module utils
export sendReceivePrompt, chunktext, extractStepFromPlan, checkTotalTaskInPlan,
detectCharacters, findDetectedCharacter, extract_number, toolNameBeingCalled,
isUsePlans, conversationSummary, checkReasonableness, replaceHeaders,
addShortMem!, splittext, dictToString, removeHeaders, keepOnlyKeys, experience,
messagesToString, messagesToString_nomark, removeTrailingCharacters, shortMemLatestTask
using UUIDs, Dates, DataStructures
using CommUtils, GeneralUtils
using ..type
#------------------------------------------------------------------------------------------------100
"""
Send a msg to registered mqtt topic within mqttClient.
```jldoctest
julia> using JSON3, UUIDs, Dates, FileIO, CommUtils, ChatAgent
julia> newAgent = ChatAgent.agentReact(
"Jene",
mqttClientSpec,
role=:assistant_react,
msgMeta=msgMeta
)
```
"""
function sendReceivePrompt(a::T, prompt::String; max_tokens=256, timeout::Int=120,
temperature::AbstractFloat=0.2, stopword=[]) where {T<:agent}
a.msgMeta[:msgId] = "$(uuid4())" # new msg id for each msg
msg = Dict(
:msgMeta=> a.msgMeta,
:txt=> prompt,
:max_tokens=> max_tokens,
:temperature=> temperature,
:stopword=> stopword,
)
payloadChannel = Channel(1)
# send prompt
CommUtils.request(a.mqttClient, msg)
starttime = Dates.now()
result = nothing
while true
timepass = (Dates.now() - starttime).value / 1000.0
CommUtils.mqttRun(a.mqttClient, payloadChannel)
if isready(payloadChannel)
topic, payload = take!(payloadChannel)
if payload[:msgMeta][:repondToMsgId] == msg[:msgMeta][:msgId]
result = haskey(payload, :txt) ? payload[:txt] : nothing
break
end
elseif timepass <= timeout
# skip, within waiting period
elseif timepass > timeout
println("sendReceivePrompt timeout $timepass/$timeout")
result = nothing
break
else
error("undefined condition. timepass=$timepass timeout=$timeout $(@__LINE__)")
end
end
return result
end
"""
Detect given characters. Output is a list of named tuple of detected char.
```jldoctest
julia> text = "I like to eat apples and use utensils."
julia> characters = ["eat", "use", "i"]
julia> result = detectCharacters(text, characters)
4-element Vector{Any}:
(char = "i", start = 4, stop = 4)
(char = "eat", start = 11, stop = 13)
(char = "use", start = 26, stop = 28)
(char = "i", start = 35, stop = 35)
```
"""
function detectCharacters(text::T1, characters::Vector{T2}) where {T1<:AbstractString, T2<:AbstractString}
result = []
for i in eachindex(text)
for char in characters
l = length(char)
char_startInd = i
char_endInd = i+l-1 # -1 because Julia use inclusive index
if char_endInd > length(text)
# skip
else
try # some time StringIndexError: invalid index [535], valid nearby indices [534]=>'é', [536]=>' '
if text[char_startInd: char_endInd] == char
push!(result, (char=char, start=char_startInd, stop=char_endInd))
end
catch
end
end
end
end
return result
end
"""
Chunk a text into smaller pieces by header.
```jldoctest
julia> using ChatAgent
julia> text = "Plan: First, we need to find out what kind of wine the user wants."
julia> headers = ChatAgent.detectCharacters(text, ["Nope", "sick", "First", "user", "Then", ])
3-element Vector{Any}:
(char = "First", start = 7, stop = 11)
(char = "user", start = 56, stop = 59)
(char = "Then", start = 102, stop = 105)
julia> chunkedtext = ChatAgent.chunktext(text, headers)
OrderedDict{String, String} with 3 entries:
"Act 1:" => " wikisearch"
"Actinput 1:" => " latest AMD GPU"
"Thought 1:" => " I should always think about..."
