diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index eee73f9..0ee742d 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -17,13 +17,13 @@ jobs:
         with:
           update-conda: true
           python-version: ${{ matrix.python-version }}
-          conda-channels: defaults, conda-forge
-      - name: Conda env configuration with mamba
+          conda-channels: conda-forge
+      - name: Install locked Ansible environment
         run: |
-            conda install mamba
-            mamba env create -f environment.yml
+            conda create --yes --name duck --file linux-64.spec
             source activate duck
             pip install -e ".[dev]"
+            python -m pip check
       - name: Test with conda
         run: |
             source activate duck
@@ -33,4 +33,4 @@ jobs:
         run: |
             source activate duck
             flake8 duck
-        if: matrix.python-version == 3.10
+        if: matrix.python-version == '3.10'
diff --git a/MANIFEST.in b/MANIFEST.in
index 10b740b..04ab81f 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -1,5 +1,7 @@
 include Makefile
 include *.txt
+include *.spec
+include environment.yml
 include *.rst
 include *.md
 include tox.ini
diff --git a/docs/source/dev_guide.rst b/docs/source/dev_guide.rst
index 7f508a1..ed86a09 100644
--- a/docs/source/dev_guide.rst
+++ b/docs/source/dev_guide.rst
@@ -35,7 +35,7 @@ First activate the ``duck`` Conda environment and install ``pytest``.
 
 .. code-block:: console
 
-   $ source activate duck
+   $ conda activate duck
    $ pip install -r requirements_dev.txt  # if not already installed
    OR
    $ make develop
@@ -79,10 +79,17 @@ Update the Conda specification file to build identical environments_ on a specif
 .. code-block:: console
 
   $ conda env create -f environment.yml
-  $ source activate duck
+  $ conda activate duck
   $ make clean
   $ make install
-  $ conda list -n duck --explicit > spec-file.txt
+  $ conda install -c conda-forge gunicorn gevent psycopg2=2.9.12 drmaa=0.7.9 dill pytest-cov
+  $ conda list -n duck --explicit --md5 > linux-64.spec
+
+Include the current ``wps_conda_packages`` from the Ansible playbook before
+exporting; the command above reflects the deployment packages at this update.
+Commit ``linux-64.spec`` together with changes to ``environment.yml`` and
+``requirements.txt``. The spec contains Conda packages only; PyWPS, CRAI and its models
+are installed separately by pip.
 
 .. _environments: https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#building-identical-conda-environments
 
diff --git a/docs/source/installation.rst b/docs/source/installation.rst
index 83793db..9020ab3 100644
--- a/docs/source/installation.rst
+++ b/docs/source/installation.rst
@@ -29,7 +29,7 @@ Create Conda environment named `duck`:
 .. code-block:: console
 
    $ conda env create -f environment.yml
-   $ source activate duck
+   $ conda activate duck
 
 Install Duck app:
 
@@ -108,6 +108,39 @@ Use Ansible to deploy Duck on your System
 -----------------------------------------
 
 Use the `Ansible playbook`_ for PyWPS to deploy Duck on your system.
+The Linux x86_64 deployment environment is locked in ``linux-64.spec``, replacing
+``spec-list.txt``. It includes the Conda runtime dependencies and the playbook's
+Gunicorn, gevent, psycopg2 2.9.12, DRMAA 0.7.9, dill and test packages.
 
+Set these inventory variables, including any service-specific overrides:
+
+.. code-block:: yaml
+
+   conda_env_use_spec: true
+   conda_env_spec_file: linux-64.spec
+
+Run a full environment deployment so the new packages are installed, rather than
+only updating application code. To install manually on Linux x86_64:
+
+.. code-block:: console
+
+   $ conda create -n duck --file linux-64.spec
+   $ conda activate duck
+   $ python -m pip install .
+
+PyWPS is installed by pip, along with the CRAI application and pretrained models,
+through ``requirements.txt``. These packages are not in the Conda spec.
+``environment.yml`` also installs PyWPS through its pip section. This avoids a
+Conda GDAL/PROJ conflict between Python 3.10's geospatial builds and the playbook's
+new PostgreSQL libraries; PyWPS's pip dependencies provide binary wheels instead.
+
+The CRAI Git dependencies' upstream branches are not frozen by the spec. Both
+currently require setuptools 59.5.0, so that pin is retained. Its Conda builds support Python
+up to 3.10, which determines the Python version for this environment.
+
+The environment uses Python 3.10, PyWPS 4.7 and CPU-only PyTorch 2.5 with
+Torchvision 0.20. Duck explicitly selects CPU inference. The PyTorch upper bound
+preserves the checkpoint-loading behavior used by CRAI. NumPy stays on 1.x.
+For other platforms, use ``environment.yml`` before installing Duck with pip.
 
