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tonaerospace
2023-11-28 00:58:08 +00:00
parent ef67e9fd19
commit 7825979abf
2 changed files with 51 additions and 37 deletions
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73
src/interface.jl
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@@ -3,7 +3,7 @@ module interface
export agentReact, agentReflex,
addNewMessage, clearMessage, removeLatestMsg, conversation, writeEvaluationGuideline,
grading, analyze, selfReflext
grading, analyze, selfReflext, actor_mistral_openorca2
using JSON3, DataStructures, Dates, UUIDs, HTTP
using CommUtils, GeneralUtils
@@ -319,7 +319,8 @@ function planner_mistral_openorca(a::agentReflex, usermsg::String)
return prompt
end
function actor_mistral_openorca(a::agentReflex, usermsg::T) where {T<:AbstractString}
#WORKING try use Thought/Act/ActInput/Obs loop because some time step 2 depend on step 1
function actor_mistral_openorca(a::agentReflex, usermsg, plan, step)
"""
general prompt format:
@@ -359,11 +360,13 @@ function actor_mistral_openorca(a::agentReflex, usermsg::T) where {T<:AbstractSt
{usermsg}
<|im_end|>
<|im_start|>assistant
{plan}
"""
prompt = replace(prompt, "{role}" => a.roles[a.role])
prompt = replace(prompt, "{thinkingFormat}" => a.thinkingFormat[:actor])
prompt = replace(prompt, "{step}" => step)
prompt = replace(prompt, "{plan}" => plan)
toolnames = ""
toollines = ""
for (toolname, v) in a.tools
@@ -634,22 +637,22 @@ function work(a::agentReflex, usermsg::String)
respond = sendReceivePrompt(a, prompt)
plan = split(respond, "<|im_end|>")[1]
plan = split(plan, "Response:")[1]
_plan = replace(plan, "Plan:"=>"Plan $(a.attempt):")
logmsg = "assistant: $_plan\n"
plan = replace(plan, "Plan:"=>"Plan $(a.attempt):")
logmsg = "assistant: $plan\n"
a.memory[:shortterm] *= logmsg
a.thoughtlog *= logmsg
actorstate, msgToUser = actor(a, plan)
actorstate, msgToUser = actor(a, usermsg, plan)
if actorstate == "chatbox"
respond = msgToUser
break
elseif actorstate == "all steps done"
println("all steps done")
#WORKING give answer to the question
respond = formulateRespond(a, a.memory[:shortterm])
a.memory[:shortterm] *= "Respond: $respond\n"
#TODO evaluate. if score < 8/10 try again.
# evaluate. if score < 8/10 try again.
headerToDetect = ["user:", "assistant:", ]
headers = detectCharacters(a.memory[:shortterm], headerToDetect)
chunkedtext = chunktext(a.memory[:shortterm], headers)
@@ -664,9 +667,10 @@ function work(a::agentReflex, usermsg::String)
a.thoughtlog = ""
break
else # self evaluate and reflect then try again
report = analyze(a, a.memory[:shortterm])
@show report
lessonwithcontext = selfReflext(a, report)
analysis = analyze(a, a.memory[:shortterm])
@show analysis
lessonwithcontext = selfReflext(a, analysis)
@show lessonwithcontext
a.memory[:shortterm] = ""
#TODO add lesson and context into longterm memory
@@ -676,7 +680,7 @@ function work(a::agentReflex, usermsg::String)
@show chunkedtext
push!(a.memory[:longterm], Dict(:context=>chunkedtext["Context:"],
:lesson=>chunkedtext["Lesson:"]))
error(">>>>>>>>>>")
error(">>>>>>>>>")
end
else
error("undefied condition, actorstate $actorstate $(@__LINE__)")
@@ -719,7 +723,7 @@ end
msgToUser = "message from assistant to user"
"""
function actor(a::agentReflex, plan::T) where {T<:AbstractString}
function actor(a::agentReflex, usermsg, plan)
actorState = nothing
msgToUser = nothing
@@ -731,28 +735,39 @@ function actor(a::agentReflex, plan::T) where {T<:AbstractString}
a.step += 1
@show a.step
if a.step <= totalsteps
stepdetail = extractStepFromPlan(a, plan, a.step)
prompt = actor_mistral_openorca(a, stepdetail)
# WORKING in step 2, I need to use a.memory[:shortterm] as input to actor()
prompt = actor_mistral_openorca(a, usermsg, plan, a.step)
@show prompt
respond = sendReceivePrompt(a, prompt)
