update
This commit is contained in:
narawat lamaiin
17
.vscode/launch.json
vendored
Normal file
17
.vscode/launch.json
vendored
Normal file
@@ -0,0 +1,17 @@
|
||||
{
|
||||
// Use IntelliSense to learn about possible attributes.
|
||||
// Hover to view descriptions of existing attributes.
|
||||
// For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
|
||||
"version": "0.2.0",
|
||||
"configurations": [
|
||||
{
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||||
"type": "julia",
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||||
"request": "launch",
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"name": "Run active Julia file",
|
||||
"program": "${file}",
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"stopOnEntry": false,
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"cwd": "${workspaceFolder}",
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"juliaEnv": "${command:activeJuliaEnvironment}"
|
||||
}
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||||
]
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||||
}
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275
Manifest.toml
275
Manifest.toml
@@ -1,8 +1,8 @@
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# This file is machine-generated - editing it directly is not advised
|
||||
|
||||
julia_version = "1.10.3"
|
||||
julia_version = "1.10.4"
|
||||
manifest_format = "2.0"
|
||||
project_hash = "d5182042dab089bafa4f01ef385efd46c01a0396"
|
||||
project_hash = "42fe76ec8191cf95e51733bee474db0f4870d573"
|
||||
|
||||
[[deps.AliasTables]]
|
||||
deps = ["PtrArrays", "Random"]
|
||||
@@ -21,9 +21,20 @@ uuid = "56f22d72-fd6d-98f1-02f0-08ddc0907c33"
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||||
uuid = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
|
||||
|
||||
[[deps.BitFlags]]
|
||||
git-tree-sha1 = "2dc09997850d68179b69dafb58ae806167a32b1b"
|
||||
git-tree-sha1 = "0691e34b3bb8be9307330f88d1a3c3f25466c24d"
|
||||
uuid = "d1d4a3ce-64b1-5f1a-9ba4-7e7e69966f35"
|
||||
version = "0.1.8"
|
||||
version = "0.1.9"
|
||||
|
||||
[[deps.CEnum]]
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||||
git-tree-sha1 = "eb4cb44a499229b3b8426dcfb5dd85333951ff90"
|
||||
uuid = "fa961155-64e5-5f13-b03f-caf6b980ea82"
|
||||
version = "0.4.2"
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||||
|
||||
[[deps.CSV]]
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||||
deps = ["CodecZlib", "Dates", "FilePathsBase", "InlineStrings", "Mmap", "Parsers", "PooledArrays", "PrecompileTools", "SentinelArrays", "Tables", "Unicode", "WeakRefStrings", "WorkerUtilities"]
|
||||
git-tree-sha1 = "6c834533dc1fabd820c1db03c839bf97e45a3fab"
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||||
uuid = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
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||||
version = "0.10.14"
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||||
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[[deps.Calculus]]
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deps = ["LinearAlgebra"]
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@@ -39,9 +50,9 @@ version = "1.3.5"
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||||
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||||
[[deps.CodecZlib]]
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deps = ["TranscodingStreams", "Zlib_jll"]
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||||
git-tree-sha1 = "59939d8a997469ee05c4b4944560a820f9ba0d73"
|
||||
git-tree-sha1 = "b8fe8546d52ca154ac556809e10c75e6e7430ac8"
|
||||
uuid = "944b1d66-785c-5afd-91f1-9de20f533193"
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||||
version = "0.7.4"
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||||
version = "0.7.5"
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||||
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||||
[[deps.Compat]]
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||||
deps = ["TOML", "UUIDs"]
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@@ -60,9 +71,9 @@ version = "1.1.1+0"
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||||
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[[deps.ConcurrentUtilities]]
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deps = ["Serialization", "Sockets"]
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||||
git-tree-sha1 = "6cbbd4d241d7e6579ab354737f4dd95ca43946e1"
|
||||
git-tree-sha1 = "ea32b83ca4fefa1768dc84e504cc0a94fb1ab8d1"
|
||||
uuid = "f0e56b4a-5159-44fe-b623-3e5288b988bb"
|
||||
version = "2.4.1"
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||||
version = "2.4.2"
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||||
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||||
[[deps.CondaPkg]]
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||||
deps = ["JSON3", "Markdown", "MicroMamba", "Pidfile", "Pkg", "Preferences", "TOML"]
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||||
@@ -70,11 +81,27 @@ git-tree-sha1 = "e81c4263c7ef4eca4d645ef612814d72e9255b41"
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||||
uuid = "992eb4ea-22a4-4c89-a5bb-47a3300528ab"
|
||||
version = "0.2.22"
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||||
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||||
[[deps.Crayons]]
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||||
git-tree-sha1 = "249fe38abf76d48563e2f4556bebd215aa317e15"
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||||
uuid = "a8cc5b0e-0ffa-5ad4-8c14-923d3ee1735f"
|
||||
version = "4.1.1"
|
||||
|
||||
[[deps.DBInterface]]
|
||||
git-tree-sha1 = "a444404b3f94deaa43ca2a58e18153a82695282b"
|
||||
uuid = "a10d1c49-ce27-4219-8d33-6db1a4562965"
|
||||
version = "2.6.1"
|
||||
|
||||
[[deps.DataAPI]]
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||||
git-tree-sha1 = "abe83f3a2f1b857aac70ef8b269080af17764bbe"
|
||||
uuid = "9a962f9c-6df0-11e9-0e5d-c546b8b5ee8a"
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||||
version = "1.16.0"
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||||
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||||
[[deps.DataFrames]]
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||||
deps = ["Compat", "DataAPI", "DataStructures", "Future", "InlineStrings", "InvertedIndices", "IteratorInterfaceExtensions", "LinearAlgebra", "Markdown", "Missings", "PooledArrays", "PrecompileTools", "PrettyTables", "Printf", "REPL", "Random", "Reexport", "SentinelArrays", "SortingAlgorithms", "Statistics", "TableTraits", "Tables", "Unicode"]
|
||||
git-tree-sha1 = "04c738083f29f86e62c8afc341f0967d8717bdb8"
|
||||
uuid = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
|
||||
version = "1.6.1"
|
||||
|
||||
[[deps.DataStructures]]
|
||||
deps = ["Compat", "InteractiveUtils", "OrderedCollections"]
|
||||
git-tree-sha1 = "1d0a14036acb104d9e89698bd408f63ab58cdc82"
|
||||
@@ -90,6 +117,23 @@ version = "1.0.0"
|
||||
deps = ["Printf"]
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||||
uuid = "ade2ca70-3891-5945-98fb-dc099432e06a"
|
||||
|
||||
[[deps.Decimals]]
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||||
git-tree-sha1 = "e98abef36d02a0ec385d68cd7dadbce9b28cbd88"
|
||||
uuid = "abce61dc-4473-55a0-ba07-351d65e31d42"
|
||||
version = "0.4.1"
|
||||
|
||||
[[deps.DispatchDoctor]]
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||||
deps = ["MacroTools", "Preferences"]
|
||||
git-tree-sha1 = "32d236e685d028f5bc808aae0634b58aac5128f0"
|
||||
uuid = "8d63f2c5-f18a-4cf2-ba9d-b3f60fc568c8"
|
||||
version = "0.4.10"
|
||||
|
||||
[deps.DispatchDoctor.extensions]
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||||
DispatchDoctorChainRulesCoreExt = "ChainRulesCore"
|
||||
|
||||
[deps.DispatchDoctor.weakdeps]
|
||||
ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
|
||||
|
||||
[[deps.Distributed]]
|
||||
deps = ["Random", "Serialization", "Sockets"]
|
||||
uuid = "8ba89e20-285c-5b6f-9357-94700520ee1b"
|
||||
@@ -133,6 +177,23 @@ git-tree-sha1 = "dcb08a0d93ec0b1cdc4af184b26b591e9695423a"
|
||||
uuid = "460bff9d-24e4-43bc-9d9f-a8973cb893f4"
|
||||
version = "0.1.10"
|
||||
|
||||
[[deps.ExprTools]]
|
||||
git-tree-sha1 = "27415f162e6028e81c72b82ef756bf321213b6ec"
|
||||
uuid = "e2ba6199-217a-4e67-a87a-7c52f15ade04"
|
||||
version = "0.1.10"
|
||||
|
||||
[[deps.FileIO]]
|
||||
deps = ["Pkg", "Requires", "UUIDs"]
|
||||
git-tree-sha1 = "82d8afa92ecf4b52d78d869f038ebfb881267322"
|
||||
uuid = "5789e2e9-d7fb-5bc7-8068-2c6fae9b9549"
|
||||
version = "1.16.3"
|
||||
|
||||
[[deps.FilePathsBase]]
|
||||
deps = ["Compat", "Dates", "Mmap", "Printf", "Test", "UUIDs"]
|
||||
git-tree-sha1 = "9f00e42f8d99fdde64d40c8ea5d14269a2e2c1aa"
|
||||
uuid = "48062228-2e41-5def-b9a4-89aafe57970f"
|
||||
version = "0.9.21"
|
||||
|
||||
[[deps.FileWatching]]
|
||||
uuid = "7b1f6079-737a-58dc-b8bc-7a2ca5c1b5ee"
|
||||
|
||||
@@ -148,8 +209,18 @@ weakdeps = ["PDMats", "SparseArrays", "Statistics"]
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||||
FillArraysSparseArraysExt = "SparseArrays"
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||||
FillArraysStatisticsExt = "Statistics"
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||||
|
||||
[[deps.FormatCorrector]]
|
||||
deps = ["CSV", "CondaPkg", "DataFrames", "DataStructures", "Dates", "DispatchDoctor", "FileIO", "GeneralUtils", "HTTP", "JSON3", "LLMMCTS", "LibPQ", "MQTTClient", "PrettyPrinting", "PythonCall", "Random", "Revise", "URIs", "UUIDs"]
|
||||
path = "../FormatCorrector"
|
||||
uuid = "4aa99331-0491-47cc-864d-b8dfff346b60"
|
||||
version = "0.1.0"
|
||||
|
||||
[[deps.Future]]
|
||||
deps = ["Random"]
|
||||
uuid = "9fa8497b-333b-5362-9e8d-4d0656e87820"
|
||||
|
||||
[[deps.GeneralUtils]]
|
||||
deps = ["DataStructures", "Dates", "Distributions", "JSON3", "MQTTClient", "Random", "Revise", "UUIDs"]
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||||
deps = ["CSV", "DataFrames", "DataStructures", "Dates", "Distributions", "JSON3", "MQTTClient", "Random", "Revise", "UUIDs"]
|
||||
path = "/appfolder/app/privatejuliapkg/GeneralUtils"
|
||||
uuid = "c6c72f09-b708-4ac8-ac7c-2084d70108fe"
|
||||
version = "0.1.0"
|
||||
@@ -166,15 +237,50 @@ git-tree-sha1 = "f218fe3736ddf977e0e772bc9a586b2383da2685"
|
||||
uuid = "34004b35-14d8-5ef3-9330-4cdb6864b03a"
|
||||
version = "0.3.23"
|
||||
|
||||
[[deps.Infinity]]
|
||||
deps = ["Dates", "Random", "Requires"]
|
||||
git-tree-sha1 = "cf8234411cbeb98676c173f930951ea29dca3b23"
|
||||
uuid = "a303e19e-6eb4-11e9-3b09-cd9505f79100"
|
||||
version = "0.2.4"
|
||||
|
||||
[[deps.InlineStrings]]
|
||||
git-tree-sha1 = "45521d31238e87ee9f9732561bfee12d4eebd52d"
