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34 Commits

Author SHA1 Message Date
ton 4e592173a6 update 2026-08-12 14:37:11 +07:00
ton 0cacb5c94a update 2026-08-12 04:35:34 +07:00
ton 6c96409969 update 2026-08-12 04:33:19 +07:00
ton 06d51c1ee9 update 2026-08-12 04:00:09 +07:00
ton 2ad3d1df38 update 2026-08-11 19:10:37 +07:00
ton 83c7770877 update 2026-08-11 18:57:53 +07:00
ton bad14fbe7f update 2026-08-11 18:42:34 +07:00
ton 578e8f55bd update 2026-08-11 18:28:03 +07:00
ton ae3e432b02 update 2026-08-11 17:35:56 +07:00
ton 7c14390400 update 2026-08-11 17:28:25 +07:00
ton 89885c1583 update 2026-08-11 16:43:48 +07:00
ton 5a27630ccf update 2026-08-11 12:15:05 +07:00
ton ed91260468 update 2026-08-10 20:37:28 +07:00
ton c13aeb3a74 Merge pull request 'V0.8.0 verify tool use' (#43) from v0.8.0-verify_tool_use into v0.8.0
Reviewed-on: #43
2026-08-10 13:10:57 +00:00
ton 287704778f update 2026-08-10 20:07:15 +07:00
ton a9fa23f01b update 2026-08-10 19:19:58 +07:00
ton c5cb18f0f1 update 2026-08-10 16:10:04 +07:00
ton c78f4b023d update 2026-08-10 14:55:09 +07:00
ton 1b69f69c7d update 2026-08-10 13:33:45 +07:00
ton 3891099eaa update readme 2026-08-10 10:39:30 +07:00
ton 268d340e2f Merge pull request 'V0.8.0 use tool module' (#42) from v0.8.0-use_tool_module into v0.8.0
Reviewed-on: #42
2026-08-10 02:48:25 +00:00
ton 189bc2efcf update 2026-08-10 09:43:35 +07:00
ton 92b3e4081f update 2026-08-09 22:50:02 +07:00
ton 750eff483b update 2026-08-09 22:08:04 +07:00
ton 5cc35c78f4 Merge pull request 'V0.8.0 add tools' (#41) from v0.8.0-add_tools into v0.8.0
Reviewed-on: #41
2026-08-09 11:47:02 +00:00
ton ed5415d92a update 2026-08-09 08:45:35 +07:00
ton 6b3d575ea0 update 2026-08-09 06:50:37 +07:00
ton da16c80a0a update 2026-08-09 06:27:48 +07:00
ton 069240912b update 2026-08-09 04:45:31 +07:00
ton 2aa0d1e9a4 update 2026-08-08 19:44:06 +07:00
ton 03e1dd7628 update 2026-08-08 18:49:51 +07:00
ton 70296a3bf2 update 2026-08-08 12:21:52 +07:00
ton 75b2ce5978 update 2026-08-08 12:11:53 +07:00
ton d8172a7fbe Merge pull request 'V0.8.0 async think loop' (#40) from v0.8.0-async_think_loop into v0.8.0
Reviewed-on: #40
2026-08-08 04:13:05 +00:00
23 changed files with 2864 additions and 1683 deletions
+58 -94
View File
@@ -2,7 +2,7 @@
julia_version = "1.12.6"
manifest_format = "2.0"
project_hash = "1c1379a2cec320abc347f3acb5ee815ba9855aa6"
project_hash = "0db36d4fb31037ba05065476e6aebaf4cd0e1e8c"
[[deps.Accessors]]
deps = ["CompositionsBase", "ConstructionBase", "Dates", "InverseFunctions", "MacroTools"]
@@ -97,9 +97,9 @@ uuid = "944b1d66-785c-5afd-91f1-9de20f533193"
version = "0.7.8"
[[deps.CommonSolve]]
git-tree-sha1 = "eeaad7cef88554c2fa56b5a3f71cfd5cb708c662"
git-tree-sha1 = "cf963add2340ad9960e5eb22844e61ad8f931fe1"
uuid = "38540f10-b2f7-11e9-35d8-d573e4eb0ff2"
version = "0.2.11"
version = "0.2.13"
[[deps.Compat]]
deps = ["TOML", "UUIDs"]
@@ -146,9 +146,9 @@ version = "1.6.0"
StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
[[deps.Crayons]]
git-tree-sha1 = "249fe38abf76d48563e2f4556bebd215aa317e15"
git-tree-sha1 = "54b76cbb40d9a0f5368c880725b2f141da77c94f"
uuid = "a8cc5b0e-0ffa-5ad4-8c14-923d3ee1735f"
version = "4.1.1"
version = "4.2.0"
[[deps.DBInterface]]
git-tree-sha1 = "a444404b3f94deaa43ca2a58e18153a82695282b"
@@ -168,9 +168,9 @@ version = "1.8.2"
[[deps.DataStructures]]
deps = ["OrderedCollections"]
git-tree-sha1 = "6fb53a69613a0b2b68a0d12671717d307ab8b24e"
git-tree-sha1 = "b0bc6d2cad1fed8b7fd59a1551a991cb3d2809e6"
uuid = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
version = "0.19.5"
version = "0.19.6"
[[deps.DataValueInterfaces]]
git-tree-sha1 = "bfc1187b79289637fa0ef6d4436ebdfe6905cbd6"
@@ -208,9 +208,9 @@ version = "1.11.0"
[[deps.Distributions]]
deps = ["AliasTables", "FillArrays", "LinearAlgebra", "PDMats", "Printf", "QuadGK", "Random", "Roots", "SpecialFunctions", "Statistics", "StatsAPI", "StatsBase", "StatsFuns"]
git-tree-sha1 = "cd3c5ac74cd3923c8945c6a81518c46abd0e73a3"
git-tree-sha1 = "d2facc77c08c1c2bfb1a77c148edd05b3db5410b"
uuid = "31c24e10-a181-5473-b8eb-7969acd0382f"
version = "0.25.129"
version = "0.25.130"
[deps.Distributions.extensions]
DistributionsChainRulesCoreExt = "ChainRulesCore"
@@ -240,15 +240,9 @@ uuid = "4e289a0a-7415-4d19-859d-a7e5c4648b56"
version = "1.0.7"
[[deps.ExprTools]]
git-tree-sha1 = "27415f162e6028e81c72b82ef756bf321213b6ec"
git-tree-sha1 = "d2e49e7efd29719d6f28b891b0e0e159daa9d2b4"
uuid = "e2ba6199-217a-4e67-a87a-7c52f15ade04"
version = "0.1.10"
[[deps.EzXML]]
deps = ["Printf", "XML2_jll"]
git-tree-sha1 = "7ea1aa5869e2626ccae84480e4f37185bc6f41d3"
uuid = "8f5d6c58-4d21-5cfd-889c-e3ad7ee6a615"
version = "1.2.3"
version = "0.1.11"
[[deps.FileIO]]
deps = ["Pkg", "Requires", "UUIDs"]
@@ -277,9 +271,9 @@ version = "1.11.0"
[[deps.FillArrays]]
deps = ["LinearAlgebra"]
git-tree-sha1 = "2f979084d1e13948a3352cf64a25df6bd3b4dca3"
git-tree-sha1 = "5bad39456d9f0166184fce2248783dd9862645c1"
uuid = "1a297f60-69ca-5386-bcde-b61e274b549b"
version = "1.16.0"
version = "1.17.0"
weakdeps = ["PDMats", "SparseArrays", "StaticArrays", "Statistics"]
[deps.FillArrays.extensions]
@@ -300,11 +294,11 @@ version = "1.1.0"
[[deps.GeneralUtils]]
deps = ["CSV", "DataFrames", "DataStructures", "Dates", "Distributions", "Graphs", "HTTP", "JSON", "LibPQ", "NATS", "PrettyPrinting", "Random", "Revise", "SHA", "StringDistances", "UUIDs"]
git-tree-sha1 = "93293126d24d3929ef6a5067f347bc28c6582c71"
git-tree-sha1 = "129b8fa1bf3bf6d8c0a080f39db09b9b986ef8de"
repo-rev = "main"
repo-url = "https://git.yiem.cc/ton/GeneralUtils"
uuid = "c6c72f09-b708-4ac8-ac7c-2084d70108fe"
version = "0.5.10"
version = "0.5.11"
[[deps.Graphs]]
deps = ["ArnoldiMethod", "DataStructures", "Inflate", "LinearAlgebra", "Random", "SimpleTraits", "SparseArrays", "Statistics"]
@@ -321,9 +315,9 @@ version = "1.14.0"
[[deps.HTTP]]
deps = ["Base64", "CodecZlib", "Dates", "EnumX", "PrecompileTools", "Random", "Reseau", "SHA", "URIs", "UUIDs", "Zlib_jll"]
git-tree-sha1 = "c2c808326222b6dc4bec295a83b55f79aeec98e0"
git-tree-sha1 = "0a58fbbdee93d132a2fb1159b7f5e1b5c2465e71"
uuid = "cd3eb016-35fb-5094-929b-558a96fad6f3"
version = "2.5.5"
version = "2.6.4"
[[deps.HashArrayMappedTries]]
git-tree-sha1 = "2eaa69a7cab70a52b9687c8bf950a5a93ec895ae"
@@ -332,9 +326,9 @@ version = "0.2.0"
[[deps.HypergeometricFunctions]]
deps = ["Gamma", "LinearAlgebra"]
git-tree-sha1 = "18d7deab5fb0440dc6a7b6993c5c27b25420de10"
git-tree-sha1 = "31bb6c92405c084617facc1d7ed9eb6c402d061e"
uuid = "34004b35-14d8-5ef3-9330-4cdb6864b03a"
version = "0.3.29"
version = "0.3.30"
[[deps.ICU_jll]]
deps = ["Artifacts", "JLLWrappers", "Libdl"]
@@ -412,9 +406,9 @@ version = "1.8.0"
[[deps.JSON]]
deps = ["Dates", "Logging", "Parsers", "PrecompileTools", "StructUtils", "UUIDs", "Unicode"]
git-tree-sha1 = "c89d196f5ffb64bfbf80985b699ea913b0d2c211"
git-tree-sha1 = "65979512c25a0727f050e6e4be40f0fd9ec893f7"
uuid = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
version = "1.6.1"
version = "1.7.0"
weakdeps = ["ArrowTypes"]
[deps.JSON.extensions]
@@ -432,9 +426,9 @@ weakdeps = ["ArrowTypes"]
[[deps.JuliaInterpreter]]
deps = ["CodeTracking", "InteractiveUtils", "Random", "UUIDs"]
git-tree-sha1 = "58927c485919bf17ea308d9d82156de1adf4b006"
git-tree-sha1 = "c3d401f110454b4ea24a76be33f6ee0d7d385103"
uuid = "aa1ae85d-cabe-5617-a682-6adf51b2e16a"
version = "0.10.12"
version = "0.11.4"
[[deps.JuliaSyntaxHighlighting]]
deps = ["StyledStrings"]
@@ -506,12 +500,6 @@ version = "1.11.3+1"
uuid = "8f399da3-3557-5675-b5ff-fb832c97cbdb"
version = "1.11.0"
[[deps.Libiconv_jll]]
deps = ["Artifacts", "JLLWrappers", "Libdl"]
git-tree-sha1 = "be484f5c92fad0bd8acfef35fe017900b0b73809"
uuid = "94ce4f54-9a6c-5748-9c1c-f9c7231a4531"
version = "1.18.0+0"
[[deps.LinearAlgebra]]
deps = ["Libdl", "OpenBLAS_jll", "libblastrampoline_jll"]
uuid = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
@@ -539,9 +527,9 @@ version = "1.11.0"
[[deps.LoweredCodeUtils]]
deps = ["CodeTracking", "Compiler", "JuliaInterpreter"]
git-tree-sha1 = "3733419e9a71156b389f3e331672d2e95436783f"
git-tree-sha1 = "1d4c737ab26f51ceed52ab2019c09b7660eb7440"
uuid = "6f1432cf-f94c-5a45-995e-cdbf5db27b0b"
version = "3.6.2"
version = "3.8.0"
[[deps.MacroTools]]
git-tree-sha1 = "1e0228a030642014fe5cfe68c2c0a818f9e3f522"
@@ -599,9 +587,9 @@ version = "0.1.1"
[[deps.NanoDates]]
deps = ["Dates", "Parsers"]
git-tree-sha1 = "850a0557ae5934f6e67ac0dc5ca13d0328422d1f"
git-tree-sha1 = "77c7e98ca39aefb481f9b97a2f4f5c5471c08a1d"
uuid = "46f1a544-deae-4307-8689-c12aa3c955c6"
version = "1.0.3"
version = "1.1.0"
[[deps.NetworkOptions]]
uuid = "ca575930-c2e3-43a9-ace4-1e988b2c1908"
@@ -640,15 +628,15 @@ uuid = "efe28fd5-8261-553b-a9e1-b2916fc3738e"
version = "0.5.6+0"
[[deps.OrderedCollections]]
git-tree-sha1 = "94ba93778373a53bfd5a0caaf7d809c445292ff4"
git-tree-sha1 = "05f45c2e0de6259db764adbfd2f1dc6d3f8de13c"
uuid = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
version = "1.8.2"
version = "2.0.1"
[[deps.PDMats]]
deps = ["LinearAlgebra", "SparseArrays", "SuiteSparse"]
git-tree-sha1 = "26766d4b5f1a410c218a19b85a672c6edb693c65"
git-tree-sha1 = "123266c25174ef6c8d4718920abc206452cf8de6"
uuid = "90014a1f-27ba-587c-ab20-58faa44d9150"
version = "0.11.40"
version = "0.11.41"
weakdeps = ["StatsBase"]
[deps.PDMats.extensions]
@@ -656,9 +644,9 @@ weakdeps = ["StatsBase"]
[[deps.Parsers]]
deps = ["Dates", "PrecompileTools", "UUIDs"]
git-tree-sha1 = "32a4e09c5f29402573d673901778a0e03b0807b9"
git-tree-sha1 = "3de8f5e6e90ebfa8d6d1f86997d6cdcd6a912ff3"
uuid = "69de0a69-1ddd-5017-9359-2bf0b02dc9f0"
version = "2.8.6"
version = "2.8.7"
[[deps.Pkg]]
deps = ["Artifacts", "Dates", "Downloads", "FileWatching", "LibGit2", "Libdl", "Logging", "Markdown", "Printf", "Random", "SHA", "TOML", "Tar", "UUIDs", "p7zip_jll"]
@@ -688,15 +676,15 @@ uuid = "21216c6a-2e73-6563-6e65-726566657250"
version = "1.5.2"
[[deps.PrettyPrinting]]
git-tree-sha1 = "142ee93724a9c5d04d78df7006670a93ed1b244e"
git-tree-sha1 = "0b7f4ad437e31c51cf5b91fb103579b04025170a"
uuid = "54e16d92-306c-5ea0-a30b-337be88ac337"
version = "0.4.2"
version = "0.4.3"
[[deps.PrettyTables]]
deps = ["Crayons", "LaTeXStrings", "Markdown", "PrecompileTools", "Printf", "REPL", "Reexport", "StringManipulation", "Tables"]
git-tree-sha1 = "ebf455bb866ee6737030e3d3816bb6a0683c4325"
git-tree-sha1 = "4ac881f5432bd93463a41767a814a45245be22b6"
uuid = "08abe8d2-0d0c-5749-adfa-8a2ac140af0d"
version = "3.4.0"
version = "3.4.6"
[deps.PrettyTables.extensions]
PrettyTablesExcelExt = "XLSX"
@@ -757,15 +745,15 @@ version = "1.3.1"
[[deps.Reseau]]
deps = ["NetworkOptions", "OpenSSL_jll", "PrecompileTools", "Random", "SHA"]
git-tree-sha1 = "0eab6d95ed40c2ef3992255c1c71e4f9748932b5"
git-tree-sha1 = "701ef63506992668c0069a4d1ac1540b77258e6c"
uuid = "802f3686-a58f-41ce-bb0c-3c43c75bba36"
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version = "1.3.6"
[[deps.Revise]]
deps = ["CRC32c", "CodeTracking", "FileWatching", "InteractiveUtils", "JuliaInterpreter", "LibGit2", "LoweredCodeUtils", "OrderedCollections", "Preferences", "REPL", "UUIDs"]
git-tree-sha1 = "27e3ee13fc8739a59b380d6163d6a82f52c03bd7"
deps = ["CRC32c", "CodeTracking", "FileWatching", "JuliaInterpreter", "LibGit2", "LoweredCodeUtils", "OrderedCollections", "Preferences", "REPL", "UUIDs"]
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[deps.Revise.extensions]
@@ -779,15 +767,15 @@ version = "0.9.0"
[[deps.Rmath_jll]]
deps = ["Artifacts", "JLLWrappers", "Libdl"]
