diff --git a/poetry.lock b/poetry.lock
index 621da2c..865112a 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -235,7 +235,7 @@ version = "4.12.0"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
     {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
@@ -248,6 +248,93 @@ typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""}
 [package.extras]
 trio = ["trio (>=0.31.0) ; python_version < \"3.10\"", "trio (>=0.32.0) ; python_version >= \"3.10\""]
 
+[[package]]
+name = "appnope"
+version = "0.1.4"
+description = "Disable App Nap on macOS >= 10.9"
+optional = false
+python-versions = ">=3.6"
+groups = ["dev"]
+markers = "platform_system == \"Darwin\""
+files = [
+    {file = "appnope-0.1.4-py2.py3-none-any.whl", hash = "sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c"},
+    {file = "appnope-0.1.4.tar.gz", hash = "sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee"},
+]
+
+[[package]]
+name = "argon2-cffi"
+version = "25.1.0"
+description = "Argon2 for Python"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "argon2_cffi-25.1.0-py3-none-any.whl", hash = "sha256:fdc8b074db390fccb6eb4a3604ae7231f219aa669a2652e0f20e16ba513d5741"},
+    {file = "argon2_cffi-25.1.0.tar.gz", hash = "sha256:694ae5cc8a42f4c4e2bf2ca0e64e51e23a040c6a517a85074683d3959e1346c1"},
+]
+
+[package.dependencies]
+argon2-cffi-bindings = "*"
+
+[[package]]
+name = "argon2-cffi-bindings"
+version = "25.1.0"
+description = "Low-level CFFI bindings for Argon2"
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
+    {file = "argon2_cffi_bindings-25.1.0-cp314-cp314t-macosx_10_13_universal2.whl", hash = "sha256:3d3f05610594151994ca9ccb3c771115bdb4daef161976a266f0dd8aa9996b8f"},
+    {file = "argon2_cffi_bindings-25.1.0-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:8b8efee945193e667a396cbc7b4fb7d357297d6234d30a489905d96caabde56b"},
+    {file = "argon2_cffi_bindings-25.1.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:3c6702abc36bf3ccba3f802b799505def420a1b7039862014a65db3205967f5a"},
+    {file = "argon2_cffi_bindings-25.1.0-cp314-cp314t-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:a1c70058c6ab1e352304ac7e3b52554daadacd8d453c1752e547c76e9c99ac44"},
+    {file = "argon2_cffi_bindings-25.1.0-cp314-cp314t-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:e2fd3bfbff3c5d74fef31a722f729bf93500910db650c925c2d6ef879a7e51cb"},
+    {file = "argon2_cffi_bindings-25.1.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:c4f9665de60b1b0e99bcd6be4f17d90339698ce954cfd8d9cf4f91c995165a92"},
+    {file = "argon2_cffi_bindings-25.1.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:ba92837e4a9aa6a508c8d2d7883ed5a8f6c308c89a4790e1e447a220deb79a85"},
+    {file = "argon2_cffi_bindings-25.1.0-cp314-cp314t-win32.whl", hash = "sha256:84a461d4d84ae1295871329b346a97f68eade8c53b6ed9a7ca2d7467f3c8ff6f"},
+    {file = "argon2_cffi_bindings-25.1.0-cp314-cp314t-win_amd64.whl", hash = "sha256:b55aec3565b65f56455eebc9b9f34130440404f27fe21c3b375bf1ea4d8fbae6"},
+    {file = "argon2_cffi_bindings-25.1.0-cp314-cp314t-win_arm64.whl", hash = "sha256:87c33a52407e4c41f3b70a9c2d3f6056d88b10dad7695be708c5021673f55623"},
+    {file = "argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_10_9_universal2.whl", hash = "sha256:aecba1723ae35330a008418a91ea6cfcedf6d31e5fbaa056a166462ff066d500"},
+    {file = "argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_10_9_x86_64.whl", hash = "sha256:2630b6240b495dfab90aebe159ff784d08ea999aa4b0d17efa734055a07d2f44"},
+    {file = "argon2_cffi_bindings-25.1.0-cp39-abi3-macosx_11_0_arm64.whl", hash = "sha256:7aef0c91e2c0fbca6fc68e7555aa60ef7008a739cbe045541e438373bc54d2b0"},
+    {file = "argon2_cffi_bindings-25.1.0-cp39-abi3-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:1e021e87faa76ae0d413b619fe2b65ab9a037f24c60a1e6cc43457ae20de6dc6"},
+    {file = "argon2_cffi_bindings-25.1.0-cp39-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:d3e924cfc503018a714f94a49a149fdc0b644eaead5d1f089330399134fa028a"},
+    {file = "argon2_cffi_bindings-25.1.0-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:c87b72589133f0346a1cb8d5ecca4b933e3c9b64656c9d175270a000e73b288d"},
+    {file = "argon2_cffi_bindings-25.1.0-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:1db89609c06afa1a214a69a462ea741cf735b29a57530478c06eb81dd403de99"},
+    {file = "argon2_cffi_bindings-25.1.0-cp39-abi3-win32.whl", hash = "sha256:473bcb5f82924b1becbb637b63303ec8d10e84c8d241119419897a26116515d2"},
+    {file = "argon2_cffi_bindings-25.1.0-cp39-abi3-win_amd64.whl", hash = "sha256:a98cd7d17e9f7ce244c0803cad3c23a7d379c301ba618a5fa76a67d116618b98"},
+    {file = "argon2_cffi_bindings-25.1.0-cp39-abi3-win_arm64.whl", hash = "sha256:b0fdbcf513833809c882823f98dc2f931cf659d9a1429616ac3adebb49f5db94"},
+    {file = "argon2_cffi_bindings-25.1.0-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:6dca33a9859abf613e22733131fc9194091c1fa7cb3e131c143056b4856aa47e"},
+    {file = "argon2_cffi_bindings-25.1.0-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:21378b40e1b8d1655dd5310c84a40fc19a9aa5e6366e835ceb8576bf0fea716d"},
+    {file = "argon2_cffi_bindings-25.1.0-pp310-pypy310_pp73-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:5d588dec224e2a83edbdc785a5e6f3c6cd736f46bfd4b441bbb5aa1f5085e584"},
+    {file = "argon2_cffi_bindings-25.1.0-pp310-pypy310_pp73-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:5acb4e41090d53f17ca1110c3427f0a130f944b896fc8c83973219c97f57b690"},
+    {file = "argon2_cffi_bindings-25.1.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:da0c79c23a63723aa5d782250fbf51b768abca630285262fb5144ba5ae01e520"},
+    {file = "argon2_cffi_bindings-25.1.0.tar.gz", hash = "sha256:b957f3e6ea4d55d820e40ff76f450952807013d361a65d7f28acc0acbf29229d"},
+]
+
+[package.dependencies]
+cffi = {version = ">=1.0.1", markers = "python_version < \"3.14\""}
+
+[[package]]
+name = "arrow"
+version = "1.4.0"
+description = "Better dates & times for Python"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "arrow-1.4.0-py3-none-any.whl", hash = "sha256:749f0769958ebdc79c173ff0b0670d59051a535fa26e8eba02953dc19eb43205"},
+    {file = "arrow-1.4.0.tar.gz", hash = "sha256:ed0cc050e98001b8779e84d461b0098c4ac597e88704a655582b21d116e526d7"},
+]
+
+[package.dependencies]
+python-dateutil = ">=2.7.0"
+tzdata = {version = "*", markers = "python_version >= \"3.9\""}
+
+[package.extras]
+doc = ["doc8", "sphinx (>=7.0.0)", "sphinx-autobuild", "sphinx-autodoc-typehints", "sphinx_rtd_theme (>=1.3.0)"]
+test = ["dateparser (==1.*)", "pre-commit", "pytest", "pytest-cov", "pytest-mock", "pytz (==2025.2)", "simplejson (==3.*)"]
+
 [[package]]
 name = "asn1crypto"
 version = "1.5.1"
@@ -260,18 +347,103 @@ files = [
     {file = "asn1crypto-1.5.1.tar.gz", hash = "sha256:13ae38502be632115abf8a24cbe5f4da52e3b5231990aff31123c805306ccb9c"},
 ]
 
+[[package]]
+name = "asttokens"
+version = "3.0.1"
+description = "Annotate AST trees with source code positions"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "asttokens-3.0.1-py3-none-any.whl", hash = "sha256:15a3ebc0f43c2d0a50eeafea25e19046c68398e487b9f1f5b517f7c0f40f976a"},
+    {file = "asttokens-3.0.1.tar.gz", hash = "sha256:71a4ee5de0bde6a31d64f6b13f2293ac190344478f081c3d1bccfcf5eacb0cb7"},
+]
+
+[package.extras]
+astroid = ["astroid (>=2,<5)"]
+test = ["astroid (>=2,<5)", "pytest (<9.0)", "pytest-cov", "pytest-xdist"]
+
+[[package]]
+name = "async-lru"
+version = "2.0.5"
+description = "Simple LRU cache for asyncio"
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
+    {file = "async_lru-2.0.5-py3-none-any.whl", hash = "sha256:ab95404d8d2605310d345932697371a5f40def0487c03d6d0ad9138de52c9943"},
+    {file = "async_lru-2.0.5.tar.gz", hash = "sha256:481d52ccdd27275f42c43a928b4a50c3bfb2d67af4e78b170e3e0bb39c66e5bb"},
+]
+
 [[package]]
 name = "attrs"
 version = "25.4.0"
 description = "Classes Without Boilerplate"
 optional = false
 python-versions = ">=3.9"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "attrs-25.4.0-py3-none-any.whl", hash = "sha256:adcf7e2a1fb3b36ac48d97835bb6d8ade15b8dcce26aba8bf1d14847b57a3373"},
     {file = "attrs-25.4.0.tar.gz", hash = "sha256:16d5969b87f0859ef33a48b35d55ac1be6e42ae49d5e853b597db70c35c57e11"},
 ]
 
+[[package]]
+name = "babel"
+version = "2.17.0"
+description = "Internationalization utilities"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "babel-2.17.0-py3-none-any.whl", hash = "sha256:4d0b53093fdfb4b21c92b5213dba5a1b23885afa8383709427046b21c366e5f2"},
+    {file = "babel-2.17.0.tar.gz", hash = "sha256:0c54cffb19f690cdcc52a3b50bcbf71e07a808d1c80d549f2459b9d2cf0afb9d"},
+]
+
+[package.extras]
+dev = ["backports.zoneinfo ; python_version < \"3.9\"", "freezegun (>=1.0,<2.0)", "jinja2 (>=3.0)", "pytest (>=6.0)", "pytest-cov", "pytz", "setuptools", "tzdata ; sys_platform == \"win32\""]
+
+[[package]]
+name = "beautifulsoup4"
+version = "4.14.3"
+description = "Screen-scraping library"
+optional = false
+python-versions = ">=3.7.0"
+groups = ["dev"]
+files = [
+    {file = "beautifulsoup4-4.14.3-py3-none-any.whl", hash = "sha256:0918bfe44902e6ad8d57732ba310582e98da931428d231a5ecb9e7c703a735bb"},
+    {file = "beautifulsoup4-4.14.3.tar.gz", hash = "sha256:6292b1c5186d356bba669ef9f7f051757099565ad9ada5dd630bd9de5fa7fb86"},
+]
+
+[package.dependencies]
+soupsieve = ">=1.6.1"
+typing-extensions = ">=4.0.0"
+
+[package.extras]
+cchardet = ["cchardet"]
+chardet = ["chardet"]
+charset-normalizer = ["charset-normalizer"]
+html5lib = ["html5lib"]
+lxml = ["lxml"]
+
+[[package]]
+name = "bleach"
+version = "6.3.0"
+description = "An easy safelist-based HTML-sanitizing tool."
+optional = false
+python-versions = ">=3.10"
+groups = ["dev"]
+files = [
+    {file = "bleach-6.3.0-py3-none-any.whl", hash = "sha256:fe10ec77c93ddf3d13a73b035abaac7a9f5e436513864ccdad516693213c65d6"},
+    {file = "bleach-6.3.0.tar.gz", hash = "sha256:6f3b91b1c0a02bb9a78b5a454c92506aa0fdf197e1d5e114d2e00c6f64306d22"},
+]
+
+[package.dependencies]
+tinycss2 = {version = ">=1.1.0,<1.5", optional = true, markers = "extra == \"css\""}
+webencodings = "*"
+
+[package.extras]
+css = ["tinycss2 (>=1.1.0,<1.5)"]
+
 [[package]]
 name = "blinker"
 version = "1.9.0"
@@ -342,7 +514,7 @@ version = "2025.11.12"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.7"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "certifi-2025.11.12-py3-none-any.whl", hash = "sha256:97de8790030bbd5c2d96b7ec782fc2f7820ef8dba6db909ccf95449f2d062d4b"},
     {file = "certifi-2025.11.12.tar.gz", hash = "sha256:d8ab5478f2ecd78af242878415affce761ca6bc54a22a27e026d7c25357c3316"},
@@ -354,8 +526,7 @@ version = "2.0.0"
 description = "Foreign Function Interface for Python calling C code."
 optional = false
 python-versions = ">=3.9"
-groups = ["main"]
-markers = "platform_python_implementation != \"PyPy\""
+groups = ["main", "dev"]
 files = [
     {file = "cffi-2.0.0-cp310-cp310-macosx_10_13_x86_64.whl", hash = "sha256:0cf2d91ecc3fcc0625c2c530fe004f82c110405f101548512cce44322fa8ac44"},
     {file = "cffi-2.0.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f73b96c41e3b2adedc34a7356e64c8eb96e03a3782b535e043a986276ce12a49"},
@@ -442,6 +613,7 @@ files = [
     {file = "cffi-2.0.0-cp39-cp39-win_amd64.whl", hash = "sha256:b882b3df248017dba09d6b16defe9b5c407fe32fc7c65a9c69798e6175601be9"},
     {file = "cffi-2.0.0.tar.gz", hash = "sha256:44d1b5909021139fe36001ae048dbdde8214afa20200eda0f64c068cac5d5529"},
 ]
+markers = {main = "platform_python_implementation != \"PyPy\""}
 
 [package.dependencies]
 pycparser = {version = "*", markers = "implementation_name != \"PyPy\""}
@@ -452,7 +624,7 @@ version = "3.4.4"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 optional = false
 python-versions = ">=3.7"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "charset_normalizer-3.4.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:e824f1492727fa856dd6eda4f7cee25f8518a12f3c4a56a74e8095695089cf6d"},
     {file = "charset_normalizer-3.4.4-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4bd5d4137d500351a30687c2d3971758aac9a19208fc110ccb9d7188fbe709e8"},
@@ -602,12 +774,27 @@ version = "0.4.6"
 description = "Cross-platform colored terminal text."
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
-groups = ["main"]
-markers = "platform_system == \"Windows\""
+groups = ["main", "dev"]
 files = [
     {file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"},
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
+markers = {main = "platform_system == \"Windows\"", dev = "sys_platform == \"win32\""}
+
+[[package]]
+name = "comm"
+version = "0.2.3"
+description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "comm-0.2.3-py3-none-any.whl", hash = "sha256:c615d91d75f7f04f095b30d1c1711babd43bdc6419c1be9886a85f2f4e489417"},
+    {file = "comm-0.2.3.tar.gz", hash = "sha256:2dc8048c10962d55d7ad693be1e7045d891b7ce8d999c97963a5e3e99c055971"},
+]
+
+[package.extras]
+test = ["pytest"]
 
 [[package]]
 name = "contourpy"
@@ -701,6 +888,111 @@ mypy = ["bokeh", "contourpy[bokeh,docs]", "docutils-stubs", "mypy (==1.17.0)", "
 test = ["Pillow", "contourpy[test-no-images]", "matplotlib"]
 test-no-images = ["pytest", "pytest-cov", "pytest-rerunfailures", "pytest-xdist", "wurlitzer"]
 
