Files
ChatAgent/src/interface.jl
2023-11-23 10:08:41 +00:00

1119 lines
33 KiB
Julia
Executable File

module interface
export agentReact, agentReflex,
addNewMessage, clearMessage, removeLatestMsg, generatePrompt_tokenPrefix,
generatePrompt_tokenSuffix, conversation, work, detectCharacters, chunktext,
findDetectedCharacter, wikisearch, sendReceivePrompt
using JSON3, DataStructures, Dates, UUIDs, HTTP
using CommUtils, GeneralUtils
using ..type
# ---------------------------------------------------------------------------- #
# pythoncall setting #
# ---------------------------------------------------------------------------- #
# Ref: https://github.com/JuliaPy/PythonCall.jl/issues/252
# by setting the following variables, PythonCall will use system python or conda python and
# packages installed by system or conda
# if these setting are not set (comment out), PythonCall will use its own python and package that
# installed by CondaPkg (from env_preparation.jl)
# ENV["JULIA_CONDAPKG_BACKEND"] = "Null"
# systemPython = split(read(`which python`, String), "\n")[1]
# ENV["JULIA_PYTHONCALL_EXE"] = systemPython # find python location with $> which python ex. raw"/root/conda/bin/python"
# using PythonCall
# const py_agents = PythonCall.pynew()
# const py_llms = PythonCall.pynew()
# function __init__()
# # PythonCall.pycopy!(py_cv2, pyimport("cv2"))
# # equivalent to from urllib.request import urlopen in python
# PythonCall.pycopy!(py_agents, pyimport("langchain.agents"))
# PythonCall.pycopy!(py_llms, pyimport("langchain.llms"))
# end
#------------------------------------------------------------------------------------------------100
"""
add new message to agent
# Example
```jldoctest
julia> addNewMessage(agent1, "user", "Where should I go to buy snacks")
````
"""
function addNewMessage(a::T1, role::String, content::T2) where {T1<:agent, T2<:AbstractString}
if role a.availableRole # guard against typo
error("role is not in agent.availableRole")
end
# check whether user messages exceed limit
userMsg = 0
for i in a.messages
if i[:role] == "user"
userMsg += 1
end
end
messageleft = 0
if userMsg > a.maxUserMsg # delete all conversation
clearMessage(a)
messageleft = a.maxUserMsg
else
userMsg += 1
d = Dict(:role=> role, :content=> content, :timestamp=> Dates.now())
push!(a.messages, d)
messageleft = a.maxUserMsg - userMsg
end
return messageleft
end
function clearMessage(a::T) where {T<:agent}
for i in eachindex(a.messages)
if length(a.messages) > 1 # system instruction will NOT be deleted
pop!(a.messages)
else
break
end
end
a.thought = "nothing"
end
function removeLatestMsg(a::T) where {T<:agent}
if length(a.messages) > 1
pop!(a.messages)
end
end
# function generatePrompt_mistral_openorca(a::T, usermsg::String, role::Symbol) where {T<:agent}
# prompt =
# """
# <|im_start|>system
# {systemMsg}
# <|im_end|>
# Here are the context for the question:
# {context}
# """
# prompt = replace(prompt, "{systemMsg}" => a.roles[role])
# toolnames = ""
# toollines = ""
# for (toolname, v) in a.tools
# toolline = "$toolname: $(v[:description]) $(v[:input]) $(v[:output])\n"
# toollines *= toolline
# toolnames *= "$toolname,"
# end
# prompt = replace(prompt, "{toolnames}" => toolnames)
# prompt = replace(prompt, "{tools}" => toollines)
# prompt = replace(prompt, "{context}" => a.context)
# prompt *= "<|im_start|>user\n" * usermsg * "\n<|im_end|>\n"
# prompt *= "<|im_start|>assistant\n"
# return prompt
# end
# function generatePrompt_mistral_openorca(a::T, usermsg::String,
# thinkingMode::Symbol=:nothinking) where {T<:agent}
# prompt =
# """
# <|im_start|>system
# {systemMsg}
# You have access to the following tools:
# {tools}
# {thinkingMode}
# <|im_end|>
# Here are the context for the question:
# {context}
# """
# prompt = replace(prompt, "{systemMsg}" => a.roles[a.role])
# prompt = replace(prompt, "{thinkingMode}" => a.thinkingMode[thinkingMode])
# toolnames = ""
# toollines = ""
# for (toolname, v) in a.tools
# toolline = "$toolname: $(v[:description]) $(v[:input]) $(v[:output])\n"
# toollines *= toolline
# toolnames *= "$toolname,"
# end
# prompt = replace(prompt, "{toolnames}" => toolnames)
# prompt = replace(prompt, "{tools}" => toollines)
# prompt = replace(prompt, "{context}" => a.context)
# prompt *= "<|im_start|>user\nQuestion: " * usermsg * "\n<|im_end|>\n"
# prompt *= "<|im_start|>assistant\n"
# return prompt
# end
function generatePrompt_mistral_openorca(a::T, usermsg::String,
thinkingMode::Symbol=:nothinking) where {T<:agent}
prompt =
"""
<|im_start|>system
{systemMsg}
{tools}
{thinkingMode}
<|im_end|>
Here are the context for the assignment:
{context}
"""
prompt = replace(prompt, "{systemMsg}" => a.roles[a.role])
prompt = replace(prompt, "{thinkingMode}" => a.thinkingMode[thinkingMode])
toolnames = ""
toollines = ""
for (toolname, v) in a.tools
toolline = "$toolname: $(v[:description]) $(v[:input]) $(v[:output])\n"
toollines *= toolline
toolnames *= "$toolname,"
end
prompt = replace(prompt, "{toolnames}" => toolnames)
prompt = replace(prompt, "{context}" => a.context)
prompt *= "<|im_start|>user\nAssignment: " * usermsg * "\n<|im_end|>\n"
prompt *= "<|im_start|>assistant\n"
return prompt
end
function chat_mistral_openorca(a::agentReflex, usermsg::String)
"""
general prompt format:
"
<|im_start|>system
{role}
{tools}
{thinkingFormat}
<|im_end|>
{context}
<|im_start|>user
{usermsg}
<|im_end|>
<|im_start|>assistant
"
Note:
{context} =
"
{earlierConversation}
{env status}
{shortterm memory}
{longterm memory}
"
"""
prompt =
"""
<|im_start|>system
{role}
{tools}
{thinkingFormat}
<|im_end|>
{context}
<|im_start|>user
{usermsg}
<|im_end|>
<|im_start|>assistant
"""
prompt = replace(prompt, "{role}" => a.roles[a.role])
prompt = replace(prompt, "{thinkingFormat}" => "")
context =
"""
{earlierConversation}
{current status}
{longterm memory}
"""
context = replace(context, "{earlierConversation}" => "My earlier talk with the user:\n$(a.earlierConversation)")
context = replace(context, "{current status}" => "")
context = replace(context, "{longterm memory}" => "")
prompt = replace(prompt, "{context}" => context)
prompt = replace(prompt, "{usermsg}" => "Assignment: $usermsg")
return prompt
end
function planner_mistral_openorca(a::agentReflex, usermsg::String)
"""
general prompt format:
"
<|im_start|>system
{role}
{tools}
{thinkingFormat}
<|im_end|>
{context}
<|im_start|>user
{usermsg}
<|im_end|>
<|im_start|>assistant
"
Note:
{context} =
"
{earlierConversation}
{env status}
{shortterm memory}
{longterm memory}
"
"""
prompt =
"""
<|im_start|>system
{role}
{tools}
{thinkingFormat}
<|im_end|>
{context}
<|im_start|>user
{usermsg}
<|im_end|>
<|im_start|>assistant
"""
prompt = replace(prompt, "{role}" => a.roles[a.role])
prompt = replace(prompt, "{thinkingFormat}" => a.thinkingFormat[:planner])
toolnames = ""
toollines = ""
for (toolname, v) in a.tools
toolline = "$toolname: $(v[:description]) $(v[:input]) $(v[:output])\n"
toollines *= toolline
toolnames *= "$toolname,"
end
prompt = replace(prompt, "{toolnames}" => toolnames)
prompt = replace(prompt, "{tools}" => "You have access to the following tools:\n$toollines")
context =
"""
{earlierConversation}
{current status}
{longterm memory}
"""
context = replace(context, "{earlierConversation}" => "My earlier talk with the user:\n$(a.earlierConversation)")
context = replace(context, "{current status}" => "")
context = replace(context, "{longterm memory}" => "")
prompt = replace(prompt, "{context}" => context)
prompt = replace(prompt, "{usermsg}" => "Assignment: $usermsg")
return prompt
end
"""
Chat with llm.
