diff --git a/fieldExtraction/poetry.lock b/fieldExtraction/poetry.lock
index aca7853..1695f3f 100644
--- a/fieldExtraction/poetry.lock
+++ b/fieldExtraction/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 2.0.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 2.1.4 and should not be changed by hand.
 
 [[package]]
 name = "aiohappyeyeballs"
@@ -118,7 +118,7 @@ propcache = ">=0.2.0"
 yarl = ">=1.17.0,<2.0"
 
 [package.extras]
-speedups = ["Brotli", "aiodns (>=3.3.0)", "brotlicffi"]
+speedups = ["Brotli ; platform_python_implementation == \"CPython\"", "aiodns (>=3.3.0)", "brotlicffi ; platform_python_implementation != \"CPython\""]
 
 [[package]]
 name = "aiosignal"
@@ -222,6 +222,45 @@ files = [
 [package.dependencies]
 argon2-cffi-bindings = "*"
 
+[[package]]
+name = "argon2-cffi-bindings"
+version = "21.2.0"
+description = "Low-level CFFI bindings for Argon2"
+optional = false
+python-versions = ">=3.6"
+groups = ["dev"]
+markers = "python_version >= \"3.14\""
+files = [
+    {file = "argon2-cffi-bindings-21.2.0.tar.gz", hash = "sha256:bb89ceffa6c791807d1305ceb77dbfacc5aa499891d2c55661c6459651fc39e3"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:ccb949252cb2ab3a08c02024acb77cfb179492d5701c7cbdbfd776124d4d2367"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9524464572e12979364b7d600abf96181d3541da11e23ddf565a32e70bd4dc0d"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b746dba803a79238e925d9046a63aa26bf86ab2a2fe74ce6b009a1c3f5c8f2ae"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:58ed19212051f49a523abb1dbe954337dc82d947fb6e5a0da60f7c8471a8476c"},
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+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-win32.whl", hash = "sha256:603ca0aba86b1349b147cab91ae970c63118a0f30444d4bc80355937c950c082"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-win_amd64.whl", hash = "sha256:b2ef1c30440dbbcba7a5dc3e319408b59676e2e039e2ae11a8775ecf482b192f"},
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+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d4966ef5848d820776f5f562a7d45fdd70c2f330c961d0d745b784034bd9f48d"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:20ef543a89dee4db46a1a6e206cd015360e5a75822f76df533845c3cbaf72670"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ed2937d286e2ad0cc79a7087d3c272832865f779430e0cc2b4f3718d3159b0cb"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:5e00316dabdaea0b2dd82d141cc66889ced0cdcbfa599e8b471cf22c620c329a"},
+]
+
+[package.dependencies]
+cffi = ">=1.0.1"
+
+[package.extras]
+dev = ["cogapp", "pre-commit", "pytest", "wheel"]
+tests = ["pytest"]
+
 [[package]]
 name = "argon2-cffi-bindings"
 version = "25.1.0"
@@ -229,6 +268,7 @@ description = "Low-level CFFI bindings for Argon2"
 optional = false
 python-versions = ">=3.9"
 groups = ["dev"]
+markers = "python_version < \"3.14\""
 files = [
     {file = "argon2_cffi_bindings-25.1.0-cp314-cp314t-macosx_10_13_universal2.whl", hash = "sha256:3d3f05610594151994ca9ccb3c771115bdb4daef161976a266f0dd8aa9996b8f"},
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@@ -259,10 +299,7 @@ files = [
 ]
 
 [package.dependencies]
-cffi = [
-    {version = ">=1.0.1", markers = "python_version < \"3.14\""},
-    {version = ">=2.0.0b1", markers = "python_version >= \"3.14\""},
-]
+cffi = {version = ">=1.0.1", markers = "python_version < \"3.14\""}
 
 [[package]]
 name = "arrow"
@@ -325,12 +362,12 @@ files = [
 ]
 
 [package.extras]
-benchmark = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
-cov = ["cloudpickle", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
-dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit-uv", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+benchmark = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"]
+cov = ["cloudpickle ; platform_python_implementation == \"CPython\"", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"]
+dev = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pre-commit-uv", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"]
 docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier"]
-tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
-tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"]
+tests = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"]
+tests-mypy = ["mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\""]
 
 [[package]]
 name = "babel"
@@ -345,95 +382,18 @@ files = [
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-
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-
-[package.extras]
-tests = ["pytest (>=3.2.1,!=3.3.0)"]
-typecheck = ["mypy"]
+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 = "4.13.4"
+version = "4.13.5"
 description = "Screen-scraping library"
 optional = false
 python-versions = ">=3.7.0"
 groups = ["dev"]
 files = [
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 ]
 
 [package.dependencies]
@@ -513,18 +473,18 @@ css = ["tinycss2 (>=1.1.0,<1.5)"]
 
 [[package]]
 name = "boto3"
-version = "1.40.4"
+version = "1.40.17"
 description = "The AWS SDK for Python"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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 [package.dependencies]
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+botocore = ">=1.40.17,<1.41.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.13.0,<0.14.0"
 
@@ -533,14 +493,14 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.40.4"
+version = "1.40.17"
 description = "Low-level, data-driven core of boto 3."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -549,40 +509,7 @@ python-dateutil = ">=2.1,<3.0.0"
 urllib3 = {version = ">=1.25.4,<2.2.0 || >2.2.0,<3", markers = "python_version >= \"3.10\""}
 
 [package.extras]
-crt = ["awscrt (==0.23.8)"]
-
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-name = "build"
-version = "1.3.0"
-description = "A simple, correct Python build frontend"
-optional = false
-python-versions = ">=3.9"
-groups = ["main"]
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-colorama = {version = "*", markers = "os_name == \"nt\""}
-packaging = ">=19.1"
-pyproject_hooks = "*"
-
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-uv = ["uv (>=0.1.18)"]
-virtualenv = ["virtualenv (>=20.11)", "virtualenv (>=20.17)", "virtualenv (>=20.31)"]
-
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-description = "Extensible memoizing collections and decorators"
-optional = false
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-groups = ["main"]
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-]
+crt = ["awscrt (==0.27.6)"]
 
 [[package]]
 name = "certifi"
@@ -602,7 +529,7 @@ version = "1.17.1"
 description = "Foreign Function Interface for Python calling C code."
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
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 [package.dependencies]
 pycparser = "*"
 
-[[package]]
-name = "cffi"
-version = "2.0.0b1"
-description = "Foreign Function Interface for Python calling C code."
-optional = false
-python-versions = ">=3.9"
-groups = ["main", "dev"]
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 name = "comm"
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 [package.extras]
-toml = ["tomli"]
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 [[package]]
 name = "dataclasses-json"
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 [[package]]
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 [package.extras]
-tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipython", "littleutils", "pytest", "rich"]
+tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipython", "littleutils", "pytest", "rich ; python_version >= \"3.11\""]
 
 [[package]]
 name = "faiss-cpu"
@@ -1221,6 +958,7 @@ description = "A library for efficient similarity search and clustering of dense
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
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 packaging = "*"
 
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@@ -1284,31 +1092,14 @@ devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benc
 
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 name = "filelock"
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 [[package]]
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 ssh = ["paramiko"]
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 tqdm = ["tqdm"]
 
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 [[package]]
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 version = "3.2.4"
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 test = ["objgraph", "psutil", "setuptools"]
 
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 python-versions = ">=3.8"
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 socks = ["socksio (==1.*)"]
 trio = ["trio (>=0.22.0,<1.0)"]
 
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-
-[package.extras]
-test = ["Cython (>=0.29.24)"]
-
 [[package]]
 name = "httpx"
 version = "0.28.1"
@@ -1786,7 +1412,7 @@ httpcore = "==1.*"
 idna = "*"
 
 [package.extras]
-brotli = ["brotli", "brotlicffi"]
+brotli = ["brotli ; platform_python_implementation == \"CPython\"", "brotlicffi ; platform_python_implementation != \"CPython\""]
 cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"]
 http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
@@ -1806,14 +1432,14 @@ files = [
 
 [[package]]
 name = "huggingface-hub"
-version = "0.34.3"
+version = "0.34.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.8.0"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -1827,37 +1453,22 @@ tqdm = ">=4.42.1"
 typing-extensions = ">=3.7.4.3"
 
 [package.extras]
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 cli = ["InquirerPy (==0.3.4)"]
-dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "authlib (>=1.3.2)", "fastapi", "gradio (>=4.0.0)", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "mypy (>=1.14.1,<1.15.0)", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
+dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "authlib (>=1.3.2)", "fastapi", "gradio (>=4.0.0)", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0) ; python_version >= \"3.9\"", "mypy (>=1.14.1,<1.15.0) ; python_version == \"3.8\"", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
 hf-transfer = ["hf-transfer (>=0.1.4)"]
 hf-xet = ["hf-xet (>=1.1.2,<2.0.0)"]
 inference = ["aiohttp"]
 mcp = ["aiohttp", "mcp (>=1.8.0)", "typer"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
-quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "mypy (>=1.14.1,<1.15.0)", "ruff (>=0.9.0)"]
+quality = ["libcst (>=1.4.0)", "mypy (==1.15.0) ; python_version >= \"3.9\"", "mypy (>=1.14.1,<1.15.0) ; python_version == \"3.8\"", "ruff (>=0.9.0)"]
 tensorflow = ["graphviz", "pydot", "tensorflow"]
 tensorflow-testing = ["keras (<3.0)", "tensorflow"]
 testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "authlib (>=1.3.2)", "fastapi", "gradio (>=4.0.0)", "httpx", "itsdangerous", "jedi", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
 torch = ["safetensors[torch]", "torch"]
 typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
 
-[[package]]
-name = "humanfriendly"
-version = "10.0"
-description = "Human friendly output for text interfaces using Python"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
-groups = ["main"]
-files = [
-    {file = "humanfriendly-10.0-py2.py3-none-any.whl", hash = "sha256:1697e1a8a8f550fd43c2865cd84542fc175a61dcb779b6fee18cf6b6ccba1477"},
-    {file = "humanfriendly-10.0.tar.gz", hash = "sha256:6b0b831ce8f15f7300721aa49829fc4e83921a9a301cc7f606be6686a2288ddc"},
-]
-
-[package.dependencies]
-pyreadline3 = {version = "*", markers = "sys_platform == \"win32\" and python_version >= \"3.8\""}
-
 [[package]]
 name = "idna"
 version = "3.10"
@@ -1873,50 +1484,6 @@ files = [
 [package.extras]
 all = ["flake8 (>=7.1.1)", "mypy (>=1.11.2)", "pytest (>=8.3.2)", "ruff (>=0.6.2)"]
 
-[[package]]
-name = "importlib-metadata"
-version = "8.7.0"
-description = "Read metadata from Python packages"
-optional = false
-python-versions = ">=3.9"
-groups = ["main"]
-files = [
-    {file = "importlib_metadata-8.7.0-py3-none-any.whl", hash = "sha256:e5dd1551894c77868a30651cef00984d50e1002d06942a7101d34870c5f02afd"},
-    {file = "importlib_metadata-8.7.0.tar.gz", hash = "sha256:d13b81ad223b890aa16c5471f2ac3056cf76c5f10f82d6f9292f0b415f389000"},
-]
-
-[package.dependencies]
-zipp = ">=3.20"
-
-[package.extras]
-check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
-cover = ["pytest-cov"]
-doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-enabler = ["pytest-enabler (>=2.2)"]
-perf = ["ipython"]
-test = ["flufl.flake8", "importlib_resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"]
-type = ["pytest-mypy"]
-
-[[package]]
-name = "importlib-resources"
-version = "6.5.2"
-description = "Read resources from Python packages"
-optional = false
-python-versions = ">=3.9"
-groups = ["main"]
-files = [
-    {file = "importlib_resources-6.5.2-py3-none-any.whl", hash = "sha256:789cfdc3ed28c78b67a06acb8126751ced69a3d5f79c095a98298cd8a760ccec"},
-    {file = "importlib_resources-6.5.2.tar.gz", hash = "sha256:185f87adef5bcc288449d98fb4fba07cea78bc036455dd44c5fc4a2fe78fed2c"},
-]
-
-[package.extras]
-check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
-cover = ["pytest-cov"]
-doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-enabler = ["pytest-enabler (>=2.2)"]
-test = ["jaraco.test (>=5.4)", "pytest (>=6,!=8.1.*)", "zipp (>=3.17)"]
-type = ["pytest-mypy"]
-
 [[package]]
 name = "iniconfig"
 version = "2.1.0"
@@ -2213,18 +1780,18 @@ files = [
 
 [[package]]
 name = "json5"
-version = "0.12.0"
+version = "0.12.1"
 description = "A Python implementation of the JSON5 data format."
 optional = false
 python-versions = ">=3.8.0"
 groups = ["dev"]
 files = [
-    {file = "json5-0.12.0-py3-none-any.whl", hash = "sha256:6d37aa6c08b0609f16e1ec5ff94697e2cbbfbad5ac112afa05794da9ab7810db"},
-    {file = "json5-0.12.0.tar.gz", hash = "sha256:0b4b6ff56801a1c7dc817b0241bca4ce474a0e6a163bfef3fc594d3fd263ff3a"},
+    {file = "json5-0.12.1-py3-none-any.whl", hash = "sha256:d9c9b3bc34a5f54d43c35e11ef7cb87d8bdd098c6ace87117a7b7e83e705c1d5"},
+    {file = "json5-0.12.1.tar.gz", hash = "sha256:b2743e77b3242f8d03c143dd975a6ec7c52e2f2afe76ed934e53503dd4ad4990"},
 ]
 
 [package.extras]
-dev = ["build (==1.2.2.post1)", "coverage (==7.5.4)", "coverage (==7.8.0)", "mypy (==1.14.1)", "mypy (==1.15.0)", "pip (==25.0.1)", "pylint (==3.2.7)", "pylint (==3.3.6)", "ruff (==0.11.2)", "twine (==6.1.0)", "uv (==0.6.11)"]
+dev = ["build (==1.2.2.post1)", "coverage (==7.5.4) ; python_version < \"3.9\"", "coverage (==7.8.0) ; python_version >= \"3.9\"", "mypy (==1.14.1) ; python_version < \"3.9\"", "mypy (==1.15.0) ; python_version >= \"3.9\"", "pip (==25.0.1)", "pylint (==3.2.7) ; python_version < \"3.9\"", "pylint (==3.3.6) ; python_version >= \"3.9\"", "ruff (==0.11.2)", "twine (==6.1.0)", "uv (==0.6.11)"]
 
 [[package]]
 name = "jsonpatch"
@@ -2255,14 +1822,14 @@ files = [
 
 [[package]]
 name = "jsonschema"
-version = "4.25.0"
+version = "4.25.1"
 description = "An implementation of JSON Schema validation for Python"
 optional = false
 python-versions = ">=3.9"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
-    {file = "jsonschema-4.25.0-py3-none-any.whl", hash = "sha256:24c2e8da302de79c8b9382fee3e76b355e44d2a4364bb207159ce10b517bd716"},
-    {file = "jsonschema-4.25.0.tar.gz", hash = "sha256:e63acf5c11762c0e6672ffb61482bdf57f0876684d8d249c0fe2d730d48bc55f"},
+    {file = "jsonschema-4.25.1-py3-none-any.whl", hash = "sha256:3fba0169e345c7175110351d456342c364814cfcf3b964ba4587f22915230a63"},
+    {file = "jsonschema-4.25.1.tar.gz", hash = "sha256:e4a9655ce0da0c0b67a085847e00a3a51449e1157f4f75e9fb5aa545e122eb85"},
 ]
 
