diff --git a/align_system/algorithms/outlines_adm.py b/align_system/algorithms/outlines_adm.py
index 7d34ed97..a23a11dc 100644
--- a/align_system/algorithms/outlines_adm.py
+++ b/align_system/algorithms/outlines_adm.py
@@ -7,6 +7,7 @@
 
 import outlines
 from outlines.samplers import MultinomialSampler
+from outlines.models.vllm import VLLM
 import jinja2
 from rich.highlighter import JSONHighlighter
 from swagger_client.models import (
@@ -73,11 +74,10 @@ def __init__(self,
 
             model_kwargs['torch_dtype'] = torch_dtype
 
-        self.model = outlines.models.transformers(
+        self.model = outlines.models.vllm(
             model_name,
-            device=device,
-            model_kwargs=model_kwargs,
-            tokenizer_kwargs=kwargs.get('tokenizer_kwargs', {}))
+            device=device
+        )
         # NOTE: In cases where we want multiple samples, we're passing
         # in a list of prompts (this allows us to shuffle answers in
         # each prompt), rather than setting the number of samples in
@@ -86,7 +86,7 @@ def __init__(self,
         self.sampler = sampler
 
     def dialog_to_prompt(self, dialog):
-        tokenizer = self.model.tokenizer.tokenizer
+        tokenizer = self.model.tokenizer
 
         try:
             encoded_dialog = tokenizer.apply_chat_template(dialog)
@@ -218,32 +218,48 @@ def top_level_choose_action(self,
             if "incontext" in kwargs and "number" in incontext_settings and incontext_settings["number"] > 0:
                 scenario_to_match = scenario_state_description_1(scenario_state)
                 prompt_to_match, _ = self._state_to_top_level_prompt(scenario_state, available_actions)
-                
+
                 # Create positive ICL example generators
                 positive_target = {'kdma': kdma, 'name': name, 'value': value}
-                positive_icl_example_generator = incontext_utils.BaselineIncontextExampleGenerator(incontext_settings,
-                                                                                                    [positive_target])
+                positive_icl_example_generator = (
+                    incontext_utils.BaselineIncontextExampleGenerator(
+                        incontext_settings,
+                        [positive_target]
+                    )
+                )
                 # Get subset of relevant of examples
-                positive_selected_icl_examples = positive_icl_example_generator.select_icl_examples(kdma, 
-                                                                                                    scenario_to_match, 
-                                                                                                    prompt_to_match)
+                positive_selected_icl_examples = (
+                    positive_icl_example_generator.select_icl_examples(
+                        kdma,
+                        scenario_to_match,
+                        prompt_to_match
+                    )
+                )
                 # Create positive ICL prompts
                 for icl_sample in positive_selected_icl_examples:
                     positive_icl_examples.extend([
                         {"role": "user", "content": icl_sample['prompt']},
                         {"role": "assistant", "content": f'{icl_sample["response"]}'}
                     ])
-                
+
                 # Create negative ICL prompts
                 if num_negative_samples > 0:
                     # Create negative ICL example generators
                     negative_target = {'kdma': kdma, 'name': name, 'value': negative_value}
-                    negative_icl_example_generator = incontext_utils.BaselineIncontextExampleGenerator(incontext_settings,
-                                                                                                    [negative_target])
+                    negative_icl_example_generator = (
+                        incontext_utils.BaselineIncontextExampleGenerator(
+                            incontext_settings,
+                            [negative_target]
+                        )
+                    )
                     # Get subset of relevant of examples
-                    negative_selected_icl_examples = negative_icl_example_generator.select_icl_examples(kdma, 
-                                                                                                    scenario_to_match, 
-                                                                                                    prompt_to_match)
+                    negative_selected_icl_examples = (
+                        negative_icl_example_generator.select_icl_examples(
+                            kdma,
+                            scenario_to_match,
+                            prompt_to_match
+                        )
+                    )
                     for icl_sample in negative_selected_icl_examples:
                         negative_icl_examples.extend([
                             {"role": "user", "content": icl_sample['prompt']},
diff --git a/poetry.lock b/poetry.lock
index 764a4161..cfc64ffd 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
 [[package]]
 name = "absl-py"
@@ -274,6 +274,85 @@ files = [
     {file = "certifi-2024.6.2.tar.gz", hash = "sha256:3cd43f1c6fa7dedc5899d69d3ad0398fd018ad1a17fba83ddaf78aa46c747516"},
 ]
 