git-tree-sha1 = "58cdd8fb2201a6267e1db87ff148dd6c1dbd8ad8"
git-tree-sha1 = "6d40b2fe70437b01397d2a4d5b020008da4e7019"
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[[deps.Roots]]
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[deps.Roots.extensions]
RootsChainRulesCoreExt = "ChainRulesCore"
@@ -840,12 +828,6 @@ git-tree-sha1 = "084c47c7c5ce5cfecefa0a98dff69eb3646b5a80"
uuid = "91c51154-3ec4-41a3-a24f-3f23e20d615c"
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[[deps.Serde]]
deps = ["CSV", "Dates", "EzXML", "JSON", "TOML", "UUIDs", "YAML"]
git-tree-sha1 = "f397fc8779cc53e4677c2708f3802c6996f28d00"
uuid = "db9b398d-9517-45f8-9a95-92af99003e0e"
version = "3.7.2"
[[deps.Serialization]]
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version = "1.11.0"
@@ -879,9 +861,9 @@ version = "1.12.0"
[[deps.SpecialFunctions]]
deps = ["IrrationalConstants", "LogExpFunctions", "OpenLibm_jll", "OpenSpecFun_jll"]
git-tree-sha1 = "6547cbdd8ce32efba0d21c5a40fa96d1a3548f9f"
git-tree-sha1 = "c3ac026e735264e9bdc6a9bcbd1b1e781b36e3bc"
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version = "2.8.3"
[deps.SpecialFunctions.extensions]
SpecialFunctionsChainRulesCoreExt = "ChainRulesCore"
@@ -932,9 +914,9 @@ version = "0.34.12"
[[deps.StatsFuns]]
deps = ["HypergeometricFunctions", "IrrationalConstants", "LogExpFunctions", "Reexport", "Rmath", "SpecialFunctions"]
git-tree-sha1 = "770240df9a3b8888065046948f7a09b4e0f997d5"
git-tree-sha1 = "91a5737baed20ee31f3faea0e51f57461f6a689e"
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version = "2.2.0"
version = "2.2.1"
[deps.StatsFuns.extensions]
StatsFunsChainRulesCoreExt = "ChainRulesCore"
@@ -950,17 +932,11 @@ git-tree-sha1 = "cd83a04baf746e3b43b83c61b7de77ab0409b80a"
uuid = "88034a9c-02f8-509d-84a9-84ec65e18404"
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[[deps.StringEncodings]]
deps = ["Libiconv_jll"]
git-tree-sha1 = "b765e46ba27ecf6b44faf70df40c57aa3a547dcb"
uuid = "69024149-9ee7-55f6-a4c4-859efe599b68"
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[[deps.StringManipulation]]
deps = ["PrecompileTools"]
git-tree-sha1 = "d05693d339e37d6ab134c5ab53c29fce5ee5d7d5"
git-tree-sha1 = "8a90c1d77c3277a5d43b83927b3cbe2c70a37484"
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version = "0.4.7"
[[deps.StructTypes]]
deps = ["Dates", "UUIDs"]
@@ -970,9 +946,9 @@ version = "1.11.0"
[[deps.StructUtils]]
deps = ["Dates", "UUIDs"]
git-tree-sha1 = "82bee338d650aa515f31866c460cb7e3bcef90b8"
git-tree-sha1 = "c65ae4aa47e543c278aea0a3468786d33021a3ff"
uuid = "ec057cc2-7a8d-4b58-b3b3-92acb9f63b42"
version = "2.8.2"
version = "2.8.4"
[deps.StructUtils.extensions]
StructUtilsMeasurementsExt = ["Measurements"]
@@ -1046,9 +1022,9 @@ uuid = "3bb67fe8-82b1-5028-8e26-92a6c54297fa"
version = "0.11.3"
[[deps.URIs]]
git-tree-sha1 = "bef26fb046d031353ef97a82e3fdb6afe7f21b1a"
git-tree-sha1 = "3b0738bd7c5645641845da25cbd99800b8718689"
uuid = "5c2747f8-b7ea-4ff2-ba2e-563bfd36b1d4"
version = "1.6.1"
version = "1.6.2"
[[deps.UTCDateTimes]]
deps = ["Dates", "TimeZones"]
@@ -1076,23 +1052,11 @@ git-tree-sha1 = "cd1659ba0d57b71a464a29e64dbc67cfe83d54e7"
uuid = "76eceee3-57b5-4d4a-8e66-0e911cebbf60"
version = "1.6.1"
[[deps.XML2_jll]]
deps = ["Artifacts", "JLLWrappers", "Libdl", "Libiconv_jll", "Zlib_jll"]
git-tree-sha1 = "3f3315d89fc954a28f5b471bce698ed6e27481be"
uuid = "02c8fc9c-b97f-50b9-bbe4-9be30ff0a78a"
version = "2.15.3+0"
[[deps.YAML]]
deps = ["Base64", "Dates", "Printf", "StringEncodings"]
git-tree-sha1 = "a1c0c7585346251353cddede21f180b96388c403"
uuid = "ddb6d928-2868-570f-bddf-ab3f9cf99eb6"
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[[deps.YiemAgent]]
deps = ["Base64", "CSV", "DataFrames", "DataStructures", "Dates", "HTTP", "JSON", "LLMMCTS", "LibPQ", "NATS", "PrettyPrinting", "Random", "Revise", "SQLLLM", "Serde", "Serialization", "URIs", "UUIDs"]
deps = ["Base64", "CSV", "DataFrames", "DataStructures", "Dates", "GeneralUtils", "HTTP", "JSON", "LLMMCTS", "LibPQ", "NATS", "PrettyPrinting", "Random", "Revise", "SQLLLM", "Serialization", "URIs", "UUIDs"]
path = "."
uuid = "e012c34b-7f78-48e0-971c-7abb83b6f0a2"
version = "0.7.4"
version = "0.8.0"
[[deps.Zlib_jll]]
deps = ["Libdl"]
-2
View File
@@ -19,7 +19,6 @@ PrettyPrinting = "54e16d92-306c-5ea0-a30b-337be88ac337"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"
SQLLLM = "2ebc79c7-cc10-4a3a-9665-d2e1d61e63d3"
Serde = "db9b398d-9517-45f8-9a95-92af99003e0e"
Serialization = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
URIs = "5c2747f8-b7ea-4ff2-ba2e-563bfd36b1d4"
UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
@@ -34,4 +33,3 @@ JSON = "1.6.1"
LLMMCTS = "0.1.5"
NATS = "0.1.0"
SQLLLM = "0.2.8"
Serde = "3.7.2"
+30 -19
View File
@@ -1,23 +1,34 @@
# YiemAgent
## TODO
- [WORKING] build prompt()
- [ ] build agent runLoop()
- [ ] build MCP server connector
- [ ] executeplan() to execute the plan
- [ ] add comprehensive tests
Julia framework for building agents with tool use.
## Changelog
## Getting Started
### Version 0.8.0
- Converted snake_case fields to camelCase:
- `llmModel`: `base_url``baseUrl`, `context_window``contextWindow`, `max_tokens``maxTokens`
- Converted PascalCase type references to camelCase:
- `AgentState``agentState`
- `AgentTool``agentTool`
- `AgentMessage``agentMessage`
- `PendingMessageQueue``pendingMessageQueue`
- `ActiveRun``activeRun`
- `StreamFn``streamFn`
- `ThinkingLevel``thinkingLevel`
- `ToolExecutionMode``toolExecutionMode`
1. Install dependencies: `]add JSON, DataStructures, UUIDs, Dates, ...`
2. Create a `yiemAgent` with `loadTools("src/tools")`
3. Call `runAgent(agent, "message")` then `takeResponse(agent)`
## Architecture
```
src/
├── YiemAgent.jl # Module entry point
├── type.jl # Core types (messages, tools, agent state)
├── utils.jl # Message formatting, validation
├── agentCore.jl # Agent loop, tool execution pipeline
├── api.jl # Public API (runAgent, takeResponse, etc.)
└── tools/
├── registry.jl # Tool registry (loadTools, registerTool, listTools)
├── getWeather.jl # Weather lookup tool
├── getTime.jl # Time lookup tool
├── writeTool.jl # Create new tool files (self-modifying)
└── README.md # Tool development guide
```
## Tool Development
See `src/tools/README.md` for:
- Tool anatomy (schema, execute, getTool)
- Validation hooks
- Agent loop lifecycle
- Self-modifying tools (`writeTool`)
+1625
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File diff suppressed because it is too large Load Diff
-92
View File
@@ -1,92 +0,0 @@
# Dynamic Tool Loading
Tools can be loaded dynamically from `.jl` files in the `src/tools/` directory without hardcoding filenames in the main module.
## How It Works
1. `src/tools/registry.jl` defines a `loadTools(dir::String)` function that scans a directory for `.jl` files
2. Each tool file must define a single function: `getTool()::agentTool`
3. `loadTools()` sorts files alphabetically, includes each one, calls `getTool()`, and registers the result
4. Loaded tools are returned as `Vector{agentTool}` for use when constructing a `yiemAgent`
## Directory Structure
```
src/
├── tools/
│ ├── registry.jl # Tool loader (do not edit)
│ ├── getWeather.jl # Your tool
│ └── query_db.jl # Another tool
├── type.jl
├── utils.jl
├── agentCore.jl
├── api.jl
└── YiemAgent.jl
```
## Creating a Tool
Each `.jl` file in `src/tools/` must define `getTool()` returning an `agentTool`:
```julia
# src/tools/getWeather.jl
function getTool()::agentTool
return agentTool(
name = "getWeather",
label = "Weather Lookup",
description = "Fetch current weather and forecast for a given city.",
inputSchema = Dict{String,Any}(
"type" => "object",
"properties" => Dict(
"city" => Dict("type" => "string", "description" => "City and country"),
"units" => Dict("type" => "string", "enum" => ["celsius", "fahrenheit"], "default" => "celsius")
),
"required" => ["city"]
),
execute = (toolCallId, args, signal, onPartialResult) -> begin
city = args["city"]
return agentToolResult(
[textContent("Weather in $(city): Sunny, 22C")],
Dict{Any,Any}(), nothing, false
)
end,
prepareArguments = nothing,
parallelToolExecute = false
)
end
```
No `module` wrapper needed — the registry includes each file in the current module scope so all types (`agentTool`, `textContent`, `agentToolResult`, etc.) resolve correctly.
## Loading Tools
```julia
using .YiemAgent
using .YiemAgent: toolRegistry
# Load all tool files from src/tools/
tools = YiemAgent.loadTools(joinpath(@__DIR__, "src", "tools"))
# Create agent with loaded tools
agent = yiemAgent(
systemPrompt = "You are a helpful assistant.",
model = my_model,
tools = tools,
llmCall = my_llm_call,
agentEventSink = my_event_sink
)
```
## Available Functions
| Function | Description |
|----------|-------------|
| `loadTools(dir::String)` | Scan directory and load all `.jl` tool files |
| `registerTool(tool::agentTool)` | Register a single tool into the global registry |
| `getTools()` | Get deep copy of all registered tools |
| `listTools()` | List all registered tools as `(name, label)` pairs |
| `clearTools()` | Clear the global registry |
## File Loading Order
Files are sorted alphabetically before loading, so `01_database.jl` loads before `02_weather.jl`. This ensures deterministic registration order.
+77 -2
View File
@@ -1,2 +1,77 @@
# ── executeToolCalls() Julia pseudo code ──────────────────────────
# Full call stack from runLoop → executeToolCalls → prepare → execute → finalize → emit
i am not sure that's the case. see my NATS message log:
<NATS debug message>
Info: debug
payload = "new user msg"
Info: debug
payload = "new user msg"
Info: debug
payload = "new user msg"
Info: debug
payload = "new user msg"
Info: debug
payload = "new user msg"
Info: debug
payload = "new user msg"
Info: debug
payload = "new user msg"
Info: debug
payload = "_process_message 3"
Info: debug
payload = "_process_message 5"
Info: debug
payload = "_process_message 6"
Info: debug
payload = "_process_message 7"
</NATS debug message>
my NATS receiver report the following for a long time
Info: debug
payload = "new user msg"
untill I Ctrl + d so shutdown the process then i got the following report
Info: debug
payload = "_process_message 3"
Info: debug
payload = "_process_message 5"
Info: debug
payload = "_process_message 6"
Info: debug
payload = "_process_message 7"
my point is if _process_message() actually run then this code in _process_message()
"raw_msg = take!(agent.inputChannel)"
should take the new msg message out of agent.inputChannel and there should be only one debug message showing
Info: debug
payload = "new user msg"
before reaching error("debug marker")
+1 -1
View File
@@ -13,7 +13,7 @@ module YiemAgent
include("utils.jl")
using .utils
include("tools/registry.jl")
include("toolRegistry.jl")
using .toolRegistry
# include("llmfunction.jl")
+207 -102
View File
@@ -1,14 +1,142 @@
module agentCore
export _agent_loop, OpenAiToUserMessage
export yiemAgent, _agent_loop, OpenAiToUserMessage
using JSON, DataStructures, Dates, UUIDs, HTTP, Random, PrettyPrinting, Serialization,
DataFrames, Serde, Base.Threads
DataFrames, Base.Threads
using GeneralUtils
using ..type, ..utils
using ..type, ..utils, ..toolRegistry
# ---------------------------------------------- 100 --------------------------------------------- #
"""
docstring
"""
mutable struct yiemAgent <: agent # High-level agent wrapper
_state::agentState # Current state (prompt, model, messages, tools, etc.)
