diff --git a/Dockerfile.tmpl b/Dockerfile.tmpl
index f3193876..d6bc3f9b 100644
--- a/Dockerfile.tmpl
+++ b/Dockerfile.tmpl
@@ -1,66 +1,58 @@
-ARG BASE_IMAGE_REPO \
-    BASE_IMAGE_TAG \
-    CPU_BASE_IMAGE_NAME \
-    GPU_BASE_IMAGE_NAME \
-    LIGHTGBM_VERSION \
-    TORCH_VERSION \
-    TORCHAUDIO_VERSION \
-    TORCHVISION_VERSION \
-    JAX_VERSION
+FROM us-docker.pkg.dev/colab-images/public/runtime:latest
 
-{{ if eq .Accelerator "gpu" }}
-FROM gcr.io/kaggle-images/python-lightgbm-whl:${GPU_BASE_IMAGE_NAME}-${BASE_IMAGE_TAG}-${LIGHTGBM_VERSION} AS lightgbm_whl
-FROM gcr.io/kaggle-images/python-torch-whl:${GPU_BASE_IMAGE_NAME}-${BASE_IMAGE_TAG}-${TORCH_VERSION} AS torch_whl
-FROM gcr.io/kaggle-images/python-jaxlib-whl:${GPU_BASE_IMAGE_NAME}-${BASE_IMAGE_TAG}-${JAX_VERSION} AS jaxlib_whl
-FROM ${BASE_IMAGE_REPO}/${GPU_BASE_IMAGE_NAME}:${BASE_IMAGE_TAG}
-{{ else }}
-FROM ${BASE_IMAGE_REPO}/${CPU_BASE_IMAGE_NAME}:${BASE_IMAGE_TAG}
-{{ end }}
+ADD kaggle_requirements.txt /kaggle_requirements.txt
+
+# Freeze existing requirements from base image for critical packages:
+RUN pip freeze | grep -E 'tensorflow|keras|torch|jax|lightgbm' > /colab_requirements.txt
+
+# Merge requirements files:
+RUN cat /colab_requirements.txt >> /requirements.txt
+RUN cat /kaggle_requirements.txt >> /requirements.txt
+
+# TODO: GPU requirements.txt
+# TODO: merge them better (override matching ones).
 
-# Ensures shared libraries installed with conda can be found by the dynamic link loader.
-ENV LIBRARY_PATH="$LIBRARY_PATH:/opt/conda/lib" \
-    LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/opt/conda/lib"
+# Install uv & Kaggle packages
+RUN curl -LsSf https://astral.sh/uv/install.sh | sh
+RUN export PATH="${HOME}/.local/bin:${PATH}" && uv pip install --system -r /requirements.txt
+ENV PATH="~/.local/bin:${PATH}"
 
+# Install manual packages:
+# b/183041606#comment5: the Kaggle data proxy doesn't support these APIs. If the library is missing, it falls back to using a regular BigQuery query to fetch data.
+RUN uv pip uninstall --system google-cloud-bigquery-storage
+
+# NOTE(herbison): uv fails to install this for some reason
+RUN pip install git+https://github.com/Kaggle/learntools
+
+# We install an incompatible pair of libs (shapely<, libpysal==4.9.2) so we can't put this one in the requirements.txt
+RUN uv pip install --system  "libpysal==4.9.2"
+
+# Adding non-package dependencies:
+
+ADD clean-layer.sh  /tmp/clean-layer.sh
+ADD patches/nbconvert-extensions.tpl /opt/kaggle/nbconvert-extensions.tpl
+ADD patches/template_conf.json /opt/kaggle/conf.json
+
+# /opt/conda/lib/python3.10/site-packages
+ARG PACKAGE_PATH=/usr/local/lib/python3.10/dist-packages
+
+# Install GPU-specific non-pip packages.
 {{ if eq .Accelerator "gpu" }}
 ARG CUDA_MAJOR_VERSION \
     CUDA_MINOR_VERSION
 ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION} \
     CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
+
 # Make sure we are on the right version of CUDA
 RUN update-alternatives --set cuda /usr/local/cuda-$CUDA_MAJOR_VERSION.$CUDA_MINOR_VERSION
-# NVIDIA binaries from the host are mounted to /opt/bin.
-ENV PATH=/opt/bin:${PATH} \
-    # Add CUDA stubs to LD_LIBRARY_PATH to support building the GPU image on a CPU machine.
-    LD_LIBRARY_PATH_NO_STUBS="$LD_LIBRARY_PATH" \
-    LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64/stubs"
-RUN ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/local/cuda/lib64/stubs/libcuda.so.1
-{{ end }}
 
-# Keep these variables in sync if base image is updated.
-ENV TENSORFLOW_VERSION=2.16.1 \
-    # See https://github.com/tensorflow/io#tensorflow-version-compatibility
-    TENSORFLOW_IO_VERSION=0.37.0
-
-# We need to redefine the ARG here to get the ARG value defined above the FROM instruction.
-# See: https://docs.docker.com/engine/reference/builder/#understand-how-arg-and-from-interact
-ARG LIGHTGBM_VERSION \
-    TORCH_VERSION \
-    TORCHAUDIO_VERSION \
-    TORCHVISION_VERSION \
-    JAX_VERSION
-
-# Disable pesky logs like: KMP_AFFINITY: pid 6121 tid 6121 thread 0 bound to OS proc set 0
-# See: https://stackoverflow.com/questions/57385766/disable-tensorflow-log-information
-ENV KMP_WARNINGS=0 \
-    # Also make the KMP logs noverbose.
-    # https://stackoverflow.com/questions/70250304/stop-tensorflow-from-printing-warning-message
-    KMP_SETTINGS=false \
-    # Remove the pip as the root user warning.
-    PIP_ROOT_USER_ACTION=ignore
+RUN uv pip install --system "pycuda"
+
+# Remove CUDA_VERSION from non-GPU image.
+{{ else }}
+ENV CUDA_VERSION=""
+{{ end }}
 