 .. _Ansible playbook: http://ansible-wps-playbook.readthedocs.io/en/latest/index.html
diff --git a/duck/clintai.py b/duck/clintai.py
index 338c5e3..9949132 100644
--- a/duck/clintai.py
+++ b/duck/clintai.py
@@ -52,7 +52,7 @@ def run(dataset, dataset_name, variable_name, outdir, update_status):
         eval_name=dataset.stem,
         data_name=dataset.name,
         data_type=variable_name,
-        eval_parameters=info_models[dataset_name]["eval-parameters"])
+        eval_parameters=info_models[dataset_name]["eval_parameters"])
     # print(f"written cfg {cfg_file}")
     try:
         evaluate(arg_file=cfg_file.as_posix(), prog_func=update_status)
diff --git a/duck/processes/wps_clintai.py b/duck/processes/wps_clintai.py
index f8885f9..75418bc 100644
--- a/duck/processes/wps_clintai.py
+++ b/duck/processes/wps_clintai.py
@@ -33,7 +33,7 @@ def __init__(self):
                          abstract="Enter a URL pointing to a NetCDF file with missing values.",
                          min_occurs=1,
                          max_occurs=1,
-                         default="https://www.metoffice.gov.uk/hadobs/hadcrut5/data/current/non-infilled/HadCRUT.5.0.1.0.anomalies.ensemble_mean.nc", # noqa
+                         default="https://www.metoffice.gov.uk/hadobs/hadcrut5/data/HadCRUT.5.0.2.0/non-infilled/HadCRUT.5.0.2.0.anomalies.ensemble_mean.nc", # noqa
                          supported_formats=[FORMATS.NETCDF, FORMATS.ZIP]),
             LiteralInput('variable_name', 'Variable name', data_type='string',
                          abstract='Enter here the variable name to be infilled.',
diff --git a/environment-docs.yml b/environment-docs.yml
index ad73bdc..14806e3 100644
--- a/environment-docs.yml
+++ b/environment-docs.yml
@@ -2,9 +2,10 @@
 name: duck-docs
 channels:
 - conda-forge
-- defaults
+- nodefaults
 dependencies:
-- pywps>=4.4
+- python=3.10
+- pywps>=4.7,<4.8
 - sphinx
 - nbsphinx
 - ipython
diff --git a/environment.yml b/environment.yml
index 36cf0fb..06beec9 100644
--- a/environment.yml
+++ b/environment.yml
@@ -1,31 +1,38 @@
 name: duck
 channels:
-- conda-forge
-- pytorch
+  - conda-forge
+  - nodefaults
 dependencies:
-- pip
-- python>=3.7
-- pywps>=4.5.1,<4.6
-- jinja2
-- click
-- psutil
-# tests
-- pytest
-- requests
-- flake8
-# clint ai
-- pytorch>=1.11.0
-- tqdm>=4.64.0
-- torchvision>=0.12.0
-- numpy>=1.21.6
-- matplotlib>=3.5.1
-- tensorboardX>=2.5
-- tensorboard>=2.9.0
-- xarray>=2022.3.0
-- dask>=2022.7.0
-- netcdf4>=1.5.8
-- setuptools==59.5.0
-- xesmf>=0.6.2
-# plot
-- cartopy>=0.20.2
-- numba>=0.55.1
+  # CRAI requires setuptools 59.5; its Conda builds support Python <=3.10.
+  - python=3.10
+  - pip
+  - jinja2
+  - click
+  - psutil
+  - requests
+  # CRAI runs inference on the CPU; retain legacy checkpoint loading behavior.
+  - pytorch>=2.5,<2.6
+  - torchvision>=0.20,<0.21
+  - pytorch-cpu
+  # Match PyTorch 2.5.1 wheel metadata when pip installs CRAI.
+  - sympy=1.13.1
+  - torchmetrics>=0.11.2,<0.12
+  - tqdm>=4.64
+  - numpy>=1.26,<2
+  - matplotlib-base>=3.8,<3.9
+  - tensorboardx>=2.5
+  - tensorboard>=2.9
+  - xarray>=2023.1,<2025
+  - dask>=2023.1,<2025
+  - netcdf4>=1.6
+  # Required by both upstream CRAI packages' build metadata.
+  - setuptools=59.5.0
+  - xesmf>=0.8,<0.9
+  - cartopy>=0.22,<0.24
+  - numba>=0.59,<0.61
+  # PyWPS uses pip wheels to avoid the Conda GDAL/PROJ conflict on Python 3.10.
+  - pip:
+      - pywps>=4.7,<4.8
+  # tests
+  - pytest>=6,<9
+  - flake8