|
||||
uuid = "842dd82b-1e85-43dc-bf29-5d0ee9dffc48"
|
||||
version = "1.4.2"
|
||||
|
||||
[deps.InlineStrings.extensions]
|
||||
ArrowTypesExt = "ArrowTypes"
|
||||
ParsersExt = "Parsers"
|
||||
|
||||
[deps.InlineStrings.weakdeps]
|
||||
ArrowTypes = "31f734f8-188a-4ce0-8406-c8a06bd891cd"
|
||||
Parsers = "69de0a69-1ddd-5017-9359-2bf0b02dc9f0"
|
||||
|
||||
[[deps.InteractiveUtils]]
|
||||
deps = ["Markdown"]
|
||||
uuid = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
|
||||
|
||||
[[deps.Intervals]]
|
||||
deps = ["Dates", "Printf", "RecipesBase", "Serialization", "TimeZones"]
|
||||
git-tree-sha1 = "ac0aaa807ed5eaf13f67afe188ebc07e828ff640"
|
||||
uuid = "d8418881-c3e1-53bb-8760-2df7ec849ed5"
|
||||
version = "1.10.0"
|
||||
|
||||
[[deps.InvertedIndices]]
|
||||
git-tree-sha1 = "0dc7b50b8d436461be01300fd8cd45aa0274b038"
|
||||
uuid = "41ab1584-1d38-5bbf-9106-f11c6c58b48f"
|
||||
version = "1.3.0"
|
||||
|
||||
[[deps.IrrationalConstants]]
|
||||
git-tree-sha1 = "630b497eafcc20001bba38a4651b327dcfc491d2"
|
||||
uuid = "92d709cd-6900-40b7-9082-c6be49f344b6"
|
||||
version = "0.2.2"
|
||||
|
||||
[[deps.IterTools]]
|
||||
git-tree-sha1 = "42d5f897009e7ff2cf88db414a389e5ed1bdd023"
|
||||
uuid = "c8e1da08-722c-5040-9ed9-7db0dc04731e"
|
||||
version = "1.10.0"
|
||||
|
||||
[[deps.IteratorInterfaceExtensions]]
|
||||
git-tree-sha1 = "a3f24677c21f5bbe9d2a714f95dcd58337fb2856"
|
||||
uuid = "82899510-4779-5014-852e-03e436cf321d"
|
||||
@@ -200,16 +306,32 @@ version = "1.14.0"
|
||||
|
||||
[[deps.JuliaInterpreter]]
|
||||
deps = ["CodeTracking", "InteractiveUtils", "Random", "UUIDs"]
|
||||
git-tree-sha1 = "e9648d90370e2d0317f9518c9c6e0841db54a90b"
|
||||
git-tree-sha1 = "a6adc2dcfe4187c40dc7c2c9d2128e326360e90a"
|
||||
uuid = "aa1ae85d-cabe-5617-a682-6adf51b2e16a"
|
||||
version = "0.9.31"
|
||||
version = "0.9.32"
|
||||
|
||||
[[deps.Kerberos_krb5_jll]]
|
||||
deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
|
||||
git-tree-sha1 = "60274b4ab38e8d1248216fe6b6ace75ae09b0502"
|
||||
uuid = "b39eb1a6-c29a-53d7-8c32-632cd16f18da"
|
||||
version = "1.19.3+0"
|
||||
|
||||
[[deps.LLMMCTS]]
|
||||
deps = ["JSON3"]
|
||||
deps = ["GeneralUtils", "JSON3"]
|
||||
path = "/appfolder/app/privatejuliapkg/LLMMCTS"
|
||||
uuid = "d76c5a4d-449e-4835-8cc4-dd86ec44f241"
|
||||
version = "0.1.0"
|
||||
|
||||
[[deps.LaTeXStrings]]
|
||||
git-tree-sha1 = "50901ebc375ed41dbf8058da26f9de442febbbec"
|
||||
uuid = "b964fa9f-0449-5b57-a5c2-d3ea65f4040f"
|
||||
version = "1.3.1"
|
||||
|
||||
[[deps.LayerDicts]]
|
||||
git-tree-sha1 = "6087ad3521d6278ebe5c27ae55e7bbb15ca312cb"
|
||||
uuid = "6f188dcb-512c-564b-bc01-e0f76e72f166"
|
||||
version = "1.0.0"
|
||||
|
||||
[[deps.LazyArtifacts]]
|
||||
deps = ["Artifacts", "Pkg"]
|
||||
uuid = "4af54fe1-eca0-43a8-85a7-787d91b784e3"
|
||||
@@ -233,6 +355,18 @@ deps = ["Artifacts", "LibSSH2_jll", "Libdl", "MbedTLS_jll"]
|
||||
uuid = "e37daf67-58a4-590a-8e99-b0245dd2ffc5"
|
||||
version = "1.6.4+0"
|
||||
|
||||
[[deps.LibPQ]]
|
||||
deps = ["CEnum", "DBInterface", "Dates", "Decimals", "DocStringExtensions", "FileWatching", "Infinity", "Intervals", "IterTools", "LayerDicts", "LibPQ_jll", "Libdl", "Memento", "OffsetArrays", "SQLStrings", "Tables", "TimeZones", "UTCDateTimes"]
|
||||
git-tree-sha1 = "74feb1a63ebbcdcf1730016d2a4dfad0a655404f"
|
||||
uuid = "194296ae-ab2e-5f79-8cd4-7183a0a5a0d1"
|
||||
version = "1.17.1"
|
||||
|
||||
[[deps.LibPQ_jll]]
|
||||
deps = ["Artifacts", "JLLWrappers", "Kerberos_krb5_jll", "Libdl", "OpenSSL_jll", "Pkg"]
|
||||
git-tree-sha1 = "a299629703a93d8efcefccfc16b18ad9a073d131"
|
||||
uuid = "08be9ffa-1c94-5ee5-a977-46a84ec9b350"
|
||||
version = "14.3.0+1"
|
||||
|
||||
[[deps.LibSSH2_jll]]
|
||||
deps = ["Artifacts", "Libdl", "MbedTLS_jll"]
|
||||
uuid = "29816b5a-b9ab-546f-933c-edad1886dfa8"
|
||||
@@ -247,9 +381,9 @@ uuid = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
|
||||
|
||||
[[deps.LogExpFunctions]]
|
||||
deps = ["DocStringExtensions", "IrrationalConstants", "LinearAlgebra"]
|
||||
git-tree-sha1 = "18144f3e9cbe9b15b070288eef858f71b291ce37"
|
||||
git-tree-sha1 = "a2d09619db4e765091ee5c6ffe8872849de0feea"
|
||||
uuid = "2ab3a3ac-af41-5b50-aa03-7779005ae688"
|
||||
version = "0.3.27"
|
||||
version = "0.3.28"
|
||||
|
||||
[deps.LogExpFunctions.extensions]
|
||||
LogExpFunctionsChainRulesCoreExt = "ChainRulesCore"
|
||||
@@ -272,9 +406,9 @@ version = "1.0.3"
|
||||
|
||||
[[deps.LoweredCodeUtils]]
|
||||
deps = ["JuliaInterpreter"]
|
||||
git-tree-sha1 = "c6a36b22d2cca0e1a903f00f600991f97bf5f426"
|
||||
git-tree-sha1 = "eeaedcf337f33c039f9f3a209a8db992deefd7e9"
|
||||
uuid = "6f1432cf-f94c-5a45-995e-cdbf5db27b0b"
|
||||
version = "2.4.6"
|
||||
version = "2.4.8"
|
||||
|
||||
[[deps.MQTTClient]]
|
||||
deps = ["Distributed", "Random", "Sockets"]
|
||||
@@ -307,6 +441,12 @@ deps = ["Artifacts", "Libdl"]
|
||||
uuid = "c8ffd9c3-330d-5841-b78e-0817d7145fa1"
|
||||
version = "2.28.2+1"
|
||||
|
||||
[[deps.Memento]]
|
||||
deps = ["Dates", "Distributed", "Requires", "Serialization", "Sockets", "Test", "UUIDs"]
|
||||
git-tree-sha1 = "bb2e8f4d9f400f6e90d57b34860f6abdc51398e5"
|
||||
uuid = "f28f55f0-a522-5efc-85c2-fe41dfb9b2d9"
|
||||
version = "1.4.1"
|
||||
|
||||
[[deps.MicroMamba]]
|
||||
deps = ["Pkg", "Scratch", "micromamba_jll"]
|
||||
git-tree-sha1 = "011cab361eae7bcd7d278f0a7a00ff9c69000c51"
|
||||
@@ -322,6 +462,12 @@ version = "1.2.0"
|
||||
[[deps.Mmap]]
|
||||
uuid = "a63ad114-7e13-5084-954f-fe012c677804"
|
||||
|
||||
[[deps.Mocking]]
|
||||
deps = ["Compat", "ExprTools"]
|
||||
git-tree-sha1 = "bf17d9cb4f0d2882351dfad030598f64286e5936"
|
||||
uuid = "78c3b35d-d492-501b-9361-3d52fe80e533"
|
||||
version = "0.7.8"
|
||||
|
||||
[[deps.MozillaCACerts_jll]]
|
||||
uuid = "14a3606d-f60d-562e-9121-12d972cd8159"
|
||||
version = "2023.1.10"
|
||||
@@ -336,6 +482,17 @@ version = "1.0.2"
|
||||
uuid = "ca575930-c2e3-43a9-ace4-1e988b2c1908"
|
||||
version = "1.2.0"
|
||||
|
||||
[[deps.OffsetArrays]]
|
||||
git-tree-sha1 = "1a27764e945a152f7ca7efa04de513d473e9542e"
|
||||
uuid = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
|
||||
version = "1.14.1"
|
||||
|
||||
[deps.OffsetArrays.extensions]
|
||||
OffsetArraysAdaptExt = "Adapt"
|
||||
|
||||
[deps.OffsetArrays.weakdeps]
|
||||
Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
|
||||
|
||||
[[deps.OpenBLAS_jll]]
|
||||
deps = ["Artifacts", "CompilerSupportLibraries_jll", "Libdl"]
|
||||
uuid = "4536629a-c528-5b80-bd46-f80d51c5b363"
|
||||
@@ -354,9 +511,9 @@ version = "1.4.3"
|
||||
|
||||
[[deps.OpenSSL_jll]]
|
||||
deps = ["Artifacts", "JLLWrappers", "Libdl"]
|
||||
git-tree-sha1 = "3da7367955dcc5c54c1ba4d402ccdc09a1a3e046"
|
||||
git-tree-sha1 = "a12e56c72edee3ce6b96667745e6cbbe5498f200"
|
||||
uuid = "458c3c95-2e84-50aa-8efc-19380b2a3a95"
|
||||
version = "3.0.13+1"
|
||||
version = "1.1.23+0"
|
||||
|
||||
[[deps.OpenSpecFun_jll]]
|
||||
deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl", "Pkg"]
|
||||
@@ -392,6 +549,12 @@ deps = ["Artifacts", "Dates", "Downloads", "FileWatching", "LibGit2", "Libdl", "
|
||||
uuid = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
|
||||
version = "1.10.0"
|
||||
|
||||
[[deps.PooledArrays]]
|
||||
deps = ["DataAPI", "Future"]
|
||||
git-tree-sha1 = "36d8b4b899628fb92c2749eb488d884a926614d3"
|
||||
uuid = "2dfb63ee-cc39-5dd5-95bd-886bf059d720"
|
||||
version = "1.4.3"
|
||||
|
||||
[[deps.PrecompileTools]]
|
||||
deps = ["Preferences"]
|
||||
git-tree-sha1 = "5aa36f7049a63a1528fe8f7c3f2113413ffd4e1f"
|
||||
@@ -409,6 +572,12 @@ git-tree-sha1 = "142ee93724a9c5d04d78df7006670a93ed1b244e"
|
||||
uuid = "54e16d92-306c-5ea0-a30b-337be88ac337"
|
||||
version = "0.4.2"
|
||||
|
||||
[[deps.PrettyTables]]
|
||||
deps = ["Crayons", "LaTeXStrings", "Markdown", "PrecompileTools", "Printf", "Reexport", "StringManipulation", "Tables"]
|
||||
git-tree-sha1 = "66b20dd35966a748321d3b2537c4584cf40387c7"
|
||||
uuid = "08abe8d2-0d0c-5749-adfa-8a2ac140af0d"
|
||||
version = "2.3.2"
|
||||
|
||||
[[deps.Printf]]
|
||||
deps = ["Unicode"]
|
||||
uuid = "de0858da-6303-5e67-8744-51eddeeeb8d7"
|
||||
@@ -438,6 +607,12 @@ uuid = "3fa0cd96-eef1-5676-8a61-b3b8758bbffb"
|
||||
deps = ["SHA"]
|
||||
uuid = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
|
||||
|
||||
[[deps.RecipesBase]]
|
||||
deps = ["PrecompileTools"]
|
||||
git-tree-sha1 = "5c3d09cc4f31f5fc6af001c250bf1278733100ff"
|
||||
uuid = "3cdcf5f2-1ef4-517c-9805-6587b60abb01"
|
||||
version = "1.3.4"
|
||||
|
||||
[[deps.Reexport]]
|
||||
git-tree-sha1 = "45e428421666073eab6f2da5c9d310d99bb12f9b"
|
||||
uuid = "189a3867-3050-52da-a836-e630ba90ab69"
|
||||
@@ -451,9 +626,9 @@ version = "1.3.0"
|
||||
|
||||
[[deps.Revise]]
|
||||
deps = ["CodeTracking", "Distributed", "FileWatching", "JuliaInterpreter", "LibGit2", "LoweredCodeUtils", "OrderedCollections", "Pkg", "REPL", "Requires", "UUIDs", "Unicode"]
|
||||
git-tree-sha1 = "12aa2d7593df490c407a3bbd8b86b8b515017f3e"
|
||||
git-tree-sha1 = "85ddd93ea15dcd8493400600e09104a9e94bb18d"
|
||||
uuid = "295af30f-e4ad-537b-8983-00126c2a3abe"
|
||||
version = "3.5.14"
|
||||
version = "3.5.15"
|
||||
|
||||
[[deps.Rmath]]
|
||||
deps = ["Random", "Rmath_jll"]
|
||||
@@ -471,12 +646,29 @@ version = "0.4.2+0"
|
||||
uuid = "ea8e919c-243c-51af-8825-aaa63cd721ce"
|
||||
version = "0.7.0"
|
||||
|
||||
[[deps.SQLLLM]]
|
||||
deps = ["CSV", "CondaPkg", "DataFrames", "DataStructures", "Dates", "DispatchDoctor", "FileIO", "FormatCorrector", "GeneralUtils", "HTTP", "JSON3", "LLMMCTS", "LibPQ", "MQTTClient", "PrettyPrinting", "PythonCall", "Random", "Revise", "Tables", "URIs", "UUIDs"]
|
||||
path = "/appfolder/app/privatejuliapkg/SQLLLM"
|
||||
uuid = "2ebc79c7-cc10-4a3a-9665-d2e1d61e63d3"
|
||||
version = "0.1.0"
|
||||
|
||||
[[deps.SQLStrings]]
|
||||
git-tree-sha1 = "55de0530689832b1d3d43491ee6b67bd54d3323c"
|
||||
uuid = "af517c2e-c243-48fa-aab8-efac3db270f5"
|
||||
version = "0.1.0"
|
||||
|
||||
[[deps.Scratch]]
|
||||
deps = ["Dates"]
|
||||
git-tree-sha1 = "3bac05bc7e74a75fd9cba4295cde4045d9fe2386"
|
||||
uuid = "6c6a2e73-6563-6170-7368-637461726353"
|
||||
version = "1.2.1"
|
||||
|
||||
[[deps.SentinelArrays]]
|
||||
deps = ["Dates", "Random"]
|
||||
git-tree-sha1 = "ff11acffdb082493657550959d4feb4b6149e73a"
|
||||
uuid = "91c51154-3ec4-41a3-a24f-3f23e20d615c"
|
||||
version = "1.4.5"
|
||||
|
||||
[[deps.Serialization]]
|
||||
uuid = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
|
||||
|
||||
@@ -542,6 +734,12 @@ version = "1.3.1"
|
||||
ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
|
||||
InverseFunctions = "3587e190-3f89-42d0-90ee-14403ec27112"
|
||||
|
||||
[[deps.StringManipulation]]