 [package.dependencies]
@@ -2290,7 +1857,7 @@ version = "2025.4.1"
 description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
 optional = false
 python-versions = ">=3.9"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "jsonschema_specifications-2025.4.1-py3-none-any.whl", hash = "sha256:4653bffbd6584f7de83a67e0d620ef16900b390ddc7939d56684d6c81e33f1af"},
     {file = "jsonschema_specifications-2025.4.1.tar.gz", hash = "sha256:630159c9f4dbea161a6a2205c3011cc4f18ff381b189fff48bb39b9bf26ae608"},
@@ -2340,7 +1907,7 @@ traitlets = ">=5.3"
 
 [package.extras]
 docs = ["ipykernel", "myst-parser", "pydata-sphinx-theme", "sphinx (>=4)", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
-test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pytest (<8.2.0)", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"]
+test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko ; sys_platform == \"win32\"", "pre-commit", "pytest (<8.2.0)", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"]
 
 [[package]]
 name = "jupyter-console"
@@ -2432,14 +1999,14 @@ jupyter_server = ">=1.1.2"
 
 [[package]]
 name = "jupyter-server"
-version = "2.16.0"
+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-2.16.0-py3-none-any.whl", hash = "sha256:3d8db5be3bc64403b1c65b400a1d7f4647a5ce743f3b20dbdefe8ddb7b55af9e"},
-    {file = "jupyter_server-2.16.0.tar.gz", hash = "sha256:65d4b44fdf2dcbbdfe0aa1ace4a842d4aaf746a2b7b168134d5aaed35621b7f6"},
+    {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]
@@ -2452,7 +2019,6 @@ jupyter-events = ">=0.11.0"
 jupyter-server-terminals = ">=0.4.4"
 nbconvert = ">=6.4.4"
 nbformat = ">=5.3.0"
-overrides = ">=5.0"
 packaging = ">=22.0"
 prometheus-client = ">=0.9"
 pywinpty = {version = ">=2.0.1", markers = "os_name == \"nt\""}
@@ -2489,20 +2055,20 @@ test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (>
 
 [[package]]
 name = "jupyterlab"
-version = "4.4.5"
+version = "4.4.6"
 description = "JupyterLab computational environment"
 optional = false
 python-versions = ">=3.9"
 groups = ["dev"]
 files = [
-    {file = "jupyterlab-4.4.5-py3-none-any.whl", hash = "sha256:e76244cceb2d1fb4a99341f3edc866f2a13a9e14c50368d730d75d8017be0863"},
-    {file = "jupyterlab-4.4.5.tar.gz", hash = "sha256:0bd6c18e6a3c3d91388af6540afa3d0bb0b2e76287a7b88ddf20ab41b336e595"},
+    {file = "jupyterlab-4.4.6-py3-none-any.whl", hash = "sha256:e877e930f46dde2e3ee9da36a935c6cd4fdb15aa7440519d0fde696f9fadb833"},
+    {file = "jupyterlab-4.4.6.tar.gz", hash = "sha256:e0b720ff5392846bdbc01745f32f29f4d001c071a4bff94d8b516ba89b5a4157"},
 ]
 
 [package.dependencies]
 async-lru = ">=1.0.0"
-httpx = ">=0.25.0"
-ipykernel = ">=6.5.0"
+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"
@@ -2571,34 +2137,6 @@ files = [
     {file = "jupyterlab_widgets-3.0.15.tar.gz", hash = "sha256:2920888a0c2922351a9202817957a68c07d99673504d6cd37345299e971bb08b"},
 ]
 
-[[package]]
-name = "kubernetes"
-version = "33.1.0"
-description = "Kubernetes python client"
-optional = false
-python-versions = ">=3.6"
-groups = ["main"]
-files = [
-    {file = "kubernetes-33.1.0-py2.py3-none-any.whl", hash = "sha256:544de42b24b64287f7e0aa9513c93cb503f7f40eea39b20f66810011a86eabc5"},
-    {file = "kubernetes-33.1.0.tar.gz", hash = "sha256:f64d829843a54c251061a8e7a14523b521f2dc5c896cf6d65ccf348648a88993"},
-]
-
-[package.dependencies]
-certifi = ">=14.05.14"
-durationpy = ">=0.7"
-google-auth = ">=1.0.1"
-oauthlib = ">=3.2.2"
-python-dateutil = ">=2.5.3"
-pyyaml = ">=5.4.1"
-requests = "*"
-requests-oauthlib = "*"
-six = ">=1.9.0"
-urllib3 = ">=1.24.2"
-websocket-client = ">=0.32.0,<0.40.0 || >0.40.0,<0.41.dev0 || >=0.43.dev0"
-
-[package.extras]
-adal = ["adal (>=1.0.2)"]
-
 [[package]]
 name = "langchain"
 version = "0.3.27"
@@ -2641,84 +2179,64 @@ xai = ["langchain-xai"]
 
 [[package]]
 name = "langchain-aws"
-version = "0.2.30"
+version = "0.2.31"
 description = "An integration package connecting AWS and LangChain"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "langchain_aws-0.2.30-py3-none-any.whl", hash = "sha256:947fe4ece30bde0a37ea721b87049d7642607bd2ba9d2d93c9890736972b4274"},
-    {file = "langchain_aws-0.2.30.tar.gz", hash = "sha256:67c31f0784045a4a73ef78a2c18f392e14c1e9f7b55870e62f18039cadfb925c"},
+    {file = "langchain_aws-0.2.31-py3-none-any.whl", hash = "sha256:dc46bd7e198f0a3c119bb26a9329a572e7898108aa00057198be3916f477e988"},
+    {file = "langchain_aws-0.2.31.tar.gz", hash = "sha256:7e0257d50b05d0fc2f2763c50f93151fd06326e2f55286673289b0ddfc83e52b"},
 ]
 
 [package.dependencies]
 boto3 = ">=1.39.7"
-langchain-core = ">=0.3.72,<0.4.0"
+langchain-core = ">=0.3.74,<0.4.0"
 numpy = {version = ">=1.26.0,<3", markers = "python_version >= \"3.12\""}
 pydantic = ">=2.10.0,<3"
 
 [package.extras]
-tools = ["beautifulsoup4 (>=4.13.4)", "bedrock-agentcore (>=0.1.0)", "playwright (>=1.53.0)"]
-
-[[package]]
-name = "langchain-chroma"
-version = "0.2.5"
-description = "An integration package connecting Chroma and LangChain."
-optional = false
-python-versions = ">=3.9"
-groups = ["main"]
-files = [
-    {file = "langchain_chroma-0.2.5-py3-none-any.whl", hash = "sha256:dcb80330cd8ac9a87695a5ba237a15affeb805751bdb42dee213b12e0d379825"},
-    {file = "langchain_chroma-0.2.5.tar.gz", hash = "sha256:b63e9df8c3fbb316313c232214b7bc8b696a505039a6f7adf29b992a74cc4b2e"},
-]
-
-[package.dependencies]
-chromadb = ">=1.0.9"
-langchain-core = ">=0.3.70"
-numpy = [
-    {version = ">=1.26.0", markers = "python_version < \"3.13\""},
-    {version = ">=2.1.0", markers = "python_version >= \"3.13\""},
-]
+tools = ["beautifulsoup4 (>=4.13.4)", "bedrock-agentcore (>=0.1.0) ; python_version >= \"3.10\"", "playwright (>=1.53.0)"]
 
 [[package]]
 name = "langchain-community"
-version = "0.3.27"
+version = "0.3.28"
 description = "Community contributed LangChain integrations."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "langchain_community-0.3.27-py3-none-any.whl", hash = "sha256:581f97b795f9633da738ea95da9cb78f8879b538090c9b7a68c0aed49c828f0d"},
-    {file = "langchain_community-0.3.27.tar.gz", hash = "sha256:e1037c3b9da0c6d10bf06e838b034eb741e016515c79ef8f3f16e53ead33d882"},
+    {file = "langchain_community-0.3.28-py3-none-any.whl", hash = "sha256:52e437b8f4e899ff59fb90c54b5320bf99153da34f214488ebacdbc969a50faf"},
+    {file = "langchain_community-0.3.28.tar.gz", hash = "sha256:c97e03d91cade6c9fb73d756119744e1d4c4ea4b6b0a09f6faadfbb7360d335e"},
 ]
 
 [package.dependencies]
 aiohttp = ">=3.8.3,<4.0.0"
-dataclasses-json = ">=0.5.7,<0.7"
+dataclasses-json = ">=0.6.7,<0.7"
 httpx-sse = ">=0.4.0,<1.0.0"
-langchain = ">=0.3.26,<1.0.0"
-langchain-core = ">=0.3.66,<1.0.0"
+langchain = ">=0.3.27,<1.0.0"
+langchain-core = ">=0.3.74,<1.0.0"
 langsmith = ">=0.1.125"
 numpy = [
     {version = ">=1.26.2", markers = "python_version < \"3.13\""},
     {version = ">=2.1.0", markers = "python_version >= \"3.13\""},
 ]
-pydantic-settings = ">=2.4.0,<3.0.0"
+pydantic-settings = ">=2.10.1,<3.0.0"
 PyYAML = ">=5.3"
-requests = ">=2,<3"
+requests = ">=2.32.5,<3"
 SQLAlchemy = ">=1.4,<3"
 tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10"
 
 [[package]]
 name = "langchain-core"
-version = "0.3.72"
+version = "0.3.75"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "langchain_core-0.3.72-py3-none-any.whl", hash = "sha256:9fa15d390600eb6b6544397a7aa84be9564939b6adf7a2b091179ea30405b240"},
-    {file = "langchain_core-0.3.72.tar.gz", hash = "sha256:4de3828909b3d7910c313242ab07b241294650f5cb6eac17738dd3638b1cd7de"},
+    {file = "langchain_core-0.3.75-py3-none-any.whl", hash = "sha256:03ca1fadf955ee3c7d5806a841f4b3a37b816acea5e61a7e6ba1298c05eea7f5"},
+    {file = "langchain_core-0.3.75.tar.gz", hash = "sha256:ab0eb95a06ed6043f76162e6086b45037690cb70b7f090bd83b5ebb8a05b70ed"},
 ]
 
 [package.dependencies]
@@ -2764,14 +2282,14 @@ types-requests = ">=2.31.0.2,<3.0.0.0"
 
 [[package]]
 name = "langsmith"
-version = "0.4.13"
+version = "0.4.18"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "langsmith-0.4.13-py3-none-any.whl", hash = "sha256:dab7b16ee16986995007bf5a777f45c18f8bf7453f67ae2ebcb46ce43c214297"},
-    {file = "langsmith-0.4.13.tar.gz", hash = "sha256:1ae7dbb5d8150647406f49885a2dd16ab12bd990254b5dc23718838b3d086fde"},
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@@ -2808,31 +2326,6 @@ interegular = ["interegular (>=0.3.1,<0.4.0)"]
 nearley = ["js2py"]
 regex = ["regex"]
 
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-
 [[package]]
 name = "markupsafe"
 version = "3.0.2"
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 [package.dependencies]
 traitlets = "*"
 
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+    {file = "multidict-6.6.4-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:0b2e886624be5773e69cf32bcb8534aecdeb38943520b240fed3d5596a430f2f"},
+    {file = "multidict-6.6.4-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:be5bf4b3224948032a845d12ab0f69f208293742df96dc14c4ff9b09e508fc17"},
+    {file = "multidict-6.6.4-cp39-cp39-win32.whl", hash = "sha256:10a68a9191f284fe9d501fef4efe93226e74df92ce7a24e301371293bd4918ae"},
+    {file = "multidict-6.6.4-cp39-cp39-win_amd64.whl", hash = "sha256:ee25f82f53262f9ac93bd7e58e47ea1bdcc3393cef815847e397cba17e284210"},
+    {file = "multidict-6.6.4-cp39-cp39-win_arm64.whl", hash = "sha256:f9867e55590e0855bcec60d4f9a092b69476db64573c9fe17e92b0c50614c16a"},
+    {file = "multidict-6.6.4-py3-none-any.whl", hash = "sha256:27d8f8e125c07cb954e54d75d04905a9bba8a439c1d84aca94949d4d03d8601c"},
+    {file = "multidict-6.6.4.tar.gz", hash = "sha256:d2d4e4787672911b48350df02ed3fa3fffdc2f2e8ca06dd6afdf34189b76a9dd"},
 ]
 
 [[package]]
@@ -3475,7 +2817,7 @@ 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)", "ipykernel", "jupyter-server[test] (>=2.4.0,<3)", "jupyterlab-server[test] (>=2.27.1,<3)", "nbval", "pytest (>=7.0)", "pytest-console-scripts", "pytest-timeout", "pytest-tornasync", "requests"]
+test = ["importlib-resources (>=5.0) ; python_version < \"3.10\"", "ipykernel", "jupyter-server[test] (>=2.4.0,<3)", "jupyterlab-server[test] (>=2.27.1,<3)", "nbval", "pytest (>=7.0)", "pytest-console-scripts", "pytest-timeout", "pytest-tornasync", "requests"]
 
 [[package]]
 name = "notebook-shim"
@@ -3586,13 +2928,27 @@ description = "CUBLAS native runtime libraries"
 optional = false
 python-versions = ">=3"
 groups = ["main"]
-markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version >= \"3.14\""
 files = [
     {file = "nvidia_cublas_cu12-12.6.4.1-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:08ed2686e9875d01b58e3cb379c6896df8e76c75e0d4a7f7dace3d7b6d9ef8eb"},
     {file = "nvidia_cublas_cu12-12.6.4.1-py3-none-manylinux_2_27_aarch64.whl", hash = "sha256:235f728d6e2a409eddf1df58d5b0921cf80cfa9e72b9f2775ccb7b4a87984668"},
     {file = "nvidia_cublas_cu12-12.6.4.1-py3-none-win_amd64.whl", hash = "sha256:9e4fa264f4d8a4eb0cdbd34beadc029f453b3bafae02401e999cf3d5a5af75f8"},
 ]
 
