Files
ChatAgent_v2/src/interface.jl
2023-11-21 07:00:01 +00:00

989 lines
33 KiB
Julia
Executable File

module interface
export agentReact, addNewMessage, clearMessage, removeLatestMsg, generatePrompt_tokenPrefix,
generatePrompt_tokenSuffix, conversation, work, detectCharacters, chunktext,
findDetectedCharacter, wikisearch
using JSON3, DataStructures, Dates, UUIDs, HTTP
using CommUtils, GeneralUtils
# ---------------------------------------------------------------------------- #
# 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
abstract type agent end
@kwdef mutable struct agentReact <: agent
availableRole::AbstractVector = ["system", "user", "assistant"]
agentName::String = "assistant"
maxUserMsg::Int = 10
earlierConversation::String = "" # summary of earlier conversation
mqttClient::Union{mqttClient, Nothing} = nothing
msgMeta::Union{Dict, Nothing} = nothing
""" Dict(Role=> Content) ; Role can be system, user, assistant
Example:
messages=[
Dict(:role=>"system", :content=> "You are a helpful assistant."),
Dict(:role=>"assistant", :content=> "How may I help you"),
Dict(:role=>"user", :content=> "Hello, how are you"),
]
"""
role::Symbol = :assistant
roles::Dict = Dict(:assistant => "You are a helpful assistant.",)
# Ref: Chat prompt format https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/discussions/3
# messages= [Dict(:role=>"system", :content=> "", :timestamp=> Dates.now()),]
messages = Vector{Dict{Symbol, Any}}()
context::String = "nothing" # internal thinking area
tools::Union{Dict, Nothing} = nothing
thought::String = "nothing" # contain unfinished thoughts for ReAct agent only
thoughtround::Int = 0 # no. of thinking round
thoughtlimit::Int = 5 # thinking round limit
thinkingMode::Union{Dict, Nothing} = nothing
end
function agentReact(
agentName::String,
mqttClientSpec::NamedTuple;
role::Symbol=:assistant,
roles::Dict=Dict(
:assistant =>
"""
You are a helpful assistant who answer the user's questions as best you can.
""",
:sommelier =>
"""
You are a sommelier at an online wine reseller who always ask user for wine relevant info before you could help them choosing wine.
You provide a personalized recommendation of up to two wines based on the user's preference, and you describe the benefits of each wine in detail.
You don't know other people personal info previously.
Info used to select wine:
- type of food
- occasion
- user's personal taste of wine
- wine price range
- temperature at the serving location
- wine we have in stock
""",
),
thinkingMode::Dict=Dict(
:no_thinking=> "",
:thinking=>
"""Use the following format:
Question: the input question your user is asking and you must answer
Plan: first you should always think about the question and the info you have thoroughly then extract and devise a complete plan to find the answer (pay attention to variables and their corresponding numerals).
Thought: ask yourself do you have all the info you need? And what to do according to the plan (pay attention to correct numeral calculation and commonsense).
Act: the tool that match your thought, should be one of {toolnames}
ActInput: the input to the action (pay attention to the tool's input)
Obs: the result of the action
... (this Plan/Thought/Act/ActInput/Obs can repeat N times until you know the answer.)