|
||||
deps = ["PrecompileTools"]
|
||||
git-tree-sha1 = "a04cabe79c5f01f4d723cc6704070ada0b9d46d5"
|
||||
uuid = "892a3eda-7b42-436c-8928-eab12a02cf0e"
|
||||
version = "0.3.4"
|
||||
|
||||
[[deps.StructTypes]]
|
||||
deps = ["Dates", "UUIDs"]
|
||||
git-tree-sha1 = "ca4bccb03acf9faaf4137a9abc1881ed1841aa70"
|
||||
@@ -562,6 +760,12 @@ deps = ["Dates"]
|
||||
uuid = "fa267f1f-6049-4f14-aa54-33bafae1ed76"
|
||||
version = "1.0.3"
|
||||
|
||||
[[deps.TZJData]]
|
||||
deps = ["Artifacts"]
|
||||
git-tree-sha1 = "1607ad46cf8d642aa779a1d45af1c8620dbf6915"
|
||||
uuid = "dc5dba14-91b3-4cab-a142-028a31da12f7"
|
||||
version = "1.2.0+2024a"
|
||||
|
||||
[[deps.TableTraits]]
|
||||
deps = ["IteratorInterfaceExtensions"]
|
||||
git-tree-sha1 = "c06b2f539df1c6efa794486abfb6ed2022561a39"
|
||||
@@ -583,10 +787,20 @@ version = "1.10.0"
|
||||
deps = ["InteractiveUtils", "Logging", "Random", "Serialization"]
|
||||
uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
|
||||
|
||||
[[deps.TimeZones]]
|
||||
deps = ["Dates", "Downloads", "InlineStrings", "Mocking", "Printf", "Scratch", "TZJData", "Unicode", "p7zip_jll"]
|
||||
git-tree-sha1 = "a6ae8d7a27940c33624f8c7bde5528de21ba730d"
|
||||
uuid = "f269a46b-ccf7-5d73-abea-4c690281aa53"
|
||||
version = "1.17.0"
|
||||
weakdeps = ["RecipesBase"]
|
||||
|
||||
[deps.TimeZones.extensions]
|
||||
TimeZonesRecipesBaseExt = "RecipesBase"
|
||||
|
||||
[[deps.TranscodingStreams]]
|
||||
git-tree-sha1 = "5d54d076465da49d6746c647022f3b3674e64156"
|
||||
git-tree-sha1 = "60df3f8126263c0d6b357b9a1017bb94f53e3582"
|
||||
uuid = "3bb67fe8-82b1-5028-8e26-92a6c54297fa"
|
||||
version = "0.10.8"
|
||||
version = "0.11.0"
|
||||
weakdeps = ["Random", "Test"]
|
||||
|
||||
[deps.TranscodingStreams.extensions]
|
||||
@@ -597,6 +811,12 @@ git-tree-sha1 = "67db6cc7b3821e19ebe75791a9dd19c9b1188f2b"
|
||||
uuid = "5c2747f8-b7ea-4ff2-ba2e-563bfd36b1d4"
|
||||
version = "1.5.1"
|
||||
|
||||
[[deps.UTCDateTimes]]
|
||||
deps = ["Dates", "TimeZones"]
|
||||
git-tree-sha1 = "4af3552bf0cf4a071bf3d14bd20023ea70f31b62"
|
||||
uuid = "0f7cfa37-7abf-4834-b969-a8aa512401c2"
|
||||
version = "1.6.1"
|
||||
|
||||
[[deps.UUIDs]]
|
||||
deps = ["Random", "SHA"]
|
||||
uuid = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
|
||||
@@ -609,6 +829,17 @@ git-tree-sha1 = "c81331b3b2e60a982be57c046ec91f599ede674a"
|
||||
uuid = "e17b2a0c-0bdf-430a-bd0c-3a23cae4ff39"
|
||||
version = "1.0.0"
|
||||
|
||||
[[deps.WeakRefStrings]]
|
||||
deps = ["DataAPI", "InlineStrings", "Parsers"]
|
||||
git-tree-sha1 = "b1be2855ed9ed8eac54e5caff2afcdb442d52c23"
|
||||
uuid = "ea10d353-3f73-51f8-a26c-33c1cb351aa5"
|
||||
version = "1.4.2"
|
||||
|
||||
[[deps.WorkerUtilities]]
|
||||
git-tree-sha1 = "cd1659ba0d57b71a464a29e64dbc67cfe83d54e7"
|
||||
uuid = "76eceee3-57b5-4d4a-8e66-0e911cebbf60"
|
||||
version = "1.6.1"
|
||||
|
||||
[[deps.Zlib_jll]]
|
||||
deps = ["Libdl"]
|
||||
uuid = "83775a58-1f1d-513f-b197-d71354ab007a"
|
||||
|
||||
@@ -15,5 +15,7 @@ MQTTClient = "985f35cc-2c3d-4943-b8c1-f0931d5f0959"
|
||||
PrettyPrinting = "54e16d92-306c-5ea0-a30b-337be88ac337"
|
||||
PythonCall = "6099a3de-0909-46bc-b1f4-468b9a2dfc0d"
|
||||
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
|
||||
Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"
|
||||
SQLLLM = "2ebc79c7-cc10-4a3a-9665-d2e1d61e63d3"
|
||||
URIs = "5c2747f8-b7ea-4ff2-ba2e-563bfd36b1d4"
|
||||
UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
|
||||
|
||||
1196
src/interface BACKUP.jl
Normal file
1196
src/interface BACKUP.jl
Normal file
File diff suppressed because it is too large
Load Diff
893
src/interface.jl
893
src/interface.jl
@@ -39,8 +39,8 @@ macro executeStringFunction(functionStr, args...)
|
||||
func_expr = Meta.parse(functionStr)
|
||||
|
||||
# Create a new function with the parsed expression
|
||||
function_to_call = eval(Expr(:function, Expr(:call, func_expr, args...),
|
||||
func_expr.args[2:end]...))
|
||||
function_to_call = eval(Expr(:function,
|
||||
Expr(:call, func_expr, args...), func_expr.args[2:end]...))
|
||||
|
||||
# Call the newly created function with the provided arguments
|
||||
function_to_call(args...)
|
||||
@@ -97,169 +97,328 @@ julia> output_thoughtDict = Dict(
|
||||
|
||||
# Signature
|
||||
"""
|
||||
function decisionMaker(config::T1, state::T2)::Dict{Symbol, Any} where {T1<:AbstractDict, T2<:AbstractDict}
|
||||
customerinfo =
|
||||
"""
|
||||
I will give you the following information about customer:
|
||||
$(JSON3.write(state[:customerinfo]))
|
||||
"""
|
||||
function decisionMaker(a::T)::Dict{Symbol, Any} where {T<:agent}
|
||||
|
||||
storeinfo =
|
||||
"""
|
||||
I will give you the following information about your store:
|
||||
$(JSON3.write(state[:storeinfo]))
|
||||
"""
|
||||
# lessonDict = copy(JSON3.read("lesson.json"))
|
||||
|
||||
lessonDict = copy(JSON3.read("lesson.json"))
|
||||
# lesson =
|
||||
# if isempty(lessonDict)
|
||||
# ""
|
||||
# else
|
||||
# lessons = Dict{Symbol, Any}()
|
||||
# for (k, v) in lessonDict
|
||||
# lessons[k] = lessonDict[k][:lesson]
|
||||
# end
|
||||
|
||||
lesson =
|
||||
if isempty(lessonDict)
|
||||
""
|
||||
else
|
||||
lessons = Dict{Symbol, Any}()
|
||||
for (k, v) in lessonDict
|
||||
lessons[k] = lessonDict[k][:lesson]
|
||||
end
|
||||
# """
|
||||
# You have attempted to help the user before and failed, either because your reasoning for the
|
||||
# recommendation was incorrect or your response did not exactly match the user expectation.
|
||||
# The following lesson(s) give a plan to avoid failing to help the user in the same way you
|
||||
# did previously. Use them to improve your strategy to help the user.
|
||||
|
||||
"""
|
||||
You have attempted to help the user before and failed, either because your reasoning for the
|
||||
recommendation was incorrect or your response did not exactly match the user expectation.
|
||||
The following lesson(s) give a plan to avoid failing to help the user in the same way you
|
||||
did previously. Use them to improve your strategy to help the user.
|
||||
# Here are some lessons in JSON format:
|
||||
# $(JSON3.write(lessons))
|
||||
|
||||
Here are some lessons in JSON format:
|
||||
$(JSON3.write(lessons))
|
||||
# When providing the thought and action for the current trial, that into account these failed
|
||||
# trajectories and make sure not to repeat the same mistakes and incorrect answers.
|
||||
# """
|
||||
# end
|
||||
|
||||
When providing the thought and action for the current trial, that into account these failed
|
||||
trajectories and make sure not to repeat the same mistakes and incorrect answers.
|
||||
"""
|
||||
end
|
||||
# _prompt =
|
||||
# """
|
||||
# You are a helpful sommelier working for a wine store.
|
||||
# Your goal is to recommend the best wine from your inventory that match the user preferences.
|
||||
# You are also keen to improve your recommendation with lesson(s).
|
||||
|
||||
_prompt =
|
||||
# You must follow the following criteria:
|
||||
# 1) Get to know how much the user willing to spend
|
||||
# 2) Get to know type of wine the user is looking for e.g. red, white, sparkling, rose, dessert, fortified
|
||||
# 3) Get to know what occasion the user is buying wine for
|
||||
# 4) Get to know what characteristics of wine the user is looking for
|
||||
# e.g. tannin, sweetness, intensity, acidity
|
||||
# 5) Get to know what food the user will have with wine
|
||||
# 6) Check your inventory for the best wine that match the user preference
|
||||
# 7) Recommend wine to the user
|
||||
|
||||
# You should only respond with interleaving Thought, Action, Observation steps.
|
||||
# Thought can reason about the current situation, and Action can be three types:
|
||||
# 1) winestock[query], which you can use to find wine in your inventory. The more input data the better.
|
||||
# 2) chatbox[text], which you can use to interact with the user.
|
||||
# After each observation, provide the next Thought and next Action.
|
||||
|
||||
# You should only respond in JSON format as describe below:
|
||||
# {
|
||||
# "thought": "your reasoning",
|
||||
# "action": {"name": "action to take", "input": "action input"},
|
||||
# "observation": "result of the action"
|
||||
# }
|
||||
|
||||
# Here are some examples:
|
||||
# {
|
||||
# "question": "I would like to buy a sedan with 8 seats.",
|
||||
# "thought_1": "Our showroom carries various vehicle model. But I'm not sure whether we have a models that fits the user demand, I need to check our inventory.",
|
||||
# "action_1": {"name": "inventory", "input": "sedan with 8 seats."},
|
||||
# "observation_1": "Several model has 8 seats. Available color are black, red green"
|
||||
# }
|
||||
# {
|
||||
# "thought": "I have a few color for the user to choose from. I will ask him what color he likes.",
|
||||
# "action": {"name": "chatbox", "input": "Which color do you like?"}
|
||||
# "observation": "I'll take black."
|
||||
# }
|
||||
|
||||
# $lesson
|
||||
|
||||
# Let's begin!
|
||||
|
||||
# $(JSON3.write(state[:thoughtHistory]))
|
||||
# {"thought"
|
||||
# """
|
||||
|
||||
systemmsg =
|
||||
"""
|
||||
You are a helpful sommelier working for a wine store.
|
||||
Your goal is to recommend the best wine from your inventory that match the user preferences.
|
||||
You are also keen to improve your recommendation with lesson(s).
|
||||
Your task is to help the user choose the best wine that match the user preferences from your inventory.
|
||||
You are also eager to improve your helpfulness.
|
||||
|
||||
You must follow the following criteria:
|
||||
1) Get to know how much the user willing to spend
|
||||
2) Get to know type of wine the user is looking for e.g. red, white, sparkling, rose, dessert, fortified
|
||||
3) Get to know what occasion the user is buying wine for
|
||||
4) Get to know what characteristics of wine the user is looking for
|
||||
e.g. tannin, sweetness, intensity, acidity
|
||||
5) Get to know what food the user will have with wine
|
||||
6) Check your inventory for the best wine that match the user preference
|
||||
7) Recommend wine to the user
|
||||
You must follow the following guidelines:
|
||||
- Get to know how much the user willing to spend
|
||||
- Get to know type of wine the user is looking for e.g. red, white, sparkling, rose, dessert, fortified
|
||||
- Get to know what occasion the user is buying wine for
|
||||
- Get to know what characteristics of wine the user is looking for e.g. tannin, sweetness, intensity, acidity
|
||||
- Get to know what food the user will have with wine
|
||||
|
||||
You should only respond with interleaving Thought, Action, Observation steps.