-ADD clean-layer.sh  /tmp/clean-layer.sh
-ADD patches/nbconvert-extensions.tpl /opt/kaggle/nbconvert-extensions.tpl
-ADD patches/template_conf.json /opt/kaggle/conf.json
 
 # Update GPG key per documentation at https://cloud.google.com/compute/docs/troubleshooting/known-issues
 RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key add -
@@ -78,141 +70,18 @@ RUN sed -i "s/httpredir.debian.org/debian.uchicago.edu/" /etc/apt/sources.list &
     apt-get install -y graphviz && pip install graphviz && \
     /tmp/clean-layer.sh
 
-# b/128333086: Set PROJ_DATA to points to the proj4 cartographic library.
-ENV PROJ_DATA=/opt/conda/share/proj
-
-# Install micromamba, setup channels, and replace conda with micromamba
-ENV MAMBA_ROOT_PREFIX=/opt/conda
-RUN curl -L "https://micro.mamba.pm/install.sh" -o /tmp/micromamba-install.sh \
-    && bash /tmp/micromamba-install.sh \
-    && rm /tmp/micromamba-install.sh \
-    && mv ~/.local/bin/micromamba /usr/bin/micromamba \
-    && (!(which conda) || cp /usr/bin/micromamba $(which conda)) \
-    && micromamba config append channels nvidia \
-    && micromamba config append channels rapidsai \
-    && micromamba config append channels conda-forge \
-    && micromamba config set channel_priority flexible \
-    && python -m nb_conda_kernels.install --disable
-
-# Install conda packages not available on pip.
-# When using pip in a conda environment, conda commands should be ran first and then
-# the remaining pip commands: https://www.anaconda.com/using-pip-in-a-conda-environment/
-RUN micromamba install -y mkl cartopy imagemagick pyproj "shapely<2" && \
-    rm -rf /opt/conda/lib/python3.10/site-packages/pyproj/proj_dir/ && \
-    /tmp/clean-layer.sh
-
-# Install spacy
-# b/232247930: uninstall pyarrow to avoid double installation with the GPU specific version.
-# b/341938540: unistall grpc-cpp to allow >=v24.4 cudf and cuml to be installed.
-{{ if eq .Accelerator "gpu" }}
-RUN pip uninstall -y pyarrow && \
-    micromamba install -vvvy spacy "cudf>=24.4" "cuml>=24.4" cupy cuda-version=$CUDA_MAJOR_VERSION.$CUDA_MINOR_VERSION && \
-    /tmp/clean-layer.sh
-{{ else }}
-RUN pip install spacy && \
-    /tmp/clean-layer.sh
-{{ end}}
-
-# Install PyTorch
-# b/356397043: magma-cuda121 is the latest version
-{{ if eq .Accelerator "gpu" }}
-COPY --from=torch_whl /tmp/whl/*.whl /tmp/torch/
-# b/356397043: We are currently using cuda 12.3,
-# but magma-cuda121 is the latest compatible version 
-RUN micromamba install -y -c pytorch magma-cuda121 && \
-    pip install /tmp/torch/*.whl && \
-    sudo apt -y install libsox-dev && \
-    rm -rf /tmp/torch && \
-    /tmp/clean-layer.sh
-{{ else }}
-RUN pip install \
-        torch==$TORCH_VERSION+cpu \
-        torchvision==$TORCHVISION_VERSION+cpu \
-        torchaudio==$TORCHAUDIO_VERSION+cpu \
-        --index-url https://download.pytorch.org/whl/cpu && \
-    /tmp/clean-layer.sh
-{{ end }}
-
-# Install LightGBM
-{{ if eq .Accelerator "gpu" }}
-COPY --from=lightgbm_whl /tmp/whl/*.whl /tmp/lightgbm/
-# Install OpenCL (required by LightGBM GPU version)
-RUN apt-get install -y ocl-icd-libopencl1 clinfo && \
-    mkdir -p /etc/OpenCL/vendors && \
-    echo "libnvidia-opencl.so.1" > /etc/OpenCL/vendors/nvidia.icd && \
-    pip install /tmp/lightgbm/*.whl && \
-    rm -rf /tmp/lightgbm && \
-    /tmp/clean-layer.sh
-{{ else }}
-RUN pip install lightgbm==$LIGHTGBM_VERSION && \
-    /tmp/clean-layer.sh
-{{ end }}
-
-# Install JAX
-{{ if eq .Accelerator "gpu" }}
-COPY --from=jaxlib_whl /tmp/whl/*.whl /tmp/jax/
-# b/319722433#comment9: Use pip wheels once versions matches our CUDA version.
-RUN pip install /tmp/jax/*.whl jax==$JAX_VERSION && \
-    /tmp/clean-layer.sh
-{{ else }}
-RUN pip install jax[cpu] && \
-    /tmp/clean-layer.sh
-{{ end }}
-
-
-# Install GPU specific packages
-{{ if eq .Accelerator "gpu" }}
-# Install GPU-only packages
-# No specific package for nnabla-ext-cuda 12.x minor versions.
-RUN export PATH=/usr/local/cuda/bin:$PATH && \
-    export CUDA_ROOT=/usr/local/cuda && \
-    pip install pycuda \
-        # TODO(379932879): pip resolver fails when not specified.
-        pynvrtc==9.2 \
-        pynvml && \
-    /tmp/clean-layer.sh
-{{ end }}
-
-RUN apt-get update && \
-    apt-get install -y default-jre && \
-    /tmp/clean-layer.sh
-
-RUN pip install -f http://h2o-release.s3.amazonaws.com/h2o/latest_stable_Py.html h2o && /tmp/clean-layer.sh
-
-RUN pip install \
-        "tensorflow==${TENSORFLOW_VERSION}" \
-        "tensorflow-io==${TENSORFLOW_IO_VERSION}" \
-        tensorflow-probability \
-        tensorflow_decision_forests \
-        tensorflow-text \
-        "tensorflow_hub>=0.16.0" \
-        tf-keras \
-        "keras>3" \
-        keras-cv \
-        keras-nlp && \
-    /tmp/clean-layer.sh
-
 ADD patches/keras_internal.py \
     patches/keras_internal_test.py \
-    /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/keras/
+    $PACKAGE_PATH/tensorflow_decision_forests/keras/
 
