diff --git a/Makefile b/Makefile
index 7b1d1f9b73..1de00d50c9 100644
--- a/Makefile
+++ b/Makefile
@@ -19,7 +19,7 @@ OPEN_PR="true"
 # Force the installation of a Concrete Python version, which is very useful with nightly versions
 # /!\ WARNING /!\: This version should NEVER be a wildcard as it might create some
 # issues when trying to run it in the future.
-CONCRETE_PYTHON_VERSION="concrete-python==2.5.0"
+CONCRETE_PYTHON_VERSION="concrete-python==2.5.1"
 
 # Force the installation of Concrete Python's latest version, release-candidates included
 # CONCRETE_PYTHON_VERSION="$$(poetry run python \
diff --git a/deps_licenses/licenses_linux_user.txt b/deps_licenses/licenses_linux_user.txt
index 06973639d9..3382fd123e 100644
--- a/deps_licenses/licenses_linux_user.txt
+++ b/deps_licenses/licenses_linux_user.txt
@@ -1,6 +1,7 @@
 Name, Version, License
 GitPython, 3.1.41, BSD License
 PyYAML, 6.0.1, MIT License
+annotated-types, 0.6.0, MIT License
 anyio, 4.2.0, MIT License
 boto3, 1.34.37, Apache Software License
 botocore, 1.34.37, Apache Software License
@@ -9,11 +10,11 @@ certifi, 2023.7.22, Mozilla Public License 2.0 (MPL 2.0)
 charset-normalizer, 3.3.2, MIT License
 click, 8.1.7, BSD License
 coloredlogs, 15.0.1, MIT License
-concrete-python, 2.5, BSD-3-Clause
+concrete-python, 2.5.1, BSD-3-Clause
 dependencies, 2.0.1, BSD License
 dill, 0.3.8, BSD License
 exceptiongroup, 1.2.0, MIT License
-fastapi, 0.102.0, MIT License
+fastapi, 0.109.2, MIT License
 filelock, 3.13.1, The Unlicense (Unlicense)
 flatbuffers, 23.5.26, Apache Software License
 fsspec, 2024.2.0, BSD License
@@ -43,7 +44,8 @@ packaging, 23.2, Apache Software License; BSD License
 pluggy, 1.4.0, MIT License
 protobuf, 3.20.3, BSD-3-Clause
 psutil, 5.9.8, BSD License
-pydantic, 1.10.14, MIT License
+pydantic, 2.6.1, MIT License
+pydantic_core, 2.16.2, MIT License
 pytest, 7.4.1, MIT License
 pytest-json-report, 1.5.0, MIT
 pytest-metadata, 3.1.0, Mozilla Public License 2.0 (MPL 2.0)
@@ -60,7 +62,7 @@ skops, 0.5.0, MIT
 skorch, 0.11.0, new BSD 3-Clause
 smmap, 5.0.1, BSD License
 sniffio, 1.3.0, Apache Software License; MIT License
-starlette, 0.27.0, BSD License
+starlette, 0.36.3, BSD License
 sympy, 1.12, BSD License
 tabulate, 0.8.10, MIT License
 threadpoolctl, 3.2.0, BSD License
diff --git a/deps_licenses/licenses_mac_intel_user.txt b/deps_licenses/licenses_mac_intel_user.txt
index a4f62a220c..deb4314a80 100644
--- a/deps_licenses/licenses_mac_intel_user.txt
+++ b/deps_licenses/licenses_mac_intel_user.txt
@@ -1,6 +1,7 @@
 Name, Version, License
 GitPython, 3.1.41, BSD License
 PyYAML, 6.0.1, MIT License
+annotated-types, 0.6.0, MIT License
 anyio, 4.2.0, MIT License
 boto3, 1.34.37, Apache Software License
 botocore, 1.34.37, Apache Software License
@@ -9,11 +10,11 @@ certifi, 2023.7.22, Mozilla Public License 2.0 (MPL 2.0)
 charset-normalizer, 3.3.2, MIT License
 click, 8.1.7, BSD License
 coloredlogs, 15.0.1, MIT License
-concrete-python, 2.5, BSD-3-Clause
+concrete-python, 2.5.1, BSD-3-Clause
 dependencies, 2.0.1, BSD License
 dill, 0.3.8, BSD License
 exceptiongroup, 1.2.0, MIT License
-fastapi, 0.102.0, MIT License
+fastapi, 0.109.2, MIT License
 filelock, 3.13.1, The Unlicense (Unlicense)
 flatbuffers, 23.5.26, Apache Software License
 fsspec, 2024.2.0, BSD License