```
"""
function chunktext(text::T1, headers::T2) where {T1<:AbstractString, T2<:AbstractVector}
result = OrderedDict{String, Any}()
for (i, v) in enumerate(headers)
if i < length(headers)
nextheader = headers[i+1]
body = text[v[:stop]+1: nextheader[:start]-1]
# push!(result, (header=v[:char], body=body))
result[v[:char]] = body
else
body = text[v[:stop]+1: end]
# push!(result, (header=v[:char], body=body))
result[v[:char]] = body
end
end
return result
end
function extractStepFromPlan(a::agent, plan::T, step::Int) where {T<:AbstractString}
prompt =
"""
<|im_start|>system
You are a helpful assistant.
Your job is to extract step $step in the user plan.
Use the following format only:
{copy the step and put it here}
<|im_end|>
<|im_start|>user
$plan
<|im_end|>
<|im_start|>assistant
"""
response = sendReceivePrompt(a, prompt)
return response
end
function checkTotalTaskInPlan(a::agent)
headers = []
for (k, v) in a.memory[:shortterm]
push!(headers, k)
end
# Plan will have number e.g. Plan 3: so I need a way to detect latest Plan
header = nothing
for i in reverse(headers)
if occursin("Plan", i)
header = i
break
end
end
p = a.memory[:shortterm][header]
plan = "Plan: $p"
prompt =
"""
<|im_start|>system
You are a helpful assistant.
Your job is to determine how many steps in a user plan.
Use the following format to answer:
Total step number is {}
<|im_end|>
<|im_start|>user
$plan
<|im_end|>
<|im_start|>assistant
"""
response = sendReceivePrompt(a, prompt)
result = extract_number(response)
return result
end
"""
Find a given character from a vector of named tuple.
Output is character location index inside detectedCharacters
```jldoctest
julia a = [ (char = "i", start = 4, stop = 4)
(char = "eat", start = 11, stop = 13)
(char = "use", start = 26, stop = 28)
(char = "i", start = 35, stop = 35) ]
julia> findDetectedCharacter(a, "i")
[1, 4]
```
"""
function findDetectedCharacter(detectedCharacters, character)
allchar = [i[1] for i in detectedCharacters]
return findall(isequal.(allchar, character))
end
function extract_number(text::T) where {T<:AbstractString}
regex = r"\d+" # regular expression to match one or more digits
match = Base.match(regex, text) # find the first match in the text
if match !== nothing
number = parse(Int, match.match)
return number
else
error("No number found in the text $(@__LINE__)")
end
end
"""
Extract toolname from text.
```jldoctest
julia> text = " internetsearch\n"
julia> tools = Dict(
:internetsearch=>Dict(
:name => "internetsearch",
:description => "Useful for when you need to search the Internet",
:input => "Input should be a search query.",
:output => "",
# :func => internetsearch # function
),
:chatbox=>Dict(
:name => "chatbox",
:description => "Useful for when you need to ask a customer what you need to know or to talk with them.",
:input => "Input should be a conversation to customer.",
:output => "" ,
),
)
julia> toolname = toolNameBeingCalled(text, tools)
```
"""
function toolNameBeingCalled(text::T, tools::Dict) where {T<:AbstractString}
toolNameBeingCalled = nothing
for (k, v) in tools
toolname = String(k)
if contains(text, toolname)
toolNameBeingCalled = toolname
break
end
end
return toolNameBeingCalled
end
# function chooseThinkingMode(a::agentReflex, usermsg::String)
# thinkingmode = nothing
# if length(a.memory[:log]) != 0
# thinkingmode = :continue_thinking
# else
# prompt =
# """
# <|im_start|>system
# {systemMsg}
# You always use tools if there is a chance to impove your response.
# You have access to the following tools:
# {tools}
# Your job is to determine whether you will use tools or actions to response.
# Choose one of the following choices:
# Choice 1: If you don't need to use tools or actions to response to the stimulus say, "{no}".
# Choice 2: If you think the user want to get wine say, "{yes}".
# <|im_end|>
# <|im_start|>user
# {input}
# <|im_end|>
# <|im_start|>assistant
# """
# toollines = ""
# for (toolname, v) in a.tools
# if toolname ∉ ["chatbox", "nothing"]
# toolline = "$toolname: $(v[:description]) $(v[:input]) $(v[:output])\n"
# toollines *= toolline
# end
# end
# prompt = replace(prompt, "{systemMsg}" => a.roles[a.role])
# prompt = replace(prompt, "{tools}" => toollines)
# prompt = replace(prompt, "{input}" => usermsg)
# result = sendReceivePrompt(a, prompt)
# willusetools = GeneralUtils.getStringBetweenCharacters(result, "{", "}")
# thinkingmode = willusetools == "yes" ? :new_thinking : :no_thinking
# end
# return thinkingmode
# end
""" Determine from a user message whether an assistant need to use tools.