-# b/350573866: xgboost v2.1.0 breaks learntools
 RUN apt-get install -y libfreetype6-dev && \
-    apt-get install -y libglib2.0-0 libxext6 libsm6 libxrender1 libfontconfig1 --fix-missing && \
-    rm -rf /opt/conda/lib/python3.10/site-packages/numpy* && \
-    pip install "numpy==1.26.4" && \
-    pip install gensim \
-        textblob \
-        wordcloud \
-        "xgboost==2.0.3" \
-        pydot \
-        hep_ml && \
-    # NLTK Project datasets
-    mkdir -p /usr/share/nltk_data && \
+    apt-get install -y libglib2.0-0 libxext6 libsm6 libxrender1 libfontconfig1 --fix-missing
+
+# NLTK Project datasets
+RUN mkdir -p /usr/share/nltk_data && \
     # NLTK Downloader no longer continues smoothly after an error, so we explicitly list
     # the corpuses that work
-    # "yes | ..." answers yes to the retry prompt in case of an error. See b/133762095.
-    yes | python -m nltk.downloader -d /usr/share/nltk_data abc alpino averaged_perceptron_tagger \
+    python -m nltk.downloader -d /usr/share/nltk_data abc alpino averaged_perceptron_tagger \
     basque_grammars biocreative_ppi bllip_wsj_no_aux \
     book_grammars brown brown_tei cess_cat cess_esp chat80 city_database cmudict \
     comtrans conll2000 conll2002 conll2007 crubadan dependency_treebank \
@@ -225,276 +94,13 @@ RUN apt-get install -y libfreetype6-dev && \
     sentiwordnet shakespeare sinica_treebank smultron snowball_data spanish_grammars \
     state_union stopwords subjectivity swadesh switchboard tagsets timit toolbox treebank \
     twitter_samples udhr2 udhr unicode_samples universal_tagset universal_treebanks_v20 \
-    vader_lexicon verbnet webtext word2vec_sample wordnet wordnet_ic words ycoe && \
-    pip install scikit-image && \
-    pip install opencv-contrib-python opencv-python && \
-    /tmp/clean-layer.sh
-
-RUN pip install cython \
-        fasttext \
-        opencv-contrib-python \
-        opencv-python \
-        "scipy<1.14.0" \
-        # Scikit-learn accelerated library for x86
-        "scikit-learn-intelex>=2023.0.1" \
-        # HDF5 support
-        h5py \
-        # PUDB, for local debugging convenience
-        pudb \
-        imbalanced-learn \
-        # Profiling and other utilities
-        line_profiler \
-        bokeh \
-        numba \
-        datashader \
-        # b/328788268: libpysal 4.10 seems to fail with "module 'shapely' has no attribute 'Geometry'. Did you mean: 'geometry'"
-        "libpysal==4.9.2" \
-        # b/276344496: Install specific version of boto3, because 1.26.103 is broken.
-        "boto3==1.26.100" \
-        Boruta && \
-    # Pandoc is a dependency of deap
-    apt-get install -y pandoc && \
-    /tmp/clean-layer.sh
+    vader_lexicon verbnet webtext word2vec_sample wordnet wordnet_ic words ycoe
 
