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youremail@yourdomain.com
2023-12-26 14:24:44 +00:00
parent 3b3cbbc83f
commit a593d4994c
2 changed files with 236 additions and 12 deletions
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247
src/interface.jl
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@@ -134,7 +134,7 @@ function chat_mistral_openorca(a::agentReflex)
<|assistant|>
"""
response = sendReceivePrompt(a, prompt)
response = sendReceivePrompt(a, prompt, timeout=180)
response = split(response, "<|im_end|>")[1]
return response
@@ -268,6 +268,24 @@ function updatePlan(a::agentReflex)
end
function actor_mistral_openorca(a::agentReflex, taskrecap="")
getonlykeys = ["Actinput", "Obs"]
worknoplan = similar(a.memory[:shortterm])
for (k, v) in a.memory[:shortterm]
count = 0
for i in getonlykeys
if occursin(i, k)
count += 1
end
end
if count != 0
worknoplan[k] = v
end
end
work = dictToString(worknoplan)
"""
general prompt format:
@@ -320,8 +338,9 @@ function actor_mistral_openorca(a::agentReflex, taskrecap="")
aware = ""
if taskrecap != ""
start = "Self-awareness"
aware = "Self-awareness: based on the recap and the plan, state your current understanding of the matter."
# aware = "Self-awareness: based on the recap, check your progress against the plan and assess the current situation to identify tasks that you need to address."
# aware = "Self-awareness: based on the recap, assess your progress against the plan then identify areas where you need to address."
# aware = "Self-awareness: based on the recap and the plan, state your current understanding of the matter in details then identify areas where you need to address."
aware = "Self-awareness: based on earlier conversation with the user, check your progress against the plan then assess the current situation to identify tasks that you need to address."
end
winestockResult = ""
@@ -344,20 +363,17 @@ function actor_mistral_openorca(a::agentReflex, taskrecap="")
<Your plan>
$(a.memory[:shortterm]["Plan 1:"])
</Your plan>
<Your earlier work's recap>
$taskrecap
</Your earlier work's recap>
$winestockResult
<Your job>
Use the following format:
$aware
Thought: based on the plan and self-awareness, What to do? (P.S. ask the user one by one question, pay attention to correct numeral calculation and commonsense)
Act: an action to take based on your thought, must be one of [{toolnames}]
Thought: based on the plan and self-awareness, What to do? (P.S.1 pay attention to correct numeral calculation and commonsense.)
Act: an action to take, must be one of [{toolnames}]
Actinput: your input to the action based on your thought (pay attention to the tool's input)
Obs: observed result of the action
</Your job>
</s>
<|assistant|>
$work
$start:
"""
prompt = replace(prompt, "{toolnames}" => toolnames)
@@ -373,7 +389,7 @@ function actor_mistral_openorca(a::agentReflex, taskrecap="")
while true # while Thought or Act is empty, run actor again
# tempcounter += 0.1
@show tempcounter
response = sendReceivePrompt(a, prompt, max_tokens=1024, temperature=tempcounter)
response = sendReceivePrompt(a, prompt, max_tokens=1024, temperature=tempcounter, timeout=180)
response = splittext(response, ["Obs", "<|im_end|>"])
latestTask = shortMemLatestTask(a.memory[:shortterm]) +1
@@ -443,6 +459,201 @@ function actor_mistral_openorca(a::agentReflex, taskrecap="")
return toolname, toolinput, chunkedtext
end
# function actor_mistral_openorca(a::agentReflex, taskrecap="")
# getonlykeys = ["Actinput", "Obs"]
# worknoplan = similar(a.memory[:shortterm])
# for (k, v) in a.memory[:shortterm]
# count = 0
# for i in getonlykeys
# if occursin(i, k)
# count += 1
# end
# end
# if count != 0
# worknoplan[k] = v
# end
# end
# work = dictToString(worknoplan)
# """
# general prompt format:
# "
# <|im_start|>system
# {role}
# {tools}
# {thinkingFormat}
# <|im_end|>
# {context}
# <|im_start|>user
# {usermsg}
# <|im_end|>
# <|im_start|>assistant
# "
# Note:
# {context} =
# "
# {earlierConversation}
# {env state}
# {shortterm memory}
# {longterm memory}
# "
# """
# #BUG BIG output from winestock cause recap() to fail.
# #BUG2 LLM repeat winestock search without recommending wine
# toolnames = ""
# toollines = ""
# for (toolname, v) in a.tools
# toolline = "$toolname: $(v[:description]) $(v[:input]) $(v[:output])\n"
# toollines *= toolline
# toolnames *= "$toolname, "
# end
# # shorttermMemory = dictToString(a.memory[:shortterm], skiplist=["user:"])
# # conversation = conversationSummary(a)
# # println("")
# # @show conversationSum = conversation
# # context =
# # """
# # Your talk with the user:
# # $conversation
# # """
# start = "Thought"
# aware = ""
# if taskrecap != ""
# start = "Self-awareness"
# # aware = "Self-awareness: based on the recap, assess your progress against the plan then identify areas where you need to address."
# # aware = "Self-awareness: based on the recap and the plan, state your current understanding of the matter in details then identify areas where you need to address."
# aware = "Self-awareness: based on the recap, check your progress against the plan and assess the current situation to identify tasks that you need to address."