+[[package]]
+name = "coverage"
+version = "7.13.1"
+description = "Code coverage measurement for Python"
+optional = false
+python-versions = ">=3.10"
+groups = ["dev"]
+files = [
+    {file = "coverage-7.13.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e1fa280b3ad78eea5be86f94f461c04943d942697e0dac889fa18fff8f5f9147"},
+    {file = "coverage-7.13.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c3d8c679607220979434f494b139dfb00131ebf70bb406553d69c1ff01a5c33d"},
+    {file = "coverage-7.13.1-cp310-cp310-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:339dc63b3eba969067b00f41f15ad161bf2946613156fb131266d8debc8e44d0"},
+    {file = "coverage-7.13.1-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:db622b999ffe49cb891f2fff3b340cdc2f9797d01a0a202a0973ba2562501d90"},
+    {file = "coverage-7.13.1-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d1443ba9acbb593fa7c1c29e011d7c9761545fe35e7652e85ce7f51a16f7e08d"},
+    {file = "coverage-7.13.1-cp310-cp310-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:c832ec92c4499ac463186af72f9ed4d8daec15499b16f0a879b0d1c8e5cf4a3b"},
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+]
+
+[[package]]
+name = "decorator"
+version = "5.2.1"
+description = "Decorators for Humans"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "decorator-5.2.1-py3-none-any.whl", hash = "sha256:d316bb415a2d9e2d2b3abcc4084c6502fc09240e292cd76a76afc106a1c8e04a"},
+    {file = "decorator-5.2.1.tar.gz", hash = "sha256:65f266143752f734b0a7cc83c46f4618af75b8c5911b00ccb61d0ac9b6da0360"},
+]
+
+[[package]]
+name = "defusedxml"
+version = "0.7.1"
+description = "XML bomb protection for Python stdlib modules"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+groups = ["dev"]
+files = [
+    {file = "defusedxml-0.7.1-py2.py3-none-any.whl", hash = "sha256:a352e7e428770286cc899e2542b6cdaedb2b4953ff269a210103ec58f6198a61"},
+    {file = "defusedxml-0.7.1.tar.gz", hash = "sha256:1bb3032db185915b62d7c6209c5a8792be6a32ab2fedacc84e01b52c51aa3e69"},
+]
+
 [[package]]
 name = "deprecation"
 version = "2.1.0"
@@ -1011,6 +1367,21 @@ docs = ["myst-parser (==0.18.0)", "sphinx (==5.1.1)"]
 ssh = ["paramiko (>=2.4.3)"]
 websockets = ["websocket-client (>=1.3.0)"]
 
+[[package]]
+name = "executing"
+version = "2.2.1"
+description = "Get the currently executing AST node of a frame, and other information"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "executing-2.2.1-py2.py3-none-any.whl", hash = "sha256:760643d3452b4d777d295bb167ccc74c64a81df23fb5e08eff250c425a4b2017"},
+    {file = "executing-2.2.1.tar.gz", hash = "sha256:3632cc370565f6648cc328b32435bd120a1e4ebb20c77e3fdde9a13cd1e533c4"},
+]
+
+[package.extras]
+tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipython", "littleutils", "pytest", "rich ; python_version >= \"3.11\""]
+
 [[package]]
 name = "fastapi"
 version = "0.124.2"
@@ -1034,6 +1405,21 @@ all = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.8)", "httpx (>
 standard = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.8)", "httpx (>=0.23.0,<1.0.0)", "jinja2 (>=3.1.5)", "python-multipart (>=0.0.18)", "uvicorn[standard] (>=0.12.0)"]
 standard-no-fastapi-cloud-cli = ["email-validator (>=2.0.0)", "fastapi-cli[standard-no-fastapi-cloud-cli] (>=0.0.8)", "httpx (>=0.23.0,<1.0.0)", "jinja2 (>=3.1.5)", "python-multipart (>=0.0.18)", "uvicorn[standard] (>=0.12.0)"]
 
+[[package]]
+name = "fastjsonschema"
+version = "2.21.2"
+description = "Fastest Python implementation of JSON schema"
+optional = false
+python-versions = "*"
+groups = ["dev"]
+files = [
+    {file = "fastjsonschema-2.21.2-py3-none-any.whl", hash = "sha256:1c797122d0a86c5cace2e54bf4e819c36223b552017172f32c5c024a6b77e463"},
+    {file = "fastjsonschema-2.21.2.tar.gz", hash = "sha256:b1eb43748041c880796cd077f1a07c3d94e93ae84bba5ed36800a33554ae05de"},
+]
+
+[package.extras]
+devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benchmark", "pytest-cache", "validictory"]
+
 [[package]]
 name = "filelock"
 version = "3.20.0"
@@ -1159,6 +1545,18 @@ type1 = ["xattr ; sys_platform == \"darwin\""]
 unicode = ["unicodedata2 (>=17.0.0) ; python_version <= \"3.14\""]
 woff = ["brotli (>=1.0.1) ; platform_python_implementation == \"CPython\"", "brotlicffi (>=0.8.0) ; platform_python_implementation != \"CPython\"", "zopfli (>=0.1.4)"]
 
+[[package]]
+name = "fqdn"
+version = "1.5.1"
+description = "Validates fully-qualified domain names against RFC 1123, so that they are acceptable to modern bowsers"
+optional = false
+python-versions = ">=2.7, !=3.0, !=3.1, !=3.2, !=3.3, !=3.4, <4"
+groups = ["dev"]
+files = [
+    {file = "fqdn-1.5.1-py3-none-any.whl", hash = "sha256:3a179af3761e4df6eb2e026ff9e1a3033d3587bf980a0b1b2e1e5d08d7358014"},
+    {file = "fqdn-1.5.1.tar.gz", hash = "sha256:105ed3677e767fb5ca086a0c1f4bb66ebc3c100be518f0e0d755d9eae164d89f"},
+]
+
 [[package]]
 name = "frozenlist"
 version = "1.8.0"
@@ -1616,7 +2014,7 @@ version = "0.16.0"
 description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "h11-0.16.0-py3-none-any.whl", hash = "sha256:63cf8bbe7522de3bf65932fda1d9c2772064ffb3dae62d55932da54b31cb6c86"},
     {file = "h11-0.16.0.tar.gz", hash = "sha256:4e35b956cf45792e4caa5885e69fba00bdbc6ffafbfa020300e549b208ee5ff1"},
@@ -1628,7 +2026,7 @@ version = "1.0.9"
 description = "A minimal low-level HTTP client."
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "httpcore-1.0.9-py3-none-any.whl", hash = "sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55"},
     {file = "httpcore-1.0.9.tar.gz", hash = "sha256:6e34463af53fd2ab5d807f399a9b45ea31c3dfa2276f15a2c3f00afff6e176e8"},
@@ -1650,7 +2048,7 @@ version = "0.28.1"
 description = "The next generation HTTP client."
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad"},
     {file = "httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc"},
@@ -1703,7 +2101,7 @@ version = "3.11"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "idna-3.11-py3-none-any.whl", hash = "sha256:771a87f49d9defaf64091e6e6fe9c18d4833f140bd19464795bc32d966ca37ea"},
     {file = "idna-3.11.tar.gz", hash = "sha256:795dafcc9c04ed0c1fb032c2aa73654d8e8c5023a7df64a53f39190ada629902"},
@@ -1736,6 +2134,114 @@ perf = ["ipython"]
 test = ["flufl.flake8", "importlib_resources (>=1.3) ; python_version < \"3.9\"", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"]
 type = ["pytest-mypy"]
 
+[[package]]
+name = "iniconfig"
+version = "2.3.0"
+description = "brain-dead simple config-ini parsing"
+optional = false
+python-versions = ">=3.10"
+groups = ["dev"]
+files = [
+    {file = "iniconfig-2.3.0-py3-none-any.whl", hash = "sha256:f631c04d2c48c52b84d0d0549c99ff3859c98df65b3101406327ecc7d53fbf12"},
+    {file = "iniconfig-2.3.0.tar.gz", hash = "sha256:c76315c77db068650d49c5b56314774a7804df16fee4402c1f19d6d15d8c4730"},
+]
+
+[[package]]
+name = "ipykernel"
+version = "7.1.0"
+description = "IPython Kernel for Jupyter"
+optional = false
+python-versions = ">=3.10"
+groups = ["dev"]
+files = [
+    {file = "ipykernel-7.1.0-py3-none-any.whl", hash = "sha256:763b5ec6c5b7776f6a8d7ce09b267693b4e5ce75cb50ae696aaefb3c85e1ea4c"},
+    {file = "ipykernel-7.1.0.tar.gz", hash = "sha256:58a3fc88533d5930c3546dc7eac66c6d288acde4f801e2001e65edc5dc9cf0db"},
+]
+
+[package.dependencies]
+appnope = {version = ">=0.1.2", markers = "platform_system == \"Darwin\""}
+comm = ">=0.1.1"
+debugpy = ">=1.6.5"
+ipython = ">=7.23.1"
+jupyter-client = ">=8.0.0"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+matplotlib-inline = ">=0.1"
+nest-asyncio = ">=1.4"
+packaging = ">=22"
+psutil = ">=5.7"
+pyzmq = ">=25"
+tornado = ">=6.2"
+traitlets = ">=5.4.0"
+
+[package.extras]
+cov = ["coverage[toml]", "matplotlib", "pytest-cov", "trio"]
+docs = ["intersphinx-registry", "myst-parser", "pydata-sphinx-theme", "sphinx (<8.2.0)", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "trio"]
+pyqt5 = ["pyqt5"]
+pyside6 = ["pyside6"]
+test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0,<9)", "pytest-asyncio (>=0.23.5)", "pytest-cov", "pytest-timeout"]
+
+[[package]]
+name = "ipython"
+version = "9.8.0"
+description = "IPython: Productive Interactive Computing"
+optional = false
+python-versions = ">=3.11"
+groups = ["dev"]
+files = [
+    {file = "ipython-9.8.0-py3-none-any.whl", hash = "sha256:ebe6d1d58d7d988fbf23ff8ff6d8e1622cfdb194daf4b7b73b792c4ec3b85385"},
+    {file = "ipython-9.8.0.tar.gz", hash = "sha256:8e4ce129a627eb9dd221c41b1d2cdaed4ef7c9da8c17c63f6f578fe231141f83"},
+]
+
+[package.dependencies]
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+decorator = ">=4.3.2"
+ipython-pygments-lexers = ">=1.0.0"
+jedi = ">=0.18.1"
+matplotlib-inline = ">=0.1.5"
+pexpect = {version = ">4.3", markers = "sys_platform != \"win32\" and sys_platform != \"emscripten\""}
+prompt_toolkit = ">=3.0.41,<3.1.0"
+pygments = ">=2.11.0"
+stack_data = ">=0.6.0"
+traitlets = ">=5.13.0"
+
+[package.extras]
+all = ["ipython[doc,matplotlib,test,test-extra]"]
+black = ["black"]
+doc = ["docrepr", "exceptiongroup", "intersphinx_registry", "ipykernel", "ipython[matplotlib,test]", "setuptools (>=70.0)", "sphinx (>=8.0)", "sphinx-rtd-theme (>=0.1.8)", "sphinx_toml (==0.0.4)", "typing_extensions"]
+matplotlib = ["matplotlib (>3.9)"]
+test = ["packaging (>=20.1.0)", "pytest (>=7.0.0)", "pytest-asyncio (>=1.0.0)", "setuptools (>=61.2)", "testpath (>=0.2)"]
+test-extra = ["curio", "ipykernel (>6.30)", "ipython[matplotlib]", "ipython[test]", "jupyter_ai", "nbclient", "nbformat", "numpy (>=1.27)", "pandas (>2.1)", "trio (>=0.1.0)"]
+
+[[package]]
+name = "ipython-pygments-lexers"
+version = "1.1.1"
+description = "Defines a variety of Pygments lexers for highlighting IPython code."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "ipython_pygments_lexers-1.1.1-py3-none-any.whl", hash = "sha256:a9462224a505ade19a605f71f8fa63c2048833ce50abc86768a0d81d876dc81c"},
+    {file = "ipython_pygments_lexers-1.1.1.tar.gz", hash = "sha256:09c0138009e56b6854f9535736f4171d855c8c08a563a0dcd8022f78355c7e81"},
+]
+
+[package.dependencies]
+pygments = "*"
+
+[[package]]
+name = "isoduration"
+version = "20.11.0"
+description = "Operations with ISO 8601 durations"
+optional = false
+python-versions = ">=3.7"
+groups = ["dev"]
+files = [
+    {file = "isoduration-20.11.0-py3-none-any.whl", hash = "sha256:b2904c2a4228c3d44f409c8ae8e2370eb21a26f7ac2ec5446df141dde3452042"},
+    {file = "isoduration-20.11.0.tar.gz", hash = "sha256:ac2f9015137935279eac671f94f89eb00584f940f5dc49462a0c4ee692ba1bd9"},
+]
+
+[package.dependencies]
+arrow = ">=0.15.0"
+
 [[package]]
 name = "itsdangerous"
 version = "2.2.0"
@@ -1748,13 +2254,33 @@ files = [
     {file = "itsdangerous-2.2.0.tar.gz", hash = "sha256:e0050c0b7da1eea53ffaf149c0cfbb5c6e2e2b69c4bef22c81fa6eb73e5f6173"},
 ]
 
+[[package]]
+name = "jedi"
+version = "0.19.2"
+description = "An autocompletion tool for Python that can be used for text editors."
+optional = false
+python-versions = ">=3.6"
+groups = ["dev"]
+files = [
+    {file = "jedi-0.19.2-py2.py3-none-any.whl", hash = "sha256:a8ef22bde8490f57fe5c7681a3c83cb58874daf72b4784de3cce5b6ef6edb5b9"},
+    {file = "jedi-0.19.2.tar.gz", hash = "sha256:4770dc3de41bde3966b02eb84fbcf557fb33cce26ad23da12c742fb50ecb11f0"},
+]
+
+[package.dependencies]
+parso = ">=0.8.4,<0.9.0"
+
+[package.extras]
+docs = ["Jinja2 (==2.11.3)", "MarkupSafe (==1.1.1)", "Pygments (==2.8.1)", "alabaster (==0.7.12)", "babel (==2.9.1)", "chardet (==4.0.0)", "commonmark (==0.8.1)", "docutils (==0.17.1)", "future (==0.18.2)", "idna (==2.10)", "imagesize (==1.2.0)", "mock (==1.0.1)", "packaging (==20.9)", "pyparsing (==2.4.7)", "pytz (==2021.1)", "readthedocs-sphinx-ext (==2.1.4)", "recommonmark (==0.5.0)", "requests (==2.25.1)", "six (==1.15.0)", "snowballstemmer (==2.1.0)", "sphinx (==1.8.5)", "sphinx-rtd-theme (==0.4.3)", "sphinxcontrib-serializinghtml (==1.1.4)", "sphinxcontrib-websupport (==1.2.4)", "urllib3 (==1.26.4)"]
+qa = ["flake8 (==5.0.4)", "mypy (==0.971)", "types-setuptools (==67.2.0.1)"]
+testing = ["Django", "attrs", "colorama", "docopt", "pytest (<9.0.0)"]
+
 [[package]]
 name = "jinja2"
 version = "3.1.6"
 description = "A very fast and expressive template engine."
 optional = false
 python-versions = ">=3.7"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "jinja2-3.1.6-py3-none-any.whl", hash = "sha256:85ece4451f492d0c13c5dd7c13a64681a86afae63a5f347908daf103ce6d2f67"},
     {file = "jinja2-3.1.6.tar.gz", hash = "sha256:0137fb05990d35f1275a587e9aee6d56da821fc83491a0fb838183be43f66d6d"},
@@ -1903,6 +2429,18 @@ files = [
     {file = "joblib-1.5.2.tar.gz", hash = "sha256:3faa5c39054b2f03ca547da9b2f52fde67c06240c31853f306aea97f13647b55"},
 ]
 
+[[package]]
+name = "json5"
+version = "0.13.0"
+description = "A Python implementation of the JSON5 data format."
+optional = false
+python-versions = ">=3.8.0"
+groups = ["dev"]
+files = [
+    {file = "json5-0.13.0-py3-none-any.whl", hash = "sha256:9a08e1dd65f6a4d4c6fa82d216cf2477349ec2346a38fd70cc11d2557499fbcc"},
+    {file = "json5-0.13.0.tar.gz", hash = "sha256:b1edf8d487721c0bf64d83c28e91280781f6e21f4a797d3261c7c828d4c165bf"},
+]
+
 [[package]]
 name = "jsonpatch"
 version = "1.33"
@@ -1924,12 +2462,271 @@ version = "3.0.0"
 description = "Identify specific nodes in a JSON document (RFC 6901)"
 optional = false
 python-versions = ">=3.7"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "jsonpointer-3.0.0-py2.py3-none-any.whl", hash = "sha256:13e088adc14fca8b6aa8177c044e12701e6ad4b28ff10e65f2267a90109c9942"},
     {file = "jsonpointer-3.0.0.tar.gz", hash = "sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef"},
 ]
 