@@ -39,7 +40,8 @@ packaging, 23.2, Apache Software License; BSD License
 pluggy, 1.4.0, MIT License
 protobuf, 3.20.3, BSD-3-Clause
 psutil, 5.9.8, BSD License
-pydantic, 1.10.14, MIT License
+pydantic, 2.6.1, MIT License
+pydantic_core, 2.16.2, MIT License
 pytest, 7.4.1, MIT License
 pytest-json-report, 1.5.0, MIT
 pytest-metadata, 3.1.0, Mozilla Public License 2.0 (MPL 2.0)
@@ -56,7 +58,7 @@ skops, 0.5.0, MIT
 skorch, 0.11.0, new BSD 3-Clause
 smmap, 5.0.1, BSD License
 sniffio, 1.3.0, Apache Software License; MIT License
-starlette, 0.27.0, BSD License
+starlette, 0.36.3, BSD License
 sympy, 1.12, BSD License
 tabulate, 0.8.10, MIT License
 threadpoolctl, 3.2.0, BSD License
diff --git a/deps_licenses/licenses_mac_silicon_user.txt b/deps_licenses/licenses_mac_silicon_user.txt
index 3cc266d606..aee8c479b5 100644
--- a/deps_licenses/licenses_mac_silicon_user.txt
+++ b/deps_licenses/licenses_mac_silicon_user.txt
@@ -1,6 +1,7 @@
 Name, Version, License
 GitPython, 3.1.41, BSD License
 PyYAML, 6.0.1, MIT License
+annotated-types, 0.6.0, MIT License
 anyio, 4.2.0, MIT License
 boto3, 1.34.37, Apache Software License
 botocore, 1.34.37, Apache Software License
@@ -9,11 +10,11 @@ certifi, 2023.7.22, Mozilla Public License 2.0 (MPL 2.0)
 charset-normalizer, 3.3.2, MIT License
 click, 8.1.7, BSD License
 coloredlogs, 15.0.1, MIT License
-concrete-python, 2.5, BSD-3-Clause
+concrete-python, 2.5.1, BSD-3-Clause
 dependencies, 2.0.1, BSD License
 dill, 0.3.8, BSD License
 exceptiongroup, 1.2.0, MIT License
-fastapi, 0.102.0, MIT License
+fastapi, 0.109.2, MIT License
 filelock, 3.13.1, The Unlicense (Unlicense)
 flatbuffers, 23.5.26, Apache Software License
 fsspec, 2024.2.0, BSD License
@@ -39,7 +40,8 @@ packaging, 23.2, Apache Software License; BSD License
 pluggy, 1.4.0, MIT License
 protobuf, 3.20.3, BSD-3-Clause
 psutil, 5.9.8, BSD License
-pydantic, 1.10.14, MIT License
+pydantic, 2.6.1, MIT License
+pydantic_core, 2.16.2, MIT License
 pytest, 7.4.1, MIT License
 pytest-json-report, 1.5.0, MIT
 pytest-metadata, 3.1.0, Mozilla Public License 2.0 (MPL 2.0)
@@ -56,7 +58,7 @@ skops, 0.5.0, MIT
 skorch, 0.11.0, new BSD 3-Clause
 smmap, 5.0.1, BSD License
 sniffio, 1.3.0, Apache Software License; MIT License
-starlette, 0.27.0, BSD License
+starlette, 0.36.3, BSD License
 sympy, 1.12, BSD License
 tabulate, 0.8.10, MIT License
 threadpoolctl, 3.2.0, BSD License
@@ -65,8 +67,9 @@ tomli, 2.0.1, MIT License
 torch, 1.13.1, BSD License
 tqdm, 4.66.1, MIT License; Mozilla Public License 2.0 (MPL 2.0)
 transformers, 4.37.2, Apache Software License
-typing_extensions, 4.5.0, Python Software Foundation License
-urllib3, 2.0.7, MIT License
+typing_extensions, 4.8.0, Python Software Foundation License
+urllib3, 1.26.18, MIT License
 uvicorn, 0.21.1, BSD License
 xgboost, 1.6.2, Apache Software License
 z3-solver, 4.12.5.0, MIT License
+zipp, 3.17.0, MIT License
diff --git a/deps_licenses/licenses_mac_silicon_user.txt.md5 b/deps_licenses/licenses_mac_silicon_user.txt.md5
index 9bbd5eac4c..b034f733a8 100644
--- a/deps_licenses/licenses_mac_silicon_user.txt.md5
+++ b/deps_licenses/licenses_mac_silicon_user.txt.md5
@@ -1 +1 @@
-f709427468f5be4ee6836603495fea72
+9c3d935d7550eb54ba02c322722e34d9
diff --git a/poetry.lock b/poetry.lock
index 6dbf6d9467..092c50325a 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
 
