RHOAIENG-27434: Create ROCm Tensorflow Python 3.12 Image #1259
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""" WalkthroughA new Jupyter notebook environment targeting AMD ROCm with TensorFlow and Python 3.12 on UBI9 is introduced. The update adds a multi-stage Dockerfile, a Pipfile for dependency management, Kubernetes deployment manifests using Kustomize, and a comprehensive Jupyter notebook for validating the installed environment and key packages. Changes
Estimated code review effort🎯 4 (Complex) | ⏱️ ~90 minutes Possibly related issues
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Actionable comments posted: 11
🧹 Nitpick comments (1)
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb (1)
48-53: tf2onnx conversion test needs more comprehensive validation.The current test only checks that the conversion result is not None, but doesn't validate the actual ONNX model structure or functionality.
def test_tf2onnx_conversion(self): - # Replace this with an actual TensorFlow model conversion using tf2onnx model = tf.keras.Sequential([tf.keras.layers.Dense(1, input_shape=(10,))]) - onnx_model = tf2onnx.convert.from_keras(model) + onnx_model, _ = tf2onnx.convert.from_keras(model) self.assertTrue(onnx_model is not None) + # Verify ONNX model has expected structure + self.assertTrue(hasattr(onnx_model, 'graph'), "ONNX model should have a graph") + self.assertTrue(len(onnx_model.graph.node) > 0, "ONNX model should have nodes")
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⛔ Files ignored due to path filters (1)
jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile.lockis excluded by!**/*.lock
📒 Files selected for processing (6)
jupyter/rocm/tensorflow/ubi9-python-3.12/Dockerfile.rocm(1 hunks)jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile(1 hunks)jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/kustomization.yaml(1 hunks)jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml(1 hunks)jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml(1 hunks)jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb(1 hunks)
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🧠 Learnings (7)
📓 Common learnings
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/minimal/ubi9-python-3.12/Dockerfile.cpu:21-24
Timestamp: 2025-07-01T06:48:13.154Z
Learning: jiridanek creates comprehensive follow-up issues from review comments that expand scope appropriately, include clear acceptance criteria, proper backlinks, and structured implementation guidance. Issue #1241 demonstrates this by turning a specific oc client checksum concern into a thorough security enhancement plan covering all downloaded binaries across the Python 3.12 implementation.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1247
File: .github/workflows/build-notebooks-TEMPLATE.yaml:50-53
Timestamp: 2025-07-01T14:36:52.852Z
Learning: In the opendatahub-io/notebooks repository, the test runner's Python version (configured in GitHub Actions UV setup) intentionally doesn't need to match the Python version of the container images being tested. jiridanek's team uses Python 3.12 for running tests while images may use different Python versions (like 3.11), and this approach works fine since the test code is separate from the application code running inside the containers.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-20T11:51:59.716Z
Learning: This project follows the practice of associating PRs with Jira tickets from https://issues.redhat.com for traceability between requirements, release process, and product documentation. This is critical for enterprise software development compliance and cross-team coordination.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/trustyai/ubi9-python-3.11/Pipfile:49-49
Timestamp: 2025-06-28T14:15:41.168Z
Learning: TrustyAI's jupyter-bokeh was pinned to 3.0.5 due to compatibility requirements with TrustyAI's visualization components, but the actual deployed version in requirements.txt shows 3.0.7, indicating incremental testing. The upgrade to 4.0.5 in this PR represents the completion of a gradual migration strategy from the 3.x series after confirming compatibility with Bokeh 3.7.3.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22
Timestamp: 2025-06-30T14:36:53.890Z
Learning: The pod-patch.yaml file in jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/ is used only for running tests, not production deployments. This affects the risk assessment for resource management configurations like sizeLimit on emptyDir volumes.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/minimal/ubi9-python-3.12/Dockerfile.rocm:43-55
Timestamp: 2025-07-01T06:48:21.070Z
Learning: When security concerns are raised during PR reviews in opendatahub-io/notebooks, comprehensive follow-up issues are created (often by CodeRabbit) to track all related security enhancements with clear acceptance criteria and implementation guidance. This ensures security improvements are systematically addressed in dedicated efforts rather than blocking current deliverables.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T10:41:56.419Z
Learning: jiridanek's team uses containerized dependency locking for cross-platform compatibility in opendatahub-io/notebooks. They run `pipenv lock` inside UBI9 containers with specific platform arguments (`--platform=linux/amd64 --python-version 3.12`) to avoid host OS dependency conflicts when generating Pipfile.lock files.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T10:41:56.419Z
Learning: In the opendatahub-io/notebooks repository, TensorFlow packages with `extras = ["and-cuda"]` can cause build conflicts on macOS due to platform-specific CUDA packages. When the Dockerfile installs CUDA system-wide, removing the extras and letting TensorFlow find CUDA at runtime resolves these conflicts.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/trustyai/ubi9-python-3.11/Pipfile:49-49
Timestamp: 2025-06-28T14:15:41.168Z