+[[package]]
+name = "jsonschema"
+version = "4.25.1"
+description = "An implementation of JSON Schema validation for Python"
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
+    {file = "jsonschema-4.25.1-py3-none-any.whl", hash = "sha256:3fba0169e345c7175110351d456342c364814cfcf3b964ba4587f22915230a63"},
+    {file = "jsonschema-4.25.1.tar.gz", hash = "sha256:e4a9655ce0da0c0b67a085847e00a3a51449e1157f4f75e9fb5aa545e122eb85"},
+]
+
+[package.dependencies]
+attrs = ">=22.2.0"
+fqdn = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+idna = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+isoduration = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+jsonpointer = {version = ">1.13", optional = true, markers = "extra == \"format-nongpl\""}
+jsonschema-specifications = ">=2023.03.6"
+referencing = ">=0.28.4"
+rfc3339-validator = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+rfc3986-validator = {version = ">0.1.0", optional = true, markers = "extra == \"format-nongpl\""}
+rfc3987-syntax = {version = ">=1.1.0", optional = true, markers = "extra == \"format-nongpl\""}
+rpds-py = ">=0.7.1"
+uri-template = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
+webcolors = {version = ">=24.6.0", optional = true, markers = "extra == \"format-nongpl\""}
+
+[package.extras]
+format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
+format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "rfc3987-syntax (>=1.1.0)", "uri-template", "webcolors (>=24.6.0)"]
+
+[[package]]
+name = "jsonschema-specifications"
+version = "2025.9.1"
+description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
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+    {file = "jsonschema_specifications-2025.9.1.tar.gz", hash = "sha256:b540987f239e745613c7a9176f3edb72b832a4ac465cf02712288397832b5e8d"},
+]
+
+[package.dependencies]
+referencing = ">=0.31.0"
+
+[[package]]
+name = "jupyter-client"
+version = "8.7.0"
+description = "Jupyter protocol implementation and client libraries"
+optional = false
+python-versions = ">=3.10"
+groups = ["dev"]
+files = [
+    {file = "jupyter_client-8.7.0-py3-none-any.whl", hash = "sha256:3671a94fd25e62f5f2f554f5e95389c2294d89822378a5f2dd24353e1494a9e0"},
+    {file = "jupyter_client-8.7.0.tar.gz", hash = "sha256:3357212d9cbe01209e59190f67a3a7e1f387a4f4e88d1e0433ad84d7b262531d"},
+]
+
+[package.dependencies]
+jupyter-core = ">=5.1"
+python-dateutil = ">=2.8.2"
+pyzmq = ">=25.0"
+tornado = ">=6.4.1"
+traitlets = ">=5.3"
+
+[package.extras]
+docs = ["ipykernel", "myst-parser", "pydata-sphinx-theme", "sphinx (>=4)", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
+test = ["anyio", "coverage", "ipykernel (>=6.14)", "mypy", "paramiko ; sys_platform == \"win32\"", "pre-commit", "pytest", "pytest-cov", "pytest-jupyter[client] (>=0.6.2)", "pytest-timeout"]
+
+[[package]]
+name = "jupyter-core"
+version = "5.9.1"
+description = "Jupyter core package. A base package on which Jupyter projects rely."
+optional = false
+python-versions = ">=3.10"
+groups = ["dev"]
+files = [
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+    {file = "jupyter_core-5.9.1.tar.gz", hash = "sha256:4d09aaff303b9566c3ce657f580bd089ff5c91f5f89cf7d8846c3cdf465b5508"},
+]
+
+[package.dependencies]
+platformdirs = ">=2.5"
+traitlets = ">=5.3"
+
+[package.extras]
+docs = ["intersphinx-registry", "myst-parser", "pydata-sphinx-theme", "sphinx-autodoc-typehints", "sphinxcontrib-spelling", "traitlets"]
+test = ["ipykernel", "pre-commit", "pytest (<9)", "pytest-cov", "pytest-timeout"]
+
+[[package]]
+name = "jupyter-events"
+version = "0.12.0"
+description = "Jupyter Event System library"
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
+    {file = "jupyter_events-0.12.0-py3-none-any.whl", hash = "sha256:6464b2fa5ad10451c3d35fabc75eab39556ae1e2853ad0c0cc31b656731a97fb"},
+    {file = "jupyter_events-0.12.0.tar.gz", hash = "sha256:fc3fce98865f6784c9cd0a56a20644fc6098f21c8c33834a8d9fe383c17e554b"},
+]
+
+[package.dependencies]
+jsonschema = {version = ">=4.18.0", extras = ["format-nongpl"]}
+packaging = "*"
+python-json-logger = ">=2.0.4"
+pyyaml = ">=5.3"
+referencing = "*"
+rfc3339-validator = "*"
+rfc3986-validator = ">=0.1.1"
+traitlets = ">=5.3"
+
+[package.extras]
+cli = ["click", "rich"]
+docs = ["jupyterlite-sphinx", "myst-parser", "pydata-sphinx-theme (>=0.16)", "sphinx (>=8)", "sphinxcontrib-spelling"]
+test = ["click", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.19.0)", "pytest-console-scripts", "rich"]
+
+[[package]]
+name = "jupyter-lsp"
+version = "2.3.0"
+description = "Multi-Language Server WebSocket proxy for Jupyter Notebook/Lab server"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "jupyter_lsp-2.3.0-py3-none-any.whl", hash = "sha256:e914a3cb2addf48b1c7710914771aaf1819d46b2e5a79b0f917b5478ec93f34f"},
+    {file = "jupyter_lsp-2.3.0.tar.gz", hash = "sha256:458aa59339dc868fb784d73364f17dbce8836e906cd75fd471a325cba02e0245"},
+]
+
+[package.dependencies]
+jupyter_server = ">=1.1.2"
+
+[[package]]
+name = "jupyter-server"
+version = "2.17.0"
+description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications."
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
+    {file = "jupyter_server-2.17.0-py3-none-any.whl", hash = "sha256:e8cb9c7db4251f51ed307e329b81b72ccf2056ff82d50524debde1ee1870e13f"},
+    {file = "jupyter_server-2.17.0.tar.gz", hash = "sha256:c38ea898566964c888b4772ae1ed58eca84592e88251d2cfc4d171f81f7e99d5"},
+]
+
+[package.dependencies]
+anyio = ">=3.1.0"
+argon2-cffi = ">=21.1"
+jinja2 = ">=3.0.3"
+jupyter-client = ">=7.4.4"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+jupyter-events = ">=0.11.0"
+jupyter-server-terminals = ">=0.4.4"
+nbconvert = ">=6.4.4"
+nbformat = ">=5.3.0"
+packaging = ">=22.0"
+prometheus-client = ">=0.9"
+pywinpty = {version = ">=2.0.1", markers = "os_name == \"nt\""}
+pyzmq = ">=24"
+send2trash = ">=1.8.2"
+terminado = ">=0.8.3"
+tornado = ">=6.2.0"
+traitlets = ">=5.6.0"
+websocket-client = ">=1.7"
+
+[package.extras]
+docs = ["ipykernel", "jinja2", "jupyter-client", "myst-parser", "nbformat", "prometheus-client", "pydata-sphinx-theme", "send2trash", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-openapi (>=0.8.0)", "sphinxcontrib-spelling", "sphinxemoji", "tornado", "typing-extensions"]
+test = ["flaky", "ipykernel", "pre-commit", "pytest (>=7.0,<9)", "pytest-console-scripts", "pytest-jupyter[server] (>=0.7)", "pytest-timeout", "requests"]
+
+[[package]]
+name = "jupyter-server-terminals"
+version = "0.5.3"
+description = "A Jupyter Server Extension Providing Terminals."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "jupyter_server_terminals-0.5.3-py3-none-any.whl", hash = "sha256:41ee0d7dc0ebf2809c668e0fc726dfaf258fcd3e769568996ca731b6194ae9aa"},
+    {file = "jupyter_server_terminals-0.5.3.tar.gz", hash = "sha256:5ae0295167220e9ace0edcfdb212afd2b01ee8d179fe6f23c899590e9b8a5269"},
+]
+
+[package.dependencies]
+pywinpty = {version = ">=2.0.3", markers = "os_name == \"nt\""}
+terminado = ">=0.8.3"
+
+[package.extras]
+docs = ["jinja2", "jupyter-server", "mistune (<4.0)", "myst-parser", "nbformat", "packaging", "pydata-sphinx-theme", "sphinxcontrib-github-alt", "sphinxcontrib-openapi", "sphinxcontrib-spelling", "sphinxemoji", "tornado"]
+test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (>=0.5.3)", "pytest-timeout"]
+
+[[package]]
+name = "jupyterlab"
+version = "4.5.1"
+description = "JupyterLab computational environment"
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
+    {file = "jupyterlab-4.5.1-py3-none-any.whl", hash = "sha256:31b059de96de0754ff1f2ce6279774b6aab8c34d7082e9752db58207c99bd514"},
+    {file = "jupyterlab-4.5.1.tar.gz", hash = "sha256:09da1ddfbd9eec18b5101dbb8515612aa1e47443321fb99503725a88e93d20d9"},
+]
+
+[package.dependencies]
+async-lru = ">=1.0.0"
+httpx = ">=0.25.0,<1"
+ipykernel = ">=6.5.0,<6.30.0 || >6.30.0"
+jinja2 = ">=3.0.3"
+jupyter-core = "*"
+jupyter-lsp = ">=2.0.0"
+jupyter-server = ">=2.4.0,<3"
+jupyterlab-server = ">=2.28.0,<3"
+notebook-shim = ">=0.2"
+packaging = "*"
+setuptools = ">=41.1.0"
+tornado = ">=6.2.0"
+traitlets = "*"
+
+[package.extras]
+dev = ["build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.11.12)"]
+docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-jupyter", "sphinx (>=1.8,<8.2.0)", "sphinx-copybutton"]
+docs-screenshots = ["altair (==6.0.0)", "ipython (==8.16.1)", "ipywidgets (==8.1.5)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.3.post1)", "matplotlib (==3.10.0)", "nbconvert (>=7.0.0)", "pandas (==2.2.3)", "scipy (==1.15.1)"]
+test = ["coverage", "pytest (>=7.0)", "pytest-check-links (>=0.7)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter (>=0.5.3)", "pytest-timeout", "pytest-tornasync", "requests", "requests-cache", "virtualenv"]
+upgrade-extension = ["copier (>=9,<10)", "jinja2-time (<0.3)", "pydantic (<3.0)", "pyyaml-include (<3.0)", "tomli-w (<2.0)"]
+
+[[package]]
+name = "jupyterlab-pygments"
+version = "0.3.0"
+description = "Pygments theme using JupyterLab CSS variables"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "jupyterlab_pygments-0.3.0-py3-none-any.whl", hash = "sha256:841a89020971da1d8693f1a99997aefc5dc424bb1b251fd6322462a1b8842780"},
+    {file = "jupyterlab_pygments-0.3.0.tar.gz", hash = "sha256:721aca4d9029252b11cfa9d185e5b5af4d54772bb8072f9b7036f4170054d35d"},
+]
+
+[[package]]
+name = "jupyterlab-server"
+version = "2.28.0"
+description = "A set of server components for JupyterLab and JupyterLab like applications."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "jupyterlab_server-2.28.0-py3-none-any.whl", hash = "sha256:e4355b148fdcf34d312bbbc80f22467d6d20460e8b8736bf235577dd18506968"},
+    {file = "jupyterlab_server-2.28.0.tar.gz", hash = "sha256:35baa81898b15f93573e2deca50d11ac0ae407ebb688299d3a5213265033712c"},
+]
+
+[package.dependencies]
+babel = ">=2.10"
+jinja2 = ">=3.0.3"
+json5 = ">=0.9.0"
+jsonschema = ">=4.18.0"
+jupyter-server = ">=1.21,<3"
+packaging = ">=21.3"
+requests = ">=2.31"
+
+[package.extras]
+docs = ["autodoc-traits", "jinja2 (<3.2.0)", "mistune (<4)", "myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-copybutton", "sphinxcontrib-openapi (>0.8)"]
+openapi = ["openapi-core (>=0.18.0,<0.19.0)", "ruamel-yaml"]
+test = ["hatch", "ipykernel", "openapi-core (>=0.18.0,<0.19.0)", "openapi-spec-validator (>=0.6.0,<0.8.0)", "pytest (>=7.0,<8)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter[server] (>=0.6.2)", "pytest-timeout", "requests-mock", "ruamel-yaml", "sphinxcontrib-spelling", "strict-rfc3339", "werkzeug"]
+
 [[package]]
 name = "kiwisolver"
 version = "1.4.9"
@@ -2276,6 +3073,24 @@ otel = ["opentelemetry-api (>=1.30.0)", "opentelemetry-exporter-otlp-proto-http
 pytest = ["pytest (>=7.0.0)", "rich (>=13.9.4)", "vcrpy (>=7.0.0)"]
 vcr = ["vcrpy (>=7.0.0)"]
 
+[[package]]
+name = "lark"
+version = "1.3.1"
+description = "a modern parsing library"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "lark-1.3.1-py3-none-any.whl", hash = "sha256:c629b661023a014c37da873b4ff58a817398d12635d3bbb2c5a03be7fe5d1e12"},
+    {file = "lark-1.3.1.tar.gz", hash = "sha256:b426a7a6d6d53189d318f2b6236ab5d6429eaf09259f1ca33eb716eed10d2905"},
+]
+
+[package.extras]
+atomic-cache = ["atomicwrites"]
+interegular = ["interegular (>=0.3.1,<0.4.0)"]
+nearley = ["js2py"]
+regex = ["regex"]
+
 [[package]]
 name = "mako"
 version = "1.3.10"
@@ -2302,7 +3117,7 @@ version = "3.0.3"
 description = "Safely add untrusted strings to HTML/XML markup."
 optional = false
 python-versions = ">=3.9"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "markupsafe-3.0.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:2f981d352f04553a7171b8e44369f2af4055f888dfb147d55e42d29e29e74559"},
     {file = "markupsafe-3.0.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e1c1493fb6e50ab01d20a22826e57520f1284df32f2d8601fdd90b6304601419"},
@@ -2494,6 +3309,36 @@ python-dateutil = ">=2.7"
 [package.extras]
 dev = ["meson-python (>=0.13.1,<0.17.0)", "pybind11 (>=2.13.2,!=2.13.3)", "setuptools (>=64)", "setuptools_scm (>=7)"]
 
+[[package]]
+name = "matplotlib-inline"
+version = "0.2.1"
+description = "Inline Matplotlib backend for Jupyter"
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
+    {file = "matplotlib_inline-0.2.1-py3-none-any.whl", hash = "sha256:d56ce5156ba6085e00a9d54fead6ed29a9c47e215cd1bba2e976ef39f5710a76"},
+    {file = "matplotlib_inline-0.2.1.tar.gz", hash = "sha256:e1ee949c340d771fc39e241ea75683deb94762c8fa5f2927ec57c83c4dffa9fe"},
+]
+
+[package.dependencies]
+traitlets = "*"
+
+[package.extras]
+test = ["flake8", "nbdime", "nbval", "notebook", "pytest"]
+
+[[package]]
+name = "mistune"
+version = "3.2.0"
+description = "A sane and fast Markdown parser with useful plugins and renderers"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "mistune-3.2.0-py3-none-any.whl", hash = "sha256:febdc629a3c78616b94393c6580551e0e34cc289987ec6c35ed3f4be42d0eee1"},
+    {file = "mistune-3.2.0.tar.gz", hash = "sha256:708487c8a8cdd99c9d90eb3ed4c3ed961246ff78ac82f03418f5183ab70e398a"},
+]
+
 [[package]]
 name = "mlflow"
 version = "3.7.0"
@@ -2775,18 +3620,142 @@ files = [
     {file = "mypy_extensions-1.1.0.tar.gz", hash = "sha256:52e68efc3284861e772bbcd66823fde5ae21fd2fdb51c62a211403730b916558"},
 ]
 
