update

src/interface.jl

@@ -2,7 +2,7 @@ module interface
 
 export decisionMaker, evaluator, reflector, transition, query
 
-using LibPQ, DataStructures, JSON3, UUIDs, PrettyPrinting, Dates
+using LibPQ, DataStructures, JSON, UUIDs, PrettyPrinting, Dates
 using GeneralUtils, LLMMCTS
 using ..util, ..llmfunction
 
@@ -106,33 +106,6 @@ function decisionMaker(state::T1, additionalinfo, text2textInstructLLM::Function
   ; querySQLVectorDBF::Union{T2, Nothing}=nothing, maxattempt=10
   )::Dict{String, Any} where {T1<:AbstractDict, T2<:Function}
 
-  # lessonDict =
-  # if isfile("lesson.json")
-  #   lessonDict = copy(JSON3.read("lesson.json"))
-  # else
-  #   lessonDict = nothing
-  # end
-
-  # lessonDict = nothing
-
-  # lesson =
-  # if lessonDict === nothing
-  #   ""
-  # else
-  #   """
-  #   You have attempted to help the user before and failed, either because your reasoning for the 
-  #   recommendation was incorrect or your response did not exactly match the user expectation. 
-  #   The following lesson(s) give a plan to avoid failing to help the user in the same way you 
-  #   did previously. Use them to improve your strategy to help the user.
-
-  #   Here are some lessons in JSON format:
-  #   $(JSON3.write(lessonDict))
-
-  #   When providing the thought and action for the current trial, that into account these failed 
-  #   trajectories and make sure not to repeat the same mistakes and incorrect answers. 
-  #   """
-  # end
-
   systemmsg = 
   """
     You are a helpful assistant that find the data from a database to satisfy the user's question. 
@@ -188,7 +161,7 @@ similarSQL_ = "None"
    if length(state["thoughtHistory"]) == 1
      sql, distance = querySQLVectorDBF(state["thoughtHistory"]["question"])
      similarSQL_ = sql !== nothing ? sql : "None"
-   end
+   end
 
 
   for attempt in 1:maxattempt
@@ -211,7 +184,7 @@ similarSQL_ = "None"
       $workprogress
       </progress>
       <suggestion> This is your mentor's suggestion for the immediately preceding action and observation
-$(state["suggestion"])
+$(state["suggestion"])
       </suggestion>
       P.S. $errornote
     </context>
@@ -239,7 +212,7 @@ $(state["suggestion"])
 
     responsedict = nothing
     try
-      responsedict = copy(JSON3.read(response))  
+      responsedict = copy(JSON.parse(response))  
     catch
       println("\nERROR YiemAgent generatechat() failed to parse response: $response", @__FILE__, ":", @__LINE__, " $(Dates.now())")
       continue
@@ -307,10 +280,10 @@ responsedict["thoughthistory"] = state["thoughtHistory"]
     responsedict["system"] = systemmsg
     responsedict["prompt"] = prompt
     responsedict["context"] = context
-    responsedict["think"] = think
+    responsedict["think"] = think
 
     # # read sessionId
-    # sessionid = JSON3.read("/appfolder/app/sessionid.json")
+    # sessionid = JSON.parse("/appfolder/app/sessionid.json")
     # # save to filename ./log/decisionlog.txt
     # println("saving SQLLLM decisionMaker() to disk")
     # filename = "agent_decision_log_$(sessionid[:id]).json"
@@ -324,7 +297,7 @@ responsedict["thoughthistory"] = state["thoughtHistory"]
     #   end
     # else
     #   # read the file and append new data
-    #   decisionlist = copy(JSON3.read(filepath))
+    #   decisionlist = copy(JSON.parse(filepath))
     #   push!(decisionlist, responsedict)
     #   println("Appending new data to file $filepath")
     #   open(filepath, "w") do io
@@ -343,7 +316,7 @@ end
 
 #   # lessonDict =
 #   # if isfile("lesson.json")
-#   #   lessonDict = copy(JSON3.read("lesson.json"))
+#   #   lessonDict = copy(JSON.parse("lesson.json"))
 #   # else
 #   #   lessonDict = nothing
 #   # end
@@ -754,7 +727,7 @@ function evaluator(state::T1, thoughtDict, text2textInstructLLM::Function, llmFo
     # responsedict[:think] = think
 
     # # read sessionId
-    # sessionid = JSON3.read("/appfolder/app/sessionid.json")
+    # sessionid = JSON.parse("/appfolder/app/sessionid.json")
     # # save to filename ./log/decisionlog.txt
     # println("saving SQLLLM evaluator() to disk")
     # filename = "agent_evaluator_log_$(sessionid[:id]).json"
@@ -768,7 +741,7 @@ function evaluator(state::T1, thoughtDict, text2textInstructLLM::Function, llmFo
     #   end
     # else
     #   # read the file and append new data
-    #   decisionlist = copy(JSON3.read(filepath))
+    #   decisionlist = copy(JSON.parse(filepath))
     #   push!(decisionlist, responsedict)
     #   println("Appending new data to file $filepath")
     #   open(filepath, "w") do io
@@ -917,7 +890,7 @@ function reflector(config::T1, state::T2)::String where {T1<:AbstractDict, T2<:A
         error("Not valid JSON")
       end
 
-      reflectionDict = copy(JSON3.read(responseJsonStr)) 
+      reflectionDict = copy(JSON.parse(responseJsonStr)) 
 
       # check if dict has all required value
       dummya::AbstractString = reflectionDict[:reflection]
@@ -1295,7 +1268,7 @@ function query(query::T, executeSQL::Function, text2textInstructLLM::Function;
   end
   latestKey, latestInd = GeneralUtils.findHighestIndexKey(resultState[:thoughtHistory], "observation")
 action_input = "action_input_$latestInd"  # latest sql
-   sql = resultState["thoughtHistory"][action_input]
+   sql = resultState["thoughtHistory"][action_input]
   extractedTableContent = resultState["thoughtHistory"][latestKey]
 
   # add to vectorDB only if the answer is achieved and the state is terminal 
@@ -1355,7 +1328,7 @@ function makeNewState(currentstate::T1, thoughtDict::T4, rawresponse, response::
 newstate["reward"] = reward
    newstate["select"] = select
    newstate["isterminal"] = isterminal
-   newstate["rawresponse"] = rawresponse  # whatever return from action
+   newstate["rawresponse"] = rawresponse  # whatever return from action
 
   newNodeKey = GeneralUtils.uuid4snakecase()