Learning: The jupyter-bokeh package was previously pinned to version 3.0.5 in the TrustyAI notebook image due to compatibility requirements with TrustyAI components, as indicated by the comment "Should be pinned down to this version in order to be compatible with trustyai" that was removed in this update.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/datascience/ubi9-python-3.11/Pipfile:34-36
Timestamp: 2025-06-28T14:13:27.890Z
Learning: In the opendatahub-io/notebooks repository, the dependency pinning strategy follows a deliberate pattern: core `jupyterlab` package uses exact pinning (==) across all notebook images to ensure UI consistency, while JupyterLab extensions and all server components (jupyter-server, jupyter-server-proxy, jupyter-server-terminals) use compatible release (~=) pinning to allow automatic security updates and bug fixes while maintaining API compatibility.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1197
File: runtimes/minimal/ubi9-python-3.11/requirements.txt:395-405
Timestamp: 2025-06-26T15:28:35.416Z
Learning: psutil version 7.x is compatible with UBI9, CentOS Stream 9, and RHEL 9 platforms in the opendatahub-io/notebooks repository. The upgrade from psutil 5.x to 7.x has been validated for these environments.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/trustyai/ubi9-python-3.11/Pipfile:49-49
Timestamp: 2025-06-28T14:21:09.429Z
Learning: TrustyAI 0.6.1 (latest version as of June 2025) has a hard dependency constraint on jupyter-bokeh~=3.0.5, preventing upgrades to jupyter-bokeh 4.x in notebook images that include TrustyAI. This requires either waiting for TrustyAI to update their dependency or excluding TrustyAI from jupyter-bokeh upgrades.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/base/statefulset.yaml:54-60
Timestamp: 2025-06-30T14:43:08.138Z
Learning: Issue #1212 in opendatahub-io/notebooks demonstrates that missing securityContext configuration (allowPrivilegeEscalation, runAsNonRoot, seccompProfile) causes runtime pods to fail reaching ready state and timeout after 300s on OpenShift due to PodSecurity policy violations.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: Runtime deployment tests in opendatahub-io/notebooks may show PodSecurity warnings about allowPrivilegeEscalation, capabilities, runAsNonRoot, and seccompProfile settings. These warnings occur on OpenShift but not on GitHub Actions because GitHub Actions uses upstream Kubernetes without SecurityContextConstraints (SCC).
jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/kustomization.yaml (5)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22
Timestamp: 2025-06-30T14:36:53.890Z
Learning: The pod-patch.yaml file in jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/ is used only for running tests, not production deployments. This affects the risk assessment for resource management configurations like sizeLimit on emptyDir volumes.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/rocm/pytorch/ubi9-python-3.11/requirements.txt:987-989
Timestamp: 2025-06-28T15:06:03.344Z
Learning: In the opendatahub-io/notebooks repository, checks for broken links and missing files in kustomization manifests are already performed by `ci/kustomize.sh`, which is invoked from `.github/workflows/code-quality.yaml` (lines 112–116). No additional pytest is needed for this purpose.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: StatefulSet selector issue with empty `spec.selector: {}` is a known systemic problem across multiple images in opendatahub-io/notebooks repository, tracked in issue #1236. This affects multiple StatefulSet manifests and is being addressed centrally rather than in individual PRs.
jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml (3)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22
Timestamp: 2025-06-30T14:36:53.890Z
Learning: The pod-patch.yaml file in jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/ is used only for running tests, not production deployments. This affects the risk assessment for resource management configurations like sizeLimit on emptyDir volumes.
jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml (7)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T07:11:44.903Z
Learning: Resource limits in StatefulSet manifests in opendatahub-io/notebooks are configured for testing purposes, not production deployments. This affects risk assessment when reviewing resource configurations like memory and CPU limits.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: StatefulSet selector issue with empty `spec.selector: {}` is a known systemic problem across multiple images in opendatahub-io/notebooks repository, tracked in issue #1236. This affects multiple StatefulSet manifests and is being addressed centrally rather than in individual PRs.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22
Timestamp: 2025-06-30T14:36:53.890Z
Learning: The pod-patch.yaml file in jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/ is used only for running tests, not production deployments. This affects the risk assessment for resource management configurations like sizeLimit on emptyDir volumes.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/base/statefulset.yaml:54-60
Timestamp: 2025-06-30T14:43:08.138Z
Learning: Issue #1212 in opendatahub-io/notebooks demonstrates that missing securityContext configuration (allowPrivilegeEscalation, runAsNonRoot, seccompProfile) causes runtime pods to fail reaching ready state and timeout after 300s on OpenShift due to PodSecurity policy violations.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: Runtime deployment tests in opendatahub-io/notebooks may show PodSecurity warnings about allowPrivilegeEscalation, capabilities, runAsNonRoot, and seccompProfile settings. These warnings occur on OpenShift but not on GitHub Actions because GitHub Actions uses upstream Kubernetes without SecurityContextConstraints (SCC).