# user sends prompt message to agent. if agent is idle, it process user message right away.
# if agent is running, it process user message after the current tool call finished.
inputChannel::Channel
# Buffers messages the user sends while the agent is busy. Processed after all inputChannel
# messages are handled and the agent is idle (not using a tool call).
followUpChannel::Channel
# agent sends response message to user after processing all user messages in inputChannel
# and all followUp messages.
outputChannel::Channel
_agent_loop::Union{Task, Nothing} # agent loop running in the background
# Preprocess/transform messages and context (modify, filter, prune, inject context from memory,
# reorder, ...) for a single LLM call in _process_message()'s loop.
# returns new Vector{agentMessage}
prepareContext::Union{Function, Nothing}
# Convert prepareContext()'s new Vector{agentMessage} to LLM message format
formatMsgForLLM::Function
# A callable struct. Actually invoke the LLM to get a completion response.
# The LLM response comes back as an assistantMessage whose content is an array of content blocks.
# Each block has a type — "text", "thinking", or "toolCall".
# The code filters for type === "toolCall" blocks, then passes them to executeToolCalls().
llmCall
# Callback invoked before executing a tool call (ask for user permission/confirmation/abort, etc..)
beforeToolCall::Union{Function, Nothing}
# Callback invoked after executing a tool call to sanitize tools output so the output is ready
# to be converted into toolResults message
afterToolCall::Union{Function, Nothing}
# prepareNextTurn::Union{Function, Nothing} # Callback to prepare the next conversation turn
# prepareNextTurnWithContext::Union{Function, Nothing} # Same but receives context
sessionId::Union{String, Nothing} # Optional session identifier
maxRetryDelayMs::Union{Int64, Nothing} # Maximum delay between retries (ms)
parallelToolExecute::Bool # Default: false
agentEventSink # agent emits its status via this function
end
"""
Create a new yiemAgent instance with a background loop task.
Spawns a background `@spawn` task that runs the agent loop, listening
on `inputChannel` and `followUpChannel` channels concurrently.
# Keyword Arguments
- `systemPrompt::String`: System prompt for the agent
- `model`: LLM model to use
- `tools::OrderedDict{String, agentTool}`: Available tools keyed by name (default: empty)
- `messages::Vector{agentMessage}`: Initial conversation messages (default: empty)
- `formatMsgForLLM::Function`: Convert agent messages to LLM message format (default: `defaultformatMsgForLLM`)
- `llmCall::Function`: Function to invoke the LLM (required)
- `prepareContext::Union{Function, Nothing}`: Preprocess/transform messages before sending to LLM (default: `nothing`)
- `beforeToolCall::Union{Function, Nothing}`: Callback invoked before executing a tool call (default: `nothing`)
- `afterToolCall::Union{Function, Nothing}`: Callback invoked after executing a tool call (default: `nothing`)
- `prepareNextTurn::Union{Function, Nothing}`: Callback to prepare the next conversation turn (default: `nothing`)
- `prepareNextTurnWithContext::Union{Function, Nothing}`: Same but receives context (default: `nothing`)
- `sessionId::Union{String, Nothing}`: Optional session identifier (default: `nothing`)
- `maxRetryDelayMs::Union{Int64, Nothing}`: Maximum delay between retries in milliseconds (default: `nothing`)
- `parallelToolExecute::Bool`: Run tool calls in parallel (default: `false`)
- `agentEventSink::Function`: Callback to receive agent events
# Returns
- A new `yiemAgent` instance with an active background task
"""
function yiemAgent(
toolsFolderPath::String,
llmCall,
;
systemPrompt::String="You are helpful assistant.",
model=nothing,
messages::Vector{agentMessage}=agentMessage[],
prepareContext::Function=prepareContext,
formatMsgForLLM::Function=formatMsgForLLM,
beforeToolCall::Function=beforeToolCall,
afterToolCall::Function=afterToolCall,
# prepareNextTurn::Union{Function, Nothing}=nothing,
# prepareNextTurnWithContext::Union{Function, Nothing}=nothing,
sessionId::Union{String, Nothing}=nothing,
maxRetryDelayMs::Union{Int64, Nothing}=nothing,
parallelToolExecute::Bool=false,
agentEventSink=agentEventSink,
)
# Create channels: input (user -> agent), followUp (async queue), output (agent -> user)
inputChannel = Channel(16)
followUp = Channel(32)
outputChannel = Channel(16)
# load tools from toolsFolderPath
toolStore1 = toolStore(name="myagent")
loadTools(toolStore1, toolsFolderPath)
# Create struct with a placeholder task, then spawn and replace it
agent = yiemAgent(
agentState(systemPrompt, model, getTools(toolStore1), messages),
inputChannel,
followUp,
outputChannel,
nothing, # placeholder — replaced below
prepareContext,
formatMsgForLLM,
llmCall,
beforeToolCall,
afterToolCall,
# prepareNextTurn,
# prepareNextTurnWithContext,
sessionId,
maxRetryDelayMs,
parallelToolExecute,
agentEventSink,
)
# Spawn the background loop and attach it
agent._agent_loop = @spawn _agent_loop(agent)
return agent
end
"""
Private agent loop. Runs in a background `@spawn` task.
@@ -81,7 +209,8 @@ function _agent_loop(agent::yiemAgent)
if isready(agent.inputChannel)
# message will be taken in _process_message()
msg = fetch!(agent.inputChannel)
msg = fetch(agent.inputChannel)
agent.agentEventSink("new user msg")
else
yield()
end
@@ -107,9 +236,11 @@ function _agent_loop(agent::yiemAgent)
# start _process_message loop
if agent._state.activeRun == false
agent.agentEventSink("_agent_loop 2")
# Dispatch message through the processing pipeline
processingTask = Threads.@spawn _process_message(agent)
processingTask = Threads.@spawn _process_message(agent)
agent._state.activeRun = true
agent.agentEventSink("_agent_loop 3")
end
# during agent runs, check followUp message after _process_message() is done
@@ -173,6 +304,7 @@ julia> # Currently returns a placeholder echo response
```
"""
function _process_message(agent::yiemAgent)::assistantMessage
agent.agentEventSink("_process_message 1")
# loop until llmCall() response didn't use tool calls
final_response = nothing
while true
@@ -185,21 +317,26 @@ function _process_message(agent::yiemAgent)::assistantMessage
Dict(
"type" => "image_url",
"image_url" => Dict("url" => "data:mime_type;base64,image2_base64_string")
)
),
]
),
)
"""
# Drain inputChannel and convert OpenAI-format messages to userMessage type
while isready(agent.inputChannel)
agent.agentEventSink("_process_message 2")
raw_msg = take!(agent.inputChannel)
agent.agentEventSink("_process_message 3")
if raw_msg === :shutdown
agent.agentEventSink("_process_message 4")
# Re-emit shutdown signal for the loop to handle
put!(agent.inputChannel, :shutdown)
break
end
agent.agentEventSink("_process_message 5")
user_msg = OpenAiToUserMessage(raw_msg)
push!(agent._state.messages, user_msg)
agent.agentEventSink("_process_message 6")
end
# call agent.prepareContext()
@@ -208,10 +345,11 @@ function _process_message(agent::yiemAgent)::assistantMessage
# Call agent.formatMsgForLLM(agent._state) to format for LLM
formatted_messages = agent.formatMsgForLLM(preparedContext)
agent.agentEventSink("_process_message 7")
# Call llmCall() (blocking — the task waits here)
error("debug marker")
response = agent.llmCall(formatted_messages)
error(5555555)
agent.agentEventSink("_process_message 8")
#WORKING Check if LLM used tool calls (inspect content for tool_call blocks)
has_tool_calls = false
@@ -509,41 +647,42 @@ prepareToolCall(context, msg, tc, config, abortedSignal)
```
"""
function prepareToolCall(
context::agentContext,
assistantMsg::assistantMessage,
toolCall::agentToolCall,
config::agentLoopConfig,
signal::Union{Nothing, abortSignal},
context::agentContext,
assistantMsg::assistantMessage,
toolCall::agentToolCall,
config::agentLoopConfig,
signal::Union{Nothing, abortSignal},
)::Union{preparedToolCall,immediateOutcome}
tool = find(t -> t.name == toolCall.name, context.tools)
if tool === nothing
return immediateOutcome(createErrorToolResult("Tool $toolCall.name not found"), true)
tool = get(context.tools, toolCall.name, nothing)
if tool === nothing
return immediateOutcome(createErrorToolResult("Tool $toolCall.name not found"), true)
end
try
# 1. prepare arguments (tool-specific transform)
prepared = prepareToolCallArguments(tool, toolCall)
validatedArgs = validateToolArguments(tool, prepared)
# 2. beforeToolCall hook — can block
if config.beforeToolCall !== nothing
before = config.beforeToolCall(
beforeToolCallContext(assistantMsg, toolCall, validatedArgs, context),
signal
)
if signal !== nothing && signal.aborted
return immediateOutcome(createErrorToolResult("Operation aborted"), true)
end
if before !== nothing && before.block
return immediateOutcome(
createErrorToolResult(get(before, :reason, "Tool execution was blocked")), true)
end
end
try
# 1. prepare arguments (tool-specific transform)
prepared = prepareToolCallArguments(tool, toolCall)
validatedArgs = validateToolArguments(tool, prepared)
# 2. beforeToolCall hook — can block
if config.beforeToolCall !== nothing
before = config.beforeToolCall(
assistantMsgCtx(assistantMsg, toolCall, validatedArgs, context), signal
)
if signal !== nothing && signal.aborted
return immediateOutcome(createErrorToolResult("Operation aborted"), true)
end
if before !== nothing && before.block
return immediateOutcome(
createErrorToolResult(get(before, :reason, "Tool execution was blocked")), true)
end
end
return preparedToolCall(tool, toolCall, validatedArgs)
catch err
return immediateOutcome(createErrorToolResult(sprint(showerror, err)), true)
end
return preparedToolCall(tool, toolCall, validatedArgs)
catch err
return immediateOutcome(createErrorToolResult(sprint(showerror, err)), true)
end
end
# ── per-call execution ──────────────────────────────────────────
@@ -681,61 +820,28 @@ function finalizeExecutedToolCall(
signal::Union{Nothing,abortSignal},
)::finalizedOutcome
result = executed.result
isError = executed.isError
result = executed.result
isError = executed.isError
if config.afterToolCall !== nothing
try
after = config.afterToolCall(
afterCtx(assistantMsg, prep.toolCall, prep.args, result, isError, context), signal
)
if after !== nothing
result = merge(result, dict(:content=>get(after,:content,result.content),
:details=>get(after,:details,result.details),
:usage=>get(after,:usage,result.usage),
:terminate=>get(after,:terminate,result.terminate)))
isError = get(after, :isError, isError)
end
catch err
result = createErrorToolResult(sprint(showerror, err))
isError = true
end
if config.afterToolCall !== nothing
try
after = config.afterToolCall(
afterToolCallContext(assistantMsg, prep.toolCall, prep.args, result, isError, context), signal
)
if after !== nothing
result = merge(result, dict(:content=>get(after,:content,result.content),
:details=>get(after,:details,result.details),
:usage=>get(after,:usage,result.usage),
:terminate=>get(after,:terminate,result.terminate)))
isError = get(after, :isError, isError)
end
catch err
result = createErrorToolResult(sprint(showerror, err))
isError = true
end
end
return finalizedOutcome(prep.toolCall, result, isError)
end
"""
emitToolExecutionEnd(finalized, emit)
Emits the `toolExecutionEnd` event with the finalized outcome,
signalling to listeners that the tool call has completed.
This event is part of the tool execution lifecycle:
`toolExecutionStart` → (zero or more `toolExecutionUpdate` events) →
`toolExecutionEnd`. Listeners (such as the TUI or logging systems)
use this lifecycle to track individual tool calls. The event carries
the final result so listeners have all the data they need without
requiring external state lookups.
# Arguments
- `finalized::finalizedOutcome`: The finalized outcome to report
- `emit::Function`: Event emitter
# Notes
- Part of a three-event lifecycle per tool call
- Carries the complete result so listeners need no external lookups
# Examples
```julia
# Emits a single event; returns nothing
emitToolExecutionEnd(finalized, emit)
# (emit receives toolExecEndEvent("call_1", "search_wine", result, false))
```
"""
function emitToolExecutionEnd(finalized::finalizedOutcome, emit::Function)
emit(toolExecEndEvent(finalized.toolCall.id, finalized.toolCall.name,
finalized.result, finalized.isError))
return finalizedOutcome(prep.toolCall, result, isError)
end
# ── sequential execution ────────────────────────────────────────
@@ -816,7 +922,8 @@ function executeToolCallsSequential(
finalized = finalizeExecutedToolCall(context, assistantMsg, prep, executed, config, signal)
end
emitToolExecutionEnd(finalized, emit)
emit(toolExecEndEvent(finalized.toolCall.id, finalized.toolCall.name,
finalized.result, finalized.isError))
push!(messages, createToolResultMessage(finalized))
push!(finalizedCalls, finalized)
@@ -903,13 +1010,15 @@ function executeToolCallsParallel(
if prep isa immediateOutcome
finalized = finalizedOutcome(tc, prep.result, prep.isError)
emitToolExecutionEnd(finalized, emit)
emit(toolExecEndEvent(finalized.toolCall.id, finalized.toolCall.name,
finalized.result, finalized.isError))
push!(entries, finalized)
else
task = task() do
executed = executePreparedToolCall(prep, signal, emit)
finalized = finalizeExecutedToolCall(context, assistantMsg, prep, executed, config, signal)
emitToolExecutionEnd(finalized, emit)
emit(toolExecEndEvent(finalized.toolCall.id, finalized.toolCall.name,
finalized.result, finalized.isError))
return finalized
end
schedule(task)
@@ -996,13 +1105,9 @@ function executeToolCalls(
hasSequential = false
for tc in toolCalls
for t in context.tools
if t.name == tc.name && !t.parallelToolExecute
hasSequential = true
break
end
end
if hasSequential
t = get(context.tools, tc.name, nothing)
if t !== nothing && !t.parallelToolExecute
hasSequential = true
break
end
end
+15 -16
View File
@@ -3,14 +3,13 @@ module api
export prompt
using JSON, DataStructures, Dates, UUIDs, HTTP, Random, PrettyPrinting, Serialization,
DataFrames, Serde
DataFrames
using GeneralUtils
using ..type, ..utils
using ..type, ..utils, ..agentCore, ..toolRegistry
# ---------------------------------------------- 100 --------------------------------------------- #
"""
Send a message to the agent's input channel.
@@ -25,16 +24,16 @@ The agent processes messages from `inputChannel` in the background task.
- The same `agent` instance for chaining
# Notes
- Use `take_response(agent)` to receive the agent's response after sending a message.
- Use `follow_up(agent, msg)` to send messages while the agent is still processing.
- Use `takeResponse(agent)` to receive the agent's response after sending a message.
- Use `followUp(agent, msg)` to send messages while the agent is still processing.
# Examples
```jldoctest
julia> run_agent(agent, "Hello!")
julia> runAgent(agent, "Hello!")
yiemAgent(...)
```
"""
function run_agent(agent::yiemAgent, msg)
function runAgent(agent::yiemAgent, msg)
put!(agent.inputChannel, msg)
return agent
end
@@ -51,15 +50,15 @@ Blocks until the agent sends a response.
- An `assistantMessage` instance representing the agent's response
# Notes
- Use `run_agent(agent, msg)` to send a message before calling this function.
- Use `runAgent(agent, msg)` to send a message before calling this function.
# Examples
```jldoctest
julia> response = take_response(agent)
julia> response = takeResponse(agent)
assistantMessage(...)
```
"""
function take_response(agent::yiemAgent)
function takeResponse(agent::yiemAgent)
return take!(agent.outputChannel)
end
@@ -77,17 +76,17 @@ and before any tool call results are sent.
- The same `agent` instance for chaining
# Notes
- Use `run_agent(agent, msg)` for the primary message and `follow_up(agent, msg)` for additional
- Use `runAgent(agent, msg)` for the primary message and `followUp(agent, msg)` for additional
messages while the agent is processing.
- Follow-up messages are buffered in a separate channel (capacity 32 by default).
# Examples
```jldoctest
julia> follow_up(agent, "Also consider red wines")
julia> followUp(agent, "Also consider red wines")
yiemAgent(...)