+[[package]]
+name = "cffi"
+version = "1.17.1"
+description = "Foreign Function Interface for Python calling C code."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "cffi-1.17.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:df8b1c11f177bc2313ec4b2d46baec87a5f3e71fc8b45dab2ee7cae86d9aba14"},
+    {file = "cffi-1.17.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8f2cdc858323644ab277e9bb925ad72ae0e67f69e804f4898c070998d50b1a67"},
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+    {file = "cffi-1.17.1.tar.gz", hash = "sha256:1c39c6016c32bc48dd54561950ebd6836e1670f2ae46128f67cf49e789c52824"},
+]
+
+[package.dependencies]
+pycparser = "*"
+
 [[package]]
 name = "charset-normalizer"
 version = "3.3.2"
@@ -605,6 +684,26 @@ files = [
 [package.extras]
 test = ["pytest (>=6)"]
 
+[[package]]
+name = "fastapi"
+version = "0.115.0"
+description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "fastapi-0.115.0-py3-none-any.whl", hash = "sha256:17ea427674467486e997206a5ab25760f6b09e069f099b96f5b55a32fb6f1631"},
+    {file = "fastapi-0.115.0.tar.gz", hash = "sha256:f93b4ca3529a8ebc6fc3fcf710e5efa8de3df9b41570958abf1d97d843138004"},
+]
+
+[package.dependencies]
+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"
+starlette = ">=0.37.2,<0.39.0"
+typing-extensions = ">=4.8.0"
+
+[package.extras]
+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 = "filelock"
 version = "3.14.0"
@@ -814,6 +913,22 @@ test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask-expr", "dask[dataframe,
 test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"]
 tqdm = ["tqdm"]
 
+[[package]]
+name = "gguf"
+version = "0.10.0"
+description = "Read and write ML models in GGUF for GGML"
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.dependencies]
+numpy = ">=1.17"
+pyyaml = ">=5.1"
+tqdm = ">=4.27"
+
 [[package]]
 name = "greenlet"
 version = "3.0.3"
@@ -917,6 +1032,54 @@ http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
 trio = ["trio (>=0.22.0,<0.26.0)"]
 
+[[package]]
+name = "httptools"
+version = "0.6.1"
+description = "A collection of framework independent HTTP protocol utils."
+optional = false
+python-versions = ">=3.8.0"
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+]
+
+[package.extras]
+test = ["Cython (>=0.29.24,<0.30.0)"]
+
 [[package]]
 name = "httpx"
 version = "0.27.0"
@@ -1002,6 +1165,29 @@ files = [
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 ]
 
+[[package]]
+name = "importlib-metadata"
+version = "8.5.0"
+description = "Read metadata from Python packages"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "importlib_metadata-8.5.0-py3-none-any.whl", hash = "sha256:45e54197d28b7a7f1559e60b95e7c567032b602131fbd588f1497f47880aa68b"},
+    {file = "importlib_metadata-8.5.0.tar.gz", hash = "sha256:71522656f0abace1d072b9e5481a48f07c138e00f079c38c8f883823f9c26bd7"},
+]
+
+[package.dependencies]
+zipp = ">=3.20"
+
+[package.extras]
+check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
+cover = ["pytest-cov"]
+doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+enabler = ["pytest-enabler (>=2.2)"]
+perf = ["ipython"]
+test = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"]
+type = ["pytest-mypy"]
+
 [[package]]
 name = "importlib-resources"
 version = "6.4.0"
@@ -1020,20 +1206,6 @@ zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
 docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
 testing = ["jaraco.test (>=5.4)", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-ruff (>=0.2.1)", "zipp (>=3.17)"]
 
-[[package]]
-name = "intel-openmp"
-version = "2021.4.0"
-description = "Intel OpenMP* Runtime Library"
-optional = false
-python-versions = "*"
-files = [
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-
 [[package]]
 name = "interegular"
 version = "0.3.3"
@@ -1062,6 +1234,76 @@ MarkupSafe = ">=2.0"
 [package.extras]
 i18n = ["Babel (>=2.7)"]
 
+[[package]]
+name = "jiter"
+version = "0.5.0"
+description = "Fast iterable JSON parser."
+optional = false
+python-versions = ">=3.8"
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 version = "1.4.2"
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+[[package]]
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+description = "Enforce the output format (JSON Schema, Regex etc) of a language model"
+optional = false
+python-versions = "<4.0,>=3.8"
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+packaging = "*"
+pydantic = ">=1.10.8"
+pyyaml = "*"
+
 [[package]]
 name = "markdown-it-py"
 version = "3.0.0"
@@ -1552,22 +1811,28 @@ files = [
 ]
 