jupyter/rocm/tensorflow/ubi9-python-3.12/Dockerfile.rocm (9)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T10:41:56.419Z
Learning: In the opendatahub-io/notebooks repository, TensorFlow packages with `extras = ["and-cuda"]` can cause build conflicts on macOS due to platform-specific CUDA packages. When the Dockerfile installs CUDA system-wide, removing the extras and letting TensorFlow find CUDA at runtime resolves these conflicts.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T10:41:56.419Z
Learning: jiridanek's team uses containerized dependency locking for cross-platform compatibility in opendatahub-io/notebooks. They run `pipenv lock` inside UBI9 containers with specific platform arguments (`--platform=linux/amd64 --python-version 3.12`) to avoid host OS dependency conflicts when generating Pipfile.lock files.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1154
File: manifests/base/jupyter-pytorch-notebook-imagestream.yaml:0-0
Timestamp: 2025-06-16T11:06:33.139Z
Learning: In the opendatahub-io/notebooks repository, N-1 versions of images in manifest files (like imagestream.yaml files) should not be updated regularly. The versions of packages like codeflare-sdk in N-1 images are frozen to what was released when the image was moved from N to N-1 version. N-1 images are only updated for security vulnerabilities of packages, not for regular version bumps. This is why the version of packages in N-1 images may be quite old compared to the latest N version.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22
Timestamp: 2025-06-30T14:35:34.805Z
Learning: In the opendatahub-io/notebooks repository, mounting emptyDir volumes over /opt/app-root/src is intentional behavior that matches production deployment patterns where odh-dashboard mounts empty PVCs at this location (the $HOME directory). This mounting is expected to hide base image content.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/base/statefulset.yaml:54-60
Timestamp: 2025-06-30T14:43:08.138Z
Learning: Issue #1212 in opendatahub-io/notebooks demonstrates that missing securityContext configuration (allowPrivilegeEscalation, runAsNonRoot, seccompProfile) causes runtime pods to fail reaching ready state and timeout after 300s on OpenShift due to PodSecurity policy violations.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: Runtime deployment tests in opendatahub-io/notebooks may show PodSecurity warnings about allowPrivilegeEscalation, capabilities, runAsNonRoot, and seccompProfile settings. These warnings occur on OpenShift but not on GitHub Actions because GitHub Actions uses upstream Kubernetes without SecurityContextConstraints (SCC).
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: OpenShift CI infrastructure issues in opendatahub-io/notebooks can manifest as "ContainerFailed one or more containers exited" errors in release steps, or as "Entrypoint received interrupt: terminated" messages when pods are killed during CI runs. These are typically infrastructure-level issues rather than code problems.
jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile (7)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T10:41:56.419Z
Learning: jiridanek's team uses containerized dependency locking for cross-platform compatibility in opendatahub-io/notebooks. They run `pipenv lock` inside UBI9 containers with specific platform arguments (`--platform=linux/amd64 --python-version 3.12`) to avoid host OS dependency conflicts when generating Pipfile.lock files.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/datascience/ubi9-python-3.11/Pipfile:34-36
Timestamp: 2025-06-28T14:13:27.890Z
Learning: In the opendatahub-io/notebooks repository, the dependency pinning strategy follows a deliberate pattern: core `jupyterlab` package uses exact pinning (==) across all notebook images to ensure UI consistency, while JupyterLab extensions and all server components (jupyter-server, jupyter-server-proxy, jupyter-server-terminals) use compatible release (~=) pinning to allow automatic security updates and bug fixes while maintaining API compatibility.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/trustyai/ubi9-python-3.11/Pipfile:49-49
Timestamp: 2025-06-28T14:15:41.168Z
Learning: The jupyter-bokeh package was previously pinned to version 3.0.5 in the TrustyAI notebook image due to compatibility requirements with TrustyAI components, as indicated by the comment "Should be pinned down to this version in order to be compatible with trustyai" that was removed in this update.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T10:41:56.419Z
Learning: In the opendatahub-io/notebooks repository, TensorFlow packages with `extras = ["and-cuda"]` can cause build conflicts on macOS due to platform-specific CUDA packages. When the Dockerfile installs CUDA system-wide, removing the extras and letting TensorFlow find CUDA at runtime resolves these conflicts.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/trustyai/ubi9-python-3.11/Pipfile:49-49
Timestamp: 2025-06-28T14:21:09.429Z
Learning: The jupyter-bokeh pinning to 3.0.5 in TrustyAI notebook image was not due to TrustyAI code compatibility issues, but because the trustyai package itself explicitly declares jupyter-bokeh~=3.0.5 as a hard dependency, causing pip dependency resolution conflicts when trying to upgrade to jupyter-bokeh 4.x.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/trustyai/ubi9-python-3.11/Pipfile:49-49
Timestamp: 2025-06-28T14:21:09.429Z
Learning: TrustyAI explicitly declares jupyter-bokeh~=3.0.5 as a hard dependency in both their requirements.txt and pyproject.toml files, with no open issues tracking jupyter-bokeh 4.x compatibility. This creates an unresolvable pip dependency conflict when trying to upgrade jupyter-bokeh to 4.x in notebook images that include TrustyAI.
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb (7)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1247
File: .github/workflows/build-notebooks-TEMPLATE.yaml:50-53
Timestamp: 2025-07-01T14:36:52.852Z
Learning: In the opendatahub-io/notebooks repository, the test runner's Python version (configured in GitHub Actions UV setup) intentionally doesn't need to match the Python version of the container images being tested. jiridanek's team uses Python 3.12 for running tests while images may use different Python versions (like 3.11), and this approach works fine since the test code is separate from the application code running inside the containers.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/trustyai/ubi9-python-3.11/Pipfile:49-49
Timestamp: 2025-06-28T14:15:41.168Z
Learning: TrustyAI's jupyter-bokeh was pinned to 3.0.5 due to compatibility requirements with TrustyAI's visualization components, but the actual deployed version in requirements.txt shows 3.0.7, indicating incremental testing. The upgrade to 4.0.5 in this PR represents the completion of a gradual migration strategy from the 3.x series after confirming compatibility with Bokeh 3.7.3.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T10:41:56.419Z
Learning: In the opendatahub-io/notebooks repository, TensorFlow packages with `extras = ["and-cuda"]` can cause build conflicts on macOS due to platform-specific CUDA packages. When the Dockerfile installs CUDA system-wide, removing the extras and letting TensorFlow find CUDA at runtime resolves these conflicts.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/trustyai/ubi9-python-3.11/Pipfile:49-49
Timestamp: 2025-06-28T14:15:41.168Z
Learning: The jupyter-bokeh package was previously pinned to version 3.0.5 in the TrustyAI notebook image due to compatibility requirements with TrustyAI components, as indicated by the comment "Should be pinned down to this version in order to be compatible with trustyai" that was removed in this update.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: Test failures in opendatahub-io/notebooks should be categorized as either repository bugs (code/configuration issues) or infrastructure issues (CI platform problems) for proper diagnosis and resolution.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1218
File: jupyter/rocm/pytorch/ubi9-python-3.11/requirements.txt:987-989
Timestamp: 2025-06-28T15:06:03.344Z
Learning: In the opendatahub-io/notebooks repository, checks for broken links and missing files in kustomization manifests are already performed by `ci/kustomize.sh`, which is invoked from `.github/workflows/code-quality.yaml` (lines 112–116). No additional pytest is needed for this purpose.