```
"""
function follow_up(agent::yiemAgent, msg)
function followUp(agent::yiemAgent, msg)
put!(agent.followUpChannel, msg)
return agent
end
@@ -105,16 +104,16 @@ then closes all channels (`inputChannel`, `outputChannel`, `followUpChannel`).
- `nothing`
# Notes
- After calling `stop_agent`, the agent is no longer usable. A new agent must be created
- After calling `stopAgent`, the agent is no longer usable. A new agent must be created
for further interaction.
- If the background task throws a `TaskFailedException`, it is rethrown.
# Examples
```jldoctest
julia> stop_agent(agent)
julia> stopAgent(agent)
```
"""
function stop_agent(agent::yiemAgent)
function stopAgent(agent::yiemAgent)
put!(agent.inputChannel, :shutdown)
try
fetch(agent._agent_loop)
+271
View File
@@ -0,0 +1,271 @@
module toolRegistry
export toolStore, loadTools, registerTool, getTools, clearTools, listTool
using Dates
using JSON, DataStructures
using ..type
"""
Per-agent isolated tool storage.
Each agent gets its own `toolStore` so tool registration is independent —
`registerTool(store, tool)` only affects that agent's tool set.
# Fields
- `tools::OrderedDict{String, agentTool}` — keyed by name for O(1) lookup + ordered iteration
- `name::String` — identifier for debugging/logs
"""
struct toolStore
tools::OrderedDict{String, agentTool}
name::String
end
"""
toolStore(; name="default") -> toolStore
Create a new empty tool store.
# Keyword Arguments
- `name::String`: Display name for logging (default: `"default"`)
# Example
```julia
julia> store = toolStore(name="agent1")
toolStore(OrderedDict{String, agentTool}(), "agent1")
```
"""
function toolStore(; name::String="default")::toolStore
toolStore(OrderedDict{String, agentTool}(), name)
end
"""
listTool(store::toolStore) -> agentTool
Return an `agentTool` definition for listing registered tools.
Each call produces a **new** tool object that captures (closes over)
`store`. `loadTools` auto-registers one so the LLM can discover tools
at runtime.
# Arguments
- `store`: The tool store whose tools will be listed when the tool runs
# Example
```julia
julia> store = toolStore(name="agent1");
julia> loadTools(store, "src/tools") # auto-registers listTools
[toolRegistry:agent1] Loaded tool: getWeather (Weather Lookup)
[toolRegistry:agent1] Registered tool: listTools
julia> tools = getTools(store)
OrderedDict{String, agentTool} with 4 entries:
"getWeather" => agentTool(...)
"getTime" => agentTool(...)
"writeTool" => agentTool(...)
"listTools" => agentTool(...)
```
"""
function listTool(store::toolStore)::agentTool
return agentTool(
name = "listTools",
label = "List Tools",
description = "List all available tools with their names, labels, and descriptions. Use this before creating a new tool to check for name collisions.",
inputSchema = Dict{String,Any}(
"type" => "object",
"properties" => Dict{String,Any}(),
"required" => Any[]
),
execute = (toolCallId, args, signal, onPartialResult) -> begin
tools = getTools(store)
if isempty(tools)
result_text = "No tools registered."
else
lines = String["- $(t.name): $(t.label)$(t.description)" for (k, t) in tools]
result_text = "Available tools:\n" * join(lines, "\n")
end
return agentToolResult(
[textContent(result_text)],
Dict{Any,Any}("count" => length(tools)),
nothing, false
)
end,
prepareArguments = nothing,
validateRequiredArgs = nothing,
parallelToolExecute = false
)
end
"""
Load `.jl` tool files from `dir` into `store`, then auto-register
`listTool` so the LLM can discover available tools at runtime.
Each `.jl` file must define `function getTool()::agentTool ... end`.
Files are sorted alphabetically for deterministic registration order.
Each file is loaded into its own Julia submodule to avoid name collisions.
# Arguments
- `store`: Tool store to populate
- `dir`: Directory containing `.jl` tool files
# Returns
- The same `store.tools` dict (modified in place)
# Errors
- Throws `ArgumentError` if `dir` does not exist or a file lacks `getTool()`
# Example
```julia
julia> store = toolStore(name="agent1");
julia> loadTools(store, "src/tools")
[toolRegistry:agent1] Loaded tool: getWeather (Weather Lookup)
[toolRegistry:agent1] Loaded tool: getTime (Time Lookup)
[toolRegistry:agent1] Registered tool: listTools
OrderedDict{String, agentTool} with 3 entries:
"getWeather" => agentTool(...)
"getTime" => agentTool(...)
"listTools" => agentTool(...)
```
"""
function loadTools(store::toolStore, dir::String)::OrderedDict{String, agentTool}
if !isdir(dir)
throw(ArgumentError("Tool directory does not exist: $dir"))
end
jl_files = filter(f -> endswith(f, ".jl") && !occursin(r"(?i)registry", f), readdir(dir))
sort!(jl_files)
for filename in jl_files
filepath = joinpath(dir, filename)
# Derive a unique module name from the filename only (not full path).
# e.g. "getWeather.jl" -> "_tool_getWeather"
mod_name = Symbol("_tool_", replace(rstrip(filename, '.'), ".jl" => ""))
# Build the complete module as a string and eval the parsed code.
# Julia does not allow `module ... end` inside eval(quote ...),
# and constructing the module AST by hand is fragile.
# Instead, we generate the full module source as a string,
# parse it, and eval the resulting expression.
# Each tool file declares its own dependencies via `using` statements
# at the top of the file — the registry only injects `using ..type`
# to make core types (agentTool, textContent, etc.) available.
file_content = read(filepath, String)
module_code = """
module $(mod_name)
using ..type
$(file_content)
end
"""
mod = eval(Meta.parse(module_code))
# Call getTool() via Core.eval in the submodule's scope.
# This evaluates getTool() entirely within the new module's world,
# completely avoiding world-age issues — no invokelatest needed.
# Note: all uses of `tool` must be inside the `try` block because
# Julia 1.12's SSA form doesn't track `tool` as definitely assigned
# after a `try-catch` where it's only assigned inside `try`.
try
tool = Core.eval(mod, :(getTool()))
if !(tool isa agentTool)
throw(ArgumentError(
"getTool() in $(filepath) did not return an agentTool instance, got: $(typeof(tool))"
))
end
store.tools[tool.name] = tool
println("[$(store.name)] Loaded tool: $(tool.name) ($(tool.label))")
catch e
if e isa UndefVarError || occursin("getTool", sprint(showerror, e))
throw(ArgumentError(
"Tool file $(filepath) does not define a `getTool()` function in module $(mod_name). " *
"Each tool file must define: function getTool()::agentTool ... end"
))
end
rethrow(e)
end
end
registerTool(store, listTool(store))
return store.tools
end
"""
registerTool(store::toolStore, tool::agentTool) -> OrderedDict{String, agentTool}
Add `tool` to `store`, overwriting any existing tool with the same name.
# Arguments
- `store`: Tool store to modify
- `tool`: The `agentTool` to register
# Returns
- The same `store.tools` dict (modified in place)
# Example
```julia
julia> store = toolStore(name="agent1");
julia> registerTool(store, listTool(store))
[toolRegistry:agent1] Registered tool: listTools
OrderedDict{String, agentTool} with 1 entry:
"listTools" => agentTool(...)
```
"""
function registerTool(store::toolStore, tool::agentTool)::OrderedDict{String, agentTool}
store.tools[tool.name] = tool
println("[$(store.name)] Registered tool: $(tool.name)")
return store.tools
end
"""
Return the tools registered in `store`.
The returned dict is the **same object** stored inside `store` — mutations
to it (e.g. via `registerTool`) are visible through subsequent calls.
# Arguments
- `store`: Tool store to query
# Returns
- `OrderedDict{String, agentTool}`: Tools keyed by name, in registration order
# Example
```julia
julia> tools = getTools(store)
OrderedDict{String, agentTool} with 2 entries:
"getWeather" => agentTool(...)
"getTime" => agentTool(...)
```
"""
function getTools(store::toolStore)::OrderedDict{String, agentTool}
return store.tools
end
"""
Remove all tools from `store`.
# Arguments
- `store`: Tool store to clear
# Returns
- `nothing`
# Example
```julia
julia> clearTools(store)
[toolRegistry:agent1] Registry cleared
nothing
julia> getTools(store)
OrderedDict{String, agentTool} with 0 entries
```
"""
function clearTools(store::toolStore)::Nothing
empty!(store.tools)
println("[$(store.name)] Registry cleared")
return nothing
end
end # module
-568
View File
@@ -1,568 +0,0 @@
# Tools
Tools allow the agent to perform actions and fetch data. Each tool defines a **schema** (what arguments it accepts) and an **execution function** (what it does).
## Quick Start
Add a new tool by creating a `.jl` file in `src/tools/`. The file must define a `getTool()` function that returns an `agentTool`:
```julia
# src/tools/my_tool.jl
function executeTool(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal}, onPartialResult::Function)::agentToolResult
city = args["city"]
return agentToolResult(
[textContent("Hello from $(city)!")],
Dict{Any,Any}(), nothing, false
)
end
function getTool()::agentTool
return agentTool(
name = "my_tool",
label = "My Tool",
description = "Says hello to a city.",
inputSchema = Dict{String,Any}(
"type" => "object",
"properties" => Dict(
"city" => Dict("type" => "string", "description" => "City name")
),
"required" => ["city"]
),
execute = executeTool,
prepareArguments = nothing,
validateRequiredArgs = nothing,
parallelToolExecute = false
)
end
```
When `loadTools()` or `registerTool()` is called, the tool becomes available to the agent.
## Tool Anatomy
Each tool has 3 main parts:
### 1. Schema (`inputSchema`)
JSON Schema (MCP format) describing the tool's arguments. The `"required"` array lists mandatory fields:
```julia
inputSchema = Dict{String,Any}(
"type" => "object",
"properties" => Dict(
"city" => Dict("type" => "string", "description" => "City name"),
"units" => Dict("type" => "string", "enum" => ["celsius", "fahrenheit"], "default" => "celsius")
),
"required" => ["city"]
)
```
### 2. Execution Function (`execute`)
A function with the signature:
```julia
execute(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal}, onPartialResult::Function)::agentToolResult
```
- **`toolCallId`** — unique ID for this invocation (from the LLM's tool call)
- **`args`** — validated arguments provided by the LLM
- **`signal`** — abort signal for cancellable operations
- **`onPartialResult`** — callback for streaming progress updates
- **Returns** — `agentToolResult` with content, details, usage, and termination flag
```julia
function executeTool(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal}, onPartialResult::Function)::agentToolResult
# Optional: stream progress updates
onPartialResult(Dict("status" => "Fetching data..."))
# Do work
result = "Weather in $(args["city"]): Sunny, 22°C"
# Return result
return agentToolResult(
[textContent(result)],
Dict{Any,Any}(), # details
nothing, # usage
false # terminate (true to stop agent loop)
)
end
```
### 3. Tool Definition (`getTool()`)
Returns an `agentTool` struct:
| Field | Type | Description |
|---|---|---|
| `name` | `String` | Unique identifier (e.g. `"getWeather"`) |
| `label` | `String` | Human-readable name (e.g. `"Weather Lookup"`) |
| `description` | `String` | What the tool does (shown to the LLM) |
| `inputSchema` | `Any` | JSON Schema (MCP format) |
| `execute` | `Function` | The execution function |
| `prepareArguments` | `Union{Function,Nothing}` | Optional argument transform before validation |
| `validateRequiredArgs` | `Union{Function,Nothing}` | Optional custom validation |
| `parallelToolExecute` | `Bool` | Run this tool in parallel with others |
## Argument Validation
Validation happens **before** tool execution, in the `prepareToolCall` phase. Invalid calls return an error immediately without invoking `execute`, `beforeToolCall`, or logging `toolExecutionStart`.
### Default: JSON Schema Required Fields
Set `validateRequiredArgs = nothing` to use the default validator, which checks that all fields in `inputSchema["required"]` are present:
```julia
# src/tools/getWeather.jl — uses default validation
function getTool()::agentTool
return agentTool(
name = "getWeather",
# ...
validateRequiredArgs = nothing, # uses default
)
end
```
### Custom Validation Hook
Override `validateRequiredArgs` when you need:
- **Cross-field constraints** (e.g. "at least one of X or Y")
- **Format validation** (e.g. regex patterns, date parsing)
- **Domain rules** (e.g. value ranges, business logic)
The hook signature takes only `args`:
```julia
function validateRequiredArgs(args::Dict{String,Any})::Union{Nothing,String}
tz = get(args, "timezone", nothing)
city = get(args, "city", "")
if !haskey(args, "timezone") && isempty(city)
return "Missing required argument: provide at least one of 'timezone' or 'city'"
end
if tz !== nothing
tz_str = string(tz)
if !occursin(r"^[A-Za-z]+\/[A-Za-z]+(/[A-Za-z]+)*$", tz_str)
return "Invalid timezone format: '$tz_str'. Use IANA format, e.g. 'America/New_York'"
end
end
return nothing
end
```
Return `nothing` to pass, or an error `String` to fail. The error is fed back to the LLM so it can retry with corrected arguments.
## Tool Lifecycle — Framework Internals
This section traces the full code path from the moment the LLM returns tool calls to the final result being fed back into the conversation. All code references are to `agentCore.jl`.
### Phase 1: Detect Tool Calls in LLM Response
After the LLM returns an `assistantMessage`, the loop at `agentCore.jl:220-244` inspects each `content` block:
```julia
# agentCore.jl:217-244
has_tool_calls = false
tool_call_list = agentToolCall[]
for content_block in response.content
if content_block isa Dict
# OpenAI-style: type == "tool_calls" with array of tool calls
if get(content_block, :type, "") == "tool_calls"
for tc_data in get(content_block, :tool_calls, [])
tc = agentToolCall(
type="function",
id=get(tc_data, :id, string(uuid4())),
name=get(tc_data, :function, Dict{String,Any}())[:name],
arguments=get(tc_data, :function, Dict{String,Any}())[:arguments],
)
push!(tool_call_list, tc)
end
# Alternative style: type == "tool_call" single dict per block
elseif get(content_block, :type, "") == "tool_call"
tc = agentToolCall(
type="function",
id=get(tc_data, :id, string(uuid4())),
name=get(tc_data, :name, ""),
arguments=get(tc_data, :arguments, Dict{String,Any}()),
)
push!(tool_call_list, tc)
end
end
end
```
Each content block with `type == "tool_calls"` or `type == "tool_call"` extracts an `agentToolCall` (id, name, arguments dict) and collects them into a `Vector{agentToolCall}`.