 RUN apt-get install -y git-lfs && \
-    # vtk with dependencies
+    # vtk dependencies
     apt-get install -y libgl1-mesa-glx && \
-    pip install vtk && \
-    # xvfbwrapper with dependencies
+    # xvfbwrapper dependencies
     apt-get install -y xvfb && \
-    pip install xvfbwrapper && \
-    /tmp/clean-layer.sh
-
-RUN pip install mpld3 \
-        gpxpy \
-        arrow \
-        nilearn \
-        nibabel \
-        imgaug \
-        preprocessing \
-        path.py && \
-    pip install deap \
-        # b/302136621: Fix eli5 import for learntools, newer version require scikit-learn > 1.3
-        "tpot==0.12.1" \
-        scikit-optimize \
-        haversine \
-        toolz cytoolz \
-        plotly \
-        hyperopt \
-        langid \
-        # Useful data exploration libraries (for missing data and generating reports)
-        missingno \
-        pandas-profiling \
-        bayesian-optimization \
-        matplotlib-venn \
-        pyldavis \
-        mlxtend \
-        altair \
-        ImageHash \
-        ecos \
-        CVXcanon \
-        pymc3 \
-        tifffile \
-        geojson \
-        pydicom \
-        wavio \
-        SimpleITK \
-        squarify \
-        fuzzywuzzy \
-        python-louvain \
-        pyexcel-ods \
-        sklearn-pandas \
-        prophet \
-        holidays \
-        holoviews \
-        scikit-multilearn \
-        leven \
-        catboost \
-        folium \
-        scikit-plot \
-        fury dipy \
-        plotnine \
-        scikit-surprise \
-        pymongo \
-        eli5 \
-        kaggle \
-        kagglehub \
-        google-generativeai \
-        pytest && \
-    /tmp/clean-layer.sh
-
- # Add google PAIR-code Facets
-RUN cd /opt/ && git clone https://github.com/PAIR-code/facets && cd facets/ && jupyter nbextension install facets-dist/ --user && \
-    export PYTHONPATH=$PYTHONPATH:/opt/facets/facets_overview/python/ && \
-    pip install librosa \
-        sentencepiece \
-        cufflinks \
-        lime \
-        memory_profiler && \
-    /tmp/clean-layer.sh
-
-RUN pip install annoy \
-        category_encoders && \
-    # b/183041606#comment5: the Kaggle data proxy doesn't support these APIs. If the library is missing, it falls back to using a regular BigQuery query to fetch data.
-    pip uninstall -y google-cloud-bigquery-storage && \
-    # google-cloud-automl 2.0.0 introduced incompatible API changes, need to pin to 1.0.1
-    # After launch this should be installed from pip
-    pip install git+https://github.com/googleapis/python-aiplatform.git@mb-release \
-        google-cloud-automl==1.0.1 \
-        google-api-core==1.33.2 \
-        google-cloud-bigquery \
-        google-cloud-storage && \
-    # Split these installations to avoid `pip._vendor.resolvelib.resolvers.ResolutionTooDeep: 200000`
-    # b/315753846: Unpin translate package.
-    pip install google-cloud-translate==3.12.1 \
-        google-cloud-language==2.* \
-        google-cloud-videointelligence==2.* \
-        google-cloud-vision==2.* \
-        protobuf==3.20.3 \
-        # Pandas data reader
-        pandas-datareader \
-        emoji \
-        # Add Japanese morphological analysis engine
-        janome \
-        # yellowbrick machine learning visualization library
-        yellowbrick \
-        mlcrate && \
-    /tmp/clean-layer.sh
-
-# b/273059949: The pre-installed nbconvert is slow on html conversions and has to be force-uninstalled.
-# b/274619697: learntools also requires a specific nbconvert right now
-RUN rm -rf /opt/conda/lib/python3.10/site-packages/{nbconvert,nbclient,mistune,platformdirs}*
-
-RUN pip install bleach \
-        certifi \
-        cycler \
-        decorator \
-        entrypoints \
-        html5lib \
-        ipykernel \
-        ipython \
-        ipython-genutils \
-        ipywidgets==8.1.5 \
-        isoweek \
-        jedi \
-        jsonschema \
-        jupyter-client \
-        jupyter-console \
-        jupyter-core \
-        jupyterlab-lsp \
-        MarkupSafe \
-        mistune \
-        nbformat \
-        notebook \
-        "nbconvert==6.4.5" \
-        papermill \
-        python-lsp-server[all] \
-        olefile \
-        kornia \
-        pandas_summary \
-        pandocfilters \
-        pexpect \
-        pickleshare \
-        Pillow && \
-    # Install openslide and its python binding
-    apt-get install -y openslide-tools && \
-    pip install openslide-python \
-        ptyprocess \
-        Pygments \
-        pyparsing \
-        pytz \
-        PyYAML \
-        pyzmq \
-        qtconsole \
-        six \
-        terminado \
-        tornado \
-        tqdm \
-        traitlets \
-        wcwidth \
-        webencodings \
-        widgetsnbextension \
-        # Require pyarrow newer than https://github.com/advisories/GHSA-5wvp-7f3h-6wmm
-        {{ if eq .Accelerator "gpu" }} pyarrow {{ else }} "pyarrow>=14.0.1" {{ end }} 
-
-RUN python -m spacy download en_core_web_sm && python -m spacy download en_core_web_lg && \
-    apt-get update && apt-get install -y ffmpeg && \
-    /tmp/clean-layer.sh
-
-    ###########
-    #
-    #      NEW CONTRIBUTORS:
-    # Please add new pip/apt installs in this block. Don't forget a "&& \" at the end
-    # of all non-final lines. Thanks!
-    #
-    ###########
-
-RUN rm /opt/conda/lib/python3.10/site-packages/google*/direct_url.json && \
-    rm /opt/conda/lib/python3.10/site-packages/google*/REQUESTED
-# dlib has a libmkl incompatibility:
-# test_dlib_face_detector (test_dlib.TestDLib) ... INTEL MKL ERROR: /opt/conda/bin/../lib/libmkl_avx512.so.2: undefined symbol: mkl_sparse_optimize_bsr_trsm_i8.
-# Intel MKL FATAL ERROR: Cannot load libmkl_avx512.so.2 or libmkl_def.so.2.
-# nnabla breaks protobuf compatibiilty:
-RUN pip install wandb \
-        pyemd \
-        pympler \
-        featuretools \
-        #-e git+https://github.com/SohierDane/BigQuery_Helper#egg=bq_helper \
-        git+https://github.com/Kaggle/learntools \
-        ray \
-        gym \
-        pyarabic \
-        pandasql \
-	    # b/302136621: Fix eli5 import for learntools
-        scikit-learn==1.2.2 \
-	    # b/329869023 shap 0.45.0 breaks learntools
-        shap==0.44.1 \
-        cesium \
-        rgf_python \
-        jieba  \
-        tsfresh \
-        optuna \
-        plotly_express \
-        albumentations \
-        Rtree \
-        accelerate && \
-        apt-get -y install libspatialindex-dev && \
-    # b/370860329: newer versions are not capable with current tensorflow
-    rm -rf /opt/conda/lib/python3.10/site-packages/numpy* && \
-    pip install "numpy==1.26.4" && \
-    pip install pytorch-ignite \
-        bqplot \
-        earthengine-api \
-        transformers \
-        datasets \
-        s3fs \
-        gcsfs \
-        kaggle-environments \
-        # geopandas > v0.14.4 breaks learn tools
-        geopandas==v0.14.4 \
-        "shapely<2" \
-        pydub \
-        pydegensac \
-        torchmetrics \
-        pytorch-lightning \
-        sympy \
-        # flask is used by agents in the simulation competitions.
-        flask \
-        # pycrypto is used by competitions team.
-        pycryptodome \
-        nbdev \
-        easyocr \
-        onnx \
-        tables \
-        openpyxl \
-        timm \
-        torchinfo && \
-    pip install git+https://github.com/facebookresearch/segment-anything.git && \
-    # b/370860329: newer versions are not capable with current tensorflow
-    pip install --no-dependencies fastai fastdownload && \
-    # b/343971718: remove duplicate aiohttp installs, and reinstall it
-    rm -rf /opt/conda/lib/python3.10/site-packages/aiohttp* && \
-    micromamba install --force-reinstall -y aiohttp && \
     /tmp/clean-layer.sh
 