```jldoctest
julia> using JSON3, UUIDs, Dates, FileIO, CommUtils, ChatAgent
julia> mqttClientSpec = (
clientName= "someclient", # name of this client
clientID= "$(uuid4())",
broker= "mqtt.yiem.ai",
pubtopic= (imgAI="img/api/v0.0.1/gpu/request",
txtAI="txt/api/v0.1.0/gpu/request"),
subtopic= (imgAI="agent/api/v0.1.0/img/respond",
txtAI="agent/api/v0.1.0/txt/respond"),
keepalive= 30,
)
julia> msgMeta = Dict(
:msgPurpose=> "updateStatus",
:from=> "agent",
:to=> "llmAI",
:requestrespond=> "request",
:sendto=> "", # destination topic
:replyTo=> "agent/api/v0.1.0/txt/respond", # requester ask responder to send reply to this topic
:repondToMsgId=> "", # responder is responding to this msg id
:taskstatus=> "", # "complete", "fail", "waiting" or other status
:timestamp=> Dates.now(),
:msgId=> "$(uuid4())",
)
julia> newAgent = ChatAgent.agentReact(
"Jene",
mqttClientSpec,
role=:assistant_react,
msgMeta=msgMeta
)
julia> respond = ChatAgent.conversation(newAgent, "Hi! how are you?")
```
"""
function conversation(a::T, usermsg::String) where {T<:agent}
respond = nothing
if a.thought != "nothing" # continue thought
_ = addNewMessage(a, "user", usermsg)
a.thought *= "Obs $(a.thinkinground): $usermsg\n"
prompt = a.thought
respond = work(a, prompt)
else # new thought
thinkingmode = chooseThinkingMode(a, usermsg)
@show thinkingmode
if thinkingmode == :no_thinking
a.context = conversationSummary(a) #TODO should be long conversation before use summary because it leaves out details
_ = addNewMessage(a, "user", usermsg)
prompt = generatePrompt_mistral_openorca(a, usermsg, thinkingmode)
@show prompt
respond = sendReceivePrompt(a, prompt)
respond = split(respond, "<|im_end|>")[1]
respond = replace(respond, "\n" => "")
_ = addNewMessage(a, "assistant", respond)
@show respond
elseif thinkingmode == :thinking
a.context = conversationSummary(a)
_ = addNewMessage(a, "user", usermsg)
prompt = generatePrompt_mistral_openorca(a, usermsg, thinkingmode)
respond = work(a, prompt)
else
error("undefined condition thinkingmode = $thinkingmode")
end
end
return respond
end
"""
Continuously run llm functions except when llm is getting Answer: or chatbox.
There are many work() depend on thinking mode.
"""
function work(a::T, prompt::String, maxround::Int=3) where {T<:agent}
respond = nothing
while true
a.thinkinground += 1
@show a.thinkinground
toolname = nothing
toolinput = nothing
if a.thinkinground > a.thinkingroundlimit
a.thought *= "Thought $(a.thinkinground): I think I know the answer."