### Phase 2: Dispatch to Sequential or Parallel Execution
At `agentCore.jl:247`, the framework checks if any tool calls exist and decides execution mode:
```julia
# agentCore.jl:247-265
context = agentContext(agent._state.systemPrompt, agent._state.messages, agent._state.tools)
config = agentLoopConfig(
agent._state.tools,
agent.beforeToolCall,
agent.afterToolCall,
agent.parallelToolExecute ? "parallel" : "sequential",
)
batch = executeToolCalls(context, response, tool_call_list, config, signal, emit)
```
`executeToolCalls` (`agentCore.jl:988-1015`) checks:
- `config.toolExecution == "sequential"` → sequential mode
- Any tool has `parallelToolExecute == false` → sequential mode
- Otherwise → parallel mode
### Phase 3: Per-Call Preparation (`prepareToolCall`)
Each tool call goes through `prepareToolCall` (`agentCore.jl:511-547`):
```
1. Look up tool by name: find(t -> t.name == tc.name, context.tools)
2. If not found → immediateOutcome("Tool X not found", true)
3. Run tool.prepareArguments (if defined) → transforms raw LLM args
4. Run validateToolArguments → validateRequiredArgs (hook or default)
→ if fails → throws ArgumentError → caught below
5. Run beforeToolCall hook (if defined) → can block execution
→ if blocked → immediateOutcome("Tool execution was blocked", true)
6. Return preparedToolCall(tool, tc, validatedArgs)
```
If any step throws (validation, prepareArguments, beforeToolCall), the catch block at `agentCore.jl:545` converts it to an `immediateOutcome`:
```julia
catch err
return immediateOutcome(createErrorToolResult(sprint(showerror, err)), true)
end
```
### Phase 4: Execution (`executePreparedToolCall`)
For each `preparedToolCall`, `executePreparedToolCall` (`agentCore.jl:589-617`) runs:
```julia
function executePreparedToolCall(prep::preparedToolCall, signal, emit)::executedOutcome
updateEvents = promise[]
accepting = true
try
result = prep.tool.execute(
prep.toolCall.id, prep.args, signal,
partialResult -> begin
if accepting
push!(updateEvents, emit(toolExecUpdateEvent(..., partialResult)))
end
end
)
accepting = false
wait.(updateEvents)
return executedOutcome(result, false)
catch err
accepting = false
wait.(updateEvents)
return executedOutcome(createErrorToolResult(sprint(showerror, err)), true)
end
end
```
Key behaviors:
- Calls `tool.execute(id, args, signal, onPartialResult)` — your tool's `executeTool` function
- `signal` can be checked inside `executeTool` for cancellation
- `onPartialResult` is called for streaming updates, which are emitted as `toolExecutionUpdate` events
- `accepting` guard prevents emitting updates after the result is already captured
- `wait.(updateEvents)` ensures all streaming updates are delivered before returning
- Execution errors are caught and returned as `executedOutcome(isError=true)` — never thrown
### Phase 5: Finalization (`finalizeExecutedToolCall`)
After execution, `finalizeExecutedToolCall` (`agentCore.jl:675-706`) runs the `afterToolCall` hook:
```julia
function finalizeExecutedToolCall(context, assistantMsg, prep, executed, config, signal)::finalizedOutcome
result = executed.result
isError = executed.isError
if config.afterToolCall !== nothing
try
after = config.afterToolCall(afterCtx(assistantMsg, prep.toolCall, prep.args, result, isError, context), signal)
if after !== nothing
# Hook can mutate: content, details, usage, terminate, isError
result = merge(result, dict(...))
isError = get(after, :isError, isError)
end
catch err
result = createErrorToolResult(sprint(showerror, err))
isError = true
end
end
return finalizedOutcome(prep.toolCall, result, isError)
end
```
The hook can:
- Mask sensitive data from result content
- Normalize usage tracking
- Flip `terminate: true` based on business logic
- Wrap errors in friendlier messages for the LLM
If the hook itself throws, the error is caught and converted to an error outcome.
### Phase 6: Emit Events and Create Result Message
Each call emits `toolExecutionEnd`:
```julia
function emitToolExecutionEnd(finalized::finalizedOutcome, emit::Function)
emit(toolExecEndEvent(finalized.toolCall.id, finalized.toolCall.name, finalized.result, finalized.isError))
end
```
Then creates the `toolResultMessage` for conversation history (`agentCore.jl:373-379`):
```julia
function createToolResultMessage(f::finalizedOutcome)::toolResultMessage
return toolResultMessage(
"toolResult", f.toolCall.id, f.toolCall.name,
f.result.content, f.result.details, f.result.usage,
get(f.result, :addedToolNames, string[]), f.isError, nowMillis()
)
end
```
### Phase 7: Batch Assembly and Loop Control
In `executeToolCallsSequential` (`agentCore.jl:795-829`) or `executeToolCallsParallel` (`agentCore.jl:888-936`), all results are collected:
```julia
messages = toolResultMessage[]
for finalized in finalizedCalls
push!(messages, createToolResultMessage(finalized))
end
return agentToolCallBatch(messages, shouldTerminate(finalizedCalls))
```
`shouldTerminate` (`agentCore.jl:409`) returns `true` only if ALL tools in the batch set `result.terminate == true`. If `false`, the agent loop at `agentCore.jl:176-308` feeds the tool results back to the LLM for another turn.
### Data Flow Summary
```
response.content (Vector{Any})
└── phase 1: parse content blocks
└── tool_call_list :: Vector{agentToolCall}
└── phase 2: dispatch to sequential/parallel
└── phase 3: prepareToolCall
└── preparedToolCall or immediateOutcome
└── phase 4: executePreparedToolCall
└── executedOutcome
└── phase 5: finalizeExecutedToolCall
└── finalizedOutcome
└── phase 6: createToolResultMessage
└── toolResultMessage
└── phase 7: agentToolCallBatch
└── pushed to agent._state.messages
└── loop back to LLM
```
## Execution Modes
### Sequential
Tools execute one at a time in order. Required when:
- Tools have implicit dependencies
- Tools share state (e.g. writing to the same file)
- Tools have `parallelToolExecute = false`
Set globally via `agentLoopConfig.toolExecution = "sequential"`, or per-tool via `parallelToolExecute = false`.
### Parallel
Tools execute concurrently when all are independent. Reduces wall-clock time. Set `parallelToolExecute = true` on individual tools, or set `agentLoopConfig.toolExecution = "parallel"`.
## Streaming Partial Results
For long-running tools (API calls, file uploads, training), use `onPartialResult` to stream progress:
```julia
function executeTool(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal}, onPartialResult::Function)::agentToolResult
onPartialResult(Dict("status" => "Step 1: Fetching data..."))
sleep(1)
onPartialResult(Dict("status" => "Step 2: Processing..."))
sleep(1)
return agentToolResult(
[textContent("Done!")],
Dict{Any,Any}(), nothing, false
)
end
```
UI listeners and the TUI consume these events in real time via `toolExecutionUpdate`.
## Loading Tools
### Auto-load from Directory
```julia
using .toolRegistry
tools = loadTools("src/tools") # scans for *.jl files with getTool()
```
Files are loaded alphabetically for deterministic registration order.
### Manual Registration
```julia
tool = getTool() # from your tool module
registerTool(tool)
```
## Using Tools with an Agent
Loading tools only registers them — you must pass them to the `yiemAgent` and provide an `llmCall` function. Here is the complete flow:
```julia
using .YiemAgent
using .toolRegistry
# 1. Load tools from the tools directory
tools = loadTools("src/tools")
# [toolRegistry] Loading tool from: src/tools/getTime.jl
# [toolRegistry] Loaded tool: getTime — Time Lookup
# [toolRegistry] Loading tool from: src/tools/getWeather.jl
# [toolRegistry] Loaded tool: getWeather — Weather Lookup
# 2. Define your LLM call function
function my_llm_call(messages::Dict)::assistantMessage
# Call your LLM API here (OpenAI, Anthropic, local model, etc.)
# Return an assistantMessage with the response content
# If the LLM wants to call a tool, include tool_call content blocks
...
end
# 3. Define your event sink (optional, for logging/debugging)
function my_event_sink(event)
if event isa toolExecStartEvent
println("[EVENT] Tool start: $(event.toolName)")
elseif event isa toolExecEndEvent
status = event.isError ? "ERROR" : "OK"
println("[EVENT] Tool end: $(event.toolName)$status")
end
end
# 4. Create the agent with tools
agent = yiemAgent(
systemPrompt = "You are a helpful assistant that can check weather and time.",
model = my_model,
tools = tools, # pass loaded tools
llmCall = my_llm_call, # your LLM function
agentEventSink = my_event_sink, # event handler
)
# 5. Send a message and get a response
run_agent(agent, "What's the weather in Tokyo?")
response = take_response(agent)
# response.content contains the LLM's reply (with tool results if applicable)
println(response.content)
# 6. When done, stop the agent
stop_agent(agent)
```
### How It Works
1. **User sends a message** via `run_agent(agent, "What's the weather in Tokyo?")`. The message goes into `inputChannel`.
2. **Agent loop** (`_agent_loop`) picks it up, converts it to a `userMessage`, and adds it to `agent._state.messages`.
3. **LLM is called** via `agent.llmCall(formatted_messages)`. The LLM sees the system prompt, conversation history, and the tool definitions in the prompt (via `formatMsgForLLM`).
4. **If the LLM uses a tool**, it returns a response with `tool_call` content blocks. The agent:
- Extracts each tool call (name, arguments)
- Runs validation (`validateRequiredArgs` or default)
- Executes the tool (or returns an error if validation fails)
- Feeds the result back as a `toolResultMessage` in the conversation
5. **LLM is called again** with the tool results. This repeats until the LLM returns a text response with no tool calls.
6. **Final response** is sent to `outputChannel` — retrieve it with `take_response(agent)`.
### Minimal Working Example
```julia
using .YiemAgent
using .toolRegistry
# Load tools
tools = loadTools("src/tools")
# Mock LLM that echoes back a tool call, then a text response
call_count = 0
function mock_llm_call(messages::Dict)::assistantMessage
global call_count += 1
if call_count == 1
# First call: LLM decides to use getWeather
return assistantMessage(
content=[
Dict("type" => "tool_calls",
"tool_calls" => [Dict("id" => "call_1", "name" => "getWeather",
"arguments" => Dict("city" => "Tokyo"))])
],
model = "mock",
usage = llmUsage(0, 0)
)
else
# Second call: LLM returns text (after tool result)
return assistantMessage(
content = [textContent("The weather in Tokyo is sunny, 22°C.")],
model = "mock",
usage = llmUsage(0, 0)
)
end
end
# Create agent
agent = yiemAgent(
systemPrompt = "You are a helpful assistant.",
tools = tools,
llmCall = mock_llm_call,
agentEventSink = e -> nothing, # no events
)
# Run
run_agent(agent, "What's the weather in Tokyo?")
response = take_response(agent)
stop_agent(agent)
```
## Available Tools
| Tool | Description | Validation |
|---|---|---|
| `getWeather` | Fetch weather for a city | Default (JSON Schema required) |
| `getTime` | Get current time for a timezone or city | Custom (cross-field + format) |
## Example: Error Flow
When the LLM calls a tool with invalid arguments:
```
User: "What's the weather?"
└── LLM: call getWeather() with no arguments
└── prepareToolCall → validateRequiredArgs → "Missing required arguments: city"
└── immediateOutcome → error tool result
└── LLM sees: "Missing required arguments: city"
└── LLM retries: call getWeather(city="Tokyo")
└── executeTool → "Weather in Tokyo: Sunny, 22°C"
```
The agent feeds the error back to the LLM as a tool result message, allowing it to self-correct.
+7 -14
View File
@@ -1,3 +1,5 @@
using Dates
"""
Validate required arguments for the getTime tool.
@@ -39,26 +41,17 @@ end
"""
Execute the getTime tool.
# Arguments
- `toolCallId::String`: Unique identifier for this tool call
- `args::Dict{String,Any}`: Parsed arguments from the LLM
- `signal::Union{Nothing,abortSignal}`: Optional abort signal
- `onPartialResult::Function`: Callback for streaming partial results
# Returns
- `agentToolResult`: Result content with current time data
Returns mock time data for the given timezone or city.
"""
function executeTool(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal}, onPartialResult::Function)::agentToolResult
function executeTool(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal},
onPartialResult::Function)::agentToolResult
tz = get(args, "timezone", nothing)
city = get(args, "city", "")
# Simulate time lookup — replace with actual timezone API call
if tz !== nothing
result = "Current time in $(tz): $(now())"
else
result = "Current time in $(city): $(now())"
end
return agentToolResult(
[textContent(result)],
Dict{Any,Any}(), nothing, false
@@ -76,8 +69,8 @@ function getTool()::agentTool
inputSchema = Dict{String,Any}(
"type" => "object",
"properties" => Dict(
"timezone" => Dict("type" => "string", "description", "IANA timezone, e.g. 'America/New_York'"),
"city" => Dict("type" => "string", "description", "City name as fallback")
"timezone" => Dict("type" => "string", "description" => "IANA timezone, e.g. 'America/New_York'"),
"city" => Dict("type" => "string", "description" => "City name as fallback")
),
"required" => []
),
+5 -18
View File
@@ -1,31 +1,18 @@
"""
Execute the getWeather tool.
# Arguments
- `toolCallId::String`: Unique identifier for this tool call
- `args::Dict{String,Any}`: Parsed arguments from the LLM
- `signal::Union{Nothing,abortSignal}`: Optional abort signal
- `onPartialResult::Function`: Callback for streaming partial results
# Returns
- `agentToolResult`: Result content with weather data
Returns mock weather data for the given city and temperature units.
"""
function executeTool(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal}, onPartialResult::Function)::agentToolResult
function executeTool(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal},
onPartialResult::Function)::agentToolResult
city = get(args, "city", "")
units = get(args, "units", "celsius")
# Simulate weather fetch — replace with actual API call
# You can call onPartialResult() here for streaming progress updates:
# onPartialResult(Dict("status" => "Fetching weather data..."))
# onPartialResult(Dict("status" => "Processing..."))
temp = units == "fahrenheit" ? "72" : "22"
unit_symbol = units == "celsius" ? "°C" : "°F"
return agentToolResult(
[textContent("Weather in $(city): Sunny, $(temp)$(unit_symbol)")],
Dict{Any,Any}(), nothing, false
)
)
end
"""
@@ -44,7 +31,7 @@ function getTool()::agentTool
),
"required" => ["city"]
),
execute = executeTool, # reference the function defined above
execute = executeTool,
prepareArguments = nothing,
validateRequiredArgs = nothing,
parallelToolExecute = false
-142
View File
@@ -1,142 +0,0 @@
module toolRegistry
export loadTools, registerTool, getTools, listTools, clearTools
using ..type
# Global registry — populated at runtime by loadTools() or registerTool()
const _registry = Vector{agentTool}()
"""
Load all tool modules from a directory.
Scans `dir` for `.jl` files. Each file must define a function named
`getTool()::agentTool`. Files are sorted alphabetically so tool
registration order is deterministic.
# Tool file format
Each `.jl` file defines one function `getTool()` that returns an `agentTool`:
```julia
# src/tools/getWeather.jl
function getTool()::agentTool
return agentTool(
name = "getWeather",
label = "Weather Lookup",
description = "Fetch current weather and forecast for a given city.",
inputSchema = Dict{String,Any}(
"type" => "object",
"properties" => Dict(
"city" => Dict("type" => "string", "description" => "City and country"),
"units" => Dict("type" => "string", "enum" => ["celsius", "fahrenheit"], "default" => "celsius")
),
"required" => ["city"]
),
execute = (toolCallId, args, signal, onPartialResult) -> begin
city = args["city"]
return agentToolResult(
[textContent("Sunny, 22C in $(city)")],
Dict{Any,Any}(), nothing, false
)
end,
prepareArguments = nothing,
parallelToolExecute = false
)
end
```
# Arguments
- `dir::String`: Directory path to scan for `.jl` tool files
# Returns
- `Vector{agentTool}`: All loaded tools
# Errors
- Throws `ArgumentError` if a tool file does not define a `getTool` function
"""
function loadTools(dir::String)::Vector{agentTool}
if !isdir(dir)
throw(ArgumentError("Tool directory does not exist: $dir"))
end
tools = agentTool[]
jl_files = filter(f -> endswith(f, ".jl"), readdir(dir))
sort!(jl_files)
for filename in jl_files
filepath = joinpath(dir, filename)
println("[toolRegistry] Loading tool from: $filepath")
# Include the file in the current module scope so all types resolve
# (agentTool, textContent, agentToolResult, etc. are all available)
include(filepath)
# Validate that getTool was defined (include() places it in current module scope)
if !isdefined(@__MODULE__, :getTool)
throw(ArgumentError(
"Tool file $(filepath) does not define a `getTool()` function. " *
"Each tool file must define: function getTool()::agentTool ... end"
))
end
# Call getTool() — it runs in current scope where types are visible
tool = getTool()
if !(tool isa agentTool)
throw(ArgumentError(
"getTool() in $(filepath) did not return an agentTool instance, got: $(typeof(tool))"
))
end
push!(_registry, tool)
push!(tools, tool)
println("[toolRegistry] Loaded tool: $(tool.name)$(tool.label)")
end
return tools
end
"""
Register a single agentTool into the global registry.
