diff --git a/Manifest.toml b/Manifest.toml index 3469f0b..b7ca320 100644 --- a/Manifest.toml +++ b/Manifest.toml @@ -2,7 +2,7 @@ julia_version = "1.12.6" manifest_format = "2.0" -project_hash = "09bd5c43d6ad954d8be233d27fc343ea1149c0b0" +project_hash = "d8b83d09e35f3ba09b54977607be02d80ec68613" [[deps.Accessors]] deps = ["CompositionsBase", "ConstructionBase", "Dates", "InverseFunctions", "MacroTools"] @@ -760,9 +760,7 @@ version = "0.7.0" [[deps.SQLLLM]] deps = ["CSV", "DataFrames", "DataStructures", "Dates", "FileIO", "GeneralUtils", "HTTP", "JSON", "LLMMCTS", "LibPQ", "PrettyPrinting", "Random", "Revise", "StatsBase", "Tables", "URIs", "UUIDs"] -git-tree-sha1 = "93cc1ae6202279a2eb4e1dbfff706c5bc158609d" -repo-rev = "main" -repo-url = "https://git.yiem.cc/ton/SQLLLM" +path = "../SQLLLM" uuid = "2ebc79c7-cc10-4a3a-9665-d2e1d61e63d3" version = "0.2.5" @@ -983,10 +981,10 @@ uuid = "76eceee3-57b5-4d4a-8e66-0e911cebbf60" version = "1.6.1" [[deps.YiemAgent]] -deps = ["CSV", "DataFrames", "DataStructures", "Dates", "GeneralUtils", "HTTP", "JSON", "LibPQ", "NATS", "PrettyPrinting", "Random", "Revise", "SQLLLM", "Serialization", "URIs", "UUIDs"] +deps = ["CSV", "DataFrames", "DataStructures", "Dates", "GeneralUtils", "HTTP", "JSON", "LLMMCTS", "LibPQ", "NATS", "PrettyPrinting", "Random", "Revise", "Serialization", "URIs", "UUIDs"] path = "." uuid = "e012c34b-7f78-48e0-971c-7abb83b6f0a2" -version = "0.4.0" +version = "0.4.1" [[deps.Zlib_jll]] deps = ["Libdl"] diff --git a/Project.toml b/Project.toml index 11bd808..889d30f 100644 --- a/Project.toml +++ b/Project.toml @@ -30,4 +30,3 @@ HTTP = "2.4.0" JSON = "1.6.1" LLMMCTS = "0.1.5" NATS = "0.1.0" -SQLLLM = "0.2.5" diff --git a/src/interface.jl b/src/interface.jl index cc00f16..382684a 100644 --- a/src/interface.jl +++ b/src/interface.jl @@ -75,7 +75,7 @@ OrderedDict{String, Any} with 4 entries: """ function decisionMaker(a::T; recentevents::Integer=20, maxattempt=10 ) where {T<:agent} - println("\nExecuting YiemAgent decisionMaker()") + # lessonDict = copy(JSON.parsefile("lesson.json")) # lesson = @@ -108,9 +108,9 @@ function decisionMaker(a::T; recentevents::Integer=20, maxattempt=10 context = """ - + $(GeneralUtils.dict_to_string_html(a.memory["shortmem"])) - + """ @@ -269,9 +269,9 @@ function evaluator(a::T1, timeline, decisiondict, evaluateecontext context = """ - + $timeline - + $evaluateecontext @@ -320,177 +320,10 @@ function evaluator(a::T1, timeline, decisiondict, evaluateecontext println("\nEvaluator() ", @__FILE__, ":", @__LINE__, " $(Dates.now())") pprintln(Dict(responsedict)) - - # # read sessionId - # sessionid = a.id - # # save to filename ./log/decisionlog.txt - # println("saving SQLLLM evaluator() to disk") - # filename = "agent_evaluator_log_$(sessionid[:id]).json" - # filepath = "/appfolder/app/log/$filename" - # # check whether there is a file path exists before writing to it - # if !isfile(filepath) - # decisionlist = [responsedict] - # println("Creating file $filepath") - # open(filepath, "w") do io - # JSON.pretty(io, decisionlist) - # end - # else - # # read the file and append new data - # decisionlist = copy(JSON.parsefile(filepath)) - # push!