diff --git a/linux-64.spec b/linux-64.spec
new file mode 100644
index 0000000..f100d81
--- /dev/null
+++ b/linux-64.spec
@@ -0,0 +1,226 @@
+# Linux x86_64 deployment environment (resolved 2026-10-09).
+# Sources: environment.yml plus ansible-wps-playbook wps_conda_packages.
+# Target virtual packages: Linux 5.14, glibc 2.17 (CPU-only).
+# PyWPS, CRAI and pretrained models are installed by pip install .
+# Create: conda create --name duck --file linux-64.spec
+# platform: linux-64
+@EXPLICIT
+https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.7.22-hbd8a1cb_0.conda#0f51e2391ade309db462a55611263e9c
+https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.2-h25fd6f3_3.conda#0de0122d9570a8ab637c6b73db268389
+https://conda.anaconda.org/conda-forge/linux-64/llvm-openmp-23.1.3-h7148c6a_0.conda#373b64bc33e184b56f4f168bd7c2b733
+https://conda.anaconda.org/conda-forge/noarch/python_abi-3.10-9_cp310.conda#3bb52811c66f1f07377537cc82ccb093
+https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda#fcb489df604d100968b737f2cb6076c6
+https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-8_kmp_llvm.conda#b4d1b93dd1dab4eea23395fd5e5b357d
+https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_7.conda#aa459086047c0e5e27023ab19f8cb86a
+https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.46.1-default_hbd61a6d_102.conda#449500f2c089da11c40f5c21312e3e07
+https://conda.anaconda.org/conda-forge/linux-64/libgcc-16.2.0-ha9f2e26_7.conda#735629b400b70eeab21a2ba8f5b1c2ce
+https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_10.conda#e675fabcf81499adc7edf58124fb1e01
+https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.34.8-hebe6cf0_2.conda#3ad2b403be8fc5612b9159e2ce621f69
+https://conda.anaconda.org/conda-forge/linux-64/giflib-5.2.2-ha257d8a_1.conda#bd7c3a8586ed0101f094962100d30a63
+https://conda.anaconda.org/conda-forge/linux-64/keyutils-1.6.3-h7cc23a3_1.conda#ba55d1b89fd7775e67de8291029b4059
+https://conda.anaconda.org/conda-forge/linux-64/libbrotlicommon-1.2.0-h39a168f_3.conda#7a2499a177753582fb7ae7e9dc4a908a
+https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.25-hd45a770_1.conda#40f9b31aa9cf007789867df0decd0492
+https://conda.anaconda.org/conda-forge/linux-64/libev-4.33-h280c20c_3.conda#7bc31538d6e3fb349e897353969237ec
+https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.8.5-hd2095e1_0.conda#72cfd2b95b0540247220b42f58a148d7
+https://conda.anaconda.org/conda-forge/linux-64/libffi-3.7.0-h81df57d_1.conda#6525a0b06aa4fd390795f0740636a9dd
+https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-16.2.0-h69a702a_7.conda#2005515ac9340f816fb2ac7e83afe553
+https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-16.2.0-h6b99dfc_7.conda#7719ed7be38ad8c492c4bd5cc2bce0c4
+https://conda.anaconda.org/conda-forge/linux-64/libiconv-1.18-h0cb94f2_3.conda#f92233bf33e24a25668bb2119e2c51f9
+https://conda.anaconda.org/conda-forge/linux-64/libjpeg-turbo-3.2.0-hb03c661_1.conda#898d1c9793eaa52efc4727bd84d2e39a
+https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.3-hb03c661_1.conda#1390b7c5ac0b1d8e447bc5efa6d3c8c2
+https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.1-hb9d3cd8_1.conda#d864d34357c3b65a4b731f78c0801dc4
+https://conda.anaconda.org/conda-forge/linux-64/libntlm-1.8-hb9d3cd8_0.conda#7c7927b404672409d9917d49bff5f2d6
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+https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.6-hdb14827_1.conda#ee6c0cd80a60961a1f48aa3e0b91f986