# Arguments
- `tool::agentTool`: The tool to register
# Returns
- `Vector{agentTool}`: Updated registry
"""
function registerTool(tool::agentTool)::Vector{agentTool}
push!(_registry, tool)
println("[toolRegistry] Registered tool: $(tool.name)")
return _registry
end
"""
Get all registered tools.
# Returns
- `Vector{agentTool}`: Copy of the registry
"""
function getTools()::Vector{agentTool}
return deepcopy(_registry)
end
"""
List all registered tool names and labels.
# Returns
- `Vector{Tuple{String,String}}`: Pairs of (name, label)
"""
function listTools()::Vector{Tuple{String,String}}
return [(t.name, t.label) for t in _registry]
end
"""
Clear all registered tools from the global registry.
"""
function clearTools()::Nothing
empty!(_registry)
println("[toolRegistry] Registry cleared")
return nothing
end
end # module
+273
View File
@@ -0,0 +1,273 @@
using JSON
"""
Tool that writes new Julia tool module files to disk.
The agent can use this tool when it encounters a task that no existing tool
can handle. Provide the tool's name, label, description, inputSchema, and
execute logic as Julia code. The tool is written to `src/tools/<name>.jl`.
After calling this tool, restart the agent so `loadTools(agent._tool_store, "src/tools")` picks
up the new file. The new tool is immediately available.
# Example
1. Agent calls writeTool with a spec for a "searchWine" tool
2. writeTool generates src/tools/searchWine.jl
3. Restart agent — loadTools() picks up the new file
4. Agent calls searchWine with args
# How It Works
writeTool is a **file writer**, not a code generator. The LLM provides the
tool logic as `executeCode`, and writeTool wraps it in Julia boilerplate:
- Converts `inputSchema` Dict into Julia `Dict{String,Any}(...)` string
- Indents `executeCode` with 4 spaces
- Wraps it inside `function executeTool(...)::agentToolResult ... end`
- Appends `getTool()` returning an `agentTool` struct
- Writes the combined string to `src/tools/<name>.jl`
# Important Notes
- The `executeCode` string is embedded literally into the generated tool.
Use `args["param_name"]` to access input parameters.
- The code string should be the function body (NOT wrapped in a function).
Lines will be indented with 4 spaces inside the execute function.
- Tool names must be valid Julia identifiers (lowercase letters, digits, underscores,
no leading digits or special characters).
"""
"""
Validate that a tool name is a valid Julia identifier.
"""
function validateToolName(name::String)::Union{Nothing,String}
if !occursin(r"^[a-zA-Z_][a-zA-Z0-9_!]*$", name)
return "Invalid tool name: '$name'. Tool names must be valid Julia identifiers (letters, digits, underscores, starting with a letter or underscore)."
end
return nothing
end
"""
Indent a multi-line code string by the specified number of spaces.
"""
function indent_code(code::String, n::Int)::String
prefix = " "^n
lines = split(code, '\n')
result_lines = String[prefix * line for line in lines]
return join(result_lines, "\n")
end
"""
Convert a Julia Dict to a valid Julia Dict{String,Any}(...) literal string.
"""
function dict_to_julia_literal(d)::String
if d isa Dict
items = String[]
for (k, v) in d
key_str = json_string(k)
val_str = value_to_julia(v)
push!(items, "$key_str => $val_str")
end
return "Dict{String,Any}(" * join(items, ", ") * ")"
else
return value_to_julia(d)
end
end
function value_to_julia(v)::String
if v isa Dict
return dict_to_julia_literal(v)
elseif v isa Vector
items = [value_to_julia(x) for x in v]
return "[" * join(items, ", ") * "]"
elseif v isa String
escaped = replace(v, "\\" => "\\\\")
escaped = replace(escaped, "\"" => "\\\"")
return "\"$escaped\""
elseif v isa Number
return string(v)
elseif v isa Bool
return string(v)
elseif v === nothing
return "nothing"
else
return "\"$(v)\""
end
end
"""
Convert any Julia value to a JSON string.
"""
function json_string(v)::String
return JSON.json(v)
end
"""
Define and return the writeTool agentTool.
"""
function getTool()::agentTool
return agentTool(
name = "writeTool",
label = "Create Tool",
description = "Write a new Julia tool module file to src/tools/<name>.jl. The LLM provides the tool logic as executeCode; writeTool wraps it in Julia boilerplate and writes the file. Restart the agent to load the new tool.",
inputSchema = Dict{String,Any}(
"type" => "object",
"properties" => Dict(
"name" => Dict("type" => "string", "description" => "Unique tool name (valid Julia identifier, no spaces or special chars)"),
"label" => Dict("type" => "string", "description" => "Human-readable tool name shown in tool descriptions"),
"description" => Dict("type" => "string", "description" => "What the tool does (shown to LLM for tool selection decisions)"),
"inputSchema" => Dict(
"type" => "object",
"description" => "JSON Schema describing tool parameters in MCP format"
),
"executeCode" => Dict("type" => "string", "description" => "Julia code for the execute function body. Use args[\"key\"] to access parameters. Do NOT wrap in a function definition."),
"validateCode" => Dict("type" => "string", "optional" => true, "description" => "Optional custom validation Julia code (runs before execute). Use args[\"key\"] to access parameters. Return nothing to pass, or a string error message to fail."),
"prepareCode" => Dict("type" => "string", "optional" => true, "description" => "Optional argument preparation code (runs before validation). Return modified args dict."),
"parallel" => Dict("type" => "boolean", "default" => false, "description" => "Whether this tool can run in parallel with other tools")
),
"required" => ["name", "label", "description", "inputSchema", "executeCode"]
),
execute = (toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal}, onPartialResult::Function) -> begin
tool_name = get(args, "name", "")::String
tool_label = get(args, "label", tool_name)::String
tool_description = get(args, "description", "")::String
tool_schema = get(args, "inputSchema", Dict{String,Any}())::Dict{String,Any}
execute_code = get(args, "executeCode", "")::String
validate_code = get(args, "validateCode", nothing)::Union{String,Nothing}
prepare_code = get(args, "prepareCode", nothing)::Union{String,Nothing}
parallel = get(args, "parallel", false)::Bool
# Validate tool name
name_err = validateToolName(tool_name)
if name_err !== nothing
return agentToolResult(
[textContent(name_err)],
Dict{Any,Any}(), nothing, false
)
end
# Validate required fields
if isempty(tool_name)
return agentToolResult(
[textContent("Missing required field: 'name'")],
Dict{Any,Any}(), nothing, false
)
end
if isempty(tool_description)
return agentToolResult(
[textContent("Missing required field: 'description'")],
Dict{Any,Any}(), nothing, false
)
end
if isempty(execute_code)
return agentToolResult(
[textContent("Missing required field: 'executeCode'")],
Dict{Any,Any}(), nothing, false
)
end
onPartialResult(Dict("status" => "Generating tool: $tool_name"))
# Build the tool file path
script_dir = dirname(@__FILE__)
tools_dir = dirname(script_dir)
filepath = joinpath(tools_dir, "$(tool_name).jl")
# Check for naming conflicts
if isfile(filepath)
return agentToolResult(
[textContent("Tool file already exists: $filepath. Rename the tool or delete the existing file first.")],
Dict{Any,Any}(), nothing, false
)
end
onPartialResult(Dict("status" => "Writing file: $(basename(filepath))"))
# Convert schema Dict to a Julia Dict literal string
schema_literal = dict_to_julia_literal(tool_schema)
# Build optional validation function
validate_section = if validate_code !== nothing && !isempty(validate_code)
indented = indent_code(validate_code, 4)
"function validateRequiredArgs(args::Dict{String,Any})::Union{Nothing,String}\n$indented\n return nothing\nend\n"
else
""
end
# Build optional prepare function
prepare_section = if prepare_code !== nothing && !isempty(prepare_code)
indented = indent_code(prepare_code, 4)
"function prepareArguments(args::Dict{String,Any})::Dict{String,Any}\n$indented\n return args\nend\n"
else
""
end
# Indent user's execute code for embedding inside execute function body
indented_exec = indent_code(execute_code, 4)
# Escape description for Julia string literal
escaped_desc = replace(tool_description, "\\" => "\\\\")
escaped_desc = replace(escaped_desc, "\"" => "\\\"")
# Build the complete tool file content
parts = String[]
push!(parts, "# Auto-generated tool: $tool_name\n")
push!(parts, "# Generated by writeTool at $(now())\n\n")
if !isempty(validate_section)
push!(parts, validate_section)
push!(parts, "\n")
end
if !isempty(prepare_section)
push!(parts, prepare_section)
push!(parts, "\n")
end
push!(parts, "\n")
push!(parts, "# Execute function\n")
push!(parts, "function executeTool(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal}, onPartialResult::Function)::agentToolResult\n")
push!(parts, "$indented_exec\n")
push!(parts, "end\n\n")
push!(parts, "# Tool definition\n")
push!(parts, "function getTool()::agentTool\n")
push!(parts, " return agentTool(\n")
push!(parts, " name = \"$(tool_name)\",\n")
push!(parts, " label = \"$(tool_label)\",\n")
push!(parts, " description = \"$(escaped_desc)\",\n")
push!(parts, " inputSchema = $schema_literal,\n")
push!(parts, " execute = executeTool,\n")
if validate_code !== nothing && !isempty(validate_code)
push!(parts, " validateRequiredArgs = validateRequiredArgs,\n")
else
push!(parts, " validateRequiredArgs = nothing,\n")
end
if prepare_code !== nothing && !isempty(prepare_code)
push!(parts, " prepareArguments = prepareArguments,\n")
else
push!(parts, " prepareArguments = nothing,\n")
end
push!(parts, " parallelToolExecute = $parallel\n")
push!(parts, " )\n")
push!(parts, "end\n")
tool_code = join(parts)
# Write the file — tool is loaded on next agent restart via loadTools(store, "src/tools")
write(filepath, tool_code)
onPartialResult(Dict("status" => "Done"))
return agentToolResult(
[textContent("Tool '$(tool_name)' written to $filepath. Restart the agent so loadTools(agent._tool_store, \"src/tools\") picks it up, then call listTools to verify.")],
Dict{Any,Any}(
"file" => filepath,
"name" => tool_name,
"label" => tool_label,
"description" => tool_description,
),
nothing, false
)
end,
prepareArguments = nothing,
validateRequiredArgs = nothing,
parallelToolExecute = false
)
end
+47 -163
View File
@@ -9,12 +9,12 @@
# Message types
userMessage, assistantMessage, toolResultMessage,
# Tool types
agentTool, validateRequiredArgs
agentTool, validateRequiredArgs,
# Context types
agentContext, agentState, agentToolCall, prepareNextTurnContext,
# Loop & execution types
agentLoopConfig, abortSignal, agentToolResult,
assistantMsgCtx, afterCtx,
agentLoopConfig, abortSignal, agentToolResult,beforeToolCallContext,
beforeToolCallResult, afterToolCallContext,
# Event types
toolExecStartEvent, toolExecUpdateEvent, toolExecEndEvent,
# Agent
@@ -23,7 +23,7 @@
preparedToolCall, immediateOutcome, executedOutcome, finalizedOutcome,
agentToolCallBatch,
# Functions (defined elsewhere)
run_agent, take_response, follow_up, stop_agent
runAgent, takeResponse, followUp, stopAgent
using Dates, UUIDs, DataStructures, JSON, NATS, Base.Threads
@@ -144,7 +144,7 @@ assistantMessage("assistant", [textContent("Hello!")], "", "", "gpt-4", ..., "en
```
"""
function assistantMessage(; role="assistant", content=Vector{messageContent}(),
api="", provider="", model="", usage=llmUsage(0, 0), stopReason="end_turn",
api="", provider="", model=nothing, usage=llmUsage(0, 0), stopReason="end_turn",
errorMessage=nothing, timestamp=now())
return assistantMessage(role, content, api, provider, model, usage, stopReason, errorMessage, timestamp)
end
@@ -248,7 +248,7 @@ tool = agentTool(
execute=(toolCallId, args, signal, onPartialResult) -> begin
city = args["city"]
return agentToolResult(
[textContent("Sunny, 22C in $(city)")],
[textContent("Sunny, 22C in Bangkok")],
Dict{Any,Any}(), nothing, false
)
end,
@@ -269,6 +269,17 @@ struct agentTool # A tool available to the agent
parallelToolExecute::Bool # Override: run tool calls sequentially or in parallel
end
"""
Keyword constructor for agentTool — allows `agentTool(name=..., label=..., ...)`.
"""
function agentTool(; name::String, label::String, description::String, inputSchema::Any,
execute::Function, prepareArguments::Union{Function, Nothing}=nothing,
validateRequiredArgs::Union{Function, Nothing}=nothing,
parallelToolExecute::Bool=false)
return agentTool(name, label, description, inputSchema, execute,
prepareArguments, validateRequiredArgs, parallelToolExecute)
end
# ------------------------------------------------------------------------------------------------ #
# Agent context #
@@ -280,7 +291,7 @@ Snapshot of the agent's conversation context.
# Arguments
- `systemPrompt::String`: System prompt for the agent
- `messages::Vector{agentMessage}`: Conversation messages
- `tools::Union{Vector{agentTool}, Nothing}`: Available tools
- `tools::Union{Dict{String, agentTool}, Nothing}`: Available tools keyed by name for O(1) lookup
# Returns
- A new `agentContext` instance
@@ -288,7 +299,7 @@ Snapshot of the agent's conversation context.
struct agentContext # Snapshot of the agent's conversation context
systemPrompt::String # System prompt for the agent
messages::Vector{agentMessage} # Conversation messages
tools::Union{Vector{agentTool}, Nothing} # Available tools
tools::Union{Dict{String, agentTool}, Nothing} # Available tools keyed by name
end
@@ -297,9 +308,9 @@ end
# ------------------------------------------------------------------------------------------------ #
mutable struct agentState # Mutable runtime state of an agent
systemPrompt::String # System prompt text
model::llmModel # LLM model to use
tools::Vector{agentTool} # Available tools
systemPrompt::String # System prompt for the agent
model::Union{llmModel, Nothing} # LLM model to use
tools::OrderedDict{String, agentTool} # Available tools keyed by name, insertion-ordered
# messages history includes userMessage, assistantMessage, toolResultMessage. NO system prompt
messages::Vector{agentMessage}
@@ -318,7 +329,7 @@ new state from external references.
# Arguments
- `systemPrompt::String`: System prompt text
- `model::llmModel`: LLM model to use (defaults to an unknown model)
- `tools::Vector{agentTool}`: Available tools (deep copied)
- `tools::OrderedDict{String, agentTool}`: Available tools keyed by name (deep copied)
- `messages::Vector{agentMessage}`: Conversation messages (deep copied)
# Returns
@@ -327,24 +338,24 @@ new state from external references.
