diff --git a/poetry.lock b/poetry.lock
index 506d733..4b1a7e7 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
 
 [[package]]
 name = "airium"
@@ -312,38 +312,38 @@ files = [
 
 [[package]]
 name = "bcrypt"
-version = "4.1.3"
+version = "4.2.0"
 description = "Modern password hashing for your software and your servers"
 optional = false
 python-versions = ">=3.7"
 files = [
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-    {file = "bcrypt-4.1.3-cp37-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4a8bea4c152b91fd8319fef4c6a790da5c07840421c2b785084989bf8bbb7455"},
-    {file = "bcrypt-4.1.3-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3d3b317050a9a711a5c7214bf04e28333cf528e0ed0ec9a4e55ba628d0f07c1a"},
-    {file = "bcrypt-4.1.3-cp37-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:094fd31e08c2b102a14880ee5b3d09913ecf334cd604af27e1013c76831f7b05"},
-    {file = "bcrypt-4.1.3-cp37-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:4fb253d65da30d9269e0a6f4b0de32bd657a0208a6f4e43d3e645774fb5457f3"},
-    {file = "bcrypt-4.1.3-cp37-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:193bb49eeeb9c1e2db9ba65d09dc6384edd5608d9d672b4125e9320af9153a15"},
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-    {file = "bcrypt-4.1.3-cp37-abi3-win_amd64.whl", hash = "sha256:8a893d192dfb7c8e883c4576813bf18bb9d59e2cfd88b68b725990f033f1b978"},
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+    {file = "bcrypt-4.2.0-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:cb2a8ec2bc07d3553ccebf0746bbf3d19426d1c6d1adbd4fa48925f66af7b9e8"},
+    {file = "bcrypt-4.2.0-cp39-abi3-win32.whl", hash = "sha256:77800b7147c9dc905db1cba26abe31e504d8247ac73580b4aa179f98e6608f34"},
+    {file = "bcrypt-4.2.0-cp39-abi3-win_amd64.whl", hash = "sha256:61ed14326ee023917ecd093ee6ef422a72f3aec6f07e21ea5f10622b735538a9"},
+    {file = "bcrypt-4.2.0-pp310-pypy310_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:39e1d30c7233cfc54f5c3f2c825156fe044efdd3e0b9d309512cc514a263ec2a"},
+    {file = "bcrypt-4.2.0-pp310-pypy310_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:f4f4acf526fcd1c34e7ce851147deedd4e26e6402369304220250598b26448db"},
+    {file = "bcrypt-4.2.0-pp39-pypy39_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:1ff39b78a52cf03fdf902635e4c81e544714861ba3f0efc56558979dd4f09170"},
+    {file = "bcrypt-4.2.0-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:373db9abe198e8e2c70d12b479464e0d5092cc122b20ec504097b5f2297ed184"},
+    {file = "bcrypt-4.2.0.tar.gz", hash = "sha256:cf69eaf5185fd58f268f805b505ce31f9b9fc2d64b376642164e9244540c1221"},
 ]
 
 [package.extras]
@@ -458,13 +458,13 @@ virtualenv = ["virtualenv (>=20.0.35)"]
 
 [[package]]
 name = "cachetools"
-version = "5.3.3"
+version = "5.4.0"
 description = "Extensible memoizing collections and decorators"
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "cachetools-5.4.0-py3-none-any.whl", hash = "sha256:3ae3b49a3d5e28a77a0be2b37dbcb89005058959cb2323858c2657c4a8cab474"},
+    {file = "cachetools-5.4.0.tar.gz", hash = "sha256:b8adc2e7c07f105ced7bc56dbb6dfbe7c4a00acce20e2227b3f355be89bc6827"},
 ]
 
 [[package]]
@@ -494,13 +494,13 @@ ujson = ["ujson (>=5.7.0)"]
 
 [[package]]
 name = "certifi"
-version = "2024.6.2"
+version = "2024.7.4"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
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+    {file = "certifi-2024.7.4-py3-none-any.whl", hash = "sha256:c198e21b1289c2ab85ee4e67bb4b4ef3ead0892059901a8d5b622f24a1101e90"},
+    {file = "certifi-2024.7.4.tar.gz", hash = "sha256:5a1e7645bc0ec61a09e26c36f6106dd4cf40c6db3a1fb6352b0244e7fb057c7b"},
 ]
 
 [[package]]
@@ -934,43 +934,38 @@ test-no-images = ["pytest", "pytest-cov", "pytest-xdist", "wurlitzer"]
 
 [[package]]
 name = "cryptography"
-version = "42.0.8"
+version = "43.0.0"
 description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
 optional = false
 python-versions = ">=3.7"
 files = [
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 [package.dependencies]
@@ -983,18 +978,18 @@ nox = ["nox"]
 pep8test = ["check-sdist", "click", "mypy", "ruff"]
 sdist = ["build"]
 ssh = ["bcrypt (>=3.1.5)"]
-test = ["certifi", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-xdist"]
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 test-randomorder = ["pytest-randomly"]
 
 [[package]]
 name = "curies"
-version = "0.7.9"
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 description = "Idiomatic conversion between URIs and compact URIs (CURIEs)."
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
@@ -1027,33 +1022,13 @@ tests = ["pytest", "pytest-cov", "pytest-xdist"]
 
 [[package]]
 name = "debugpy"
-version = "1.8.1"
+version = "1.8.3"
 description = "An implementation of the Debug Adapter Protocol for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
@@ -1251,21 +1226,6 @@ files = [
 lxml = "*"
 six = "*"
 
-[[package]]
-name = "email-validator"
-version = "2.1.2"
-description = "A robust email address syntax and deliverability validation library."
-optional = false
-python-versions = ">=3.8"
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-
-[package.dependencies]
-dnspython = ">=2.0.0"
-idna = ">=2.0.0"
-
 [[package]]
 name = "et-xmlfile"
 version = "1.1.0"
@@ -1298,13 +1258,13 @@ dev = ["flake8", "ipython", "mock", "pytest", "pytest-cov", "restview", "setupto
 
 [[package]]
 name = "exceptiongroup"
-version = "1.2.1"
+version = "1.2.2"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.extras]
@@ -1340,47 +1300,23 @@ importlib-resources = {version = ">=5.0", markers = "python_version < \"3.10\""}
 
 [[package]]
 name = "fastapi"
-version = "0.111.0"
+version = "0.112.0"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
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-orjson = ">=3.2.1"
 pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<2.0.0 || >2.0.0,<2.0.1 || >2.0.1,<2.1.0 || >2.1.0,<3.0.0"
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 typing-extensions = ">=4.8.0"
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-uvicorn = {version = ">=0.12.0", extras = ["standard"]}
 
 [package.extras]
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-
-[[package]]
-name = "fastapi-cli"
-version = "0.0.4"
-description = "Run and manage FastAPI apps from the command line with FastAPI CLI. 🚀"
-optional = false
-python-versions = ">=3.8"
-files = [
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-]
-
-[package.dependencies]
-typer = ">=0.12.3"
-
-[package.extras]
-standard = ["fastapi", "uvicorn[standard] (>=0.15.0)"]
+all = ["email_validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.5)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=2.11.2)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.7)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
+standard = ["email_validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.5)", "httpx (>=0.23.0)", "jinja2 (>=2.11.2)", "python-multipart (>=0.0.7)", "uvicorn[standard] (>=0.12.0)"]
 
 [[package]]
 name = "fastjsonschema"
@@ -1453,18 +1389,18 @@ files = [
 
 [[package]]
 name = "filelock"
-version = "3.15.1"
+version = "3.15.4"
 description = "A platform independent file lock."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
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 [package.extras]
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 [package.dependencies]
@@ -1677,36 +1613,33 @@ test = ["coverage[toml]", "ddt (>=1.1.1,!=1.4.3)", "mock", "mypy", "pre-commit",
 
 [[package]]
 name = "google-api-core"
-version = "2.19.0"
+version = "2.8.2"
 description = "Google API client core library"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.6"
 files = [
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+protobuf = ">=3.15.0,<5.0.0dev"
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-grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
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 [[package]]
 name = "google-api-python-client"
-version = "2.133.0"
+version = "2.139.0"
 description = "Google API Client Library for Python"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -1718,13 +1651,13 @@ uritemplate = ">=3.0.1,<5"
 
 [[package]]
 name = "google-auth"
-version = "2.30.0"
+version = "2.32.0"
 description = "Google Authentication Library"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -1756,13 +1689,13 @@ httplib2 = ">=0.19.0"
 
 [[package]]
 name = "google-auth-oauthlib"
-version = "1.2.0"
+version = "1.2.1"
 description = "Google Authentication Library"
 optional = false
 python-versions = ">=3.6"
 files = [
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 ]
 
 [package.dependencies]
@@ -1787,20 +1720,20 @@ requests = "*"
 
 [[package]]
 name = "googleapis-common-protos"
-version = "1.63.1"
+version = "1.56.4"
 description = "Common protobufs used in Google APIs"
 optional = false
 python-versions = ">=3.7"
 files = [
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+protobuf = ">=3.15.0,<5.0.0dev"
 
 [package.extras]
-grpc = ["grpcio (>=1.44.0,<2.0.0.dev0)"]
+grpc = ["grpcio (>=1.0.0,<2.0.0dev)"]
 
 [[package]]
 name = "gpt4all"
@@ -1910,61 +1843,61 @@ test = ["objgraph", "psutil"]
 
 [[package]]
 name = "grpcio"
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 description = "HTTP/2-based RPC framework"
 optional = false
 python-versions = ">=3.8"
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+]
+
+[package.extras]
+protobuf = ["grpcio-tools (>=1.65.4)"]
 
 [[package]]
 name = "gspread"
@@ -2111,13 +2044,13 @@ socks = ["socksio (==1.*)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "0.23.4"
+version = "0.24.5"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.8.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -2130,17 +2063,17 @@ tqdm = ">=4.42.1"
 typing-extensions = ">=3.7.4.3"
 
 [package.extras]
-all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.3.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
+all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.5.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 cli = ["InquirerPy (==0.3.4)"]
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 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
 hf-transfer = ["hf-transfer (>=0.1.4)"]
 inference = ["aiohttp", "minijinja (>=1.0)"]
-quality = ["mypy (==1.5.1)", "ruff (>=0.3.0)"]
+quality = ["mypy (==1.5.1)", "ruff (>=0.5.0)"]
 tensorflow = ["graphviz", "pydot", "tensorflow"]
 tensorflow-testing = ["keras (<3.0)", "tensorflow"]
-testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
-torch = ["safetensors", "torch"]
+testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "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]]
@@ -2284,22 +2217,22 @@ files = [
 
 [[package]]
 name = "importlib-metadata"
-version = "7.1.0"
+version = "8.0.0"
 description = "Read metadata from Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
 zipp = ">=0.5"
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
 perf = ["ipython"]
-testing = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-perf (>=0.9.2)", "pytest-ruff (>=0.2.1)"]
+test = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-perf (>=0.9.2)", "pytest-ruff (>=0.2.1)"]
 
 [[package]]
 name = "importlib-resources"
@@ -2341,20 +2274,6 @@ files = [
     {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
 ]
 
-[[package]]
-name = "intel-openmp"
-version = "2021.4.0"
-description = "Intel OpenMP* Runtime Library"
-optional = false
-python-versions = "*"
-files = [
-    {file = "intel_openmp-2021.4.0-py2.py3-none-macosx_10_15_x86_64.macosx_11_0_x86_64.whl", hash = "sha256:41c01e266a7fdb631a7609191709322da2bbf24b252ba763f125dd651bcc7675"},
-    {file = "intel_openmp-2021.4.0-py2.py3-none-manylinux1_i686.whl", hash = "sha256:3b921236a38384e2016f0f3d65af6732cf2c12918087128a9163225451e776f2"},
-    {file = "intel_openmp-2021.4.0-py2.py3-none-manylinux1_x86_64.whl", hash = "sha256:e2240ab8d01472fed04f3544a878cda5da16c26232b7ea1b59132dbfb48b186e"},
-    {file = "intel_openmp-2021.4.0-py2.py3-none-win32.whl", hash = "sha256:6e863d8fd3d7e8ef389d52cf97a50fe2afe1a19247e8c0d168ce021546f96fc9"},
-    {file = "intel_openmp-2021.4.0-py2.py3-none-win_amd64.whl", hash = "sha256:eef4c8bcc8acefd7f5cd3b9384dbf73d59e2c99fc56545712ded913f43c4a94f"},
-]
-
 [[package]]
 name = "intervaltree"
 version = "3.1.0"
@@ -2370,13 +2289,13 @@ sortedcontainers = ">=2.0,<3.0"
 