 # Download base easyocr models.
@@ -512,12 +118,7 @@ RUN mkdir -p /root/.EasyOCR/model && \
     /tmp/clean-layer.sh
 
 # Tesseract and some associated utility packages
-RUN apt-get install tesseract-ocr -y && \
-    pip install pytesseract \
-        wand \
-        pdf2image \
-        PyPDF && \
-    /tmp/clean-layer.sh
+RUN apt-get install tesseract-ocr -y
 
 ENV TESSERACT_PATH=/usr/bin/tesseract \
     # For Facets
@@ -525,39 +126,12 @@ ENV TESSERACT_PATH=/usr/bin/tesseract \
     # For Theano with MKL
     MKL_THREADING_LAYER=GNU
 
-# b/308525631: Pin Matplotlib until seaborn can be upgraded
-# to >0.13.0 (now it's stuck by a package conflict with ydata-profiling 4.5.1).
-RUN JAXVER=$(pip freeze | grep -e "^jax==") && \
-    pip install --upgrade \
-        "matplotlib==3.7.5" \
-        # ipympl adds interactive widget support for matplotlib
-        ipympl==0.7.0 \
-        "seaborn==0.12.2" \
-        pyupset \
-        python-dateutil dask dask-expr igraph \
-        pyyaml joblib geopy mne pyshp \
-        pandas \
-        polars \
-        flax \
-        "${JAXVER}" && \
-    /tmp/clean-layer.sh
-
 # Temporary fixes and patches
-# Temporary patch for Dask getting downgraded, which breaks Keras
-RUN pip install --upgrade dask && \
-    # Stop jupyter nbconvert trying to rewrite its folder hierarchy
-    mkdir -p /root/.jupyter && touch /root/.jupyter/jupyter_nbconvert_config.py && touch /root/.jupyter/migrated && \
-    # TODO(b/380921973): Ensure only matplotlib 3.7.5 files are present.
-    rm -r /opt/conda/lib/python3.10/site-packages/matplotlib-3.9.2.dist-info/ && \
+# Stop jupyter nbconvert trying to rewrite its folder hierarchy
+RUN mkdir -p /root/.jupyter && touch /root/.jupyter/jupyter_nbconvert_config.py && touch /root/.jupyter/migrated && \
     mkdir -p /.jupyter && touch /.jupyter/jupyter_nbconvert_config.py && touch /.jupyter/migrated && \
-    # Stop Matplotlib printing junk to the console on first load
-    sed -i "s/^.*Matplotlib is building the font cache using fc-list.*$/# Warning removed by Kaggle/g" /opt/conda/lib/python3.10/site-packages/matplotlib/font_manager.py && \
     # Make matplotlib output in Jupyter notebooks display correctly
     mkdir -p /etc/ipython/ && echo "c = get_config(); c.IPKernelApp.matplotlib = 'inline'" > /etc/ipython/ipython_config.py && \
-    # Temporary patch for broken libpixman 0.38 in conda-forge, symlink to system libpixman 0.34 untile conda package gets updated to 0.38.5 or higher.
-    ln -sf /usr/lib/x86_64-linux-gnu/libpixman-1.so.0.34.0 /opt/conda/lib/libpixman-1.so.0.38.0 && \
-    # b/333854354: pin jupyter-server to version 2.12.5; later versions break LSP (b/333854354)
-    pip install --force-reinstall --no-deps jupyter_server==2.12.5 && \
     /tmp/clean-layer.sh
 
 # Fix to import bq_helper library without downgrading setuptools
@@ -566,50 +140,35 @@ RUN mkdir -p ~/src && git clone https://github.com/SohierDane/BigQuery_Helper ~/
     mv ~/src/BigQuery_Helper/bq_helper.py ~/src/BigQuery_Helper/bq_helper/__init__.py && \
     mv ~/src/BigQuery_Helper/test_helper.py ~/src/BigQuery_Helper/bq_helper/ && \
     sed -i 's/)/packages=["bq_helper"])/g' ~/src/BigQuery_Helper/setup.py && \
-    pip install -e ~/src/BigQuery_Helper && \
+    uv pip install --system -e ~/src/BigQuery_Helper && \
     /tmp/clean-layer.sh
 