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-name = "mkl"
-version = "2021.4.0"
-description = "Intel® oneAPI Math Kernel Library"
+name = "mistral-common"
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+description = ""
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 [package.dependencies]
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-tbb = "==2021.*"
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+numpy = {version = ">=1.25", markers = "python_version >= \"3.9\""}
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+typing-extensions = ">=4.11.0,<5.0.0"
+
+[package.extras]
+opencv = ["opencv-python-headless (>=4.0.0,<5.0.0)"]
 
 [[package]]
 name = "mpmath"
@@ -1586,6 +1851,131 @@ docs = ["sphinx"]
 gmpy = ["gmpy2 (>=2.1.0a4)"]
 tests = ["pytest (>=4.6)"]
 
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 [[package]]
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 python-versions = ">=3"
 files = [
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+    {file = "nvidia_cusolver_cu11-11.4.1.48-py3-none-manylinux2014_aarch64.whl", hash = "sha256:1a96acb05768610bc414dbef5b25ebd2d820fc8a1e8c72097f41f53d80934d61"},
+    {file = "nvidia_cusolver_cu11-11.4.1.48-py3-none-manylinux2014_x86_64.whl", hash = "sha256:ea9fb1ad8c644ca9ed55af13cc39af3b7ba4c3eb5aef18471fe1fe77d94383cb"},
     {file = "nvidia_cusolver_cu11-11.4.1.48-py3-none-win_amd64.whl", hash = "sha256:7efe43b113495a64e2cf9a0b4365bd53b0a82afb2e2cf91e9f993c9ef5e69ee8"},
 ]
 
@@ -1958,9 +2363,22 @@ optional = false
 python-versions = ">=3"
 files = [
     {file = "nvidia_cusparse_cu11-11.7.5.86-py3-none-manylinux1_x86_64.whl", hash = "sha256:4ae709fe78d3f23f60acaba8c54b8ad556cf16ca486e0cc1aa92dca7555d2d2b"},
+    {file = "nvidia_cusparse_cu11-11.7.5.86-py3-none-manylinux2014_aarch64.whl", hash = "sha256:6c7da46abee7567e619d4aa2e90a1b032cfcbd1211d429853b1a6e87514a14b2"},
+    {file = "nvidia_cusparse_cu11-11.7.5.86-py3-none-manylinux2014_x86_64.whl", hash = "sha256:8d7cf1628fd8d462b5d2ba6678fae34733a48ecb80495b9c68672ec6a6dde5ef"},
     {file = "nvidia_cusparse_cu11-11.7.5.86-py3-none-win_amd64.whl", hash = "sha256:a0f6ee81cd91be606fc2f55992d06b09cd4e86d74b6ae5e8dd1631cf7f5a8706"},
 ]
 
+[[package]]
+name = "nvidia-ml-py"
+version = "12.560.30"
+description = "Python Bindings for the NVIDIA Management Library"
+optional = false
+python-versions = "*"
+files = [
+    {file = "nvidia-ml-py-12.560.30.tar.gz", hash = "sha256:f0254dc7400647680a072ee02509bfd46102b60bdfeca321576d4d4817e7fe97"},
+    {file = "nvidia_ml_py-12.560.30-py3-none-any.whl", hash = "sha256:fea371c94d63e38a611c17bbb85fe400e9c8ddb9e8684a9cd0e47786a4bc3c73"},
+]
+
 [[package]]
 name = "nvidia-nccl-cu11"
 version = "2.20.5"
@@ -1979,6 +2397,8 @@ optional = false
 python-versions = ">=3"
 files = [
     {file = "nvidia_nvtx_cu11-11.8.86-py3-none-manylinux1_x86_64.whl", hash = "sha256:890656d8bd9b4e280231c832e1f0d03459200ba4824ddda3dcb59b1e1989b9f5"},
+    {file = "nvidia_nvtx_cu11-11.8.86-py3-none-manylinux2014_aarch64.whl", hash = "sha256:5e84b97062eb102b45a8a9172a06cfe28b239b1635075a13d6474e91295e0468"},
+    {file = "nvidia_nvtx_cu11-11.8.86-py3-none-manylinux2014_x86_64.whl", hash = "sha256:979f5b2aef5da164c5c53c64c85c3dfa61b8b4704f4f963bb568bf98fa8472e8"},
     {file = "nvidia_nvtx_cu11-11.8.86-py3-none-win_amd64.whl", hash = "sha256:54031010ee38d774b2991004d88f90bbd7bbc1458a96bbc4b42662756508c252"},
 ]
 