 [[package]]
 name = "ipykernel"
-version = "6.29.4"
+version = "6.29.5"
 description = "IPython Kernel for Jupyter"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "ipykernel-6.29.4-py3-none-any.whl", hash = "sha256:1181e653d95c6808039c509ef8e67c4126b3b3af7781496c7cbfb5ed938a27da"},
-    {file = "ipykernel-6.29.4.tar.gz", hash = "sha256:3d44070060f9475ac2092b760123fadf105d2e2493c24848b6691a7c4f42af5c"},
+    {file = "ipykernel-6.29.5-py3-none-any.whl", hash = "sha256:afdb66ba5aa354b09b91379bac28ae4afebbb30e8b39510c9690afb7a10421b5"},
+    {file = "ipykernel-6.29.5.tar.gz", hash = "sha256:f093a22c4a40f8828f8e330a9c297cb93dcab13bd9678ded6de8e5cf81c56215"},
 ]
 
 [package.dependencies]
@@ -2640,13 +2559,13 @@ files = [
 
 [[package]]
 name = "jsonschema"
-version = "4.22.0"
+version = "4.23.0"
 description = "An implementation of JSON Schema validation for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jsonschema-4.22.0-py3-none-any.whl", hash = "sha256:ff4cfd6b1367a40e7bc6411caec72effadd3db0bbe5017de188f2d6108335802"},
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+    {file = "jsonschema-4.23.0-py3-none-any.whl", hash = "sha256:fbadb6f8b144a8f8cf9f0b89ba94501d143e50411a1278633f56a7acf7fd5566"},
+    {file = "jsonschema-4.23.0.tar.gz", hash = "sha256:d71497fef26351a33265337fa77ffeb82423f3ea21283cd9467bb03999266bc4"},
 ]
 
 [package.dependencies]
@@ -2662,11 +2581,14 @@ rfc3986-validator = {version = ">0.1.0", optional = true, markers = "extra == \"
 rfc3987 = {version = "*", optional = true, markers = "extra == \"format\""}
 rpds-py = ">=0.7.1"
 uri-template = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
-webcolors = {version = ">=1.11", optional = true, markers = "extra == \"format-nongpl\""}
+webcolors = [
+    {version = ">=1.11", optional = true, markers = "extra == \"format\""},
+    {version = ">=24.6.0", optional = true, markers = "extra == \"format-nongpl\""},
+]
 
 [package.extras]
 format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
-format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=1.11)"]
+format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=24.6.0)"]
 
 [[package]]
 name = "jsonschema-specifications"
@@ -2811,13 +2733,13 @@ jupyter-server = ">=1.1.2"
 
 [[package]]
 name = "jupyter-server"
-version = "2.14.1"
+version = "2.14.2"
 description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyter_server-2.14.1-py3-none-any.whl", hash = "sha256:16f7177c3a4ea8fe37784e2d31271981a812f0b2874af17339031dc3510cc2a5"},
-    {file = "jupyter_server-2.14.1.tar.gz", hash = "sha256:12558d158ec7a0653bf96cc272bc7ad79e0127d503b982ed144399346694f726"},
+    {file = "jupyter_server-2.14.2-py3-none-any.whl", hash = "sha256:47ff506127c2f7851a17bf4713434208fc490955d0e8632e95014a9a9afbeefd"},
+    {file = "jupyter_server-2.14.2.tar.gz", hash = "sha256:66095021aa9638ced276c248b1d81862e4c50f292d575920bbe960de1c56b12b"},
 ]
 
 [package.dependencies]
@@ -2909,13 +2831,13 @@ files = [
 
 [[package]]
 name = "jupyterlab-server"
-version = "2.27.2"
+version = "2.27.3"
 description = "A set of server components for JupyterLab and JupyterLab like applications."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyterlab_server-2.27.2-py3-none-any.whl", hash = "sha256:54aa2d64fd86383b5438d9f0c032f043c4d8c0264b8af9f60bd061157466ea43"},
-    {file = "jupyterlab_server-2.27.2.tar.gz", hash = "sha256:15cbb349dc45e954e09bacf81b9f9bcb10815ff660fb2034ecd7417db3a7ea27"},
+    {file = "jupyterlab_server-2.27.3-py3-none-any.whl", hash = "sha256:e697488f66c3db49df675158a77b3b017520d772c6e1548c7d9bcc5df7944ee4"},
+    {file = "jupyterlab_server-2.27.3.tar.gz", hash = "sha256:eb36caca59e74471988f0ae25c77945610b887f777255aa21f8065def9e51ed4"},
 ]
 
 [package.dependencies]
@@ -3134,13 +3056,13 @@ regex = ["regex"]
 
 [[package]]
 name = "linkml"
-version = "1.7.10"
+version = "1.8.1"
 description = "Linked Open Data Modeling Language"
 optional = false
 python-versions = "<4.0.0,>=3.8.1"
 files = [
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-    {file = "linkml-1.7.10.tar.gz", hash = "sha256:1c38601c3cd495e34490b8cf7277fd3674ec68dcbe9f5efcec2658093801ce91"},
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+    {file = "linkml-1.8.1.tar.gz", hash = "sha256:19e53478119af11e7a6633d764c13dc9d849d3ff9e7d2efc87c9158041e7b7bb"},
 ]
 
 [package.dependencies]
@@ -3153,7 +3075,7 @@ jinja2 = ">=3.1.0"
 jsonasobj2 = ">=1.0.3,<2.0.0"
 jsonschema = {version = ">=4.0.0", extras = ["format"]}
 linkml-dataops = "*"
-linkml-runtime = ">=1.7.4"
+linkml-runtime = "1.8.0"
 openpyxl = "*"
 parse = "*"
 prefixcommons = ">=0.1.7"
@@ -3194,13 +3116,13 @@ linkml-runtime = ">=1.1.6"
 
 [[package]]
 name = "linkml-renderer"
-version = "0.3.0"
+version = "0.3.1"
 description = "linkml-renderer"
 optional = false
-python-versions = ">=3.8,<4.0"
+python-versions = "<4.0,>=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -3211,13 +3133,13 @@ pydantic = "*"
 
 [[package]]
 name = "linkml-runtime"
-version = "1.7.7"
+version = "1.8.0"
 description = "Runtime environment for LinkML, the Linked open data modeling language"
 optional = false
 python-versions = "<4.0,>=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -3237,13 +3159,13 @@ requests = "*"
 
 [[package]]
 name = "llm"
-version = "0.14"
+version = "0.15"
 description = "A CLI utility and Python library for interacting with Large Language Models, including OpenAI, PaLM and local models installed on your own machine."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -3258,7 +3180,7 @@ python-ulid = "*"
 PyYAML = "*"
 setuptools = "*"
 sqlite-migrate = ">=0.1a2"
-sqlite-utils = ">=3.35.0"
+sqlite-utils = ">=3.37"
 
 [package.extras]
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@@ -3531,40 +3457,40 @@ files = [
 
 [[package]]
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+version = "3.9.1"
 description = "Python plotting package"
 optional = false
 python-versions = ">=3.9"
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 ]
 
 [package.dependencies]
@@ -3637,24 +3563,6 @@ files = [
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 ]
 
-[[package]]
-name = "mkl"
-version = "2021.4.0"
-description = "Intel® oneAPI Math Kernel Library"
-optional = false
-python-versions = "*"
-files = [
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-]
-
-[package.dependencies]
-intel-openmp = "==2021.*"
-tbb = "==2021.*"
-
 [[package]]
 name = "mmh3"
 version = "4.1.0"
@@ -3901,13 +3809,13 @@ test = ["pep440", "pre-commit", "pytest", "testpath"]
 
 [[package]]
 name = "ndex2"
-version = "3.8.0"
+version = "3.9.0"
 description = "Nice CX Python includes a client and a data model."
 optional = false
 python-versions = "*"
 files = [
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 ]
 
 [package.dependencies]
@@ -4080,12 +3988,13 @@ files = [
 
 [[package]]
 name = "nvidia-cudnn-cu12"
-version = "8.9.2.26"
+version = "9.1.0.70"
 description = "cuDNN runtime libraries"
 optional = false
 python-versions = ">=3"
 files = [
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 ]
 
 [package.dependencies]
@@ -4156,14 +4065,14 @@ files = [
 
 [[package]]
 name = "nvidia-nvjitlink-cu12"
-version = "12.5.40"
+version = "12.6.20"
 description = "Nvidia JIT LTO Library"
 optional = false
 python-versions = ">=3"
 files = [
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 ]
 
 [[package]]
@@ -4179,13 +4088,13 @@ files = [
 
 [[package]]
 name = "oaklib"
-version = "0.6.9"
+version = "0.6.14"
 description = "Ontology Access Kit: Python library for common ontology operations over a variety of backends"
 optional = false
 python-versions = "<4.0.0,>=3.9"
 files = [
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 ]
 
 [package.dependencies]
@@ -4194,15 +4103,15 @@ appdirs = ">=1.4.4"
 class-resolver = ">=0.4.2"
 click = "*"
 curies = ">=0.6.6"
-defusedxml = ">=0.7.1,<0.8.0"
+defusedxml = ">=0.7.1"
 eutils = ">=0.6.0"
 funowl = ">=0.2.0"
-jsonlines = ">=4.0.0,<5.0.0"
+jsonlines = "*"
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 kgcl-schema = ">=0.6.8,<0.7.0"
 linkml-renderer = ">=0.3.0"
 linkml-runtime = ">=1.5.3"
-ndex2 = ">=3.5.0,<4.0.0"
+ndex2 = ">=3.5.0"
 networkx = ">=2.7.1"
 ols-client = ">=0.1.1"
 ontoportal-client = ">=0.0.3"
@@ -4217,11 +4126,11 @@ semsql = ">=0.3.1"
 SPARQLWrapper = "*"
 SQLAlchemy = ">=1.4.32"
 sssom = ">=0.4.4,<0.5.0"
-tenacity = ">=8.2.3,<9.0.0"
+tenacity = ">=8.2.3"
 
 [package.extras]
 gilda = ["gilda (>=1.0.0)", "urllib3 (<2)"]
-llm = ["aiohttp", "html2text", "llm"]
+llm = ["aiohttp", "html2text", "llm (>=0.14,<0.15)"]
 semsimian = ["semsimian (>=0.2.16)"]
 
 [[package]]
@@ -4264,42 +4173,42 @@ tests = ["coverage", "pytest"]
 
 [[package]]
 name = "onnxruntime"
-version = "1.18.0"
+version = "1.18.1"
 description = "ONNX Runtime is a runtime accelerator for Machine Learning models"
 optional = false
 python-versions = "*"
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 ]
 
 [package.dependencies]
 coloredlogs = "*"
 flatbuffers = "*"
-numpy = ">=1.21.6"
+numpy = ">=1.21.6,<2.0"
 packaging = "*"
 protobuf = "*"
 sympy = "*"
@@ -4325,13 +4234,13 @@ tests = ["coverage", "pytest", "unittest-templates"]
 
 [[package]]
 name = "openai"
-version = "1.34.0"
+version = "1.38.0"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.7.1"
 files = [
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 ]
 
 [package.dependencies]
@@ -4348,13 +4257,13 @@ datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
 
 [[package]]
 name = "openpyxl"
-version = "3.1.4"
+version = "3.1.5"
 description = "A Python library to read/write Excel 2010 xlsx/xlsm files"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -4362,42 +4271,42 @@ et-xmlfile = "*"
 
 [[package]]
 name = "opentelemetry-api"
-version = "1.25.0"
+version = "1.26.0"
 description = "OpenTelemetry Python API"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_api-1.25.0-py3-none-any.whl", hash = "sha256:757fa1aa020a0f8fa139f8959e53dec2051cc26b832e76fa839a6d76ecefd737"},
-    {file = "opentelemetry_api-1.25.0.tar.gz", hash = "sha256:77c4985f62f2614e42ce77ee4c9da5fa5f0bc1e1821085e9a47533a9323ae869"},
+    {file = "opentelemetry_api-1.26.0-py3-none-any.whl", hash = "sha256:7d7ea33adf2ceda2dd680b18b1677e4152000b37ca76e679da71ff103b943064"},
+    {file = "opentelemetry_api-1.26.0.tar.gz", hash = "sha256:2bd639e4bed5b18486fef0b5a520aaffde5a18fc225e808a1ac4df363f43a1ce"},
 ]
 