Arguments:
a, one of ChatAgent's agent.
Return:
1. true/false # is LLM going to use tools
2. objective # what LLM going to do
"""
function isUsePlans(a::agentReflex)
toollines = ""
for (toolname, v) in a.tools
if toolname ∉ ["chatbox"] # LLM will always use chatbox
toolline = "$toolname: $(v[:description]) $(v[:input]) $(v[:output])\n"
toollines *= toolline
end
end
conversation = messagesToString(a.messages)
aboutYourself =
"""
Your name is $(a.agentName)
$(a.roles[a.role])
"""
prompt =
"""
<|system|>
$aboutYourself
$toollines
Your job is to decide whether you need think thoroughly or use tools in order to respond to the user's question.
user: Hello!. How are you?
assistant: {"thought": "the user is greeting me, I don't need to think about it.", "anwer": "no"}
user: "What's tomorrow weather like?"
assistant: {"thought": "I will need to use weather tools to check for tomorrow's temperature.", "anwer": "yes"}
$conversation
<|assistant|>
"""
isuseplan = false
if length(a.memory[:shortterm]) != 0
isuseplan = true
elseif a.role == :sommelier
isuseplan = true
else
# if LLM mentions any tools, use Plan/Thought/Act loop
response = sendReceivePrompt(a, prompt, temperature=0.2, max_tokens=64, stopword=["<|", ""])
for (toolname, v) in a.tools
if occursin("Yes", String(response))
isuseplan = true
break
end
end
end
return isuseplan
end
"""
make a conversation summary.
```jldoctest
julia> conversation = [
Dict(:role=> "user", :content=> "I would like to get a bottle of wine", :timestamp=> Dates.now()),
Dict(:role=> "assistant", :content=> "What kind of Thai dishes are you having?", :timestamp=> Dates.now()),
Dict(:role=> "user", :content=> "It a pad thai.", :timestamp=> Dates.now()),
Dict(:role=> "assistant", :content=> "Is there any special occasion for this event?", :timestamp=> Dates.now()),
Dict(:role=> "user", :content=> "We'll hold a wedding party at the beach.", :timestamp=> Dates.now()),
Dict(:role=> "assistant", :content=> "What is your preferred type of wine?", :timestamp=> Dates.now()),
Dict(:role=> "user", :content=> "I like dry white wine with medium tanins.", :timestamp=> Dates.now()),
Dict(:role=> "assistant", :content=> "What is your preferred price range for this bottle of wine?", :timestamp=> Dates.now()),
Dict(:role=> "user", :content=> "lower than 50 dollars.", :timestamp=> Dates.now()),
Dict(:role=> "assistant", :content=> "Based on your preferences and our stock, I recommend the following two wines for you:
1. Pierre Girardin \"Murgers des Dents de Chien\" - Saint-Aubin 1er Cru (17 USD)
2. Etienne Sauzet'Les Perrieres' - Puligny Montrachet Premier Cru (22 USD)
The first wine, Pierre Girardin \"Murgers des Dents de Chien\" - Saint-Aubin 1er Cru, is a great choice for its affordable price and refreshing taste.
It pairs well with Thai dishes and will be perfect for your beach wedding party.
The second wine, Etienne Sauzet'Les Perrieres' - Puligny Montrachet Premier Cru, offers a more complex flavor profile and slightly higher price point, but still remains within your budget.
Both wines are suitable for serving at 22 C temperature.", :timestamp=> Dates.now()),
]
julia> summary = conversationSummary(conversation)
```
"""
function conversationSummary(a::T) where {T<:agent}
conversation = messagesToString_nomark(a.messages, addressAIas="I")
prompt =
"""
<|system|>
Your conversation with the user:
$conversation
Your job is to paraphrase a conversation from your perspective.