+[[package]]
+name = "nvidia-cublas-cu12"
+version = "12.8.4.1"
+description = "CUBLAS native runtime libraries"
+optional = false
+python-versions = ">=3"
+groups = ["main"]
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.14\""
+files = [
+    {file = "nvidia_cublas_cu12-12.8.4.1-py3-none-manylinux_2_27_aarch64.whl", hash = "sha256:b86f6dd8935884615a0683b663891d43781b819ac4f2ba2b0c9604676af346d0"},
+    {file = "nvidia_cublas_cu12-12.8.4.1-py3-none-manylinux_2_27_x86_64.whl", hash = "sha256:8ac4e771d5a348c551b2a426eda6193c19aa630236b418086020df5ba9667142"},
+    {file = "nvidia_cublas_cu12-12.8.4.1-py3-none-win_amd64.whl", hash = "sha256:47e9b82132fa8d2b4944e708049229601448aaad7e6f296f630f2d1a32de35af"},
+]
+
 [[package]]
 name = "nvidia-cuda-cupti-cu12"
 version = "12.6.80"
@@ -3600,7 +2956,7 @@ description = "CUDA profiling tools runtime libs."
 optional = false
 python-versions = ">=3"
 groups = ["main"]
-markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version >= \"3.14\""
 files = [
     {file = "nvidia_cuda_cupti_cu12-12.6.80-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:166ee35a3ff1587f2490364f90eeeb8da06cd867bd5b701bf7f9a02b78bc63fc"},
     {file = "nvidia_cuda_cupti_cu12-12.6.80-py3-none-manylinux2014_aarch64.whl", hash = "sha256:358b4a1d35370353d52e12f0a7d1769fc01ff74a191689d3870b2123156184c4"},
@@ -3609,6 +2965,20 @@ files = [
     {file = "nvidia_cuda_cupti_cu12-12.6.80-py3-none-win_amd64.whl", hash = "sha256:bbe6ae76e83ce5251b56e8c8e61a964f757175682bbad058b170b136266ab00a"},
 ]
 
+[[package]]
+name = "nvidia-cuda-cupti-cu12"
+version = "12.8.90"
+description = "CUDA profiling tools runtime libs."
+optional = false
+python-versions = ">=3"
+groups = ["main"]
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.14\""
+files = [
+    {file = "nvidia_cuda_cupti_cu12-12.8.90-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:4412396548808ddfed3f17a467b104ba7751e6b58678a4b840675c56d21cf7ed"},
+    {file = "nvidia_cuda_cupti_cu12-12.8.90-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:ea0cb07ebda26bb9b29ba82cda34849e73c166c18162d3913575b0c9db9a6182"},
+    {file = "nvidia_cuda_cupti_cu12-12.8.90-py3-none-win_amd64.whl", hash = "sha256:bb479dcdf7e6d4f8b0b01b115260399bf34154a1a2e9fe11c85c517d87efd98e"},
+]
+
 [[package]]
 name = "nvidia-cuda-nvrtc-cu12"
 version = "12.6.77"
@@ -3616,13 +2986,27 @@ description = "NVRTC native runtime libraries"
 optional = false
 python-versions = ">=3"
 groups = ["main"]
-markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version >= \"3.14\""
 files = [
     {file = "nvidia_cuda_nvrtc_cu12-12.6.77-py3-none-manylinux2014_aarch64.whl", hash = "sha256:5847f1d6e5b757f1d2b3991a01082a44aad6f10ab3c5c0213fa3e25bddc25a13"},
     {file = "nvidia_cuda_nvrtc_cu12-12.6.77-py3-none-manylinux2014_x86_64.whl", hash = "sha256:35b0cc6ee3a9636d5409133e79273ce1f3fd087abb0532d2d2e8fff1fe9efc53"},
     {file = "nvidia_cuda_nvrtc_cu12-12.6.77-py3-none-win_amd64.whl", hash = "sha256:f7007dbd914c56bd80ea31bc43e8e149da38f68158f423ba845fc3292684e45a"},
 ]
 
+[[package]]
+name = "nvidia-cuda-nvrtc-cu12"
+version = "12.8.93"
+description = "NVRTC native runtime libraries"
+optional = false
+python-versions = ">=3"
+groups = ["main"]
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.14\""
+files = [
+    {file = "nvidia_cuda_nvrtc_cu12-12.8.93-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl", hash = "sha256:a7756528852ef889772a84c6cd89d41dfa74667e24cca16bb31f8f061e3e9994"},
+    {file = "nvidia_cuda_nvrtc_cu12-12.8.93-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:fc1fec1e1637854b4c0a65fb9a8346b51dd9ee69e61ebaccc82058441f15bce8"},
+    {file = "nvidia_cuda_nvrtc_cu12-12.8.93-py3-none-win_amd64.whl", hash = "sha256:7a4b6b2904850fe78e0bd179c4b655c404d4bb799ef03ddc60804247099ae909"},
+]
+
 [[package]]
 name = "nvidia-cuda-runtime-cu12"
 version = "12.6.77"
@@ -3630,7 +3014,7 @@ description = "CUDA Runtime native Libraries"
 optional = false
 python-versions = ">=3"
 groups = ["main"]
-markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version >= \"3.14\""
 files = [
     {file = "nvidia_cuda_runtime_cu12-12.6.77-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:6116fad3e049e04791c0256a9778c16237837c08b27ed8c8401e2e45de8d60cd"},
     {file = "nvidia_cuda_runtime_cu12-12.6.77-py3-none-manylinux2014_aarch64.whl", hash = "sha256:d461264ecb429c84c8879a7153499ddc7b19b5f8d84c204307491989a365588e"},
@@ -3639,6 +3023,20 @@ files = [
     {file = "nvidia_cuda_runtime_cu12-12.6.77-py3-none-win_amd64.whl", hash = "sha256:86c58044c824bf3c173c49a2dbc7a6c8b53cb4e4dca50068be0bf64e9dab3f7f"},
 ]
 
+[[package]]
+name = "nvidia-cuda-runtime-cu12"
+version = "12.8.90"
+description = "CUDA Runtime native Libraries"
+optional = false
+python-versions = ">=3"
+groups = ["main"]
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.14\""
+files = [
+    {file = "nvidia_cuda_runtime_cu12-12.8.90-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:52bf7bbee900262ffefe5e9d5a2a69a30d97e2bc5bb6cc866688caa976966e3d"},
+    {file = "nvidia_cuda_runtime_cu12-12.8.90-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:adade8dcbd0edf427b7204d480d6066d33902cab2a4707dcfc48a2d0fd44ab90"},
+    {file = "nvidia_cuda_runtime_cu12-12.8.90-py3-none-win_amd64.whl", hash = "sha256:c0c6027f01505bfed6c3b21ec546f69c687689aad5f1a377554bc6ca4aa993a8"},
+]
+
 [[package]]
 name = "nvidia-cudnn-cu12"
 version = "9.5.1.17"
@@ -3646,7 +3044,7 @@ description = "cuDNN runtime libraries"
 optional = false
 python-versions = ">=3"
 groups = ["main"]
-markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version >= \"3.14\""
 files = [
     {file = "nvidia_cudnn_cu12-9.5.1.17-py3-none-manylinux_2_28_aarch64.whl", hash = "sha256:9fd4584468533c61873e5fda8ca41bac3a38bcb2d12350830c69b0a96a7e4def"},
     {file = "nvidia_cudnn_cu12-9.5.1.17-py3-none-manylinux_2_28_x86_64.whl", hash = "sha256:30ac3869f6db17d170e0e556dd6cc5eee02647abc31ca856634d5a40f82c15b2"},
@@ -3656,6 +3054,23 @@ files = [
 [package.dependencies]
 nvidia-cublas-cu12 = "*"
 
+[[package]]
+name = "nvidia-cudnn-cu12"
+version = "9.10.2.21"
+description = "cuDNN runtime libraries"
+optional = false
+python-versions = ">=3"
+groups = ["main"]
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.14\""
+files = [
+    {file = "nvidia_cudnn_cu12-9.10.2.21-py3-none-manylinux_2_27_aarch64.whl", hash = "sha256:c9132cc3f8958447b4910a1720036d9eff5928cc3179b0a51fb6d167c6cc87d8"},
+    {file = "nvidia_cudnn_cu12-9.10.2.21-py3-none-manylinux_2_27_x86_64.whl", hash = "sha256:949452be657fa16687d0930933f032835951ef0892b37d2d53824d1a84dc97a8"},
+    {file = "nvidia_cudnn_cu12-9.10.2.21-py3-none-win_amd64.whl", hash = "sha256:c6288de7d63e6cf62988f0923f96dc339cea362decb1bf5b3141883392a7d65e"},
+]
+
+[package.dependencies]
+nvidia-cublas-cu12 = "*"
+
 [[package]]
 name = "nvidia-cufft-cu12"
 version = "11.3.0.4"
@@ -3663,7 +3078,7 @@ description = "CUFFT native runtime libraries"
 optional = false
 python-versions = ">=3"
 groups = ["main"]
-markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version >= \"3.14\""
 files = [
     {file = "nvidia_cufft_cu12-11.3.0.4-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:d16079550df460376455cba121db6564089176d9bac9e4f360493ca4741b22a6"},
     {file = "nvidia_cufft_cu12-11.3.0.4-py3-none-manylinux2014_aarch64.whl", hash = "sha256:8510990de9f96c803a051822618d42bf6cb8f069ff3f48d93a8486efdacb48fb"},
@@ -3675,6 +3090,23 @@ files = [
 [package.dependencies]
 nvidia-nvjitlink-cu12 = "*"
 
+[[package]]
+name = "nvidia-cufft-cu12"
+version = "11.3.3.83"
+description = "CUFFT native runtime libraries"
+optional = false
+python-versions = ">=3"
+groups = ["main"]
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.14\""
+files = [
+    {file = "nvidia_cufft_cu12-11.3.3.83-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:848ef7224d6305cdb2a4df928759dca7b1201874787083b6e7550dd6765ce69a"},
+    {file = "nvidia_cufft_cu12-11.3.3.83-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:4d2dd21ec0b88cf61b62e6b43564355e5222e4a3fb394cac0db101f2dd0d4f74"},
+    {file = "nvidia_cufft_cu12-11.3.3.83-py3-none-win_amd64.whl", hash = "sha256:7a64a98ef2a7c47f905aaf8931b69a3a43f27c55530c698bb2ed7c75c0b42cb7"},
+]
+
+[package.dependencies]
+nvidia-nvjitlink-cu12 = "*"
+
 [[package]]
 name = "nvidia-cufile-cu12"
 version = "1.11.1.6"
@@ -3682,12 +3114,25 @@ description = "cuFile GPUDirect libraries"
 optional = false
 python-versions = ">=3"
 groups = ["main"]
-markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version >= \"3.14\""
 files = [
     {file = "nvidia_cufile_cu12-1.11.1.6-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:cc23469d1c7e52ce6c1d55253273d32c565dd22068647f3aa59b3c6b005bf159"},
     {file = "nvidia_cufile_cu12-1.11.1.6-py3-none-manylinux_2_27_aarch64.whl", hash = "sha256:8f57a0051dcf2543f6dc2b98a98cb2719c37d3cee1baba8965d57f3bbc90d4db"},
 ]
 
+[[package]]
+name = "nvidia-cufile-cu12"
+version = "1.13.1.3"
+description = "cuFile GPUDirect libraries"
+optional = false
+python-versions = ">=3"
+groups = ["main"]
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.14\""
+files = [
+    {file = "nvidia_cufile_cu12-1.13.1.3-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:1d069003be650e131b21c932ec3d8969c1715379251f8d23a1860554b1cb24fc"},
+    {file = "nvidia_cufile_cu12-1.13.1.3-py3-none-manylinux_2_27_aarch64.whl", hash = "sha256:4beb6d4cce47c1a0f1013d72e02b0994730359e17801d395bdcbf20cfb3bb00a"},
+]
+
 [[package]]
 name = "nvidia-curand-cu12"
 version = "10.3.7.77"
@@ -3695,7 +3140,7 @@ description = "CURAND native runtime libraries"
 optional = false
 python-versions = ">=3"
 groups = ["main"]
-markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version >= \"3.14\""
 files = [
     {file = "nvidia_curand_cu12-10.3.7.77-py3-none-manylinux2014_aarch64.whl", hash = "sha256:6e82df077060ea28e37f48a3ec442a8f47690c7499bff392a5938614b56c98d8"},
     {file = "nvidia_curand_cu12-10.3.7.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:a42cd1344297f70b9e39a1e4f467a4e1c10f1da54ff7a85c12197f6c652c8bdf"},
@@ -3704,6 +3149,20 @@ files = [
     {file = "nvidia_curand_cu12-10.3.7.77-py3-none-win_amd64.whl", hash = "sha256:6d6d935ffba0f3d439b7cd968192ff068fafd9018dbf1b85b37261b13cfc9905"},
 ]
 
+[[package]]
+name = "nvidia-curand-cu12"
+version = "10.3.9.90"
+description = "CURAND native runtime libraries"
+optional = false
+python-versions = ">=3"
+groups = ["main"]
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.14\""
+files = [
+    {file = "nvidia_curand_cu12-10.3.9.90-py3-none-manylinux_2_27_aarch64.whl", hash = "sha256:dfab99248034673b779bc6decafdc3404a8a6f502462201f2f31f11354204acd"},
+    {file = "nvidia_curand_cu12-10.3.9.90-py3-none-manylinux_2_27_x86_64.whl", hash = "sha256:b32331d4f4df5d6eefa0554c565b626c7216f87a06a4f56fab27c3b68a830ec9"},
+    {file = "nvidia_curand_cu12-10.3.9.90-py3-none-win_amd64.whl", hash = "sha256:f149a8ca457277da854f89cf282d6ef43176861926c7ac85b2a0fbd237c587ec"},
+]
+
 [[package]]
 name = "nvidia-cusolver-cu12"
 version = "11.7.1.2"
@@ -3711,7 +3170,7 @@ description = "CUDA solver native runtime libraries"
 optional = false
 python-versions = ">=3"
 groups = ["main"]
-markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version >= \"3.14\""
 files = [
     {file = "nvidia_cusolver_cu12-11.7.1.2-py3-none-manylinux2014_aarch64.whl", hash = "sha256:0ce237ef60acde1efc457335a2ddadfd7610b892d94efee7b776c64bb1cac9e0"},
     {file = "nvidia_cusolver_cu12-11.7.1.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:e9e49843a7707e42022babb9bcfa33c29857a93b88020c4e4434656a655b698c"},
@@ -3725,6 +3184,25 @@ nvidia-cublas-cu12 = "*"
 nvidia-cusparse-cu12 = "*"
 nvidia-nvjitlink-cu12 = "*"
 
