update
This commit is contained in:
314
src/interface.jl
314
src/interface.jl
@@ -159,11 +159,11 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
|
||||
- If you are unable to find the requested information, kindly inform the user, "The current data in our database does not provide the specific answer to your query".
|
||||
- Text information in the database usually stored in lower case. If your search returns empty, try using lower case to search.
|
||||
|
||||
You should then respond to the user with interleaving Understanding, Reasoning, Plan, Action:
|
||||
1) Comprehension:
|
||||
- State your comprehension about the current situation.
|
||||
2) Plan: Given the current circumstances, outline a detailed, step-by-step plan to accomplish the task. Be specific.
|
||||
3) Action_name (Must be aligned with your plan): Can be one of the following functions:
|
||||
You should then respond to the user with interleaving Comprehension, Plan, Action_name, Action_input:
|
||||
Comprehension: state your comprehension about the current situation.
|
||||
Plan: Given the current circumstances, outline a detailed, step-by-step plan to accomplish the task. Be specific.
|
||||
Action_name: (Typically corresponds to the execution of the first step in your plan)
|
||||
Can be one of the following function names:
|
||||
- RUNSQL, which you can use to execute SQL against the database. Action_input for this function must be a single SQL query to be executed against the database.
|
||||
For more effective text search, it's necessary to use case-insensitivity and the ILIKE operator.
|
||||
Do not wrap the SQL as it will be executed against the database directly and SQL must be ended with ';'.
|
||||
@@ -195,6 +195,8 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
|
||||
similarSQL_ = sql !== nothing ? sql : "None"
|
||||
end
|
||||
|
||||
header = ["Comprehension:", "Plan:", "Action_name:", "Action_input:"]
|
||||
dictkey = ["comprehension", "plan", "action_name", "action_input"]
|
||||
|
||||
for attempt in 1:10
|
||||
QandA = generatequestion(state, context, text2textInstructLLM; similarSQL=similarSQL_)
|
||||
@@ -252,37 +254,31 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
|
||||
continue
|
||||
end
|
||||
|
||||
header = ["Comprehension:", "Plan:", "Action_name:", "Action_input:"]
|
||||
dictkey = ["comprehension", "plan", "action_name", "action_input"]
|
||||
|
||||
# detect if there are more than 1 key per categories
|
||||
wordcount = GeneralUtils.countGivenWords(response, header)
|
||||
duplicateKeywordFlag = false
|
||||
for (i, v) in enumerate(wordcount)
|
||||
keyword = header[i]
|
||||
keywordNumber = v
|
||||
if keywordNumber > 1
|
||||
errornote = "\nSQL query has duplicated keyword, $keyword"
|
||||
println("Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
duplicateKeywordFlag = true
|
||||
break
|
||||
end
|
||||
end
|
||||
duplicateKeywordFlag == true ? continue : nothing
|
||||
# # detect if there are more than 1 key per categories
|
||||
# wordcount = GeneralUtils.countGivenWords(response, header)
|
||||
# duplicateKeywordFlag = false
|
||||
# for (i, v) in enumerate(wordcount)
|
||||
# keyword = header[i]
|
||||
# keywordNumber = v
|
||||
# if keywordNumber > 1
|
||||
# errornote = "\nSQL query has duplicated keyword, $keyword"
|
||||
# println("Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
# duplicateKeywordFlag = true
|
||||
# break
|
||||
# end
|
||||
# end
|
||||
# duplicateKeywordFlag == true ? continue : nothing
|
||||
|
||||
# check whether response has all header
|
||||
kw = []
|
||||
# use for loop and detect_keyword function to get the exact variation of each keyword in the text then push to kw list
|
||||
for keyword in header
|
||||
detected = GeneralUtils.detect_keyword(keyword, response)
|
||||
push!(kw, detected)
|
||||
end
|
||||
if nothing ∈ kw
|
||||
println("Some keywords are missing, Required keywords=$header, Response keywords=$kw ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
continue # try again next loop
|
||||
detected_kw = GeneralUtils.detect_keyword(header, response)