You must refers to yourself by "I" in the summary.
<|/s|>
<|assistant|>
Paraphrase:
"""
result = sendReceivePrompt(a, prompt)
summary = split(result, "<|/s|>")[1]
summary =
return summary
end
""" Convert a vector of dict into 1-continous string.
Arguments:
vecofdict, a vector of dict
Return:
1-continous string
# Example
```jldoctest
julia> using ChatAgent
julia> agent = ChatAgent.agentReflex("Jene")
julia> agent.messages = [Dict(:role=> "user", :content=> "Hi there."),
Dict(:role=> "assistant", :content=> "Hello! How can I assist you today?"),]
julia> messagesToString(agent.messages)
"<|im_start|>user: Hi there.\n<|im_end|><|im_start|>assistant: Hello! How can I assist you today?\n<|im_end|>"
```
"""
function messagesToString(messages::AbstractVector{T}; addressAIas="assistant") where {T<:AbstractDict}
conversation = ""
if length(messages)!= 0
for msg in messages
role = msg[:role]
content = msg[:content]
nouse = 0
for i in reverse(content)
if i == '\n' || i == ' '
nouse += 1
else
break
end
end
if role == "user"
conversation *= "<|$role|>\n $(content[1:end-nouse])\n"
elseif role == "assistant"
conversation *= "<|$addressAIas|>\n $(content[1:end-nouse])\n"
else
error("undefied condition role = $role $(@__LINE__)")
end
end
else
conversation = "N/A"
end
return conversation
end
# function messagesToString(messages::AbstractVector{T}; addressAIas="assistant") where {T<:AbstractDict}
# conversation = ""
# if length(messages)!= 0
# for msg in messages
# role = msg[:role]
# content = msg[:content]
# nouse = 0
# for i in reverse(content)
# if i == '\n' || i == ' '
# nouse += 1
# else
# break
# end
# end
# if role == "user"
# conversation *= "<|im_start|>$role: $(content[1:end-nouse])\n<|im_end|>"
# elseif role == "assistant"
# conversation *= "<|im_start|>$addressAIas: $(content[1:end-nouse])\n<|im_end|>"
# else
# error("undefied condition role = $role $(@__LINE__)")
# end
# end
# else
# conversation = "N/A"
# end
# return conversation
# end
""" Convert a vector of dict into 1-continous string.
Arguments:
vecofdict, a vector of dict
Return:
1-continous string
# Example
```jldoctest
julia> using ChatAgent
julia> agent = ChatAgent.agentReflex("Jene")
julia> agent.messages = [Dict(:role=> "user", :content=> "Hi there."),
Dict(:role=> "assistant", :content=> "Hello! How can I assist you today?"),]
julia> messagesToString(agent.messages)
"user: Hi there.\nassistant: Hello! How can I assist you today?\n"
```
"""
function messagesToString_nomark(messages::AbstractVector{T}; addressAIas="assistant") where {T<:AbstractDict}
conversation = ""
if length(messages)!= 0
for msg in messages
role = msg[:role]
content = msg[:content]
content = removeTrailingCharacters(content)
if role == "user"
conversation *= "$role: $content\n"
elseif role == "assistant"
conversation *= "$addressAIas: $content\n"
else
error("undefied condition role = $role $(@__LINE__)")
end
end
else
conversation = "N/A"
end
return conversation
end
function dictToString(shortMemory::T;
skiplist::Union{Vector{String}, Vector{Symbol}}=[""]) where {T<:AbstractDict}
s = ""
for (k, v) in shortMemory
if k ∉ skiplist
new_v = removeTrailingCharacters(v)
s1 = "$k $new_v\n"
s *= s1
end
end
return s
end
# function dictToString(dict::T;
# skiplist::Union{Array{String}, Array{Symbol}}=[]) where {T<:AbstractDict}
# s = ""
# for (k, v) in dict
# if k ∉ skiplist
# s1 = "$k $v"
# s *= s1
# # ensure a newline seperate each sentences
# if s[end] != "\n"
# s *= "\n"
# end
# end
# end
# return s
# end
""" Remove trailing characters from text.