 [[package]]
 name = "absl-py"
@@ -132,6 +132,20 @@ files = [
     {file = "alabaster-0.7.13.tar.gz", hash = "sha256:a27a4a084d5e690e16e01e03ad2b2e552c61a65469419b907243193de1a84ae2"},
 ]
 
+[[package]]
+name = "annotated-types"
+version = "0.6.0"
+description = "Reusable constraint types to use with typing.Annotated"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "annotated_types-0.6.0-py3-none-any.whl", hash = "sha256:0641064de18ba7a25dee8f96403ebc39113d0cb953a01429249d5c7564666a43"},
+    {file = "annotated_types-0.6.0.tar.gz", hash = "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"},
+]
+
+[package.dependencies]
+typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.9\""}
+
 [[package]]
 name = "anyio"
 version = "4.2.0"
@@ -815,23 +829,23 @@ test = ["pytest"]
 
 [[package]]
 name = "concrete-python"
-version = "2.5"
+version = "2.5.1"
 description = "A state-of-the-art homomorphic encryption framework"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "concrete_python-2.5-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:b9cb6f281ae0d7c5e3fe8f43584a61fbd3f8ddb640656a4ea091af012814a02e"},
-    {file = "concrete_python-2.5-cp310-cp310-macosx_11_0_x86_64.whl", hash = "sha256:f38b6873eea1f8e72ec5d5ccdcbf4f611f576213ea6ba474ecda2c7ce818ae40"},
-    {file = "concrete_python-2.5-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:fa26ec5f11c03d7fad6f7b82b0509a4db488dc921c9eb649fc1be403e27e358f"},
-    {file = "concrete_python-2.5-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:78ae8c3b4362a05515857b3c81395abcd0e199997a9993d06098875771ac7c57"},
-    {file = "concrete_python-2.5-cp311-cp311-macosx_11_0_x86_64.whl", hash = "sha256:a7979f317394f0cdbdf93be613ac433e5de3fddca3c7b17d0f3989c153fac2c7"},
-    {file = "concrete_python-2.5-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:21073c95ef3eaff7e95fe646f27b75b133ff81ed2e57d7bb33b08c19dee5211e"},
-    {file = "concrete_python-2.5-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:43145e7397a4f1ec34fae4535a76b2022609728dcf50bed340757ad6c9e9d7d9"},
-    {file = "concrete_python-2.5-cp38-cp38-macosx_11_0_x86_64.whl", hash = "sha256:2d631616c3102decd5ca071e4f2cf2d26308948fc461d14803ba73e4d01998ab"},
-    {file = "concrete_python-2.5-cp38-cp38-manylinux_2_28_x86_64.whl", hash = "sha256:f9c99ca634dd86efbef8f8baec66c3a63a3e80f759b1befebb19ba7be93bd68b"},
-    {file = "concrete_python-2.5-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:8ccad39025a35ebc234f2c086bd18033eca478d97e8e429b6855b65495aa0e11"},
-    {file = "concrete_python-2.5-cp39-cp39-macosx_11_0_x86_64.whl", hash = "sha256:4e2323982fed6168d09b9648e6feebdadbc236051afc398b2b59f9cb177b757e"},
-    {file = "concrete_python-2.5-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:9c168f18b3c6a1938bdb6306b7be2ffd6d2076e45cfd4935b7a842f0b72d1091"},