+
+# install imagemagick for wand
+# https://docs.wand-py.org/en/latest/guide/install.html#install-imagemagick-on-debian-ubuntu
+RUN apt-get install libmagickwand-dev
+
+# Override default imagemagick policies
+ADD patches/imagemagick-policy.xml /etc/ImageMagick-6/policy.xml
+
+# Add Kaggle module resolver
+ADD patches/kaggle_module_resolver.py $PACKAGE_PATH/tensorflow_hub/kaggle_module_resolver.py
+RUN sed -i '/from tensorflow_hub import uncompressed_module_resolver/a from tensorflow_hub import kaggle_module_resolver' $PACKAGE_PATH/tensorflow_hub/config.py && \
+    sed -i '/_install_default_resolvers()/a \ \ registry.resolver.add_implementation(kaggle_module_resolver.KaggleFileResolver())' $PACKAGE_PATH/tensorflow_hub/config.py
+
 # Add BigQuery client proxy settings
-ENV PYTHONUSERBASE "/root/.local"
+ENV PYTHONUSERBASE="/root/.local"
 ADD patches/kaggle_gcp.py \
     patches/kaggle_secrets.py \
     patches/kaggle_session.py \
     patches/kaggle_web_client.py \ 
     patches/kaggle_datasets.py \
     patches/log.py \
-    patches/sitecustomize.py \
-    /root/.local/lib/python3.10/site-packages/
+    $PACKAGE_PATH/
 
-# Override default imagemagick policies
-ADD patches/imagemagick-policy.xml /etc/ImageMagick-6/policy.xml
-
-# Add Kaggle module resolver
-ADD patches/kaggle_module_resolver.py /opt/conda/lib/python3.10/site-packages/tensorflow_hub/kaggle_module_resolver.py
-RUN sed -i '/from tensorflow_hub import uncompressed_module_resolver/a from tensorflow_hub import kaggle_module_resolver' /opt/conda/lib/python3.10/site-packages/tensorflow_hub/config.py && \
-    sed -i '/_install_default_resolvers()/a \ \ registry.resolver.add_implementation(kaggle_module_resolver.KaggleFileResolver())' /opt/conda/lib/python3.10/site-packages/tensorflow_hub/config.py && \
-    # Disable preloaded jupyter modules (they add to startup, and break when they are missing)
-    sed -i /bq_stats/d /etc/ipython/ipython_kernel_config.py && \
-    sed -i /beatrix/d /etc/ipython/ipython_kernel_config.py && \
-    sed -i /bigquery/d /etc/ipython/ipython_kernel_config.py && \
-    sed -i /sql/d /etc/ipython/ipython_kernel_config.py
-
-# Force only one libcusolver
-{{ if eq .Accelerator "gpu" }}
-RUN rm /opt/conda/bin/../lib/libcusolver.so.11 && ln -s /usr/local/cuda/lib64/libcusolver.so.11 /opt/conda/bin/../lib/libcusolver.so.11
-{{ else }}
-RUN ln -s /usr/local/cuda/lib64/libcusolver.so.11 /opt/conda/bin/../lib/libcusolver.so.11
-{{ end }}
-
-# b/270147159: conda ships with a version of libtinfo which is missing version info causing warnings, replace it with a good version.
-RUN rm /opt/conda/lib/libtinfo.so.6 && ln -s /usr/lib/x86_64-linux-gnu/libtinfo.so.6 /opt/conda/lib/libtinfo.so.6 && \
-    # b/276358430: fix Jupyter lsp freezing up the jupyter server
-    pip install "jupyter-lsp==1.5.1"
-
-# Set backend for matplotlib
-ENV MPLBACKEND="agg" \  
-    # Set LC_ALL
-    # https://github.com/explosion/spaCy/issues/12872#issuecomment-1661847588
-    LC_ALL="POSIX"
+# Figure out why this is in a different place?
+# Found by doing a export PYTHONVERBOSE=1 and then running python and checking for where it looked for it.
+ADD patches/sitecustomize.py /usr/lib/python3.10/sitecustomize.py
 
 ARG GIT_COMMIT=unknown \
     BUILD_DATE=unknown
@@ -620,10 +179,6 @@ LABEL git-commit=$GIT_COMMIT \
 ENV GIT_COMMIT=${GIT_COMMIT} \
     BUILD_DATE=${BUILD_DATE}
 
-LABEL tensorflow-version=$TENSORFLOW_VERSION \
-    # Used in the Jenkins `Docker GPU Build` step to restrict the images being pruned.
-    kaggle-lang=python
-
 # Correlate current release with the git hash inside the kernel editor by running `!cat /etc/git_commit`.
 RUN echo "$GIT_COMMIT" > /etc/git_commit && echo "$BUILD_DATE" > /etc/build_date
 