🪛 Checkov (3.2.334)
jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml
[MEDIUM] 2-60: Containers should not run with allowPrivilegeEscalation
(CKV_K8S_20)
[MEDIUM] 2-60: Minimize the admission of root containers
(CKV_K8S_23)
jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/kustomization.yaml
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Please add your new image to Makefile. There are two places. Uncommenting the relevant line(s) should do the trick. I'll try to ask rabbit if it can give precise instructions.
@coderabbitai the new python 3.12 image has to be added in the two lists in Makefile. For Pipfile lock updates and for all-images target so that GitHub actions CI runs on it. Can you please explain how this is to be accomplished?
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@coderabbitai the new python 3.12 image has to be added in the two lists in Makefile. For Pipfile lock updates and for all-images target so that GitHub actions CI runs on it. Can you please explain how this is to be accomplished? |
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Tip For best results, initiate chat on the files or code changes. 🧩 Analysis chain@jiridanek, I'll help you identify where to add the new Python 3.12 ROCm TensorFlow image in the Makefile. Let me examine the current Makefile structure first. 🏁 Script executed: Length of output: 23173 Perfect! I can see exactly what needs to be done. The Makefile already has the infrastructure in place for the ROCm TensorFlow Python 3.12 image, but the entries are currently commented out. You need to uncomment two specific lines: 1. For Pipfile lock updates (around line 445):In the # jupyter/rocm/tensorflow/ubi9-python-$(PYTHON_VERSION)So it becomes: else ifeq ($(PYTHON_VERSION), 3.12)
BASE_DIRS := \
jupyter/minimal/ubi9-python-$(PYTHON_VERSION) \
jupyter/datascience/ubi9-python-$(PYTHON_VERSION) \
jupyter/pytorch/ubi9-python-$(PYTHON_VERSION) \
jupyter/tensorflow/ubi9-python-$(PYTHON_VERSION) \
jupyter/rocm/pytorch/ubi9-python-$(PYTHON_VERSION) \
jupyter/rocm/tensorflow/ubi9-python-$(PYTHON_VERSION)
# jupyter/trustyai/ubi9-python-$(PYTHON_VERSION)
# codeserver/ubi9-python-$(PYTHON_VERSION)2. For all-images target (around line 515):In the # rocm-jupyter-tensorflow-ubi9-python-$(RELEASE_PYTHON_VERSION)So it becomes: else ifeq ($(RELEASE_PYTHON_VERSION), 3.12)
all-images: \
jupyter-minimal-ubi9-python-$(RELEASE_PYTHON_VERSION) \
jupyter-datascience-ubi9-python-$(RELEASE_PYTHON_VERSION) \
cuda-jupyter-minimal-ubi9-python-$(RELEASE_PYTHON_VERSION) \
cuda-jupyter-tensorflow-ubi9-python-$(RELEASE_PYTHON_VERSION) \
cuda-jupyter-pytorch-ubi9-python-$(RELEASE_PYTHON_VERSION) \
rocm-jupyter-pytorch-ubi9-python-$(RELEASE_PYTHON_VERSION) \
rocm-jupyter-tensorflow-ubi9-python-$(RELEASE_PYTHON_VERSION)These changes will:
The build target 🧠 Learnings used |
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[APPROVALNOTIFIER] This PR is NOT APPROVED This pull-request has been approved by: The full list of commands accepted by this bot can be found here.
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Actionable comments posted: 0
♻️ Duplicate comments (4)
jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml (2)
12-17: Emptyselectorand templatelabelsremain unresolvedThe StatefulSet is still invalid because
spec.selectorandtemplate.metadata.labelsare empty.
Kubernetes rejects this manifest (.spec.selector: Invalid value: {}).Tracked centrally in issue #1236 – no further action needed here.
18-60: MissingsecurityContext– container may run privileged / as rootNeither pod nor container define
securityContext;allowPrivilegeEscalationisn’t disabled and the user isn’t set to non-root.
These violations are already flagged by Checkov (CKV_K8S_20 / 23) and covered by issue #1212.No additional changes required in this PR.
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb (2)
67-67: Remove or assign useless expression.Line 67 contains a standalone
predictionsexpression that doesn't serve any purpose. Either remove it or assign it to a variable for inspection.The broader concern about adding assertions to validate model performance is already tracked in issue #1261.
- predictions
80-95: TensorBoard test functionality tracked for improvement.The enhancement to add verification of TensorBoard log file creation is already tracked in issue #1263.