+[[package]]
+name = "nbclient"
+version = "0.10.4"
+description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor."
+optional = false
+python-versions = ">=3.10.0"
+groups = ["dev"]
+files = [
+    {file = "nbclient-0.10.4-py3-none-any.whl", hash = "sha256:9162df5a7373d70d606527300a95a975a47c137776cd942e52d9c7e29ff83440"},
+    {file = "nbclient-0.10.4.tar.gz", hash = "sha256:1e54091b16e6da39e297b0ece3e10f6f29f4ac4e8ee515d29f8a7099bd6553c9"},
+]
+
+[package.dependencies]
+jupyter-client = ">=6.1.12"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+nbformat = ">=5.1.3"
+traitlets = ">=5.4"
+
+[package.extras]
+dev = ["pre-commit"]
+docs = ["autodoc-traits", "flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "mock", "moto", "myst-parser", "nbconvert (>=7.1.0)", "pytest (>=9.0.1,<10)", "pytest-asyncio (>=1.3.0)", "pytest-cov (>=4.0)", "sphinx (>=1.7)", "sphinx-book-theme", "sphinxcontrib-spelling", "testpath", "xmltodict"]
+test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=7.1.0)", "pytest (>=9.0.1,<10)", "pytest-asyncio (>=1.3.0)", "pytest-cov (>=4.0)", "testpath", "xmltodict"]
+
+[[package]]
+name = "nbconvert"
+version = "7.16.6"
+description = "Converting Jupyter Notebooks (.ipynb files) to other formats.  Output formats include asciidoc, html, latex, markdown, pdf, py, rst, script.  nbconvert can be used both as a Python library (`import nbconvert`) or as a command line tool (invoked as `jupyter nbconvert ...`)."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
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+    {file = "nbconvert-7.16.6.tar.gz", hash = "sha256:576a7e37c6480da7b8465eefa66c17844243816ce1ccc372633c6b71c3c0f582"},
+]
+
+[package.dependencies]
+beautifulsoup4 = "*"
+bleach = {version = "!=5.0.0", extras = ["css"]}
+defusedxml = "*"
+jinja2 = ">=3.0"
+jupyter-core = ">=4.7"
+jupyterlab-pygments = "*"
+markupsafe = ">=2.0"
+mistune = ">=2.0.3,<4"
+nbclient = ">=0.5.0"
+nbformat = ">=5.7"
+packaging = "*"
+pandocfilters = ">=1.4.1"
+pygments = ">=2.4.1"
+traitlets = ">=5.1"
+
+[package.extras]
+all = ["flaky", "ipykernel", "ipython", "ipywidgets (>=7.5)", "myst-parser", "nbsphinx (>=0.2.12)", "playwright", "pydata-sphinx-theme", "pyqtwebengine (>=5.15)", "pytest (>=7)", "sphinx (==5.0.2)", "sphinxcontrib-spelling", "tornado (>=6.1)"]
+docs = ["ipykernel", "ipython", "myst-parser", "nbsphinx (>=0.2.12)", "pydata-sphinx-theme", "sphinx (==5.0.2)", "sphinxcontrib-spelling"]
+qtpdf = ["pyqtwebengine (>=5.15)"]
+qtpng = ["pyqtwebengine (>=5.15)"]
+serve = ["tornado (>=6.1)"]
+test = ["flaky", "ipykernel", "ipywidgets (>=7.5)", "pytest (>=7)"]
+webpdf = ["playwright"]
+
+[[package]]
+name = "nbformat"
+version = "5.10.4"
+description = "The Jupyter Notebook format"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "nbformat-5.10.4-py3-none-any.whl", hash = "sha256:3b48d6c8fbca4b299bf3982ea7db1af21580e4fec269ad087b9e81588891200b"},
+    {file = "nbformat-5.10.4.tar.gz", hash = "sha256:322168b14f937a5d11362988ecac2a4952d3d8e3a2cbeb2319584631226d5b3a"},
+]
+
+[package.dependencies]
+fastjsonschema = ">=2.15"
+jsonschema = ">=2.6"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+traitlets = ">=5.1"
+
+[package.extras]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
+test = ["pep440", "pre-commit", "pytest", "testpath"]
+
 [[package]]
 name = "nest-asyncio"
 version = "1.6.0"
 description = "Patch asyncio to allow nested event loops"
 optional = false
 python-versions = ">=3.5"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "nest_asyncio-1.6.0-py3-none-any.whl", hash = "sha256:87af6efd6b5e897c81050477ef65c62e2b2f35d51703cae01aff2905b1852e1c"},
     {file = "nest_asyncio-1.6.0.tar.gz", hash = "sha256:6f172d5449aca15afd6c646851f4e31e02c598d553a667e38cafa997cfec55fe"},
 ]
 
+[[package]]
+name = "notebook"
+version = "7.5.1"
+description = "Jupyter Notebook - A web-based notebook environment for interactive computing"
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
+    {file = "notebook-7.5.1-py3-none-any.whl", hash = "sha256:f4e2451c19910c33b88709b84537e11f6368c1cdff1aa0c43db701aea535dd44"},
+    {file = "notebook-7.5.1.tar.gz", hash = "sha256:b2fb4cef4d47d08c33aecce1c6c6e84be05436fbd791f88fce8df9fbca088b75"},
+]
+
+[package.dependencies]
+jupyter-server = ">=2.4.0,<3"
+jupyterlab = ">=4.5.1,<4.6"
+jupyterlab-server = ">=2.28.0,<3"
+notebook-shim = ">=0.2,<0.3"
+tornado = ">=6.2.0"
+
+[package.extras]
+dev = ["hatch", "pre-commit"]
+docs = ["myst-parser", "nbsphinx", "pydata-sphinx-theme", "sphinx (>=1.3.6)", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
+test = ["importlib-resources (>=5.0) ; python_version < \"3.10\"", "ipykernel", "jupyter-server[test] (>=2.4.0,<3)", "jupyterlab-server[test] (>=2.28.0,<3)", "nbval", "pytest (>=7.0)", "pytest-console-scripts", "pytest-timeout", "pytest-tornasync", "requests"]
+
+[[package]]
+name = "notebook-shim"
+version = "0.2.4"
+description = "A shim layer for notebook traits and config"
+optional = false
+python-versions = ">=3.7"
+groups = ["dev"]
+files = [
+    {file = "notebook_shim-0.2.4-py3-none-any.whl", hash = "sha256:411a5be4e9dc882a074ccbcae671eda64cceb068767e9a3419096986560e1cef"},
+    {file = "notebook_shim-0.2.4.tar.gz", hash = "sha256:b4b2cfa1b65d98307ca24361f5b30fe785b53c3fd07b7a47e89acb5e6ac638cb"},
+]
+
+[package.dependencies]
+jupyter-server = ">=1.8,<3"
+
+[package.extras]
+test = ["pytest", "pytest-console-scripts", "pytest-jupyter", "pytest-tornasync"]
+
 [[package]]
 name = "numpy"
 version = "2.3.5"
@@ -3125,7 +4094,7 @@ version = "25.0"
 description = "Core utilities for Python packages"
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "packaging-25.0-py3-none-any.whl", hash = "sha256:29572ef2b1f17581046b3a2227d5c611fb25ec70ca1ba8554b24b0e69331a484"},
     {file = "packaging-25.0.tar.gz", hash = "sha256:d443872c98d677bf60f6a1f2f8c1cb748e8fe762d2bf9d3148b5599295b0fc4f"},
@@ -3227,6 +4196,50 @@ sql-other = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-d
 test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)"]
 xml = ["lxml (>=4.9.2)"]
 
+[[package]]
+name = "pandocfilters"
+version = "1.5.1"
+description = "Utilities for writing pandoc filters in python"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+groups = ["dev"]
+files = [
+    {file = "pandocfilters-1.5.1-py2.py3-none-any.whl", hash = "sha256:93be382804a9cdb0a7267585f157e5d1731bbe5545a85b268d6f5fe6232de2bc"},
+    {file = "pandocfilters-1.5.1.tar.gz", hash = "sha256:002b4a555ee4ebc03f8b66307e287fa492e4a77b4ea14d3f934328297bb4939e"},
+]
+
+[[package]]
+name = "parso"
+version = "0.8.5"
+description = "A Python Parser"
+optional = false
+python-versions = ">=3.6"
+groups = ["dev"]
+files = [
+    {file = "parso-0.8.5-py2.py3-none-any.whl", hash = "sha256:646204b5ee239c396d040b90f9e272e9a8017c630092bf59980beb62fd033887"},
+    {file = "parso-0.8.5.tar.gz", hash = "sha256:034d7354a9a018bdce352f48b2a8a450f05e9d6ee85db84764e9b6bd96dafe5a"},
+]
+
+[package.extras]
+qa = ["flake8 (==5.0.4)", "mypy (==0.971)", "types-setuptools (==67.2.0.1)"]
+testing = ["docopt", "pytest"]
+
+[[package]]
+name = "pexpect"
+version = "4.9.0"
+description = "Pexpect allows easy control of interactive console applications."
+optional = false
+python-versions = "*"
+groups = ["dev"]
+markers = "sys_platform != \"win32\" and sys_platform != \"emscripten\""
+files = [
+    {file = "pexpect-4.9.0-py2.py3-none-any.whl", hash = "sha256:7236d1e080e4936be2dc3e326cec0af72acf9212a7e1d060210e70a47e253523"},
+    {file = "pexpect-4.9.0.tar.gz", hash = "sha256:ee7d41123f3c9911050ea2c2dac107568dc43b2d3b0c7557a33212c398ead30f"},
+]
+
+[package.dependencies]
+ptyprocess = ">=0.5"
+
 [[package]]
 name = "pillow"
 version = "12.0.0"
@@ -3342,7 +4355,7 @@ version = "4.5.1"
 description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`."
 optional = false
 python-versions = ">=3.10"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "platformdirs-4.5.1-py3-none-any.whl", hash = "sha256:d03afa3963c806a9bed9d5125c8f4cb2fdaf74a55ab60e5d59b3fde758104d31"},
     {file = "platformdirs-4.5.1.tar.gz", hash = "sha256:61d5cdcc6065745cdd94f0f878977f8de9437be93de97c1c12f853c9c0cdcbda"},
@@ -3353,6 +4366,52 @@ docs = ["furo (>=2025.9.25)", "proselint (>=0.14)", "sphinx (>=8.2.3)", "sphinx-
 test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=8.4.2)", "pytest-cov (>=7)", "pytest-mock (>=3.15.1)"]
 type = ["mypy (>=1.18.2)"]
 
+[[package]]
+name = "pluggy"
+version = "1.6.0"
+description = "plugin and hook calling mechanisms for python"
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
+    {file = "pluggy-1.6.0-py3-none-any.whl", hash = "sha256:e920276dd6813095e9377c0bc5566d94c932c33b27a3e3945d8389c374dd4746"},
+    {file = "pluggy-1.6.0.tar.gz", hash = "sha256:7dcc130b76258d33b90f61b658791dede3486c3e6bfb003ee5c9bfb396dd22f3"},
+]
+
+[package.extras]
+dev = ["pre-commit", "tox"]
+testing = ["coverage", "pytest", "pytest-benchmark"]
+
+[[package]]
+name = "prometheus-client"
+version = "0.23.1"
+description = "Python client for the Prometheus monitoring system."
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
+    {file = "prometheus_client-0.23.1-py3-none-any.whl", hash = "sha256:dd1913e6e76b59cfe44e7a4b83e01afc9873c1bdfd2ed8739f1e76aeca115f99"},
+    {file = "prometheus_client-0.23.1.tar.gz", hash = "sha256:6ae8f9081eaaaf153a2e959d2e6c4f4fb57b12ef76c8c7980202f1e57b48b2ce"},
+]
+
+[package.extras]
+twisted = ["twisted"]
+
+[[package]]
+name = "prompt-toolkit"
+version = "3.0.52"
+description = "Library for building powerful interactive command lines in Python"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "prompt_toolkit-3.0.52-py3-none-any.whl", hash = "sha256:9aac639a3bbd33284347de5ad8d68ecc044b91a762dc39b7c21095fcd6a19955"},
+    {file = "prompt_toolkit-3.0.52.tar.gz", hash = "sha256:28cde192929c8e7321de85de1ddbe736f1375148b02f2e17edd840042b1be855"},
+]
+
+[package.dependencies]
+wcwidth = "*"
+
 [[package]]
 name = "propcache"
 version = "0.4.1"
@@ -3504,6 +4563,69 @@ files = [
     {file = "protobuf-6.31.1.tar.gz", hash = "sha256:d8cac4c982f0b957a4dc73a80e2ea24fab08e679c0de9deb835f4a12d69aca9a"},
 ]
 
+[[package]]
+name = "psutil"
+version = "7.2.1"
+description = "Cross-platform lib for process and system monitoring."
+optional = false
+python-versions = ">=3.6"
+groups = ["dev"]
+files = [
+    {file = "psutil-7.2.1-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:ba9f33bb525b14c3ea563b2fd521a84d2fa214ec59e3e6a2858f78d0844dd60d"},
+    {file = "psutil-7.2.1-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:81442dac7abfc2f4f4385ea9e12ddf5a796721c0f6133260687fec5c3780fa49"},
+    {file = "psutil-7.2.1-cp313-cp313t-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ea46c0d060491051d39f0d2cff4f98d5c72b288289f57a21556cc7d504db37fc"},
+    {file = "psutil-7.2.1-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:35630d5af80d5d0d49cfc4d64c1c13838baf6717a13effb35869a5919b854cdf"},
+    {file = "psutil-7.2.1-cp313-cp313t-win_amd64.whl", hash = "sha256:923f8653416604e356073e6e0bccbe7c09990acef442def2f5640dd0faa9689f"},
+    {file = "psutil-7.2.1-cp313-cp313t-win_arm64.whl", hash = "sha256:cfbe6b40ca48019a51827f20d830887b3107a74a79b01ceb8cc8de4ccb17b672"},
+    {file = "psutil-7.2.1-cp314-cp314t-macosx_10_15_x86_64.whl", hash = "sha256:494c513ccc53225ae23eec7fe6e1482f1b8a44674241b54561f755a898650679"},
+    {file = "psutil-7.2.1-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:3fce5f92c22b00cdefd1645aa58ab4877a01679e901555067b1bd77039aa589f"},
+    {file = "psutil-7.2.1-cp314-cp314t-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:93f3f7b0bb07711b49626e7940d6fe52aa9940ad86e8f7e74842e73189712129"},
+    {file = "psutil-7.2.1-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d34d2ca888208eea2b5c68186841336a7f5e0b990edec929be909353a202768a"},
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+    {file = "psutil-7.2.1-cp314-cp314t-win_arm64.whl", hash = "sha256:08a2f175e48a898c8eb8eace45ce01777f4785bc744c90aa2cc7f2fa5462a266"},
+    {file = "psutil-7.2.1-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:b2e953fcfaedcfbc952b44744f22d16575d3aa78eb4f51ae74165b4e96e55f42"},
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+    {file = "psutil-7.2.1-cp37-abi3-win_amd64.whl", hash = "sha256:b1b0671619343aa71c20ff9767eced0483e4fc9e1f489d50923738caf6a03c17"},
+    {file = "psutil-7.2.1-cp37-abi3-win_arm64.whl", hash = "sha256:0d67c1822c355aa6f7314d92018fb4268a76668a536f133599b91edd48759442"},
+    {file = "psutil-7.2.1.tar.gz", hash = "sha256:f7583aec590485b43ca601dd9cea0dcd65bd7bb21d30ef4ddbf4ea6b5ed1bdd3"},
+]
+
+[package.extras]
+dev = ["abi3audit", "black", "check-manifest", "coverage", "packaging", "psleak", "pylint", "pyperf", "pypinfo", "pytest", "pytest-cov", "pytest-instafail", "pytest-xdist", "requests", "rstcheck", "ruff", "setuptools", "sphinx", "sphinx_rtd_theme", "toml-sort", "twine", "validate-pyproject[all]", "virtualenv", "vulture", "wheel"]
+test = ["psleak", "pytest", "pytest-instafail", "pytest-xdist", "setuptools"]
+
+[[package]]
+name = "ptyprocess"
+version = "0.7.0"
+description = "Run a subprocess in a pseudo terminal"
+optional = false
+python-versions = "*"
+groups = ["dev"]
+markers = "os_name != \"nt\" or sys_platform != \"win32\" and sys_platform != \"emscripten\""
+files = [
+    {file = "ptyprocess-0.7.0-py2.py3-none-any.whl", hash = "sha256:4b41f3967fce3af57cc7e94b888626c18bf37a083e3651ca8feeb66d492fef35"},
+    {file = "ptyprocess-0.7.0.tar.gz", hash = "sha256:5c5d0a3b48ceee0b48485e0c26037c0acd7d29765ca3fbb5cb3831d347423220"},
+]
+
+[[package]]
+name = "pure-eval"
+version = "0.2.3"
+description = "Safely evaluate AST nodes without side effects"
+optional = false
+python-versions = "*"
+groups = ["dev"]
+files = [
+    {file = "pure_eval-0.2.3-py3-none-any.whl", hash = "sha256:1db8e35b67b3d218d818ae653e27f06c3aa420901fa7b081ca98cbedc874e0d0"},
+    {file = "pure_eval-0.2.3.tar.gz", hash = "sha256:5f4e983f40564c576c7c8635ae88db5956bb2229d7e9237d03b3c0b0190eaf42"},
+]
+
+[package.extras]
+tests = ["pytest"]
+
 [[package]]
 name = "py4j"
 version = "0.10.9.9"
@@ -3610,12 +4732,12 @@ version = "2.23"
 description = "C parser in Python"
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
-markers = "platform_python_implementation != \"PyPy\" and implementation_name != \"PyPy\""
+groups = ["main", "dev"]
 files = [
     {file = "pycparser-2.23-py3-none-any.whl", hash = "sha256:e5c6e8d3fbad53479cab09ac03729e0a9faf2bee3db8208a550daf5af81a5934"},
     {file = "pycparser-2.23.tar.gz", hash = "sha256:78816d4f24add8f10a06d6f05b4d424ad9e96cfebf68a4ddc99c65c0720d00c2"},
 ]
+markers = {main = "platform_python_implementation != \"PyPy\" and implementation_name != \"PyPy\"", dev = "implementation_name != \"PyPy\""}
 