Arguments:
text, text you want to remove trailing characters
charTobeRemoved, a list of characters to be removed
Return:
text with specified trailing characters removed
# Example
```jldoctest
julia> text = "Hello! How can I assist you today?\n\n "
julia> removelist = ['\n', ' ',]
julia> removeTrailingCharacters(text, charTobeRemoved=removelist)
"Hello! How can I assist you today?"
```
"""
function removeTrailingCharacters(text; charTobeRemoved::AbstractVector{T}=['\n', ' ',]) where {T<:Char}
nouse = 0
for i in reverse(text)
if i ∈ charTobeRemoved
nouse += 1
else
break
end
end
return text[1:end-nouse]
end
#TODO
function checkReasonableness(userMsg::String, context::String, tools)
# Ref: https://www.youtube.com/watch?v=XV4IBaZqbps
prompt =
"""
<|im_start|>system
You are a helpful assistant. Your job is to check the reasonableness of user assignments.
If the user assignment can be answered given the tools available say, "This is a reasonable assignment".
If the user assignment cannot be answered then provide some feedback to the user that may improve
their assignment.
Here is the context for the assignment:
{context}
<|im_end|>
<|im_start|>user
{assignment}
<|im_end|>
<|im_start|>assistant
"""
context = "You have access to the following tools:
WineStock: useful for when you need to find info about wine by matching your description, price, name or ID. Input should be a search query with as much details as possible."
prompt = replace(prompt, "{assignment}" => userMsg)
prompt = replace(prompt, "{context}" => context)
output_py = llm(
prompt,
max_tokens=512,
temperature=0.1,
# top_p=top_p,
echo=false,
stop=["", "<>", ],
)
_output_jl = pyconvert(Dict, output_py);
output = pyconvert(Dict, _output_jl["choices"][1]);
output["text"]
end
""" Add chunked text to a short term memory of a chat agent
Arguments:
shortMem = short memory of a chat agent,
chunkedtext = a dict contains text
Return: no return
# Example
```jldoctest
julia> chunkedtext = OrderedDict{String, String}(
"Thought 1:" => " I should always think about...",
"Act 1:" => " wikisearch",
"Actinput 1:" => " latest AMD GPU",)
julia> shortMem = OrderedDict{String, Any}()
julia> addShortMem!(shortMem, chunkedtext)
OrderedDict{String, Any} with 3 entries:
"Thought 1:" => " I should always think about..."
"Act 1:" => " wikisearch"
"Actinput 1:" => " latest AMD GPU"
```
"""
function addShortMem!(shortMem::OrderedDict{String, Any}, chunkedtext::T) where {T<:AbstractDict}
for (k, v) in chunkedtext
shortMem[k] = v
end
return shortMem
end
""" Split text using all keywords in a list. Start spliting from rightmost of the text.
Arguments:
text = a text you want to split
list = a list of keywords you want to split
Return:
a leftmost text after split
# Example
```jldoctest
julia> text = "Consider the type of food, occasion and temperature at the serving location."
julia> list = ["at", "and"]
"Consider the type of food, occasion "
```
"""
function splittext(text, list)
newtext = text
for i in list
newtext = split(newtext, i)[1]
end
return newtext
end
"""
Add step number to header in a text
"""
function addStepNumber(text::T, headers, step::Int) where {T<:AbstractString}
newtext = text
for i in headers
if occursin(i[:char], newtext)
new = replace(i[:char], ":"=> " $step:")
newtext = replace(newtext, i[:char]=>new )
end
end
return newtext
end
function addStepNumber(text::T, headers, step::Int, substep::Int) where {T<:AbstractString}
newtext = text
for i in headers
if occursin(i[:char], newtext)
new = replace(i[:char], ":"=> " $step-$substep:")
newtext = replace(newtext, i[:char]=>new )
end
end
return newtext
end
""" Add step number to header in a text
Arguments:
text = a text you want to split
headers = a list of keywords you want to add step and substep to
step = a number you want to add
Return:
a leftmost text after split
# Example
```jldoctest
julia> text = "Consider the type of food, occasion and temperature at the serving location."
julia> headers = ["Thought", "Act"]
```
"""
function replaceHeaders(text::T, headers, step::Int) where {T<:AbstractString}
newtext = text
for i in headers
header = i[1:end-1] # not include ":"
if occursin(header, newtext)
startind = findfirst(header, newtext)[1]
stopind = findnext(":", newtext, startind+1)[end]
word = newtext[startind: stopind]
newword = "$header $step:"
newtext = replace(newtext, word=> newword)
if header == "Thought:"
error(1)
end
end
end
return newtext
end
""" Remove headers of specific step from memory.