🧹 Nitpick comments (1)
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb (1)
15-15: Remove unused tensorboard import.The
tensorboardimport is not used anywhere in the test code and should be removed to keep the imports clean.-import tensorboard
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⛔ Files ignored due to path filters (2)
jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile.lockis excluded by!**/*.lockruntimes/rocm-tensorflow/ubi9-python-3.12/Pipfile.lockis excluded by!**/*.lock
📒 Files selected for processing (9)
Makefile(2 hunks)jupyter/datascience/ubi9-python-3.12/mssql-2022.repo-x86_64(1 hunks)jupyter/rocm/tensorflow/ubi9-python-3.12/Dockerfile.rocm(1 hunks)jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile(1 hunks)jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/kustomization.yaml(1 hunks)jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml(1 hunks)jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml(1 hunks)jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb(1 hunks)runtimes/rocm-tensorflow/ubi9-python-3.12/requirements.txt(11 hunks)
✅ Files skipped from review due to trivial changes (1)
- jupyter/datascience/ubi9-python-3.12/mssql-2022.repo-x86_64
🚧 Files skipped from review as they are similar to previous changes (6)
- jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/kustomization.yaml
- jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile
- jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml
- Makefile
- jupyter/rocm/tensorflow/ubi9-python-3.12/Dockerfile.rocm
- runtimes/rocm-tensorflow/ubi9-python-3.12/requirements.txt
🧰 Additional context used
🧠 Learnings (3)
📓 Common learnings
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-09T08:07:24.937Z
Learning: jiridanek requested GitHub issue creation for tensorflow_rocm Python 3.12 compatibility problem during PR #1333 review. Issue #1354 was successfully created with comprehensive problem description covering missing cp312 wheels causing build failures, three solution options (upstream TensorFlow, Python 3.11 only, custom build), clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-23T16:18:42.922Z
Learning: The TensorFlow ROCm Python 3.12 compatibility issue in opendatahub-io/notebooks PR #1259 was caused by using tensorflow-rocm==2.14.0.600 in Pipfile.lock which lacks Python 3.12 wheels, while the Pipfile specifies tensorflow_rocm=~=2.18.1. The solution requires updating Pipfile sources to include https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4/ repository which contains tensorflow_rocm-2.18.1-cp312-cp312-manylinux_2_28_x86_64.whl and regenerating Pipfile.lock using the piplock-refresh GitHub Action.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Dockerfile.rocm:50-50
Timestamp: 2025-07-08T19:30:01.738Z
Learning: jiridanek requested GitHub issue creation for multi-architecture support in ROCm TensorFlow image during PR #1333 review. Issue #1346 was created with comprehensive problem description covering hardcoded x86_64 architecture breaking multi-arch support, detailed impact analysis, three solution options (runtime detection, BuildKit TARGETARCH integration, hybrid approach) with pros/cons analysis, comprehensive acceptance criteria covering core requirements and testing, phased implementation guidance, related files identification, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/pytorch/ubi9-python-3.12/utils/bootstrapper.py:619-626
Timestamp: 2025-07-08T19:33:14.340Z
Learning: jiridanek requested GitHub issue creation for Python 3.12 version check bug in bootstrapper.py during PR #1333 review. Issue #1348 was created with comprehensive problem description covering version check exclusion affecting all Python 3.12 runtime images, detailed impact analysis of bootstrapper execution failures, clear solution with code examples, affected files list including all 6 runtime bootstrapper copies, acceptance criteria for testing and verification, implementation notes about code duplication and upstream reporting, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: The Python 3.11 infrastructure for ROCm TensorFlow images in opendatahub-io/notebooks is already properly configured in the Makefile with both BASE_DIRS entries for Pipfile lock renewals and all-images targets for CI builds, requiring only commenting out the corresponding Python 3.12 entries when downgrading due to wheel availability issues.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: jupyter/pytorch/ubi9-python-3.12/Dockerfile.cuda:65-66
Timestamp: 2025-07-09T12:31:02.033Z
Learning: jiridanek requested GitHub issue creation for MSSQL repo file hardcoding problem during PR #1320 review. Issue #1363 was created and updated with comprehensive problem description covering hardcoded x86_64 MSSQL repo files breaking multi-architecture builds across 10 affected Dockerfiles (including datascience, CUDA, ROCm, and TrustyAI variants), detailed root cause analysis, three solution options with code examples, clear acceptance criteria for all image types, implementation guidance following established multi-architecture patterns, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py:1-769
Timestamp: 2025-07-08T19:35:49.482Z
Learning: jiridanek requested GitHub issue creation for bootstrapper code duplication problem in runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py during PR #1333 review. After an initial failed attempt, issue #1349 was successfully created with comprehensive problem description covering maintenance overhead and consistency risks from duplicate implementations across 5 Python 3.12 runtime environments, four solution options (symlinks, import-based, template-based, direct shared import) with pros/cons analysis, clear acceptance criteria for consolidation and maintainability, step-by-step implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/datascience/ubi9-python-3.12/Pipfile:33-34
Timestamp: 2025-07-08T19:26:17.140Z