Thought: I think I know the answer
Answer: Answer of the original question
Begin!""",
),
tools::Dict=Dict(
:wikisearch=>Dict(
:name => "wikisearch",
:description => "Useful for when you need to search an encyclopedia",
:input => "Input is keywords and not a question.",
:output => "",
:func => wikisearch, # put function here
),
:chatbox=>Dict(
:name => "chatbox",
:description => "Useful for when you need to ask a customer for more context.",
:input => "Input should be a conversation to customer.",
:output => "" ,
:func => nothing,
),
# :wineStock=>Dict(
# :name => "wineStock",
# :description => "useful for when you need to search for wine by your description, price, name or ID.",
# :input => "Input should be a search query with as much details as possible.",
# :output => "" ,
# :func => nothing,
# ),
# :NTHING=>Dict(
# :name => "NTHING",
# :description => "useful for when you don't need to use tools or actions",
# :input => "No input is needed",
# :output => "" ,
# :func => nothing,
# ),
),
msgMeta::Dict=Dict(
:msgPurpose=> "updateStatus",
:from=> "chatbothub",
:to=> "llmAI",
:requestrespond=> "request",
:sendto=> "", # destination topic
:replyTo=> "chatbothub/llm/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())",
),
availableRole::AbstractArray=["system", "user", "assistant"],
maxUserMsg::Int=10,)
newAgent = agentReact()
newAgent.availableRole = availableRole
newAgent.maxUserMsg = maxUserMsg
newAgent.mqttClient = CommUtils.mqttClient(mqttClientSpec)
newAgent.msgMeta = msgMeta
newAgent.tools = tools
newAgent.role = role
newAgent.roles = roles
newAgent.thinkingMode = thinkingMode
return newAgent
end
"""
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"
a.context = "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 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)
if thinkingMode [:react]
prompt = replace(prompt, "{tools}" => "You have access to the following tools:\n$toollines")
end
prompt = replace(prompt, "{context}" => a.context)
prompt *= "<|im_start|>user\nQuestion: " * usermsg * "\n<|im_end|>\n"
prompt *= "<|im_start|>assistant\n"
return prompt
end
"""
Chat with llm.
```jldoctest
julia> using JSON3, UUIDs, Dates, FileIO, CommUtils, ChatAgent
julia> mqttClientSpec = (
clientName= "someclient", # name of this client
clientID= "$(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.thoughtround): $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.thoughtround += 1
@show a.thoughtround
toolname = nothing
toolinput = nothing
if a.thoughtround > a.thoughtlimit
a.thought *= "Thought $(a.thoughtround): I think I know the answer."
prompt = a.thought
end
@show prompt
respond = sendReceivePrompt(a, prompt)
headerToDetect = nothing
if a.thoughtround == 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.thoughtround):")[1]
headerToDetect = ["Question $(a.thoughtround):", "Plan $(a.thoughtround):",
"Thought $(a.thoughtround):", "Act $(a.thoughtround):",
"ActInput $(a.thoughtround):", "Obs $(a.thoughtround):",
"...", "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.thoughtround):")
if length(Answer) == 1 && length(Act) == 0
a.thought = "nothing" # question finished, no more thought
a.context = "nothing"
a.thoughtround = 0
respond = chunkedtext[AnswerInd][:body]
respond = replace(respond, "<|im_end|>"=>"")
_ = addNewMessage(a, "assistant", respond)
break
else
# check for tool being called
ActHeader = a.thoughtround == 1 ? "Act:" : "Act $(a.thoughtround):"
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.thoughtround == 1 ? "ActInput:" : "ActInput $(a.thoughtround):"
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.thoughtround -= 1
continue
end
if a.thought == "nothing"
thought = ""
for i in chunkedtext
header = i[:header]
header = replace(header, ":"=>" $(a.thoughtround):") # add number so that llm not confused
body = i[:body]
thought *= "$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.thoughtround): $_result\n"
a.thought *= result
prompt = a.thought
end
end
end
@show respond
return respond
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 context:
{context}
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 = $role")
end
end
prompt = replace(prompt, "{conversation}" => conversation)
prompt = replace(prompt, "{context}" => a.context)
result = sendReceivePrompt(a, prompt)
summary = result === nothing ? "nothing" : result
summary = replace(summary, "<|im_end|>" => "")
if summary[1:1] == "\n"
summary = summary[2:end]
end
end
return summary
end
function makeSummary(a::T1, input::T2) where {T1<:agent, T2<:AbstractString}
summary = "Nothing."
prompt =
"""
<|im_start|>system
Your need to determine now whether you can make a summary of user's text.
You have the following choices:
If you cannot make a summary say, "{no}".
If you can make a summary say, "{yes}".
<|im_end|>
<|im_start|>user
{input}
<|im_end|>
<|im_start|>assistant
"""
prompt = replace(prompt, "{input}" => usermsg)
result = sendReceivePrompt(a, prompt)
result = GeneralUtils.getStringBetweenCharacters(result, "{", "}")
if result == "yes"
prompt =
"""
<|im_start|>system
You are a helpful assistant.
Your job is to make a concise summary of user's text.