|
||||
Thought can reason about the current situation, and Action can be three types:
|
||||
1) winestock[query], which you can use to find wine in your inventory. The more input data the better.
|
||||
2) chatbox[text], which you can use to interact with the user.
|
||||
3) recommendbox[answer], which returns your wine recommendation to the user.
|
||||
After each observation, provide the next Thought and next Action.
|
||||
At each round of conversation, the user will give you the current situation:
|
||||
Context: ...
|
||||
Your earlier conversation with the user: ...
|
||||
|
||||
You should only respond in JSON format as describe below:
|
||||
{
|
||||
"thought": "your reasoning",
|
||||
"action": {"name": "action to take", "input": "action input"},
|
||||
"observation": "result of the action"
|
||||
}
|
||||
You should then respond to the user with interleaving Thought, Plan, Action and Observation:
|
||||
- thought:
|
||||
1) State your reasoning about the current situation.
|
||||
- plan: Based on the current situation, what would you do to complete the task? Be specific.
|
||||
- action (Must be aligned with your plan): Can be one of the following functions:
|
||||
1) CHATBOX[text], which you can use to talk with the user. "text" is in verbal English.
|
||||
2) WINESTOCK[query], which you can use to find info about wine in your inventory. "query" is a search term in verbal English.
|
||||
- observation: result of the action.
|
||||
|
||||
Here are some examples:
|
||||
{
|
||||
"question": "I would like to buy a sedan with 8 seats.",
|
||||
"thought_1": "Our showroom carries various vehicle model. But I'm not sure whether we have a models that fits the user demand, I need to check our inventory.",
|
||||
"action_1": {"name": "inventory", "input": "sedan with 8 seats."},
|
||||
"observation_1": "Several model has 8 seats. Available color are black, red green"
|
||||
}
|
||||
{
|
||||
"thought": "I have a few color for the user to choose from. I will ask him what color he likes.",
|
||||
"action": {"name": "chatbox", "input": "Which color do you like?"}
|
||||
"observation": "I'll take black."
|
||||
}
|
||||
|
||||
$lesson
|
||||
You should only respond in format as described below:
|
||||
thought: ...
|
||||
plan: ...
|
||||
action_name: ...
|
||||
action_input: ...
|
||||
observation: ...
|
||||
|
||||
Let's begin!
|
||||
|
||||
$(JSON3.write(state[:thoughtHistory]))
|
||||
{"thought"
|
||||
"""
|
||||
|
||||
# apply LLM specific instruct format
|
||||
externalService = config[:externalservice][:text2textinstruct]
|
||||
llminfo = externalService[:llminfo]
|
||||
prompt =
|
||||
if llminfo[:name] == "llama3instruct"
|
||||
formatLLMtext_llama3instruct("system", _prompt)
|
||||
else
|
||||
error("llm model name is not defied yet $(@__LINE__)")
|
||||
end
|
||||
usermsg =
|
||||
"""
|
||||
Context: None
|
||||
Your earlier conversation with the user: $(chatHistoryToString(a))
|
||||
"""
|
||||
|
||||
msgMeta = GeneralUtils.generate_msgMeta(
|
||||
externalService[:mqtttopic],
|
||||
senderName= "decisionMaker",
|
||||
senderId= string(uuid4()),
|
||||
receiverName= "text2textinstruct",
|
||||
mqttBroker= config[:mqttServerInfo][:broker],
|
||||
mqttBrokerPort= config[:mqttServerInfo][:port],
|
||||
)
|
||||
_prompt =
|
||||
[
|
||||
Dict(:name=> "system", :text=> systemmsg),
|
||||
Dict(:name=> "user", :text=> usermsg)
|
||||
]
|
||||
|
||||
outgoingMsg = Dict(
|
||||
:msgMeta=> msgMeta,
|
||||
:payload=> Dict(
|
||||
:text=> prompt,
|
||||
:kwargs=> Dict(
|
||||
:max_tokens=> 512,
|
||||
:stop=> ["<|eot_id|>"],
|
||||
)
|
||||
)
|
||||
)
|
||||
@show outgoingMsg
|
||||
|
||||
for attempt in 1:5
|
||||
# put in model format
|
||||
prompt = GeneralUtils.formatLLMtext(_prompt, "llama3instruct")
|
||||
prompt *=
|
||||
"""
|
||||
<|start_header_id|>assistant<|end_header_id|>
|
||||
"""
|
||||
response = nothing # store for show when error msg show up
|
||||
for attempt in 1:10
|
||||
try
|
||||
response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg)
|
||||
_responseJsonStr = response[:response][:text]
|
||||
expectedJsonExample =
|
||||
"""
|
||||
Here is an expected JSON format:
|
||||
{
|
||||
"thought": "...",
|
||||
"action": {"name": "...", "input": "..."},
|
||||
"observation": "..."
|
||||
}
|
||||
"""
|
||||
responseJsonStr = jsoncorrection(config, _responseJsonStr, expectedJsonExample)
|
||||
thoughtDict = copy(JSON3.read(responseJsonStr))
|
||||
response = a.text2textInstructLLM(prompt)
|
||||
responsedict = GeneralUtils.textToDict(response,
|
||||
["thought", "plan", "action_name", "action_input", "observation"],
|
||||
rightmarker=":", symbolkey=true)
|
||||
|
||||
# check if dict has all required value
|
||||
thought::AbstractString = thoughtDict[:thought]
|
||||
actionname::AbstractString = thoughtDict[:action][:name]
|
||||
actioninput::AbstractString = thoughtDict[:action][:input]
|
||||
if actionname ∈ ["winestock", "chatbox", "recommendbox"]
|
||||
# LLM use available function
|
||||
elseif thought == ""
|
||||
error("DecisionMaker has no thought")
|
||||
elseif length(actioninput) == 0
|
||||
error("DecisionMaker has no actioninput")
|
||||
else
|
||||
error("DecisionMaker use wrong function")
|
||||
if responsedict[:action_name] ∉ ["CHATBOX", "WINESTOCK"]
|
||||
error("decisionMaker didn't use the given functions ", @__LINE__)
|
||||
end
|
||||
|
||||
return thoughtDict
|
||||
for i ∈ [:thought, :plan, :action_name]
|
||||
if length(JSON3.write(responsedict[i])) == 0
|
||||
error("$i is empty ", @__LINE__)
|
||||
end
|
||||
end
|
||||
|
||||
# check if there are more than 1 key per categories
|
||||
for i ∈ [:thought, :plan, :action_name, :action_input, :observation]
|
||||
matchkeys = GeneralUtils.findMatchingDictKey(responsedict, i)
|
||||
if length(matchkeys) > 1
|
||||
error("DecisionMaker has more than one key per categories")
|
||||
end
|
||||
end
|
||||
println("--> 1")
|
||||
pprintln(responsedict)
|
||||
return responsedict
|
||||
catch e
|
||||
io = IOBuffer()
|
||||
showerror(io, e)
|
||||
errorMsg = String(take!(io))
|
||||
st = sprint((io, v) -> show(io, "text/plain", v), stacktrace(catch_backtrace()))
|
||||
println("")
|
||||
@warn "Attempt $attempt. Error occurred: $errorMsg\n$st"
|
||||
println("Attempt $attempt. Error occurred: $errorMsg\n$st")
|
||||
println("")
|
||||
end
|
||||
end
|
||||
error("DecisionMaker failed to generate a thought")
|
||||
error("DecisionMaker failed to generate a thought ", response)
|
||||
end
|
||||
# function decisionMaker(a::T)::Dict{Symbol, Any} where {T<:agent}
|
||||
|
||||
# # lessonDict = copy(JSON3.read("lesson.json"))
|
||||
|
||||
# # lesson =
|
||||
# # if isempty(lessonDict)
|
||||
# # ""
|
||||
# # else
|
||||
# # lessons = Dict{Symbol, Any}()
|
||||
# # for (k, v) in lessonDict
|
||||
# # lessons[k] = lessonDict[k][:lesson]
|
||||
# # end
|
||||
|
||||
# # """
|
||||
# # You have attempted to help the user before and failed, either because your reasoning for the
|
||||
# # recommendation was incorrect or your response did not exactly match the user expectation.
|
||||
# # The following lesson(s) give a plan to avoid failing to help the user in the same way you
|
||||
# # did previously. Use them to improve your strategy to help the user.
|
||||
|
||||
# # Here are some lessons in JSON format:
|
||||
# # $(JSON3.write(lessons))
|
||||
|
||||
# # When providing the thought and action for the current trial, that into account these failed
|
||||
# # trajectories and make sure not to repeat the same mistakes and incorrect answers.
|
||||
# # """
|
||||
# # end
|
||||
|
||||
# _prompt =
|
||||
# """
|
||||
# You are a helpful sommelier working for a wine store.
|
||||
# Your goal is to recommend the best wine from your inventory that match the user preferences.
|
||||
# You are also keen to improve your recommendation with lesson(s).
|
||||
|
||||
# You must follow the following criteria:
|
||||
# 1) Get to know how much the user willing to spend
|
||||
# 2) Get to know type of wine the user is looking for e.g. red, white, sparkling, rose, dessert, fortified
|
||||
# 3) Get to know what occasion the user is buying wine for
|
||||
# 4) Get to know what characteristics of wine the user is looking for
|
||||
# e.g. tannin, sweetness, intensity, acidity
|
||||
# 5) Get to know what food the user will have with wine
|
||||
# 6) Check your inventory for the best wine that match the user preference
|
||||
# 7) Recommend wine to the user
|
||||
|
||||
# You should only respond with interleaving Thought, Action, Observation steps.
|
||||
# Thought can reason about the current situation, and Action can be three types:
|
||||
# 1) winestock[query], which you can use to find wine in your inventory. The more input data the better.
|
||||
# 2) chatbox[text], which you can use to interact with the user.
|
||||
# After each observation, provide the next Thought and next Action.
|
||||
|
||||
# You should only respond in JSON format as describe below:
|
||||
# {
|
||||
# "thought": "your reasoning",
|
||||
# "action": {"name": "action to take", "input": "action input"},
|
||||
# "observation": "result of the action"
|
||||
# }
|
||||
|
||||
# Here are some examples:
|
||||
# {
|
||||
# "question": "I would like to buy a sedan with 8 seats.",
|
||||
# "thought_1": "Our showroom carries various vehicle model. But I'm not sure whether we have a models that fits the user demand, I need to check our inventory.",