(decisionlist, responsedict) - # println("Appending new data to file $filepath") - # open(filepath, "w") do io - # JSON.pretty(io, decisionlist) - # end - # end - - return responsedict + return responsedict end error("Evaluator failed to generate an evaluation, Response: \n$response\n<|End of error|>") end -# function evaluator(a::T1, timeline, decisiondict, evaluateecontext -# ) where {T1<:agent} - -# systemmsg = -# """ -# -# - You are a master sommelier of an online wine store. -# -# -# - Under your supervision, a trainee sommelier is engaging with a store customer. Each time the customer speaks, the trainee will assess the situation, determine the next course of action, and pause to await your guidance before proceeding. -# -# -# - Improve a trainee sommelier decision based on the store policy and guidelines while ensuring seamless interactions between the trainee and customers. -# -# -# - trajectory: A conversation between your trainee and the customer that have occurred up until now -# - evaluatee_context: The context that evaluatee use to make a decision -# - evaluatee_decision: The decision made by the evaluatee, consists of the following elements: -# "plan" is the trainee's plan -# "action_name" is the name of the action taken, which can be one of the available tool name. -# "action_input" is the input to the action. -# -# -# - Use only infomation provided by the store policy and guidelines as a bedrocks for your response. -# -# -# - The trainee's plan, action_name, and action_input must be logically consistent -# - The trainee's action_input should be in a proper format as specified by the tools. -# - The trainee's action name and action input should make sense. For example, if the trainee isn't finished talking, he shouldn't use the END_CONVER_GUIDELINE tool. -# -# -# 1) trajectory_evaluation: Analyze the trajectory of a solution to answer the user's original question. -# - Evaluate the correctness of each section and the overall trajectory based on the given question. -# - Provide detailed reasoning and analysis, focusing on the latest thought, action, and observation. -# - Incomplete trajectory are acceptable if the thoughts and actions up to that point are correct, even if the final answer isn't reached. -# - Do not generate additional thoughts or actions. -# 2) decision_evaluation: -# - Examine how the trainee's decisions align with the store's policies and guidelines before proceeding. -# 3) suggestion: Based store policy and guidelines, provide a suggestion for the immediate decision step only. -# 4) approval: Can be "yes" or "no". "no" if the suggestion contradict the trainee's decision; otherwise, it is "yes". - -# -# -# { -# "trajectory_evaluation": "...", -# "decision_evaluation": "...", -# "suggestion": "...", -# "approval": "...", -# } -# - -# Let's begin! -# """ -# requiredKeys = [:trajectory_evaluation, :decision_evaluation, :approval, :suggestion] -# errornote = "N/A" - -# for attempt in 1:10 -# evaluateecontext = replace(evaluateecontext, "" => "") -# evaluateecontext = replace(evaluateecontext, "" => "") - -# context = -# """ -# -# -# $timeline -# -# -# $evaluateecontext -# -# -# {plan: $(decisiondict["plan"]), action_name: $(decisiondict["action_name"]), action_input: $(decisiondict["action_input"])} -# -# P.S. $errornote -# -# """ - -# unformatPrompt = -# [ -# Dict("name" => "system", "text" => systemmsg), -# ] - -# # put in model format -# prompt = GeneralUtils.formatLLMtext(unformatPrompt, a.llmFormatName) -# # add info -# prompt = prompt * context - -# response = a.context.text2textInstructLLM(prompt; senderId=a.id) -# response = GeneralUtils.deFormatLLMtext(response, a.llmFormatName) -# response = GeneralUtils.remove_french_accents(response) -# # response = replace(response, '$'=>"USD") -# think, response = GeneralUtils.extractthink(response) - -# responsedict = nothing -# try -# responsedict = copy(JSON.parsefile(response)) -# catch -# println("\nERROR YiemAgent generatechat() failed to parse response: $response", @__FILE__, ":", @__LINE__, " $(Dates.now())") -# continue -# end - -# # check whether all answer's key points are in responsedict -# ispass, errormsg = checkAgentResponse_JSON(responsedict, requiredKeys) -# if !ispass -# errornote = errormsg -# println("\nERROR YiemAgent evaluator() $errornote --(not qualify response)> $responsedict", @__FILE__, ":", @__LINE__, " $(Dates.now())\n") -# continue -# end - -# # if accepted_as_answer ∉ ["yes", "no"] # [PENDING] add errornote into the prompt -# # error("generated accepted_as_answer has wrong format") -# # end - -# println("\nEvaluator() ", @__FILE__, ":", @__LINE__, " $(Dates.now())") -# pprintln(Dict(responsedict)) - -# # # read sessionId -# # sessionid = a.id -# # # save to filename ./log/decisionlog.txt -# # println("saving SQLLLM evaluator() to disk") -# # filename = "agent_evaluator_log_$(sessionid[:id]).json" -# # filepath = "/appfolder/app/log/$filename" -# # # check whether there is a file path exists before writing to it -# # if !isfile(filepath) -# # decisionlist = [responsedict] -# # println("Creating file $filepath") -# # open(filepath, "w") do io -# # JSON.pretty(io, decisionlist) -# # end -# # else -# # # read the file and append new data -# # decisionlist = copy(JSON.parsefile(filepath)) -# # push!(decisionlist, responsedict) -# # println("Appending new data to file $filepath") -# # open(filepath, "w") do io -# # JSON.pretty(io, decisionlist) -# # end -# # end - -# return responsedict -# end -# error("Evaluator failed to generate an evaluation, Response: \n$response\n<|End of error|>") -# end - """ Chat with llm. @@ -543,8 +376,8 @@ function conversation(a::sommelier; userinput::Union{Dict{String, Any}, JSON.Obj # thinking loop until AI wants to communicate with the user loopcount = 0 while true - @info "YiemAgent conversation() 2-0 count $loopcount" @__LINE__ loopcount += 1 + @info "YiemAgent conversation() 2-0 count $loopcount" @__LINE__ thoughtdict, _ = think(a) if thoughtdict["action_name"] ∈ ["CHAT_BOX"] @info "YiemAgent conversation() 2-1" @__LINE__ @@ -566,45 +399,6 @@ function conversation(a::sommelier; userinput::Union{Dict{String, Any}, JSON.Obj end end -# function conversation(a::Union{companion, virtualcustomer}, userinput::Dict; -# converPartnerName::Union{String, Nothing}=nothing, -# maximumMsg=50) - -# chatresponse = nothing - -# if userinput["text"] == "newtopic" -# clearhistory(a) -# return "Okay. What shall we talk about?" -# else -# # add usermsg to a.chathistory -# addNewMessage(a, "user", userinput["text"]; maximumMsg=maximumMsg) - -# # add user activity to events memory -# push!(a.memory["events"], -# eventdict(; -# event_description="the user talks to the assistant.", -# timestamp=Dates.now(), -# subject="user", -# action_name="CHAT_BOX", -# action_input=userinput["text"], -# ) -# ) -# chatresponse = generatechat(a; converPartnerName=converPartnerName, recentEventNum=20) - -# addNewMessage(a, "assistant", chatresponse; maximumMsg=maximumMsg) - -# push!(a.memory["events"], -# eventdict(; -# event_description="the assistant talks to the user.", -# timestamp=Dates.now(), -# subject="assistant", -# action_name="CHAT_BOX", -# action_input=chatresponse, -# ) -# ) -# return chatresponse -# end -# end """ # Arguments @@ -831,9 +625,9 @@ function generatechat(a::T; recentevents::Integer=20, maxattempt=10 context = """ - + $(GeneralUtils.dict_to_string_html(a.memory["shortmem"])) - + """