<|im_end|>
<|im_start|>user
{input}
<|im_end|>
<|im_start|>assistant
"""
prompt = replace(prompt, "{input}" => input)
result = sendReceivePrompt(a, prompt)
summary = replace(result, "<|im_end|>" => "")
if summary[1:1] == "\n"
summary = summary[2:end]
end
end
return summary
end
function chooseThinkingMode(a::T, usermsg::String) where {T<:agent}
prompt =
"""
<|im_start|>system
{systemMsg}
You have access to the following tools:
{tools}
Your need to determine now whether you will use tools or actions to answer the question.
You have the following choices:
If you already know the answer or don't need tools or actions say, "{no}".
If you need tools or actions to answer the question say, "{yes}".
<|im_end|>
<|im_start|>user
{input}
<|im_end|>
<|im_start|>assistant
"""
toollines = ""
for (toolname, v) in a.tools
if toolname ["chatbox", "nothing"]
toolline = "$toolname: $(v[:description]) $(v[:input]) $(v[:output])\n"
toollines *= toolline
end
end
prompt = replace(prompt, "{systemMsg}" => a.roles[a.role])
prompt = replace(prompt, "{tools}" => toollines)
prompt = replace(prompt, "{input}" => usermsg)
result = sendReceivePrompt(a, prompt)
willusetools = GeneralUtils.getStringBetweenCharacters(result, "{", "}")
thinkingMode = willusetools == "yes" ? :thinking : :no_thinking
return thinkingMode
end
function identifyUserIntention(a::T, usermsg::String) where {T<:agent}
prompt =
"""
<|im_start|>system
You are a helpful assistant. Your job is to determine intention of the question.
You have the following choices:
If the user question is about general conversation say, "{chat}".
If the user question is about getting wine say, "{wine}".
<|im_end|>
Here are the context for the question:
{context}
<|im_start|>user
{input}
<|im_end|>
<|im_start|>assistant
"""
prompt = replace(prompt, "{context}" => "")
prompt = replace(prompt, "{input}" => usermsg)
result = sendReceivePrompt(a, prompt)
answer = result === nothing ? nothing : GeneralUtils.getStringBetweenCharacters(result, "{", "}")
return answer
end
"""
Send a msg to registered mqtt topic within mqttClient.
```jldoctest
julia> using JSON3, UUIDs, Dates, FileIO, CommUtils, ChatAgent
julia> mqttClientSpec = (
clientName= "someclient", # name of this client
clientID= "$(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 $(@__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
function answerNow(a::T) where {T<:agent}
prompt =
"""
<|im_start|>system
{systemMsg}
Your need to determine now whether you will use tools or actions to answer the question.
You have the following choices:
If you don't need tools or actions to answer the question say, "{no}".
If you need tools or actions to answer the question say, "{yes}".
<|im_end|>
"""
prompt = replace(prompt, "{systemMsg}" => a.thought)
error("answerNow done")
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 questions.
If the user question can be answered given the tools available say, "This is a reasonable question".
If the user question cannot be answered then provide some feedback to the user that may improve
their question.
Here is the context for the question:
{context}
<|im_end|>
<|im_start|>user
{question}
<|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, "{question}" => 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
"""
Search wikipedia.
Args:
query (string): The query to search for
Returns:
string: The search result text from wikipedia
```jldoctest
julia> using HTTP, JSON3
julia> result = wikisearch("AMD")
"Advanced Micro Devices, Inc., commonly abbreviated as AMD, is an ..."
```
"""
function wikisearch(phrase::T) where {T<:AbstractString}
url = "https://en.wikipedia.org/w/api.php?action=query&format=json&prop=extracts&titles=$(replace(phrase, " " => "%20"))&exintro=1&explaintext=1"
response = HTTP.get(url)
json_data = JSON3.read(String(response.body))
page_id = first(keys(json_data["query"]["pages"]))
if page_id == "-1"
return "Sorry, I couldn't find any Wikipedia page for the given phrase."
end
result = nothing
try
result = json_data["query"]["pages"][page_id]["extract"]
catch
result = "No info available."
end
if result == ""
result = "No info available."
end
return result
end
end # module