+[[package]]
+name = "nvidia-cusolver-cu12"
+version = "11.7.3.90"
+description = "CUDA solver native runtime libraries"
+optional = false
+python-versions = ">=3"
+groups = ["main"]
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.14\""
+files = [
+    {file = "nvidia_cusolver_cu12-11.7.3.90-py3-none-manylinux_2_27_aarch64.whl", hash = "sha256:db9ed69dbef9715071232caa9b69c52ac7de3a95773c2db65bdba85916e4e5c0"},
+    {file = "nvidia_cusolver_cu12-11.7.3.90-py3-none-manylinux_2_27_x86_64.whl", hash = "sha256:4376c11ad263152bd50ea295c05370360776f8c3427b30991df774f9fb26c450"},
+    {file = "nvidia_cusolver_cu12-11.7.3.90-py3-none-win_amd64.whl", hash = "sha256:4a550db115fcabc4d495eb7d39ac8b58d4ab5d8e63274d3754df1c0ad6a22d34"},
+]
+
+[package.dependencies]
+nvidia-cublas-cu12 = "*"
+nvidia-cusparse-cu12 = "*"
+nvidia-nvjitlink-cu12 = "*"
+
 [[package]]
 name = "nvidia-cusparse-cu12"
 version = "12.5.4.2"
@@ -3732,7 +3210,7 @@ description = "CUSPARSE native runtime libraries"
 optional = false
 python-versions = ">=3"
 groups = ["main"]
-markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version >= \"3.14\""
 files = [
     {file = "nvidia_cusparse_cu12-12.5.4.2-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:d25b62fb18751758fe3c93a4a08eff08effedfe4edf1c6bb5afd0890fe88f887"},
     {file = "nvidia_cusparse_cu12-12.5.4.2-py3-none-manylinux2014_aarch64.whl", hash = "sha256:7aa32fa5470cf754f72d1116c7cbc300b4e638d3ae5304cfa4a638a5b87161b1"},
@@ -3744,6 +3222,23 @@ files = [
 [package.dependencies]
 nvidia-nvjitlink-cu12 = "*"
 
+[[package]]
+name = "nvidia-cusparse-cu12"
+version = "12.5.8.93"
+description = "CUSPARSE native runtime libraries"
+optional = false
+python-versions = ">=3"
+groups = ["main"]
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.14\""
+files = [
+    {file = "nvidia_cusparse_cu12-12.5.8.93-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:9b6c161cb130be1a07a27ea6923df8141f3c295852f4b260c65f18f3e0a091dc"},
+    {file = "nvidia_cusparse_cu12-12.5.8.93-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:1ec05d76bbbd8b61b06a80e1eaf8cf4959c3d4ce8e711b65ebd0443bb0ebb13b"},
+    {file = "nvidia_cusparse_cu12-12.5.8.93-py3-none-win_amd64.whl", hash = "sha256:9a33604331cb2cac199f2e7f5104dfbb8a5a898c367a53dfda9ff2acb6b6b4dd"},
+]
+
+[package.dependencies]
+nvidia-nvjitlink-cu12 = "*"
+
 [[package]]
 name = "nvidia-cusparselt-cu12"
 version = "0.6.3"
@@ -3751,13 +3246,27 @@ description = "NVIDIA cuSPARSELt"
 optional = false
 python-versions = "*"
 groups = ["main"]
-markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version >= \"3.14\""
 files = [
     {file = "nvidia_cusparselt_cu12-0.6.3-py3-none-manylinux2014_aarch64.whl", hash = "sha256:8371549623ba601a06322af2133c4a44350575f5a3108fb75f3ef20b822ad5f1"},
     {file = "nvidia_cusparselt_cu12-0.6.3-py3-none-manylinux2014_x86_64.whl", hash = "sha256:e5c8a26c36445dd2e6812f1177978a24e2d37cacce7e090f297a688d1ec44f46"},
     {file = "nvidia_cusparselt_cu12-0.6.3-py3-none-win_amd64.whl", hash = "sha256:3b325bcbd9b754ba43df5a311488fca11a6b5dc3d11df4d190c000cf1a0765c7"},
 ]
 
+[[package]]
+name = "nvidia-cusparselt-cu12"
+version = "0.7.1"
+description = "NVIDIA cuSPARSELt"
+optional = false
+python-versions = "*"
+groups = ["main"]
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.14\""
+files = [
+    {file = "nvidia_cusparselt_cu12-0.7.1-py3-none-manylinux2014_aarch64.whl", hash = "sha256:8878dce784d0fac90131b6817b607e803c36e629ba34dc5b433471382196b6a5"},
+    {file = "nvidia_cusparselt_cu12-0.7.1-py3-none-manylinux2014_x86_64.whl", hash = "sha256:f1bb701d6b930d5a7cea44c19ceb973311500847f81b634d802b7b539dc55623"},
+    {file = "nvidia_cusparselt_cu12-0.7.1-py3-none-win_amd64.whl", hash = "sha256:f67fbb5831940ec829c9117b7f33807db9f9678dc2a617fbe781cac17b4e1075"},
+]
+
 [[package]]
 name = "nvidia-nccl-cu12"
 version = "2.26.2"
@@ -3765,12 +3274,25 @@ description = "NVIDIA Collective Communication Library (NCCL) Runtime"
 optional = false
 python-versions = ">=3"
 groups = ["main"]
-markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version >= \"3.14\""
 files = [
     {file = "nvidia_nccl_cu12-2.26.2-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:5c196e95e832ad30fbbb50381eb3cbd1fadd5675e587a548563993609af19522"},
     {file = "nvidia_nccl_cu12-2.26.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:694cf3879a206553cc9d7dbda76b13efaf610fdb70a50cba303de1b0d1530ac6"},
 ]
 
+[[package]]
+name = "nvidia-nccl-cu12"
+version = "2.27.3"
+description = "NVIDIA Collective Communication Library (NCCL) Runtime"
+optional = false
+python-versions = ">=3"
+groups = ["main"]
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.14\""
+files = [
+    {file = "nvidia_nccl_cu12-2.27.3-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:9ddf1a245abc36c550870f26d537a9b6087fb2e2e3d6e0ef03374c6fd19d984f"},
+    {file = "nvidia_nccl_cu12-2.27.3-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:adf27ccf4238253e0b826bce3ff5fa532d65fc42322c8bfdfaf28024c0fbe039"},
+]
+
 [[package]]
 name = "nvidia-nvjitlink-cu12"
 version = "12.6.85"
@@ -3778,13 +3300,27 @@ description = "Nvidia JIT LTO Library"
 optional = false
 python-versions = ">=3"
 groups = ["main"]
-markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version >= \"3.14\""
 files = [
     {file = "nvidia_nvjitlink_cu12-12.6.85-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl", hash = "sha256:eedc36df9e88b682efe4309aa16b5b4e78c2407eac59e8c10a6a47535164369a"},
     {file = "nvidia_nvjitlink_cu12-12.6.85-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:cf4eaa7d4b6b543ffd69d6abfb11efdeb2db48270d94dfd3a452c24150829e41"},
     {file = "nvidia_nvjitlink_cu12-12.6.85-py3-none-win_amd64.whl", hash = "sha256:e61120e52ed675747825cdd16febc6a0730537451d867ee58bee3853b1b13d1c"},
 ]
 
+[[package]]
+name = "nvidia-nvjitlink-cu12"
+version = "12.8.93"
+description = "Nvidia JIT LTO Library"
+optional = false
+python-versions = ">=3"
+groups = ["main"]
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.14\""
+files = [
+    {file = "nvidia_nvjitlink_cu12-12.8.93-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl", hash = "sha256:81ff63371a7ebd6e6451970684f916be2eab07321b73c9d244dc2b4da7f73b88"},
+    {file = "nvidia_nvjitlink_cu12-12.8.93-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:adccd7161ace7261e01bb91e44e88da350895c270d23f744f0820c818b7229e7"},
+    {file = "nvidia_nvjitlink_cu12-12.8.93-py3-none-win_amd64.whl", hash = "sha256:bd93fbeeee850917903583587f4fc3a4eafa022e34572251368238ab5e6bd67f"},
+]
+
 [[package]]
 name = "nvidia-nvtx-cu12"
 version = "12.6.77"
@@ -3792,7 +3328,7 @@ description = "NVIDIA Tools Extension"
 optional = false
 python-versions = ">=3"
 groups = ["main"]
-markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version >= \"3.14\""
 files = [
     {file = "nvidia_nvtx_cu12-12.6.77-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:f44f8d86bb7d5629988d61c8d3ae61dddb2015dee142740536bc7481b022fe4b"},
     {file = "nvidia_nvtx_cu12-12.6.77-py3-none-manylinux2014_aarch64.whl", hash = "sha256:adcaabb9d436c9761fca2b13959a2d237c5f9fd406c8e4b723c695409ff88059"},
@@ -3802,58 +3338,19 @@ files = [
 ]
 
 [[package]]
-name = "oauthlib"
-version = "3.3.1"
-description = "A generic, spec-compliant, thorough implementation of the OAuth request-signing logic"
+name = "nvidia-nvtx-cu12"
+version = "12.8.90"
+description = "NVIDIA Tools Extension"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3"
 groups = ["main"]
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.14\""
 files = [
-    {file = "oauthlib-3.3.1-py3-none-any.whl", hash = "sha256:88119c938d2b8fb88561af5f6ee0eec8cc8d552b7bb1f712743136eb7523b7a1"},
-    {file = "oauthlib-3.3.1.tar.gz", hash = "sha256:0f0f8aa759826a193cf66c12ea1af1637f87b9b4622d46e866952bb022e538c9"},
+    {file = "nvidia_nvtx_cu12-12.8.90-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:d7ad891da111ebafbf7e015d34879f7112832fc239ff0d7d776b6cb685274615"},
+    {file = "nvidia_nvtx_cu12-12.8.90-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:5b17e2001cc0d751a5bc2c6ec6d26ad95913324a4adb86788c944f8ce9ba441f"},
+    {file = "nvidia_nvtx_cu12-12.8.90-py3-none-win_amd64.whl", hash = "sha256:619c8304aedc69f02ea82dd244541a83c3d9d40993381b3b590f1adaed3db41e"},
 ]
 
-[package.extras]
-rsa = ["cryptography (>=3.0.0)"]
-signals = ["blinker (>=1.4.0)"]
-signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
-
-[[package]]
-name = "onnxruntime"
-version = "1.22.1"
-description = "ONNX Runtime is a runtime accelerator for Machine Learning models"
-optional = false
-python-versions = ">=3.10"
-groups = ["main"]
-files = [
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-    {file = "onnxruntime-1.22.1-cp313-cp313-macosx_13_0_universal2.whl", hash = "sha256:d29c7d87b6cbed8fecfd09dca471832384d12a69e1ab873e5effbb94adc3e966"},
-    {file = "onnxruntime-1.22.1-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:460487d83b7056ba98f1f7bac80287224c31d8149b15712b0d6f5078fcc33d0f"},
-    {file = "onnxruntime-1.22.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:b0c37070268ba4e02a1a9d28560cd00cd1e94f0d4f275cbef283854f861a65fa"},
-    {file = "onnxruntime-1.22.1-cp313-cp313-win_amd64.whl", hash = "sha256:70980d729145a36a05f74b573435531f55ef9503bcda81fc6c3d6b9306199982"},
-    {file = "onnxruntime-1.22.1-cp313-cp313t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:33a7980bbc4b7f446bac26c3785652fe8730ed02617d765399e89ac7d44e0f7d"},
-    {file = "onnxruntime-1.22.1-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:6e7e823624b015ea879d976cbef8bfaed2f7e2cc233d7506860a76dd37f8f381"},
-]
-
-[package.dependencies]
-coloredlogs = "*"
-flatbuffers = "*"
-numpy = ">=1.21.6"
-packaging = "*"
-protobuf = "*"
-sympy = "*"
-
 [[package]]
 name = "openpyxl"
 version = "3.1.5"
@@ -3869,212 +3366,97 @@ files = [
 [package.dependencies]
 et-xmlfile = "*"
 
-[[package]]
-name = "opentelemetry-api"
-version = "1.36.0"
-description = "OpenTelemetry Python API"
-optional = false
-python-versions = ">=3.9"
-groups = ["main"]
-files = [
-    {file = "opentelemetry_api-1.36.0-py3-none-any.whl", hash = "sha256:02f20bcacf666e1333b6b1f04e647dc1d5111f86b8e510238fcc56d7762cda8c"},
-    {file = "opentelemetry_api-1.36.0.tar.gz", hash = "sha256:9a72572b9c416d004d492cbc6e61962c0501eaf945ece9b5a0f56597d8348aa0"},
-]
-
-[package.dependencies]
-importlib-metadata = ">=6.0,<8.8.0"
-typing-extensions = ">=4.5.0"
-
-[[package]]
-name = "opentelemetry-exporter-otlp-proto-common"
-version = "1.36.0"
-description = "OpenTelemetry Protobuf encoding"
-optional = false
-python-versions = ">=3.9"
-groups = ["main"]
-files = [
-    {file = "opentelemetry_exporter_otlp_proto_common-1.36.0-py3-none-any.whl", hash = "sha256:0fc002a6ed63eac235ada9aa7056e5492e9a71728214a61745f6ad04b923f840"},
-    {file = "opentelemetry_exporter_otlp_proto_common-1.36.0.tar.gz", hash = "sha256:6c496ccbcbe26b04653cecadd92f73659b814c6e3579af157d8716e5f9f25cbf"},
-]
-
-[package.dependencies]
-opentelemetry-proto = "1.36.0"
-
-[[package]]
-name = "opentelemetry-exporter-otlp-proto-grpc"
-version = "1.36.0"
-description = "OpenTelemetry Collector Protobuf over gRPC Exporter"
-optional = false
-python-versions = ">=3.9"
-groups = ["main"]
-files = [
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-]
-
-[package.dependencies]
-googleapis-common-protos = ">=1.57,<2.0"
-grpcio = [
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-    {version = ">=1.66.2,<2.0.0", markers = "python_version >= \"3.13\""},
-]
-opentelemetry-api = ">=1.15,<2.0"
-opentelemetry-exporter-otlp-proto-common = "1.36.0"
-opentelemetry-proto = "1.36.0"
-opentelemetry-sdk = ">=1.36.0,<1.37.0"
-typing-extensions = ">=4.6.0"
-
-[[package]]
-name = "opentelemetry-proto"
-version = "1.36.0"
-description = "OpenTelemetry Python Proto"
-optional = false
-python-versions = ">=3.9"
-groups = ["main"]
-files = [
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-    {file = "opentelemetry_proto-1.36.0.tar.gz", hash = "sha256:0f10b3c72f74c91e0764a5ec88fd8f1c368ea5d9c64639fb455e2854ef87dd2f"},
-]
-
-[package.dependencies]
-protobuf = ">=5.0,<7.0"
-
-[[package]]
-name = "opentelemetry-sdk"
-version = "1.36.0"
-description = "OpenTelemetry Python SDK"
-optional = false
-python-versions = ">=3.9"
-groups = ["main"]
-files = [
-    {file = "opentelemetry_sdk-1.36.0-py3-none-any.whl", hash = "sha256:19fe048b42e98c5c1ffe85b569b7073576ad4ce0bcb6e9b4c6a39e890a6c45fb"},
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-
-[package.dependencies]
-opentelemetry-api = "1.36.0"
-opentelemetry-semantic-conventions = "0.57b0"
-typing-extensions = ">=4.5.0"
-
-[[package]]
-name = "opentelemetry-semantic-conventions"
-version = "0.57b0"
-description = "OpenTelemetry Semantic Conventions"
-optional = false
-python-versions = ">=3.9"
-groups = ["main"]
-files = [
-    {file = "opentelemetry_semantic_conventions-0.57b0-py3-none-any.whl", hash = "sha256:757f7e76293294f124c827e514c2a3144f191ef175b069ce8d1211e1e38e9e78"},
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-]
-
-[package.dependencies]
-opentelemetry-api = "1.36.0"
-typing-extensions = ">=4.5.0"
-
 [[package]]
 name = "orjson"
-version = "3.11.1"
-description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy"
+version = "3.11.2"
+description = ""
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
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 [package.dependencies]
@@ -4186,14 +3568,14 @@ files = [
 