prompt = a.thought
end
@show prompt
respond = sendReceivePrompt(a, prompt)
headerToDetect = nothing
if a.thinkinground == 1
try
respond = split(respond, "Obs:")[1]
headerToDetect = ["Question:", "Plan:", "Thought:", "Act:", "ActInput:", "Obs:", "...", "Answer:",
"Conclusion:", "Summary:"]
catch
end
else
try
respond = split(respond, "Obs $(a.thinkinground):")[1]
headerToDetect = ["Question $(a.thinkinground):", "Plan $(a.thinkinground):",
"Thought $(a.thinkinground):", "Act $(a.thinkinground):",
"ActInput $(a.thinkinground):", "Obs $(a.thinkinground):",
"...", "Answer:",
"Conclusion:", "Summary:"]
catch
end
end
@show respond
headers = detectCharacters(respond, headerToDetect)
chunkedtext = chunktext(respond, headers)
Answer = findDetectedCharacter(headers, "Answer:")
AnswerInd = length(Answer) != 0 ? Answer[1] : nothing
Act = findDetectedCharacter(headers, "Act $(a.thinkinground):")
if length(Answer) == 1 && length(Act) == 0
a.thought = "nothing" # assignment finished, no more thought
a.context = "nothing"
a.thinkinground = 0
respond = chunkedtext[AnswerInd][:body]
respond = replace(respond, "<|im_end|>"=>"")
_ = addNewMessage(a, "assistant", respond)
break
else
# check for tool being called
ActHeader = a.thinkinground == 1 ? "Act:" : "Act $(a.thinkinground):"
if length(findDetectedCharacter(headers, ActHeader)) != 0 # check whether there is Act: in a respond
ActInd = findDetectedCharacter(headers, ActHeader)[1]
toolname = toolNameBeingCalled(chunkedtext[ActInd][:body], a.tools)
end
ActInputHeader = a.thinkinground == 1 ? "ActInput:" : "ActInput $(a.thinkinground):"
if length(findDetectedCharacter(headers, ActInputHeader)) != 0 # check whether there is ActInput: in a respond
ActInputInd = findDetectedCharacter(headers, ActInputHeader)[1]
toolinput = chunkedtext[ActInputInd][:body]
end
# clean up
if occursin(" \"", toolinput)
toolinput = GeneralUtils.getStringBetweenCharacters(toolinput, " \"", "\"\n")
else
toolinput = GeneralUtils.getStringBetweenCharacters(toolinput, " ", "\n")
end
@show toolname
@show toolinput
if toolname === nothing || toolinput === nothing
println("toolname $toolname toolinput $toolinput retry thinking")
a.thinkinground -= 1
continue
end
if a.thought == "nothing"
thought = ""
for i in chunkedtext
header = i[:header]
header = replace(header, ":"=>" $(a.thinkinground):") # add number so that llm not confused
body = i[:body]
thought *= "$header $body"
end
a.thought = prompt * thought
else
a.thought *= respond
end
if toolname == "chatbox" # chat with user
a.thought *= toolinput
respond = toolinput
_ = addNewMessage(a, "assistant", respond)
break
else # function call
f = a.tools[Symbol(toolname)][:func]
_result = f(toolinput)
if _result != "No info available." #TODO for use with wikisearch(). Not good for other tools
_result = makeSummary(a, _result)
end
result = "Obs $(a.thinkinground): $_result\n"
a.thought *= result
prompt = a.thought
end
end
end
@show respond
return respond
end
function conversation(a::agentReflex, usermsg::String; thinkingroundlimit::Int=3)
a.thinkingroundlimit = thinkingroundlimit
respond = nothing
# determine thinking mode
a.thinkingmode = chooseThinkingMode(a, usermsg)
@show a.thinkingmode
if a.thinkingmode == :no_thinking
a.earlierConversation = conversationSummary(a) #TODO should be long conversation before use summary because it leaves out details
_ = addNewMessage(a, "user", usermsg)
prompt = chat_mistral_openorca(a, usermsg) #TODO rewrite this function
@show prompt
respond = sendReceivePrompt(a, prompt)
respond = split(respond, "<|im_end|>")[1]
respond = replace(respond, "\n" => "")
_ = addNewMessage(a, "assistant", respond)
@show respond
else
respond = work(a, usermsg)
end
return respond
end
#WORKING
function work(a::agentReflex, usermsg::String)
if a.thinkingmode == :new_thinking
a.earlierConversation = conversationSummary(a)
_ = addNewMessage(a, "user", usermsg)
elseif a.thinkingmode == :continue_thinking
_ = addNewMessage(a, "user", usermsg)
a.thought *= "Obs $(a.attempt): $usermsg\n"
else
error("undefined condition thinkingmode = $thinkingmode")
end
while true
# plan
a.attempt += 1
@show a.attempt
toolname = nothing
toolinput = nothing
prompt = planner_mistral_openorca(a, usermsg)
@show prompt
respond = sendReceivePrompt(a, prompt)
plan = split(respond, "<|im_end|>")[1]
@show respond
step = 0
while true
step += 1
isstep, stepdetail = extractStepFromPlan(a, plan, step)
@show isstep
@show stepdetail
if isstep
error("work done")
end
# evaluate
end
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}
prompt =
"""
<|im_start|>system
You talked with a user earlier.