 [package.dependencies]
 deprecated = ">=1.2.6"
-importlib-metadata = ">=6.0,<=7.1"
+importlib-metadata = ">=6.0,<=8.0.0"
 
 [[package]]
 name = "opentelemetry-exporter-otlp-proto-common"
-version = "1.25.0"
+version = "1.26.0"
 description = "OpenTelemetry Protobuf encoding"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_exporter_otlp_proto_common-1.25.0-py3-none-any.whl", hash = "sha256:15637b7d580c2675f70246563363775b4e6de947871e01d0f4e3881d1848d693"},
-    {file = "opentelemetry_exporter_otlp_proto_common-1.25.0.tar.gz", hash = "sha256:c93f4e30da4eee02bacd1e004eb82ce4da143a2f8e15b987a9f603e0a85407d3"},
+    {file = "opentelemetry_exporter_otlp_proto_common-1.26.0-py3-none-any.whl", hash = "sha256:ee4d8f8891a1b9c372abf8d109409e5b81947cf66423fd998e56880057afbc71"},
+    {file = "opentelemetry_exporter_otlp_proto_common-1.26.0.tar.gz", hash = "sha256:bdbe50e2e22a1c71acaa0c8ba6efaadd58882e5a5978737a44a4c4b10d304c92"},
 ]
 
 [package.dependencies]
-opentelemetry-proto = "1.25.0"
+opentelemetry-proto = "1.26.0"
 
 [[package]]
 name = "opentelemetry-exporter-otlp-proto-grpc"
-version = "1.25.0"
+version = "1.26.0"
 description = "OpenTelemetry Collector Protobuf over gRPC Exporter"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_exporter_otlp_proto_grpc-1.25.0-py3-none-any.whl", hash = "sha256:3131028f0c0a155a64c430ca600fd658e8e37043cb13209f0109db5c1a3e4eb4"},
-    {file = "opentelemetry_exporter_otlp_proto_grpc-1.25.0.tar.gz", hash = "sha256:c0b1661415acec5af87625587efa1ccab68b873745ca0ee96b69bb1042087eac"},
+    {file = "opentelemetry_exporter_otlp_proto_grpc-1.26.0-py3-none-any.whl", hash = "sha256:e2be5eff72ebcb010675b818e8d7c2e7d61ec451755b8de67a140bc49b9b0280"},
+    {file = "opentelemetry_exporter_otlp_proto_grpc-1.26.0.tar.gz", hash = "sha256:a65b67a9a6b06ba1ec406114568e21afe88c1cdb29c464f2507d529eb906d8ae"},
 ]
 
 [package.dependencies]
@@ -4405,19 +4314,19 @@ deprecated = ">=1.2.6"
 googleapis-common-protos = ">=1.52,<2.0"
 grpcio = ">=1.0.0,<2.0.0"
 opentelemetry-api = ">=1.15,<2.0"
-opentelemetry-exporter-otlp-proto-common = "1.25.0"
-opentelemetry-proto = "1.25.0"
-opentelemetry-sdk = ">=1.25.0,<1.26.0"
+opentelemetry-exporter-otlp-proto-common = "1.26.0"
+opentelemetry-proto = "1.26.0"
+opentelemetry-sdk = ">=1.26.0,<1.27.0"
 
 [[package]]
 name = "opentelemetry-instrumentation"
-version = "0.46b0"
+version = "0.47b0"
 description = "Instrumentation Tools & Auto Instrumentation for OpenTelemetry Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_instrumentation-0.46b0-py3-none-any.whl", hash = "sha256:89cd721b9c18c014ca848ccd11181e6b3fd3f6c7669e35d59c48dc527408c18b"},
-    {file = "opentelemetry_instrumentation-0.46b0.tar.gz", hash = "sha256:974e0888fb2a1e01c38fbacc9483d024bb1132aad92d6d24e2e5543887a7adda"},
+    {file = "opentelemetry_instrumentation-0.47b0-py3-none-any.whl", hash = "sha256:88974ee52b1db08fc298334b51c19d47e53099c33740e48c4f084bd1afd052d5"},
+    {file = "opentelemetry_instrumentation-0.47b0.tar.gz", hash = "sha256:96f9885e450c35e3f16a4f33145f2ebf620aea910c9fd74a392bbc0f807a350f"},
 ]
 
 [package.dependencies]
@@ -4427,55 +4336,55 @@ wrapt = ">=1.0.0,<2.0.0"
 
 [[package]]
 name = "opentelemetry-instrumentation-asgi"
-version = "0.46b0"
+version = "0.47b0"
 description = "ASGI instrumentation for OpenTelemetry"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_instrumentation_asgi-0.46b0-py3-none-any.whl", hash = "sha256:f13c55c852689573057837a9500aeeffc010c4ba59933c322e8f866573374759"},
-    {file = "opentelemetry_instrumentation_asgi-0.46b0.tar.gz", hash = "sha256:02559f30cf4b7e2a737ab17eb52aa0779bcf4cc06573064f3e2cb4dcc7d3040a"},
+    {file = "opentelemetry_instrumentation_asgi-0.47b0-py3-none-any.whl", hash = "sha256:b798dc4957b3edc9dfecb47a4c05809036a4b762234c5071212fda39ead80ade"},
+    {file = "opentelemetry_instrumentation_asgi-0.47b0.tar.gz", hash = "sha256:e78b7822c1bca0511e5e9610ec484b8994a81670375e570c76f06f69af7c506a"},
 ]
 
 [package.dependencies]
 asgiref = ">=3.0,<4.0"
 opentelemetry-api = ">=1.12,<2.0"
-opentelemetry-instrumentation = "0.46b0"
-opentelemetry-semantic-conventions = "0.46b0"
-opentelemetry-util-http = "0.46b0"
+opentelemetry-instrumentation = "0.47b0"
+opentelemetry-semantic-conventions = "0.47b0"
+opentelemetry-util-http = "0.47b0"
 
 [package.extras]
 instruments = ["asgiref (>=3.0,<4.0)"]
 
 [[package]]
 name = "opentelemetry-instrumentation-fastapi"
-version = "0.46b0"
+version = "0.47b0"
 description = "OpenTelemetry FastAPI Instrumentation"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_instrumentation_fastapi-0.46b0-py3-none-any.whl", hash = "sha256:e0f5d150c6c36833dd011f0e6ef5ede6d7406c1aed0c7c98b2d3b38a018d1b33"},
-    {file = "opentelemetry_instrumentation_fastapi-0.46b0.tar.gz", hash = "sha256:928a883a36fc89f9702f15edce43d1a7104da93d740281e32d50ffd03dbb4365"},
+    {file = "opentelemetry_instrumentation_fastapi-0.47b0-py3-none-any.whl", hash = "sha256:5ac28dd401160b02e4f544a85a9e4f61a8cbe5b077ea0379d411615376a2bd21"},
+    {file = "opentelemetry_instrumentation_fastapi-0.47b0.tar.gz", hash = "sha256:0c7c10b5d971e99a420678ffd16c5b1ea4f0db3b31b62faf305fbb03b4ebee36"},
 ]
 
 [package.dependencies]
 opentelemetry-api = ">=1.12,<2.0"
-opentelemetry-instrumentation = "0.46b0"
-opentelemetry-instrumentation-asgi = "0.46b0"
-opentelemetry-semantic-conventions = "0.46b0"
-opentelemetry-util-http = "0.46b0"
+opentelemetry-instrumentation = "0.47b0"
+opentelemetry-instrumentation-asgi = "0.47b0"
+opentelemetry-semantic-conventions = "0.47b0"
+opentelemetry-util-http = "0.47b0"
 
 [package.extras]
-instruments = ["fastapi (>=0.58,<1.0)"]
+instruments = ["fastapi (>=0.58,<1.0)", "fastapi-slim (>=0.111.0,<0.112.0)"]
 
 [[package]]
 name = "opentelemetry-proto"
-version = "1.25.0"
+version = "1.26.0"
 description = "OpenTelemetry Python Proto"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_proto-1.25.0-py3-none-any.whl", hash = "sha256:f07e3341c78d835d9b86665903b199893befa5e98866f63d22b00d0b7ca4972f"},
-    {file = "opentelemetry_proto-1.25.0.tar.gz", hash = "sha256:35b6ef9dc4a9f7853ecc5006738ad40443701e52c26099e197895cbda8b815a3"},
+    {file = "opentelemetry_proto-1.26.0-py3-none-any.whl", hash = "sha256:6c4d7b4d4d9c88543bcf8c28ae3f8f0448a753dc291c18c5390444c90b76a725"},
+    {file = "opentelemetry_proto-1.26.0.tar.gz", hash = "sha256:c5c18796c0cab3751fc3b98dee53855835e90c0422924b484432ac852d93dc1e"},
 ]
 
 [package.dependencies]
@@ -4483,98 +4392,104 @@ protobuf = ">=3.19,<5.0"
 
 [[package]]
 name = "opentelemetry-sdk"
-version = "1.25.0"
+version = "1.26.0"
 description = "OpenTelemetry Python SDK"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_sdk-1.25.0-py3-none-any.whl", hash = "sha256:d97ff7ec4b351692e9d5a15af570c693b8715ad78b8aafbec5c7100fe966b4c9"},
-    {file = "opentelemetry_sdk-1.25.0.tar.gz", hash = "sha256:ce7fc319c57707ef5bf8b74fb9f8ebdb8bfafbe11898410e0d2a761d08a98ec7"},
+    {file = "opentelemetry_sdk-1.26.0-py3-none-any.whl", hash = "sha256:feb5056a84a88670c041ea0ded9921fca559efec03905dddeb3885525e0af897"},
+    {file = "opentelemetry_sdk-1.26.0.tar.gz", hash = "sha256:c90d2868f8805619535c05562d699e2f4fb1f00dbd55a86dcefca4da6fa02f85"},
 ]
 
 [package.dependencies]
-opentelemetry-api = "1.25.0"
-opentelemetry-semantic-conventions = "0.46b0"
+opentelemetry-api = "1.26.0"
+opentelemetry-semantic-conventions = "0.47b0"
 typing-extensions = ">=3.7.4"
 
 [[package]]
 name = "opentelemetry-semantic-conventions"
-version = "0.46b0"
+version = "0.47b0"
 description = "OpenTelemetry Semantic Conventions"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_semantic_conventions-0.46b0-py3-none-any.whl", hash = "sha256:6daef4ef9fa51d51855d9f8e0ccd3a1bd59e0e545abe99ac6203804e36ab3e07"},
-    {file = "opentelemetry_semantic_conventions-0.46b0.tar.gz", hash = "sha256:fbc982ecbb6a6e90869b15c1673be90bd18c8a56ff1cffc0864e38e2edffaefa"},
+    {file = "opentelemetry_semantic_conventions-0.47b0-py3-none-any.whl", hash = "sha256:4ff9d595b85a59c1c1413f02bba320ce7ea6bf9e2ead2b0913c4395c7bbc1063"},
+    {file = "opentelemetry_semantic_conventions-0.47b0.tar.gz", hash = "sha256:a8d57999bbe3495ffd4d510de26a97dadc1dace53e0275001b2c1b2f67992a7e"},
 ]
 
 [package.dependencies]
-opentelemetry-api = "1.25.0"
+deprecated = ">=1.2.6"
+opentelemetry-api = "1.26.0"
 
 [[package]]
 name = "opentelemetry-util-http"
-version = "0.46b0"
+version = "0.47b0"
 description = "Web util for OpenTelemetry"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_util_http-0.46b0-py3-none-any.whl", hash = "sha256:8dc1949ce63caef08db84ae977fdc1848fe6dc38e6bbaad0ae3e6ecd0d451629"},
-    {file = "opentelemetry_util_http-0.46b0.tar.gz", hash = "sha256:03b6e222642f9c7eae58d9132343e045b50aca9761fcb53709bd2b663571fdf6"},
+    {file = "opentelemetry_util_http-0.47b0-py3-none-any.whl", hash = "sha256:3d3215e09c4a723b12da6d0233a31395aeb2bb33a64d7b15a1500690ba250f19"},
+    {file = "opentelemetry_util_http-0.47b0.tar.gz", hash = "sha256:352a07664c18eef827eb8ddcbd64c64a7284a39dd1655e2f16f577eb046ccb32"},
 ]
 