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 name = "parso"
-version = "0.8.4"
+version = "0.8.5"
 description = "A Python Parser"
 optional = false
 python-versions = ">=3.6"
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 files = [
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 ]
 
 [package.extras]
@@ -4350,19 +3732,19 @@ fpx = ["olefile"]
 mic = ["olefile"]
 test-arrow = ["pyarrow"]
 tests = ["check-manifest", "coverage (>=7.4.2)", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "trove-classifiers (>=2024.10.12)"]
-typing = ["typing-extensions"]
+typing = ["typing-extensions ; python_version < \"3.10\""]
 xmp = ["defusedxml"]
 
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 name = "platformdirs"
-version = "4.3.8"
+version = "4.4.0"
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 optional = false
 python-versions = ">=3.9"
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@@ -4386,30 +3768,6 @@ files = [
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 testing = ["coverage", "pytest", "pytest-benchmark"]
 
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-six = ">=1.5"
-
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-
 [[package]]
 name = "prometheus-client"
 version = "0.22.1"
@@ -4548,25 +3906,6 @@ files = [
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 [package.extras]
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 [[package]]
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@@ -5264,20 +4318,20 @@ files = [
 
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-description = "Pseudo terminal support for Windows from Python."
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 [[package]]
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+version = "27.0.2"
 description = "Python bindings for 0MQ"
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 python-versions = ">=3.8"
 groups = ["dev"]
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 [package.dependencies]
@@ -5591,7 +4645,7 @@ version = "0.36.2"
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 python-versions = ">=3.9"
-groups = ["main", "dev"]
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@@ -5701,14 +4755,14 @@ files = [
 
 [[package]]
 name = "requests"
-version = "2.32.4"
+version = "2.32.5"
 description = "Python HTTP for Humans."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["main", "dev"]
 files = [
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 ]
 
 [package.dependencies]
@@ -5721,25 +4775,6 @@ urllib3 = ">=1.21.1,<3"
 socks = ["PySocks (>=1.5.6,!=1.5.7)"]
 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
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-description = "OAuthlib authentication support for Requests."
-optional = false
-python-versions = ">=3.4"
-groups = ["main"]
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-[package.dependencies]
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-
-[package.extras]
-rsa = ["oauthlib[signedtoken] (>=3.0.0)"]
-
 [[package]]
 name = "requests-toolbelt"
 version = "1.0.0"
@@ -5800,32 +4835,13 @@ lark = ">=1.2.2"
 [package.extras]
 testing = ["pytest (>=8.3.5)"]
 
-[[package]]
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-[package.extras]
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-
 [[package]]
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 version = "0.27.0"
 description = "Python bindings to Rust's persistent data structures (rpds)"
 optional = false
 python-versions = ">=3.9"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
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@@ -5984,21 +5000,6 @@ files = [
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-groups = ["main"]
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 [[package]]
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@@ -6019,27 +5020,27 @@ crt = ["botocore[crt] (>=1.37.4,<2.0a.0)"]
 
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 [package.extras]
@@ -6178,7 +5179,7 @@ numpy = ">=1.25.2,<2.6"
 [package.extras]
 dev = ["cython-lint (>=0.12.2)", "doit (>=0.36.0)", "mypy (==1.10.0)", "pycodestyle", "pydevtool", "rich-click", "ruff (>=0.0.292)", "types-psutil", "typing_extensions"]
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+test = ["Cython", "array-api-strict (>=2.3.1)", "asv", "gmpy2", "hypothesis (>=6.30)", "meson", "mpmath", "ninja ; sys_platform != \"emscripten\"", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
 
 [[package]]
 name = "send2trash"
@@ -6193,9 +5194,9 @@ files = [
 ]
 
 [package.extras]
-nativelib = ["pyobjc-framework-Cocoa", "pywin32"]
-objc = ["pyobjc-framework-Cocoa"]
-win32 = ["pywin32"]
+nativelib = ["pyobjc-framework-Cocoa ; sys_platform == \"darwin\"", "pywin32 ; sys_platform == \"win32\""]
+objc = ["pyobjc-framework-Cocoa ; sys_platform == \"darwin\""]
+win32 = ["pywin32 ; sys_platform == \"win32\""]
 
 [[package]]
 name = "sentence-transformers"
@@ -6238,25 +5239,13 @@ files = [
 ]
 
 [package.extras]
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 [[package]]
 name = "six"
@@ -6296,69 +5285,59 @@ files = [
 
 [[package]]
 name = "sqlalchemy"
-version = "2.0.42"
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 description = "Database Abstraction Library"
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 python-versions = ">=3.7"
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 ]
 
 [package.dependencies]
@@ -6537,6 +5516,7 @@ description = "Tensors and Dynamic neural networks in Python with strong GPU acc
 optional = false
 python-versions = ">=3.9.0"
 groups = ["main"]
+markers = "python_version >= \"3.14\""
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 opt-einsum = ["opt-einsum (>=3.3)"]
 optree = ["optree (>=0.13.0)"]
 
+[[package]]
+name = "torch"
+version = "2.8.0"
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-dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "beautifulsoup4", "codecarbon (>=2.8.1)", "cookiecutter (==1.7.3)", "datasets (>=2.15.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "kenlm", "kernels (>=0.6.1,<=0.9)", "libcst", "librosa", "mistral-common[opencv] (>=1.6.3)", "nltk (<=3.8.1)", "num2words", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "pandas (<2.3.0)", "parameterized (>=0.9)", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic (>=2)", "pytest (>=7.2.0)", "pytest-asyncio", "pytest-order", "pytest-rerunfailures", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.11.2)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm (!=1.0.18,<=1.0.19)", "tokenizers (>=0.21,<0.22)", "torch (>=2.1)", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
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+dev = ["GitPython (<3.1.19)", "GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "accelerate (>=0.26.0)", "av", "beautifulsoup4", "codecarbon (>=2.8.1)", "cookiecutter (==1.7.3)", "cookiecutter (==1.7.3)", "datasets (>=2.15.0)", "datasets (>=2.15.0)", "datasets (>=2.15.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "kernels (>=0.6.1,<=0.9)", "libcst", "libcst", "librosa", "mistral-common[opencv] (>=1.6.3)", "mistral-common[opencv] (>=1.6.3)", "nltk (<=3.8.1)", "num2words", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "pandas (<2.3.0)", "parameterized (>=0.9)", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic (>=2)", "pytest (>=7.2.0)", "pytest-asyncio", "pytest-order", "pytest-rerunfailures", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.11.2)", "ruff (==0.11.2)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict_core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm (!=1.0.18,<=1.0.19)", "tokenizers (>=0.21,<0.22)", "torch (>=2.1)", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic_lite (>=1.0.7)", "urllib3 (<2.0.0)"]
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+dev-torch = ["GitPython (<3.1.19)", "GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "beautifulsoup4", "codecarbon (>=2.8.1)", "cookiecutter (==1.7.3)", "cookiecutter (==1.7.3)", "datasets (>=2.15.0)", "datasets (>=2.15.0)", "datasets (>=2.15.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "kenlm", "kernels (>=0.6.1,<=0.9)", "libcst", "libcst", "librosa", "mistral-common[opencv] (>=1.6.3)", "nltk (<=3.8.1)", "num2words", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "pandas (<2.3.0)", "parameterized (>=0.9)", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic (>=2)", "pytest (>=7.2.0)", "pytest-asyncio", "pytest-order", "pytest-rerunfailures", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.11.2)", "ruff (==0.11.2)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict_core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm (!=1.0.18,<=1.0.19)", "tokenizers (>=0.21,<0.22)", "torch (>=2.1)", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic_lite (>=1.0.7)", "urllib3 (<2.0.0)"]
 flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)", "scipy (<1.13.0)"]
 flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
 ftfy = ["ftfy"]
-hf-xet = ["hf-xet"]
+hf-xet = ["hf_xet"]
 hub-kernels = ["kernels (>=0.6.1,<=0.9)"]
 integrations = ["kernels (>=0.6.1,<=0.9)", "optuna", "ray[tune] (>=2.7.0)", "sigopt"]
-ja = ["fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "rhoknp (>=1.1.0,<1.3.1)", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)"]
+ja = ["fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "rhoknp (>=1.1.0,<1.3.1)", "sudachidict_core (>=20220729)", "sudachipy (>=0.6.6)", "unidic (>=1.0.2)", "unidic_lite (>=1.0.7)"]
 mistral-common = ["mistral-common[opencv] (>=1.6.3)"]
 modelcreation = ["cookiecutter (==1.7.3)"]
 natten = ["natten (>=0.14.6,<0.15.0)"]
@@ -6712,7 +5756,7 @@ serving = ["accelerate (>=0.26.0)", "fastapi", "openai (>=1.98.0)", "pydantic (>
 sigopt = ["sigopt"]
 sklearn = ["scikit-learn"]
 speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
-testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (>=2.15.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "libcst", "mistral-common[opencv] (>=1.6.3)", "nltk (<=3.8.1)", "parameterized (>=0.9)", "psutil", "pydantic (>=2)", "pytest (>=7.2.0)", "pytest-asyncio", "pytest-order", "pytest-rerunfailures", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.11.2)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
+testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (>=2.15.0)", "datasets (>=2.15.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "libcst", "mistral-common[opencv] (>=1.6.3)", "nltk (<=3.8.1)", "parameterized (>=0.9)", "psutil", "pydantic (>=2)", "pytest (>=7.2.0)", "pytest-asyncio", "pytest-order", "pytest-rerunfailures", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.11.2)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
 tf = ["keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
 tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<0.24)", "tensorflow-text (<2.16)", "tf2onnx"]
 tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
@@ -6722,7 +5766,7 @@ tokenizers = ["tokenizers (>=0.21,<0.22)"]
 torch = ["accelerate (>=0.26.0)", "torch (>=2.1)"]
 torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
 torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"]
-torchhub = ["filelock", "huggingface-hub (>=0.34.0,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.21,<0.22)", "torch (>=2.1)", "tqdm (>=4.27)"]
+torchhub = ["filelock", "huggingface-hub (>=0.34.0,<1.0)", "importlib_metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.21,<0.22)", "torch (>=2.1)", "tqdm (>=4.27)"]
 video = ["av"]
 vision = ["Pillow (>=10.0.1,<=15.0)"]
 
@@ -6733,7 +5777,7 @@ description = "A language and compiler for custom Deep Learning operations"
 optional = false
 python-versions = "*"
 groups = ["main"]
-markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version >= \"3.14\""
 files = [
     {file = "triton-3.3.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:b74db445b1c562844d3cfad6e9679c72e93fdfb1a90a24052b03bb5c49d1242e"},
     {file = "triton-3.3.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:b31e3aa26f8cb3cc5bf4e187bf737cbacf17311e1112b781d4a059353dfd731b"},
@@ -6752,45 +5796,52 @@ tests = ["autopep8", "isort", "llnl-hatchet", "numpy", "pytest", "pytest-forked"
 tutorials = ["matplotlib", "pandas", "tabulate"]
 
 [[package]]
-name = "typer"
-version = "0.16.0"
-description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
+name = "triton"
+version = "3.4.0"
+description = "A language and compiler for custom Deep Learning operations"
 optional = false
-python-versions = ">=3.7"
+python-versions = "<3.14,>=3.9"
 groups = ["main"]
+markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.14\""
 files = [
-    {file = "typer-0.16.0-py3-none-any.whl", hash = "sha256:1f79bed11d4d02d4310e3c1b7ba594183bcedb0ac73b27a9e5f28f6fb5b98855"},
-    {file = "typer-0.16.0.tar.gz", hash = "sha256:af377ffaee1dbe37ae9440cb4e8f11686ea5ce4e9bae01b84ae7c63b87f1dd3b"},
+    {file = "triton-3.4.0-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:7ff2785de9bc02f500e085420273bb5cc9c9bb767584a4aa28d6e360cec70128"},
+    {file = "triton-3.4.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:7b70f5e6a41e52e48cfc087436c8a28c17ff98db369447bcaff3b887a3ab4467"},
+    {file = "triton-3.4.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:31c1d84a5c0ec2c0f8e8a072d7fd150cab84a9c239eaddc6706c081bfae4eb04"},
+    {file = "triton-3.4.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:00be2964616f4c619193cb0d1b29a99bd4b001d7dc333816073f92cf2a8ccdeb"},
+    {file = "triton-3.4.0-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:7936b18a3499ed62059414d7df563e6c163c5e16c3773678a3ee3d417865035d"},
+    {file = "triton-3.4.0-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:98e5c1442eaeabae2e2452ae765801bd53cd4ce873cab0d1bdd59a32ab2d9397"},
 ]
 
 [package.dependencies]
-click = ">=8.0.0"
-rich = ">=10.11.0"
-shellingham = ">=1.3.0"
-typing-extensions = ">=3.7.4.3"
+setuptools = ">=40.8.0"
+
+[package.extras]
+build = ["cmake (>=3.20,<4.0)", "lit"]
+tests = ["autopep8", "isort", "llnl-hatchet", "numpy", "pytest", "pytest-forked", "pytest-xdist", "scipy (>=1.7.1)"]
+tutorials = ["matplotlib", "pandas", "tabulate"]
 
 [[package]]
 name = "types-python-dateutil"
-version = "2.9.0.20250708"
+version = "2.9.0.20250822"
 description = "Typing stubs for python-dateutil"
 optional = false
 python-versions = ">=3.9"
 groups = ["dev"]
 files = [
-    {file = "types_python_dateutil-2.9.0.20250708-py3-none-any.whl", hash = "sha256:4d6d0cc1cc4d24a2dc3816024e502564094497b713f7befda4d5bc7a8e3fd21f"},
-    {file = "types_python_dateutil-2.9.0.20250708.tar.gz", hash = "sha256:ccdbd75dab2d6c9696c350579f34cffe2c281e4c5f27a585b2a2438dd1d5c8ab"},
+    {file = "types_python_dateutil-2.9.0.20250822-py3-none-any.whl", hash = "sha256:849d52b737e10a6dc6621d2bd7940ec7c65fcb69e6aa2882acf4e56b2b508ddc"},
+    {file = "types_python_dateutil-2.9.0.20250822.tar.gz", hash = "sha256:84c92c34bd8e68b117bff742bc00b692a1e8531262d4507b33afcc9f7716cd53"},
 ]
 
 [[package]]
 name = "types-requests"
-version = "2.32.4.20250611"
+version = "2.32.4.20250809"
 description = "Typing stubs for requests"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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-anyio = ">=3.0.0"
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 [[package]]
 name = "wcwidth"
 version = "0.2.13"
@@ -7124,7 +5977,7 @@ version = "1.8.0"
 description = "WebSocket client for Python with low level API options"
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
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 optional = ["python-socks", "wsaccel"]
 test = ["websockets"]
 
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-]
-
-[package.dependencies]
-cffi = {version = ">=1.11", markers = "platform_python_implementation == \"PyPy\""}
-
-[package.extras]
-cffi = ["cffi (>=1.11)"]
+cffi = ["cffi (>=1.17) ; python_version >= \"3.13\" and platform_python_implementation != \"PyPy\""]
 
 [metadata]
 lock-version = "2.1"
 python-versions = "^3.12"
-content-hash = "8d7212070e6a14f472e3fb95bac71fc6380405a383d8f8d9602109c67b4d3705"
+content-hash = "70ce2a6a771ecefd5e6b22ebc37180593311f4cbad2543b7aa0ceaf17a03f743"
diff --git a/fieldExtraction/pyproject.toml b/fieldExtraction/pyproject.toml
index 6666d9d..65e3245 100644
--- a/fieldExtraction/pyproject.toml
+++ b/fieldExtraction/pyproject.toml
@@ -1,5 +1,5 @@
 [tool.poetry]
-name = "doczy-smart-chunking"
+name = "doczy-field-extraction"
 version = "0.1.0"
 description = ""
 authors = ["Alex Galarce <agalarce@aarete.com>"]
@@ -19,7 +19,6 @@ openpyxl = "^3.1.5"
 pytest-mock = "^3.14.0"
 langchain = "^0.3.14"
 langchainhub = "^0.1.21"
-langchain-chroma = "^0.2.0"
 langchain-aws = "^0.2.11"
 langchain-text-splitters = "^0.3.5"
 langchain-community = "^0.3.15"
diff --git a/fieldExtraction/src/investment/file_processing.py b/fieldExtraction/src/investment/file_processing.py
index 1c44a02..e0cad4a 100644
--- a/fieldExtraction/src/investment/file_processing.py
+++ b/fieldExtraction/src/investment/file_processing.py
@@ -1,4 +1,5 @@
 import pandas as pd
+import logging
 
 import src.codes.code_funcs as code_funcs
 import src.investment.aarete_derived as aarete_derived
@@ -22,7 +23,7 @@ from src.utils.string_utils import datetime_str
 
 def process_file(file_object, constants: Constants, run_timestamp):
     filename, contract_text = file_object
-    print(f"{datetime_str()} Processing {filename}...")
+    logging.info(f"{datetime_str()} Processing {filename}...")
 
