update
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100
src/interface.jl
100
src/interface.jl
@@ -9,7 +9,7 @@ export agentReact, agentReflex,
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using JSON3, DataStructures, Dates, UUIDs, HTTP, Random
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using CommUtils, GeneralUtils
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using ..type, ..utils
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using ..type, ..utils, ..llmfunction
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# ---------------------------------------------------------------------------- #
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# pythoncall setting #
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@@ -494,12 +494,16 @@ function selfAwareness(a::agentReflex)
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chunkedtext = chunktext(response, headers[1:3])
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println("")
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_infomatch = chunkedtext["Info matching:"]
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_infomatch = GeneralUtils.getStringBetweenCharacters(_infomatch, '{', '}', endCharLocation="next")
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infomatch = copy(JSON3.read(_infomatch))
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_infomatch = GeneralUtils.getStringBetweenCharacters(_infomatch, '{', '}', endCharLocation="end")
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infomatch = GeneralUtils.JSON3read_stringKey(_infomatch)
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# infomatch = copy(JSON3.read(_infomatch))
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println("")
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@show chunkedtext
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println("")
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@show infomatch
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keywordMemoryUpdate!(a.memory[:keyword], infomatch)
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response = "What I know about user:" * JSON3.write(a.memory[:keyword]) # * response
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@@ -817,41 +821,6 @@ function actor_mistral_openorca(a::agentReflex, selfaware=nothing)
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end
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end
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# prompt =
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# """
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# <|system|>
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# <About yourself>
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# $aboutYourself
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# </About yourself>
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# <You have access to the following tools>
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# $toollines
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# </You have access to the following tools>
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# <Your plan>
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# $(a.memory[:shortterm]["Plan 1:"])
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# </Your plan>
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# <What I know about the user>
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# $(JSON3.write(a.memory[:keyword]))
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# </What I know about the user>
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# <Your job>
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# Use the following format:
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# $thought
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# Act: based on your thought what action to choose?, must be one of [{toolnames}].
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# Actinput: your input to the action (pay attention to the tool's input)
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# Obs: observed result of the action
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# </Your job>
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# <Example>
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# <What I know about the user>
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# $(readKeywordMemory(a))
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# </What I know about the user>
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# Thought: based on what you know, I think he also need to know whether there are any charging station near by his house. I should search the internet to get this info.
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# Act: internetsearch
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# Actinput: {\"internetsearch\": \"EV charging station near Bangkok\"}
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# </Example>
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# </s>
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# <|assistant|>
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# $startword
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# """
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"""
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- Car type is SUV
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- Brand is Lexus
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@@ -894,9 +863,9 @@ function actor_mistral_openorca(a::agentReflex, selfaware=nothing)
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- Luxury level is high
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</What I know about the user>
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<|assistant|>
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Thought: I still don't know what color the user like. I should ask the user.
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Thought: Based on what I know about the user, I still don't know what color the user like. I should ask the user.
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Act: askbox
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Actinput: {\"askbox\": \"What color do you like?\"}
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Actinput:
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</|assistant|>
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</Example 1>
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</s>
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@@ -1007,7 +976,6 @@ function actor_mistral_openorca(a::agentReflex, selfaware=nothing)
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end
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if check_1 && check_2 && check_3 && check_4 && check_5 && check_6 && check_7
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#TODO paraphrase selfaware
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break
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end
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# print all check_1 to check_6
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@@ -1034,21 +1002,27 @@ function actor_mistral_openorca(a::agentReflex, selfaware=nothing)
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"Check $latestTask:",]
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headers = detectCharacters(response, headerToDetect)
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chunkedtext = chunktext(response, headers)
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chunkedtext["Act $latestTask:"] = toolname
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println("")
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@show chunkedtext
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toolinput = chunkedtext["Actinput $latestTask:"]
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# because tools has JSON input but sometime LLM output is not JSON, we need to check.
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if occursin("{", toolinput)
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act = GeneralUtils.getStringBetweenCharacters(response, '{', '}', endCharLocation="end")
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act = copy(JSON3.read(act))
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chunkedtext["Actinput $latestTask:"] = JSON3.write(act[Symbol(toolname)])
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a.memory[:c] = chunkedtext
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toolinput = act[Symbol(toolname)]
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end
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# # because tools has JSON input but sometime LLM output is not JSON, we need to check.
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# if occursin("{", toolinput)
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# act = GeneralUtils.getStringBetweenCharacters(response, '{', '}', endCharLocation="end")
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# act = copy(JSON3.read(act))
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# println("")
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# @show act
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# chunkedtext["Actinput $latestTask:"] = JSON3.write(act[Symbol(toolname)])
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# a.memory[:c] = chunkedtext
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# toolinput = act[Symbol(toolname)]
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# end
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chunkedtext["Act $latestTask:"] = toolname
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return (toolname=toolname, toolinput=toolinput, chunkedtext=chunkedtext, selfaware=selfaware)
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end
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@@ -1275,25 +1249,29 @@ function actor(a::agentReflex)
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end
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actorResult = actor_mistral_openorca(a, selfaware)
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println("")
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toolname, toolinput, chunkedtext, selfaware = actorResult
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println("")
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@show toolname
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@show toolinput
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println(typeof(toolinput))
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println("")
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addShortMem!(a.memory[:shortterm], chunkedtext)
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println("")
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if toolname == "askbox" # chat with user
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msgToUser = toolinput
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msgToUser = askbox(toolinput)
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actorState = toolname
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#WORKING add only a single Q1 to memory because LLM need to ask the user only 1 question at a time
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latestTask = shortMemLatestTask(a.memory[:shortterm]) +1
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chunkedtext["Actinput $latestTask:"] = msgToUser
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addShortMem!(a.memory[:shortterm], chunkedtext)
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break
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elseif toolname == "finalanswer"
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addShortMem!(a.memory[:shortterm], chunkedtext)
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println(">>> already done")
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actorState = "formulateFinalResponse"
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break
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else # function call
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addShortMem!(a.memory[:shortterm], chunkedtext)
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f = a.tools[toolname][:func]
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toolresult = f(a, actorResult)
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@show toolresult
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@@ -1922,12 +1900,12 @@ end
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""" Convert keyword memory into a string.
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Arguments:
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a, one of ChatAgent's agent.
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keywordmemory, a dictionary of keyword memory.
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Arguments\n
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a : one of ChatAgent's agent.
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keywordmemory : a dictionary of keyword memory.
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Return:
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a string of LLM readout from keyword memory
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Return\n
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result : a string of LLM readout from keyword memory
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Example:
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```jldoctest
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