|
||||
if sum(values(detected_kw)) < length(header)
|
||||
errornote = "\nSQL decisionMaker() response does not have all header"
|
||||
continue
|
||||
elseif sum(values(detected_kw)) > length(header)
|
||||
errornote = "\nSQL decisionMaker() response has duplicated header"
|
||||
continue
|
||||
end
|
||||
|
||||
# textToDict() search for action_input
|
||||
responsedict = GeneralUtils.textToDict(response, header;
|
||||
dictKey=dictkey, symbolkey=true)
|
||||
|
||||
@@ -315,7 +311,7 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
|
||||
end
|
||||
end
|
||||
|
||||
for i ∈ [:comprehension, :plan, :action_name, :action_input]
|
||||
for i ∈ Symbol.(dictkey)
|
||||
if length(JSON3.write(responsedict[i])) == 0
|
||||
errornote = "\n $i is empty"
|
||||
println("Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
@@ -323,14 +319,14 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
|
||||
end
|
||||
end
|
||||
|
||||
# check if there are more than 1 key per categories
|
||||
for i ∈ [:comprehension, :plan, :action_name, :action_input]
|
||||
matchkeys = GeneralUtils.findMatchingDictKey(responsedict, i)
|
||||
if length(matchkeys) > 1
|
||||
errornote = "\n $i has more than one key"
|
||||
println("Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
# check whether response has all header
|
||||
detected_kw = GeneralUtils.detect_keyword(header, response)
|
||||
if sum(values(detected_kw)) < length(header)
|
||||
errornote = "\nSQL decisionMaker() response does not have all header"
|
||||
continue
|
||||
elseif sum(values(detected_kw)) > length(header)
|
||||
errornote = "\nSQL decisionMaker() response has duplicated header"
|
||||
continue
|
||||
end
|
||||
end
|
||||
|
||||
state[:decisionMaker] = responsedict
|
||||
@@ -340,244 +336,7 @@ function decisionMaker(state::T1, context, text2textInstructLLM::Function,
|
||||
end
|
||||
error("DecisionMaker failed to generate a thought \n", response)
|
||||
end
|
||||
# function decisionMaker(state::T1, context, text2textInstructLLM::Function,
|
||||
# ; querySQLVectorDBF::Union{T2, Nothing}=nothing
|
||||
# )::Dict{Symbol, 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 query.
|
||||
# You are also eager to improve your helpfulness.
|
||||
|
||||
# For your information:
|
||||
# - Observation: Result of the immediately preceding action
|
||||
|
||||
# At each round of conversation, the user will give you the current situation:
|
||||
# User Query: ...
|
||||
# Example: ...
|
||||
# Your Q&A: ...
|
||||
# Your work progress: ...
|
||||
# Evaluation: Evaluation of the immediately preceding action and observation
|
||||
# Suggestion: Suggestion for the immediately preceding action and observation
|
||||
|
||||
# You must follow the following guidelines:
|
||||
# - Keep SQL queries focused only on the provided information.
|
||||
|
||||
# You should follow the following guidelines:
|
||||
# - Do not create any table in the database
|
||||
# - A junction table can be used to link tables together. Another use case is for filtering data.
|
||||
# - If you can't find a single table that can be used to answer the user's query, try joining multiple tables to see if you can obtain the answer.
|
||||
# - If you are unable to find the requested information, kindly inform the user, "The current data in our database does not provide the specific answer to your query".
|
||||
# - Text information in the database usually stored in lower case. If your search returns empty, try using lower case to search.
|
||||
|
||||
# You should then respond to the user with interleaving Understanding, Reasoning, Plan, Action:
|
||||
# 1) Comprehension:
|
||||
# - State your comprehension about the current situation.
|
||||
# 2) Plan: Given the current circumstances, outline a detailed, step-by-step plan to accomplish the task. Be specific.
|
||||
# 3) Action_name (Must be aligned with your plan): Can be one of the following functions:
|
||||
# - GETDATA, which you can use to get the data from the database. Action_input for this function must be a single SQL query to be executed against the database.