     ################## PREPROCESS ##################
     contract_text = preprocess.clean_text(contract_text)
@@ -33,7 +34,7 @@ def process_file(file_object, constants: Constants, run_timestamp):
     exhibit_dict, all_exhibit_headers = preprocess.one_to_n_exhibit_chunking(
         text_dict, constants.EXHIBIT_HEADER_MARKERS, filename
     )
-    print(f"{datetime_str()} Preprocessing Complete - {filename}")
+    logging.info(f"{datetime_str()} Preprocessing Complete - {filename}")
 
     ################## ONE TO N ##################
     if string_utils.contains_reimbursement(contract_text):
@@ -44,11 +45,11 @@ def process_file(file_object, constants: Constants, run_timestamp):
         one_to_n_results = postprocessing_funcs.generate_reimb_ids(
             one_to_n_results
         )  # Add reimb_id
-        print(f"{datetime_str()} One to N Complete - {filename}")
+        logging.info(f"{datetime_str()} One to N Complete - {filename}")
     else:
         one_to_n_results = pd.DataFrame([{"FILE_NAME": filename}])
         dynamic_one_to_one_fields = FieldSet()
-        print(f"{datetime_str()} No One to N Found, Skipping - {filename}")
+        logging.info(f"{datetime_str()} No One to N Found, Skipping - {filename}")
 
     ################## ONE TO ONE ##################
     one_to_one_results = run_one_to_one_prompts(
@@ -60,7 +61,7 @@ def process_file(file_object, constants: Constants, run_timestamp):
         constants,
     )  # Return dict
     one_to_one_results["FILE_NAME"] = filename
-    print(f"{datetime_str()} One to One Complete - {filename}")
+    logging.info(f"{datetime_str()} One to One Complete - {filename}")
 
     ################## MERGE ##################
     merged_results = row_funcs.merge_one_to_one_into_one_to_n(
@@ -69,13 +70,13 @@ def process_file(file_object, constants: Constants, run_timestamp):
 
     ################## CODES ##################
     results_with_code = code_funcs.code_breakout(merged_results, constants)
-    print(f"{datetime_str()} Codes Complete - {filename}")
+    logging.info(f"{datetime_str()} Codes Complete - {filename}")
 
     final_results = code_funcs.grouper_breakout(results_with_code)
 
     ################## POSTPROCESS ##################
     final_df = postprocess.postprocess(final_results, constants)
-    print(f"{datetime_str()} Postprocessing Complete - {filename}")
+    logging.info(f"{datetime_str()} Postprocessing Complete - {filename}")
 
     ################## WRITE INDIVIDUAL ##################
     if config.WRITE_TO_S3:
@@ -83,7 +84,7 @@ def process_file(file_object, constants: Constants, run_timestamp):
     else:
         io_utils.write_local(final_df, filename, "", "individual")
 
-    print(f"{datetime_str()} Writing Complete - {filename}")
+    logging.info(f"{datetime_str()} Writing Complete - {filename}")
     return final_df
 
 
@@ -180,7 +181,9 @@ def run_one_to_n_prompts(filename, exhibit_dict, all_exhibit_headers, constants)
     one_to_n_results = aarete_derived.get_crosswalk_fields(one_to_n_results)
 
     ################## Determine LOB Relationship ##################
-    one_to_n_results = one_to_n_funcs.get_lob_relationship(one_to_n_results, exhibit_dict, filename)
+    one_to_n_results = one_to_n_funcs.get_lob_relationship(
+        one_to_n_results, exhibit_dict, filename
+    )
 
     ################## Fill NA Mapping ##################
     one_to_n_results = aarete_derived.fill_na_mapping(one_to_n_results)
diff --git a/fieldExtraction/src/investment/main.py b/fieldExtraction/src/investment/main.py
index 85c6c5a..0fb8b29 100644
--- a/fieldExtraction/src/investment/main.py
+++ b/fieldExtraction/src/investment/main.py
@@ -90,7 +90,7 @@ def main(testing=False, test_params={}):
                 k: v for k, v in input_dict.items() if k in test_params["input_files"]
             }
 
-    print(f"Total Input Files : {len(input_dict)}")
+    logging.info(f"Total Input Files : {len(input_dict)}")
 
     # Process files with run_timestamp
     successful_results = []
@@ -114,7 +114,7 @@ def main(testing=False, test_params={}):
             except (
                 Exception
             ) as e:  # When there's an issue with the future itself (not the processing inside the future)
-                print(f"Error processing future: {str(e)}")
+                logging.error(f"Error processing future: {str(e)}")
                 # Coerce this to the format expected by pd.concat (so a single-row dataframe)
                 error_results.append(pd.DataFrame([{"error": str(e)}]))
 
diff --git a/fieldExtraction/src/investment/one_to_n_funcs.py b/fieldExtraction/src/investment/one_to_n_funcs.py
index 3f2d320..14428e7 100644
--- a/fieldExtraction/src/investment/one_to_n_funcs.py
+++ b/fieldExtraction/src/investment/one_to_n_funcs.py
@@ -1176,7 +1176,7 @@ def split_reimb_dates(one_to_n_results: list, filename: str) -> list:
     """
 
     if not one_to_n_results or not isinstance(one_to_n_results, list):
-        print("No valid data to process")
+        logging.info("No valid data to process")
         return one_to_n_results
 
     # Filter records that have non-empty REIMB_DATES
@@ -1195,7 +1195,7 @@ def split_reimb_dates(one_to_n_results: list, filename: str) -> list:
             records_to_process.append((i, record))
 
     if not records_to_process:
-        print("No valid date ranges to process")
+        logging.info("No valid date ranges to process")
         # Still remove the REIMB_DATES field from all records
         for record in one_to_n_results:
             if "REIMB_DATES" in record:
@@ -1225,13 +1225,13 @@ def split_reimb_dates(one_to_n_results: list, filename: str) -> list:
                 if "end_date" in llm_output_cleaned:
                     record["REIMB_TERMINATION_DT"] = llm_output_cleaned["end_date"]
             else:
-                print(
+                logging.error(
                     f"Invalid LLM output format for index {index}: {llm_output_cleaned}"
                 )
 
         except Exception as e:
             # Broader exception handling for LLM calls and JSON parsing
-            print(f"Error processing dates for index {index}: {str(e)}")
+            logging.error(f"Error processing dates for index {index}: {str(e)}")
             # Continue processing other records even if one fails
             continue
 
@@ -1386,14 +1386,13 @@ def run_grouper_breakout(service: str, methodology: str, filename: str) -> dict:
     grouper_questions = FieldSet(
         file_path=config.FIELD_JSON_PATH, field_type="grouper"
     ).print_prompt_dict()
-    prompt = prompt_templates.GROUPER_BREAKOUT(
-        service, methodology, grouper_questions
-    )
+    prompt = prompt_templates.GROUPER_BREAKOUT(service, methodology, grouper_questions)
     logging.debug(f"Running GROUPER breakout in {filename} with prompt: {prompt}")
     llm_response = llm_utils.invoke_claude(prompt, "sonnet_latest", filename)
     logging.debug(f"LLM Response for GROUPER breakout in {filename}: {llm_response}")
     return string_utils.universal_json_load(llm_response) or {}
 
+
 def run_outliers_breakout(service: str, methodology: str, filename: str) -> dict:
     """
     Runs focused OUTLIERS analysis using specialized prompt.
diff --git a/fieldExtraction/src/investment/one_to_one_funcs.py b/fieldExtraction/src/investment/one_to_one_funcs.py
index e774e0e..6d79f38 100644
--- a/fieldExtraction/src/investment/one_to_one_funcs.py
+++ b/fieldExtraction/src/investment/one_to_one_funcs.py
@@ -94,7 +94,7 @@ def filter_payer_from_providers(
         if similarity_score < threshold:
             filtered_providers.append(provider)
         else:
-            print(
+            logging.info(
                 f"Filtered out provider that matched payer: '{provider_name}' similar to '{payer_name}' with score {similarity_score}"
             )
 
@@ -210,7 +210,7 @@ def run_smart_chunked_fields(
                 answers_dict[field.field_name] = field_answer
 
         except Exception as e:
-            print(f"Error processing field {field}: {type(e)}, {str(e)}")
+            logging.error(f"Error processing field {field}: {type(e)}, {str(e)}")
             for field in fields:
                 answers_dict[field.field_name] = f"Error: {str(e)}"
 
@@ -300,7 +300,7 @@ def run_full_context_fields(
         )
         full_context_answers_dict = string_utils.universal_json_load(claude_answer_raw)
     except Exception as e:
-        print(f"Error processing high accuracy fields: {str(e)}")
+        logging.error(f"Error processing high accuracy fields: {str(e)}")
         full_context_answers_dict = {}
         for field in full_context_fields.list_fields():
             full_context_answers_dict[field] = f"Error: {str(e)}"
diff --git a/fieldExtraction/src/investment/table_funcs.py b/fieldExtraction/src/investment/table_funcs.py
index bc0ca0b..25b66b4 100644
--- a/fieldExtraction/src/investment/table_funcs.py
+++ b/fieldExtraction/src/investment/table_funcs.py
@@ -96,7 +96,7 @@ def convert_str_to_dataframe(text: str, is_continuation: bool = False) -> pd.Dat
                         # Empty list - return empty DataFrame
                         return pd.DataFrame()
         except (SyntaxError, ValueError):
-            print(f"Invalid list format: {list_str}")
+            logging.error(f"Invalid list format: {list_str}")
 
     # Fall back to dict format (old format) - but warn about deprecation
     dict_match = re.search(DICTIONARY_PATTERN, text)
@@ -111,7 +111,7 @@ def convert_str_to_dataframe(text: str, is_continuation: bool = False) -> pd.Dat
                 # No need to set the headers explicitly, DataFrame will use keys as column names
                 return pd.DataFrame(parsed_data, dtype=str)
         except (SyntaxError, ValueError):
-            print(f"Invalid dictionary format: {dict_str}")
+            logging.error(f"Invalid dictionary format: {dict_str}")
 
     return pd.DataFrame()  # Return empty DataFrame if no valid format found
 
@@ -136,7 +136,7 @@ def convert_str_to_dict(text: str) -> Dict[str, Any]:
         try:
             return ast.literal_eval(dict_str)
         except (SyntaxError, ValueError):
-            print(f"Invalid dictionary format: {dict_str}")
+            logging.error(f"Invalid dictionary format: {dict_str}")
     return {}
 
 
diff --git a/fieldExtraction/src/investment/tin_npi_funcs.py b/fieldExtraction/src/investment/tin_npi_funcs.py
index d8eda84..01df973 100644
--- a/fieldExtraction/src/investment/tin_npi_funcs.py
+++ b/fieldExtraction/src/investment/tin_npi_funcs.py
@@ -1,4 +1,5 @@
 import json
+import logging
 import re
 from typing import Optional
 
@@ -309,7 +310,9 @@ def identify_group_provider(
             return new_group_provider
 
     except Exception as e:
-        print(f"Error parsing group provider response: {response}. Exception: {e}")
+        logging.error(
+            f"Error parsing group provider response: {response}. Exception: {e}"
+        )
         return None
 
     # Fallback: if no match found, return None
@@ -400,7 +403,7 @@ def get_provider_info(text_dict: dict, page_num: str, filename: str) -> list:
             providers = [providers]
         elif not isinstance(providers, list):
             # If not a list or dict, create a default list with error info
-            print(
+            logging.warning(
                 f"Warning: Unexpected format in provider info response: {type(providers)}"
             )
             providers = [
@@ -423,8 +426,8 @@ def get_provider_info(text_dict: dict, page_num: str, filename: str) -> list:
 
         return providers
     except ValueError as e:  # Handle JSON parsing error
-        print(f"Error parsing JSON response from LLM: {str(e)}")
-        print(f"Raw response: {claude_answer_raw}")
+        logging.error(f"Error parsing JSON response from LLM: {str(e)}")
+        logging.error(f"Raw response: {claude_answer_raw}")
         # Return a default value
         return [
             {
diff --git a/fieldExtraction/src/investment/vision_funcs.py b/fieldExtraction/src/investment/vision_funcs.py
index 9a4246f..6151460 100644
--- a/fieldExtraction/src/investment/vision_funcs.py
+++ b/fieldExtraction/src/investment/vision_funcs.py
@@ -1,5 +1,6 @@
 import base64
 from io import BytesIO
+import logging
 from typing import List
 
 import fitz  # PyMuPDF
@@ -115,5 +116,5 @@ def process_pdf_pages_to_base64_images(
             return base64_images
 
     except (ValueError, fitz.FileDataError) as e:
-        print(f"Error processing PDF pages: {str(e)}")
+        logging.error(f"Error processing PDF pages: {str(e)}")
         raise
diff --git a/fieldExtraction/src/utils/io_utils.py b/fieldExtraction/src/utils/io_utils.py
index c00b15e..f70a934 100644
--- a/fieldExtraction/src/utils/io_utils.py
+++ b/fieldExtraction/src/utils/io_utils.py
@@ -1,3 +1,4 @@
+import logging
 import os
 import tempfile
 from io import StringIO
@@ -26,21 +27,23 @@ def read_local(file_path):  # io_utils.py
                     return file_contents
             except UnicodeDecodeError:
                 # If ANSI also fails, log an error message or handle it accordingly
-                print(f"Failed to decode {file_path} with UTF-8 and cp1252 encodings.")
+                logging.error(
+                    f"Failed to decode {file_path} with UTF-8 and cp1252 encodings."
+                )
 
     if os.path.isfile(file_path) and file_path.endswith(".csv"):
         try:
             df = pd.read_csv(file_path)
             return df
         except Exception:
-            print("Failed to read .csv file.")
+            logging.error("Failed to read .csv file.")
 