|
||||
# "action_1": {"name": "inventory", "input": "sedan with 8 seats."},
|
||||
# "observation_1": "Several model has 8 seats. Available color are black, red green"
|
||||
# }
|
||||
# {
|
||||
# "thought": "I have a few color for the user to choose from. I will ask him what color he likes.",
|
||||
# "action": {"name": "chatbox", "input": "Which color do you like?"}
|
||||
# "observation": "I'll take black."
|
||||
# }
|
||||
|
||||
# $lesson
|
||||
|
||||
# Let's begin!
|
||||
|
||||
# $(JSON3.write(state[:thoughtHistory]))
|
||||
# {"thought"
|
||||
# """
|
||||
|
||||
# # apply LLM specific instruct format
|
||||
# externalService = config[:externalservice][:text2textinstruct]
|
||||
# llminfo = externalService[:llminfo]
|
||||
# prompt =
|
||||
# if llminfo[:name] == "llama3instruct"
|
||||
# formatLLMtext_llama3instruct("system", _prompt)
|
||||
# else
|
||||
# error("llm model name is not defied yet $(@__LINE__)")
|
||||
# end
|
||||
|
||||
# msgMeta = GeneralUtils.generate_msgMeta(
|
||||
# externalService[:mqtttopic],
|
||||
# senderName= "decisionMaker",
|
||||
# senderId= string(uuid4()),
|
||||
# receiverName= "text2textinstruct",
|
||||
# mqttBroker= config[:mqttServerInfo][:broker],
|
||||
# mqttBrokerPort= config[:mqttServerInfo][:port],
|
||||
# )
|
||||
|
||||
# outgoingMsg = Dict(
|
||||
# :msgMeta=> msgMeta,
|
||||
# :payload=> Dict(
|
||||
# :text=> prompt,
|
||||
# :kwargs=> Dict(
|
||||
# :max_tokens=> 512,
|
||||
# :stop=> ["<|eot_id|>"],
|
||||
# )
|
||||
# )
|
||||
# )
|
||||
# @show outgoingMsg
|
||||
|
||||
# for attempt in 1:5
|
||||
# try
|
||||
# response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg)
|
||||
# _responseJsonStr = response[:response][:text]
|
||||
# expectedJsonExample =
|
||||
# """
|
||||
# Here is an expected JSON format:
|
||||
# {
|
||||
# "thought": "...",
|
||||
# "action": {"name": "...", "input": "..."},
|
||||
# "observation": "..."
|
||||
# }
|
||||
# """
|
||||
# responseJsonStr = jsoncorrection(config, _responseJsonStr, expectedJsonExample)
|
||||
# thoughtDict = copy(JSON3.read(responseJsonStr))
|
||||
|
||||
# # check if dict has all required value
|
||||
# thought::AbstractString = thoughtDict[:thought]
|
||||
# actionname::AbstractString = thoughtDict[:action][:name]
|
||||
# actioninput::AbstractString = thoughtDict[:action][:input]
|
||||
# if actionname ∈ ["winestock", "chatbox", "recommendbox"]
|
||||
# # LLM use available function
|
||||
# elseif thought == ""
|
||||
# error("DecisionMaker has no thought")
|
||||
# elseif length(actioninput) == 0
|
||||
# error("DecisionMaker has no actioninput")
|
||||
# else
|
||||
# error("DecisionMaker use wrong function")
|
||||
# end
|
||||
|
||||
# return thoughtDict
|
||||
# catch e
|
||||
# io = IOBuffer()
|
||||
# showerror(io, e)
|
||||
# errorMsg = String(take!(io))
|
||||
# st = sprint((io, v) -> show(io, "text/plain", v), stacktrace(catch_backtrace()))
|
||||
# println("")
|
||||
# @warn "Attempt $attempt. Error occurred: $errorMsg\n$st"
|
||||
# println("")
|
||||
# end
|
||||
# end
|
||||
# error("DecisionMaker failed to generate a thought")
|
||||
# end
|
||||
|
||||
|
||||
""" Assigns a scalar value to each new child node to be used for selec-
|
||||
@@ -551,97 +710,132 @@ function reflector(config::T1, state::T2)::String where {T1<:AbstractDict, T2<:A
|
||||
end
|
||||
|
||||
|
||||
""" Get a new state
|
||||
|
||||
# Arguments
|
||||
- `a::T1`
|
||||
one of YiemAgent's agent
|
||||
- `state::T2`
|
||||
current game state
|
||||
- `thoughtDict::T3`
|
||||
contain Thought, Action, Observation
|
||||
- `isterminal::Function`
|
||||
a function to determine terminal state
|
||||
|
||||
# Return
|
||||
- `(newNodeKey, newstate, isterminalstate, reward)::Tuple{String, Dict{Symbol, <:Any}, Bool, <:Number}`
|
||||
|
||||
# Example
|
||||
```jldoctest
|
||||
julia> state = Dict{Symbol, Dict{Symbol, Any}}(
|
||||
:thoughtHistory => Dict(:question => "Hello, I want to buy a bottle of wine."),
|
||||
:storeinfo => Dict(),
|
||||
:customerinfo => Dict()
|
||||
)
|
||||
julia> thoughtDict = Dict(
|
||||
:question=> "I want to buy a bottle of wine.",
|
||||
:thought_1=> "The customer wants to buy a bottle of wine.",
|
||||
:action_1=> Dict{Symbol, Any}(
|
||||
:name=>"Chatbox",
|
||||
:input=>"What occasion are you buying the wine for?",
|
||||
),
|
||||
:observation_1 => ""
|
||||
)
|
||||
```
|
||||
# """ Chat with llm.
|
||||
|
||||
# TODO
|
||||
- [] add other actions
|
||||
- [WORKING] add embedding of newstate and store in newstate[:embedding]
|
||||
# # Arguments
|
||||
# `a::agent`
|
||||
# an agent
|
||||
|
||||
# Signature
|
||||
"""
|
||||
function transition(state::T2, config::T1, decisionMaker::Function, evaluator::Function,
|
||||
reflector::Function
|
||||
)::Tuple{String, Dict{Symbol, <:Any}, Integer} where {T1<:AbstractDict, T2<:AbstractDict}
|
||||
# # Return
|
||||
# None
|
||||
|
||||
thoughtDict = decisionMaker(config, state)
|
||||
# # Example
|
||||
# ```jldoctest
|
||||
# julia> using JSON3, UUIDs, Dates, FileIO, MQTTClient, ChatAgent
|
||||
# julia> const mqttBroker = "mqtt.yiem.cc"
|
||||
# julia> mqttclient, connection = MakeConnection(mqttBroker, 1883)
|
||||
# julia> tools=Dict( # update input format
|
||||
# "askbox"=>Dict(
|
||||
# :description => "<askbox tool description>Useful for when you need to ask the user for more context. Do not ask the user their own question.</askbox tool description>",
|
||||
# :input => "<input>Input is a text in JSON format.</input><input example>{\"Q1\": \"How are you doing?\", \"Q2\": \"How may I help you?\"}</input example>",
|
||||
# :output => "" ,
|
||||
# :func => nothing,
|
||||
# ),
|
||||
# )
|
||||
# julia> msgMeta = Dict(
|
||||
# :msgPurpose=> "updateStatus",
|
||||
# :from=> "agent",
|
||||
# :to=> "llmAI",
|
||||
# :requestresponse=> "request",
|
||||
# :sendto=> "", # destination topic
|
||||
# :replyTo=> "agent/api/v0.1.0/txt/response", # requester ask responseer to send reply to this topic
|
||||
# :repondToMsgId=> "", # responseer is responseing to this msg id
|
||||
# :taskstatus=> "", # "complete", "fail", "waiting" or other status
|
||||
# :timestamp=> Dates.now(),
|
||||
# :msgId=> "$(uuid4())",
|
||||
# )
|
||||
# julia> a = ChatAgent.agentReflex(
|
||||
# "Jene",
|
||||
# mqttclient,
|
||||
# msgMeta,
|
||||
# agentConfigTopic, # I need a function to send msg to config topic to get load balancer
|
||||
# role=:sommelier,
|
||||
# tools=tools
|
||||
# )
|
||||
# julia> newAgent = ChatAgent.agentReact(agent)
|
||||
# julia> response = ChatAgent.conversation(newAgent, "Hi! how are you?")
|
||||
# ```
|
||||
|
||||
actionname = thoughtDict[:action][:name]
|
||||
actioninput = thoughtDict[:action][:input]
|
||||
# # TODO
|
||||
# - [] update docstring
|
||||
# - [x] MCTS() for planning
|
||||
# - [] add recap to initialState for earlier completed question
|
||||
# - [WORKING] conversation loop
|
||||
|
||||
# map action and input() to llm function
|
||||
response, select, reward, isterminal =
|
||||
if actionname == "chatbox"
|
||||
# deepcopy(state[:virtualCustomerChatHistory]) because I want to keep it clean
|
||||
# so that other simulation start from this same node is not contaminated with actioninput
|
||||
virtualWineUserChatbox(config, actioninput, deepcopy(state[:virtualCustomerChatHistory])) # virtual customer
|
||||
elseif actionname == "winestock"
|
||||
winestock(config, actioninput)
|
||||
elseif actionname == "recommendbox"
|
||||
virtualWineUserRecommendbox(config, actioninput)
|
||||
else
|
||||
error("undefined LLM function. Requesting $actionname")
|
||||
end
|
||||
# # Signature
|
||||
# """
|
||||
# function conversation(a::T, userinput::Dict) where {T<:agent}
|
||||
# config = deepcopy(a.config)
|
||||
# pprint(config)
|
||||
# if userinput[:text] == "newtopic"
|
||||
# clearhistory(a)
|
||||
# return "Okay. What shall we talk about?"
|
||||
# else
|
||||
# # add usermsg to a.chathistory
|
||||
# addNewMessage(a, "user", userinput[:text])
|
||||
|
||||
newNodeKey, newstate = LLMMCTS.makeNewState(state, thoughtDict, response, select, reward,
|
||||
isterminal)
|
||||
if actionname == "chatbox"
|
||||
push!(newstate[:virtualCustomerChatHistory], Dict(:name=>"assistant", :text=> actioninput) )
|
||||
push!(newstate[:virtualCustomerChatHistory], Dict(:name=>"user", :text=> response))
|
||||
end
|
||||
# if isempty(a.plan[:currenttrajectory])
|
||||
|
||||
stateevaluation, progressvalue = evaluator(config, newstate)
|
||||
# # initial state
|
||||
# a.plan[:currenttrajectory] = Dict{Symbol, Any}(
|
||||
# # deepcopy the info to prevent modifying the info unintentionally during MCTS planning
|
||||
# :customerinfo=> deepcopy(a.keywordinfo[:customerinfo]),
|
||||
# :storeinfo=> deepcopy(a.keywordinfo[:storeinfo]),
|
||||
# :userselect=> nothing,
|
||||
# :reward=> 0,
|
||||
# :isterminal=> false,
|
||||
# :evaluation=> nothing,
|
||||
# :lesson=> nothing,
|
||||
|
||||
if newstate[:reward] < 0
|
||||
pprint(newstate[:thoughtHistory])
|
||||
newstate[:evaluation] = stateevaluation
|
||||
newstate[:lesson] = reflector(config, newstate)
|
||||
# :totalTrajectoryReward=> nothing,
|
||||
|
||||
# store new lesson for later use
|
||||
lessonDict = copy(JSON3.read("lesson.json"))
|
||||
latestLessonKey, latestLessonIndice =
|
||||
GeneralUtils.findHighestIndexKey(lessonDict, "lesson")
|
||||
nextIndice = latestLessonKey == :NA ? 1 : latestLessonIndice + 1
|
||||
newLessonKey = Symbol("lesson_$(nextIndice)")
|
||||
lessonDict[newLessonKey] = newstate
|
||||
open("lesson.json", "w") do io
|
||||
JSON3.pretty(io, lessonDict)
|
||||
end
|
||||
print("---> reflector()")
|
||||
end
|
||||
# # contain question, thought_1, action_1, observation_1, thought_2, ...
|
||||
# :thoughtHistory=> OrderedDict{Symbol, Any}(
|
||||
# #[] :recap=>,
|
||||
# :question=> userinput[:text],
|
||||
# ),
|
||||
|
||||
return (newNodeKey, newstate, progressvalue)
|
||||
end
|
||||
# # store conversation for virtual customer because the virtual customer agent is just
|
||||
# # a function and stateless.
|
||||
# :virtualCustomerChatHistory=> Vector{Dict{Symbol, Any}}(
|
||||
# [Dict(:name=> "user", :text=> userinput[:text])]
|
||||
# ),
|
||||
# )
|
||||
# else
|
||||
# _, a.plan[:currenttrajectory] = makeNewState(a.plan[:currenttrajectory],
|
||||
# a.plan[:activeplan][:thoughtHistory], userinput[:text], userinput[:select],
|
||||
# userinput[:reward], userinput[:isterminal])
|
||||
# end
|
||||
# end
|
||||
|
||||
# while true
|
||||
# bestNextState, besttrajectory = LLMMCTS.runMCTS(a.plan[:currenttrajectory],
|
||||
# transition, config, decisionMaker, evaluator, reflector;
|
||||
# totalsample=2, maxDepth=3, maxiterations=3, explorationweight=1.0)
|
||||
# a.plan[:activeplan] = bestNextState
|
||||
|
||||
# latestActionKey, latestActionIndice =
|
||||
# GeneralUtils.findHighestIndexKey(bestNextState[:thoughtHistory], "action")
|
||||
# actionname = bestNextState[:thoughtHistory][latestActionKey][:name]
|
||||
# actioninput = bestNextState[:thoughtHistory][latestActionKey][:input]
|
||||
|
||||
# # transition
|
||||
# if actionname == "chatbox"
|
||||
# # add usermsg to a.chathistory
|
||||
# addNewMessage(a, "assistant", actioninput)
|
||||
# return actioninput
|
||||
# elseif actionname == "recommendbox"
|
||||
# # add usermsg to a.chathistory
|
||||
# addNewMessage(a, "assistant", actioninput)
|
||||
# return actioninput
|
||||
# else
|
||||
# _, a.plan[:currenttrajectory] = transition(a, a.plan[:currenttrajectory], a.plan[:activeplan])
|
||||
# end
|
||||
# end
|
||||
# end
|
||||
|
||||
|
||||
|
||||
@@ -700,8 +894,7 @@ julia> response = ChatAgent.conversation(newAgent, "Hi! how are you?")
|
||||
# Signature
|
||||
"""
|
||||
function conversation(a::T, userinput::Dict) where {T<:agent}
|
||||
config = deepcopy(a.config)
|
||||
pprint(config)
|
||||
|
||||
if userinput[:text] == "newtopic"
|
||||
clearhistory(a)
|
||||
return "Okay. What shall we talk about?"