 [[package]]
 name = "pydantic"
@@ -3797,6 +4919,21 @@ gcp-secret-manager = ["google-cloud-secret-manager (>=2.23.1)"]
 toml = ["tomli (>=2.0.1)"]
 yaml = ["pyyaml (>=6.0.1)"]
 
+[[package]]
+name = "pygments"
+version = "2.19.2"
+description = "Pygments is a syntax highlighting package written in Python."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "pygments-2.19.2-py3-none-any.whl", hash = "sha256:86540386c03d588bb81d44bc3928634ff26449851e99741617ecb9037ee5ec0b"},
+    {file = "pygments-2.19.2.tar.gz", hash = "sha256:636cb2477cec7f8952536970bc533bc43743542f70392ae026374600add5b887"},
+]
+
+[package.extras]
+windows-terminal = ["colorama (>=0.4.6)"]
+
 [[package]]
 name = "pyjwt"
 version = "2.10.1"
@@ -3850,13 +4987,75 @@ files = [
 [package.extras]
 diagrams = ["jinja2", "railroad-diagrams"]
 
+[[package]]
+name = "pytest"
+version = "9.0.2"
+description = "pytest: simple powerful testing with Python"
+optional = false
+python-versions = ">=3.10"
+groups = ["dev"]
+files = [
+    {file = "pytest-9.0.2-py3-none-any.whl", hash = "sha256:711ffd45bf766d5264d487b917733b453d917afd2b0ad65223959f59089f875b"},
+    {file = "pytest-9.0.2.tar.gz", hash = "sha256:75186651a92bd89611d1d9fc20f0b4345fd827c41ccd5c299a868a05d70edf11"},
+]
+
+[package.dependencies]
+colorama = {version = ">=0.4", markers = "sys_platform == \"win32\""}
+iniconfig = ">=1.0.1"
+packaging = ">=22"
+pluggy = ">=1.5,<2"
+pygments = ">=2.7.2"
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+[[package]]
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+description = "Send file to trash natively under Mac OS X, Windows and Linux"
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+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*"
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+[package.extras]
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+objc = ["pyobjc-framework-Cocoa ; sys_platform == \"darwin\""]
+win32 = ["pywin32 ; sys_platform == \"win32\""]
+
 [[package]]
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 version = "80.9.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
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 python-versions = ">=3.9"
-groups = ["main"]
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 description = "Python 2 and 3 compatibility utilities"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
-groups = ["main"]
+groups = ["main", "dev"]
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 ]
 
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+python-versions = ">=3.9"
+groups = ["dev"]
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+
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 version = "2.0.45"
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 dev = ["build"]
 doc = ["sphinx"]
 
+[[package]]
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+version = "0.6.3"
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+optional = false
+python-versions = "*"
+groups = ["dev"]
+files = [
+    {file = "stack_data-0.6.3-py3-none-any.whl", hash = "sha256:d5558e0c25a4cb0853cddad3d77da9891a08cb85dd9f9f91b9f8cd66e511e695"},
+    {file = "stack_data-0.6.3.tar.gz", hash = "sha256:836a778de4fec4dcd1dcd89ed8abff8a221f58308462e1c4aa2a3cf30148f0b9"},
+]
+
+[package.dependencies]
+asttokens = ">=2.1.0"
+executing = ">=1.2.0"
+pure-eval = "*"
+
+[package.extras]
+tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
+
 [[package]]
 name = "starlette"
 version = "0.50.0"
@@ -4678,6 +6253,28 @@ files = [
 doc = ["reno", "sphinx"]
 test = ["pytest", "tornado (>=4.5)", "typeguard"]
 
+[[package]]
+name = "terminado"
+version = "0.18.1"
+description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library."
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "terminado-0.18.1-py3-none-any.whl", hash = "sha256:a4468e1b37bb318f8a86514f65814e1afc977cf29b3992a4500d9dd305dcceb0"},
+    {file = "terminado-0.18.1.tar.gz", hash = "sha256:de09f2c4b85de4765f7714688fff57d3e75bad1f909b589fde880460c753fd2e"},
+]
+
+[package.dependencies]
+ptyprocess = {version = "*", markers = "os_name != \"nt\""}
+pywinpty = {version = ">=1.1.0", markers = "os_name == \"nt\""}
+tornado = ">=6.1.0"
+
+[package.extras]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
+test = ["pre-commit", "pytest (>=7.0)", "pytest-timeout"]
+typing = ["mypy (>=1.6,<2.0)", "traitlets (>=5.11.1)"]
+
 [[package]]
 name = "threadpoolctl"
 version = "3.6.0"
@@ -4764,6 +6361,25 @@ requests = ">=2.26.0"
 [package.extras]
 blobfile = ["blobfile (>=2)"]
 
+[[package]]
+name = "tinycss2"
+version = "1.4.0"
+description = "A tiny CSS parser"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "tinycss2-1.4.0-py3-none-any.whl", hash = "sha256:3a49cf47b7675da0b15d0c6e1df8df4ebd96e9394bb905a5775adb0d884c5289"},
+    {file = "tinycss2-1.4.0.tar.gz", hash = "sha256:10c0972f6fc0fbee87c3edb76549357415e94548c1ae10ebccdea16fb404a9b7"},
+]
+
+[package.dependencies]
+webencodings = ">=0.4"
+
+[package.extras]
+doc = ["sphinx", "sphinx_rtd_theme"]
+test = ["pytest", "ruff"]
+
 [[package]]
 name = "tomlkit"
 version = "0.13.3"
@@ -4776,6 +6392,28 @@ files = [
     {file = "tomlkit-0.13.3.tar.gz", hash = "sha256:430cf247ee57df2b94ee3fbe588e71d362a941ebb545dec29b53961d61add2a1"},
 ]
 
+[[package]]
+name = "tornado"
+version = "6.5.4"
+description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
+    {file = "tornado-6.5.4-cp39-abi3-macosx_10_9_universal2.whl", hash = "sha256:d6241c1a16b1c9e4cc28148b1cda97dd1c6cb4fb7068ac1bedc610768dff0ba9"},
+    {file = "tornado-6.5.4-cp39-abi3-macosx_10_9_x86_64.whl", hash = "sha256:2d50f63dda1d2cac3ae1fa23d254e16b5e38153758470e9956cbc3d813d40843"},
+    {file = "tornado-6.5.4-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d1cf66105dc6acb5af613c054955b8137e34a03698aa53272dbda4afe252be17"},
+    {file = "tornado-6.5.4-cp39-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:50ff0a58b0dc97939d29da29cd624da010e7f804746621c78d14b80238669335"},
+    {file = "tornado-6.5.4-cp39-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e5fb5e04efa54cf0baabdd10061eb4148e0be137166146fff835745f59ab9f7f"},
+    {file = "tornado-6.5.4-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:9c86b1643b33a4cd415f8d0fe53045f913bf07b4a3ef646b735a6a86047dda84"},
+    {file = "tornado-6.5.4-cp39-abi3-musllinux_1_2_i686.whl", hash = "sha256:6eb82872335a53dd063a4f10917b3efd28270b56a33db69009606a0312660a6f"},
+    {file = "tornado-6.5.4-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:6076d5dda368c9328ff41ab5d9dd3608e695e8225d1cd0fd1e006f05da3635a8"},
+    {file = "tornado-6.5.4-cp39-abi3-win32.whl", hash = "sha256:1768110f2411d5cd281bac0a090f707223ce77fd110424361092859e089b38d1"},
+    {file = "tornado-6.5.4-cp39-abi3-win_amd64.whl", hash = "sha256:fa07d31e0cd85c60713f2b995da613588aa03e1303d75705dca6af8babc18ddc"},
+    {file = "tornado-6.5.4-cp39-abi3-win_arm64.whl", hash = "sha256:053e6e16701eb6cbe641f308f4c1a9541f91b6261991160391bfc342e8a551a1"},
+    {file = "tornado-6.5.4.tar.gz", hash = "sha256:a22fa9047405d03260b483980635f0b041989d8bcc9a313f8fe18b411d84b1d7"},
+]
+
 [[package]]
 name = "tqdm"
 version = "4.67.1"
@@ -4799,13 +6437,29 @@ notebook = ["ipywidgets (>=6)"]
 slack = ["slack-sdk"]
 telegram = ["requests"]
 
+[[package]]
+name = "traitlets"
+version = "5.14.3"
+description = "Traitlets Python configuration system"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
+    {file = "traitlets-5.14.3-py3-none-any.whl", hash = "sha256:b74e89e397b1ed28cc831db7aea759ba6640cb3de13090ca145426688ff1ac4f"},
+    {file = "traitlets-5.14.3.tar.gz", hash = "sha256:9ed0579d3502c94b4b3732ac120375cda96f923114522847de4b3bb98b96b6b7"},
+]
+
+[package.extras]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
+test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,<8.2)", "pytest-mock", "pytest-mypy-testing"]
+
 [[package]]
 name = "typing-extensions"
 version = "4.15.0"
 description = "Backported and Experimental Type Hints for Python 3.9+"
 optional = false
 python-versions = ">=3.9"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "typing_extensions-4.15.0-py3-none-any.whl", hash = "sha256:f0fa19c6845758ab08074a0cfa8b7aecb71c999ca73d62883bc25cc018c4e548"},
     {file = "typing_extensions-4.15.0.tar.gz", hash = "sha256:0cea48d173cc12fa28ecabc3b837ea3cf6f38c6d1136f85cbaaf598984861466"},
@@ -4848,7 +6502,7 @@ version = "2025.2"
 description = "Provider of IANA time zone data"
 optional = false
 python-versions = ">=2"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "tzdata-2025.2-py2.py3-none-any.whl", hash = "sha256:1a403fada01ff9221ca8044d701868fa132215d84beb92242d9acd2147f667a8"},
     {file = "tzdata-2025.2.tar.gz", hash = "sha256:b60a638fcc0daffadf82fe0f57e53d06bdec2f36c4df66280ae79bce6bd6f2b9"},
@@ -4944,13 +6598,28 @@ databricks = ["unitycatalog-ai[databricks]"]
 databricks-dev = ["databricks-langchain", "langgraph", "unitycatalog-ai[databricks-dev]"]
 dev = ["databricks-langchain", "langgraph", "unitycatalog-ai[dev]"]
 
+[[package]]
+name = "uri-template"
+version = "1.3.0"
+description = "RFC 6570 URI Template Processor"
+optional = false
+python-versions = ">=3.7"
+groups = ["dev"]
+files = [
+    {file = "uri-template-1.3.0.tar.gz", hash = "sha256:0e00f8eb65e18c7de20d595a14336e9f337ead580c70934141624b6d1ffdacc7"},
+    {file = "uri_template-1.3.0-py3-none-any.whl", hash = "sha256:a44a133ea12d44a0c0f06d7d42a52d71282e77e2f937d8abd5655b8d56fc1363"},
+]
+
+[package.extras]
+dev = ["flake8", "flake8-annotations", "flake8-bandit", "flake8-bugbear", "flake8-commas", "flake8-comprehensions", "flake8-continuation", "flake8-datetimez", "flake8-docstrings", "flake8-import-order", "flake8-literal", "flake8-modern-annotations", "flake8-noqa", "flake8-pyproject", "flake8-requirements", "flake8-typechecking-import", "flake8-use-fstring", "mypy", "pep8-naming", "types-PyYAML"]
+
 [[package]]
 name = "urllib3"
 version = "2.6.2"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
 python-versions = ">=3.9"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "urllib3-2.6.2-py3-none-any.whl", hash = "sha256:ec21cddfe7724fc7cb4ba4bea7aa8e2ef36f607a4bab81aa6ce42a13dc3f03dd"},
     {file = "urllib3-2.6.2.tar.gz", hash = "sha256:016f9c98bb7e98085cb2b4b17b87d2c702975664e4f060c6532e64d1c1a5e797"},
@@ -5030,6 +6699,59 @@ files = [
 docs = ["Sphinx (>=1.8.1)", "docutils", "pylons-sphinx-themes (>=1.0.9)"]
 testing = ["coverage (>=7.6.0)", "pytest", "pytest-cov"]
 
+[[package]]
+name = "wcwidth"
+version = "0.2.14"
+description = "Measures the displayed width of unicode strings in a terminal"
+optional = false
+python-versions = ">=3.6"
+groups = ["dev"]
+files = [
+    {file = "wcwidth-0.2.14-py2.py3-none-any.whl", hash = "sha256:a7bb560c8aee30f9957e5f9895805edd20602f2d7f720186dfd906e82b4982e1"},
+    {file = "wcwidth-0.2.14.tar.gz", hash = "sha256:4d478375d31bc5395a3c55c40ccdf3354688364cd61c4f6adacaa9215d0b3605"},
+]
+
+[[package]]
+name = "webcolors"
+version = "25.10.0"
+description = "A library for working with the color formats defined by HTML and CSS."
+optional = false
+python-versions = ">=3.10"
+groups = ["dev"]
+files = [
+    {file = "webcolors-25.10.0-py3-none-any.whl", hash = "sha256:032c727334856fc0b968f63daa252a1ac93d33db2f5267756623c210e57a4f1d"},
+    {file = "webcolors-25.10.0.tar.gz", hash = "sha256:62abae86504f66d0f6364c2a8520de4a0c47b80c03fc3a5f1815fedbef7c19bf"},
+]
+
+[[package]]
+name = "webencodings"
+version = "0.5.1"
+description = "Character encoding aliases for legacy web content"
+optional = false
+python-versions = "*"
+groups = ["dev"]
+files = [
+    {file = "webencodings-0.5.1-py2.py3-none-any.whl", hash = "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78"},
+    {file = "webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"},
+]
+
+[[package]]
+name = "websocket-client"
+version = "1.9.0"
+description = "WebSocket client for Python with low level API options"
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
+    {file = "websocket_client-1.9.0-py3-none-any.whl", hash = "sha256:af248a825037ef591efbf6ed20cc5faa03d3b47b9e5a2230a529eeee1c1fc3ef"},
+    {file = "websocket_client-1.9.0.tar.gz", hash = "sha256:9e813624b6eb619999a97dc7958469217c3176312b3a16a4bd1bc7e08a46ec98"},
+]
+
+[package.extras]
+docs = ["Sphinx (>=6.0)", "myst-parser (>=2.0.0)", "sphinx_rtd_theme (>=1.1.0)"]
+optional = ["python-socks", "wsaccel"]
+test = ["pytest", "websockets"]
+
 [[package]]
 name = "werkzeug"
 version = "3.1.4"
@@ -5493,4 +7215,4 @@ cffi = ["cffi (>=1.17,<2.0) ; platform_python_implementation != \"PyPy\" and pyt
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.12,<3.14"
-content-hash = "f8d46d5d030a1737cbbf62f043da37eae551a108faffa442fd4a4619777a374f"
+content-hash = "feecaf95150c592328f8e9a1ac0f74bd371ce92cc482c74061a9fc2e715d9c8f"
diff --git a/pyproject.toml b/pyproject.toml
index 46ff902..f01f75c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -24,6 +24,14 @@ databricks-langchain = ">=0.1.0"
 sqlglot = ">=20.0.0"
 pydantic = ">=2.0.0"
 typing_extensions = ">=4.15.0"
+mlflow = ">=2.10.0"
+
+[tool.poetry.group.dev.dependencies]
+pytest = ">=7.0.0"
+pytest-cov = ">=4.0.0"
+pytest-asyncio = ">=0.21.0"
+notebook = ">=6.5.0"
+ipykernel = ">=6.25.0"
 
 [build-system]
 requires = ["poetry-core"]
diff --git a/requirements.txt b/requirements.txt
index a670df2..cd04628 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,6 +1,8 @@
 # Snowflake dependencies (for data extraction)
 snowflake-connector-python>=3.0.0
 snowflake-snowpark-python>=1.0.0
+requests>=2.31.0
+typing-extensions>=4.15.0
 python-dotenv>=1.0.0
 
 # Translation graph dependencies
@@ -11,8 +13,10 @@ langgraph>=0.1.0
 sqlglot>=20.0.0
 pydantic>=2.0.0
 
-# Databricks LLM support
+# Databricks LLM support & Evaluation
 databricks-langchain>=0.1.0
+databricks-sdk>=0.1.0
+mlflow>=2.10.0
 