 [[package]]
 name = "orjson"
-version = "3.10.5"
+version = "3.10.6"
 description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [[package]]
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 [package.dependencies]
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 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
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 fpx = ["olefile"]
 mic = ["olefile"]
 tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"]
@@ -4841,13 +4767,13 @@ xmp = ["defusedxml"]
 
 [[package]]
 name = "pip"
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+version = "24.2"
 description = "The PyPA recommended tool for installing Python packages."
 optional = false
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 [[package]]
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 networkx = ">=2.3,<4.0"
 python-dateutil = ">=2.8,<3.0"
 
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@@ -5343,13 +5279,13 @@ jsonasobj = ">=1.2.1"
 
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+version = "2.9.0"
 description = "JSON Web Token implementation in Python"
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 [package.extras]
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+docs = ["sphinx", "sphinx-rtd-theme", "zope.interface"]
 tests = ["coverage[toml] (==5.0.4)", "pytest (>=6.0.0,<7.0.0)"]
 
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 ]
 
 [package.dependencies]
@@ -5435,6 +5361,7 @@ dnspython = ">=1.16.0,<3.0.0"
 
 [package.extras]
 aws = ["pymongo-auth-aws (>=1.1.0,<2.0.0)"]
+docs = ["furo (==2023.9.10)", "readthedocs-sphinx-search (>=0.3,<1.0)", "sphinx (>=5.3,<8)", "sphinx-rtd-theme (>=2,<3)", "sphinxcontrib-shellcheck (>=1,<2)"]
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 gssapi = ["pykerberos", "winkerberos (>=0.5.0)"]
 ocsp = ["certifi", "cryptography (>=2.5)", "pyopenssl (>=17.2.0)", "requests (<3.0.0)", "service-identity (>=18.1.0)"]
@@ -5494,22 +5421,22 @@ files = [
 
 [[package]]
 name = "pyproject-api"
-version = "1.6.1"
+version = "1.7.1"
 description = "API to interact with the python pyproject.toml based projects"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
-packaging = ">=23.1"
+packaging = ">=24.1"
 tomli = {version = ">=2.0.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
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+docs = ["furo (>=2024.5.6)", "sphinx-autodoc-typehints (>=2.2.1)"]
+testing = ["covdefaults (>=2.3)", "pytest (>=8.2.2)", "pytest-cov (>=5)", "pytest-mock (>=3.14)", "setuptools (>=70.1)"]
 
 [[package]]
 name = "pyproject-hooks"
@@ -5628,13 +5555,13 @@ xml = ["lxml"]
 
 [[package]]
 name = "pytest"
-version = "8.2.2"
+version = "8.3.2"
 description = "pytest: simple powerful testing with Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -5642,7 +5569,7 @@ colorama = {version = "*", markers = "sys_platform == \"win32\""}
 exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""}
 iniconfig = "*"
 packaging = "*"
-pluggy = ">=1.5,<2.0"
+pluggy = ">=1.5,<2"
 tomli = {version = ">=1", markers = "python_version < \"3.11\""}
 
 [package.extras]
@@ -5700,20 +5627,6 @@ files = [
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 ]
 
-[[package]]
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-version = "0.0.9"
-description = "A streaming multipart parser for Python"
-optional = false
-python-versions = ">=3.8"
-files = [
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-
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-
 [[package]]
 name = "python-pptx"
 version = "0.6.23"
@@ -6111,90 +6024,90 @@ rpds-py = ">=0.7.0"
 
 [[package]]
 name = "regex"
-version = "2024.5.15"
+version = "2024.7.24"
 description = "Alternative regular expression module, to replace re."
 optional = false
 python-versions = ">=3.8"
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 [[package]]
@@ -6337,110 +6250,114 @@ jupyter = ["ipywidgets (>=7.5.1,<9)"]
 
 [[package]]
 name = "rpds-py"
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 ]
 
 [package.dependencies]
@@ -6722,8 +6639,8 @@ threadpoolctl = ">=3.1.0"
 
 [package.extras]
 benchmark = ["matplotlib (>=3.3.4)", "memory_profiler (>=0.57.0)", "pandas (>=1.1.5)"]
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+build = ["cython (>=3.0.10)", "meson-python (>=0.16.0)", "numpy (>=1.19.5)", "scipy (>=1.6.0)"]
+docs = ["Pillow (>=7.1.2)", "matplotlib (>=3.3.4)", "memory_profiler (>=0.57.0)", "numpydoc (>=1.2.0)", "pandas (>=1.1.5)", "plotly (>=5.14.0)", "polars (>=0.20.23)", "pooch (>=1.6.0)", "pydata-sphinx-theme (>=0.15.3)", "scikit-image (>=0.17.2)", "seaborn (>=0.9.0)", "sphinx (>=7.3.7)", "sphinx-copybutton (>=0.5.2)", "sphinx-design (>=0.5.0)", "sphinx-gallery (>=0.16.0)", "sphinx-prompt (>=1.4.0)", "sphinx-remove-toctrees (>=1.0.0.post1)", "sphinxcontrib-sass (>=0.3.4)", "sphinxext-opengraph (>=0.9.1)"]
 examples = ["matplotlib (>=3.3.4)", "pandas (>=1.1.5)", "plotly (>=5.14.0)", "pooch (>=1.6.0)", "scikit-image (>=0.17.2)", "seaborn (>=0.9.0)"]
 install = ["joblib (>=1.2.0)", "numpy (>=1.19.5)", "scipy (>=1.6.0)", "threadpoolctl (>=3.1.0)"]
 maintenance = ["conda-lock (==2.5.6)"]
@@ -6794,21 +6711,22 @@ stats = ["scipy (>=1.3)", "statsmodels (>=0.10)"]
 
 [[package]]
 name = "selenium"
-version = "4.21.0"
-description = ""
+version = "4.23.1"
+description = "Official Python bindings for Selenium WebDriver"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
 certifi = ">=2021.10.8"
 trio = ">=0.17,<1.0"
 trio-websocket = ">=0.9,<1.0"
-typing_extensions = ">=4.9.0"
+typing_extensions = ">=4.9,<5.0"
 urllib3 = {version = ">=1.26,<3", extras = ["socks"]}
+websocket-client = ">=1.8,<2.0"
 
 [[package]]
 name = "semsql"
@@ -6869,18 +6787,19 @@ train = ["accelerate (>=0.20.3)", "datasets"]
 
 [[package]]
 name = "setuptools"
-version = "70.0.0"
+version = "72.1.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
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+core = ["importlib-metadata (>=6)", "importlib-resources (>=5.10.2)", "jaraco.text (>=3.7)", "more-itertools (>=8.8)", "ordered-set (>=3.1.1)", "packaging (>=24)", "platformdirs (>=2.6.2)", "tomli (>=2.0.1)", "wheel (>=0.43.0)"]
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 [[package]]
 name = "shellingham"
@@ -7031,27 +6950,27 @@ whisper-local = ["openai-whisper", "soundfile"]
 
 [[package]]
 name = "sphinx"
-version = "7.3.7"
+version = "7.4.7"
 description = "Python documentation generator"
 optional = false
 python-versions = ">=3.9"
 files = [
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 [package.dependencies]
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-babel = ">=2.9"
-colorama = {version = ">=0.4.5", markers = "sys_platform == \"win32\""}
-docutils = ">=0.18.1,<0.22"
+babel = ">=2.13"
+colorama = {version = ">=0.4.6", markers = "sys_platform == \"win32\""}
+docutils = ">=0.20,<0.22"
 imagesize = ">=1.3"
-importlib-metadata = {version = ">=4.8", markers = "python_version < \"3.10\""}
-Jinja2 = ">=3.0"
-packaging = ">=21.0"
-Pygments = ">=2.14"
-requests = ">=2.25.0"
-snowballstemmer = ">=2.0"
+importlib-metadata = {version = ">=6.0", markers = "python_version < \"3.10\""}
+Jinja2 = ">=3.1"
+packaging = ">=23.0"
+Pygments = ">=2.17"
+requests = ">=2.30.0"
+snowballstemmer = ">=2.2"
 sphinxcontrib-applehelp = "*"
 sphinxcontrib-devhelp = "*"
 sphinxcontrib-htmlhelp = ">=2.0.0"
@@ -7063,18 +6982,18 @@ tomli = {version = ">=2", markers = "python_version < \"3.11\""}
 
 [package.extras]
 docs = ["sphinxcontrib-websupport"]
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-test = ["cython (>=3.0)", "defusedxml (>=0.7.1)", "pytest (>=6.0)", "setuptools (>=67.0)"]
+lint = ["flake8 (>=6.0)", "importlib-metadata (>=6.0)", "mypy (==1.10.1)", "pytest (>=6.0)", "ruff (==0.5.2)", "sphinx-lint (>=0.9)", "tomli (>=2)", "types-docutils (==0.21.0.20240711)", "types-requests (>=2.30.0)"]
+test = ["cython (>=3.0)", "defusedxml (>=0.7.1)", "pytest (>=8.0)", "setuptools (>=70.0)", "typing_extensions (>=4.9)"]
 
 [[package]]
 name = "sphinx-autodoc-typehints"
-version = "2.1.1"
+version = "2.2.3"
 description = "Type hints (PEP 484) support for the Sphinx autodoc extension"
 optional = false
 python-versions = ">=3.9"
 files = [
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+    {file = "sphinx_autodoc_typehints-2.2.3-py3-none-any.whl", hash = "sha256:b7058e8c5831e5598afca1a78fda0695d3291388d954464a6e480c36198680c0"},
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 ]
 
 [package.dependencies]
@@ -7158,49 +7077,49 @@ dev = ["bump2version", "sphinxcontrib-httpdomain", "transifex-client", "wheel"]
 
 [[package]]
 name = "sphinxcontrib-applehelp"
-version = "1.0.8"
+version = "2.0.0"
 description = "sphinxcontrib-applehelp is a Sphinx extension which outputs Apple help books"
 optional = false
 python-versions = ">=3.9"
 files = [
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+    {file = "sphinxcontrib_applehelp-2.0.0-py3-none-any.whl", hash = "sha256:4cd3f0ec4ac5dd9c17ec65e9ab272c9b867ea77425228e68ecf08d6b28ddbdb5"},
+    {file = "sphinxcontrib_applehelp-2.0.0.tar.gz", hash = "sha256:2f29ef331735ce958efa4734873f084941970894c6090408b079c61b2e1c06d1"},
 ]
 
 [package.extras]
-lint = ["docutils-stubs", "flake8", "mypy"]
+lint = ["mypy", "ruff (==0.5.5)", "types-docutils"]
 standalone = ["Sphinx (>=5)"]
 test = ["pytest"]
 
 [[package]]
 name = "sphinxcontrib-devhelp"
-version = "1.0.6"
+version = "2.0.0"
 description = "sphinxcontrib-devhelp is a sphinx extension which outputs Devhelp documents"
 optional = false
 python-versions = ">=3.9"
 files = [
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+    {file = "sphinxcontrib_devhelp-2.0.0-py3-none-any.whl", hash = "sha256:aefb8b83854e4b0998877524d1029fd3e6879210422ee3780459e28a1f03a8a2"},
+    {file = "sphinxcontrib_devhelp-2.0.0.tar.gz", hash = "sha256:411f5d96d445d1d73bb5d52133377b4248ec79db5c793ce7dbe59e074b4dd1ad"},
 ]
 
 [package.extras]
-lint = ["docutils-stubs", "flake8", "mypy"]
+lint = ["mypy", "ruff (==0.5.5)", "types-docutils"]
 standalone = ["Sphinx (>=5)"]
 test = ["pytest"]
 
 [[package]]
 name = "sphinxcontrib-htmlhelp"
-version = "2.0.5"
+version = "2.1.0"
 description = "sphinxcontrib-htmlhelp is a sphinx extension which renders HTML help files"
 optional = false
 python-versions = ">=3.9"
 files = [
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 typing-extensions = ">=4.6.0"
 
 [package.extras]
@@ -7433,13 +7352,13 @@ test = ["black", "mypy", "pytest", "ruff"]
 