@@ -1999,23 +2419,24 @@ PyYAML = ">=5.1.0"
 
 [[package]]
 name = "openai"
-version = "1.31.2"
+version = "1.48.0"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.7.1"
 files = [
-    {file = "openai-1.31.2-py3-none-any.whl", hash = "sha256:203cf21294f347c3d7b591e0ccbe18389d6f8967d4237214b926ea76b1e1781c"},
-    {file = "openai-1.31.2.tar.gz", hash = "sha256:966ab3165b926cb5ec091d2434c90613e2ea8b73ffad984f7fec34bde971725a"},
+    {file = "openai-1.48.0-py3-none-any.whl", hash = "sha256:7c4af223f0bf615ce4a12453729952c9a8b04ffe8c78aa77981b12fd970149cf"},
+    {file = "openai-1.48.0.tar.gz", hash = "sha256:1d3b69ea62c287c4885a6f3ce840768564cd5f52c60ac5f890fef80d43cc4799"},
 ]
 
 [package.dependencies]
 anyio = ">=3.5.0,<5"
 distro = ">=1.7.0,<2"
 httpx = ">=0.23.0,<1"
+jiter = ">=0.4.0,<1"
 pydantic = ">=1.9.0,<3"
 sniffio = "*"
 tqdm = ">4"
-typing-extensions = ">=4.7,<5"
+typing-extensions = ">=4.11,<5"
 
 [package.extras]
 datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
@@ -2105,9 +2526,9 @@ files = [
 
 [package.dependencies]
 numpy = [
+    {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
     {version = ">=1.22.4", markers = "python_version < \"3.11\""},
     {version = ">=1.23.2", markers = "python_version == \"3.11\""},
-    {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
@@ -2138,6 +2559,20 @@ sql-other = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-d
 test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)"]
 xml = ["lxml (>=4.9.2)"]
 
+[[package]]
+name = "partial-json-parser"
+version = "0.2.1.1.post4"
+description = "Parse partial JSON generated by LLM"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "partial_json_parser-0.2.1.1.post4-py3-none-any.whl", hash = "sha256:960144ff29ab9358b69c17dca6e867687438f0dd206ea113677040f14f9ccedd"},
+    {file = "partial_json_parser-0.2.1.1.post4.tar.gz", hash = "sha256:a38f11ceb89a86fbfbd0acad4170d417dcb317621c6ec9ab5f2b6652f3f460bf"},
+]
+
+[package.extras]
+playground = ["rich"]
+
 [[package]]
 name = "pillow"
 version = "10.3.0"
@@ -2224,6 +2659,55 @@ tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "pa
 typing = ["typing-extensions"]
 xmp = ["defusedxml"]
 
+[[package]]
+name = "prometheus-client"
+version = "0.21.0"
+description = "Python client for the Prometheus monitoring system."
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "prometheus_client-0.21.0.tar.gz", hash = "sha256:96c83c606b71ff2b0a433c98889d275f51ffec6c5e267de37c7a2b5c9aa9233e"},
+]
+
+[package.extras]
+twisted = ["twisted"]
+
+[[package]]
+name = "prometheus-fastapi-instrumentator"
+version = "7.0.0"
+description = "Instrument your FastAPI with Prometheus metrics."
+optional = false
+python-versions = ">=3.8.1,<4.0.0"
+files = [
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+]
+
+[package.dependencies]
+prometheus-client = ">=0.8.0,<1.0.0"
+starlette = ">=0.30.0,<1.0.0"
+
+[[package]]
+name = "protobuf"
+version = "5.28.2"
+description = ""
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "protobuf-5.28.2-cp39-cp39-win32.whl", hash = "sha256:ca53faf29896c526863366a52a8f4d88e69cd04ec9571ed6082fa117fac3ab36"},
+    {file = "protobuf-5.28.2-cp39-cp39-win_amd64.whl", hash = "sha256:8ddc60bf374785fb7cb12510b267f59067fa10087325b8e1855b898a0d81d276"},
+    {file = "protobuf-5.28.2-py3-none-any.whl", hash = "sha256:52235802093bd8a2811abbe8bf0ab9c5f54cca0a751fdd3f6ac2a21438bffece"},
+    {file = "protobuf-5.28.2.tar.gz", hash = "sha256:59379674ff119717404f7454647913787034f03fe7049cbef1d74a97bb4593f0"},
+]
+
 [[package]]
 name = "psutil"
 version = "5.9.8"
@@ -2252,6 +2736,17 @@ files = [
 [package.extras]
 test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"]
 