 # Environment variable management
 python-dotenv>=1.0.0
diff --git a/run_local_benchmark.py b/run_local_benchmark.py
new file mode 100755
index 0000000..2031d15
--- /dev/null
+++ b/run_local_benchmark.py
@@ -0,0 +1,119 @@
+#!/usr/bin/env python3
+"""
+Run evaluation benchmark locally with Databricks connection.
+
+Usage:
+    python3 run_local_benchmark.py
+    python3 run_local_benchmark.py --artifact-type tables --batch-size 5
+"""
+
+import os
+import sys
+import argparse
+import logging
+from pathlib import Path
+
+from dotenv import load_dotenv
+
+# Load .env from project root
+env_path = Path(__file__).parent / ".env"
+if env_path.exists():
+    load_dotenv(env_path)
+    print(f"✅ Loaded .env from: {env_path}")
+
+# Add src to path
+sys.path.insert(0, str(Path(__file__).parent / "src"))
+
+import mlflow
+from databricks_langchain import ChatDatabricks
+
+from artifact_translation_package.evaluation import run_benchmark, ModelConfig
+from artifact_translation_package.evaluation.model_benchmark import create_default_model_configs
+
+
+def get_experiment_name(custom_name: str = None) -> str:
+    """Get experiment name, auto-detecting user if not provided."""
+    if custom_name:
+        return custom_name
+    try:
+        from databricks.sdk import WorkspaceClient
+        username = WorkspaceClient().current_user.me().user_name
+        return f"/Users/{username}/sql-translation-benchmark"
+    except Exception:
+        return "/Shared/sql-translation-benchmark"
+
+
+def setup_mlflow(experiment_name: str) -> str:
+    """Configure MLflow with Databricks tracking."""
+    mlflow.set_tracking_uri("databricks")
+    
+    try:
+        mlflow.set_experiment(experiment_name)
+    except Exception:
+        mlflow.create_experiment(experiment_name)
+        mlflow.set_experiment(experiment_name)
+    
+    print(f"✅ MLflow experiment: {experiment_name}")
+    return experiment_name
+
+
+def parse_args():
+    """Parse command line arguments."""
+    parser = argparse.ArgumentParser(description="SQL translation benchmark")
+    parser.add_argument("--artifact-type", default="tables", help="Artifact type")
+    parser.add_argument("--dataset-source", help="Dataset JSON path")
+    parser.add_argument("--experiment-name", help="MLflow experiment name")
+    parser.add_argument("--batch-size", type=int, default=5, help="Batch size")
+    parser.add_argument("--judge-endpoint", default="databricks-llama-4-maverick")
+    parser.add_argument("--models", nargs="+", help="Model endpoints to test")
+    return parser.parse_args()
+
+
+def main():
+    """Run benchmark."""
+    args = parse_args()
+    
+    logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s")
+    
+    print("\n" + "="*70)
+    print("🚀 SQL Translation Benchmark")
+    print("="*70)
+    
+    experiment_name = setup_mlflow(get_experiment_name(args.experiment_name))
+    
+    # Configure models
+    if args.models:
+        model_configs = [
+            ModelConfig(name=ep, endpoint=ep, temperature=0.1, max_tokens=4000)
+            for ep in args.models
+        ]
+    else:
+        model_configs = create_default_model_configs()
+    
+    print(f"Models: {[c.name for c in model_configs]}")
+    print(f"Artifact: {args.artifact_type}, Batch: {args.batch_size}")
+    
+    try:
+        results_df = run_benchmark(
+            artifact_type=args.artifact_type,
+            dataset_source=args.dataset_source,
+            experiment_name=experiment_name,
+            model_configs=model_configs,
+            batch_size=args.batch_size,
+            judge_endpoint=args.judge_endpoint
+        )
+        
+        print("\n" + "="*70)
+        print("✅ Benchmark Complete!")
+        print("="*70)
+        print(results_df.to_string())
+        print(f"\n🔗 View results: {experiment_name}")
+        
+    except Exception as e:
+        print(f"\n❌ Failed: {e}")
+        logging.error("Benchmark error", exc_info=True)
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/src/artifact_translation_package/config/ddl_config.py b/src/artifact_translation_package/config/ddl_config.py
index 4bf49ce..bbab319 100644
--- a/src/artifact_translation_package/config/ddl_config.py
+++ b/src/artifact_translation_package/config/ddl_config.py
@@ -177,12 +177,13 @@ class DDLConfig:
                 "additional_params": {
                     "endpoint": LangGraphConfig.DBX_ENDPOINT.value
                 }
-            }
+                        }
         },
         "processing": {
             "batch_size": LangGraphConfig.DDL_BATCH_SIZE.value,
             "max_concurrent_batches": LangGraphConfig.DDL_MAX_CONCURRENT.value,
-            "timeout_seconds": LangGraphConfig.DDL_TIMEOUT.value
+            "timeout_seconds": LangGraphConfig.DDL_TIMEOUT.value,
+            "evaluation_batch_size": 5  # Number of SQL statements per LLM evaluation call
         },
         "output": {
             "format": LangGraphConfig.DDL_OUTPUT_FORMAT.value,
@@ -197,6 +198,14 @@ class DDLConfig:
             "llm_validated_artifacts": ["procedures", "pipes"],
             "skip_unsupported_artifacts": ["grants", "procedures", "udfs", "stages", "pipes", "roles"]
         },
+        "benchmark": {
+            "mlflow_experiment_name": "sql-translation-benchmark",
+            "default_models": ["databricks-llama-4-maverick", "databricks-gemini-2-5-flash"],
+            "temperature_variations": [0.1, 0.2],
+            "artifact_types": ["tables", "views", "procedures"],
+            "judge_endpoint": "databricks-llama-4-maverick",  # LLM endpoint for evaluation/judging
+            "batch_size": 10
+        },
         "langsmith": {
             "tracing": LangGraphConfig.LANGSMITH_TRACING.value,
             "project": LangGraphConfig.LANGSMITH_PROJECT.value,
diff --git a/src/artifact_translation_package/evaluation/README.md b/src/artifact_translation_package/evaluation/README.md
new file mode 100644
index 0000000..7b24324
--- /dev/null
+++ b/src/artifact_translation_package/evaluation/README.md
@@ -0,0 +1,111 @@
+# SQL Translation Model Benchmark Evaluation
+
+Evaluate and compare SQL translation models (Snowflake → Databricks) using MLflow and LLM-as-a-judge.
+
+## Prerequisites
+
+Before running the benchmark, ensure you have:
+
+1. **Databricks CLI configured** (or `.env` file with credentials):
+   ```bash
+   # Option A: Databricks CLI
+   databricks configure --host https://your-workspace.cloud.databricks.com
+   
+   # Option B: .env file in project root
+   DATABRICKS_HOST=https://your-workspace.cloud.databricks.com
+   DATABRICKS_TOKEN=dapi...
+   ```
+
+2. **Dependencies installed**:
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+3. **Input Data**: The benchmark expects input JSON files (Snowflake DDL metadata). By default, it looks in `src/artifact_translation_package/examples/`.
+
+## Quick Start (Running the Evaluation)
+
+### Option 1: Interactive Notebook
+The simplest way to run and visualize results.
+
+1. Open `src/artifact_translation_package/evaluation/benchmark_interactive.ipynb`
+2. **Configure models**: Set your endpoints in the Config cell.
+   ```python
+   TRANSLATION_MODELS = ["databricks-llama-4-maverick", "databricks-gemini-2-5-flash"]
+   ARTIFACT_TYPE = "tables"  # or "views", "procedures"
+   ```
+3. **Run all cells**: It will trigger `run_local_benchmark.py` and display comparison charts.
+
+### Option 2: Command Line (Fastest)
+
+Run the benchmark from the project root:
+
+```bash
+# 1. Basic: Run benchmark for tables using default models
+python3 run_local_benchmark.py --artifact-type tables
+
+# 2. Advanced: Specify custom models to compare
+python3 run_local_benchmark.py \
+  --artifact-type views \
+  --models databricks-llama-4-maverick databricks-meta-llama-3-1-70b-instruct
+
+# 3. Custom Data: Specify a custom input JSON file
+python3 run_local_benchmark.py \
+  --artifact-type tables \
+  --dataset-source /path/to/your/metadata.json
+
+# 4. Settings: Control batch size for judge execution
+python3 run_local_benchmark.py --batch-size 10
+```
+
+## How Evaluation Works
+
+We use a **Strict Deduction-Based Scoring System** (starting at 100) to evaluate two independent dimensions:
+
+### Dimension 1: Compliance Score (0-100)
+**Goal**: Functional correctness. Can this code actually run on Databricks?
+- **Invalid syntax**: Automatic score of **0**.
+- **Point Deductions**:
+  - Missing `USING DELTA` (-20 pts)
+  - Using legacy types like `VARCHAR` or `TEXT` instead of `STRING` (-10 pts)
+  - Missing 3-level naming (`catalog.schema.table`) (-15 pts)
+
+### Dimension 2: Best Practices Score (0-100)
+**Goal**: Performance and Documentation. Is this production-grade code?
+- **Point Deductions**:
+  - Missing `CLUSTER BY` (Liquid Clustering) (-30 pts)
+  - Missing table properties like `autoOptimize` (-20 pts)
+  - Missing table or column `COMMENT`s (-25 pts each)
+
+## MLflow Features
+
+The benchmark automatically logs rich data to Databricks MLflow:
+
+- **Experiment Name**: Defaults to `sql-translation-benchmark` or your username.
+- **Searchable Tags**: Every run is tagged with issue categories (e.g., `has_naming_issues: true`).
+- **Issues Table**: `issues_table.json` logs every single violation found for queryable analysis.
+- **Top Issues Summary**: `top_issues_summary.txt` provides an at-a-glance summary of the most common mistakes across all samples.
+
+## Metrics Reference
+
+| Metric | Threshold | Description |
+|--------|-----------|-------------|
+| `avg_compliance` | 0-100 | Mean functional correctness score. |
+| `avg_best_practices` | 0-100 | Mean optimization/docs score. |
+| `compliant_pct` | >= 70 | % of statements that are functional. |
+| `syntax_valid_pct` | 100% | % of statements with valid Databricks SQL syntax. |
+
+## Troubleshooting
+
+| Issue | Cause | Fix |
+|-------|-------|-----|
+| Authentication Error | Missing `DATABRICKS_TOKEN` | Check `.env` or run `databricks configure`. |
+| `File Not Found` | Custom JSON path is wrong | Verify `--dataset-source` path. |
+| Model not found | Incorrect endpoint name | Verify name in Databricks Model Serving UI. |
+| Low scores | Model performance | Check `top_issues_summary.txt` to find systemic errors. |
+
+## Deployment to Databricks
+
+To run this directly within a Databricks Job or Notebook:
+1. Ensure the `requirements.txt` libraries are installed on the cluster.
+2. The benchmark will automatically detect it is running in Databricks and create MLflow experiments in your User workspace folder.
diff --git a/src/artifact_translation_package/evaluation/__init__.py b/src/artifact_translation_package/evaluation/__init__.py
new file mode 100644
index 0000000..023defb
--- /dev/null
+++ b/src/artifact_translation_package/evaluation/__init__.py
@@ -0,0 +1,36 @@
+"""
+Evaluation and benchmarking module for SQL translation quality assessment.
+
+This module provides tools for evaluating and benchmarking SQL translation models
+using MLflow and LLM-as-a-judge patterns.
+"""
+
+from artifact_translation_package.evaluation.evaluation_dataset import (
+    EvaluationDataset,
+    load_evaluation_dataset
+)
+from artifact_translation_package.evaluation.databricks_sql_scorer import (
+    DatabricksSQLComplianceScorer,
+    create_compliance_scorer
+)
+from artifact_translation_package.evaluation.model_benchmark import (
+    ModelConfig,
+    ModelBenchmark,
+    create_default_model_configs
+)
+from artifact_translation_package.evaluation.run_benchmark import (
+    BenchmarkRunner,
+    run_benchmark
+)
+
+__all__ = [
+    "EvaluationDataset",
+    "load_evaluation_dataset",
+    "DatabricksSQLComplianceScorer",
+    "create_compliance_scorer",
+    "ModelConfig",
+    "ModelBenchmark",
+    "create_default_model_configs",
+    "BenchmarkRunner",
+    "run_benchmark"
+]
diff --git a/src/artifact_translation_package/evaluation/benchmark_interactive.ipynb b/src/artifact_translation_package/evaluation/benchmark_interactive.ipynb
new file mode 100644
index 0000000..85ecf28
--- /dev/null
+++ b/src/artifact_translation_package/evaluation/benchmark_interactive.ipynb
@@ -0,0 +1,167 @@
+{
+    "cells": [
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "# SQL Translation Model Benchmark - Interactive\n",
+                "\n",
+                "Simple notebook interface to run benchmarks using the `run_local_benchmark.py` script.\n",
+                "\n",
+                "## What This Does\n",
+                "\n",
+                "- 🤖 Compares SQL translation models (Llama 4 Maverick vs Gemini 2.5 Flash)\n",
+                "- ⚖️ Uses LLM-as-judge to evaluate Databricks SQL compliance\n",
+                "- 📊 Tracks results in Databricks MLflow\n",
+                "- 📈 Shows comparison charts"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "## 1. Configuration\n",
+                "\n",
+                "Edit these settings to customize your benchmark:"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# ═══════════════════════════════════════════════════════════════\n",
+                "# CONFIGURATION - Customize these settings\n",
+                "# ═══════════════════════════════════════════════════════════════\n",
+                "\n",
+                "# Models to benchmark (for SQL translation)\n",
+                "TRANSLATION_MODELS = [\n",
+                "    \"databricks-llama-4-maverick\",\n",
+                "    \"databricks-gemini-2-5-flash\",\n",
+                "]\n",
+                "\n",
+                "# Judge model (evaluates SQL compliance)\n",
+                "JUDGE_MODEL = \"databricks-llama-4-maverick\"\n",
+                "\n",
+                "# Artifact type to benchmark\n",
+                "ARTIFACT_TYPE = \"tables\"  # Options: tables, views, procedures\n",
+                "\n",
+                "# Batch size for processing\n",
+                "BATCH_SIZE = 5\n",
+                "\n",
+                "# Optional: Custom dataset path (None = use built-in examples)\n",
+                "DATASET_PATH = None  # e.g., \"../examples/tables.json\"\n",
+                "\n",
+                "print(\"📋 Configuration:\")\n",
+                "print(f\"  Translation models: {TRANSLATION_MODELS}\")\n",
+                "print(f\"  Judge model: {JUDGE_MODEL}\")\n",
+                "print(f\"  Artifact type: {ARTIFACT_TYPE}\")\n",
+                "print(f\"  Batch size: {BATCH_SIZE}\")"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "## 2. Run Benchmark\n",
+                "\n",
+                "Execute the benchmark with your configuration:"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "import sys\n",
+                "from pathlib import Path\n",
+                "\n",
+                "# Add project root to path\n",
+                "project_root = Path.cwd()\n",
+                "while not (project_root / \"run_local_benchmark.py\").exists() and project_root.parent != project_root:\n",
+                "    project_root = project_root.parent\n",
+                "\n",
+                "if not (project_root / \"run_local_benchmark.py\").exists():\n",
+                "    print(\"❌ Could not find run_local_benchmark.py\")\n",
+                "    print(f\"   Searched from: {Path.cwd()}\")\n",
+                "    print(f\"   Ended at: {project_root}\")\n",
+                "else:\n",
+                "    print(f\"✅ Found project root: {project_root}\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# Build command arguments\n",
+                "import subprocess\n",
+                "\n",
+                "cmd = [\n",
+                "    \"python3\",\n",
+                "    str(project_root / \"run_local_benchmark.py\"),\n",
+                "    \"--artifact-type\", ARTIFACT_TYPE,\n",
+                "    \"--batch-size\", str(BATCH_SIZE),\n",
+                "    \"--judge-endpoint\", JUDGE_MODEL,\n",
+                "    \"--models\"\n",
+                "] + TRANSLATION_MODELS\n",
+                "\n",
+                "if DATASET_PATH:\n",
+                "    cmd.extend([\"--dataset-source\", str(DATASET_PATH)])\n",
+                "\n",
+                "print(\"🚀 Running benchmark...\")\n",
+                "print(f\"\\nCommand: {' '.join(cmd)}\")\n",
+                "print(\"\\n\" + \"=\"*70 + \"\\n\")\n",
+                "\n",
+                "# Run the benchmark\n",
+                "result = subprocess.run(cmd, capture_output=False, text=True)\n",
+                "\n",
+                "if result.returncode == 0:\n",
+                "    print(\"\\n\" + \"=\"*70)\n",
+                "    print(\"✅ Benchmark completed successfully!\")\n",
+                "    print(\"=\"*70)\n",
+                "else:\n",
+                "    print(\"\\n\" + \"=\"*70)\n",
+                "    print(f\"❌ Benchmark failed with exit code: {result.returncode}\")\n",
+                "    print(\"=\"*70)"
+            ]
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "## 3. View Results in Databricks MLflow\n",
+                "\n",
+                "After running the benchmark:\n",
+                "\n",
+                "1. **Open Databricks workspace**\n",
+                "2. **Navigate to**: Machine Learning → Experiments\n",
+                "3. **Find your user folder**: `/Users/your.email@domain.com/`\n",
+                "4. **Open experiment**: `sql-translation-benchmark`\n",
+                "5. **Compare runs**: Select multiple runs and click \"Compare\"\n",
+                "\n",
+                "### Tips\n",
+                "\n",
+                "- **Grouped bar charts**: Select 2+ runs to see side-by-side comparisons\n",
+                "- **Metrics to compare**: `avg_compliance_score`, `syntax_valid_pct`, `best_practices_pct`\n",
+                "- **LLM traces**: View in each run's \"Traces\" tab for debugging"
+            ]
+        }
+    ],
+    "metadata": {
+        "kernelspec": {
+            "display_name": "Python 3",
+            "language": "python",
+            "name": "python3"
+        },
+        "language_info": {
+            "name": "python",
+            "version": "3.13.2"
+        }
+    },
+    "nbformat": 4,
+    "nbformat_minor": 4
+}
diff --git a/src/artifact_translation_package/evaluation/compliance_prompts.py b/src/artifact_translation_package/evaluation/compliance_prompts.py
new file mode 100644
index 0000000..0f97bb1
--- /dev/null
+++ b/src/artifact_translation_package/evaluation/compliance_prompts.py
@@ -0,0 +1,57 @@
+"""
+Databricks SQL compliance evaluation prompt.
+"""
+
+DATABRICKS_COMPLIANCE_PROMPT = """You are an expert Databricks SQL architect.
+Evaluate the provided SQL DDL in TWO INDEPENDENT DIMENSIONS:
+
+**1. COMPLIANCE (0-100): Does it meet Databricks SQL requirements?**
+Start at 100, deduct points for:
+- Invalid syntax: -100 (score becomes 0)
+- Missing Unity Catalog 3-level naming: -15
+- Using VARCHAR/TEXT/CHAR instead of STRING: -10
+- Using INT/INTEGER instead of BIGINT for IDs: -10
+- Missing USING DELTA: -20
+- MixedCase identifiers (should be snake_case): -10
+
+**2. BEST PRACTICES (0-100): Is it optimized and documented?**
+Start at 100, deduct points for:
+- Missing CLUSTER BY (Liquid Clustering): -30
+- Missing table properties (autoOptimize, etc): -20
+- Missing table COMMENT: -25
+- Missing column COMMENTs: -25
+
+**SQL to Evaluate:**
+{sql_content}
+
+**Instructions:**
+- Evaluate BOTH dimensions independently
+- Compliance = functional correctness for Databricks
+- Best Practices = production-ready optimizations and documentation
+- A SQL can be 100% compliant but 0% best practices (runs but unoptimized)
+
+Return JSON:
+{{
+    "results": [
+        {{
+            "syntax_valid": boolean,
+            "score": integer (0-100, compliance),
+            "best_practices_score": integer (0-100),
+            "error_message": string or null,
+            "issues": [
+                {{
+                    "category": "compliance" | "best_practices",
+                    "description": string,
+                    "suggestion": string,
+                    "severity": "critical" | "warning" | "info"
+                }}
+            ]
+        }}
+    ]
+}}
+"""
+
+
+def create_compliance_prompt(sql_content: str) -> str:
+    """Create a Databricks SQL compliance evaluation prompt."""
+    return DATABRICKS_COMPLIANCE_PROMPT.format(sql_content=sql_content)
diff --git a/src/artifact_translation_package/evaluation/databricks_sql_scorer.py b/src/artifact_translation_package/evaluation/databricks_sql_scorer.py
new file mode 100644
index 0000000..3783a34
--- /dev/null
+++ b/src/artifact_translation_package/evaluation/databricks_sql_scorer.py
@@ -0,0 +1,122 @@
+"""
+Databricks SQL compliance scorer for MLflow evaluation.
+
+Provides an LLM-as-a-judge scorer for evaluating Databricks SQL compliance.
+"""
+
+import logging
+from typing import Dict, Any, Optional
+
+from databricks_langchain import ChatDatabricks
+
+from artifact_translation_package.config.ddl_config import create_node_llm
+from artifact_translation_package.nodes.evaluation import create_structured_llm
+from artifact_translation_package.evaluation.compliance_prompts import create_compliance_prompt
+from artifact_translation_package.utils.evaluation_models import SQLEvaluationResult
+
+logger = logging.getLogger(__name__)
+
+COMPLIANT_THRESHOLD = 70
+DEFAULT_VALID_SCORE = 80.0
+
+
+def _clean_sql(sql: str) -> str:
+    """Remove markdown code fences from SQL."""
+    cleaned = sql.strip()
+    if cleaned.startswith("```sql"):
+        cleaned = cleaned[6:].strip()
+    elif cleaned.startswith("```"):
+        cleaned = cleaned[3:].strip()
+    if cleaned.endswith("```"):
+        cleaned = cleaned[:-3].strip()
+    return cleaned
+
+
+def _build_metrics(eval_result: SQLEvaluationResult) -> Dict[str, Any]:
+    """Convert evaluation result to metrics dictionary."""
+    compliance_score = float(getattr(eval_result, "score", 0))
+    best_practices_score = float(getattr(eval_result, "best_practices_score", 0))
+    
+    if compliance_score == 0 and eval_result.syntax_valid:
+        compliance_score = DEFAULT_VALID_SCORE
+    
+    return {
+        "is_compliant": compliance_score >= COMPLIANT_THRESHOLD,
+        "compliance_score": compliance_score,
+        "best_practices_score": best_practices_score,
+        "syntax_valid": eval_result.syntax_valid,
+        "summary": eval_result.error_message or f"Compliance: {compliance_score}, Best Practices: {best_practices_score}",
+        "issues_count": len(eval_result.issues),
+        "issues": [
+            {
+                "type": getattr(issue, "category", "syntax"),
+                "severity": getattr(issue, "severity", "warning"),
+                "description": issue.description,
+                "suggestion": issue.suggestion or "",
+                "line_number": issue.line_number
+            }
+            for issue in eval_result.issues
+        ]
+    }
+
+
+class DatabricksSQLComplianceScorer:
+    """LLM-as-judge scorer for Databricks SQL compliance."""
+    
+    def __init__(self, llm_endpoint: Optional[str] = None):
+        self.llm_endpoint = llm_endpoint
+        self._structured_llm = None
+        
+    def _init_llm(self):
+        """Initialize structured LLM on first use."""
+        if self._structured_llm is not None:
+            return
+        
+        if self.llm_endpoint:
+            llm = ChatDatabricks(endpoint=self.llm_endpoint, temperature=0.1, max_tokens=2000)
+        else:
+            llm = create_node_llm("evaluator")
+        
+        self._structured_llm = create_structured_llm(llm, batch_mode=True)
+    
+    def evaluate_sql(self, sql_statement: str) -> Dict[str, Any]:
+        """Evaluate SQL statement for Databricks compliance."""
+        if not sql_statement or not sql_statement.strip():
+            return {
+                "is_compliant": False,
+                "compliance_score": 0.0,
+                "syntax_valid": False,
+                "summary": "Empty SQL",
+                "error": "No content"
+            }
+        
+        try:
+            self._init_llm()
+            prompt = create_compliance_prompt(sql_content=_clean_sql(sql_statement))
+            response = self._structured_llm.invoke(prompt)
+            # Structured output always returns BatchSQLEvaluationResult with .results list
+            eval_result = response.results[0]
+            return _build_metrics(eval_result)
+            
+        except Exception as e:
+            logger.error(f"Evaluation error: {e}")
+            return {
+                "is_compliant": False,
+                "compliance_score": 0.0,
+                "syntax_valid": False,
+                "summary": f"Error: {e}",
+                "error": str(e)
+            }
+    
+    def __call__(self, sql_statement: str) -> Dict[str, Any]:
+        return self.evaluate_sql(sql_statement)
+
+
+def create_compliance_scorer(
+    llm_endpoint: Optional[str] = None,
+    name: str = "databricks_sql_compliance"
+) -> DatabricksSQLComplianceScorer:
+    """Create a Databricks SQL compliance scorer."""
+    scorer = DatabricksSQLComplianceScorer(llm_endpoint=llm_endpoint)
+    scorer.name = name
+    return scorer
diff --git a/src/artifact_translation_package/evaluation/evaluation_dataset.py b/src/artifact_translation_package/evaluation/evaluation_dataset.py
new file mode 100644
index 0000000..5dd9a04