|
||||
@@ -709,64 +902,246 @@ function conversation(a::T, userinput::Dict) where {T<:agent}
|
||||
# add usermsg to a.chathistory
|
||||
addNewMessage(a, "user", userinput[:text])
|
||||
|
||||
if isempty(a.plan[:currenttrajectory])
|
||||
thought = think(a)
|
||||
|
||||
# initial state
|
||||
a.plan[:currenttrajectory] = Dict{Symbol, Any}(
|
||||
# deepcopy the info to prevent modifying the info unintentionally during MCTS planning
|
||||
:customerinfo=> deepcopy(a.keywordinfo[:customerinfo]),
|
||||
:storeinfo=> deepcopy(a.keywordinfo[:storeinfo]),
|
||||
:userselect=> nothing,
|
||||
:reward=> 0,
|
||||
:isterminal=> false,
|
||||
:evaluation=> nothing,
|
||||
:lesson=> nothing,
|
||||
# thought will be added to chat model via context
|
||||
chatresponse = generatechat(a, thought)
|
||||
|
||||
:totalTrajectoryReward=> nothing,
|
||||
return chatresponse
|
||||
end
|
||||
|
||||
# contain question, thought_1, action_1, observation_1, thought_2, ...
|
||||
:thoughtHistory=> OrderedDict{Symbol, Any}(
|
||||
#[] :recap=>,
|
||||
:question=> userinput[:text],
|
||||
),
|
||||
|
||||
# store conversation for virtual customer because the virtual customer agent is just
|
||||
# a function and stateless.
|
||||
:virtualCustomerChatHistory=> Vector{Dict{Symbol, Any}}(
|
||||
[Dict(:name=> "user", :text=> userinput[:text])]
|
||||
),
|
||||
)
|
||||
end
|
||||
# function conversation(a::T, userinput::Dict) where {T<:agent}
|
||||
# config = deepcopy(a.config)
|
||||
# pprint(config)
|
||||
# if userinput[:text] == "newtopic"
|
||||
# clearhistory(a)
|
||||
# return "Okay. What shall we talk about?"
|
||||
# else
|
||||
# # add usermsg to a.chathistory
|
||||
# addNewMessage(a, "user", userinput[:text])
|
||||
|
||||
# if isempty(a.plan[:currenttrajectory])
|
||||
|
||||
# # initial state
|
||||
# a.plan[:currenttrajectory] = Dict{Symbol, Any}(
|
||||
# # deepcopy the info to prevent modifying the info unintentionally during MCTS planning
|
||||
# :customerinfo=> deepcopy(a.keywordinfo[:customerinfo]),
|
||||
# :storeinfo=> deepcopy(a.keywordinfo[:storeinfo]),
|
||||
# :userselect=> nothing,
|
||||
# :reward=> 0,
|
||||
# :isterminal=> false,
|
||||
# :evaluation=> nothing,
|
||||
# :lesson=> nothing,
|
||||
|
||||
# :totalTrajectoryReward=> nothing,
|
||||
|
||||
# # contain question, thought_1, action_1, observation_1, thought_2, ...
|
||||
# :thoughtHistory=> OrderedDict{Symbol, Any}(
|
||||
# #[] :recap=>,
|
||||
# :question=> userinput[:text],
|
||||
# ),
|
||||
|
||||
# # store conversation for virtual customer because the virtual customer agent is just
|
||||
# # a function and stateless.
|
||||
# :virtualCustomerChatHistory=> Vector{Dict{Symbol, Any}}(
|
||||
# [Dict(:name=> "user", :text=> userinput[:text])]
|
||||
# ),
|
||||
# )
|
||||
# else
|
||||
# _, a.plan[:currenttrajectory] = makeNewState(a.plan[:currenttrajectory],
|
||||
# a.plan[:activeplan][:thoughtHistory], userinput[:text], userinput[:select],
|
||||
# userinput[:reward], userinput[:isterminal])
|
||||
# end
|
||||
# end
|
||||
|
||||
# while true
|
||||
# bestNextState, besttrajectory = LLMMCTS.runMCTS(a.plan[:currenttrajectory],
|
||||
# transition, config, decisionMaker, evaluator, reflector;
|
||||
# totalsample=2, maxDepth=3, maxiterations=3, explorationweight=1.0)
|
||||
# a.plan[:activeplan] = bestNextState
|
||||
|
||||
# latestActionKey, latestActionIndice =
|
||||
# GeneralUtils.findHighestIndexKey(bestNextState[:thoughtHistory], "action")
|
||||
# actionname = bestNextState[:thoughtHistory][latestActionKey][:name]
|
||||
# actioninput = bestNextState[:thoughtHistory][latestActionKey][:input]
|
||||
|
||||
# # transition
|
||||
# if actionname == "chatbox"
|
||||
# # add usermsg to a.chathistory
|
||||
# addNewMessage(a, "assistant", actioninput)
|
||||
# return actioninput
|
||||
# elseif actionname == "recommendbox"
|
||||
# # add usermsg to a.chathistory
|
||||
# addNewMessage(a, "assistant", actioninput)
|
||||
# return actioninput
|
||||
# else
|
||||
# _, a.plan[:currenttrajectory] = transition(a, a.plan[:currenttrajectory], a.plan[:activeplan])
|
||||
# end
|
||||
# end
|
||||
# end
|
||||
|
||||
|
||||
"""
|
||||
|
||||
# Arguments
|
||||
|
||||
# Return
|
||||
|
||||
# Example
|
||||
```jldoctest
|
||||
julia>
|
||||
```
|
||||
|
||||
# TODO
|
||||
- [] update docstring
|
||||
- [x] implement the function
|
||||
- [x] add try block. check result that it is expected before returning
|
||||
|
||||
# Signature
|
||||
"""
|
||||
function think(a::T) where {T<:agent}
|
||||
thoughtDict = decisionMaker(a)
|
||||
actionname = thoughtDict[:action_name]
|
||||
actioninput = thoughtDict[:action_input]
|
||||
|
||||
# map action and input() to llm function
|
||||
response =
|
||||
if actionname == "CHATBOX"
|
||||
(result=actioninput, errormsg=nothing, success=true)
|
||||
elseif actionname == "WINESTOCK"
|
||||
DBconnection = LibPQ.Connection("host=192.168.88.12 port=5432 dbname=yiem_wine_assistant user=yiem password=yiem@Postgres_0.0")
|
||||
winestock(actioninput, DBconnection, a.text2textInstructLLM)
|
||||
else
|
||||
_, a.plan[:currenttrajectory] = makeNewState(a.plan[:currenttrajectory],
|
||||
a.plan[:activeplan][:thoughtHistory], userinput[:text], userinput[:select],
|
||||
userinput[:reward], userinput[:isterminal])
|
||||
end
|
||||
error("undefined LLM function. Requesting $actionname")
|
||||
end
|
||||
|
||||
while true
|
||||
bestNextState, besttrajectory = LLMMCTS.runMCTS(a.plan[:currenttrajectory],
|
||||
transition, config, decisionMaker, evaluator, reflector;
|
||||
totalsample=2, maxDepth=3, maxiterations=3, explorationweight=1.0)
|
||||
a.plan[:activeplan] = bestNextState
|
||||
# this section allow LLM functions above to have different return values.
|
||||
result = haskey(response, :result) ? response[:result] : nothing
|
||||
select = haskey(response, :select) ? response[:select] : nothing
|
||||
reward::Integer = haskey(response, :reward) ? response[:reward] : 0
|
||||
isterminal::Bool = haskey(response, :isterminal) ? response[:isterminal] : false
|
||||
errormsg::Union{AbstractString, Nothing} = haskey(response, :errormsg) ? response[:errormsg] : nothing
|
||||
success::Bool = haskey(response, :success) ? response[:success] : false
|
||||
a.shortmem
|
||||
return result
|
||||
end
|
||||
|
||||
latestActionKey, latestActionIndice =
|
||||
GeneralUtils.findHighestIndexKey(bestNextState[:thoughtHistory], "action")
|
||||
actionname = bestNextState[:thoughtHistory][latestActionKey][:name]
|
||||
actioninput = bestNextState[:thoughtHistory][latestActionKey][:input]
|
||||
|
||||
# transition
|
||||
if actionname == "chatbox"
|
||||
# add usermsg to a.chathistory
|
||||
addNewMessage(a, "assistant", actioninput)
|
||||
return actioninput
|
||||
elseif actionname == "recommendbox"
|
||||
# add usermsg to a.chathistory
|
||||
addNewMessage(a, "assistant", actioninput)
|
||||
return actioninput
|
||||
else
|
||||
_, a.plan[:currenttrajectory] = transition(a, a.plan[:currenttrajectory], a.plan[:activeplan])
|
||||
"""
|
||||
|
||||
# Arguments
|
||||
- `a::T1`
|
||||
one of ChatAgent's agent.
|
||||
- `input::T2`
|
||||
# Return
|
||||
A JSON string of available wine
|
||||
|
||||
# Example
|
||||
```jldoctest
|
||||
julia>
|
||||
```
|
||||
|
||||
# TODO
|
||||
- [] update docs
|
||||
- [WORKING] implement the function
|
||||
|
||||
# Signature
|
||||
"""
|
||||
function generatechat(a::T1, input::T2) where {T1<:agent, T2<:AbstractString}
|
||||
systemmsg =
|
||||
"""
|
||||
You are a helpful sommelier working for a wine store.
|
||||
Your task is to help the user choose the best wine that match the user preferences from your inventory.
|
||||
You are also eager to improve your helpfulness.
|
||||
|
||||
You must follow the following guidelines:
|
||||
- Get to know how much the user willing to spend
|
||||
- Get to know type of wine the user is looking for e.g. red, white, sparkling, rose, dessert, fortified
|
||||
- Get to know what occasion the user is buying wine for
|
||||
- Get to know what characteristics of wine the user is looking for e.g. tannin, sweetness, intensity, acidity
|
||||
- Get to know what food the user will have with wine
|
||||
|
||||
At each round of conversation, the user will give you:
|
||||
Context: ...
|
||||
Your thoughts: Your current thinking in your mind
|
||||
Your earlier conversation with the user: ...
|
||||
|
||||
You should then respond to the user with:
|
||||
- chat: what do you want to say to the user
|
||||
|
||||
You should only respond in format as described below:
|
||||
chat: ...
|
||||
|
||||
Let's begin!
|
||||
"""
|
||||
|
||||
usermsg =
|
||||
"""
|
||||
Context: None
|
||||
Your thoughts: $input
|
||||
Your earlier conversation with the user: $(chatHistoryToString(a))
|
||||
"""
|
||||
|
||||
_prompt =
|
||||
[
|
||||
Dict(:name=> "system", :text=> systemmsg),
|
||||
Dict(:name=> "user", :text=> usermsg)
|
||||
]
|
||||
|
||||
# put in model format
|
||||
prompt = GeneralUtils.formatLLMtext(_prompt, "llama3instruct")
|
||||
prompt *=
|
||||
"""
|
||||
<|start_header_id|>assistant<|end_header_id|>
|
||||
"""
|
||||
|
||||
for attempt in 1:5
|
||||
try
|
||||
response = text2textInstructLLM(prompt)
|
||||
responsedict = GeneralUtils.textToDict(response,
|
||||
["chat"],
|
||||
rightmarker=":", symbolkey=true)
|
||||
|
||||
# check if dict has all required value
|
||||
evaluationtext::AbstractString = responsedict[:evaluation]
|
||||
responsedict[:score] = parse(Int, responsedict[:score]) # convert string "5" into integer 5
|
||||
score::Integer = responsedict[:score]
|
||||
accepted_as_answer::AbstractString = responsedict[:accepted_as_answer]
|
||||
suggestion::AbstractString = responsedict[:suggestion]
|
||||
|
||||
# add to state here instead to in transition() because the latter causes julia extension crash (a bug in julia extension)
|
||||
state[:evaluation] = responsedict[:evaluation]
|
||||
state[:evaluationscore] = responsedict[:score]
|
||||
state[:accepted_as_answer] = responsedict[:accepted_as_answer]
|
||||
state[:suggestion] = responsedict[:suggestion]
|
||||
|
||||
# mark as terminal state when the answer is achieved
|
||||
if accepted_as_answer == "Yes"
|
||||
state[:isterminal] = true
|
||||
state[:reward] = 1
|
||||
end
|
||||
|
||||
return responsedict[:score]
|
||||
catch e
|
||||
io = IOBuffer()
|
||||
showerror(io, e)
|
||||
errorMsg = String(take!(io))
|
||||
st = sprint((io, v) -> show(io, "text/plain", v), stacktrace(catch_backtrace()))
|
||||
println("")
|
||||
println("Attempt $attempt. Error occurred: $errorMsg\n$st")
|
||||
println("")
|
||||
end
|
||||
end
|
||||
error("evaluator failed to generate an evaluation")
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
end
|
||||
|
||||
|
||||
|
||||
@@ -4,7 +4,7 @@ export virtualWineUserChatbox, jsoncorrection, winestock,
|
||||
virtualWineUserRecommendbox, userChatbox, userRecommendbox
|
||||
|
||||
using HTTP, JSON3, URIs, Random, PrettyPrinting, UUIDs
|
||||
using GeneralUtils
|
||||
using GeneralUtils, SQLLLM
|
||||
using ..type, ..util
|
||||
|
||||
# ---------------------------------------------- 100 --------------------------------------------- #
|
||||
@@ -357,13 +357,13 @@ julia> result = winestock(agent, input)
|
||||
```
|
||||
|
||||
# TODO
|
||||
[] update docs
|
||||
[WORKING] implement the function
|
||||
- [] update docs
|
||||
- [WORKING] implement the function
|
||||
|
||||
# Signature
|
||||
"""
|
||||
function winestock(config::T1, input::T2
|
||||
)::Union{Tuple{String, Number, Number, Bool}, Tuple{String, Nothing, Number, Bool}} where {T1<:AbstractDict, T2<:AbstractString}
|
||||
function winestock(input::T, DBconnection, text2textInstructLLM::Function
|
||||
)::Union{Tuple{String, Number, Number, Bool}, Tuple{String, Nothing, Number, Bool}} where {T<:AbstractString}
|
||||
|
||||
# SELECT *
|
||||
# FROM food
|
||||
|
||||
82
src/type.jl
82
src/type.jl
@@ -80,12 +80,8 @@ julia> agent = YiemAgent.bsommelier(
|
||||
mutable struct sommelier <: agent
|
||||
name::String # agent name
|
||||
id::String # agent id
|
||||
config::Dict # agent config
|
||||
tools::Dict
|
||||
maxiterations::Integer # how many thinking round
|
||||
totalsample::Integer # how many sample in each thinking round
|
||||
maxDepth::Integer # how many step ahead to be simulated start from current state into the future
|
||||
maxHistoryMsg::Integer # 21th and earlier messages will get summarized
|
||||
maxHistoryMsg::Integer # e.g. 21th and earlier messages will get summarized
|
||||
|
||||
""" Memory
|
||||
Ref: Chat prompt format https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/discussions/3
|
||||
@@ -97,76 +93,48 @@ mutable struct sommelier <: agent
|
||||
|
||||
"""
|
||||
chathistory::Vector{Dict{Symbol, Any}}
|
||||
keywordinfo::Dict{Symbol, Any}
|
||||
shortmem::Dict{Symbol, Any}
|
||||
|
||||
# 1-historyPoint is in Dict{Symbol, Any} and compose of:
|
||||
# state, statevalue, thought, action, observation
|
||||
plan::Dict{Symbol, Any}
|
||||
# communication function
|
||||
text2textInstructLLM::Function
|
||||
end
|
||||
|
||||
function sommelier(
|
||||
config::Dict = Dict(
|
||||
:mqttServerInfo=> Dict(
|
||||
:broker=> nothing,
|
||||
:port=> nothing,
|
||||
),
|
||||
:receivemsg=> Dict(
|
||||
:prompt=> nothing, # topic to receive prompt i.e. frontend send msg to this topic
|
||||
:internal=> nothing,
|
||||
),
|
||||
:thirdPartyService=> Dict(
|
||||
:text2textinstruct=> nothing,
|
||||
:text2textchat=> nothing,
|
||||
),
|
||||
)
|
||||
text2textInstructLLM::Function
|
||||
;
|
||||
name::String= "Assistant",
|
||||
id::String= string(uuid4()),
|
||||
tools::Dict= Dict(
|
||||
:chatbox=> Dict(
|
||||
:name => "chatbox",
|
||||
:description => "Useful for when you need to communicate with the user.",
|
||||
:input => "Input should be a conversation to the user.",
|
||||
:output => "" ,
|
||||
:func => nothing,
|
||||
),
|
||||
),
|
||||
maxiterations::Integer= 3,
|
||||
totalsample::Integer= 3,
|
||||
maxDepth::Integer= 3,
|
||||
maxHistoryMsg::Integer= 20,
|
||||
chathistory::Vector{Dict{Symbol, Any}} = Vector{Dict{Symbol, Any}}(),
|
||||
keywordinfo::Dict{Symbol, Any} = Dict{Symbol, Any}(
|
||||
:customerinfo => Dict{Symbol, Any}(),
|
||||
:storeinfo => Dict{Symbol, Any}(),
|
||||
)
|
||||
|
||||
tools = Dict( # update input format
|
||||
"chatbox"=> Dict(
|
||||
:description => "<askbox tool description>Useful for when you need to ask the user for more context. Do not ask the user their own question.</askbox tool description>",
|
||||
:input => """<input>Input is a text in JSON format.</input><input example>{\"Q1\": \"How are you doing?\", \"Q2\": \"How may I help you?\"}</input example>""",
|
||||
:output => "" ,
|
||||
),
|
||||
plan::Dict{Symbol, Any} = Dict{Symbol, Any}(
|
||||
|
||||
# store 3 to 5 best plan AI frequently used to avoid having to search MCTS all the time
|
||||
# each plan is in [historyPoint_1, historyPoint_2, ...] format
|
||||
:existingplan => Vector(),
|
||||
|
||||
:activeplan => Dict{Symbol, Any}(), # current using plan
|
||||
:currenttrajectory=> Dict{Symbol, Any}(), # store question, thought, action, observation, ...