+[[package]]
+name = "py-cpuinfo"
+version = "9.0.0"
+description = "Get CPU info with pure Python"
+optional = false
+python-versions = "*"
+files = [
+    {file = "py-cpuinfo-9.0.0.tar.gz", hash = "sha256:3cdbbf3fac90dc6f118bfd64384f309edeadd902d7c8fb17f02ffa1fc3f49690"},
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+]
+
 [[package]]
 name = "pyairports"
 version = "2.1.1"
@@ -2322,6 +2817,17 @@ files = [
     {file = "pycountry-24.6.1.tar.gz", hash = "sha256:b61b3faccea67f87d10c1f2b0fc0be714409e8fcdcc1315613174f6466c10221"},
 ]
 
+[[package]]
+name = "pycparser"
+version = "2.22"
+description = "C parser in Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "pycparser-2.22-py3-none-any.whl", hash = "sha256:c3702b6d3dd8c7abc1afa565d7e63d53a1d0bd86cdc24edd75470f4de499cfcc"},
+    {file = "pycparser-2.22.tar.gz", hash = "sha256:491c8be9c040f5390f5bf44a5b07752bd07f56edf992381b05c701439eec10f6"},
+]
+
 [[package]]
 name = "pycryptodome"
 version = "3.20.0"
@@ -2365,109 +2871,123 @@ files = [
 
 [[package]]
 name = "pydantic"
-version = "2.7.3"
+version = "2.9.2"
 description = "Data validation using Python type hints"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
-annotated-types = ">=0.4.0"
-pydantic-core = "2.18.4"
-typing-extensions = ">=4.6.1"
+annotated-types = ">=0.6.0"
+pydantic-core = "2.23.4"
+typing-extensions = [
+    {version = ">=4.12.2", markers = "python_version >= \"3.13\""},
+    {version = ">=4.6.1", markers = "python_version < \"3.13\""},
+]
 
 [package.extras]
 email = ["email-validator (>=2.0.0)"]
+timezone = ["tzdata"]
 
 [[package]]
 name = "pydantic-core"
-version = "2.18.4"
+version = "2.23.4"
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 python-versions = ">=3.8"
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@@ -3202,7 +3992,7 @@ files = [
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 pymysql = ["pymysql"]
 sqlcipher = ["sqlcipher3_binary"]
 
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 [package.dependencies]
@@ -3475,34 +4270,33 @@ testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests", "ruff"]
 
 [[package]]
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 python-versions = ">=3.8.0"
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 ]
 