|
||||
# For more effective text search, it's necessary to use case-insensitivity and the ILIKE operator.
|
||||
# Do not wrap the SQL as it will be executed against the database directly and SQL must be ended with ';'.
|
||||
# 4) Action_input: Input to the action
|
||||
|
||||
# You should only respond in format as described below:
|
||||
# Comprehension: ...
|
||||
# Plan: ...
|
||||
# Action_name: ...
|
||||
# Action_input: ...
|
||||
|
||||
# Let's begin!
|
||||
# """
|
||||
|
||||
# workprogress = ""
|
||||
# for (k, v) in state[:thoughtHistory]
|
||||
# if k ∉ [:question]
|
||||
# workprogress *= "$k: $v\n"
|
||||
# end
|
||||
# end
|
||||
|
||||
# response = nothing # store for show when error msg show up
|
||||
# errornote = ""
|
||||
|
||||
# # provide similar sql only for the first attempt
|
||||
# similarSQL_ = "None"
|
||||
# if length(state[:thoughtHistory]) == 1
|
||||
# sql, distance = querySQLVectorDBF(state[:thoughtHistory][:question])
|
||||
# similarSQL_ = sql !== nothing ? sql : "None"
|
||||
# end
|
||||
|
||||
|
||||
# for attempt in 1:10
|
||||
# QandA = generatequestion(state, context, text2textInstructLLM; similarSQL=similarSQL_)
|
||||
|
||||
# usermsg =
|
||||
# """
|
||||
# $(context[:tablelist])
|
||||
# User query: $(state[:thoughtHistory][:question])
|
||||
# Example: $similarSQL_
|
||||
# Your Q&A: $QandA
|
||||
# Your work progress: $workprogress
|
||||
# Evaluation: $(state[:evaluation])
|
||||
# Suggestion: $(state[:suggestion])
|
||||
# $errornote
|
||||
# """
|
||||
|
||||
# _prompt =
|
||||
# [
|
||||
# Dict(:name=> "system", :text=> systemmsg),
|
||||
# Dict(:name=> "user", :text=> usermsg)
|
||||
# ]
|
||||
|
||||
# # put in model format
|
||||
# prompt = GeneralUtils.formatLLMtext(_prompt; formatname="qwen")
|
||||
# response = text2textInstructLLM(prompt)
|
||||
|
||||
# # LLM tends to generate observation given that it is in the input
|
||||
# response =
|
||||
# if occursin("observation:", response)
|
||||
# string(split(response, "observation:")[1])
|
||||
# elseif occursin("Observation:", response)
|
||||
# string(split(response, "Observation:")[1])
|
||||
# elseif occursin("observation_", response)
|
||||
# string(split(response, "observation_")[1])
|
||||
# elseif occursin("Observation_", response)
|
||||
# string(split(response, "Observation_")[1])
|
||||
# else
|
||||
# response
|
||||
# end
|
||||
|
||||
# # sometime LLM output something like **Comprehension**: which is not expected
|
||||
# response = replace(response, "**"=>"")
|
||||
# response = replace(response, "***"=>"")
|
||||
|
||||
# # some time LLM output Plan_1: so we need to detect and replace topic numbering
|
||||
# regex = r"_[0-1000]+:"
|
||||
# matches = collect(eachmatch(regex, response))
|
||||
# for m in matches
|
||||
# response = replace(response, string(m.match)=>":")
|
||||
# end
|
||||
|
||||
# if occursin("NULL", response)
|
||||
# errornote = "\nSQL decisionMaker() NULL response is not allowed"
|
||||
# println("Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
# continue
|
||||
# end
|
||||
|
||||
# header = ["Comprehension:", "Plan:", "Action_name:", "Action_input:"]
|
||||
# dictkey = ["comprehension", "plan", "action_name", "action_input"]
|
||||
|
||||
# # detect if there are more than 1 key per categories
|
||||
# wordcount = GeneralUtils.countGivenWords(response, header)
|
||||
# duplicateKeywordFlag = false
|
||||
# for (i, v) in enumerate(wordcount)
|
||||
# keyword = header[i]
|
||||
# keywordNumber = v
|
||||
# if keywordNumber > 1
|
||||
# errornote = "\nSQL query has duplicated keyword, $keyword"
|
||||
# println("Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
# duplicateKeywordFlag = true
|
||||
# break
|
||||
# end
|
||||
# end
|
||||
# duplicateKeywordFlag == true ? continue : nothing
|
||||
|
||||
# # check whether response has all header
|
||||
# kw = []
|
||||
# # use for loop and detect_keyword function to get the exact variation of each keyword in the text then push to kw list
|
||||
# for keyword in header
|
||||
# detected = GeneralUtils.detect_keyword(keyword, response)
|
||||
# push!(kw, detected)
|
||||
# end
|
||||
# if nothing ∈ kw
|
||||
# println("Some keywords are missing, Required keywords=$header, Response keywords=$kw ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