Learning: jiridanek requested GitHub issue creation for jupyter-client dependency pinning inconsistency during PR #1333 review, specifically asking to note the implications of breaking changes in 9.x versions. Issue #1343 was created with comprehensive problem description covering inconsistent pinning style across all Python 3.12 runtime images, detailed breaking changes analysis (kernel protocol, session management, connection security, API changes, async/await modifications), reproducibility and security impact assessment, multiple solution options with code examples, phased acceptance criteria, implementation guidance, testing approach, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-14T15:36:29.815Z
Learning: ROCm is not supported by upstream TensorFlow, unlike CUDA. ROCm support requires the specialized tensorflow_rocm package, which creates a dependency challenge for Python 3.12 environments since tensorflow_rocm lacks Python 3.12 wheels while regular TensorFlow lacks ROCm support.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:05:33.329Z
Learning: tensorflow_rocm package has no Python 3.12 or 3.13 wheel support as of July 2025, with the latest version 2.14.0.600 only supporting Python 3.9, 3.10, and 3.11. The tensorflow-rocm upstream project appears abandoned with the last release in 2019. For Python 3.12+ ROCm TensorFlow environments, regular TensorFlow 2.18+ with runtime ROCm configuration is the recommended and industry-standard approach, as modern TensorFlow automatically detects and utilizes ROCm when properly installed.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: tensorflow_rocm package versions 2.12.1.570 through 2.14.0.600 do not provide Python 3.12 wheels (cp312) on PyPI, causing Pipfile lock failures when attempting to create Python 3.12-based ROCm TensorFlow notebook images in opendatahub-io/notebooks.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:05:33.329Z
Learning: tensorflow_rocm package has no Python 3.12 or 3.13 wheel support as of July 2025, with the latest version 2.14.0.600 only supporting Python 3.9, 3.10, and 3.11. For Python 3.12+ ROCm TensorFlow environments, regular TensorFlow with runtime ROCm configuration is the recommended alternative approach.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T10:41:56.419Z
Learning: jiridanek's team uses containerized dependency locking for cross-platform compatibility in opendatahub-io/notebooks. They run `pipenv lock` inside UBI9 containers with specific platform arguments (`--platform=linux/amd64 --python-version 3.12`) to avoid host OS dependency conflicts when generating Pipfile.lock files.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T10:41:56.419Z
Learning: In the opendatahub-io/notebooks repository, TensorFlow packages with `extras = ["and-cuda"]` can cause build conflicts on macOS due to platform-specific CUDA packages. When the Dockerfile installs CUDA system-wide, removing the extras and letting TensorFlow find CUDA at runtime resolves these conflicts.
Learnt from: grdryn
PR: opendatahub-io/notebooks#1320
File: rstudio/rhel9-python-3.11/Dockerfile.cuda:34-35
Timestamp: 2025-07-04T10:41:13.061Z
Learning: In the opendatahub-io/notebooks repository, when adapting NVIDIA CUDA Dockerfiles, the project intentionally maintains consistency with upstream NVIDIA patterns even when it might involve potential risks like empty variable expansions in package installation commands. This is considered acceptable because the containers only run on RHEL 9 with known yum/dnf behavior, and upstream consistency is prioritized over defensive coding practices.
jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml (47)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T07:11:44.903Z
Learning: Resource limits in StatefulSet manifests in opendatahub-io/notebooks are configured for testing purposes, not production deployments. This affects risk assessment when reviewing resource configurations like memory and CPU limits.
Learnt from: jiridanek
PR: #1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: #1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: StatefulSet selector issue with empty spec.selector: {} is a known systemic problem across multiple images in opendatahub-io/notebooks repository, tracked in issue #1236. This affects multiple StatefulSet manifests and is being addressed centrally rather than in individual PRs.
Learnt from: jiridanek
PR: #1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22
Timestamp: 2025-06-30T14:36:53.890Z
Learning: The pod-patch.yaml file in jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/ is used only for running tests, not production deployments. This affects the risk assessment for resource management configurations like sizeLimit on emptyDir volumes.
Learnt from: jiridanek
PR: #1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/base/statefulset.yaml:54-60
Timestamp: 2025-06-30T14:43:08.138Z
Learning: Issue #1212 in opendatahub-io/notebooks demonstrates that missing securityContext configuration (allowPrivilegeEscalation, runAsNonRoot, seccompProfile) causes runtime pods to fail reaching ready state and timeout after 300s on OpenShift due to PodSecurity policy violations.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-02T18:29:07.858Z
Learning: jiridanek consolidates systematic issues across multiple affected components into single comprehensive tracking issues rather than maintaining separate issues for each affected item. When the StatefulSet selector problem was identified across 13 different Jupyter image configurations, he requested merging issues #1236 and #1264 to track the entire scope systematically.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-02T18:29:07.858Z
Learning: jiridanek consolidates systematic issues across multiple affected components into single comprehensive tracking issues rather than maintaining separate issues for each affected item. When the StatefulSet selector problem was identified across 13 different Jupyter image configurations, he requested merging issues #1236 and #1264 to track the entire scope systematically.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: Runtime deployment tests in opendatahub-io/notebooks may show PodSecurity warnings about allowPrivilegeEscalation, capabilities, runAsNonRoot, and seccompProfile settings. These warnings occur on OpenShift but not on GitHub Actions because GitHub Actions uses upstream Kubernetes without SecurityContextConstraints (SCC).