 [package.dependencies]
 filelock = "*"
 fsspec = "*"
 jinja2 = "*"
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 nvidia-cuda-runtime-cu11 = {version = "11.8.89", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cudnn-cu11 = {version = "8.7.0.84", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cudnn-cu11 = {version = "9.1.0.70", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cufft-cu11 = {version = "10.9.0.58", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-curand-cu11 = {version = "10.3.0.86", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cusolver-cu11 = {version = "11.4.1.48", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
@@ -3510,12 +4304,45 @@ nvidia-cusparse-cu11 = {version = "11.7.5.86", markers = "platform_system == \"L
 nvidia-nccl-cu11 = {version = "2.20.5", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-nvtx-cu11 = {version = "11.8.86", 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.source]
+type = "legacy"
+url = "https://download.pytorch.org/whl/cu118"
+reference = "pytorch"
+
+[[package]]
+name = "torchvision"
+version = "0.19.0+cu118"
+description = "image and video datasets and models for torch deep learning"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "torchvision-0.19.0+cu118-cp310-cp310-linux_x86_64.whl", hash = "sha256:120cee8ca4688a287fcaae69fcc4284b48c04ef8cc7a53461200d8c047ffe998"},
+    {file = "torchvision-0.19.0+cu118-cp310-cp310-win_amd64.whl", hash = "sha256:1df164a998dd52ee9f3c43aede7a7e05b25914da4c502b317045a4c755d4a13e"},
+    {file = "torchvision-0.19.0+cu118-cp311-cp311-linux_x86_64.whl", hash = "sha256:0253ff28a46380e0149b2cff4eb96d8633a264a9774902b0d992cdf2feb6ff71"},
+    {file = "torchvision-0.19.0+cu118-cp311-cp311-win_amd64.whl", hash = "sha256:13e8d8fbcd768387b6dd12234f6bd55c14abd62c6ef933c4a97c0b1fba2486ae"},
+    {file = "torchvision-0.19.0+cu118-cp312-cp312-linux_x86_64.whl", hash = "sha256:5ab8b06c0110d28573b43b21a5f5f6a34c083c6dfe6f8870e4390d1e88723471"},
+    {file = "torchvision-0.19.0+cu118-cp312-cp312-win_amd64.whl", hash = "sha256:0102a52f7c7588c7bdf6898777dd9d2b82d61cbe429a27818875d0556137b52c"},
+    {file = "torchvision-0.19.0+cu118-cp38-cp38-linux_x86_64.whl", hash = "sha256:be0260a2aa2f77d2d4dba6b500f747ba1214c7c2e55aaac362a22b5d1dfcf3b5"},
+    {file = "torchvision-0.19.0+cu118-cp38-cp38-win_amd64.whl", hash = "sha256:c1a4a032746a2e1361789624bb345113458947aa5a8ae653719b185994d8e41f"},
+    {file = "torchvision-0.19.0+cu118-cp39-cp39-linux_x86_64.whl", hash = "sha256:1f595eae367fbe7a46ec85fe6c55fa4185ef8b31bde5ae9b018c6b615b09c7d7"},
+    {file = "torchvision-0.19.0+cu118-cp39-cp39-win_amd64.whl", hash = "sha256:03fc97a9058bb489aee898d2b7cef7e2e7636ecda1d9afbadf03e5b7268ae07a"},
+]
+
+[package.dependencies]
+numpy = "*"
+pillow = ">=5.3.0,<8.3.dev0 || >=8.4.dev0"
+torch = "2.4.0"
+
+[package.extras]
+gdown = ["gdown (>=4.7.3)"]
+scipy = ["scipy"]
 
 [package.source]
 type = "legacy"
@@ -3544,38 +4371,39 @@ telegram = ["requests"]
 
 [[package]]
 name = "transformers"
-version = "4.41.2"
+version = "4.45.0"
 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-4.45.0-py3-none-any.whl", hash = "sha256:f04a82926676056afb3bbf4df7d76ceb1fc2b2746247a87f3f9be4674adc95d7"},
+    {file = "transformers-4.45.0.tar.gz", hash = "sha256:29629f87965acc7b15e458a24580832d85da18ddc119410211747fe778c200ce"},
 ]
 