# Examples
```julia
julia> state = agentState(systemPrompt="You are a helpful assistant")
agentState("You are a helpful assistant", ..., agentTool[], agentMessage[], String[], nothing)
```
agentState("You are a helpful assistant", OrderedDict{String, agentTool}(), agentMessage[], String[], nothing)
"""
function agentState(
systemPrompt::String="",
model::llmModel=llmModel{String}("", "", "unknown", "unknown", "", false, String[], modelCost(0.0, 0.0, 0.0, 0.0), 0, 0),
tools::Vector{agentTool}=agentTool[],
messages::Vector{agentMessage}=agentMessage[],
systemPrompt::String="",
model=llmModel("model_1", "unknown", "unknown", "", false, String[],
modelCost(0.0, 0.0, 0.0, 0.0), 0, 0),
tools::OrderedDict{String, agentTool}=OrderedDict{String, agentTool}(),
messages::Vector{agentMessage}=agentMessage[],
)
agentState(
systemPrompt,
model,
deepcopy(tools),
deepcopy(messages),
Vector{String}(),
false,
nothing,
)
agentState(
systemPrompt,
model,
deepcopy(tools),
deepcopy(messages),
Vector{String}(),
false,
nothing,
)
end
@@ -384,13 +395,13 @@ end
Configuration for the agent tool execution loop.
# Arguments
- `tools::Vector{agentTool}`: Available tools
- `tools::OrderedDict{String, agentTool}`: Available tools keyed by name
- `beforeToolCall::Union{Function, Nothing}`: Callback before tool execution
- `afterToolCall::Union{Function, Nothing}`: Callback after tool execution
- `toolExecution::String`: Execution mode — "sequential" or "parallel"
"""
struct agentLoopConfig
tools::Vector{agentTool}
tools::OrderedDict{String, agentTool}
beforeToolCall::Union{Function, Nothing}
afterToolCall::Union{Function, Nothing}
toolExecution::String
@@ -431,13 +442,18 @@ Context passed to the `beforeToolCall` hook.
- `args::Dict{String,Any}`: Validated tool arguments
- `context::agentContext`: Current conversation context
"""
struct assistantMsgCtx
struct beforeToolCallContext
message::assistantMessage
toolCall::agentToolCall
args::Dict{String,Any}
context::agentContext
end
struct beforeToolCallResult
block::Bool
reason::String
end
"""
Context passed to the `afterToolCall` hook.
@@ -449,7 +465,7 @@ Context passed to the `afterToolCall` hook.
- `isError::Bool`: Whether execution resulted in an error
- `context::agentContext`: Current conversation context
"""
struct afterCtx
struct afterToolCallContext
message::assistantMessage
toolCall::agentToolCall
args::Dict{String,Any}
@@ -510,138 +526,6 @@ end
abstract type agent end
"""
docstring
"""
mutable struct yiemAgent <: agent # High-level agent wrapper
_state::agentState # Current state (prompt, model, messages, tools, etc.)
# user sends prompt message to agent. if agent is idle, it process user message right away.
# if agent is running, it process user message after the current tool call finished.
inputChannel::Channel
# Buffers messages the user sends while the agent is busy. Processed after all inputChannel
# messages are handled and the agent is idle (not using a tool call).
followUpChannel::Channel
# agent sends response message to user after processing all user messages in inputChannel
# and all followUp messages.
outputChannel::Channel
_agent_loop::Union{Task, Nothing} # agent loop running in the background
# Preprocess/transform messages and context (modify, filter, prune, inject context from memory,
# reorder, ...) for a single LLM call in _process_message()'s loop.
# returns new Vector{agentMessage}
prepareContext ::Union{Function, Nothing}
# Convert prepareContext()'s new Vector{agentMessage} to LLM message format
formatMsgForLLM::Function
# Actually invoke the LLM to get a completion response. The LLM response comes back as an
# assistantMessage whose content is an array of content blocks.
# Each block has a type — "text", "thinking", or "toolCall".
# The code filters for type === "toolCall" blocks, then passes them to executeToolCalls().
llmCall::Function
# Callback invoked before executing a tool call (ask for user permission/confirmation/abort, etc..)
beforeToolCall::Union{Function, Nothing}
executeToolCalls::Function # execute tool calls ()
# Callback invoked after executing a tool call to sanitize tools output so the output is ready
# to be converted into toolResults message
afterToolCall::Union{Function, Nothing}
# prepareNextTurn::Union{Function, Nothing} # Callback to prepare the next conversation turn
# prepareNextTurnWithContext::Union{Function, Nothing} # Same but receives context
sessionId::Union{String, Nothing} # Optional session identifier
maxRetryDelayMs::Union{Int64, Nothing} # Maximum delay between retries (ms)
parallelToolExecute::Bool # Default: false
agentEventSink::Function # agent emits its status via this function
end
"""
Create a new yiemAgent instance with a background loop task.
Spawns a background `@spawn` task that runs the agent loop, listening
on `inputChannel` and `followUpChannel` channels concurrently.
# Keyword Arguments
- `systemPrompt::String`: System prompt for the agent
- `model`: LLM model to use
- `tools::Vector{agentTool}`: Available tools (default: empty)
- `messages::Vector{agentMessage}`: Initial conversation messages (default: empty)
- `formatMsgForLLM::Function`: Convert agent messages to LLM message format (default: `defaultformatMsgForLLM`)
- `llmCall::Function`: Function to invoke the LLM (required)
- `prepareContext::Union{Function, Nothing}`: Preprocess/transform messages before sending to LLM (default: `nothing`)
- `beforeToolCall::Union{Function, Nothing}`: Callback invoked before executing a tool call (default: `nothing`)
- `afterToolCall::Union{Function, Nothing}`: Callback invoked after executing a tool call (default: `nothing`)
- `prepareNextTurn::Union{Function, Nothing}`: Callback to prepare the next conversation turn (default: `nothing`)
- `prepareNextTurnWithContext::Union{Function, Nothing}`: Same but receives context (default: `nothing`)
- `sessionId::Union{String, Nothing}`: Optional session identifier (default: `nothing`)
- `maxRetryDelayMs::Union{Int64, Nothing}`: Maximum delay between retries in milliseconds (default: `nothing`)
- `parallelToolExecute::Bool`: Run tool calls in parallel (default: `false`)
- `agentEventSink::Function`: Callback to receive agent events
# Returns
- A new `yiemAgent` instance with an active background task
# Examples
```julia
julia> agent = yiemAgent(systemPrompt="You are a helpful assistant", model=my_model)
yiemAgent(agentState(...), Channel(...), Channel(...), Channel(...), ..., ...)
```
"""
function yiemAgent(
; systemPrompt::String="You are helpful assistant.",
model=nothing,
tools::Vector{agentTool}=agentTool[],
messages::Vector{agentMessage}=agentMessage[],
prepareContext::Union{Function, Nothing}=nothing,
formatMsgForLLM::Function=defaultformatMsgForLLM,
llmCall::Function,
beforeToolCall::Union{Function, Nothing}=nothing,
afterToolCall::Union{Function, Nothing}=nothing,
# prepareNextTurn::Union{Function, Nothing}=nothing,
# prepareNextTurnWithContext::Union{Function, Nothing}=nothing,
sessionId::Union{String, Nothing}=nothing,
maxRetryDelayMs::Union{Int64, Nothing}=nothing,
parallelToolExecute::Bool=false,
agentEventSink::Function,
)
# Create channels: input (user -> agent), followUp (async queue), output (agent -> user)
inputChannel = Channel(16)
followUp = Channel(32)
outputChannel = Channel(16)
# Create struct with a placeholder task, then spawn and replace it
agent = yiemAgent(
agentState(systemPrompt, model, tools, messages),
inputChannel,
followUp,
outputChannel,
nothing, # placeholder — replaced below
prepareContext,
formatMsgForLLM,
llmCall,
beforeToolCall,
afterToolCall,
# prepareNextTurn,
# prepareNextTurnWithContext,
sessionId,
maxRetryDelayMs,
parallelToolExecute,
agentEventSink,
)
# Spawn the background loop and attach it
agent._agent_loop = @spawn _agent_loop(agent)
return agent
end
"""
preparedToolCall(tool, toolCall, args)
+34 -4
View File
@@ -1,7 +1,9 @@
module utils
export clearhistory, availableWineToText, prepareContext, formatMsgForLLM, validateRequiredArgs, validateToolArguments, _userMessageToOpenAI,
_assistantMessageToOpenAI, _toolResultMessageToOpenAI, _messageContentToBlocks
export clearhistory, availableWineToText, prepareContext, formatMsgForLLM, validateRequiredArgs,
validateToolArguments, _userMessageToOpenAI,
_assistantMessageToOpenAI, _toolResultMessageToOpenAI, _messageContentToBlocks,
beforeToolCall, afterToolCall, agentEventSink
using UUIDs, Dates, DataStructures, HTTP, JSON
using GeneralUtils
@@ -113,7 +115,7 @@ function prepareContext(state::agentState)::agentContext
#TODO filter tools from state.tools based on user intend in user message and tool description
filteredTools = state.tools
#TODO add tools to current system prompt
#TODO add filtered tools to the current system prompt / modify systemPrompt here
preparedSystemPrompt = state.systemPrompt
#TODO add system prompt, adjust/modify and inject additional context into messages
@@ -218,6 +220,34 @@ function formatMsgForLLM(ctx::agentContext)::Dict{String, Any}
return Dict("messages" => messages)
end
#TODO
function beforeToolCall(context::beforeToolCallContext, signal::abortSignal
)::beforeToolCallResult
# final context check
# seek user approval via UI
# other check
return beforeToolCallResult(false, "N/A")
end
#TODO
function afterToolCall(context::beforeToolCallContext, signal::abortSignal
)::Union{agentToolResult, Nothing}
# modify context.result if needed and return agentToolResult
return nothing
end
#TODO
function agentEventSink(x)
end
"""
Convert a userMessage to OpenAI message format.
@@ -375,7 +405,7 @@ function validateToolArguments(tool::agentTool, prepared::agentToolCall)::Dict{S
end
return prepared.arguments
end
end
+1 -1
View File
@@ -4,7 +4,7 @@ export addNewMessage, conversation, decisionMaker, reflector, generatechat,
generalconversation, detectWineryName, generateSituationReport
using JSON, DataStructures, Dates, UUIDs, HTTP, Random, PrettyPrinting, Serialization,
DataFrames, Serde
DataFrames
using GeneralUtils
using ..type, ..util, ..llmfunction
+1 -1
View File
@@ -5,7 +5,7 @@ export virtualWineUserChatbox, jsoncorrection, search_wine_database!, # recomme
extractWineAttributes_2, paraphrase, SQLexecution
using HTTP, JSON, URIs, Random, PrettyPrinting, UUIDs, Dates, DataFrames, DataStructures,
Base64, Serde, LibPQ, NATS
Base64, LibPQ, NATS
using GeneralUtils, SQLLLM
using ..type, ..util
-41
View File
@@ -1,41 +0,0 @@
# This file is machine-generated - editing it directly is not advised
julia_version = "1.11.4"
manifest_format = "2.0"
project_hash = "71d91126b5a1fb1020e1098d9d492de2a4438fd2"
[[deps.Base64]]
uuid = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
version = "1.11.0"
[[deps.InteractiveUtils]]
deps = ["Markdown"]
uuid = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
version = "1.11.0"
[[deps.Logging]]
uuid = "56ddb016-857b-54e1-b83d-db4d58db5568"
version = "1.11.0"
[[deps.Markdown]]
deps = ["Base64"]
uuid = "d6f4376e-aef5-505a-96c1-9c027394607a"
version = "1.11.0"
[[deps.Random]]
deps = ["SHA"]
uuid = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
version = "1.11.0"
[[deps.SHA]]
uuid = "ea8e919c-243c-51af-8825-aaa63cd721ce"
version = "0.7.0"
[[deps.Serialization]]
uuid = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
version = "1.11.0"
[[deps.Test]]
deps = ["InteractiveUtils", "Logging", "Random", "Serialization"]
uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
version = "1.11.0"
-2
View File
@@ -1,2 +0,0 @@
[deps]
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
-401
View File
@@ -1,401 +0,0 @@
using JSON, Dates, UUIDs, PrettyPrinting, LibPQ, Base64, DataFrames, DataStructures, HTTP, Base64,
NATS, Base.Threads
using YiemAgent, GeneralUtils, msghandler
function text2text_instruct_llm(sender_id::String, openai_msg::Dict{String, Any})
payloads = [("msg", openai_msg, "dictionary")] # List of tuples
_, msg_envelope_json_str = msghandler.smartpack(
config["externalservice"]["servicesloadbalancer"]["nats"],
payloads;
sender_id=sender_id,
msg_purpose="text2text",
broker_url=config["nats_server_info"]["url"],
fileserver_url=config["externalservice"]["fileserver"]["url"])
reply = NATS.request(agent_conn,
config["externalservice"]["servicesloadbalancer"]["nats"],
msg_envelope_json_str, timeout=120)
incoming_env_json_str = String(reply.payload)
incoming_env = msghandler.smartunpack(incoming_env_json_str)
_llm_response = incoming_env["payloads"][1][2]
llm_response = _llm_response["choices"][1]["message"]["content"]
return llm_response
end
""" get a single text embedding from a LLM service
Example
text = ["hello"]
embedding = get_embedding(text)
"""
function get_embedding(text::AbstractArray{String})
documents_dict = Dict("documents" => text)
payloads = [("documents", documents_dict, "dictionary")]
_, msg_envelope_json_str = msghandler.smartpack(
config["externalservice"]["servicesloadbalancer"]["nats"],
payloads;
msg_purpose="embedding",
broker_url=config["nats_server_info"]["url"],
fileserver_url=config["externalservice"]["fileserver"]["url"])
reply = NATS.request(agent_conn,
config["externalservice"]["servicesloadbalancer"]["nats"],
msg_envelope_json_str, timeout=120)
incoming_env_json_str = String(reply.payload)
incoming_env = msghandler.smartunpack(incoming_env_json_str)
embedding_response = incoming_env["payloads"][1][2]
return embedding_response
end
""" sql = "SELECT * FROM wine;"
result = execute_sql_winedb(sql)
"""
function execute_sql_winedb(sql::T) where {T<:AbstractString}
host_url, _port = split(config["externalservice"]["sommpanion_db"]["url"], ':')
port = parse(Int, _port)
dbname = "winedb"
user = config["externalservice"]["sommpanion_db"]["user"]
password = config["externalservice"]["sommpanion_db"]["password"]
db_connection = LibPQ.Connection("host=$host_url port=$port dbname=$dbname user=$user password=$password")
result = nothing
try
result = LibPQ.execute(db_connection, sql)
catch e
LibPQ.close(db_connection)
end
LibPQ.close(db_connection)
return result
end
""" find similar sql from vector database
sql = "SELECT * FROM wine;"
result, distance = similar_sql_vectordb(sql)
"""
function similar_sql_vectordb(sql::T; maxdistance::Number=0.2) where {T<:AbstractString}
tablename = "sqlllm_decision_repository"
# get embedding of the query
df = find_similar_text_from_vectordb(sql, tablename,
"function_input_embedding", execute_sql_vectordb)
# println(df[1, [:id, :function_output]])
row, col = size(df)
distance = row == 0 ? Inf : df[1, :distance]