--- /dev/null
+++ b/src/artifact_translation_package/evaluation/evaluation_dataset.py
@@ -0,0 +1,103 @@
+"""
+Evaluation dataset management for SQL translation benchmarking.
+"""
+
+import os
+import json
+import logging
+from pathlib import Path
+from typing import List, Dict, Any, Optional
+import pandas as pd
+
+from artifact_translation_package.utils.types import ArtifactBatch
+
+logger = logging.getLogger(__name__)
+
+
+class EvaluationDataset:
+    """Loads and prepares evaluation datasets for MLflow."""
+    
+    def __init__(self, artifact_type: str, source_file: Optional[str] = None, examples_dir: Optional[str] = None):
+        self.artifact_type = artifact_type
+        self.source_file = source_file
+        self.examples_dir = examples_dir or str(Path(__file__).parent.parent / "examples")
+        self.raw_data: List[Dict[str, Any]] = []
+        self.dataframe: Optional[pd.DataFrame] = None
+        
+    def load(self) -> "EvaluationDataset":
+        """Load evaluation data from JSON file."""
+        filepath = self.source_file or os.path.join(self.examples_dir, f"{self.artifact_type}.json")
+        
+        if not os.path.exists(filepath):
+            raise FileNotFoundError(f"Evaluation data file not found: {filepath}")
+        
+        logger.info(f"Loading evaluation data from: {filepath}")
+        
+        with open(filepath, 'r', encoding='utf-8') as f:
+            data = json.load(f)
+        
+        self.raw_data = self._extract_artifacts(data)
+        logger.info(f"Loaded {len(self.raw_data)} {self.artifact_type} for evaluation")
+        return self
+    
+    def _extract_artifacts(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
+        """Extract artifacts from JSON data."""
+        if self.artifact_type in data:
+            return data[self.artifact_type]
+        if isinstance(data, list):
+            return data
+        for key in ['items', 'artifacts']:
+            if key in data:
+                return data[key]
+        logger.warning(f"Could not find artifacts for type: {self.artifact_type}")
+        return []
+    
+    def to_dataframe(self) -> pd.DataFrame:
+        """Convert to pandas DataFrame."""
+        if not self.raw_data:
+            raise ValueError("No data loaded. Call load() first.")
+        
+        records = [
+            {
+                "artifact_id": f"{self.artifact_type}_{idx}",
+                "artifact_type": self.artifact_type,
+                "source_data": json.dumps(artifact),
+            }
+            for idx, artifact in enumerate(self.raw_data)
+        ]
+        
+        self.dataframe = pd.DataFrame(records)
+        return self.dataframe
+    
+    def to_batches(self, batch_size: int = 10) -> List[ArtifactBatch]:
+        """Convert to artifact batches for translation."""
+        if not self.raw_data:
+            raise ValueError("No data loaded. Call load() first.")
+        
+        items = [json.dumps(artifact) for artifact in self.raw_data]
+        batches = []
+        
+        for i in range(0, len(items), batch_size):
+            batch = ArtifactBatch(
+                artifact_type=self.artifact_type,
+                items=items[i:i + batch_size],
+                context={"source": "evaluation_dataset", "batch_index": len(batches)}
+            )
+            batches.append(batch)
+        
+        logger.info(f"Created {len(batches)} batches")
+        return batches
+    
+    def __len__(self) -> int:
+        return len(self.raw_data)
+
+
+def load_evaluation_dataset(
+    artifact_type: str,
+    source_file: Optional[str] = None,
+    as_dataframe: bool = True
+) -> pd.DataFrame | EvaluationDataset:
+    """Load and prepare evaluation dataset."""
+    dataset = EvaluationDataset(artifact_type=artifact_type, source_file=source_file)
+    dataset.load()
+    return dataset.to_dataframe() if as_dataframe else dataset
diff --git a/src/artifact_translation_package/evaluation/model_benchmark.py b/src/artifact_translation_package/evaluation/model_benchmark.py
new file mode 100644
index 0000000..48f5d12
--- /dev/null
+++ b/src/artifact_translation_package/evaluation/model_benchmark.py
@@ -0,0 +1,109 @@
+"""
+Model benchmark configuration for SQL translation evaluation.
+"""
+
+import logging
+from dataclasses import dataclass, field
+from typing import List, Dict, Any, Optional
+
+from artifact_translation_package.graph_builder import TranslationGraph
+from artifact_translation_package.utils.types import ArtifactBatch
+from artifact_translation_package.config.ddl_config import DDLConfig
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class ModelConfig:
+    """Configuration for a model to benchmark."""
+    name: str
+    endpoint: str
+    temperature: float = 0.2
+    max_tokens: int = 4000
+    description: Optional[str] = None
+    additional_params: Dict[str, Any] = field(default_factory=dict)
+    
+    def to_dict(self) -> Dict[str, Any]:
+        return {
+            "name": self.name,
+            "endpoint": self.endpoint,
+            "temperature": self.temperature,
+            "max_tokens": self.max_tokens,
+            **self.additional_params
+        }
+
+
+class ModelBenchmark:
+    """Manages model configurations for benchmarking SQL translation."""
+    
+    def __init__(self, artifact_type: str):
+        self.artifact_type = artifact_type
+        self.model_configs: List[ModelConfig] = []
+        
+    def add_model_config(self, config: ModelConfig) -> "ModelBenchmark":
+        """Add a model configuration."""
+        self.model_configs.append(config)
+        logger.info(f"Added model: {config.name}")
+        return self
+    
+    def run_translation(self, batches: List[ArtifactBatch], model_config: ModelConfig) -> Dict[str, Any]:
+        """Run translation using a specific model configuration."""
+        logger.info(f"Running translation with model: {model_config.name}")
+        
+        config_overrides = {
+            "llms": {
+                f"{self.artifact_type}_translator": {
+                    "provider": "databricks",
+                    "model": model_config.endpoint,
+                    "temperature": model_config.temperature,
+                    "max_tokens": model_config.max_tokens,
+                    "additional_params": {
+                        "endpoint": model_config.endpoint,
+                        **model_config.additional_params
+                    }
+                }
+            }
+        }
+        
+        graph = TranslationGraph()
+        graph.config = DDLConfig(config_overrides=config_overrides)
+        
+        result = graph.run_batches(batches)
+        result.setdefault("metadata", {})["model_config"] = model_config.to_dict()
+        result["metadata"]["artifact_type"] = self.artifact_type
+        
+        logger.info(f"Translation completed: {len(result.get(self.artifact_type, []))} results")
+        return result
+    
+    def get_model_configs(self) -> List[ModelConfig]:
+        return self.model_configs
+    
+    def __len__(self) -> int:
+        return len(self.model_configs)
+
+
+def create_default_model_configs() -> List[ModelConfig]:
+    """Create default model configurations."""
+    return [
+        ModelConfig(
+            name="llama-4-maverick",
+            endpoint="databricks-llama-4-maverick",
+            temperature=0.1,
+            max_tokens=4000,
+        ),
+        ModelConfig(
+            name="gemini-2.5-flash",
+            endpoint="databricks-gemini-2-5-flash",
+            temperature=0.1,
+            max_tokens=4000,
+        ),
+    ]
+
+
+def create_model_benchmark(artifact_type: str, use_defaults: bool = True) -> ModelBenchmark:
+    """Factory to create a ModelBenchmark."""
+    benchmark = ModelBenchmark(artifact_type)
+    if use_defaults:
+        for config in create_default_model_configs():
+            benchmark.add_model_config(config)
+    return benchmark
diff --git a/src/artifact_translation_package/evaluation/run_benchmark.py b/src/artifact_translation_package/evaluation/run_benchmark.py
new file mode 100644
index 0000000..7650997
--- /dev/null
+++ b/src/artifact_translation_package/evaluation/run_benchmark.py
@@ -0,0 +1,433 @@
+"""
+Main benchmark orchestrator for SQL translation model evaluation.
+
+This module provides the BenchmarkRunner class that coordinates the entire
+benchmarking pipeline using MLflow for experiment tracking.
+"""
+
+import os
+import logging
+from pathlib import Path
+from typing import List, Dict, Any, Optional
+from datetime import datetime
+import pandas as pd
+
+import mlflow
+
+from artifact_translation_package.evaluation.evaluation_dataset import (
+    EvaluationDataset,
+    load_evaluation_dataset
+)
+from artifact_translation_package.evaluation.databricks_sql_scorer import (
+    DatabricksSQLComplianceScorer,
+    create_compliance_scorer
+)
+from artifact_translation_package.evaluation.model_benchmark import (
+    ModelConfig,
+    ModelBenchmark,
+    create_model_benchmark,
+    create_default_model_configs
+)
+from artifact_translation_package.utils.types import ArtifactBatch
+from artifact_translation_package.config.ddl_config import get_config
+
+logger = logging.getLogger(__name__)
+
+
+class BenchmarkRunner:
+    """Orchestrates SQL translation model benchmarking using MLflow."""
+    
+    def __init__(
+        self,
+        experiment_name: str = "sql-translation-benchmark",
+        mlflow_tracking_uri: Optional[str] = None
+    ):
+        self.experiment_name = experiment_name
+        self.mlflow_tracking_uri = mlflow_tracking_uri
+        self._setup_mlflow()
+        
+    def _setup_mlflow(self):
+        """Setup MLflow experiment and tracking."""
+        if self.mlflow_tracking_uri:
+            mlflow.set_tracking_uri(self.mlflow_tracking_uri)
+            logger.info(f"Set MLflow tracking URI to: {self.mlflow_tracking_uri}")
+        
+        # mlflow.set_experiment() will create the experiment if it doesn't exist
+        try:
+            mlflow.set_experiment(self.experiment_name)
+            logger.info(f"MLflow experiment ready: {self.experiment_name}")
+        except Exception as e:
+            logger.error(f"Failed to setup MLflow experiment '{self.experiment_name}': {e}")
+            logger.error("Make sure you have the correct permissions in Databricks workspace")
+            raise RuntimeError(f"Could not setup MLflow experiment: {e}") from e
+    
+    def run_benchmark(
+        self,
+        artifact_type: str,
+        dataset_source: Optional[str] = None,
+        model_configs: Optional[List[ModelConfig]] = None,
+        batch_size: int = 10,
+        judge_endpoint: Optional[str] = None
+    ) -> pd.DataFrame:
+        """
+        Run complete benchmark comparing multiple models.
+        
+        Args:
+            artifact_type: Type of artifact to benchmark (tables, views, etc.)
+            dataset_source: Optional path to dataset file
+            model_configs: Optional list of model configs (uses defaults if None)
+            batch_size: Batch size for translation
+            judge_endpoint: Optional specific LLM endpoint for judging
+            
+        Returns:
+            DataFrame with benchmark results
+        """
+        logger.info(f"Starting benchmark for artifact type: {artifact_type}")
+        
+        # Load evaluation dataset
+        dataset = EvaluationDataset(
+            artifact_type=artifact_type,
+            source_file=dataset_source
+        )
+        dataset.load()
+        
+        logger.info(f"Loaded {len(dataset)} artifacts for evaluation")
+        
+        # Create batches for translation
+        batches = dataset.to_batches(batch_size=batch_size)
+        
+        # Setup model benchmark
+        benchmark = ModelBenchmark(artifact_type)
+        
+        if model_configs:
+            for config in model_configs:
+                benchmark.add_model_config(config)
+        else:
+            # Use default configurations
+            for config in create_default_model_configs():
+                benchmark.add_model_config(config)
+        
+        logger.info(f"Benchmarking {len(benchmark)} model configurations")
+        
+        # Create scorer for evaluation
+        scorer = create_compliance_scorer(llm_endpoint=judge_endpoint)
+        
+        # Ensure experiment is set before creating runs
+        mlflow.set_experiment(self.experiment_name)
+        
+        # Create parent run for comparison
+        parent_run_name = f"benchmark_{artifact_type}_{datetime.now().strftime('%Y%m%d_%H%M%S')}"
+        
+        with mlflow.start_run(run_name=parent_run_name) as parent_run:
+            # Log benchmark-level parameters
+            mlflow.log_params({
+                "artifact_type": artifact_type,
+                "num_models": len(benchmark),
+                "batch_size": batch_size,
+                "judge_endpoint": judge_endpoint or "databricks-llama-4-maverick"
+            })
+            
+            # Run benchmark for each model in NESTED runs
+            results = []
+            for model_config in benchmark.get_model_configs():
+                logger.info(f"\n{'='*60}")
+                logger.info(f"Benchmarking: {model_config.name}")
+                logger.info(f"{'='*60}")
+                
+                result = self._run_single_model_benchmark(
+                    model_config=model_config,
+                    batches=batches,
+                    benchmark=benchmark,
+                    scorer=scorer,
+                    artifact_type=artifact_type,
+                    parent_run_id=parent_run.info.run_id
+                )
+                results.append(result)
+        
+        # Compile results into DataFrame
+        results_df = pd.DataFrame(results)
+        
+        logger.info(f"\n{'='*60}")
+        logger.info("Benchmark Summary")
+        logger.info(f"{'='*60}")
+        logger.info(f"\n{results_df.to_string()}")
+        
+        return results_df
+    
+    def _run_single_model_benchmark(
+        self,
+        model_config: ModelConfig,
+        batches: List[ArtifactBatch],
+        benchmark: ModelBenchmark,
+        scorer: DatabricksSQLComplianceScorer,
+        artifact_type: str,
+        parent_run_id: str
+    ) -> Dict[str, Any]:
+        """
+        Run benchmark for a single model configuration as a nested run.
+        
+        Args:
+            model_config: Model configuration to benchmark
+            batches: Artifact batches to translate
+            benchmark: ModelBenchmark instance
+            scorer: Compliance scorer
+            artifact_type: Type of artifact
+            parent_run_id: Parent MLflow run ID for nesting
+            
+        Returns:
+            Dictionary with benchmark metrics
+        """
+        # Create NESTED run for this specific model
+        with mlflow.start_run(run_name=model_config.name, nested=True):
+            # Log model-specific parameters
+            mlflow.log_params({
+                "endpoint": model_config.endpoint,
+                "temperature": model_config.temperature,
+                "max_tokens": model_config.max_tokens,
+            })
+            
+            # Run translation
+            start_time = datetime.now()
+            translation_result = benchmark.run_translation(batches, model_config)
+            end_time = datetime.now()
+            translation_duration = (end_time - start_time).total_seconds()
+            
+            # Extract SQL results
+            sql_results = translation_result.get(artifact_type, [])
+            total_results = len(sql_results)
+            
+            # Evaluate each SQL statement
+            compliance_scores = []
+            best_practices_scores = []
+            syntax_valid_count = 0
+            compliant_count = 0
+            all_issues = []
+            
+            eval_start_time = datetime.now()
+            for idx, sql_statement in enumerate(sql_results):
+                try:
+                    eval_result = scorer.evaluate_sql(sql_statement)
+                    compliance_scores.append(eval_result.get("compliance_score", 0.0))
+                    best_practices_scores.append(eval_result.get("best_practices_score", 0.0))
+                    
+                    # Track metrics
+                    if eval_result.get("syntax_valid", False):
+                        syntax_valid_count += 1
+                    if eval_result.get("is_compliant", False):
+                        compliant_count += 1
+                        
+                    # Collect issues for summary
+                    for issue in eval_result.get("issues", []):
+                        issue["sql_idx"] = idx
+                        all_issues.append(issue)
+                        
+                    # Log individual evaluation (sample first 5)
+                    if idx < 5:
+                        mlflow.log_dict(
+                            eval_result,
+                            f"evaluations/sql_{idx}_evaluation.json"
+                        )
+                        
+                except Exception as e:
+                    logger.error(f"Error evaluating SQL {idx}: {str(e)}")
+                    compliance_scores.append(0.0)
+            
+            eval_end_time = datetime.now()
+            evaluation_duration = (eval_end_time - eval_start_time).total_seconds()
+            
+            # Calculate metrics
+            avg_compliance_score = (
+                sum(compliance_scores) / len(compliance_scores)
+                if compliance_scores else 0.0
+            )
+            avg_best_practices_score = (
+                sum(best_practices_scores) / len(best_practices_scores)
+                if best_practices_scores else 0.0
+            )
+            syntax_valid_pct = (syntax_valid_count / total_results * 100) if total_results > 0 else 0.0
+            compliant_pct = (compliant_count / total_results * 100) if total_results > 0 else 0.0
+            
+            # Log metrics with STANDARD names (no prefix) for grouped comparison
+            mlflow.log_metrics({
+                "avg_compliance_score": avg_compliance_score,
+                "avg_best_practices_score": avg_best_practices_score,
+                "syntax_valid_pct": syntax_valid_pct,
+                "compliant_pct": compliant_pct,
+                "total_sql": float(total_results),
+                "translation_duration_sec": translation_duration,
+                "evaluation_duration_sec": evaluation_duration,
+                "total_duration_sec": translation_duration + evaluation_duration
+            })
+            
+            # Log translation result as artifact
+            mlflow.log_dict(translation_result, "translation_result.json")
+            
+            logger.info(f"Average compliance score: {avg_compliance_score:.2f}")
+            logger.info(f"Average best practices score: {avg_best_practices_score:.2f}")
+            logger.info(f"Syntax valid: {syntax_valid_pct:.1f}%")
+            logger.info(f"Compliant: {compliant_pct:.1f}% (Score >= 70)")
+            
+            # Log top issues if any
+            if all_issues:
+                logger.info("\n❕ Top Issues Found:")
+                # Group by description to find most common issues
+                issue_counts = {}
+                for issue in all_issues:
+                    desc = issue.get("description", "Unknown issue")
+                    issue_counts[desc] = issue_counts.get(desc, 0) + 1
+                
+                # Sort and show top 5
+                sorted_issues = sorted(issue_counts.items(), key=lambda x: x[1], reverse=True)
+                for desc, count in sorted_issues[:5]:
+                    logger.info(f"  - [{count}x] {desc}")
+            
+            # Log issues to MLflow for searchability
+            if all_issues:
+                # Tag run with issue categories for filtering
+                issue_categories = set(issue.get("type", "unknown") for issue in all_issues)
+                mlflow.set_tags({
+                    f"has_{cat}_issues": "true" for cat in issue_categories
+                })
+                mlflow.set_tag("total_issues_count", len(all_issues))
+                
+                # Log issues as a table for querying in MLflow UI
+                import pandas as pd
+                issues_df = pd.DataFrame([
+                    {
+                        "sql_index": issue.get("sql_idx", -1),
+                        "category": issue.get("type", "unknown"),
+                        "severity": issue.get("severity", "warning"),
+                        "description": issue.get("description", "")[:200],  # Truncate long descriptions
+                    }
+                    for issue in all_issues
+                ])
+                mlflow.log_table(issues_df, "issues_table.json")
+                
+                # Log top issues summary as text
+                top_issues_text = "Top Issues:\n" + "\n".join(
+                    f"  [{count}x] {desc}" for desc, count in sorted_issues[:10]
+                )
+                mlflow.log_text(top_issues_text, "top_issues_summary.txt")
+            
+            return {
+
+                "model_name": model_config.name,
+                "endpoint": model_config.endpoint,
+                "temperature": model_config.temperature,
+                "avg_compliance_score": avg_compliance_score,
+                "syntax_valid_pct": syntax_valid_pct,
+                "compliant_pct": compliant_pct,
+                "total_sql_generated": total_results,
+                "translation_duration_sec": translation_duration,
+                "evaluation_duration_sec": evaluation_duration,
+            }
+
+
+def run_benchmark(
+    artifact_type: str,
+    dataset_source: Optional[str] = None,
+    experiment_name: str = "sql-translation-benchmark",
+    model_configs: Optional[List[ModelConfig]] = None,
+    batch_size: int = 10,
+    judge_endpoint: Optional[str] = None
+) -> pd.DataFrame:
+    """
+    Convenience function to run a complete benchmark.
+    
+    Args:
+        artifact_type: Type of artifact to benchmark
+        dataset_source: Optional path to dataset file
+        experiment_name: MLflow experiment name
+        model_configs: Optional list of model configurations
+        batch_size: Batch size for translation
+        judge_endpoint: Optional LLM endpoint for judging
+        
+    Returns:
+        DataFrame with benchmark results
+    """
+    runner = BenchmarkRunner(experiment_name=experiment_name)
+    
+    return runner.run_benchmark(
+        artifact_type=artifact_type,
+        dataset_source=dataset_source,
+        model_configs=model_configs,
+        batch_size=batch_size,
+        judge_endpoint=judge_endpoint
+    )
+
+
+def main():
+    """CLI entry point for running benchmarks."""
+    import argparse
+    
+    parser = argparse.ArgumentParser(
+        description="Run SQL translation model benchmarking"
+    )
+    parser.add_argument(
+        "--artifact-type",
+        type=str,
+        required=True,
+        help="Type of artifact to benchmark (tables, views, procedures, etc.)"
+    )
+    parser.add_argument(
+        "--dataset-source",
+        type=str,
+        help="Path to dataset JSON file (optional)"
+    )
+    parser.add_argument(
+        "--experiment-name",
+        type=str,
+        default="sql-translation-benchmark",
+        help="MLflow experiment name"
+    )
+    parser.add_argument(
+        "--batch-size",
+        type=int,
+        default=10,
+        help="Batch size for translation"
+    )
+    parser.add_argument(
+        "--judge-endpoint",
+        type=str,
+        help="Databricks LLM endpoint to use for judging (optional)"
+    )
+    parser.add_argument(
+        "--test-mode",
+        action="store_true",
+        help="Run in test mode with minimal data"
+    )
+    
+    args = parser.parse_args()
+    
+    # Setup logging
+    logging.basicConfig(
+        level=logging.INFO,
+        format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
+    )
+    
+    # Run benchmark
+    try:
+        results_df = run_benchmark(
+            artifact_type=args.artifact_type,
+            dataset_source=args.dataset_source,
+            experiment_name=args.experiment_name,
+            batch_size=args.batch_size if not args.test_mode else 2,
+            judge_endpoint=args.judge_endpoint
+        )
+        
+        print("\n" + "="*60)
+        print("Benchmark Complete!")
+        print("="*60)
+        print(f"\nResults saved to MLflow experiment: {args.experiment_name}")
+        print("\nView results in MLflow UI:")
+        print("  mlflow ui")
+        print("\nBenchmark Summary:")
+        print(results_df.to_string())
+        
+    except Exception as e:
+        logger.error(f"Benchmark failed: {str(e)}")
+        raise
+
+
+if __name__ == "__main__":
+    main()
diff --git a/src/artifact_translation_package/prompts/evaluation_prompts.py b/src/artifact_translation_package/prompts/evaluation_prompts.py
index 48829af..2df192c 100644
--- a/src/artifact_translation_package/prompts/evaluation_prompts.py
+++ b/src/artifact_translation_package/prompts/evaluation_prompts.py
@@ -20,21 +20,21 @@ class EvaluationPrompts(PromptBase):
 {sql_content}
 