Now you make a detailed bullet summary of the conversation from your perspective.
Here are the conversation:
{conversation}
<|im_end|>
"""
conversation = ""
summary = "nothing"
if length(a.messages)!= 0
for msg in a.messages
role = msg[:role]
content = msg[:content]
if role == "user"
conversation *= "$role: $content\n"
elseif role == "assistant"
conversation *= "I: $content\n"
else
error("undefied condition role = $role")
end
end
prompt = replace(prompt, "{conversation}" => conversation)
result = sendReceivePrompt(a, prompt)
summary = result === nothing ? "nothing" : result
summary = replace(summary, "<|im_end|>" => "")
if summary[1:1] == "\n"
summary = summary[2:end]
end
end
return summary
end
function makeSummary(a::T1, input::T2) where {T1<:agent, T2<:AbstractString}
summary = "Nothing."
prompt =
"""
<|im_start|>system
Your need to determine now whether you can make a summary of user's text.
You have the following choices:
If you cannot make a summary say, "{no}".
If you can make a summary say, "{yes}".
<|im_end|>
<|im_start|>user
{input}
<|im_end|>
<|im_start|>assistant
"""
prompt = replace(prompt, "{input}" => usermsg)
result = sendReceivePrompt(a, prompt)
result = GeneralUtils.getStringBetweenCharacters(result, "{", "}")
if result == "yes"
prompt =
"""
<|im_start|>system
You are a helpful assistant.
Your job is to make a concise summary of user's text.
<|im_end|>
<|im_start|>user
{input}
<|im_end|>
<|im_start|>assistant
"""
prompt = replace(prompt, "{input}" => input)
result = sendReceivePrompt(a, prompt)
summary = replace(result, "<|im_end|>" => "")
if summary[1:1] == "\n"
summary = summary[2:end]
end
end
return summary
end
function chooseThinkingMode(a::T, usermsg::String) where {T<:agent}
thinkingMode = nothing
if a.thought != "nothing"
thinkingMode = :continue_thinking
else
prompt =
"""
<|im_start|>system
{systemMsg}
You have access to the following tools:
{tools}
Your need to determine now whether you will use tools or actions to answer the assignment.
You have the following choices:
If you don't need tools or actions to fininsh the assignment say, "{no}".
If you need tools or actions to finish the assignment say, "{yes}".
<|im_end|>
<|im_start|>user
{input}
<|im_end|>
<|im_start|>assistant
"""
toollines = ""
for (toolname, v) in a.tools
if toolname ["chatbox", "nothing"]
toolline = "$toolname: $(v[:description]) $(v[:input]) $(v[:output])\n"
toollines *= toolline
end
end
prompt = replace(prompt, "{systemMsg}" => a.roles[a.role])
prompt = replace(prompt, "{tools}" => toollines)
prompt = replace(prompt, "{input}" => usermsg)
result = sendReceivePrompt(a, prompt)
willusetools = GeneralUtils.getStringBetweenCharacters(result, "{", "}")
thinkingMode = willusetools == "yes" ? :thinking : :no_thinking
end
return thinkingMode
end
function chooseThinkingMode(a::agentReflex, usermsg::String)
thinkingmode = nothing
if a.thoughtlog != "nothing"
thinkingmode = :continue_thinking
else
prompt =
"""
<|im_start|>system
{systemMsg}
You have access to the following tools:
{tools}
Your job is to determine whether you will use tools or actions to finish the assignment.
Choose one of the following choices:
If you don't need tools or actions to fininsh the assignment say, "{no}".
If you need tools or actions to finish the assignment say, "{yes}".