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+https://conda.anaconda.org/conda-forge/linux-64/numba-0.60.0-py310h5dc88bb_0.conda#73e2e2c0ffad216572ce01952ff0099c
+https://conda.anaconda.org/conda-forge/linux-64/pandas-2.3.3-py310h0158d43_2.conda#0610ed073acc4737d036125a5a6dbae2
+https://conda.anaconda.org/conda-forge/linux-64/pytorch-2.5.1-cpu_mkl_py310_h8ec2884_117.conda#e963dc0d636c77076b1d0b7d3bfa19ac
+https://conda.anaconda.org/conda-forge/linux-64/shapely-2.1.2-py310hc8bbb35_2.conda#0937b0e88a24c82e02d5b714acc9957c
+https://conda.anaconda.org/conda-forge/noarch/tensorboard-2.20.0-pyhe01879c_1.conda#14deadb7c56c11ad448cad15f3bf4b03
+https://conda.anaconda.org/conda-forge/noarch/tensorboardx-2.6.2.2-pyhd8ed1ab_1.conda#12edb3e9c07f9fac457d9acb27eb19c8
+https://conda.anaconda.org/conda-forge/noarch/dask-2023.3.0-pyhd8ed1ab_0.conda#aab5cea04004860e804de5bb3337f183
+https://conda.anaconda.org/conda-forge/linux-64/matplotlib-base-3.8.4-py310hef631a5_2.conda#b3fa3fc2a0fa8b53b913c94297b12e27
+https://conda.anaconda.org/conda-forge/linux-64/netcdf4-1.7.4-nompi_py310h21e55d4_104.conda#795e0bf8ab211cd6894fa8fa4067daa0
+https://conda.anaconda.org/conda-forge/linux-64/pytorch-cpu-2.5.1-cpu_mkl_hc60beec_117.conda#ed8f1b69584256350470a1b1187b9412
+https://conda.anaconda.org/conda-forge/noarch/sparse-0.17.0-pyhcf101f3_0.conda#1b59de14a7e5888f939611e1fe329e00
+https://conda.anaconda.org/conda-forge/noarch/torchmetrics-0.11.4-pyhd8ed1ab_0.conda#480cb2b6d502003e937d9e4326bc398f
+https://conda.anaconda.org/conda-forge/linux-64/torchvision-0.20.1-cpu_py310_he61ac84_6.conda#587376c2f3fdf9c6d0561e8a794ef881
+https://conda.anaconda.org/conda-forge/noarch/xarray-2024.3.0-pyhd8ed1ab_0.conda#772d7ee42b65d0840130eabd5bd3fc17
+https://conda.anaconda.org/conda-forge/linux-64/cartopy-0.23.0-py310h5eaa309_2.conda#7eecc124f1b4ebd547b0e5f2ad6c9e2f
+https://conda.anaconda.org/conda-forge/noarch/cf_xarray-0.10.6-pyhd8ed1ab_0.conda#ba7f685033288dd0baf3586500dc61b2
+https://conda.anaconda.org/conda-forge/noarch/xesmf-0.8.10-pyhd8ed1ab_0.conda#633873a69cdd56334c394f2299943d54
diff --git a/requirements.txt b/requirements.txt
index 255f252..141baef 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,8 +1,24 @@
 click
 jinja2
 psutil
-pywps>=4.5.1,<4.6
-# CRAI
-# climatereconstructionAI>=0.1.0
+pywps>=4.7,<4.8
+# Keep pip installs aligned with the Conda inference environment.
+torch>=2.5,<2.6
+torchvision>=0.20,<0.21
+torchmetrics>=0.11.2,<0.12
+tqdm>=4.64
+numpy>=1.26,<2
+matplotlib>=3.8,<3.9
+tensorboardX>=2.5
+tensorboard>=2.9
+xarray>=2023.1,<2025
+dask>=2023.1,<2025
+netCDF4>=1.6
+setuptools==59.5.0
+xesmf>=0.8,<0.9
+cartopy>=0.22,<0.24
+numba>=0.59,<0.61
+requests
+# CRAI and its pretrained models are installed by pip, after Conda.
 craimodels @ git+https://github.com/climateintelligence/craimodels@main#egg=craimodels
 climatereconstructionAI @ git+https://github.com/FREVA-CLINT/climatereconstructionAI@clint#egg=climatereconstructionAI
diff --git a/requirements_dev.txt b/requirements_dev.txt
index dd75b60..f521742 100644
--- a/requirements_dev.txt
+++ b/requirements_dev.txt
@@ -1,4 +1,4 @@
-pytest>=6.0
+pytest>=6,<9
 pytest-runner
 pytest-cov
 flake8
diff --git a/setup.py b/setup.py
index 9e66302..588c3cc 100644
--- a/setup.py
+++ b/setup.py
@@ -9,7 +9,7 @@
 here = os.path.abspath(os.path.dirname(__file__))
 README = open(os.path.join(here, 'README.rst')).read()
 CHANGES = open(os.path.join(here, 'CHANGES.rst')).read()
-REQUIRES_PYTHON = ">=3.6.0"
+REQUIRES_PYTHON = ">=3.10,<3.11"
 