+    {file = "concrete_python-2.5.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:7251d8ee55c9773dc9bcb771b286200068cbc70a352969489ba5a8d40ccb99c0"},
+    {file = "concrete_python-2.5.1-cp310-cp310-macosx_11_0_x86_64.whl", hash = "sha256:235bf2b65fa9a5510e46b47155fda75a52e2dce018b9b553b1ee0b4496d12335"},
+    {file = "concrete_python-2.5.1-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:6cef83fceea20aa6806d24e96784394f759c7cbd734f194ef8efb2fff5619198"},
+    {file = "concrete_python-2.5.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:bf13c62a46c5a5a249d749a34f5671d080a767a7996bf4c0878aeaaddbd672ab"},
+    {file = "concrete_python-2.5.1-cp311-cp311-macosx_11_0_x86_64.whl", hash = "sha256:a9953917ac3eecbb2424f2efd8dfb9cbff02b98a7e8c140684f87112ad1a125d"},
+    {file = "concrete_python-2.5.1-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:34f8774fd68bfc9e281c51f4766ea4739ff869ceab589fac7976a1b6825a2959"},
+    {file = "concrete_python-2.5.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:ad0126a84b15500d0aeea480057df45ab3aa8628228ef726a3a2f254f7a6ecd6"},
+    {file = "concrete_python-2.5.1-cp38-cp38-macosx_11_0_x86_64.whl", hash = "sha256:0ebdf576daedc5b3d487ea9217c31ffca4f6bb0dd633d00c50f095373ce004c4"},
+    {file = "concrete_python-2.5.1-cp38-cp38-manylinux_2_28_x86_64.whl", hash = "sha256:67a89c6030374d356e0164fba5f8779ac1acf2e7994d2fd0129c7218b3f6890f"},
+    {file = "concrete_python-2.5.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:2482e4eb518038a7f4f5c4fa647fe0ffce0acb49c3b3b657a3e49206b2856c86"},
+    {file = "concrete_python-2.5.1-cp39-cp39-macosx_11_0_x86_64.whl", hash = "sha256:5b465e7181eab814b0a9bd1d1215e2bdde89e1ba7c7bf068081664003c64fcca"},
+    {file = "concrete_python-2.5.1-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:0ec8dbcdf7ce225aa3e2b72c82aa79e340dc6595b1c0e392b93fe9eb9dd72f4c"},
 ]
 
 [package.dependencies]
@@ -843,7 +857,8 @@ torch = ">=1.13"
 z3-solver = ">=4.12"
 
 [package.extras]
-dev = ["auditwheel (==5.3.0)", "black (==23.1.0)", "delocate (==0.10.4)", "isort (==5.12.0)", "mypy (==1.1.1)", "pybind11 (==2.10.4)", "pydocstyle (==6.3.0)", "pylint (==2.17.1)", "pytest (==7.2.2)", "pytest-cov (==4.0.0)", "pytest-randomly (==3.15.0)", "pytest-xdist (==3.2.1)", "ruff (==0.0.259)", "wheel (==0.40.0)"]
+dev = ["auditwheel (==5.3.0)", "black (==23.1.0)", "delocate (==0.10.4)", "isort (==5.12.0)", "matplotlib (>=3.7)", "mypy (==1.1.1)", "pillow (>=10.2)", "pybind11 (==2.10.4)", "pydocstyle (==6.3.0)", "pygraphviz (>=1.11)", "pylint (==2.17.1)", "pytest (==7.2.2)", "pytest-cov (==4.0.0)", "pytest-randomly (==3.15.0)", "pytest-xdist (==3.2.1)", "ruff (==0.0.259)", "wheel (==0.40.0)"]
+full = ["matplotlib (>=3.7)", "pillow (>=10.2)", "pygraphviz (>=1.11)"]
 
 [[package]]
 name = "contourpy"
@@ -1246,22 +1261,22 @@ tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipyth
 