# end
# winestockResult = ""
# if a.winestockResult != ""
# winestockResult =
# """
# <winestock search result>
# $(a.winestockResult)
# </winestock search result>
# """
# end
# prompt =
# """
# <|system|>
# $(a.roles[a.role])
# <You have access to the following tools>
# $toollines
# </You have access to the following tools>
# <Your plan>
# $(a.memory[:shortterm]["Plan 1:"])
# </Your plan>
# <Your earlier work's recap>
# $work
# </Your earlier work's recap>
# $winestockResult
# <Your job>
# Use the following format:
# $aware
# Thought: based on the plan and self-awareness, What to do? (P.S.1 pay attention to correct numeral calculation and commonsense.)
# Act: an action to take based on your thought, must be one of [{toolnames}]
# Actinput: your input to the action based on your thought (pay attention to the tool's input)
# Obs: observed result of the action
# </Your job>
# </s>
# <|assistant|>
# $start:
# """
# prompt = replace(prompt, "{toolnames}" => toolnames)
# println("")
# @show actor_prompt = prompt
# response = nothing
# chunkedtext = nothing
# latestTask = nothing
# tempcounter = 0.2
# while true # while Thought or Act is empty, run actor again
# # tempcounter += 0.1
# @show tempcounter
# response = sendReceivePrompt(a, prompt, max_tokens=1024, temperature=tempcounter)
# response = splittext(response, ["Obs", "<|im_end|>"])
# latestTask = shortMemLatestTask(a.memory[:shortterm]) +1
# if start == "Thought"
# response = "Thought $latestTask: " * response
# else
# response = "Self-awareness $latestTask: " * response
# end
# headerToDetect = ["Question:", "Plan:", "Self-awareness:", "Thought:",
# "Act:", "Actinput:", "Obs:", "...",
# "Answer:", "Conclusion:", "Summary:"]
# # replace headers with headers with correct attempt and task number
# response = replaceHeaders(response, headerToDetect, latestTask)
# response = split(response, "<|")[1]
# response = split(response, "</")[1]
# headers = detectCharacters(response, headerToDetect)
# println("")
# headerToDetect = ["Plan $(a.attempt):",
# "Self-awareness $latestTask:",
# "Thought $latestTask:",
# "Act $latestTask:",
# "Actinput $latestTask:",
# "Obs $latestTask:",
# "Check $latestTask:",]
# headers = detectCharacters(response, headerToDetect)
# chunkedtext = chunktext(response, headers)
# # assuming length more than 10 character means LLM has valid thinking
# @show iskey_Thought = haskey(chunkedtext, "Thought $latestTask:")
# @show iskey_Act = haskey(chunkedtext, "Act $latestTask:")
# @show iskey_Actinput = haskey(chunkedtext, "Actinput $latestTask:")
# if iskey_Thought && iskey_Act && iskey_Actinput
# if chunkedtext["Thought $latestTask:"] != " " && chunkedtext["Act $latestTask:"] != " " &&
# length(chunkedtext["Actinput $latestTask:"]) > 5
# break
# end
# end
# end
# toolname = toolNameBeingCalled(chunkedtext["Act $latestTask:"], a.tools)
# toolinput = chunkedtext["Actinput $latestTask:"]
# # change trailing number to continue a.memory[:shortterm]
# headerToDetect = ["Question:", "Plan:", "Self-awareness:", "Thought:",
# "Act:", "Actinput:", "Obs:", "...",
# "Answer:", "Conclusion:", "Summary:"]
# response = replaceHeaders(response, headerToDetect, latestTask)
# println("")
# @show actor_response = response
# headerToDetect = ["Plan $(a.attempt):",
# "Thought $latestTask:",
# "Act $latestTask:",
# "Actinput $latestTask:",
# "Obs $latestTask:",
# "Check $latestTask:",]
# headers = detectCharacters(response, headerToDetect)
# chunkedtext = chunktext(response, headers)
# chunkedtext = delete!(chunkedtext, "Self-awareness $latestTask")
# return toolname, toolinput, chunkedtext
# end
"""
@@ -1162,6 +1373,14 @@ function recap(a)
work = dictToString(worknoplan)
toolnames = ""
toollines = ""
for (toolname, v) in a.tools
toolline = "$toolname: $(v[:description]) $(v[:input]) $(v[:output])\n"
toollines *= toolline
toolnames *= "$toolname, "
end
# prompt =
# """
# <|system|>
@@ -1186,6 +1405,8 @@ function recap(a)
# Recap:
# """
prompt =
"""
<|system|>
@@ -1197,12 +1418,14 @@ function recap(a)
Actinput: the input to the action
Obs: the result of the action
</Symbol meaning>
<You have access to the following tools>
$toollines
</You have access to the following tools>
<Your earlier work>
$work
</Your earlier work>
<Your job>
Extract info: extract each info in details from your earlier work into a bullet summary.
Extract info: extract each info in details from your earlier work according to the Actinput context.
</Your job>
Let's think step by step.

1
src/llmfunction.jl
View File

@@ -89,6 +89,7 @@ function winestock(a::agentReflex, phrase::T) where {T<:AbstractString}
# """
result =
"""
I found the following wines
{
1: {
wine name: Louis Latou - Corton-Charlamagne,