respond = split(respond, "<|im_end|>")[1]
@show respond
headerToDetect = ["Question:", "Plan:", "Thought:", "Act:", "ActInput:", "Obs:", "...", "Answer:",
"Conclusion:", "Summary:"]
headers = detectCharacters(respond, headerToDetect)
# some time LLM not generate a number after headers but I want it
if occursin("Act:", respond)
headerToDetect = ["Question:", "Plan:", "Thought:",
"Act:", "ActInput:", "Obs:", "...",
"Answer:", "Conclusion:", "Summary:"]
headers = detectCharacters(respond, headerToDetect)
respond = addStepNumber(respond, headers, a.step)
end
respond = split(respond, "Obs $(a.step):")[1]
# add to memory
_respond = addStepNumber(respond, headers, a.step)
a.memory[:shortterm] *= _respond
a.thoughtlog *= _respond
a.memory[:shortterm] *= respond
a.thoughtlog *= respond
headerToDetect = ["Question $(a.step):", "Plan $(a.step):", "Thought $(a.step):",
"Act $(a.step):", "ActInput $(a.step):", "Obs $(a.step):", "...",
"Answer $(a.step):", "Conclusion $(a.step):", "Summary $(a.step):"]
headers = detectCharacters(respond, headerToDetect)
chunkedtext = chunktext(respond, headers)
toolname = toolNameBeingCalled(chunkedtext["Act:"], a.tools)
toolinput = chunkedtext["ActInput:"]
@show chunkedtext
toolname = toolNameBeingCalled(chunkedtext["Act $(a.step):"], a.tools)
toolinput = chunkedtext["ActInput $(a.step):"]
@show toolname
@show toolinput
error(">>>>>>>>>")
if toolname == "chatbox" # chat with user
#TODO donot use chatbox to respond to user
respond = toolinput
msgToUser = respond
actorState = toolname
@@ -925,8 +940,7 @@ function analyze(a, shorttermMemory::T) where {T<:AbstractString}
1. What happened?
2. List all relationships, each with cause and effect .
3. Look at each relationship, figure out why it behaved that way.
4. Do relationships behaved differently than your expectation? If yes, why?
5. What could you do to improve the respond?
4. What could you do to improve the respond?
<|im_end|>
"""
@@ -935,7 +949,6 @@ function analyze(a, shorttermMemory::T) where {T<:AbstractString}
end
""" Write a lesson drawn from evaluation.
Args:
@@ -968,7 +981,7 @@ julia> report =
julia> lesson = selfReflext(agent, report)
```
"""
function selfReflext(a, report::T) where {T<:AbstractString}
function selfReflext(a, analysis::T) where {T<:AbstractString}
prompt =
"""
<|im_start|>system

15
src/type.jl
View File

@@ -95,15 +95,16 @@ function agentReflex(
:planner=>
"""Use the following format:
Stimulus: the input user gives to you and you must respond
Plan: first you should always think about the stimulus and the info you have thoroughly then extract and devise a step by step plan to prepare a respond (pay attention to correct numeral calculation and commonsense).
Plan: first you should always think about the stimulus and the info you have thoroughly then extract and devise a step by step plan to respond (pay attention to correct numeral calculation and commonsense).
""",
:actor=>
"""Use the following format:
Stimulus: the input user gives to you and you must respond
Thought: your should always think about what to do (pay attention to correct numeral calculation and commonsense).
Act: the action to take that match your thought, should be one of [{toolnames}]
ActInput: the input to the action (pay attention to the tool's input)
""",
"""Use the following format:
Plan: first you should always think about the stimulus and the info you have thoroughly then extract and devise a step by step plan to respond (pay attention to correct numeral calculation and commonsense).
Thought: your should always think what to do to carry out the plan's step {step} (pay attention to correct numeral calculation and commonsense).
Act: the action to take 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
""",
),
tools::Dict=Dict(
:chatbox=>Dict(