 [[package]]
 name = "fastapi"
-version = "0.102.0"
+version = "0.109.2"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "fastapi-0.102.0-py3-none-any.whl", hash = "sha256:34db27d0af54ee0d92c540e83c6ee6a11de93f63bbdf73fda54fff9a10c52569"},
-    {file = "fastapi-0.102.0.tar.gz", hash = "sha256:e3652cb9bdf4df1dedda4fce9454e9f75a8c969b5cdd3faf1bd5c6f5d2daab08"},
+    {file = "fastapi-0.109.2-py3-none-any.whl", hash = "sha256:2c9bab24667293b501cad8dd388c05240c850b58ec5876ee3283c47d6e1e3a4d"},
+    {file = "fastapi-0.109.2.tar.gz", hash = "sha256:f3817eac96fe4f65a2ebb4baa000f394e55f5fccdaf7f75250804bc58f354f73"},
 ]
 
 [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 = ">=0.27.0,<0.28.0"
-typing-extensions = ">=4.5.0"
+starlette = ">=0.36.3,<0.37.0"
+typing-extensions = ">=4.8.0"
 
 [package.extras]
-all = ["email-validator (>=2.0.0)", "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 (>=0.0.5)", "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)"]
+all = ["email-validator (>=2.0.0)", "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)"]
 
 [[package]]
 name = "fastjsonschema"
@@ -3379,52 +3394,49 @@ files = [
 
 [[package]]
 name = "mypy"
-version = "0.991"
+version = "1.8.0"
 description = "Optional static typing for Python"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "mypy-0.991-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7d17e0a9707d0772f4a7b878f04b4fd11f6f5bcb9b3813975a9b13c9332153ab"},
-    {file = "mypy-0.991-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:0714258640194d75677e86c786e80ccf294972cc76885d3ebbb560f11db0003d"},
-    {file = "mypy-0.991-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:0c8f3be99e8a8bd403caa8c03be619544bc2c77a7093685dcf308c6b109426c6"},
-    {file = "mypy-0.991-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc9ec663ed6c8f15f4ae9d3c04c989b744436c16d26580eaa760ae9dd5d662eb"},
-    {file = "mypy-0.991-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:4307270436fd7694b41f913eb09210faff27ea4979ecbcd849e57d2da2f65305"},
-    {file = "mypy-0.991-cp310-cp310-win_amd64.whl", hash = "sha256:901c2c269c616e6cb0998b33d4adbb4a6af0ac4ce5cd078afd7bc95830e62c1c"},
-    {file = "mypy-0.991-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:d13674f3fb73805ba0c45eb6c0c3053d218aa1f7abead6e446d474529aafc372"},
-    {file = "mypy-0.991-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:1c8cd4fb70e8584ca1ed5805cbc7c017a3d1a29fb450621089ffed3e99d1857f"},
-    {file = "mypy-0.991-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:209ee89fbb0deed518605edddd234af80506aec932ad28d73c08f1400ef80a33"},
-    {file = "mypy-0.991-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:37bd02ebf9d10e05b00d71302d2c2e6ca333e6c2a8584a98c00e038db8121f05"},
-    {file = "mypy-0.991-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:26efb2fcc6b67e4d5a55561f39176821d2adf88f2745ddc72751b7890f3194ad"},
-    {file = "mypy-0.991-cp311-cp311-win_amd64.whl", hash = "sha256:3a700330b567114b673cf8ee7388e949f843b356a73b5ab22dd7cff4742a5297"},
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+    {file = "pydantic_core-2.16.2.tar.gz", hash = "sha256:0ba503850d8b8dcc18391f10de896ae51d37fe5fe43dbfb6a35c5c5cad271a06"},
+]
+
+[package.dependencies]
+typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
 [[package]]
 name = "pydocstyle"
@@ -6321,13 +6391,13 @@ tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
 
 [[package]]
 name = "starlette"
-version = "0.27.0"
+version = "0.36.3"
 description = "The little ASGI library that shines."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "starlette-0.27.0-py3-none-any.whl", hash = "sha256:918416370e846586541235ccd38a474c08b80443ed31c578a418e2209b3eef91"},
-    {file = "starlette-0.27.0.tar.gz", hash = "sha256:6a6b0d042acb8d469a01eba54e9cda6cbd24ac602c4cd016723117d6a7e73b75"},
+    {file = "starlette-0.36.3-py3-none-any.whl", hash = "sha256:13d429aa93a61dc40bf503e8c801db1f1bca3dc706b10ef2434a36123568f044"},
+    {file = "starlette-0.36.3.tar.gz", hash = "sha256:90a671733cfb35771d8cc605e0b679d23b992f8dcfad48cc60b38cb29aeb7080"},
 ]
 