 about = {}
 with open(os.path.join(here, 'duck', '__version__.py'), 'r') as f:
@@ -17,7 +17,7 @@
 
 setup_requirements = ['pytest-runner', ]
 
-test_requirements = ['pytest>=3', ]
+test_requirements = ['pytest>=6,<9', ]
 
 requirements = [line.strip() for line in open('requirements.txt')]
 
@@ -32,9 +32,7 @@
     'Programming Language :: Python',
     'Natural Language :: English',
     'Programming Language :: Python :: 3',
-    'Programming Language :: Python :: 3.5',
-    'Programming Language :: Python :: 3.6',
-    'Programming Language :: Python :: 3.7',
+    'Programming Language :: Python :: 3.10',
     'Topic :: Scientific/Engineering :: Atmospheric Science',
     'License :: OSI Approved :: Apache Software License',
 ]
diff --git a/spec-list.txt b/spec-list.txt
deleted file mode 100644
index a74bda2..0000000
--- a/spec-list.txt
+++ /dev/null
@@ -1,333 +0,0 @@
-# This file may be used to create an environment using:
-# $ conda create --name <env> --file <this file>
-# platform: linux-64
-@EXPLICIT
-https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2
-https://conda.anaconda.org/conda-forge/linux-64/ca-certificates-2022.12.7-ha878542_0.conda
-https://conda.anaconda.org/conda-forge/noarch/font-ttf-dejavu-sans-mono-2.37-hab24e00_0.tar.bz2
-https://conda.anaconda.org/conda-forge/noarch/font-ttf-inconsolata-3.000-h77eed37_0.tar.bz2
-https://conda.anaconda.org/conda-forge/noarch/font-ttf-source-code-pro-2.038-h77eed37_0.tar.bz2
-https://conda.anaconda.org/conda-forge/noarch/font-ttf-ubuntu-0.83-hab24e00_0.tar.bz2
-https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.40-h41732ed_0.conda
-https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-12.2.0-h337968e_19.tar.bz2
-https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-12.2.0-h46fd767_19.tar.bz2
-https://conda.anaconda.org/conda-forge/noarch/poppler-data-0.4.12-hd8ed1ab_0.conda
-https://conda.anaconda.org/conda-forge/linux-64/python_abi-3.10-3_cp310.conda
-https://conda.anaconda.org/conda-forge/noarch/tzdata-2022g-h191b570_0.conda
-https://conda.anaconda.org/conda-forge/noarch/fonts-conda-forge-1-0.tar.bz2
-https://conda.anaconda.org/conda-forge/linux-64/libgfortran-ng-12.2.0-h69a702a_19.tar.bz2
-https://conda.anaconda.org/conda-forge/noarch/fonts-conda-ecosystem-1-0.tar.bz2
-https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-2_kmp_llvm.tar.bz2
-https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-12.2.0-h65d4601_19.tar.bz2
-https://conda.anaconda.org/conda-forge/linux-64/alsa-lib-1.2.8-h166bdaf_0.tar.bz2
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-https://conda.anaconda.org/conda-forge/noarch/requests-2.28.2-pyhd8ed1ab_0.conda
-https://conda.anaconda.org/conda-forge/noarch/dask-2023.1.1-pyhd8ed1ab_0.conda
-https://conda.anaconda.org/conda-forge/noarch/google-auth-2.16.0-pyh1a96a4e_1.conda
-https://conda.anaconda.org/conda-forge/linux-64/matplotlib-3.6.3-py310hff52083_0.conda
-https://conda.anaconda.org/conda-forge/noarch/owslib-0.27.2-pyhd8ed1ab_1.tar.bz2
-https://conda.anaconda.org/conda-forge/noarch/pooch-1.6.0-pyhd8ed1ab_0.tar.bz2
-https://conda.anaconda.org/conda-forge/noarch/requests-oauthlib-1.3.1-pyhd8ed1ab_0.tar.bz2
-https://conda.anaconda.org/conda-forge/noarch/sphinx-6.1.3-pyhd8ed1ab_0.conda
-https://conda.anaconda.org/conda-forge/linux-64/torchvision-0.14.1-cpu_py310hdfb2906_0.conda
-https://conda.anaconda.org/conda-forge/noarch/google-auth-oauthlib-0.4.6-pyhd8ed1ab_0.tar.bz2
-https://conda.anaconda.org/conda-forge/noarch/pywps-4.5.2-pyh6c4a22f_0.tar.bz2
-https://conda.anaconda.org/conda-forge/linux-64/scipy-1.10.0-py310h8deb116_2.conda
-https://conda.anaconda.org/conda-forge/linux-64/cartopy-0.21.1-py310hcb7e713_0.conda
-https://conda.anaconda.org/conda-forge/noarch/sparse-0.13.0-pyhd8ed1ab_0.tar.bz2
-https://conda.anaconda.org/conda-forge/noarch/tensorboard-2.11.2-pyhd8ed1ab_0.conda
-https://conda.anaconda.org/conda-forge/noarch/xesmf-0.7.0-pyhd8ed1ab_0.conda
diff --git a/tests/common.py b/tests/common.py
index eb8590a..a4bc12e 100644
--- a/tests/common.py
+++ b/tests/common.py
@@ -18,7 +18,7 @@
 