<|im_end|>
<|im_start|>user
{input}
<|im_end|>
<|im_start|>assistant
"""
toollines = ""
for (toolname, v) in a.tools
if toolname ["chatbox", "nothing"]
toolline = "$toolname: $(v[:description]) $(v[:input]) $(v[:output])\n"
toollines *= toolline
end
end
prompt = replace(prompt, "{systemMsg}" => a.roles[a.role])
prompt = replace(prompt, "{tools}" => toollines)
prompt = replace(prompt, "{input}" => usermsg)
result = sendReceivePrompt(a, prompt)
willusetools = GeneralUtils.getStringBetweenCharacters(result, "{", "}")
thinkingmode = willusetools == "yes" ? :new_thinking : :no_thinking
end
return thinkingmode
end
# function identifyUserIntention(a::T, usermsg::String) where {T<:agent}
# prompt =
# """
# <|im_start|>system
# You are a helpful assistant. Your job is to determine intention of the question.
# You have the following choices:
# If the user question is about general conversation say, "{chat}".
# If the user question is about getting wine say, "{wine}".
# <|im_end|>
# Here are the context for the question:
# {context}
# <|im_start|>user
# {input}
# <|im_end|>
# <|im_start|>assistant
# """
# prompt = replace(prompt, "{context}" => "")
# prompt = replace(prompt, "{input}" => usermsg)
# result = sendReceivePrompt(a, prompt)
# answer = result === nothing ? nothing : GeneralUtils.getStringBetweenCharacters(result, "{", "}")
# return answer
# end
"""
Send a msg to registered mqtt topic within mqttClient.
```jldoctest
julia> using JSON3, UUIDs, Dates, FileIO, CommUtils, ChatAgent
julia> mqttClientSpec = (
clientName= "someclient", # name of this client
clientID= "$(uuid4())",
broker= "mqtt.yiem.ai",
pubtopic= (imgAI="img/api/v0.0.1/gpu/request",
txtAI="txt/api/v0.1.0/gpu/request"),
subtopic= (imgAI="agent/api/v0.1.0/img/respond",
txtAI="agent/api/v0.1.0/txt/respond"),
keepalive= 30,
)
julia> msgMeta = Dict(
:msgPurpose=> "updateStatus",
:from=> "agent",
:to=> "llmAI",
:requestrespond=> "request",
:sendto=> "", # destination topic
:replyTo=> "agent/api/v0.1.0/txt/respond", # requester ask responder to send reply to this topic
:repondToMsgId=> "", # responder is responding to this msg id
:taskstatus=> "", # "complete", "fail", "waiting" or other status
:timestamp=> Dates.now(),
:msgId=> "$(uuid4())",
)
julia> newAgent = ChatAgent.agentReact(
"Jene",
mqttClientSpec,
role=:assistant_react,
msgMeta=msgMeta
)
```
"""
function sendReceivePrompt(a::T, prompt::String; timeout::Int=120) where {T<:agent}
a.msgMeta[:msgId] = "$(uuid4())" # new msg id for each msg
msg = Dict(
:msgMeta=> a.msgMeta,
:txt=> prompt,
)
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
"""
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
#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=["</response>", "<<END>>", ],
)
_output_jl = pyconvert(Dict, output_py);
output = pyconvert(Dict, _output_jl["choices"][1]);
output["text"]
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
"""
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
"""
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)
2-element Vector{Any}:
(header = "First", body = ", we need to find out what kind of wine the ")
(header = "user", body = " wants.")
```
"""
function chunktext(text::T, headers) where {T<:AbstractString}
result = []
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))
else
body = text[v[:stop]+1: end]
push!(result, (header=v[:char], body=body))
end
end
return result
end
function extractStepFromPlan(a::agent, plan::T, stepToExtract::Int) where {T<:AbstractString}
prompt =
"""
<|im_start|>system
You are a helpful assistant.
Your job is to determine whether step {$stepToExtract} is in the user plan.
Choose one of the following choices:
If there isn't say, {no}.
If there is say, {yes}. {copy the step and put it here}
<|im_end|>
<|im_start|>user
$plan
<|im_end|>
<|im_start|>assistant
"""
isStep = nothing
step = nothing
respond = sendReceivePrompt(a, prompt)
isStep = GeneralUtils.getStringBetweenCharacters(respond, "{", "}")
if isStep == "no"
isStep = false
step = "nothing"
elseif isStep == "yes"
isStep = true
step = split(respond, "{yes}")[end]
else
error("undefined condition. isStep=$isStep $(@__LINE__)")
end
return isStep, step
end
end # module