 [[package]]
 name = "sqlite-utils"
-version = "3.36"
+version = "3.37"
 description = "CLI tool and Python library for manipulating SQLite databases"
 optional = false
-python-versions = ">=3.7"
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 [package.dependencies]
@@ -7454,18 +7373,18 @@ tabulate = "*"
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 flake8 = ["flake8"]
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-test = ["black", "cogapp", "hypothesis", "pytest"]
+test = ["black (>=24.1.1)", "cogapp", "hypothesis", "pytest"]
 tui = ["trogon"]
 
 [[package]]
 name = "sssom"
-version = "0.4.9"
+version = "0.4.11"
 description = "Operations on SSSOM mapping tables"
 optional = false
 python-versions = "<4.0,>=3.8"
 files = [
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 [package.dependencies]
@@ -7537,13 +7456,13 @@ full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart (>=0.0.7
 
 [[package]]
 name = "streamlit"
-version = "1.35.0"
+version = "1.37.0"
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 optional = false
 python-versions = "!=3.9.7,>=3.8"
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 [package.dependencies]
@@ -7552,11 +7471,11 @@ blinker = ">=1.0.0,<2"
 cachetools = ">=4.0,<6"
 click = ">=7.0,<9"
 gitpython = ">=3.0.7,<3.1.19 || >3.1.19,<4"
-numpy = ">=1.19.3,<2"
-packaging = ">=16.8,<25"
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+packaging = ">=20,<25"
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 pillow = ">=7.1.0,<11"
-protobuf = ">=3.20,<5"
+protobuf = ">=3.20,<6"
 pyarrow = ">=7.0"
 pydeck = ">=0.8.0b4,<1"
 requests = ">=2.27,<3"
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 tornado = ">=6.0.3,<7"
 typing-extensions = ">=4.3.0,<5"
-watchdog = {version = ">=2.1.5", markers = "platform_system != \"Darwin\""}
+watchdog = {version = ">=2.1.5,<5", markers = "platform_system != \"Darwin\""}
 
 [package.extras]
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 [[package]]
 name = "sympy"
-version = "1.12.1"
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 python-versions = ">=3.8"
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 [package.dependencies]
-mpmath = ">=1.1.0,<1.4.0"
+mpmath = ">=1.1.0,<1.4"
+
+[package.extras]
+dev = ["hypothesis (>=6.70.0)", "pytest (>=7.1.0)"]
 
 [[package]]
 name = "tabulate"
@@ -7598,28 +7520,15 @@ files = [
 [package.extras]
 widechars = ["wcwidth"]
 
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 [[package]]
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@@ -7901,44 +7810,43 @@ files = [
 
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+    {file = "torch-2.4.0-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:cc30457ea5489c62747d3306438af00c606b509d78822a88f804202ba63111ed"},
+    {file = "torch-2.4.0-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:a046491aaf96d1215e65e1fa85911ef2ded6d49ea34c8df4d0638879f2402eef"},
+    {file = "torch-2.4.0-cp38-cp38-win_amd64.whl", hash = "sha256:688eec9240f3ce775f22e1e1a5ab9894f3d5fe60f3f586deb7dbd23a46a83916"},
+    {file = "torch-2.4.0-cp38-none-macosx_11_0_arm64.whl", hash = "sha256:3af4de2a618fb065e78404c4ba27a818a7b7957eaeff28c6c66ce7fb504b68b8"},
+    {file = "torch-2.4.0-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:618808d3f610d5f180e47a697d4ec90b810953bb1e020f424b2ac7fb0884b545"},
+    {file = "torch-2.4.0-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:ed765d232d23566052ba83632ec73a4fccde00b4c94ad45d63b471b09d63b7a7"},
+    {file = "torch-2.4.0-cp39-cp39-win_amd64.whl", hash = "sha256:a2feb98ac470109472fb10dfef38622a7ee08482a16c357863ebc7bc7db7c8f7"},
+    {file = "torch-2.4.0-cp39-none-macosx_11_0_arm64.whl", hash = "sha256:8940fc8b97a4c61fdb5d46a368f21f4a3a562a17879e932eb51a5ec62310cb31"},
 ]
 
 [package.dependencies]
 filelock = "*"
 fsspec = "*"
 jinja2 = "*"
-mkl = {version = ">=2021.1.1,<=2021.4.0", markers = "platform_system == \"Windows\""}
 networkx = "*"
 nvidia-cublas-cu12 = {version = "12.1.3.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cuda-cupti-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cuda-nvrtc-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cuda-runtime-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cudnn-cu12 = {version = "8.9.2.26", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cudnn-cu12 = {version = "9.1.0.70", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cufft-cu12 = {version = "11.0.2.54", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-curand-cu12 = {version = "10.3.2.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cusolver-cu12 = {version = "11.4.5.107", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
@@ -7946,12 +7854,12 @@ nvidia-cusparse-cu12 = {version = "12.1.0.106", markers = "platform_system == \"
 nvidia-nccl-cu12 = {version = "2.20.5", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-nvtx-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 sympy = "*"
-triton = {version = "2.3.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.12\""}
+triton = {version = "3.0.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.13\""}
 typing-extensions = ">=4.8.0"
 
 [package.extras]
 opt-einsum = ["opt-einsum (>=3.3)"]
-optree = ["optree (>=0.9.1)"]
+optree = ["optree (>=0.11.0)"]
 
 [[package]]
 name = "tornado"
@@ -7975,30 +7883,30 @@ files = [
 
 [[package]]
 name = "tox"
-version = "4.15.1"
+version = "4.16.0"
 description = "tox is a generic virtualenv management and test command line tool"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "tox-4.15.1-py3-none-any.whl", hash = "sha256:f00a5dc4222b358e69694e47e3da0227ac41253509bca9f45aa8f012053e8d9d"},
-    {file = "tox-4.15.1.tar.gz", hash = "sha256:53a092527d65e873e39213ebd4bd027a64623320b6b0326136384213f95b7076"},
+    {file = "tox-4.16.0-py3-none-any.whl", hash = "sha256:61e101061b977b46cf00093d4319438055290ad0009f84497a07bf2d2d7a06d0"},
+    {file = "tox-4.16.0.tar.gz", hash = "sha256:43499656f9949edb681c0f907f86fbfee98677af9919d8b11ae5ad77cb800748"},
 ]
 
 [package.dependencies]
-cachetools = ">=5.3.2"
+cachetools = ">=5.3.3"
 chardet = ">=5.2"
 colorama = ">=0.4.6"
-filelock = ">=3.13.1"
-packaging = ">=23.2"
-platformdirs = ">=4.1"
-pluggy = ">=1.3"
-pyproject-api = ">=1.6.1"
+filelock = ">=3.15.4"
+packaging = ">=24.1"
+platformdirs = ">=4.2.2"
+pluggy = ">=1.5"
+pyproject-api = ">=1.7.1"
 tomli = {version = ">=2.0.1", markers = "python_version < \"3.11\""}
-virtualenv = ">=20.25"
+virtualenv = ">=20.26.3"
 
 [package.extras]
-docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-argparse-cli (>=1.11.1)", "sphinx-autodoc-typehints (>=1.25.2)", "sphinx-copybutton (>=0.5.2)", "sphinx-inline-tabs (>=2023.4.21)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.11)"]
-testing = ["build[virtualenv] (>=1.0.3)", "covdefaults (>=2.3)", "detect-test-pollution (>=1.2)", "devpi-process (>=1)", "diff-cover (>=8.0.2)", "distlib (>=0.3.8)", "flaky (>=3.7)", "hatch-vcs (>=0.4)", "hatchling (>=1.21)", "psutil (>=5.9.7)", "pytest (>=7.4.4)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-xdist (>=3.5)", "re-assert (>=1.1)", "time-machine (>=2.13)", "wheel (>=0.42)"]
+docs = ["furo (>=2024.5.6)", "sphinx (>=7.3.7)", "sphinx-argparse-cli (>=1.16)", "sphinx-autodoc-typehints (>=2.2.2)", "sphinx-copybutton (>=0.5.2)", "sphinx-inline-tabs (>=2023.4.21)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.11)"]
+testing = ["build[virtualenv] (>=1.2.1)", "covdefaults (>=2.3)", "detect-test-pollution (>=1.2)", "devpi-process (>=1)", "diff-cover (>=9.1)", "distlib (>=0.3.8)", "flaky (>=3.8.1)", "hatch-vcs (>=0.4)", "hatchling (>=1.25)", "psutil (>=6)", "pytest (>=8.2.2)", "pytest-cov (>=5)", "pytest-mock (>=3.14)", "pytest-xdist (>=3.6.1)", "re-assert (>=1.1)", "setuptools (>=70.2)", "time-machine (>=2.14.2)", "wheel (>=0.43)"]
 
 [[package]]
 name = "tqdm"
@@ -8037,18 +7945,18 @@ test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,
 
 [[package]]
 name = "transformers"
-version = "4.41.2"
+version = "4.43.3"
 description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "transformers-4.41.2-py3-none-any.whl", hash = "sha256:05555d20e43f808de1ef211ab64803cdb513170cef70d29a888b589caebefc67"},
-    {file = "transformers-4.41.2.tar.gz", hash = "sha256:80a4db216533d573e9cc7388646c31ed9480918feb7c55eb211249cb23567f87"},
+    {file = "transformers-4.43.3-py3-none-any.whl", hash = "sha256:6552beada5d826c25ff9b79139d237ab9050c6ea96b73d7fd2f8a8ba23ee76a4"},
+    {file = "transformers-4.43.3.tar.gz", hash = "sha256:820c5b192bb1bf47250802901a8f0bf581e06b8fded89179d4ef08a1e903ee1c"},
 ]
 
 [package.dependencies]
 filelock = "*"
-huggingface-hub = ">=0.23.0,<1.0"
+huggingface-hub = ">=0.23.2,<1.0"
 numpy = ">=1.17"
 packaging = ">=20.0"
 pyyaml = ">=5.1"
@@ -8061,14 +7969,15 @@ tqdm = ">=4.27"
 [package.extras]
 accelerate = ["accelerate (>=0.21.0)"]
 agents = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch"]
-all = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timm", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision"]
+all = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timm (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision"]
 audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
+benchmark = ["optimum-benchmark (>=0.2.0)"]
 codecarbon = ["codecarbon (==1.2.0)"]
 deepspeed = ["accelerate (>=0.21.0)", "deepspeed (>=0.9.3)"]
-deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.21.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "optuna", "parameterized", "protobuf", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
-dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "decord (==0.6.0)", "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)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "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", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
-dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.19,<0.20)", "urllib3 (<2.0.0)"]
-dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "librosa", "nltk", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "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", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
+deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.21.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "optuna", "parameterized", "protobuf", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
+dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "decord (==0.6.0)", "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)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "librosa", "nltk", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "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 (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
+dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "librosa", "nltk", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.19,<0.20)", "urllib3 (<2.0.0)"]
+dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "librosa", "nltk", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "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 (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "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"]
@@ -8079,37 +7988,38 @@ natten = ["natten (>=0.14.6,<0.15.0)"]
 onnx = ["onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "tf2onnx"]
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-    {file = "ujson-5.10.0.tar.gz", hash = "sha256:b3cd8f3c5d8c7738257f1018880444f7b7d9b66232c64649f562d7ba86ad4bc1"},
-]
-
 [[package]]
 name = "uri-template"
 version = "1.3.0"
@@ -8358,13 +8185,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "uvicorn"
-version = "0.30.1"
+version = "0.30.5"
 description = "The lightning-fast ASGI server."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "uvicorn-0.30.1-py3-none-any.whl", hash = "sha256:cd17daa7f3b9d7a24de3617820e634d0933b69eed8e33a516071174427238c81"},
-    {file = "uvicorn-0.30.1.tar.gz", hash = "sha256:d46cd8e0fd80240baffbcd9ec1012a712938754afcf81bce56c024c1656aece8"},
+    {file = "uvicorn-0.30.5-py3-none-any.whl", hash = "sha256:b2d86de274726e9878188fa07576c9ceeff90a839e2b6e25c917fe05f5a6c835"},
+    {file = "uvicorn-0.30.5.tar.gz", hash = "sha256:ac6fdbd4425c5fd17a9fe39daf4d4d075da6fdc80f653e5894cdc2fd98752bee"},
 ]
 