@@ -633,3 +188,4 @@ ENV LD_LIBRARY_PATH="$LD_LIBRARY_PATH_NO_STUBS" \
     # Add the CUDA home.
     CUDA_HOME=/usr/local/cuda
 {{ end }}
+ENTRYPOINT ["/usr/bin/env"]
diff --git a/Jenkinsfile b/Jenkinsfile
index 93f4753d..4980b956 100644
--- a/Jenkinsfile
+++ b/Jenkinsfile
@@ -21,66 +21,6 @@ pipeline {
   }
 
   stages {
-    stage('Pre-build Packages from Source') {
-      parallel {
-        stage('torch') {
-          options {
-            timeout(time: 300, unit: 'MINUTES')
-          }
-          steps {
-            sh '''#!/bin/bash
-              set -exo pipefail
-              source config.txt
-              cd packages/
-              ./build_package --base-image $BASE_IMAGE_REPO/$GPU_BASE_IMAGE_NAME:$BASE_IMAGE_TAG \
-                --package torch \
-                --version $TORCH_VERSION \
-                --build-arg TORCHAUDIO_VERSION=$TORCHAUDIO_VERSION \
-                --build-arg TORCHVISION_VERSION=$TORCHVISION_VERSION \
-                --build-arg CUDA_MAJOR_VERSION=$CUDA_MAJOR_VERSION \
-                --build-arg CUDA_MINOR_VERSION=$CUDA_MINOR_VERSION \
-                --push
-            '''
-          }
-        }
-        stage('lightgbm') {
-          options {
-            timeout(time: 10, unit: 'MINUTES')
-          }
-          steps {
-            sh '''#!/bin/bash
-              set -exo pipefail
-              source config.txt
-              cd packages/
-              ./build_package --base-image $BASE_IMAGE_REPO/$GPU_BASE_IMAGE_NAME:$BASE_IMAGE_TAG \
-                --package lightgbm \
-                --version $LIGHTGBM_VERSION \
-                --build-arg CUDA_MAJOR_VERSION=$CUDA_MAJOR_VERSION \
-                --build-arg CUDA_MINOR_VERSION=$CUDA_MINOR_VERSION \
-                --push
-            '''
-          }
-        }
-        stage('jaxlib') {
-          options {
-            timeout(time: 300, unit: 'MINUTES')
-          }
-          steps {
-            sh '''#!/bin/bash
-              set -exo pipefail
-              source config.txt
-              cd packages/
-              ./build_package --base-image $BASE_IMAGE_REPO/$GPU_BASE_IMAGE_NAME:$BASE_IMAGE_TAG \
-                --package jaxlib \
-                --version $JAX_VERSION \
-                --build-arg CUDA_MAJOR_VERSION=$CUDA_MAJOR_VERSION \
-                --build-arg CUDA_MINOR_VERSION=$CUDA_MINOR_VERSION \
-                --push
-            '''
-          }
-        }
-      }
-    }
     stage('Build/Test/Diff') {
       parallel {
         stage('CPU') {
diff --git a/clean-layer.sh b/clean-layer.sh
index d1a048fc..467e1cac 100755
--- a/clean-layer.sh
+++ b/clean-layer.sh
@@ -19,6 +19,4 @@ apt-get clean
 # Ensures the current working directory won't be deleted
 cd /usr/local/src/
 # Delete source files used for building binaries
-rm -rf /usr/local/src/*
-# Delete conda downloaded tarballs
-conda clean -y --tarballs
+rm -rf /usr/local/src/*
\ No newline at end of file
diff --git a/config.txt b/config.txt
index e95a1af1..c0a7711c 100644
--- a/config.txt
+++ b/config.txt
@@ -1,11 +1,2 @@
-BASE_IMAGE_REPO=gcr.io/deeplearning-platform-release
-BASE_IMAGE_TAG=m122
-CPU_BASE_IMAGE_NAME=tf2-cpu.2-16.py310
-GPU_BASE_IMAGE_NAME=tf2-gpu.2-16.py310
-LIGHTGBM_VERSION=4.2.0
-TORCH_VERSION=2.4.0
-TORCHAUDIO_VERSION=2.4.0
-TORCHVISION_VERSION=0.19.0
-JAX_VERSION=0.4.26
 CUDA_MAJOR_VERSION=12
-CUDA_MINOR_VERSION=3
+CUDA_MINOR_VERSION=2
diff --git a/kaggle_requirements.txt b/kaggle_requirements.txt
new file mode 100644
index 00000000..6400d8a1
--- /dev/null
+++ b/kaggle_requirements.txt
@@ -0,0 +1,139 @@
+altair>=5.4.0
+Babel
+Boruta
+Cartopy
+ImageHash
+Janome
+PyArabic
+PyUpSet
+Pympler
+Rtree
+shapely<2
+SimpleITK
+TPOT
+Theano
+Wand
+annoy
+arrow
+bayesian-optimization
+boto3
+catboost
+category-encoders
+cesium
+comm
+cytoolz
+dask-expr
+datasets
+datashader
+deap
+dipy
+docker
+easyocr
+eli5
+emoji
+fasttext
+featuretools
+fiona
+fury
+fuzzywuzzy
+geojson
+# geopandas > v0.14.4 breaks learn tools
+geopandas==v0.14.4
+google-cloud-aiplatform
+# google-cloud-automl 2.0.0 introduced incompatible API changes, need to pin to 1.0.1
+google-cloud-automl==1.0.1
+# b/315753846: Unpin translate package.
+google-cloud-translate==3.12.1
+google-cloud-videointelligence
+google-cloud-vision
+gpxpy
+h2o
+haversine
+hep-ml
+igraph
+ipympl
+ipywidgets==8.1.5
+isoweek
+jedi
+# b/276358430: fix Jupyter lsp freezing up the jupyter server
+jupyter-lsp==1.5.1
+# b/333854354: pin jupyter-server to version 2.12.5; later versions break LSP (b/333854354)
+jupyter_server==2.12.5
+jupyterlab
+jupyterlab-lsp
+kaggle-environments
+kagglehub>=0.3.4
+# Keras 3.6 broke test_keras.py > test_train > keras.datasets.mnist.load_data():
+# See https://github.com/keras-team/keras/commit/dcefb139863505d166dd1325066f329b3033d45a
+keras<3.6
+keras-cv
+keras-nlp
+keras-tuner
+kornia
+langid
+leven
+# b/328788268: libpysal 4.10 seems to fail with "module 'shapely' has no attribute 'Geometry'. Did you mean: 'geometry'"
+libpysal<=4.9.2
+lime
+line_profiler
+mamba
+mlcrate
+mne
+mpld3
+nbdev
+nilearn
+olefile
+onnx
+openslide-bin
+openslide-python
+optuna
+pandas-profiling
+pandasql
+papermill
+path
+path.py
+pdf2image
+plotly-express
+preprocessing
+pudb
+pyLDAvis
+pycryptodome
+pydegensac
+pydicom
+pydub
+pyemd
+pyexcel-ods
+pymc3
+pymongo
+pypdf
+pytesseract
+python-lsp-server
+pytorch-ignite
+pytorch-lightning
+qgrid
+qtconsole
+ray
+rgf-python
+s3fs
+scikit-learn-intelex
+scikit-multilearn
+scikit-optimize
+scikit-plot
+scikit-surprise
+git+https://github.com/facebookresearch/segment-anything.git
+shap
+squarify
+tensorflow-cloud
+tensorflow-io
+tensorflow-text
+tensorflow_decision_forests
+timm
+torchinfo
+torchmetrics
+tsfresh
+vtk
+wandb
+wavio
+xgboost==2.0.3
+xvfbwrapper
+ydata-profiling
diff --git a/test b/test
index ef1ffe3e..c2748e81 100755
--- a/test
+++ b/test
@@ -3,7 +3,7 @@ set -e
 