 # HADCRUT4_ANOMALIES_1_NC = (TEST_DATA_CACHE_DIR / HADCRUT4_NC_ZIP).as_uri()
 HADCRUT4_TAS_NC_ZIP = "https://www.metoffice.gov.uk/hadobs/hadcrut4/data/current/gridded_fields/HadCRUT.4.6.0.0.median_netcdf.zip"  # noqa
-HadCRUT5_TAS_MEAN_NC = "https://www.metoffice.gov.uk/hadobs/hadcrut5/data/current/non-infilled/HadCRUT.5.0.1.0.anomalies.ensemble_mean.nc"  # noqa
+HadCRUT5_TAS_MEAN_NC = "https://www.metoffice.gov.uk/hadobs/hadcrut5/data/HadCRUT.5.0.2.0/non-infilled/HadCRUT.5.0.2.0.anomalies.ensemble_mean.nc"  # noqa
 
 
 class WpsTestClient(WpsClient):
diff --git a/tests/test_dependencies.py b/tests/test_dependencies.py
new file mode 100644
index 0000000..9c26f04
--- /dev/null
+++ b/tests/test_dependencies.py
@@ -0,0 +1,66 @@
+"""Smoke tests for the CRAI inference and NetCDF dependency stack."""
+
+import craimodels
+import numpy as np
+import pytest
+import torch
+import xarray as xr
+from unittest.mock import Mock
+
+from climatereconstructionai import config as cfg
+from climatereconstructionai.model.net import CRAINet
+from climatereconstructionai.utils.io import load_ckpt, load_model
+from duck.clintai import write_clintai_cfg
+from duck import clintai
+
+
+@pytest.mark.parametrize("dataset_name", ["HadCRUT4", "HadCRUT5"])
+def test_crai_dispatch_uses_installed_model_metadata(tmp_path, monkeypatch, dataset_name):
+    info = craimodels.info_models()[dataset_name]
+    dataset = tmp_path / "input.nc"
+    xr.Dataset({info["variable_name"]: ("time", [1.0])}).to_netcdf(dataset)
+    evaluate = Mock()
+    monkeypatch.setattr(clintai, "evaluate", evaluate)
+    progress = [Mock(), 0, 100]
+
+    clintai.run(dataset, dataset_name, info["variable_name"], tmp_path, progress)
+
+    evaluate.assert_called_once_with(arg_file=str(tmp_path / "clintai.cfg"), prog_func=progress)
+    config = (tmp_path / "clintai.cfg").read_text()
+    assert info["eval_parameters"] in config
+    assert (tmp_path / "test" / "input.nc").is_file()
+
+
+def test_pretrained_model_cpu_inference(tmp_path):
+    info = craimodels.info_models()["HadCRUT5"]
+    config = write_clintai_cfg(
+        tmp_path, craimodels.model_dir(), "smoke", "smoke.nc", "tas_mean",
+        info["eval_parameters"],
+    )
+    cfg.set_evaluate_args(str(config))
+    model = CRAINet(
+        img_size=(36, 72), enc_dec_layers=cfg.encoding_layers[0],
+        pool_layers=cfg.pooling_layers[0], in_channels=cfg.n_channel_steps,
+        out_channels=cfg.out_channels, bounds=np.array([[-np.inf, np.inf]]),