 [package.dependencies]
@@ -8428,15 +8255,18 @@ test = ["Cython (>=0.29.36,<0.30.0)", "aiohttp (==3.9.0b0)", "aiohttp (>=3.8.1)"
 
 [[package]]
 name = "validators"
-version = "0.28.3"
+version = "0.33.0"
 description = "Python Data Validation for Humans™"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "validators-0.28.3-py3-none-any.whl", hash = "sha256:53cafa854f13850156259d9cc479b864ee901f6a96e6b109e6fc33f98f37d99f"},
-    {file = "validators-0.28.3.tar.gz", hash = "sha256:c6c79840bcde9ba77b19f6218f7738188115e27830cbaff43264bc4ed24c429d"},
+    {file = "validators-0.33.0-py3-none-any.whl", hash = "sha256:134b586a98894f8139865953899fc2daeb3d0c35569552c5518f089ae43ed075"},
+    {file = "validators-0.33.0.tar.gz", hash = "sha256:535867e9617f0100e676a1257ba1e206b9bfd847ddc171e4d44811f07ff0bfbf"},
 ]
 
+[package.extras]
+crypto-eth-addresses = ["eth-hash[pycryptodome] (>=0.7.0)"]
+
 [[package]]
 name = "venomx"
 version = "0.1.1"
@@ -8456,13 +8286,13 @@ pyarrow = ">=15.0.0,<16.0.0"
 
 [[package]]
 name = "virtualenv"
-version = "20.26.2"
+version = "20.26.3"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "virtualenv-20.26.2-py3-none-any.whl", hash = "sha256:a624db5e94f01ad993d476b9ee5346fdf7b9de43ccaee0e0197012dc838a0e9b"},
-    {file = "virtualenv-20.26.2.tar.gz", hash = "sha256:82bf0f4eebbb78d36ddaee0283d43fe5736b53880b8a8cdcd37390a07ac3741c"},
+    {file = "virtualenv-20.26.3-py3-none-any.whl", hash = "sha256:8cc4a31139e796e9a7de2cd5cf2489de1217193116a8fd42328f1bd65f434589"},
+    {file = "virtualenv-20.26.3.tar.gz", hash = "sha256:4c43a2a236279d9ea36a0d76f98d84bd6ca94ac4e0f4a3b9d46d05e10fea542a"},
 ]
 
 [package.dependencies]
@@ -8917,4 +8747,4 @@ docs = []
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9, !=3.9.7"
-content-hash = "c6abf7d9411ef2dc271eea7a0ac1d205bb675a06d5b6f525ce3c396f79920b86"
+content-hash = "42e7eab0267544c32debd26d62c6791e4ff3f954d6d2eebe14e4aa6b06b8a211"
diff --git a/pyproject.toml b/pyproject.toml
index b9903c6..81918c6 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -42,7 +42,7 @@ textract = "1.5.0"
 jsonpath-ng = "^1.5.3"
 pygithub = "^1.59.1"
 jsonlines = "*"
-llm = "^0.14"
+llm = "^0.15"
 llm-gpt4all = "^0.1.1"
 gspread = "^5.10.0"
 defusedxml = "^0.7.1"
@@ -50,6 +50,7 @@ click-default-group = "^1.2.4"
 venomx = "^0.1.1"
 duckdb = "^1.0.0"
 python-dotenv = "^1.0.1"
+protobuf = "3.20.0"
 
 [tool.poetry.dev-dependencies]
 pytest = ">=7.1.2"
@@ -75,6 +76,7 @@ myst-parser = {version = ">=0.18.1"}
 
 [tool.poetry.scripts]
 curategpt = "curate_gpt.cli:main"
+gocampr = "curate_gpt.adhoc.gocam_predictor:main"
 
 [tool.poetry.extras]
 docs = [
diff --git a/src/curate_gpt/adhoc/gocam_predictor.py b/src/curate_gpt/adhoc/gocam_predictor.py
index ee51d15..4e73f3f 100644
--- a/src/curate_gpt/adhoc/gocam_predictor.py
+++ b/src/curate_gpt/adhoc/gocam_predictor.py
@@ -1,233 +1,22 @@
 import json
 import logging
 import sys
-from copy import copy, deepcopy
+from copy import deepcopy
 from dataclasses import dataclass, field
-from typing import Any, Dict, List, Optional, Union
+from typing import Dict, Any
 
 import click
 import yaml
-from openai import BaseModel
+from curate_gpt.utils.eval_utils import Outcome, score_prediction
 
 from curate_gpt import BasicExtractor, DBAdapter
 from curate_gpt.store import get_store
+from curate_gpt.utils.llm_utils import query_model
 from curate_gpt.wrappers.bio.gocam_wrapper import GOCAMWrapper
 
 logger = logging.getLogger(__name__)
 
 
-class Outcome(BaseModel):
-    prediction: Union[Dict[str, Any], List[Dict[str, Any]]] = {}
-    expected: Union[Dict[str, Any], List[Dict[str, Any]]] = {}
-    parameters: Dict[str, Any] = {}
-    tp: int = 0
-    tn: int = 0
-    fp: int = 0
-    fn: int = 0
-
-    precision: Optional[float] = None
-    recall: Optional[float] = None
-    f1: Optional[float] = None
-
-    by_field: Dict[str, int] = {}
-    ixn_by_field: Dict[str, List[str]] = {}
-
-    def calculate_metrics(self):
-        self.precision = self.tp / (self.tp + self.fp) if self.tp + self.fp > 0 else 0
-        self.recall = self.tp / (self.tp + self.fn) if self.tp + self.fn > 0 else 0
-        self.f1 = (
-            2 * self.precision * self.recall / (self.precision + self.recall)
-            if self.precision + self.recall > 0
-            else 0
-        )
-
-    def append_outcomes(self, outcomes: List["Outcome"]) -> None:
-        for sub_outcome in outcomes:
-            self.tp += sub_outcome.tp
-            self.fp += sub_outcome.fp
-            self.fn += sub_outcome.fn
-            for key, value in sub_outcome.by_field.items():
-                self.by_field[key] = self.by_field.get(key, 0) + value
-            for key, value in sub_outcome.ixn_by_field.items():
-                curr = set(self.ixn_by_field.get(key, []))
-                self.ixn_by_field[key] = list(curr.union(value))
-        self.calculate_metrics()
-
-    def flatten(self) -> Dict[str, Any]:
-        obj = self.model_dump()
-        for k, v in copy(obj).items():
-            if k == "parameters":
-                obj.update(v)
-                del obj[k]
-            elif isinstance(v, dict):
-                del obj[k]
-            elif isinstance(v, list):
-                obj[k] = [x for x in v if x]
-        return obj
-
-
-def score_prediction(
-    predicted: Union[Dict, List], expected: Union[Dict, List], exclude: List = None
-) -> Outcome:
-    """
-    Score the predicted activity.
-
-    >>> outcome = score_prediction({"x": 1}, {"x": 1})
-    >>> outcome.tp
-    1
-
-    >>> outcome = score_prediction([{"x": 1}], {"x": 1})
-    >>> outcome.tp
-    1
-
-
-    >>> outcome = score_prediction({"x": 1}, {"x": 2})
-    >>> outcome.tp
-    0
-    >>> outcome.recall
-    0.0
-
-    >>> outcome = score_prediction({"x": 1, "y": 2}, {"x": 1})
-    >>> outcome.tp
-    1
-    >>> outcome.fp
-    1
-
-    >>> outcome = score_prediction([{"x": 1}, {"y": 1}], {"x": 1})
-    >>> outcome.tp
-    1
-    >>> outcome.fp
-    1
-
-
-    :param predicted: The predicted activity
-    :param expected: The expected activity
-    :return: The score
-    """
-    if exclude is None:
-        exclude = ["reference_title", "reference"]
-    if isinstance(expected, list) or isinstance(predicted, list):
-        if isinstance(expected, dict):
-            expected = [expected]
-        if isinstance(predicted, dict):
-            predicted = [predicted]
-        outcomes = best_matches(predicted, expected)
-        outcome = Outcome(prediction=predicted, expected=expected)
-        for sub_outcome in outcomes:
-            outcome.tp += sub_outcome.tp
-            outcome.fp += sub_outcome.fp
-            outcome.fn += sub_outcome.fn
-            for key, value in sub_outcome.by_field.items():
-                outcome.by_field[key] = outcome.by_field.get(key, 0) + value
-            for key, value in sub_outcome.ixn_by_field.items():
-                outcome.ixn_by_field[key] = list(
-                    set(outcome.ixn_by_field.get(key, [])).union(value)
-                )
-        outcome.calculate_metrics()
-        return outcome
-    outcome = Outcome(prediction=predicted, expected=expected)
-    all_keys = set(predicted.keys()).union(expected.keys()).difference(exclude)
-    for key in all_keys:
-        if key in predicted and key in expected:
-            if key == "relationships":
-                pred_rels = predicted[key]
-                exp_rels = expected[key]
-                sub_outcomes = best_matches(pred_rels, exp_rels)
-                n_tps = 0
-                ixn = set()
-                for sub_outcome in sub_outcomes:
-                    outcome.tp += sub_outcome.tp
-                    outcome.fp += sub_outcome.fp
-                    outcome.fn += sub_outcome.fn
-                    n_tps += sub_outcome.tp
-                    if sub_outcome.precision == 1.0:
-                        ixn = ixn.union({str(predicted[key])})
-                outcome.by_field[key] = outcome.by_field.get(key, 0) + n_tps
-                outcome.ixn_by_field[key] = list(set(outcome.ixn_by_field.get(key, [])).union(ixn))
-                continue
-            if predicted[key] == expected[key]:
-                outcome.tp += 1
-                outcome.by_field[key] = outcome.by_field.get(key, 0) + 1
-                outcome.ixn_by_field[key] = list(
-                    set(outcome.ixn_by_field.get(key, [])).union({predicted[key]})
-                )
-            else:
-                outcome.fp += 1
-                outcome.fn += 1
-        elif key in predicted:
-            outcome.fp += 1
-        else:
-            outcome.fn += 1
-    outcome.calculate_metrics()
-    return outcome
-
-
-def best_matches(pred_rels, exp_rels) -> List[Outcome]:
-    """
-    Find the best matching pairs of relationships.
-
-    Example:
-
-    >>> outcomes = best_matches([], [])
-    >>> len(outcomes)
-    1
-    >>> outcome = outcomes[0]
-    >>> (outcome.tp, outcome.fp, outcome.fn)
-    (0, 0, 0)
-    >>> best_matches([{"x:": 1}], [])[0].precision
-    0.0
-    >>> outcome = best_matches([{"x": 1}], [{"x": 1}])[0]
-    >>> outcome.precision
-    1.0
-    >>> outcome = best_matches([{"x": 1}], [{"y": 1}])[0]
-    >>> outcome.precision
-    0.0
-    >>> pred_rels = [{"x":1}, {"y": 2}, {"z": 3}]
-    >>> exp_rels = [{"y":2}, {"x": 1}, {"z": 3}]
-    >>> outcomes = best_matches(pred_rels, exp_rels)
-    >>> [o.precision for o in outcomes]
-    [1.0, 1.0, 1.0]
-    >>> exp_rels.append({"z": 4})
-    >>> outcomes = best_matches(pred_rels, exp_rels)
-    >>> sorted([o.precision for o in outcomes])
-    [0.0, 1.0, 1.0, 1.0]
-
-    """
-    import numpy as np
-
-    if not pred_rels:
-        pred_rels = [{}]
-    if not exp_rels:
-        exp_rels = [{}]
-
-    # Create a matrix to store the scores
-    outcome_matrix = np.zeros((len(pred_rels), len(exp_rels)), dtype=object)
-    outcome_ix = {}
-
-    # Calculate the scores for each pair of pred_rel and exp_rel
-    for i, pred_rel in enumerate(pred_rels):
-        for j, exp_rel in enumerate(exp_rels):
-            sub_outcome = score_prediction(pred_rel, exp_rel)
-            outcome_matrix[i, j] = sub_outcome.tp
-            outcome_ix[(i, j)] = sub_outcome
-
-    # Find the best matching pairs
-    outcomes = []
-    max_row_indices = np.argmax(outcome_matrix, axis=1)
-    max_col_indices = np.argmax(outcome_matrix, axis=0)
-    best = []
-    for i, _pred_rel in enumerate(pred_rels):
-        best_j = max_row_indices[i]
-        best.append((i, best_j))
-        outcomes.append(outcome_ix[(i, best_j)])
-    for j, _exp_rel in enumerate(exp_rels):
-        best_i = max_col_indices[j]
-        if (best_i, j) not in best:
-            best.append((best_i, j))
-            outcomes.append(outcome_ix[(best_i, j)])
-    return outcomes
-
-
 @dataclass
 class GOCAMPredictor:
 