|
||||
"winestock"=> Dict(
|
||||
:description => "<winestock tool description>A handy tool for searching wine in your inventory that match the user preferences.</winestock tool description>",
|
||||
:input => """<input>Input is a JSON-formatted string that contains a detailed and precise search query.</input><input example>{\"wine type\": \"rose\", \"price\": \"max 35\", \"sweetness level\": \"sweet\", \"intensity level\": \"light bodied\", \"Tannin level\": \"low\", \"Acidity level\": \"low\"}</input example>""",
|
||||
:output => """<output>Output are wines that match the search query in JSON format.""",
|
||||
),
|
||||
# "finalanswer"=> Dict(
|
||||
# :description => "<tool description>Useful for when you are ready to recommend wines to the user.</tool description>",
|
||||
# :input => """<input format>{\"finalanswer\": \"some text\"}.</input format><input example>{\"finalanswer\": \"I recommend Zena Crown Vista\"}</input example>""",
|
||||
# :output => "" ,
|
||||
# :func => nothing,
|
||||
# ),
|
||||
)
|
||||
)
|
||||
|
||||
#[NEXTVERSION] publish to a.config[:configtopic] to get a config.
|
||||
#[NEXTVERSION] get a config message in a.mqttMsg_internal
|
||||
#[NEXTVERSION] set agent according to config
|
||||
|
||||
newAgent = sommelier(
|
||||
name,
|
||||
id,
|
||||
config,
|
||||
tools,
|
||||
maxiterations,
|
||||
totalsample,
|
||||
maxDepth,
|
||||
maxHistoryMsg,
|
||||
chathistory,
|
||||
keywordinfo,
|
||||
plan,
|
||||
Dict{Symbol, Any}(),
|
||||
text2textInstructLLM,
|
||||
)
|
||||
|
||||
return newAgent
|
||||
|
||||
407
src/util.jl
407
src/util.jl
@@ -1,7 +1,6 @@
|
||||
module util
|
||||
|
||||
export clearhistory, addNewMessage, formatLLMtext, iterativeprompting,
|
||||
formatLLMtext_llama3instruct, formatLLMtext_phi3instruct
|
||||
export clearhistory, addNewMessage, chatHistoryToString
|
||||
|
||||
using UUIDs, Dates, DataStructures, HTTP, MQTTClient, JSON3
|
||||
using GeneralUtils
|
||||
@@ -114,222 +113,242 @@ function addNewMessage(a::T1, name::String, text::T2;
|
||||
end
|
||||
|
||||
|
||||
|
||||
""" Convert a single chat dictionary into LLM model instruct format.
|
||||
|
||||
# Llama 3 instruct format example
|
||||
<|system|>
|
||||
You are a helpful AI assistant.<|end|>
|
||||
<|user|>
|
||||
I am going to Paris, what should I see?<|end|>
|
||||
<|assistant|>
|
||||
Paris, the capital of France, is known for its stunning architecture, art museums."<|end|>
|
||||
<|user|>
|
||||
What is so great about #1?<|end|>
|
||||
<|assistant|>
|
||||
|
||||
|
||||
# Arguments
|
||||
- `name::T`
|
||||
message owner name e.f. "system", "user" or "assistant"
|
||||
- `text::T`
|
||||
|
||||
# Return
|
||||
- `formattedtext::String`
|
||||
text formatted to model format
|
||||
|
||||
# Example
|
||||
```jldoctest
|
||||
julia> using Revise
|
||||
julia> using YiemAgent
|
||||
julia> d = Dict(:name=> "system",:text=> "You are a helpful, respectful and honest assistant.",)
|
||||
julia> formattedtext = YiemAgent.formatLLMtext_phi3instruct(d[:name], d[:text])
|
||||
|
||||
```
|
||||
|
||||
Signature
|
||||
"""
|
||||
function formatLLMtext_phi3instruct(name::T, text::T) where {T<:AbstractString}
|
||||
formattedtext =
|
||||
"""
|
||||
<|$name|>
|
||||
$text<|end|>\n
|
||||
"""
|
||||
|
||||
return formattedtext
|
||||
end
|
||||
|
||||
|
||||
""" Convert a single chat dictionary into LLM model instruct format.
|
||||
|
||||
# Llama 3 instruct format example
|
||||
<|begin_of_text|>
|
||||
<|start_header_id|>system<|end_header_id|>
|
||||
You are a helpful assistant.
|
||||
<|eot_id|>
|
||||
<|start_header_id|>user<|end_header_id|>
|
||||
Get me an icecream.
|
||||
<|eot_id|>
|
||||
<|start_header_id|>assistant<|end_header_id|>
|
||||
Go buy it yourself at 7-11.
|
||||
<|eot_id|>
|
||||
|
||||
# Arguments
|
||||
- `name::T`
|
||||
message owner name e.f. "system", "user" or "assistant"
|
||||
- `text::T`
|
||||
|
||||
# Return
|
||||
- `formattedtext::String`
|
||||
text formatted to model format
|
||||
|
||||
# Example
|
||||
```jldoctest
|
||||
julia> using Revise
|
||||
julia> using YiemAgent
|
||||
julia> d = Dict(:name=> "system",:text=> "You are a helpful, respectful and honest assistant.",)
|
||||
julia> formattedtext = YiemAgent.formatLLMtext_llama3instruct(d[:name], d[:text])
|
||||
"<|begin_of_text|>\n <|start_header_id|>system<|end_header_id|>\n You are a helpful, respectful and honest assistant.\n <|eot_id|>\n"
|
||||
```
|
||||
|
||||
Signature
|
||||
"""
|
||||
function formatLLMtext_llama3instruct(name::T, text::T) where {T<:AbstractString}
|
||||
formattedtext =
|
||||
if name == "system"
|
||||
"""
|
||||
<|begin_of_text|>
|
||||
<|start_header_id|>$name<|end_header_id|>
|
||||
$text
|
||||
<|eot_id|>
|
||||
"""
|
||||
else
|
||||
"""
|
||||
<|start_header_id|>$name<|end_header_id|>
|
||||
$text
|
||||
<|eot_id|>
|
||||
"""
|
||||
function chatHistoryToString(a)
|
||||
chatHistoryStr = ""
|
||||
for i in a.chathistory
|
||||
name = i[:name]
|
||||
text = i[:text]
|
||||
chatHistoryStr *= "$name> $text"
|
||||
end
|
||||
|
||||
return formattedtext
|
||||
return chatHistoryStr
|
||||
end
|
||||
|
||||
|
||||
|
||||
""" Convert a chat messages in vector of dictionary into LLM model instruct format.
|
||||
|
||||
# Arguments
|
||||
- `messages::Vector{Dict{Symbol, T}}`
|
||||
message owner name e.f. "system", "user" or "assistant"
|
||||
- `formatname::T`
|
||||
format name to be used
|
||||
|
||||
# Return
|
||||
- `formattedtext::String`
|
||||
text formatted to model format
|
||||
|
||||
# Example
|
||||
```jldoctest
|
||||
julia> using Revise
|
||||
julia> using YiemAgent
|
||||
julia> chatmessage = [
|
||||
Dict(:name=> "system",:text=> "You are a helpful, respectful and honest assistant.",),
|
||||
Dict(:name=> "user",:text=> "list me all planets in our solar system.",),
|
||||
Dict(:name=> "assistant",:text=> "I'm sorry. I don't know. You tell me.",),
|
||||
]
|
||||
julia> formattedtext = YiemAgent.formatLLMtext(chatmessage, "llama3instruct")
|
||||
"<|begin_of_text|>\n <|start_header_id|>system<|end_header_id|>\n You are a helpful, respectful and honest assistant.\n <|eot_id|>\n <|start_header_id|>user<|end_header_id|>\n list me all planets in our solar system.\n <|eot_id|>\n <|start_header_id|>assistant<|end_header_id|>\n I'm sorry. I don't know. You tell me.\n <|eot_id|>\n"
|
||||
```
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
# """ Convert a single chat dictionary into LLM model instruct format.
|
||||
|
||||
# # Llama 3 instruct format example
|
||||
# <|system|>
|
||||
# You are a helpful AI assistant.<|end|>
|
||||
# <|user|>
|
||||
# I am going to Paris, what should I see?<|end|>
|
||||
# <|assistant|>
|
||||
# Paris, the capital of France, is known for its stunning architecture, art museums."<|end|>
|
||||
# <|user|>
|
||||
# What is so great about #1?<|end|>
|
||||
# <|assistant|>
|
||||
|
||||
|
||||
# # Arguments
|
||||
# - `name::T`
|
||||
# message owner name e.f. "system", "user" or "assistant"
|
||||
# - `text::T`
|
||||
|
||||
# # Return
|
||||
# - `formattedtext::String`
|
||||
# text formatted to model format
|
||||
|
||||
# # Example
|
||||
# ```jldoctest
|
||||
# julia> using Revise
|
||||
# julia> using YiemAgent
|
||||
# julia> d = Dict(:name=> "system",:text=> "You are a helpful, respectful and honest assistant.",)
|
||||
# julia> formattedtext = YiemAgent.formatLLMtext_phi3instruct(d[:name], d[:text])
|
||||
|
||||
# ```
|
||||
|
||||
# Signature
|
||||
"""
|
||||
function formatLLMtext(messages::Vector{Dict{Symbol, T}},
|
||||
formatname::String="llama3instruct") where {T<:Any}
|
||||
f = if formatname == "llama3instruct"
|
||||
formatLLMtext_llama3instruct
|
||||
elseif formatname == "mistral"
|
||||
# not define yet
|
||||
elseif formatname == "phi3instruct"
|
||||
formatLLMtext_phi3instruct
|
||||
else
|
||||
error("$formatname template not define yet")
|
||||
end
|
||||
# """
|
||||
# function formatLLMtext_phi3instruct(name::T, text::T) where {T<:AbstractString}
|
||||
# formattedtext =
|
||||
# """
|
||||
# <|$name|>
|
||||
# $text<|end|>\n
|
||||
# """
|
||||
|
||||
str = ""
|
||||
for t in messages
|
||||
str *= f(t[:name], t[:text])
|
||||
end
|
||||
|
||||
# add <|assistant|> so that the model don't generate it and I don't need to clean it up later
|
||||
if formatname == "phi3instruct"
|
||||
str *= "<|assistant|>\n"
|
||||
end
|
||||
|
||||
return str
|
||||
end
|
||||
# return formattedtext
|
||||
# end
|
||||
|
||||
|
||||
"""