     if os.path.isfile(file_path) and file_path.endswith(".xlsx"):
         try:
             df = pd.read_excel(file_path)
             return df
         except Exception:
-            print("Failed to read .xlsx file.")
+            logging.error("Failed to read .xlsx file.")
 
 
 def list_s3_files(prefix=config.S3_PREFIX, bucket=config.S3_BUCKET):  # io_utils.py
@@ -72,7 +75,7 @@ def read_s3_pdf(pdf_path):
             temp_pdf_path = temp_pdf.name
         return temp_pdf_path
     except ClientError as e:
-        print(f"Error fetching PDF from S3: {e}")
+        logging.error(f"Error fetching PDF from S3: {e}")
         return None
 
 
@@ -108,7 +111,7 @@ def read_s3():
     files = {}
 
     for contract in contract_list:
-        print(f"Reading {contract}")
+        logging.info(f"Reading {contract}")
         try:
             data = s3_client.get_object(Bucket=bucket, Key=contract)
             if contract.endswith(".txt"):
@@ -135,7 +138,7 @@ def read_s3_csv(csv_path):  # io_utils.py
                 df = pd.read_csv(StringIO(response["Body"].read().decode("utf-8")))
                 return df
     except ClientError as e:
-        print(f"Error listing S3 objects: {e}")
+        logging.error(f"Error listing S3 objects: {e}")
 
 
 def read_input(local_path=config.LOCAL_PATH):  # io_utils.py
@@ -178,11 +181,13 @@ def filter_already_processed(input_dict, input_dict_b):  # io_utils.py
             k: v for k, v in input_dict_b.items() if k not in already_processed_b
         }
 
-        print(f"Filtering based on S3 master tracking for batch {config.BATCH_ID}:")
-        print(
+        logging.info(
+            f"Filtering based on S3 master tracking for batch {config.BATCH_ID}:"
+        )
+        logging.info(
             f"AC: Found {len(already_processed_ac)} already processed, {len(input_dict_ac)} remaining"
         )
-        print(
+        logging.info(
             f"B: Found {len(already_processed_b)} already processed, {len(input_dict_b)} remaining"
         )
 
@@ -205,11 +210,11 @@ def filter_already_processed(input_dict, input_dict_b):  # io_utils.py
             k: v for k, v in input_dict_b.items() if k not in already_processed_b
         }
 
-        print(f"Filtering based on local output directory:")
-        print(
+        logging.info(f"Filtering based on local output directory:")
+        logging.info(
             f"AC: Found {len(already_processed_ac)} already processed, {len(input_dict_ac)} remaining"
         )
-        print(
+        logging.info(
             f"B: Found {len(already_processed_b)} already processed, {len(input_dict_b)} remaining"
         )
 
@@ -298,9 +303,9 @@ def write_s3(df, filename, run_timestamp, output_type):
             Bucket=config.S3_OUTPUT_BUCKET, Key=output_path, Body=csv_buffer
         )
     except ClientError as e:
-        print(f"Error uploading to S3: {e}")
+        logging.error(f"Error uploading to S3: {e}")
 
     if output_type == "final":
-        print(f"Saved batch output file: {output_path}")
+        logging.info(f"Saved batch output file: {output_path}")
     elif output_type == "individual":
-        print(f"Saved individual output file: {output_path}")
+        logging.info(f"Saved individual output file: {output_path}")
diff --git a/fieldExtraction/src/utils/llm_utils.py b/fieldExtraction/src/utils/llm_utils.py
index 0544279..4886216 100644
--- a/fieldExtraction/src/utils/llm_utils.py
+++ b/fieldExtraction/src/utils/llm_utils.py
@@ -161,7 +161,7 @@ def invoke_claude(
         else:
             raise ValueError(f"Unsupported model_id: {model_id}")
     else:
-        print("Usage: python local_main.py <-local> OR python main.py <ec2>")
+        logging.error("Usage: python local_main.py <-local> OR python main.py <ec2>")
         raise
 
     # Store response in cache with LRU eviction
@@ -185,7 +185,6 @@ def invoke_claude_with_image_array(
     prompt, model_id, filename, base64_images, max_tokens=4096
 ):
     cache_key = get_cache_key_with_image_array(prompt, model_id, base64_images)
-    # print(f"Cache key for {filename}: {cache_key}") # printing for debugging
     # Check cache first - use get() method from LRUCache
     if cache_key in claude_cache:
         claude_cache.move_to_end(cache_key)  # Mark as recently used
@@ -218,7 +217,7 @@ def invoke_claude_with_image_array(
             )
 
     else:
-        print("Usage: python local_main.py <-local> OR python main.py <ec2>")
+        logging.error("Usage: python local_main.py <-local> OR python main.py <ec2>")
         raise
 
     # Store response in cache with LRU eviction
@@ -584,21 +583,21 @@ def ec2_claude_3_and_up(
                     ]:
                         if attempt < max_retries - 1:
                             delay = (2**attempt + random.uniform(0, 1)) * initial_delay
-                            print(
+                            logging.info(
                                 f"Attempt {attempt + 1} failed. Retrying in {delay:.2f} seconds..."
                             )
                             time.sleep(delay)
                         else:
-                            print(
+                            logging.info(
                                 f"Switching to next runtime due to {error_code}: {str(e)}."
                             )
                             break  # Switch to the next runtime
                     else:
-                        print(f"Unexpected error: {str(e)}")
+                        logging.error(f"Unexpected error: {str(e)}")
                         raise  # Reraise other exceptions
 
                 except Exception as e:
-                    print(f"Unexpected error: {str(e)}")
+                    logging.error(f"Unexpected error: {str(e)}")
                     raise
     else:  # Runtime rotation is disabled
         for attempt in range(max_retries):
@@ -639,7 +638,7 @@ def ec2_claude_3_and_up(
                 # Timeout errors should probably retry
                 if attempt < max_retries - 1:
                     delay = (2**attempt + random.uniform(0, 1)) * initial_delay
-                    print(
+                    logging.info(
                         f"Attempt {attempt + 1} failed due to timeout. Retrying in {delay:.2f} seconds..."
                     )
                     time.sleep(delay)
@@ -650,18 +649,18 @@ def ec2_claude_3_and_up(
                 if error_code in ["ThrottlingException", "TooManyRequestsException"]:
                     if attempt < max_retries - 1:
                         delay = (2**attempt + random.uniform(0, 1)) * initial_delay
-                        print(
+                        logging.info(
                             f"Attempt {attempt + 1} failed due to rate limiting. Retrying in {delay:.2f} seconds..."
                         )
                         time.sleep(delay)
                     else:
                         raise
                 else:
-                    print(f"Unexpected error: {str(e)}")
+                    logging.error(f"Unexpected error: {str(e)}")
                     raise  # Non-throttling client errors should fail immediately
 
             except Exception as e:
-                print(f"Unexpected error: {str(e)}")
+                logging.error(f"Unexpected error: {str(e)}")
                 raise
     raise Exception(f"Max retries ({max_retries}) exceeded for model {model_id}.")
 