@@ -238,7 +27,7 @@ class GOCAMPredictor:
     model_name: str = field(default="gpt-4o")
     extractor: BasicExtractor = None
     include_standard_annotations: bool = False
-    gocam_wrapper: GOCAMWrapper = field(default=GOCAMWrapper())
+    gocam_wrapper: GOCAMWrapper = field(default_factory=lambda: GOCAMWrapper())
     strict: bool = field(default=False)
 
     def __post_init__(self):
@@ -255,11 +44,10 @@ def gocam_by_id(self, id: str) -> Dict[str, Any]:
         #    raise ValueError(f"GO-CAM model not found: {id}")
         # return objs[0][0]
 
-    def predict(
-        self, gocam: Dict[str, Any], stub: Dict[str, Any], num_examples=0
-    ) -> Dict[str, Any]:
+    def predict_activity_unit(self, gocam: Dict[str, Any], stub: Dict[str, Any], num_examples=0) -> Dict[str, Any]:
         """
         Predict the missing activity in a GO-CAM model.
+
         :param gocam: The GO-CAM model
         :param stub: The stub to fill in
         :param num_examples: The number of examples to generate
@@ -327,7 +115,8 @@ def predict(
         if self.model_name.startswith("gemini"):
             response = model.prompt(prompt=system + "\n===\n" + prompt)
         else:
-            response = model.prompt(prompt=prompt, system=system)
+            response = query_model(model, prompt=prompt, system=system)
+            # response = model.prompt(prompt=prompt, system=system)
         text = response.text()
         toks = text.split("```")
         if len(toks) < 3:
@@ -435,18 +224,26 @@ def main(verbose: int, quiet: bool):
     help="Include standard annotations",
 )
 @click.option("--prior-results-file", help="Previous results")
-def predict(
-    gocam_id,
-    pmid,
-    model_name,
-    database_type,
-    database_path,
-    collection_name,
-    num_examples,
-    output,
-    include_standard_annotations,
-    prior_results_file,
-):
+def predict(gocam_id, pmid, model_name, database_type, database_path, collection_name, num_examples, output, include_standard_annotations, prior_results_file):
+    """
+    Predict GO-CAMs.
+
+    Example:
+
+        gcpr -v  predict -N 5 --model-name claude-3-opus  -o results/gocam-run-claude3-opus-N5-run1.yaml
+
+    We try and defend against API failures, e.g. implementing exponential backoff, but there is still
+    potential for runs to fail, so we allow `--prior-results-file` to start off where we left off.
+
+    Example (initial run):
+
+        gcpr -v  predict -N 5 -o results/gocam-run-N5-run1.yaml
+
+    After failure:
+
+        gcpr -v  predict -N 5 --prior-results-file results/gocam-run-N5-run1.yaml -o results/gocam-run-N5-run1.yaml
+
+    """
     already_done = []
     if prior_results_file:
         with open(prior_results_file, "r", encoding="utf-8") as f:
@@ -456,13 +253,12 @@ def predict(
         output_file = open(output, "w", encoding="utf-8")
     else:
         output_file = sys.stdout
-    predictor = GOCAMPredictor(
-        database_type=database_type,
-        database_path=database_path,
-        collection_name=collection_name,
-        model_name=model_name,
-        include_standard_annotations=include_standard_annotations,
-    )
+    predictor = GOCAMPredictor(database_type=database_type,
+                               database_path=database_path,
+                               collection_name=collection_name,
+                               model_name=model_name,
+                               include_standard_annotations=include_standard_annotations)
+    # set the list of GO-CAMs to predict; may be a specified singleton or ALL go-cams
     if gocam_id:
         gocam_ids = [gocam_id]
     else:
@@ -489,9 +285,8 @@ def predict(
         main_outcome = Outcome(prediction=[], expected=[])
         for pmid in pmids:
             refs = [a["reference"] for a in test_gocam["activities"]]
-            test_gocam["activities"] = [
-                a for a in original_gocam["activities"] if a["reference"] != pmid
-            ]
+            # the gocam model used here is simplified in that each activity has a single ref
+            test_gocam["activities"] = [a for a in original_gocam["activities"] if a["reference"] != pmid]
             expected = [a for a in original_gocam["activities"] if a["reference"] == pmid]
             if not expected:
                 raise ValueError(
@@ -499,7 +294,11 @@ def predict(
                 )
             if len(test_gocam["activities"]) >= len(original_gocam["activities"]):
                 raise ValueError(f"Invalid number of activities in GO-CAM model {gocam_id}")
-            result = predictor.predict(test_gocam, {"reference": pmid}, num_examples=num_examples)
+            try:
+                result = predictor.predict_activity_unit(test_gocam, {"reference": pmid}, num_examples=num_examples)
+            except Exception as e:
+                logger.error(f"Encountered error: {e}")
+                continue
             print("## PREDICTION")
             print(yaml.dump(result, sort_keys=False))
             print("## EXPECTED")
@@ -511,6 +310,7 @@ def predict(
                 "pmid": pmid,
                 "num_examples": num_examples,
                 "model_name": predictor.model_name,
+                "include_standard_annotations": include_standard_annotations,
             }
             print("## OUTCOME")
             print(
@@ -539,6 +339,11 @@ def predict(
 @click.option("--add-species/--no-add-species", default=False, help="Add species to the output")
 @click.argument("results_file")
 def summarize_results(results_file, tsv, output, add_species):
+    """
+    Summarize the results of a previous run through gocam-predict.
+
+    Takes the YAML output of the prediction step.
+    """
     wrapper = GOCAMWrapper()
     species_by_gocam_id = {}
 
@@ -553,6 +358,7 @@ def _get_species(id: str):
             logger.debug(f"Getting species for {id} => {species_by_gocam_id[id]}")
         return species_by_gocam_id[id]
 
+    # read in results file YAML, flattening outcomes
     with open(results_file, "r", encoding="utf-8") as f:
 
         def _outcome(x: dict):
diff --git a/src/curate_gpt/agents/dragon_agent.py b/src/curate_gpt/agents/dragon_agent.py
index 59fb8d2..4fa8ad5 100644
--- a/src/curate_gpt/agents/dragon_agent.py
+++ b/src/curate_gpt/agents/dragon_agent.py
@@ -258,16 +258,41 @@ def generate_all(
                 current_value=curr_val,
             )
 
-    def review(
-        self,
-        obj: dict,
-        context_property: str = None,
-        rules=None,
-        collection=None,
-        fields_to_predict=None,
-        primary_key=None,
-        **kwargs,
-    ) -> AnnotatedObject:
+    def generate_queries(self, context_property="name", n=5, **kwargs) -> List[str]:
+        ks = self.knowledge_source
+        ids = []
+        for obj, _, _x in ks.find({}, **kwargs):
+            ids.append(obj.get(context_property))
+        system = f"""Suggest {n} additional entities to complement the existing supplied entities.
+        Return as a comma separated list. Do not return additional information. Keep the same
+        level of specificity. You can return similar entities, but not identical/equivalent.
+        
+        ## Example (n=2)
+        
+        Current:
+        Margarita Pizza, Hawaiian Pizza, Veggie Pizza
+        
+        Suggested:
+        Mushroom Pizza, Meat Lovers Pizza.
+        """
+        ids_str = ", ".join(ids)
+        prompt = f"""Current:
+        {ids_str}
+        Suggested:
+        """
+        logger.info(f"PROMPT: {prompt}")
+        response = self.extractor.model.prompt(prompt, system=system)
+        txt = response.text()
+        if "." in txt:
+            txt = txt[0:txt.index(".")]
+        suggestions = txt.split(",")
+        suggestions = [x.strip() for x in suggestions]
+        ids_norm = [x.lower() for x in ids]
+        suggestions = [x for x in suggestions if x.lower() not in ids_norm]
+        return suggestions
+
+
+    def review(self, obj: dict, context_property: str = None, rules = None, collection = None, fields_to_predict=None, primary_key=None, **kwargs) -> AnnotatedObject:
         """
         Review an object for correctness, completeness, and consistency.
 
diff --git a/src/curate_gpt/cli.py b/src/curate_gpt/cli.py
index d56c190..41ceb21 100644
--- a/src/curate_gpt/cli.py
+++ b/src/curate_gpt/cli.py
@@ -1213,6 +1213,92 @@ def complete_multiple(
             dump(ao.object, format=output_format)
 