 [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"
 regex = "!=2019.12.17"
 requests = "*"
 safetensors = ">=0.4.1"
-tokenizers = ">=0.19,<0.20"
+tokenizers = ">=0.20,<0.21"
 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"]
+accelerate = ["accelerate (>=0.26.0)"]
+agents = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch"]
+all = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "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 (>=0.20,<0.21)", "torch", "torchaudio", "torchvision"]
 audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
+benchmark = ["optimum-benchmark (>=0.3.0)"]
 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 = ["accelerate (>=0.26.0)", "deepspeed (>=0.9.3)"]
+deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.26.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk (<=3.8.1)", "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 (==0.5.1)", "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 (>=0.26.0)", "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)", "libcst", "librosa", "nltk (<=3.8.1)", "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)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "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 (>=0.20,<0.21)", "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)", "libcst", "librosa", "nltk (<=3.8.1)", "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", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "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 (>=0.20,<0.21)", "urllib3 (<2.0.0)"]
+dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "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", "libcst", "librosa", "nltk (<=3.8.1)", "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)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "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 (>=0.20,<0.21)", "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"]
@@ -3586,41 +4414,42 @@ natten = ["natten (>=0.14.6,<0.15.0)"]
 onnx = ["onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "tf2onnx"]
 onnxruntime = ["onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)"]
 optuna = ["optuna"]
-quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "isort (>=5.5.4)", "ruff (==0.1.5)", "urllib3 (<2.0.0)"]
+quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "isort (>=5.5.4)", "libcst", "rich", "ruff (==0.5.1)", "urllib3 (<2.0.0)"]
 ray = ["ray[tune] (>=2.7.0)"]
 retrieval = ["datasets (!=2.5.0)", "faiss-cpu"]
+ruff = ["ruff (==0.5.1)"]
 sagemaker = ["sagemaker (>=2.31.0)"]
 sentencepiece = ["protobuf", "sentencepiece (>=0.1.91,!=0.1.92)"]
 serving = ["fastapi", "pydantic", "starlette", "uvicorn"]
 sigopt = ["sigopt"]
 sklearn = ["scikit-learn"]
 speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
-testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "parameterized", "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"]
-tf = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
-tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
+testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk (<=3.8.1)", "parameterized", "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 (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
+tf = ["keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
+tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<0.24)", "tensorflow-text (<2.16)", "tf2onnx"]
 tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
-timm = ["timm"]
-tokenizers = ["tokenizers (>=0.19,<0.20)"]
-torch = ["accelerate (>=0.21.0)", "torch"]
+tiktoken = ["blobfile", "tiktoken"]
+timm = ["timm (<=0.9.16)"]
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+
+[[package]]
+name = "xformers"
+version = "0.0.27.post2"
+description = "XFormers: A collection of composable Transformer building blocks."
+optional = false
+python-versions = ">=3.7"
+files = [
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+    {file = "xformers-0.0.27.post2-cp39-cp39-win_amd64.whl", hash = "sha256:d555ef6d3722941cd785cf4b7c6039b06e8a0ca1360ff661200cf043393ca5a2"},
+    {file = "xformers-0.0.27.post2.tar.gz", hash = "sha256:5c3bcefabf29532cac7eb7556fb684be209698955b004aac069742e49373bdb3"},
+]
+
+[package.dependencies]
+numpy = "*"
+torch = "2.4.0"
+
 [[package]]
 name = "xxhash"
 version = "3.4.1"
@@ -3906,20 +5074,24 @@ multidict = ">=4.0"
 
 [[package]]
 name = "zipp"
-version = "3.19.2"
+version = "3.20.2"
 description = "Backport of pathlib-compatible object wrapper for zip files"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "zipp-3.19.2-py3-none-any.whl", hash = "sha256:f091755f667055f2d02b32c53771a7a6c8b47e1fdbc4b72a8b9072b3eef8015c"},
-    {file = "zipp-3.19.2.tar.gz", hash = "sha256:bf1dcf6450f873a13e952a29504887c89e6de7506209e5b1bcc3460135d4de19"},
+    {file = "zipp-3.20.2-py3-none-any.whl", hash = "sha256:a817ac80d6cf4b23bf7f2828b7cabf326f15a001bea8b1f9b49631780ba28350"},
+    {file = "zipp-3.20.2.tar.gz", hash = "sha256:bc9eb26f4506fda01b81bcde0ca78103b6e62f991b381fec825435c836edbc29"},
 ]
 
 [package.extras]
+check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
+cover = ["pytest-cov"]
 doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
+enabler = ["pytest-enabler (>=2.2)"]
+test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"]
+type = ["pytest-mypy"]
 
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<4.0"
-content-hash = "a658d17239ceca274b049a79541fb3abfaaf5d347dc630c2cd1f3d0ed329a084"
+content-hash = "d5dc66442727161b321fe7c558691d872317dcf969626a9b94bd498d952c410d"
diff --git a/pyproject.toml b/pyproject.toml
index c3fb29ab..8857912f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -14,6 +14,7 @@ priority = "supplemental"
 [tool.poetry.dependencies]
 python = ">=3.9,<4.0"
 torch = { version = "^2.0.1", source = "pytorch" }
+torchvision = { version = "^0.19.0", source = "pytorch" }
 transformers = "^4.33.1"
 llama-index = "^0.8.21"
 langchain = "^0.0.308"
@@ -26,7 +27,7 @@ requests = "^2.31.0"
 bert-score = "^0.3.13"
 rich = "^13.6.0"
 rouge-score = "^0.1.2"
-swagger-client = {git = "https://github.com/NextCenturyCorporation/itm-evaluation-client.git", rev = "main"}
+swagger-client = {git = "https://github.com/NextCenturyCorporation/itm-evaluation-client.git", rev = "development"}
 hydra-core = "^1.3.2"
 outlines = "^0.0.46"
 setuptools = "^70.1.1"