+    )
+    checkpoint = load_ckpt(craimodels.model_dir() / cfg.model_names[0], "cpu")
+    load_model(checkpoint, model)
+    model.eval()
+    values = torch.ones(1, 1, 1, 36, 72)
+    mask = torch.ones_like(values)
+    mask[..., 10:15, 20:25] = 0
+    with torch.no_grad():
+        result = model(values * mask, mask)
+    assert result.shape == values.shape
+    assert torch.isfinite(result).all()
+
+
+def test_netcdf_roundtrip(tmp_path):
+    dataset = xr.Dataset({
+        "tas_mean": (("time", "latitude", "longitude"),
+                     np.array([[[1.0, np.nan], [2.0, 3.0]]], dtype="float32")),
+    })
+    path = tmp_path / "smoke.nc"
+    dataset.to_netcdf(path, engine="netcdf4")
+    with xr.open_dataset(path, engine="netcdf4", chunks={"time": 1}) as restored:
+        xr.testing.assert_equal(dataset, restored)
diff --git a/tests/test_wps_clintai.py b/tests/test_wps_clintai.py
index cf24782..15d3e00 100644
--- a/tests/test_wps_clintai.py
+++ b/tests/test_wps_clintai.py
@@ -2,7 +2,6 @@
 
 from pywps import Service
 from pywps.tests import (
-    assert_process_exception,
     assert_response_success,
     client_for
 )
@@ -15,23 +14,28 @@
 from duck.processes.wps_clintai import ClintAI
 
 
+def assert_wps_success(resp):
+    try:
+        assert_response_success(resp)
+    except AssertionError:
+        pytest.fail(resp.get_data(as_text=True))
+
+
 @pytest.mark.online
 def test_wps_clintai_hadcrut4_temperature_anomaly():
     client = client_for(Service(processes=[ClintAI()]))
-    datainputs = f"file=@xlink:href={HADCRUT4_TAS_NC_ZIP};variable_name=temperature_anomaly"
+    datainputs = f"file=@xlink:href={HADCRUT4_TAS_NC_ZIP};dataset_name=HadCRUT4;variable_name=temperature_anomaly"
     resp = client.get(
         f"?service=WPS&request=Execute&version=1.0.0&identifier=crai&datainputs={datainputs}"
     )
-    # print(resp.data)
-    assert_response_success(resp)
+    assert_wps_success(resp)
 
 
 @pytest.mark.online
 def test_wps_clintai_hadcrut5_tas_mean():
     client = client_for(Service(processes=[ClintAI()]))
-    datainputs = f"file=@xlink:href={HadCRUT5_TAS_MEAN_NC}"
+    datainputs = f"file=@xlink:href={HadCRUT5_TAS_MEAN_NC};dataset_name=HadCRUT5"
     resp = client.get(
         f"?service=WPS&request=Execute&version=1.0.0&identifier=crai&datainputs={datainputs}"
     )
-    # print(resp.data)
-    assert_response_success(resp)
+    assert_wps_success(resp)