 [package.dependencies]
@@ -6335,7 +6405,7 @@ anyio = ">=3.4.0,<5"
 typing-extensions = {version = ">=3.10.0", markers = "python_version < \"3.10\""}
 
 [package.extras]
-full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart", "pyyaml"]
+full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart (>=0.0.7)", "pyyaml"]
 
 [[package]]
 name = "sympy"
@@ -7112,13 +7182,13 @@ files = [
 
 [[package]]
 name = "typing-extensions"
-version = "4.5.0"
-description = "Backported and Experimental Type Hints for Python 3.7+"
+version = "4.8.0"
+description = "Backported and Experimental Type Hints for Python 3.8+"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "typing_extensions-4.5.0-py3-none-any.whl", hash = "sha256:fb33085c39dd998ac16d1431ebc293a8b3eedd00fd4a32de0ff79002c19511b4"},
-    {file = "typing_extensions-4.5.0.tar.gz", hash = "sha256:5cb5f4a79139d699607b3ef622a1dedafa84e115ab0024e0d9c044a9479ca7cb"},
+    {file = "typing_extensions-4.8.0-py3-none-any.whl", hash = "sha256:8f92fc8806f9a6b641eaa5318da32b44d401efaac0f6678c9bc448ba3605faa0"},
+    {file = "typing_extensions-4.8.0.tar.gz", hash = "sha256:df8e4339e9cb77357558cbdbceca33c303714cf861d1eef15e1070055ae8b7ef"},
 ]
 
 [[package]]
diff --git a/pyproject.toml b/pyproject.toml
index 3cc440062f..147371f58f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -34,13 +34,13 @@ readme = "README.md"
 # Investigate if it is better to fix specific versions or use lower and upper bounds  
 # FIXME: https://github.com/zama-ai/concrete-ml-internal/issues/2665
 python = ">=3.8.1,<3.11"
-concrete-python = "2.5.0"
+concrete-python = "2.5.1"
 setuptools = "65.6.3"
 skops = {version = "0.5.0"}
 xgboost = "1.6.2"
 skorch = "0.11.0"
 torch = "1.13.1"
-typing-extensions = "4.5.0"
+typing-extensions = "4.8.0"
 brevitas = "0.8.0"
 onnxoptimizer = "0.3.10"
 onnxruntime = "1.13.1"
@@ -53,7 +53,7 @@ protobuf = "3.20.3"
 
 # Deployment
 boto3 = "^1.23.5"
-fastapi = "^0.102.0"
+fastapi = "^0.109.1"
 uvicorn = "^0.21.0"
 tqdm = "^4.64.1"
 transformers = "^4.36.0"
@@ -70,7 +70,7 @@ pylint = "^2.13.0"
 pytest = "7.4.1"
 pytest-cov = "^4.1.0"
 pytest_codeblocks = "^0.14.0"
-mypy = "^0.991"
+mypy = "^1.8.0"
 pydocstyle = "^6.1.1"
 python-semantic-release = "^7.27.0"
 semver = "^2.13.0"
diff --git a/src/concrete/ml/quantization/base_quantized_op.py b/src/concrete/ml/quantization/base_quantized_op.py
index 1beac84122..385295e07c 100644
--- a/src/concrete/ml/quantization/base_quantized_op.py
+++ b/src/concrete/ml/quantization/base_quantized_op.py
@@ -20,7 +20,14 @@
     UniformQuantizationParameters,
 )
 
-ONNXOpInputOutputType = Union[numpy.ndarray, QuantizedArray, None]
+ONNXOpInputOutputType = Union[
+    numpy.ndarray,
+    QuantizedArray,
+    None,
+    bool,
+    int,
+    float,
+]
 
 ALL_QUANTIZED_OPS: Set[Type] = set()
 