|
||||
# """ Convert a single chat dictionary into LLM model instruct format.
|
||||
|
||||
Arguments\n
|
||||
-----
|
||||
# # Llama 3 instruct format example
|
||||
# <|begin_of_text|>
|
||||
# <|start_header_id|>system<|end_header_id|>
|
||||
# You are a helpful assistant.
|
||||
# <|eot_id|>
|
||||
# <|start_header_id|>user<|end_header_id|>
|
||||
# Get me an icecream.
|
||||
# <|eot_id|>
|
||||
# <|start_header_id|>assistant<|end_header_id|>
|
||||
# Go buy it yourself at 7-11.
|
||||
# <|eot_id|>
|
||||
|
||||
Return\n
|
||||
-----
|
||||
# # Arguments
|
||||
# - `name::T`
|
||||
# message owner name e.f. "system", "user" or "assistant"
|
||||
# - `text::T`
|
||||
|
||||
Example\n
|
||||
-----
|
||||
```jldoctest
|
||||
julia>
|
||||
```
|
||||
# # Return
|
||||
# - `formattedtext::String`
|
||||
# text formatted to model format
|
||||
|
||||
TODO\n
|
||||
-----
|
||||
[] update docstring
|
||||
[PENDING] implement the function
|
||||
# # Example
|
||||
# ```jldoctest
|
||||
# julia> using Revise
|
||||
# julia> using YiemAgent
|
||||
# julia> d = Dict(:name=> "system",:text=> "You are a helpful, respectful and honest assistant.",)
|
||||
# julia> formattedtext = YiemAgent.formatLLMtext_llama3instruct(d[:name], d[:text])
|
||||
# "<|begin_of_text|>\n <|start_header_id|>system<|end_header_id|>\n You are a helpful, respectful and honest assistant.\n <|eot_id|>\n"
|
||||
# ```
|
||||
|
||||
Signature\n
|
||||
-----
|
||||
"""
|
||||
function iterativeprompting(a::T, prompt::String, verification::Function) where {T<:agent}
|
||||
msgMeta = GeneralUtils.generate_msgMeta(
|
||||
a.config[:externalService][:text2textinstruct],
|
||||
senderName= "iterativeprompting",
|
||||
senderId= a.id,
|
||||
receiverName= "text2textinstruct",
|
||||
)
|
||||
# Signature
|
||||
# """
|
||||
# function formatLLMtext_llama3instruct(name::T, text::T) where {T<:AbstractString}
|
||||
# formattedtext =
|
||||
# if name == "system"
|
||||
# """
|
||||
# <|begin_of_text|>
|
||||
# <|start_header_id|>$name<|end_header_id|>
|
||||
# $text
|
||||
# <|eot_id|>
|
||||
# """
|
||||
# else
|
||||
# """
|
||||
# <|start_header_id|>$name<|end_header_id|>
|
||||
# $text
|
||||
# <|eot_id|>
|
||||
# """
|
||||
# end
|
||||
|
||||
outgoingMsg = Dict(
|
||||
:msgMeta=> msgMeta,
|
||||
:payload=> Dict(
|
||||
:text=> prompt,
|
||||
)
|
||||
)
|
||||
# return formattedtext
|
||||
# end
|
||||
|
||||
success = nothing
|
||||
result = nothing
|
||||
critique = ""
|
||||
|
||||
# iteration loop
|
||||
while true
|
||||
# send prompt to LLM
|
||||
response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg)
|
||||
error("--> iterativeprompting")
|
||||
# check for correctness and get feedback
|
||||
success, _critique = verification(response)
|
||||
|
||||
if success
|
||||
result = response
|
||||
break
|
||||
else
|
||||
# add critique to prompt
|
||||
critique *= _critique * "\n"
|
||||
replace!(prompt, "Critique: ..." => "Critique: $critique")
|
||||
end
|
||||
end
|
||||
# """ Convert a chat messages in vector of dictionary into LLM model instruct format.
|
||||
|
||||
return (success=success, result=result)
|
||||
end
|
||||
# # Arguments
|
||||
# - `messages::Vector{Dict{Symbol, T}}`
|
||||
# message owner name e.f. "system", "user" or "assistant"
|
||||
# - `formatname::T`
|
||||
# format name to be used
|
||||
|
||||
# # Return
|
||||
# - `formattedtext::String`
|
||||
# text formatted to model format
|
||||
|
||||
# # Example
|
||||
# ```jldoctest
|
||||
# julia> using Revise
|
||||
# julia> using YiemAgent
|
||||
# julia> chatmessage = [
|
||||
# Dict(:name=> "system",:text=> "You are a helpful, respectful and honest assistant.",),
|
||||
# Dict(:name=> "user",:text=> "list me all planets in our solar system.",),
|
||||
# Dict(:name=> "assistant",:text=> "I'm sorry. I don't know. You tell me.",),
|
||||
# ]
|
||||
# julia> formattedtext = YiemAgent.formatLLMtext(chatmessage, "llama3instruct")
|
||||
# "<|begin_of_text|>\n <|start_header_id|>system<|end_header_id|>\n You are a helpful, respectful and honest assistant.\n <|eot_id|>\n <|start_header_id|>user<|end_header_id|>\n list me all planets in our solar system.\n <|eot_id|>\n <|start_header_id|>assistant<|end_header_id|>\n I'm sorry. I don't know. You tell me.\n <|eot_id|>\n"
|
||||
# ```
|
||||
|
||||
# # Signature
|
||||
# """
|
||||
# function formatLLMtext(messages::Vector{Dict{Symbol, T}},
|
||||
# formatname::String="llama3instruct") where {T<:Any}
|
||||
# f = if formatname == "llama3instruct"
|
||||
# formatLLMtext_llama3instruct
|
||||
# elseif formatname == "mistral"
|
||||
# # not define yet
|
||||
# elseif formatname == "phi3instruct"
|
||||
# formatLLMtext_phi3instruct
|
||||
# else
|
||||
# error("$formatname template not define yet")
|
||||
# end
|
||||
|
||||
# str = ""
|
||||
# for t in messages
|
||||
# str *= f(t[:name], t[:text])
|
||||
# end
|
||||
|
||||
# # add <|assistant|> so that the model don't generate it and I don't need to clean it up later
|
||||
# if formatname == "phi3instruct"
|
||||
# str *= "<|assistant|>\n"
|
||||
# end
|
||||
|
||||
# return str
|
||||
# end
|
||||
|
||||
|
||||
# """
|
||||
|
||||
# Arguments\n
|
||||
# -----
|
||||
|
||||
# Return\n
|
||||
# -----
|
||||
|
||||
# Example\n
|
||||
# -----
|
||||
# ```jldoctest
|
||||
# julia>
|
||||
# ```
|
||||
|
||||
# TODO\n
|
||||
# -----
|
||||
# [] update docstring
|
||||
# [PENDING] implement the function
|
||||
|
||||
# Signature\n
|
||||
# -----
|
||||
# """
|
||||
# function iterativeprompting(a::T, prompt::String, verification::Function) where {T<:agent}
|
||||
# msgMeta = GeneralUtils.generate_msgMeta(
|
||||
# a.config[:externalService][:text2textinstruct],
|
||||
# senderName= "iterativeprompting",
|
||||
# senderId= a.id,
|
||||
# receiverName= "text2textinstruct",
|
||||
# )
|
||||
|
||||
# outgoingMsg = Dict(
|
||||
# :msgMeta=> msgMeta,
|
||||
# :payload=> Dict(
|
||||
# :text=> prompt,
|
||||
# )
|
||||
# )
|
||||
|
||||
# success = nothing
|
||||
# result = nothing
|
||||
# critique = ""
|
||||
|
||||
# # iteration loop
|
||||
# while true
|
||||
# # send prompt to LLM
|
||||
# response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg)
|
||||
# error("--> iterativeprompting")
|
||||
# # check for correctness and get feedback
|
||||
# success, _critique = verification(response)
|
||||
|
||||
# if success
|
||||
# result = response
|
||||
# break
|
||||
# else
|
||||
# # add critique to prompt
|
||||
# critique *= _critique * "\n"
|
||||
# replace!(prompt, "Critique: ..." => "Critique: $critique")
|
||||
# end
|
||||
# end
|
||||
|
||||
# return (success=success, result=result)
|
||||
# end
|
||||
|
||||
|
||||
|
||||
|
||||
@@ -13,60 +13,60 @@ client, connection = MakeConnection(config[:mqttServerInfo][:broker],
|
||||
|
||||
receiveUserMsgChannel = Channel{Dict}(4)
|
||||
receiveInternalMsgChannel = Channel{Dict}(4)
|
||||
|
||||
println(typeof(connection))
|
||||
msgMeta = GeneralUtils.generate_msgMeta(
|
||||
"N/A",
|
||||
replyTopic = config[:servicetopic][:mqtttopic] # ask frontend reply to this instance_chat_topic
|
||||
)
|
||||
|
||||
agentConfig = Dict(
|
||||
:mqttServerInfo=> config[:mqttServerInfo],
|
||||
:receivemsg=> Dict(
|
||||
:prompt=> config[:servicetopic][:mqtttopic], # topic to receive prompt i.e. frontend send msg to this topic
|
||||
:internal=> instanceInternalTopic,
|
||||
),
|
||||
:externalservice=> config[:externalservice],
|
||||
)
|
||||
# commConfig = Dict(
|
||||
# :mqttServerInfo=> config[:mqttServerInfo],
|
||||
# :receivemsg=> Dict(
|
||||
# :prompt=> config[:servicetopic][:mqtttopic], # topic to receive prompt i.e. frontend send msg to this topic
|
||||
# ),
|
||||
# :externalservice=> config[:externalservice],
|
||||
# )
|
||||
|
||||
# Instantiate an agent
|
||||
tools=Dict( # update input format
|
||||
"askbox"=> Dict(
|
||||
:description => "<askbox tool description>Useful for when you need to ask the user for more context. Do not ask the user their own question.</askbox tool description>",
|
||||
:input => """<input>Input is a text in JSON format.</input><input example>{\"Q1\": \"How are you doing?\", \"Q2\": \"How may I help you?\"}</input example>""",
|
||||
:output => "" ,
|
||||
:func => nothing,
|
||||
),
|
||||
# "winestock"=> Dict(
|
||||
# :description => "<winestock tool description>A handy tool for searching wine in your inventory that match the user preferences.</winestock tool description>",
|
||||
# :input => """<input>Input is a JSON-formatted string that contains a detailed and precise search query.</input><input example>{\"wine type\": \"rose\", \"price\": \"max 35\", \"sweetness level\": \"sweet\", \"intensity level\": \"light bodied\", \"Tannin level\": \"low\", \"Acidity level\": \"low\"}</input example>""",
|
||||
# :output => """<output>Output are wines that match the search query in JSON format.""",
|
||||
# :func => ChatAgent.winestock,
|
||||
# ),
|
||||
"finalanswer"=> Dict(
|
||||
:description => "<tool description>Useful for when you are ready to recommend wines to the user.</tool description>",
|
||||
:input => """<input format>{\"finalanswer\": \"some text\"}.</input format><input example>{\"finalanswer\": \"I recommend Zena Crown Vista\"}</input example>""",
|
||||
:output => "" ,
|
||||
:func => nothing,
|
||||
),
|
||||
function text2textInstructLLM(prompt::String)
|
||||
msgMeta = GeneralUtils.generate_msgMeta(
|
||||
config[:externalservice][:text2textinstruct][:mqtttopic],
|
||||
senderName= "yiemagent",
|
||||
senderId= string(uuid4()),
|
||||
receiverName= "text2textinstruct",
|
||||
mqttBroker= config[:mqttServerInfo][:broker],
|
||||
mqttBrokerPort= config[:mqttServerInfo][:port],
|
||||
)
|
||||
|
||||
outgoingMsg = Dict(
|
||||
:msgMeta=> msgMeta,
|
||||
:payload=> Dict(
|
||||
:text=> prompt,
|
||||
:kwargs=> Dict(
|
||||
:max_tokens=> 512,
|
||||
:stop=> ["<|eot_id|>"],
|
||||
:temperature=> 0.2,
|
||||
)
|
||||
)
|
||||
)
|
||||
|
||||
_response = GeneralUtils.sendReceiveMqttMsg(outgoingMsg)
|
||||
response = _response[:response][:text]
|
||||
|
||||
return response
|
||||
end
|
||||
|
||||
# Instantiate an agent
|
||||
a = YiemAgent.sommelier(
|
||||
agentConfig,
|
||||
text2textInstructLLM,
|
||||
name="assistant",
|
||||
id="testingSessionID", # agent instance id
|
||||
tools=tools,
|
||||
)
|
||||
|
||||
# response = YiemAgent.conversation(a, Dict(:text=> "newtopic",) )
|
||||
|
||||
response = YiemAgent.conversation(a, Dict(:text=> "Hello, I would like a get a bottle of wine",
|
||||
:select=> nothing,
|
||||
:reward=> 0,
|
||||
:isterminal=> false,
|
||||
) )
|
||||
response = YiemAgent.conversation(a, Dict(:text=> "Hello, I would like a get a bottle of wine."))
|
||||
println("---> YiemAgent: ", response)
|
||||
|
||||
#BUG mcts do not start at current chat history
|
||||
response = YiemAgent.conversation(a, Dict(:text=> "I'm having a graduation party this evening. I'll pay at most 30 bucks.",
|
||||
:select=> nothing,
|
||||
:reward=> 0,
|
||||
@@ -96,9 +96,6 @@ response = YiemAgent.winestock(a, dummyinput)
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user