Arguments:
shortMemory = a short term memory of a ChatAgent's agent
skipHeaders = a list of keys in memory you want to skip
step = a step number you want to remove
Return:
a short term memory
# Example
```jldoctest
julia> shortMemory = OrderedDict(
"user:" => "May I try this one?",
"Plan 1:" => "testing a small portion of icecream",
"Thought 1:" => "I like it.",
"Act 1:" => "chatbox",
"Actinput 1:" => "I get this one.",
"Plan 2:" => "I'm meeting my wife this afternoon",
"Thought 2:" => "I also want it for my wife",
"Act 2:" => "chatbox",
"Actinput 2:" => "I would like to get 2 more",
)
julia> skipHeaders = ["Plan"]
julia> step = 2
julia> removeHeaders(shortMemory, step, skipHeaders)
OrderedDict(
"user:" => "May I try this one?",
"Plan 1:" => "testing a small portion of icecream",
"Thought 1:" => "I like it.",
"Act 1:" => "chatbox",
"Actinput 1:" => "I get this one.",
"Plan 2:" => "I'm meeting my wife this afternoon",
)
```
"""
function removeHeaders(shortMemory::OrderedDict, step::Int,
skipHeaders::Union{Array{String}, Array{Symbol}, Nothing}=nothing)
newdict = similar(shortMemory)
for (k, v) in shortMemory
if occursin("$step", k)
if skipHeaders !== nothing
for i in skipHeaders
if occursin(i, k)
newdict[k] = v
else
# skip, not copy
end
end
else
# no copy
end
else
newdict[k] = v
end
end
return newdict
end
""" Keep only specified keys in a dictionary. All non-specified keys will be removed.
Arguments:
dict = a dictionary
keys = keys you want to keep in a dict
Return:
a dict with all non-specified keys removed
# Example
```jldoctest
julia> dict = OrderedDict(
"user:" => "May I try this one?",
"Plan 1:" => "testing a small portion of icecream",
"Thought 1:" => "I like it.",
"Act 1:" => "chatbox",
"Actinput 1:" => "I get this one.",
"Plan 2:" => "I'm meeting my wife this afternoon",
"Thought 2:" => "I also want it for my wife",
"Act 2:" => "chatbox",
"Actinput 2:" => "I would like to get 2 more",
)
julia> keys = ["user:"]
julia> keepOnlyKeys(dict, keys)
OrderedDict(
"user:" => "May I try this one?",
)
```
"""
function keepOnlyKeys(dict::T1, keys::T2) where {T1<:AbstractDict, T2<:AbstractVector}
newdict = similar(dict)
for (k, v) in dict
if k ∈ keys
newdict[k] = v
end
end
return newdict
end
""" Convert experience dict into 1 string for LLM to use.
Arguments:
dict = a dictionary contain past experience
Return:
An experience in 1 string without context keys.
# Example
```jldoctest
julia> dict = OrderedDict{String, Any}(
" This lesson can be applied to various situations => " Gathering accurate and relevant information about the user's preferences, budget, and event details is crucial for providing personalized recommendations.\n"
)
julia> experience(dict)
```
"""
function experience(dict::T) where {T<:AbstractDict}
s = ""
for (k, v) in dict
s *= v
end
return s
end
""" Get the latest step number of short term memory
Arguments:
dict = a dictionary contain past experience
Return:
latest step number
# Example
```jldoctest
julia> dict = OrderedDict(
"Plan 1:" => "1. Ask about the type of food that will be served at the wedding party.")
julia>shortMemLatestTask(dict)
1
"""
function shortMemLatestTask(dict::T) where {T<:AbstractDict}
_latest_step = keys(dict)
_latest_step = [i for i in _latest_step]
_latest_step = _latest_step[end]
latest_step = parse(Int, _latest_step[end-2:end-1])
return latest_step
end
end # end module