@@ -969,7 +976,8 @@ def cnp_round(
 
             # Update the lsbs_to_remove value in the dictionary
             self.lsbs_to_remove[rounding_operation_id] = max(
-                self.lsbs_to_remove.get(rounding_operation_id, 0), computed_lsbs_to_remove
+                self.lsbs_to_remove.get(rounding_operation_id, 0),
+                computed_lsbs_to_remove,
             )
 
         # Rounding logic
diff --git a/src/concrete/ml/quantization/post_training.py b/src/concrete/ml/quantization/post_training.py
index 0225085075..f90fb868cd 100644
--- a/src/concrete/ml/quantization/post_training.py
+++ b/src/concrete/ml/quantization/post_training.py
@@ -400,7 +400,9 @@ def _calibrate_layers_activation(
         )
 
     @abstractmethod
-    def _process_initializer(self, n_bits: int, values: numpy.ndarray) -> QuantizedArray:
+    def _process_initializer(
+        self, n_bits: int, values: Union[numpy.ndarray, float, int, bool]
+    ) -> Union[QuantizedArray, RawOpOutput]:
         """Transform a constant tensor according to the model conversion mode.
 
         The values supplied are floating point values that will be quantized.
@@ -410,7 +412,8 @@ def _process_initializer(self, n_bits: int, values: numpy.ndarray) -> QuantizedA
             values (numpy.ndarray): Float values that initialize this tensor
 
         Returns:
-            QuantizedArray: a quantized tensor with integer values on n_bits bits
+            Union[QuantizedArray, RawOpOutput]: a quantized tensor with integer
+                values on n_bits bits
         """
 
     @abstractmethod
@@ -535,14 +538,13 @@ def _quantize_layers(self, *input_calibration_data: numpy.ndarray):
                         curr_cst_inputs[input_idx] = value
                     else:
                         # Initializers are ndarray or scalar
-                        assert value is not None
-                        assert isinstance(value, numpy.ndarray) or numpy.isscalar(value)
+                        assert isinstance(value, (numpy.ndarray, float, int, bool))
                         curr_cst_inputs[input_idx] = self._process_initializer(
                             self.n_bits_op_weights, value
                         )
                 else:
                     # Initializers are ndarray or scalar
-                    assert isinstance(value, numpy.ndarray) or numpy.isscalar(value)
+                    assert isinstance(value, (numpy.ndarray, float, int, bool))
                     curr_cst_inputs[input_idx] = value
 
             has_variable_inputs = (len(curr_inputs) - len(curr_cst_inputs)) > 0
@@ -865,7 +867,9 @@ def _process_layer(
             True, quantized_op, *calibration_data, quantizers=quantizers
         )
 
-    def _process_initializer(self, n_bits: int, values: numpy.ndarray):
+    def _process_initializer(
+        self, n_bits: int, values: Union[numpy.ndarray, float, int, bool]
+    ) -> Union[QuantizedArray, RawOpOutput]:
         """Quantize a network constant tensor (a weights tensor).
 
         The values supplied are floating point values that will be quantized.
@@ -875,13 +879,14 @@ def _process_initializer(self, n_bits: int, values: numpy.ndarray):
             values (numpy.ndarray): Float values that initialize this tensor
 
         Returns:
-            QuantizedArray: a quantized tensor with integer values on n_bits bits
+            Union[QuantizedArray, RawOpOutput]: a quantized tensor with integer
+                values on n_bits bits
         """
 
         if isinstance(values, numpy.ndarray) and numpy.issubdtype(values.dtype, numpy.integer):
             return values.view(RawOpOutput)
 
-        assert isinstance(values, (numpy.ndarray, float))
+        assert isinstance(values, numpy.ndarray)
         is_signed = is_symmetric = self._check_distribution_is_symmetric_around_zero(values)
 
         return QuantizedArray(
@@ -990,7 +995,9 @@ def _process_layer(
             False, quantized_op, *calibration_data, quantizers=quantizers
         )
 
-    def _process_initializer(self, n_bits: int, values: numpy.ndarray):
+    def _process_initializer(
+        self, n_bits: int, values: Union[numpy.ndarray, float, int, bool]
+    ) -> Union[QuantizedArray, RawOpOutput]:
         """Process an already quantized weight tensor.
 