diff --git a/fieldExtraction/src/utils/string_utils.py b/fieldExtraction/src/utils/string_utils.py
index 90b03d2..db972cb 100644
--- a/fieldExtraction/src/utils/string_utils.py
+++ b/fieldExtraction/src/utils/string_utils.py
@@ -1,4 +1,5 @@
 import json
+import logging
 import re
 import traceback
 import warnings
@@ -206,9 +207,9 @@ def universal_json_load(string_dict: str):
         try:
             return json.loads(matched_str)
         except json.JSONDecodeError as e:
-            print(f"Failed to parse JSON: {e}")
-            print(f"Original string: {string_dict}")
-            print(f"Traceback: {traceback.format_exc()}")
+            logging.error(f"Failed to parse JSON: {e}")
+            logging.error(f"Original string: {string_dict}")
+            logging.error(f"Traceback: {traceback.format_exc()}")
             # Use placeholders to preserve JSON structure characters for CSV compatibility
             csv_safe_string = (
                 string_dict.replace(",", "[COMMA]")
@@ -230,9 +231,9 @@ def universal_json_load(string_dict: str):
             )  # Replace single quotes with double quotes
             return json.loads(cleaned_str)
         except json.JSONDecodeError as e:
-            print(f"Failed to parse list: {e}")
-            print(f"Original string: {string_dict}")
-            print(f"Traceback: {traceback.format_exc()}")
+            logging.error(f"Failed to parse list: {e}")
+            logging.error(f"Original string: {string_dict}")
+            logging.error(f"Traceback: {traceback.format_exc()}")
             # Use placeholders to preserve JSON structure characters for CSV compatibility
             csv_safe_string = (
                 string_dict.replace(",", "[COMMA]")
@@ -275,7 +276,7 @@ def contains_reimbursement(text, page="1", method="keyword"):
         elif isinstance(text, str):
             text_to_check = text.lower()
         else:
-            print("contains_reimbursement - Invalid data type")
+            logging.warning("contains_reimbursement - Invalid data type")
             return False
         return any(keyword in text_to_check for keyword in reimbursement_strings)
     elif method == "regex":
diff --git a/fieldExtraction/src/utils/table_utils.py b/fieldExtraction/src/utils/table_utils.py
deleted file mode 100644
index e5e8c45..0000000
--- a/fieldExtraction/src/utils/table_utils.py
+++ /dev/null
@@ -1,517 +0,0 @@
-import ast
-import copy
-import math
-import re
-from collections import defaultdict
-from typing import Any, Dict, List, Optional, Pattern, Tuple, Union
-
-import pandas as pd
-
-import src.utils.llm_utils as llm_utils
-import src.utils.string_utils as string_utils
-from src import config
-from src.prompts import preprocessing_prompts
-
-# Table regex patterns
-START_PAGE_PATTERN: Pattern[str] = re.compile(
-    r"^(?!None\n).+\n\{.*?\}", re.DOTALL
-)  # Regex for start page - shouldn't have literal `None`
-CONTINUATION_PAGE_PATTERN: Pattern[str] = re.compile(
-    r"^None\n\{.*?\}", re.DOTALL
-)  # Regex for continuation page - has literal `None` present at the start
-START_PAGE_NUM_PATTERN: str = r"\n\d+\n?"
-CONTINUATION_PAGE_NUM_PATTERN: str = r"\d+\n"
-DICTIONARY_PATTERN: str = r"\{.*\}"
-
-# Markers for table start and end
-START_MARKER: str = "-------Table Start--------"
-END_MARKER: str = "-------Table End--------"
-
-
-def count_tables(exhibit_text: str) -> int:
-    """Count number of tables found in an exhibit, through use of a
-    regex that catches the table start and end strings.
-
-    Args:
-        exhibit_text (str): Input page text
-
-    Returns:
-        int: Number of tables
-    """
-    pattern = r"-Table Start-"  # Source text contains "-------Table Start--------" but in case hyphen count is unreliable, just looking for one
-    matches = re.findall(pattern, exhibit_text)
-    return len(matches)
-
-
-def extract_first_table_from_page(text: str) -> str:
-    """
-    Extracts the first table from a given page of text based on predefined start and end markers.
-
-    Args:
-        text (str): The text content of the page from which the table needs to be extracted.
-
-    Returns:
-        str: The extracted table content as a string. If the start or end markers are not found, returns an empty string.
-    """
-    if START_MARKER not in text or END_MARKER not in text:
-        return ""
-
-    start_index: int = text.find(START_MARKER) + len(START_MARKER)
-    end_index: int = text.find(END_MARKER)
-    filtered_page: str = text[start_index:end_index].strip()
-
-    return filtered_page
-
-
-def extract_snippets_between_markers(text: str) -> List[str]:
-    """
-    Extracts all snippets from the input text that are enclosed between START_MARKER and END_MARKER.
-
-    Args:
-        text (str): The input text from which to extract the snippets.
-
-    Returns:
-        list: A list of substrings found between START_MARKER and END_MARKER in the input text.
-    """
-    return re.findall(rf"{START_MARKER}(.+?){END_MARKER}", text, re.DOTALL)
-
-
-def get_str_dictionaries_from_text(
-    text: str, only_first: bool = True
-) -> Union[List[str], str]:
-    """
-    Extracts dictionary-like strings from the given text using a predefined pattern.
-
-    Args:
-        text (str): The input text from which to extract dictionary-like strings.
-        only_first (bool, optional): If True, returns only the first match. If False, returns all matches. Defaults to True.
-
-    Returns:
-        list or str: A list of all matched dictionary-like strings if only_first is False, otherwise the first matched string.
-    """
-    matches = re.findall(DICTIONARY_PATTERN, text)
-    if not matches:
-        return ""
-    return matches[0] if only_first else matches
-
-
-def page_contains_multiple_tables(text: str) -> bool:
-    """
-    Checks if the given text contains multiple tables.
-
-    Args:
-        text (str): The text to be checked for multiple tables.
-
-    Returns:
-        bool: True if the text contains more than one table, False otherwise.
-    """
-    return len(re.findall(rf"{START_MARKER}", text)) > 1
-
-
-def get_page_metadata(page: str) -> Union[List[str], List[Tuple]]:
-    """
-    Extracts and returns metadata from a given page.
-
-    If the page contains a single table, it returns the common metadata for the table.
-    If the page contains multiple tables, it returns a list of metadata for each table (ordered by position in the page).
-    If the page contains no tables (or contains a malformed table), it returns an empty list.
-
-    Args:
-        page (str): The content of the page from which metadata is to be extracted.
-
-    Returns:
-        List[str]: A list containing metadata. If the page contains a single table,
-                   the list contains one element with the common metadata. If the
-                   page contains multiple tables, the list contains tuples where
-                   each tuple consists of the metadata and the matched dictionary pattern (the corresponding table).
-    """
-    # if the page does not contain a table (or contains a malformed table), return an empty list
-    if not re.search(START_MARKER, page) or not re.search(END_MARKER, page):
-        print("Malformed table in get_page_metadata!")
-        return []
-
-    # return the common metadata for the table (or the group of tables starting with this one)
-    if not page_contains_multiple_tables(page):
-        group_metadata = page[: page.find(START_MARKER)].strip()
-        group_metadata = re.sub(
-            START_PAGE_NUM_PATTERN, "\n", group_metadata
-        )  # Remove page number marker
-        return [group_metadata]
-    else:  # if the page contains multiple tables
-        all_tables = extract_snippets_between_markers(page)
-        table_metadata_map = []
-
-        for table in all_tables:
-            match = re.search(DICTIONARY_PATTERN, table, re.DOTALL)
-            if match:
-                metadata = table.replace(match.group(0), "").strip()
-                table_metadata_map.append((metadata, match.group(0)))
-
-        return table_metadata_map
-
-
-def convert_str_to_dict(text: str) -> Dict[str, Any]:
-    """
-    Converts a string representation of a dictionary to an actual dictionary.
-
-    This function searches for a dictionary pattern within the given text and
-    converts the matched string to a dictionary using `ast.literal_eval`.
-
-    Args:
-        text (str): The input string that potentially contains a dictionary.
-
-    Returns:
-        dict: The dictionary extracted from the input string. If no dictionary
-        pattern is found, an empty dictionary is returned.
-    """
-    match = re.search(DICTIONARY_PATTERN, text)
-    if match:
-        dict_str: str = match.group(0)
-        try:
-            return ast.literal_eval(dict_str)
-        except (SyntaxError, ValueError):
-            print(f"Invalid dictionary format: {dict_str}")
-    return {}
-
-
-def group_pages_containing_tables(
-    text_dict: Dict[str, str]
-) -> Dict[str, Dict[str, Any]]:
-    # TODO: add test cases for this function
-    """
-    Groups pages containing tables into start and continuation groups based on patterns.
-
-    Args:
-        text_dict (Dict[str, str]): A dictionary where keys are page numbers (as strings) and values are the page contents.
-
-    Returns:
-        Dict[str, Dict[str, Any]]: A dictionary where keys are the start page numbers of groups, and values are dictionaries containing:
-            - "metadata": Metadata of the start page.
-            - "group": List of page numbers in the group.
-
-    The function processes each page in the input dictionary, identifies if the page contains a table that matches a start or continuation pattern,
-    and groups the pages accordingly. If a page does not match any pattern, it is not included in any group.
-    """
-    groups: Dict[str, Dict[str, Any]] = defaultdict(dict)
-    current_group: List[str] = []
-    group_metadata: Optional[str] = None
-    for page_num, page_content in text_dict.items():
-        # We can have one or more tables present on a page. The first table (ONLY) on the page decides if the page will be a start or continuation page.
-
-        first_table_on_page = extract_first_table_from_page(page_content)
-
-        if re.search(
-            START_PAGE_PATTERN, first_table_on_page
-        ):  # Check if the page matches the start pattern
-            if current_group:  # if a group is already established previously
-                group_start_page: str = current_group[0]
-                groups[group_start_page] = {
-                    "metadata": group_metadata,
-                    "group": current_group,
-                }
-                current_group = (
-                    []
-                )  # reset the current group, because we've found the start pattern
-                group_metadata = None
-            current_group = [page_num]
-            group_metadata = get_page_metadata(page_content)
-        elif re.search(
-            CONTINUATION_PAGE_PATTERN, first_table_on_page
-        ):  # Check if the page matches the continuation pattern
-            if current_group:
-                current_group.append(page_num)
-            else:  # If the first page we're processing is a continuation page, we start a new group (edge case)
-                current_group = [page_num]
-                group_metadata = get_page_metadata(page_content)
-        else:  # If the page doesn't match any pattern
-            if current_group:  # if we're in the middle of a group, close it
-                group_start_page = current_group[0]
-                groups[group_start_page] = {
-                    "metadata": group_metadata,
-                    "group": current_group,
-                }
-                current_group = []  # reset the current group
-                group_metadata = None
-    if current_group:  # save off the current group if we're at the end of the text
-        group_start_page = current_group[0]
-        groups[group_start_page] = {"metadata": group_metadata, "group": current_group}
-    return groups
-
-
-def insert_metadata(metadata: str, table_content: str) -> str:
-    """
-    Inserts metadata at the beginning of the table content.
-
-    Args:
-        metadata (str): The metadata to be inserted.
-        table_content (str): The content of the table.
-
-    Returns:
-        str: The combined string with metadata followed by the table content.
-    """
-    return f"{metadata}\n{table_content}"
-
-
-def insert_column_headers(
-    data_dict: dict[str, list[str]], columns: list
-) -> dict[str, list[str]]:
-    """
-    Inserts column headers into a dictionary of data. It takes the existing column headers and inserts them as the first row of the data.
-
-    Args:
-        data_dict (dict): The dictionary containing the data to be modified.
-        columns (list): A list of column headers to be inserted.
-
-    Returns:
-        dict: A new dictionary with the column headers inserted. If the input dictionary is empty, returns an empty dictionary.
-    """
-    if not data_dict:
-        print("Dictionary not found in the text.")
-        return {}
-    record = list(data_dict.items())
-    modified_dict = {
-        col_name: [col_items[0]] + col_items[1]
-        for col_name, col_items in zip(columns, record)
-    }
-
-    return modified_dict
-
-
-def correct_column_headers_and_merge(
-    text_dict: dict[str, str], groups: dict[str, dict[str, Any]]
-) -> dict[str, List[pd.DataFrame]]:
-    """
-    Corrects column headers and merges tables from multiple pages.
-
-    Args:
-        text_dict (dict[str, str]): A dictionary where keys are page numbers and values are the text content of those pages.
-        groups (dict): A dictionary where keys are the starting page numbers of groups and values are dictionaries containing group data.
-
-    Returns:
-        dict: A dictionary where keys are the starting page numbers of groups and values are lists of DataFrames representing the merged tables.
-    """
-
-    page_tables_map = {}
-
-    columns_to_use: List[str] = []  # for mypy
-
-    for group_start_page, group_data in groups.items():  # Loop through groups
-        dfs_list = []
-        columns = None
-
-        for page in group_data["group"]:  # Loop through pages in the group
-            page_content = text_dict[page]
-
-            str_dicts = get_str_dictionaries_from_text(page_content, only_first=False)
-            for str_dict in str_dicts:
-                data_dict = convert_str_to_dict(str_dict)
-                # if the page contains multiple tables, rewrite the latest column headers each time
-                # Otherwise, use the column headers from the first table in the group
-                columns_to_use = (
-                    data_dict.keys() if page == group_start_page else columns_to_use
-                )
-
-                col_corrected_dict = insert_column_headers(data_dict, columns_to_use)
-
-                if (
-                    page == group_start_page
-                ):  # on the first table, we've already changed the keys to be the first row, so we need to drop that row
-                    df = pd.DataFrame(col_corrected_dict).drop(index=0)
-                else:
-                    df = pd.DataFrame(col_corrected_dict)
-
-                df["page_num"] = page
-
-                dfs_list.append(df)
-
-        tables = dfs_list
-        page_tables_map[group_start_page] = (
-            tables  # List of dataframes corresponding to the tables in the group
-        )
-    return page_tables_map
-
-
-def group_and_merge_tables(text_dict: dict[str, str]) -> tuple[dict, dict]:
-    """
-    Groups pages containing tables and merges the tables after correcting column headers.
-
-    Args:
-        text_dict (dict[str, str]): A dictionary where keys are page identifiers and values are the text content of the pages.
-
-    Returns:
-        tuple[dict, dict]: A tuple containing:
-            - groups (dict): A dictionary where keys are group identifiers and values are lists of page identifiers that belong to each group.
-            - page_tables_map (dict): A dictionary where keys are page identifiers and values are the merged tables after correcting column headers.
-    """
-    groups = group_pages_containing_tables(text_dict)
-
-    page_tables_map = correct_column_headers_and_merge(
-        text_dict, groups
-    )  # extract the tables from all pages, correct the col headers, put the individual tables in the df, then merge those dfs
-
-    return groups, page_tables_map
-
-
-def split_table_to_pages(groups: dict, page_tables_map: dict, row_limit: int) -> dict:
-    """
-    Splits tables into pages based on the provided groups and page tables map.
-    Args:
-        groups (dict): A dictionary where keys are the starting page numbers of groups and values are dictionaries containing group data.
-        page_tables_map (dict): A dictionary mapping page numbers to lists of DataFrames representing tables on those pages.
-        row_limit (int, optional): The number of rows per table split. Defaults to 5.
-    Returns:
-        dict: A dictionary where keys are the starting page numbers of groups and values are dictionaries mapping page numbers to lists of related tables.
-    """
-    group_table_split_info = {}
-
-    for group_start_page, group_data in groups.items():  # Loop through groups
-        dfs_list = page_tables_map[group_start_page]  # get list of tables for the group
-        metadata_list = group_data["metadata"]
-
-        if all(
-            [isinstance(metadata, tuple) for metadata in metadata_list]
-        ):  # if the metadata is a list of tuples, this page has multiple tables
-            metadata_list = [
-                metadata[0] for metadata in metadata_list
-            ]  # Just extract the metadata strings (the second element of the tuple in the metadata is a text dictionary snippet)
-
-        # if the group contains multiple pages with common metadata, duplicate the metadata for each page
-        # This handles cases:
-        # - when the group contains multiple pages with common metadata, this will work
-        # - when the page contains multiple tables which start AND end on the single page, this will work
-        # An unhandled edge case, when the page contains multiple tables in this scenario:
-        # - when the LAST table of a page is the beginning of a table continued onto the next page, we won't get the metadata right
-
-        # If the group has a single page with multiple tables
-        if len(group_data["group"]) > 1:  # if the group contains multiple pages
-            metadata_list = [
-                metadata_list[0] for _ in range(len(dfs_list))
-            ]  # duplicate the metadata for each page
-
-        if (
-            len(group_data["group"]) == 1
-        ):  # its a single page group with len(dfs_list) number of tables - eg [6]->[6,6,6,6] if the group contains just page "6" and page "6" has 4 tables
-            group_data["group"] = [group_data["group"][0] for _ in range(len(dfs_list))]
-
-        chunked_tables_page_mapping = defaultdict(list)
-
-        # loop through each page, metadata, and dataframe in the group
-        for page_num, metadata, df in zip(group_data["group"], metadata_list, dfs_list):
-            num_rows = df.shape[0]
-            num_tables = math.ceil(num_rows / row_limit)  # number of output tables
-
-            related_tables = []
-
-            for i in range(num_tables):
-                start_row = i * row_limit
-                end_row = min((i + 1) * row_limit, df.shape[0])
-                table_df = df.iloc[start_row:end_row, :]
-
-                str_df = str(table_df.drop(columns=["page_num"]).to_dict(orient="list"))
-
-                table_dict = insert_metadata(metadata, str_df)
-
-                assert (  # TODO: convert to `raise` instead of `assert`
-                    table_df["page_num"].nunique() == 1
-                ), "All rows in a table should belong to the same page"
-
-                page_num = table_df["page_num"].unique()[0]
-
-                related_tables.append(
-                    table_dict
-                )  # these tables are splits of a larger table from one page
-
-            chunked_tables_page_mapping[page_num].append(related_tables)
-
-        group_table_split_info[group_start_page] = chunked_tables_page_mapping
-
-    return group_table_split_info
-
-
-def replace_tables_in_page(
-    page_num: int, modified_text_dict: dict, new_tables_list: list
-) -> None:
-    """
-    Replaces existing tables within pages to modified (corrected) tables.
-    Args:
-        page_num (int): The page number where the reinsertion should occur.
-        modified_text_dict (dict): A dictionary containing the text of each page, with page numbers as keys.
-        new_tables_list (list): A list of lists, where each inner list contains tables to be inserted.
-    Returns:
-        None: This function modifies the `modified_text_dict` in place.
-    """
-
-    text = modified_text_dict[page_num]
-
-    formatted_tables = []
-
-    for (
-        table_list
-    ) in new_tables_list:  # Format new tables for insertion back into pages
-        lst = []
-
-        for table in table_list:
-            lst.append(f"{START_MARKER}\n{table}\n{END_MARKER}")
-
-        concatenated_tables = "\n".join(lst)
-
-        formatted_tables.append(concatenated_tables)
-
-    detect_tables_pattern = rf"({START_MARKER}.+?{END_MARKER})"
-
-    tables_to_replace = re.findall(detect_tables_pattern, text, re.DOTALL)
-
-    for original_table, replacement_table in zip(tables_to_replace, formatted_tables):
-        text = re.sub(
-            re.escape(original_table), replacement_table, text, count=1, flags=re.DOTALL
-        )
-
-    modified_text_dict[page_num] = text
-
-
-def reinsert_new_tables_to_text(group_table_split_info: dict, text_dict: dict) -> dict:
-    """
-    Take what's in groups, apply `replace_tables_in_page` to each group, and then reinsert the tables back into the text.
-    This is really a wrapper function for `replace_tables_in_page` which goes through each page and applies the function.
-
-    Args:
-        group_table_split_info (dict): A dictionary where the keys are the starting page numbers of groups and the values
-                                       are dictionaries mapping page numbers to lists of split tables.
-
-    Returns:
-        dict: A modified version of the original text dictionary with the tables reinserted.
-    """
-    modified_text_dict = copy.deepcopy(text_dict)
-
-    for group_start_page, chunked_tables_page_mapping in group_table_split_info.items():
-
-        for page_num in chunked_tables_page_mapping.keys():
-            split_tables_list = chunked_tables_page_mapping[page_num]
-            # perform the reinsertion (inplace)
-            replace_tables_in_page(page_num, modified_text_dict, split_tables_list)
-
-    return modified_text_dict
-
-
-def split_tables_to_separate_subpages(text_dict: dict[str, str]) -> dict[str, str]:
-    """
-    Splits the text content of each page in the input dictionary into separate subpages based on a table end marker.
-
-    Args:
-        text_dict (dict[str, str]): A dictionary where keys are page identifiers and values are the text content of those pages.
-
-    Returns:
-        dict[str, str]: A new dictionary where keys are modified page identifiers (including subpage indices) and values are the split text content. Empty strings are removed from the result.
-    """
-    new_text_dict = {}
-    for page in text_dict.keys():
-        # split the text into separate pages based on the table end marker
-        if END_MARKER in text_dict[page]:
-            new_text_list = re.split(
-                rf"(?<={END_MARKER})", text_dict[page]
-            )  # this regex will split on the end marker, and keep the end marker in the text
-            for i, text in enumerate(new_text_list):
-                new_text_dict[f"{page}.{i}"] = text
-        else:
-            new_text_dict[page] = text_dict[page]
-    return {k: v for k, v in new_text_dict.items() if v.strip()}  # remove empty strings
diff --git a/fieldExtraction/tests/test_string_utils.py b/fieldExtraction/tests/test_string_utils.py
index 03aa19f..e9af0ad 100644
--- a/fieldExtraction/tests/test_string_utils.py
+++ b/fieldExtraction/tests/test_string_utils.py
@@ -151,13 +151,12 @@ class TestStringUtils:
         result = contains_reimbursement(text, page)
         assert result == expected
 
-    def test_invalid_input_type(self, capsys):
+    def test_invalid_input_type(self, caplog):
         text = ["This is a list, not a dictionary or string."]
         page = "1"
         result = contains_reimbursement(text, page)
         assert result is False
-        captured = capsys.readouterr()
-        assert "contains_reimbursement - Invalid data type" in captured.out
+        assert "contains_reimbursement - Invalid data type" in caplog.text
 
     @pytest.mark.parametrize(
         "value, expected",