 Evaluate each SQL statement and provide a structured assessment. You must return a JSON object with the following structure:
-{
+{{
     "results": [
-        {
+        {{
             "syntax_valid": boolean,
             "error_message": string (null if syntax is valid),
             "issues": [
-                {
+                {{
                     "description": string,
                     "line_number": integer (optional),
                     "suggestion": string (optional)
-                }
+                }}
             ]
-        }
+        }}
     ]
-}
+}}
 
 The results array must contain one evaluation result for each SQL statement provided, in the same order.
 Focus only on syntax validity. If syntax is valid, set syntax_valid to true and error_message to null. If syntax is invalid, set syntax_valid to false and provide a clear error_message describing the syntax error."""
diff --git a/src/artifact_translation_package/utils/evaluation_models.py b/src/artifact_translation_package/utils/evaluation_models.py
index dc2a9bc..cefb5a2 100644
--- a/src/artifact_translation_package/utils/evaluation_models.py
+++ b/src/artifact_translation_package/utils/evaluation_models.py
@@ -45,6 +45,14 @@ class SQLIssue(BaseModel):
         default=None,
         description="Suggestion for fixing the error (optional)"
     )
+    category: Optional[str] = Field(
+        default="syntax",
+        description="Category of the issue: syntax, naming, types, performance, documentation"
+    )
+    severity: Optional[str] = Field(
+        default="error",
+        description="Severity of the issue: critical, error, warning, info"
+    )
 
 
 class SQLEvaluationResult(BaseModel):
@@ -52,13 +60,21 @@ class SQLEvaluationResult(BaseModel):
     syntax_valid: bool = Field(
         description="Whether the SQL syntax is valid for Databricks"
     )
+    score: int = Field(
+        default=0,
+        description="Compliance score from 0-100 based on strict rubric"
+    )
+    best_practices_score: int = Field(
+        default=0,
+        description="Best practices score from 0-100 for optimization and documentation"
+    )
     error_message: Optional[str] = Field(
         default=None,
         description="Error message if syntax is invalid, None if valid"
     )
     issues: List[SQLIssue] = Field(
         default_factory=list,
-        description="List of syntax errors found during evaluation"
+        description="List of syntax errors or improvement opportunities found"
     )