     :select=> nothing,
     :reward=> 0,
     :isterminal=> false,

test/test_2.jl

@@ -0,0 +1,130 @@
+using Revise      # remove when this package is completed
+using YiemAgent, GeneralUtils, JSON3, MQTTClient, Dates, UUIDs, DataStructures
+using Base.Threads
+
+# ---------------------------------------------- 100 --------------------------------------------- #
+
+config = copy(JSON3.read("config.json"))
+
+instanceInternalTopic = config[:serviceInternalTopic][:mqtttopic] * "/1" 
+
+client, connection = MakeConnection(config[:mqttServerInfo][:broker], 
+                                    config[:mqttServerInfo][:port])
+
+receiveUserMsgChannel = Channel{Dict}(4)
+receiveInternalMsgChannel = Channel{Dict}(4)
+
+msgMeta = GeneralUtils.generate_msgMeta(
+  "N/A", 
+  replyTopic = config[:servicetopic][:mqtttopic]  # ask frontend reply to this instance_chat_topic
+  )  
+
+agentConfig = Dict(
+  :mqttServerInfo=> config[:mqttServerInfo],
+  :receivemsg=>  Dict(
+    :prompt=> config[:servicetopic][:mqtttopic], # topic to receive prompt i.e. frontend send msg to this topic
+    :internal=> instanceInternalTopic,
+  ),
+  :externalservice=> config[:externalservice],
+)
+
+# Instantiate an agent
+tools=Dict( # update input format
+    "askbox"=> Dict(
+      :description => "<askbox tool description>Useful for when you need to ask the user for more context. Do not ask the user their own question.</askbox tool description>",
+      :input => """<input>Input is a text in JSON format.</input><input example>{\"Q1\": \"How are you doing?\", \"Q2\": \"How may I help you?\"}</input example>""",
+      :output => "" ,
+      :func => nothing,
+    ),
+    # "winestock"=> Dict(
+    #   :description => "<winestock tool description>A handy tool for searching wine in your inventory that match the user preferences.</winestock tool description>",
+    #   :input => """<input>Input is a JSON-formatted string that contains a detailed and precise search query.</input><input example>{\"wine type\": \"rose\", \"price\": \"max 35\", \"sweetness level\": \"sweet\", \"intensity level\": \"light bodied\", \"Tannin level\": \"low\", \"Acidity level\": \"low\"}</input example>""",
+    #   :output => """<output>Output are wines that match the search query in JSON format.""",
+    #   :func => ChatAgent.winestock,
+    # ),
+    "finalanswer"=> Dict(
+      :description => "<tool description>Useful for when you are ready to recommend wines to the user.</tool description>",
+      :input => """<input format>{\"finalanswer\": \"some text\"}.</input format><input example>{\"finalanswer\": \"I recommend Zena Crown Vista\"}</input example>""",
+      :output => "" ,
+      :func => nothing,
+    ),
+  )
+
+  a = YiemAgent.sommelier(
+    receiveUserMsgChannel,
+    receiveInternalMsgChannel,
+    agentConfig, 
+    name= "assistant",
+    id= "testingSessionID",  # agent instance id
+    tools=tools,
+  )
+
+
+input =
+OrderedDict{Symbol, Any}(
+  :question => "Hello, I would like a get a bottle of wine", 
+  :thought_1 => "A customer wants to buy a bottle of wine. Before making a recommendation, I need to know more about their preferences.", 
+  :action_1 => Dict{Symbol, Any}(
+    :name => "chatbox", 
+    :input => "What is the occasion for which you're buying this wine?"
+    ), 
+  :observation_1 => "We are holding a wedding party", 
+  
+  :thought_2 => "A wedding party, that's a great occasion! The customer might be looking for a celebratory drink. Let me ask some more questions to narrow down the options.", 
+  :action_2 => Dict{Symbol, Any}(
+    :name => "chatbox", 
+    :input => "What type of food will you be serving at the wedding?"
+    ), 
+  :observation_2 => "It will be Thai dishes.", 
+
+  :thought_3 => "With Thai food, I should recommend a wine that complements its spicy and savory flavors. And since it's a celebratory occasion, the customer might prefer a full-bodied wine.", 
+  :action_3 => Dict{Symbol, Any}(
+    :name => "chatbox", 
+    :input => "What is your budget for this bottle of wine?"
+    ), 
+  :observation_3 => "I would spend up to 50 bucks.", 
+
+  :thought_4 => "Now that I have some more information, it's time to narrow down the options.", 
+  :action_4 => Dict{Symbol, Any}(
+    :name => "winestock", 
+    :input => "red wine with full body, pairs well with spicy food, budget \$50"), 
+  :observation_4 => "I found the following wines in our stock: \n{\n  1: El Enemigo Cabernet Franc 2019\n2: Tantara Chardonnay 2017\n\n}\n", 
+  
+  :thought_5 => "Now that I have a list of potential wines, I need to know more about the customer's taste preferences.", 
+  :action_5 => Dict{Symbol, Any}(
+    :name => "chatbox", 
+    :input => "What type of wine characteristics are you looking for? (e.g. t.e.g. tannin level, sweetness, intensity, acidity)"
+    ), 
+  :observation_5 => "I like full-bodied Red wine with low tannin.", 
+  
+  :thought_6 => "Now that I have more information about the customer's preferences, it's time to make a recommendation.", 
+  :action_6 => Dict{Symbol, Any}(
+    :name => "recommendbox", 
+    :input => "El Enemigo Cabernet Franc 2019"
+    ), 
+  :observation_6 => "I don't like the one you recommend. I want dry wine."
+  )
+
+
+
+
+result = YiemAgent.reflector(a, input)
+
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