# continue # try again next loop
|
||||
# end
|
||||
|
||||
# # textToDict() search for action_input
|
||||
# responsedict = GeneralUtils.textToDict(response, header;
|
||||
# dictKey=dictkey, symbolkey=true)
|
||||
|
||||
# delete!(responsedict, :observation)
|
||||
|
||||
# # remove backticks Error occurred: MethodError: no method matching occursin(::String, ::Vector{String})
|
||||
# if occursin("```", responsedict[:action_input])
|
||||
# sql = GeneralUtils.extract_triple_backtick_text(responsedict[:action_input])[1]
|
||||
# if sql[1:4] == "sql\n"
|
||||
# sql = sql[5:end]
|
||||
# end
|
||||
# sql = split(sql, ';') # some time there are comments in the sql
|
||||
# sql = sql[1] * ';'
|
||||
|
||||
# responsedict[:action_input] = sql
|
||||
# end
|
||||
|
||||
# toollist = ["TABLEINFO", "GETDATA"]
|
||||
# if responsedict[:action_name] ∉ toollist
|
||||
# errornote = "\nYou must only use the given functions"
|
||||
# println("Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
# continue
|
||||
# end
|
||||
|
||||
# for i in toollist
|
||||
# if occursin(i, responsedict[:action_input])
|
||||
# errornote = "\n action_name is in action_input which is not allowed."
|
||||
# println("Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
# continue
|
||||
# end
|
||||
# end
|
||||
|
||||
# for i ∈ [:comprehension, :plan, :action_name, :action_input]
|
||||
# if length(JSON3.write(responsedict[i])) == 0
|
||||
# errornote = "\n $i is empty"
|
||||
# println("Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
# continue
|
||||
# end
|
||||
# end
|
||||
|
||||
# # check if there are more than 1 key per categories
|
||||
# for i ∈ [:comprehension, :plan, :action_name, :action_input]
|
||||
# matchkeys = GeneralUtils.findMatchingDictKey(responsedict, i)
|
||||
# if length(matchkeys) > 1
|
||||
# errornote = "\n $i has more than one key"
|
||||
# println("Attempt $attempt $errornote ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
|
||||
# continue
|
||||
# end
|
||||
# end
|
||||
|
||||
# state[:decisionMaker] = responsedict
|
||||
|
||||
# return responsedict
|
||||
|
||||
# end
|
||||
# error("DecisionMaker failed to generate a thought \n", response)
|
||||
# end
|
||||
|
||||
""" Assigns a scalar value to each new child node to be used for selec-
|
||||
tion and backpropagation. This value effectively quantifies the agent's progress in task completion,
|
||||
@@ -1429,7 +1188,6 @@ function generatequestion(state::T1, context, text2textInstructLLM::Function;
|
||||
|
||||
header = ["Understanding:", "Q1:"]
|
||||
dictkey = ["understanding", "q1"]
|
||||
|
||||
responsedict = GeneralUtils.textToDict(response, header;
|
||||
dictKey=dictkey, symbolkey=true)
|
||||
response = "Q1: " * responsedict[:q1]
|
||||
|
||||
41
test/Manifest.toml
Normal file
41
test/Manifest.toml
Normal file
@@ -0,0 +1,41 @@
|
||||
# This file is machine-generated - editing it directly is not advised
|
||||
|
||||
julia_version = "1.11.4"
|
||||
manifest_format = "2.0"
|
||||
project_hash = "71d91126b5a1fb1020e1098d9d492de2a4438fd2"
|
||||
|
||||
[[deps.Base64]]
|
||||
uuid = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
|
||||
version = "1.11.0"
|
||||
|
||||
[[deps.InteractiveUtils]]
|
||||
deps = ["Markdown"]
|
||||
uuid = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
|
||||
version = "1.11.0"
|
||||
|
||||
[[deps.Logging]]
|
||||
uuid = "56ddb016-857b-54e1-b83d-db4d58db5568"
|
||||
version = "1.11.0"
|
||||
|
||||
[[deps.Markdown]]
|
||||
deps = ["Base64"]
|
||||
uuid = "d6f4376e-aef5-505a-96c1-9c027394607a"
|
||||
version = "1.11.0"
|
||||
|
||||
[[deps.Random]]
|
||||
deps = ["SHA"]
|
||||
uuid = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
|
||||
version = "1.11.0"
|
||||
|
||||
[[deps.SHA]]
|
||||
uuid = "ea8e919c-243c-51af-8825-aaa63cd721ce"
|
||||
version = "0.7.0"
|
||||
|
||||
[[deps.Serialization]]
|
||||
uuid = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
|
||||
version = "1.11.0"
|
||||
|
||||
[[deps.Test]]
|
||||
deps = ["InteractiveUtils", "Logging", "Random", "Serialization"]
|
||||
uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
|
||||
version = "1.11.0"
|
||||
2
test/Project.toml
Normal file
2
test/Project.toml
Normal file
@@ -0,0 +1,2 @@
|
||||
[deps]
|
||||
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
|
||||
Reference in New Issue
Block a user