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-09T18:14:03.719Z
Learning: When analyzing OpenShift CI/Prow job failures in opendatahub-io/notebooks, namespace initialization failures with "the object has been modified; please apply your changes to the latest version and try again" errors are typically transient infrastructure issues caused by concurrent modifications to the namespace object during CI setup, not code problems.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/kustomize/base/pod.yaml:11-11
Timestamp: 2025-07-03T16:17:17.301Z
Learning: jiridanek requested GitHub issue creation for renaming placeholder image reference in codeserver/ubi9-python-3.12/kustomize/base/pod.yaml during PR #1269 review to improve code self-documentation. Issue #1313 was created with comprehensive problem description, multiple implementation options (UPPERCASE_WITH_UNDERSCORES, lowercase-with-dashes, environment variable style), acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1333
File: runtimes/pytorch/ubi9-python-3.12/Dockerfile.cuda:17-25
Timestamp: 2025-07-09T08:07:30.628Z
Learning: jiridanek requested GitHub issue creation for oc client installation permission problem in PyTorch CUDA runtime Dockerfile during PR #1333 review. Issue #1356 was created with comprehensive problem description covering USER 1001 permission conflicts with root-owned /opt/app-root/bin directory, detailed impact analysis of build failures and non-executable binaries, current problematic code snippet, complete solution with user switching approach, clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/root/usr/share/container-scripts/nginx/common.sh:4-11
Timestamp: 2025-07-03T12:08:47.691Z
Learning: jiridanek requests GitHub issue creation for shell script quality improvements identified during PR #1269 review, specifically for POSIX compliance and security issues in codeserver/ubi9-python-3.12/nginx/root/usr/share/container-scripts/nginx/common.sh. Issue #1275 was created with comprehensive problem descriptions, acceptance criteria, implementation guidance, and proper context linking.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/root/opt/app-root/etc/passwd.template:14-14
Timestamp: 2025-07-03T16:28:55.757Z
Learning: jiridanek requested GitHub issue creation for passwd template validation in codeserver/ubi9-python-3.12/nginx/root/opt/app-root/etc/passwd.template during PR #1269 review. Issue #1318 was created with comprehensive analysis of nss_wrapper approach advantages over OpenShift's native user management, including consistent user identity, application compatibility, and debugging benefits. The current approach works with OpenShift's random UID assignment by dynamically setting USER_ID and GROUP_ID to actual runtime values while providing enhanced user attributes through nss_wrapper.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/run-nginx.sh:18-23
Timestamp: 2025-07-03T16:17:23.065Z
Learning: jiridanek requested GitHub issue creation for shell script variable quoting security concern in codeserver/ubi9-python-3.12/run-nginx.sh during PR #1269 review. The issue covers unquoted variables NB_PREFIX, NOTEBOOK_ARGS, and BASE_URL that pose security risks including command injection, word-splitting vulnerabilities, and globbing issues. A comprehensive issue was created with detailed problem description, security concerns, solution with code examples, acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/root/opt/app-root/etc/generate_container_user:4-9
Timestamp: 2025-07-03T16:05:35.448Z
Learning: jiridanek requested GitHub issue creation for shell script error handling improvements in codeserver/ubi9-python-3.12/nginx/root/opt/app-root/etc/generate_container_user during PR #1269 review. A comprehensive issue was created covering silent failures, unquoted variable expansions, missing template validation, and strict mode implementation with detailed problem descriptions, phased acceptance criteria, implementation guidance with code examples, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/run-code-server.sh:7-10
Timestamp: 2025-07-03T14:01:22.819Z
Learning: jiridanek requested GitHub issue creation for container startup robustness and lifecycle management improvements in codeserver/ubi9-python-3.12/run-code-server.sh during PR #1269 review. A comprehensive issue was created covering race conditions, failure detection, process lifecycle coupling, and signal handling with detailed problem descriptions, multiple solution options, phased acceptance criteria, testing approach, and proper context linking, following the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:33:55.209Z
Learning: jiridanek requested GitHub issue creation for smart-open library S3/GCS backend compatibility concern in PR #1269. Issue #1296 was successfully created with comprehensive problem description, acceptance criteria, implementation guidance, testing approach, and proper context linking, following the established pattern of systematic issue tracking for technical improvements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T12:44:00.167Z
Learning: jiridanek requested GitHub issue creation for smart-open library S3/GCS backend compatibility concern in PR #1269. Issue #1289 was successfully created with comprehensive problem description, acceptance criteria, implementation guidance, testing approach, and proper context linking, following the established pattern of systematic issue tracking for technical improvements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T12:44:00.167Z
Learning: jiridanek requested GitHub issue creation for smart-open library compatibility concern in PR #1269, specifically about potential S3/GCS backend functionality loss due to smart-open dropping implicit extras since version 6.x. Issue creation follows established pattern of comprehensive problem descriptions, acceptance criteria, implementation guidance, and proper context linking.
Learnt from: jiridanek
PR: #1333
File: runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py:1-769
Timestamp: 2025-07-08T19:35:49.482Z
Learning: jiridanek requested GitHub issue creation for bootstrapper code duplication problem in runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py during PR #1333 review. After an initial failed attempt, issue #1349 was successfully created with comprehensive problem description covering maintenance overhead and consistency risks from duplicate implementations across 5 Python 3.12 runtime environments, four solution options (symlinks, import-based, template-based, direct shared import) with pros/cons analysis, clear acceptance criteria for consolidation and maintainability, step-by-step implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:01:18.625Z
Learning: jiridanek requested GitHub issue creation for markdown linting improvements in PR #1269, specifically addressing MD014 violations in README files and suggesting repository-wide markdown linter integration. Issue #1290 was created with comprehensive tooling recommendations, implementation phases, acceptance criteria, and systematic approach to documentation quality improvements.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/requirements.txt:435-444
Timestamp: 2025-07-03T13:59:55.040Z
Learning: jiridanek requested GitHub issue creation for numpy/scipy compatibility investigation in PR #1269, specifically for cases where theoretical version conflicts don't manifest as actual build failures. Issue #1297 was created with comprehensive investigation framework, acceptance criteria, runtime testing approach, and proper context linking, demonstrating the pattern of creating investigation-type issues for apparent but non-blocking technical concerns that require deeper understanding.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/root/usr/share/container-scripts/nginx/common.sh:1-3
Timestamp: 2025-07-03T12:07:19.365Z
Learning: jiridanek consistently requests GitHub issue creation for technical improvements identified during code reviews in opendatahub-io/notebooks, ensuring systematic tracking of code quality enhancements like shell script portability issues with comprehensive descriptions, solution options, and acceptance criteria.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:71-76
Timestamp: 2025-07-04T06:04:43.085Z
Learning: jiridanek requested GitHub issue creation for duplicate CSV loading and validation problem in jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb during PR #1306 review. Issue #1322 was created with comprehensive problem description covering code redundancy, runtime failure risks, network inefficiency, and test reliability concerns, along with detailed solution including duplicate line removal, data validation implementation, repository-wide audit, acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:01:18.625Z
Learning: jiridanek requested GitHub issue creation for markdown linting improvements in PR #1269, specifically addressing MD014 violations in README files while also suggesting repository-wide markdown linter integration. Issue #1290 was successfully created with comprehensive tooling recommendations, phased implementation plan, clear acceptance criteria, and systematic approach to documentation quality improvements, continuing the established pattern of systematic code quality enhancements.