 
+@main.command()
+@path_option
+@collection_option
+@model_option
+@limit_option
+@click.option(
+    "-P", "--query-property", default="label", show_default=True, help="Property to use for query."
+)
+@click.option(
+    "--fields-to-predict",
+    multiple=True,
+)
+@click.option(
+    "--number-of-entries",
+    "-N",
+    default=5,
+    show_default=True,
+    help="number of entries to generate",
+)
+@click.option(
+    "--docstore-path",
+    default=None,
+    help="Path to a docstore to for additional unstructured knowledge.",
+)
+@click.option("--docstore-collection", default=None, help="Collection to use in the docstore.")
+@generate_background_option
+@click.option(
+    "--rule",
+    multiple=True,
+    help="Rule to use for generating background knowledge.",
+)
+@schema_option
+@extract_format_option
+@output_format_option
+def complete_auto(
+    path,
+    collection,
+    docstore_path,
+    docstore_collection,
+    rule: List[str],
+    model,
+    query_property,
+    schema,
+    output_format,
+    extract_format,
+    number_of_entries,
+    **kwargs,
+):
+    """
+    Generate new KB entries, using model to choose new entities.
+
+    Example:
+    -------
+        curategpt complete-auto -c obo_go -N 5
+    """
+    db = ChromaDBAdapter(path)
+    if schema:
+        schema_manager = SchemaProxy(schema)
+    else:
+        schema_manager = None
+
+    # TODO: generalize
+    filtered_kwargs = {k: v for k, v in kwargs.items() if v is not None}
+    extractor = BasicExtractor(serialization_format=extract_format)
+    if model:
+        extractor.model_name = model
+    if schema_manager:
+        db.schema_proxy = schema
+        extractor.schema_proxy = schema_manager
+    dac = DragonAgent(knowledge_source=db, extractor=extractor)
+    if docstore_path or docstore_collection:
+        dac.document_adapter = ChromaDBAdapter(docstore_path)
+        dac.document_adapter_collection = docstore_collection
+    i = 0
+    while i < number_of_entries:
+        queries = dac.generate_queries(context_property=query_property, n=number_of_entries, collection=collection)
+        logging.info(f"SUGGESTIONS: {queries}")
+        if not queries:
+            raise ValueError("No results")
+        for query in queries:
+            logging.info(f"SUGGESTION: {query}")
+            ao = dac.complete(query, context_property=query_property, rules=rule, collection=collection, **filtered_kwargs)
+            print("---")
+            dump(ao.object, format=output_format)
+            i += 1
+
 @main.command()
 @path_option
 @collection_option
@@ -1674,8 +1760,8 @@ def apply_patch(input_file, patch, primary_key):
                 logging.debug(f"Applying: {actual_patch}")
                 jsonpatch.apply_patch(inner_obj, actual_patch, in_place=True)
     else:
-        for _obj in objs:
-            jsonpatch.apply_patch(objs, patch, in_place=True)
+        for obj in objs:
+            jsonpatch.apply_patch(obj, patch, in_place=True)
     logging.info(f"Writing patch output for {len(objs)} objects")
     for obj in objs:
         print("---")
diff --git a/src/curate_gpt/extract/openai_extractor.py b/src/curate_gpt/extract/openai_extractor.py
index 608fa37..6dce54c 100644
--- a/src/curate_gpt/extract/openai_extractor.py
+++ b/src/curate_gpt/extract/openai_extractor.py
@@ -53,7 +53,7 @@ def extract(
         for example in examples:
             ex_text = example.text
             ex_object = example.object
-            print(f"EXAMPLE = {ex_text}")
+            # print(f"EXAMPLE = {ex_text}")
             messages.append(
                 {
                     "role": "user",
@@ -89,7 +89,7 @@ def extract(
                 "content": content,
             }
         )
-        print(yaml.dump(messages))
+        # print(yaml.dump(messages))
         response = openai.ChatCompletion.create(
             model=self.model,
             functions=self.functions(),
@@ -97,7 +97,7 @@ def extract(
             max_tokens=self.max_tokens,
         )
         logger.debug(f"RESPONSE = {response}")
-        print(response)
+        # print(response)
         choice = response.choices[0]
         message = choice["message"]
         if "function_call" not in message:
diff --git a/src/curate_gpt/store/chromadb_adapter.py b/src/curate_gpt/store/chromadb_adapter.py
index 26d95e5..61f7103 100644
--- a/src/curate_gpt/store/chromadb_adapter.py
+++ b/src/curate_gpt/store/chromadb_adapter.py
@@ -343,6 +343,7 @@ def _search(
         limit=10,
         include=None,
         relevance_factor: float = None,
+        expand: bool = None,
         **kwargs,
     ) -> Iterator[SEARCH_RESULT]:
         logger.info(f"Searching for {text} in {collection}")
diff --git a/src/curate_gpt/utils/eval_utils.py b/src/curate_gpt/utils/eval_utils.py
new file mode 100644
index 0000000..ede2909
--- /dev/null
+++ b/src/curate_gpt/utils/eval_utils.py
@@ -0,0 +1,206 @@
+from copy import copy
+from typing import Union, Dict, Any, List, Optional
+
+from pydantic import BaseModel
+
+
+class Outcome(BaseModel):
+    prediction: Union[Dict[str, Any], List[Dict[str, Any]]] = {}
+    expected: Union[Dict[str, Any], List[Dict[str, Any]]] = {}
+    parameters: Dict[str, Any] = {}
+    tp: int = 0
+    tn: int = 0
+    fp: int = 0
+    fn: int = 0
+
+    precision: Optional[float] = None
+    recall:  Optional[float] = None
+    f1: Optional[float] = None
+
+    by_field: Dict[str, int] = {}
+    ixn_by_field: Dict[str, List[str]] = {}
+
+    def calculate_metrics(self):
+        self.precision = self.tp / (self.tp + self.fp) if self.tp + self.fp > 0 else 0
+        self.recall = self.tp / (self.tp + self.fn) if self.tp + self.fn > 0 else 0
+        self.f1 = 2 * self.precision * self.recall / (self.precision + self.recall) if self.precision + self.recall > 0 else 0
+
+    def append_outcomes(self, outcomes: List["Outcome"]) -> None:
+        for sub_outcome in outcomes:
+            self.tp += sub_outcome.tp
+            self.fp += sub_outcome.fp
+            self.fn += sub_outcome.fn
+            for key, value in sub_outcome.by_field.items():
+                self.by_field[key] = self.by_field.get(key, 0) + value
+            for key, value in sub_outcome.ixn_by_field.items():
+                curr = set(self.ixn_by_field.get(key, []))
+                self.ixn_by_field[key] = list(curr.union(value))
+        self.calculate_metrics()
+
+    def flatten(self) -> Dict[str, Any]:
+        obj = self.model_dump()
+        for k, v in copy(obj).items():
+            if k == "parameters":
+                obj.update(v)
+                del obj[k]
+            elif isinstance(v, dict):
+                del obj[k]
+            elif isinstance(v, list):
+                obj[k] = [x for x in v if x]
+        return obj
+
+
+def score_prediction(predicted: Union[Dict, List], expected: Union[Dict, List], exclude: List = None) -> Outcome:
+    """
+    Score the predicted activity.
+
+    >>> outcome = score_prediction({"x": 1}, {"x": 1})
+    >>> outcome.tp
+    1
+
+    >>> outcome = score_prediction([{"x": 1}], {"x": 1})
+    >>> outcome.tp
+    1
+
+
+    >>> outcome = score_prediction({"x": 1}, {"x": 2})
+    >>> outcome.tp
+    0
+    >>> outcome.recall
+    0.0
+
+    >>> outcome = score_prediction({"x": 1, "y": 2}, {"x": 1})
+    >>> outcome.tp
+    1
+    >>> outcome.fp
+    1
+
+    >>> outcome = score_prediction([{"x": 1}, {"y": 1}], {"x": 1})
+    >>> outcome.tp
+    1
+    >>> outcome.fp
+    1
+
+
+    :param predicted: The predicted activity
+    :param expected: The expected activity
+    :return: The score
+    """
+    if exclude is None:
+        exclude = ["reference_title", "reference"]
+    if isinstance(expected, list) or isinstance(predicted, list):
+        if isinstance(expected, dict):
+            expected = [expected]
+        if isinstance(predicted, dict):
+            predicted = [predicted]
+        outcomes = best_matches(predicted, expected)
+        outcome = Outcome(prediction=predicted, expected=expected)
+        for sub_outcome in outcomes:
+            outcome.tp += sub_outcome.tp
+            outcome.fp += sub_outcome.fp
+            outcome.fn += sub_outcome.fn
+            for key, value in sub_outcome.by_field.items():
+                outcome.by_field[key] = outcome.by_field.get(key, 0) + value
+            for key, value in sub_outcome.ixn_by_field.items():
+                outcome.ixn_by_field[key] = list(set(outcome.ixn_by_field.get(key, [])).union(value))
+        outcome.calculate_metrics()
+        return outcome
+    outcome = Outcome(prediction=predicted, expected=expected)
+    all_keys = set(predicted.keys()).union(expected.keys()).difference(exclude)
+    for key in all_keys:
+        if key in predicted and key in expected:
+            if key == "relationships":
+                pred_rels = predicted[key]
+                exp_rels = expected[key]
+                sub_outcomes = best_matches(pred_rels, exp_rels)
+                n_tps = 0
+                ixn = set()
+                for sub_outcome in sub_outcomes:
+                    outcome.tp += sub_outcome.tp
+                    outcome.fp += sub_outcome.fp
+                    outcome.fn += sub_outcome.fn
+                    n_tps += sub_outcome.tp
+                    if sub_outcome.precision == 1.0:
+                        ixn = ixn.union({str(predicted[key])})
+                outcome.by_field[key] = outcome.by_field.get(key, 0) + n_tps
+                outcome.ixn_by_field[key] = list(set(outcome.ixn_by_field.get(key, [])).union(ixn))
+                continue
+            if predicted[key] == expected[key]:
+                outcome.tp += 1
+                outcome.by_field[key] = outcome.by_field.get(key, 0) + 1
+                outcome.ixn_by_field[key] = list(set(outcome.ixn_by_field.get(key, [])).union({predicted[key]}))
+            else:
+                outcome.fp += 1
+                outcome.fn += 1
+        elif key in predicted:
+            outcome.fp += 1
+        else:
+            outcome.fn += 1
+    outcome.calculate_metrics()
+    return outcome
+
+
+def best_matches(pred_rels, exp_rels) -> List[Outcome]:
+    """
+    Find the best matching pairs of relationships.
+
+    Example:
+
+    >>> outcomes = best_matches([], [])
+    >>> len(outcomes)
+    1
+    >>> outcome = outcomes[0]
+    >>> (outcome.tp, outcome.fp, outcome.fn)
+    (0, 0, 0)
+    >>> best_matches([{"x:": 1}], [])[0].precision
+    0.0
+    >>> outcome = best_matches([{"x": 1}], [{"x": 1}])[0]
+    >>> outcome.precision
+    1.0
+    >>> outcome = best_matches([{"x": 1}], [{"y": 1}])[0]
+    >>> outcome.precision
+    0.0
+    >>> pred_rels = [{"x":1}, {"y": 2}, {"z": 3}]
+    >>> exp_rels = [{"y":2}, {"x": 1}, {"z": 3}]
+    >>> outcomes = best_matches(pred_rels, exp_rels)
+    >>> [o.precision for o in outcomes]
+    [1.0, 1.0, 1.0]
+    >>> exp_rels.append({"z": 4})
+    >>> outcomes = best_matches(pred_rels, exp_rels)
+    >>> sorted([o.precision for o in outcomes])
+    [0.0, 1.0, 1.0, 1.0]
+
+    """
+    import numpy as np
+
+    if not pred_rels:
+        pred_rels = [{}]
+    if not exp_rels:
+        exp_rels = [{}]
+
+    # Create a matrix to store the scores
+    outcome_matrix = np.zeros((len(pred_rels), len(exp_rels)), dtype=object)
+    outcome_ix = {}
+
+    # Calculate the scores for each pair of pred_rel and exp_rel
+    for i, pred_rel in enumerate(pred_rels):
+        for j, exp_rel in enumerate(exp_rels):
+            sub_outcome = score_prediction(pred_rel, exp_rel)
+            outcome_matrix[i, j] = sub_outcome.tp
+            outcome_ix[(i, j)] = sub_outcome
+
+    # Find the best matching pairs
+    outcomes = []
+    max_row_indices = np.argmax(outcome_matrix, axis=1)
+    max_col_indices = np.argmax(outcome_matrix, axis=0)
+    best = []
+    for i, pred_rel in enumerate(pred_rels):
+        best_j = max_row_indices[i]
+        best.append((i, best_j))
+        outcomes.append(outcome_ix[(i, best_j)])
+    for j, exp_rel in enumerate(exp_rels):
+        best_i = max_col_indices[j]
+        if (best_i, j) not in best:
+            best.append((best_i, j))
+            outcomes.append(outcome_ix[(best_i, j)])
+    return outcomes
diff --git a/src/curate_gpt/utils/llm_utils.py b/src/curate_gpt/utils/llm_utils.py
new file mode 100644
index 0000000..a3cd0bd
--- /dev/null
+++ b/src/curate_gpt/utils/llm_utils.py
@@ -0,0 +1,33 @@
+import logging
+
+from llm import Model, Response
+from tenacity import wait_random_exponential, stop_after_attempt, retry_if_exception, retry
+
+logger = logging.getLogger(__name__)
+
+
+def is_rate_limit_error(exception):
+    # List of fully qualified names of RateLimitError exceptions from various libraries
+    rate_limit_errors = [
+        "openai.error.RateLimitError",
+        "openai.RateLimitError",
+        "anthropic.error.RateLimitError",
+        "anthropic.RateLimitError",
+        # Add more as needed
+    ]
+    exception_full_name = f"{exception.__class__.__module__}.{exception.__class__.__name__}"
+    logger.warning(f"Exception_full_name: {exception_full_name}")
+    logger.warning(f"Exception: {exception}")
+    return exception_full_name in rate_limit_errors
+
+
+@retry(
+    retry=retry_if_exception(is_rate_limit_error),
+    wait=wait_random_exponential(multiplier=1, max=40),
+    stop=stop_after_attempt(3),
+)
+def query_model(model: Model, *args, **kwargs) -> Response:
+    logger.debug(f"Querying model {model.model_id}, args: {args}, kwargs: {kwargs}")
+    response = model.prompt(*args, **kwargs)
+    _text = response.text()
+    return response
diff --git a/src/curate_gpt/utils/tokens.py b/src/curate_gpt/utils/tokens.py
index ce2f86d..2bba923 100644
--- a/src/curate_gpt/utils/tokens.py
+++ b/src/curate_gpt/utils/tokens.py
@@ -15,6 +15,8 @@ def max_tokens_by_model(model_id: Optional[str] = None):
     """
     if model_id == "gpt-4":
         return 8192
+    elif "gpt-4o-mini" in model_id:
+        return 16384
     elif "gpt-4o" in model_id:
         return 1024 * 128
     elif model_id == "gpt-3.5-turbo-16k":
diff --git a/src/curate_gpt/wrappers/bio/gocam_wrapper.py b/src/curate_gpt/wrappers/bio/gocam_wrapper.py
index 68229ff..cecde98 100644
--- a/src/curate_gpt/wrappers/bio/gocam_wrapper.py
+++ b/src/curate_gpt/wrappers/bio/gocam_wrapper.py
@@ -178,6 +178,7 @@ def _cls(obj: Dict) -> Optional[str]:
                 logger.warning(f"Missing object {o} in {individual_to_term}")
                 continue
             gene_id = individual_to_term[o]
+            # we only include a single pmid for each activity
             activity = {
                 "gene": gene_id,
                 "activity": individual_to_term[s],