         The values supplied are in floating point, but are discrete, in the sense
@@ -1003,8 +1010,8 @@ def _process_initializer(self, n_bits: int, values: numpy.ndarray):
             values (numpy.ndarray): Discrete float values that initialize this tensor
 
         Returns:
-            QuantizedArray: a quantized tensor with integer values on n_bits bits and with alpha as
-                the scaling factor.
+            Union[QuantizedArray, RawOpOutput]: a quantized tensor with integer values on
+                n_bits bits and with alpha as the scaling factor.
         """
 
         # Assume that integer initializer op inputs are raw values that should not be quantized
diff --git a/src/concrete/ml/quantization/quantizers.py b/src/concrete/ml/quantization/quantizers.py
index 9369e1e385..caae2ad766 100644
--- a/src/concrete/ml/quantization/quantizers.py
+++ b/src/concrete/ml/quantization/quantizers.py
@@ -832,7 +832,7 @@ class QuantizedArray:
     def __init__(
         self,
         n_bits,
-        values: Optional[numpy.ndarray],
+        values: Union[None, float, int, numpy.ndarray],
         value_is_float: bool = True,
         options: Optional[QuantizationOptions] = None,
         stats: Optional[MinMaxQuantizationStats] = None,
@@ -873,9 +873,9 @@ def __eq__(self, other):
 
     def _values_setup(
         self,
-        values: numpy.ndarray,
+        values: Union[numpy.ndarray, float, int],
         value_is_float: bool,
-        options: QuantizationOptions = None,
+        options: Optional[QuantizationOptions] = None,
         stats: Optional[MinMaxQuantizationStats] = None,
         params: Optional[UniformQuantizationParameters] = None,
     ):
@@ -898,12 +898,15 @@ def _values_setup(
                     f"got {values.dtype}: {values}",
                 )
 
-            self.values = deepcopy(values) if isinstance(values, numpy.ndarray) else values
+            assert isinstance(values, (numpy.ndarray, float))
+            self.values = (
+                deepcopy(values) if isinstance(values, numpy.ndarray) else numpy.array(values)
+            )
 
             # If no stats are provided, compute them.
             # Note that this cannot be done during tracing
             if stats is None:
-                self.quantizer.compute_quantization_stats(values)
+                self.quantizer.compute_quantization_stats(self.values)
 
             # If the quantization params are not provided, compute them
             # Note that during tracing, this does not use the tracer in any way and just
@@ -929,7 +932,10 @@ def _values_setup(
                     "when int/uint was required",
                 )
 
-            self.qvalues = deepcopy(values) if isinstance(values, numpy.ndarray) else values
+            assert isinstance(values, (numpy.ndarray, int, Tracer))
+            self.qvalues = (
+                deepcopy(values) if isinstance(values, numpy.ndarray) else numpy.array(values)
+            )
 
             # Populate self.values
             self.dequant()
@@ -994,7 +1000,7 @@ def update_values(self, values: numpy.ndarray) -> numpy.ndarray:
         Returns:
             qvalues (numpy.ndarray): Corresponding qvalues
         """
-        self.values = deepcopy(values) if isinstance(values, numpy.ndarray) else values
+        self.values = deepcopy(values) if isinstance(values, numpy.ndarray) else numpy.array(values)
         self.quant()
         return self.qvalues
 
diff --git a/src/concrete/ml/sklearn/qnn.py b/src/concrete/ml/sklearn/qnn.py
index 1bbbbcfd57..2981a66de6 100644
--- a/src/concrete/ml/sklearn/qnn.py
+++ b/src/concrete/ml/sklearn/qnn.py
@@ -141,7 +141,8 @@ def __init__(
         virtual_params = kwargs.pop("virtual_params_", {})
 
         self._kwargs = kwargs
-        vars(self).update(kwargs)
+        for key, value in kwargs.items():
+            setattr(self, key, value)
 
         self.history_ = history
         self.initialized_ = initialized
@@ -448,7 +449,8 @@ def __init__(
         virtual_params = kwargs.pop("virtual_params_", {})
 
         self._kwargs = kwargs
-        vars(self).update(kwargs)
+        for key, value in kwargs.items():
+            setattr(self, key, value)
 
         self.history_ = history
         self.initialized_ = initialized