 IMAGE_TAG='kaggle/python-build'
 IMAGE_TAG_OVERRIDE=''
-ADDITONAL_OPTS=''
+ADDITONAL_OPTS='--runtime runc ' # Use the CPU runtime by default
 PATTERN='test*.py'
 
 usage() {
@@ -69,8 +69,6 @@ readonly ADDITONAL_OPTS
 readonly PATTERN
 
 set -x
-docker run --rm --net=none -v /tmp/python-build:/tmp/python-build "$IMAGE_TAG" rm -rf /tmp/python-build/*
-docker rm jupyter_test || true
 mkdir -p /tmp/python-build/tmp
 mkdir -p /tmp/python-build/devshm
 mkdir -p /tmp/python-build/working
@@ -97,6 +95,9 @@ fi
 # Note about `--hostname localhost` (b/158137436)
 # hostname defaults to the container name which fails DNS name
 # resolution with --net=none (required to keep tests hermetic). See details in bug.
+#
+# Note about CLOUDSDK_CONFIG=/tmp/.config/gcloud
+# We use the /tmp dir since the filesystem is --read-only and we need writable space for gcloud configs.
 docker run --rm -t --read-only --net=none \
     -e HOME=/tmp -e KAGGLE_DATA_PROXY_TOKEN=test-key \
     -e KAGGLE_USER_SECRETS_TOKEN_KEY=test-secrets-key \
@@ -105,6 +106,7 @@ docker run --rm -t --read-only --net=none \
     -e KAGGLE_DATA_PROXY_PROJECT=test \
     -e TF_FORCE_GPU_ALLOW_GROWTH=true \
     -e XLA_PYTHON_CLIENT_PREALLOCATE=false \
+    -e CLOUDSDK_CONFIG=/tmp/.config/gcloud \
     --hostname localhost \
     --shm-size=2g \
     -v $PWD:/input:ro -v /tmp/python-build/working:/working \
diff --git a/tests/test_cuml.py b/tests/test_cuml.py
index bbb7f0c6..695e47ca 100644
--- a/tests/test_cuml.py
+++ b/tests/test_cuml.py
@@ -6,6 +6,7 @@
 class TestCuml(unittest.TestCase):
     @gpu_test
     @p100_exempt # b/342143152: cuML(>=24.4v) is inompatible with p100 GPUs.
+    @unittest.skip("b/381287748 cuML is not installed in Colab.")
     def test_pca_fit_transform(self):
         import unittest
         import numpy as np
diff --git a/tests/test_fastai.py b/tests/test_fastai.py
index 0de1f82f..49bce0ac 100644
--- a/tests/test_fastai.py
+++ b/tests/test_fastai.py
@@ -27,8 +27,9 @@ def test_tabular(self):
             "/input/tests/data/train.csv",
             cont_names=["pixel"+str(i) for i in range(784)],
             y_names='label',
-            procs=[FillMissing, Categorify, Normalize])       
+            procs=[FillMissing, Categorify, Normalize])
         learn = tabular_learner(dls, layers=[200, 100])
-        learn.fit_one_cycle(n_epoch=1)
+        with learn.no_bar():
+            learn.fit_one_cycle(n_epoch=1)
         
-        self.assertGreater(learn.smooth_loss, 0)
+            self.assertGreater(learn.smooth_loss, 0)
diff --git a/tests/test_lightgbm.py b/tests/test_lightgbm.py
index bcdbb1a6..7001a0a7 100644
--- a/tests/test_lightgbm.py
+++ b/tests/test_lightgbm.py
@@ -34,7 +34,9 @@ def test_cpu(self):
 
         self.assertEqual(1, gbm.best_iteration)
 
+    # TODO(b/381256047): Colab needs to install GPU-enabled lightgbm.
     @gpu_test
+    @unittest.skip("Skipping this test until b/381256047 is resolved.")
     def test_gpu(self):
         lgb_train, lgb_eval = self.load_datasets()