if row != 0 && distance < maxdistance
# if there is usable SQL, return it.
output_b64 = df[1, :function_output_base64] # pick the closest match
output_str = String(base64decode(output_b64))
rowid = df[1, :id]
println("\n--| similar sql found. row id $rowid, distance $distance ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
pprintln(output_str)
return (result=output_str, distance=distance)
else
println("\n--| similar sql not found, max distance $maxdistance ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
return (result=nothing, distance=nothing)
end
end
""" insert query and sql into vector database
query = "get all wines from wine table"
sql = "SELECT * FROM wine;"
insert_sql_vectordb(query, sql)
"""
function insert_sql_vectordb(query::T1, SQL::T2; maxdistance::Number=3
) where {T1<:AbstractString, T2<:AbstractString}
tablename = "sqlllm_decision_repository"
# get embedding of the query
# query = state[:thoughtHistory][:question]
df = find_similar_text_from_vectordb(query, tablename,
"function_input_embedding", execute_sql_vectordb)
row, col = size(df)
distance = row == 0 ? Inf : df[1, :distance]
if row == 0 || distance > maxdistance # no close enough SQL stored in the database
_query_embedding = get_embedding([query])
_query_embedding = GeneralUtils.dictify(_query_embedding)
# println("\n--- _query_embedding() ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
# println(_query_embedding)
# println("---\n")
query_embedding = _query_embedding["data"][1]["embedding"]
query = replace(query, "'" => "")
sql_base64 = base64encode(SQL)
sql_ = replace(SQL, "'" => "")
sql =
"""
INSERT INTO $tablename (function_input, function_output, function_output_base64, function_input_embedding) VALUES ('$query', '$sql_', '$sql_base64', '$query_embedding');
"""
# println("\n--| added new decision to vectorDB ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
# println(sql)
_ = execute_sql_vectordb(sql)
end
end
""" execute sql against vectordb
sql = "SELECT * FROM wine;"
result = execute_sql_vectordb(sql)
"""
function execute_sql_vectordb(sql::T) where {T<:AbstractString}
host_url, _port = split(config["externalservice"]["sommpanion_vectordb"]["url"], ':')
port = parse(Int, _port)
dbname = config["externalservice"]["sommpanion_vectordb"]["dbname"]
user = config["externalservice"]["sommpanion_vectordb"]["user"]
password = config["externalservice"]["sommpanion_vectordb"]["password"]
DBconnection = LibPQ.Connection("host=$host_url port=$port dbname=$dbname user=$user password=$password")
result = LibPQ.execute(DBconnection, sql)
close(DBconnection)
return result
end
""" search similar decision llm made from vectordb
"""
function similar_sommelier_decision(recentevents::T1; maxdistance::Integer=3
)::Union{AbstractDict, Nothing} where {T1<:AbstractString}
tablename = "sommelier_decision_repository"
# find similar
df = find_similar_text_from_vectordb(recentevents, tablename,
"function_input_embedding", execute_sql_vectordb)
row, col = size(df)
distance = row == 0 ? Inf : df[1, :distance]
if row != 0 && distance < maxdistance
# if there is usable decision, return it.
rowid = df[1, :id]
println("\n--| found similar decision. row id $rowid, distance $distance ", @__FILE__, " ", @__LINE__)
output_b64 = df[1, :function_output_base64] # pick the closest match
_output_str = String(base64decode(output_b64))
output = copy(JSON.read(_output_str))
return output
else
println("\n--| similar decision not found, max distance $maxdistance ", @__FILE__, " ", @__LINE__)
return nothing
end
end
""" search similar text from vectordb
"""
function find_similar_text_from_vectordb(text::T1, tablename::T2, embeddingColumnName::T3,
vectorDB::Function; limit::Integer=1
)::DataFrame where {T1<:AbstractString, T2<:AbstractString, T3<:AbstractString}
# get embedding from LLM service
_embedding = get_embedding([text])
_embedding = _embedding["data"][1]["embedding"]
_embedding = "$_embedding"
embedding = _embedding[4:end]
# check whether there is close enough vector already store in vectorDB. if no, add, else skip
sql = """
SELECT *, $embeddingColumnName <-> '$embedding' as distance
FROM $tablename
ORDER BY distance LIMIT $limit;
"""
response = vectorDB(sql)
df = DataFrame(response)
return df
end
""" insert decision llm made to vectordb
"""
function insert_sommelier_decision(recentevents::T1, decision::T2; maxdistance::Integer=5
) where {T1<:AbstractString, T2<:AbstractDict}
tablename = "sommelier_decision_repository"
# find similar
df = find_similar_text_from_vectordb(recentevents, tablename,
"function_input_embedding", execute_sql_vectordb)
row, col = size(df)
distance = row == 0 ? Inf : df[1, :distance]
if row == 0 || distance > maxdistance # no close enough SQL stored in the database
_embedding = get_embedding([recentevents])[1]
recentevents_embedding = _embedding["data"][1]["embedding"]
recentevents = replace(recentevents, "'" => "")
decision_json = JSON.json(decision)
decision_base64 = base64encode(decision_json)
decision = replace(decision_json, "'" => "")
sql =
"""
INSERT INTO $tablename (function_input, function_output, function_output_base64, function_input_embedding) VALUES ('$recentevents', '$decision', '$decision_base64', '$recentevents_embedding');
"""
println("\n--| added new decision to vectorDB ", @__FILE__, " ", @__LINE__)
println(sql)
_ = execute_sql_vectordb(sql)
else
println("--| similar decision previously cached, distance $distance ", @__FILE__, " ", @__LINE__)
end
end
config = JSON.parsefile("./appconfig.json")
sessionId = "0"
backend_session_topic = "sommpanion.testsubject"
agent_ch = Channel(8)
agent_conn = NATS.connect(config["nats_server_info"]["url"])
sub2 = NATS.subscribe(agent_conn, backend_session_topic) do msg
put!(agent_ch, msg)
end
agent_context = YiemAgent.agentcontext(
text2text_instruct_llm,
get_embedding,
execute_sql_winedb,
similar_sql_vectordb,
insert_sql_vectordb,
similar_sommelier_decision,
insert_sommelier_decision
)
# can't instantiate
agent = YiemAgent.sommelier(
agent_context;
name="Janie",
id=sessionId, # agent instance id
retailername="Yiem Wine Ltd.",
llmFormatName=""
)
image1_path = "test/large_image.png"
image1_bytes = read(image1_path)
image1_base64_string = base64encode(image1_bytes)
mime_type = "image/png"
data1_uri = "data:$(mime_type);base64,$(image1_base64_string)"
# 1. Read local file and encode to base64 string
image2_path = "test/small_image.png"
image2_bytes = read(image2_path)
image2_base64_string = base64encode(image2_bytes)
mime_type = "image/png"
data2_uri = "data:$(mime_type);base64,$(image2_base64_string)"
# 3. Construct payload with the Data URI
message = Dict(
"role" => "user",
"content" => [
Dict("type" => "text", "text" => "Do you know type of wine in the image?"),
Dict(
"type" => "image_url",
"image_url" => Dict("url" => data1_uri)
)
]
)
result = YiemAgent.conversation(agent; userinput=message)
println("\n$result")
# message = Dict(
# "role" => "user",
# "content" => [
# Dict("type" => "text", "text" =>
# "
# เป็นงานเลี้ยงทั่วไป
# "),
# ]
# )
# result = YiemAgent.conversation(agent; userinput=message)
# println("\n$result")
# message = Dict(
# "role" => "user",
# "content" => [
# Dict("type" => "text", "text" => "no thanks. that's all"),
# ]
# )
# result = YiemAgent.conversation(agent; userinput=message)
# println("\n$result")
# message = Dict(
# "role" => "user",
# "content" => [
# Dict("type" => "text", "text" => "What about this wine?"),
# Dict(
# "type" => "image_url",
# "image_url" => Dict("url" => data2_uri)
# )
# ]
# )
# result = YiemAgent.conversation(agent; userinput=message)
# println("\n$result")
+212
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@@ -0,0 +1,212 @@
using Test
using YiemAgent
using YiemAgent.toolRegistry
using YiemAgent.type
# Path to the real tools directory
TOOLS_DIR = joinpath(@__DIR__, "..", "src", "tools")
@testset "loadTools with toolStore" begin
# ------------------------------------------------------------------ #
# 1. loadTools throws on non-existent directory #
# ------------------------------------------------------------------ #
store = toolStore(name="test1")
@test_throws ArgumentError loadTools(store, "/nonexistent/dir/that/does/not/exist")
# ------------------------------------------------------------------ #
# 2. loadTools throws if a .jl file does not define getTool() #
# Must run BEFORE any other loadTools call (getTool binding #
# persists in module scope after include()). #
# ------------------------------------------------------------------ #
bad_dir = mktempdir()
write(joinpath(bad_dir, "noTool.jl"), "x = 42\n")
@test_throws ArgumentError loadTools(store, bad_dir)
# ------------------------------------------------------------------ #
# 3. loadTools loads actual tool files from src/tools/ #
# ------------------------------------------------------------------ #
store2 = toolStore(name="test2")
loaded = loadTools(store2, TOOLS_DIR)
@test !isempty(loaded)
@test length(loaded) == 4 # 3 files + auto-registered listTools
names = [k for k in keys(loaded)]
@test "getTime" in names
@test "getWeather" in names
@test "writeTool" in names
@test "listTools" in names
# ------------------------------------------------------------------ #
# 4. loadTools returns tools sorted alphabetically by filename #
# (getTime.jl < getWeather.jl < writeTool.jl) + listTools at end #
# ------------------------------------------------------------------ #
@test collect(keys(loaded))[1] == "getTime"
@test collect(keys(loaded))[2] == "getWeather"
@test collect(keys(loaded))[3] == "writeTool"
@test collect(keys(loaded))[4] == "listTools"
# ------------------------------------------------------------------ #
# 5. Verify loaded tool fields are correct #
# ------------------------------------------------------------------ #
# getTime
time_tool = loaded["getTime"]
@test time_tool.name == "getTime"
@test time_tool.label == "Time Lookup"
@test time_tool.validateRequiredArgs !== nothing
@test time_tool.parallelToolExecute == false
@test time_tool.inputSchema["required"] == Any[]
# getWeather
weather = loaded["getWeather"]
@test weather.name == "getWeather"
@test weather.label == "Weather Lookup"
@test weather.execute !== nothing
@test weather.parallelToolExecute == false
@test weather.inputSchema["required"] == ["city"]
# writeTool
wt = loaded["writeTool"]
@test wt.name == "writeTool"
@test wt.label == "Create Tool"
@test wt.execute !== nothing
@test "name" in wt.inputSchema["required"]
@test "executeCode" in wt.inputSchema["required"]
# ------------------------------------------------------------------ #
# 6. Tool execution returns valid results #
# ------------------------------------------------------------------ #
sig = nothing
op = x -> x # no-op partial result callback
# execute getTime
result_t = time_tool.execute("call-1", Dict{String,Any}("city" => "Tokyo"), sig, op)
@test result_t isa agentToolResult
@test result_t.content[1] isa textContent
@test occursin("Tokyo", result_t.content[1].text)
# execute getTime with timezone
result_tz = time_tool.execute("call-2", Dict{String,Any}("timezone" => "America/New_York"), sig, op)
@test result_tz isa agentToolResult
@test occursin("America/New_York", result_tz.content[1].text)
# execute getWeather
result_w = weather.execute("call-3", Dict{String,Any}("city" => "Bangkok"), sig, op)
@test result_w isa agentToolResult
@test result_w.content[1] isa textContent
@test occursin("Bangkok", result_w.content[1].text)
# execute getWeather with units
result_w2 = weather.execute("call-4", Dict{String,Any}("city" => "London", "units" => "fahrenheit"), sig, op)
@test occursin("72°F", result_w2.content[1].text)
# ------------------------------------------------------------------ #
# 7. getTools / registerTool / clearTools (per-store isolation) #
# ------------------------------------------------------------------ #
store3 = toolStore(name="test3")
registry_tools = getTools(store3)
@test isempty(registry_tools)
# listTool is not auto-registered anymore — each store starts empty
# Register tools manually
registerTool(store3, loaded["getTime"])
registerTool(store3, loaded["getWeather"])
registerTool(store3, loaded["writeTool"])
reg = getTools(store3)
@test !isempty(reg)
@test "getTime" in keys(reg)
@test "getWeather" in keys(reg)
@test "writeTool" in keys(reg)
@test collect(keys(reg))[1] == "getTime"
@test collect(keys(reg))[2] == "getWeather"
@test collect(keys(reg))[3] == "writeTool"
clearTools(store3)
@test isempty(getTools(store3))
test_tool = agentTool(
name = "manualTool",
label = "Manual Tool",
description = "Registered manually",
inputSchema = Dict{String,Any}("type" => "object", "properties" => Dict{String,Any}(), "required" => Any[]),
execute = (toolCallId, args, signal, onPartialResult) ->
agentToolResult([textContent("manual")], Dict{Any,Any}(), nothing, false),
prepareArguments = nothing,
validateRequiredArgs = nothing,
parallelToolExecute = true
)
registerTool(store3, test_tool)
reg = getTools(store3)
@test haskey(reg, "manualTool")
@test length(reg) == 1
@test reg["manualTool"].parallelToolExecute == true
# ------------------------------------------------------------------ #
# 8. getTools returns direct reference (mutations affect registry) #
# ------------------------------------------------------------------ #
copy1 = getTools(store3)
copy2 = getTools(store3)
@test copy1 === copy2 # same reference, not a deep copy
empty!(copy1)
@test isempty(getTools(store3)) # mutation propagates
# ------------------------------------------------------------------ #
# 9. Per-store isolation — two stores don't share tools #
# ------------------------------------------------------------------ #
storeA = toolStore(name="isolationA")
storeB = toolStore(name="isolationB")
registerTool(storeA, loaded["getTime"])
registerTool(storeB, loaded["getWeather"])
regA = getTools(storeA)
regB = getTools(storeB)
@test "getTime" in keys(regA)
@test "getWeather" keys(regA)
@test "getWeather" in keys(regB)
@test "getTime" keys(regB)
clearTools(storeA)
@test isempty(getTools(storeA))
@test !isempty(getTools(storeB)) # storeB unaffected
end
@testset "listTool" begin
store = toolStore(name="test_list")
loaded = loadTools(store, TOOLS_DIR) # auto-registers getWeather, getTime, writeTool + listTools
# loadTools auto-registers listTool
@test "listTools" in keys(loaded)
# listTool returns an agentTool, not a string or array
list_t = listTool(store)
@test list_t isa agentTool
@test list_t.name == "listTools"
@test list_t.label == "List Tools"
@test isempty(list_t.inputSchema["required"])
# Verify all tools appear (3 loaded + listTools = 4)
result = list_t.execute("call-1", Dict{String,Any}(), nothing, x -> x)
@test result isa agentToolResult
@test result.content[1] isa textContent
@test occursin("listTools", result.content[1].text)
@test occursin("getWeather", result.content[1].text)
@test occursin("getTime", result.content[1].text)
@test occursin("writeTool", result.content[1].text)
@test result.details["count"] == 4
# Each listTool call creates an independent closure
storeB = toolStore(name="test_listB")
registerTool(storeB, loaded["getWeather"])
list_tB = listTool(storeB)
resultA = list_t.execute("call-3", Dict{String,Any}(), nothing, x -> x)
resultB = list_tB.execute("call-4", Dict{String,Any}(), nothing, x -> x)
@test occursin("getWeather", resultA.content[1].text)
@test occursin("getWeather", resultB.content[1].text)
@test occursin("getTime", resultA.content[1].text)
@test occursin("getTime", resultB.content[1].text) == false # storeB only has getWeather
end