Learnt from: jiridanek
PR: #1333
File: runtimes/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-08T19:29:32.006Z
Learning: jiridanek requested GitHub issue creation for investigating TensorFlow "and-cuda" extras usage patterns during PR #1333 review. Issue #1345 was created with comprehensive investigation framework covering platform-specific analysis, deployment scenarios, TensorFlow version compatibility, clear acceptance criteria, and testing approach, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:59:15.788Z
Learning: jiridanek creates targeted GitHub issues for specific test quality improvements identified during PR reviews in opendatahub-io/notebooks. Issue #1268 demonstrates this by converting a review comment about insufficient tf2onnx conversion test validation into a comprehensive improvement plan with clear acceptance criteria, code examples, and ROCm-specific context.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-11T11:16:05.131Z
Learning: jiridanek requested GitHub issue creation for RStudio py311 Tekton push pipelines during PR #1379 review. Issue #1384 was successfully created covering two RStudio variants (CPU and CUDA) found in manifests/base/params-latest.env, with comprehensive problem description, implementation requirements following the same pattern as other workbench pipelines, clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1320
File: jupyter/pytorch/ubi9-python-3.12/Dockerfile.cuda:65-66
Timestamp: 2025-07-09T12:31:02.033Z
Learning: jiridanek requested GitHub issue creation for MSSQL repo file hardcoding problem during PR #1320 review. Issue #1363 was created and updated with comprehensive problem description covering hardcoded x86_64 MSSQL repo files breaking multi-architecture builds across 10 affected Dockerfiles (including datascience, CUDA, ROCm, and TrustyAI variants), detailed root cause analysis, three solution options with code examples, clear acceptance criteria for all image types, implementation guidance following established multi-architecture patterns, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1379
File: .tekton/odh-workbench-jupyter-datascience-cpu-py312-ubi9-push.yaml:14-17
Timestamp: 2025-07-11T11:15:47.424Z
Learning: jiridanek requested GitHub issue creation for CEL filter problem in datascience workbench Tekton pipelines during PR #1379 review. Issue #1383 was successfully created with comprehensive problem description covering both Python 3.11 and 3.12 pipelines incorrectly watching jupyter/minimal directories instead of jupyter/datascience directories, detailed impact analysis of pipeline execution failures, complete solution with before/after code examples, thorough acceptance criteria for path updates and pipeline triggering verification, implementation notes about repository structure alignment, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb:22-29
Timestamp: 2025-07-02T18:27:51.097Z
Learning: jiridanek consistently creates comprehensive follow-up GitHub issues from PR review comments in opendatahub-io/notebooks, turning specific code quality concerns into systematic improvements tracked with proper context, acceptance criteria, and cross-references. Issue #1266 demonstrates this pattern by expanding a specific error handling concern in load_expected_versions() into a repository-wide improvement initiative.
Learnt from: jiridanek
PR: #1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-09T08:07:24.937Z
Learning: jiridanek requested GitHub issue creation for tensorflow_rocm Python 3.12 compatibility problem during PR #1333 review. Issue #1354 was successfully created with comprehensive problem description covering missing cp312 wheels causing build failures, three solution options (upstream TensorFlow, Python 3.11 only, custom build), clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1230
File: jupyter/minimal/ubi9-python-3.12/Dockerfile.rocm:43-55
Timestamp: 2025-07-01T06:48:21.070Z
Learning: When security concerns are raised during PR reviews in opendatahub-io/notebooks, comprehensive follow-up issues are created (often by CodeRabbit) to track all related security enhancements with clear acceptance criteria and implementation guidance. This ensures security improvements are systematically addressed in dedicated efforts rather than blocking current deliverables.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/Dockerfile.cpu:4-4
Timestamp: 2025-07-04T05:49:10.314Z
Learning: jiridanek directs base image pinning security concerns to existing comprehensive issue #1242 "Improve Docker FROM image versioning by avoiding :latest tags" rather than addressing them in individual PRs, continuing the established pattern of systematic security and quality tracking in opendatahub-io/notebooks.
Learnt from: atheo89
PR: #1401
File: manifests/overlays/additional/runtime-datascience-imagestream-beta.yaml:8-10
Timestamp: 2025-07-16T10:44:40.023Z
Learning: atheo89 pointed out that the doubled slash issue in runtime-image-url annotations affects multiple imagestream files repository-wide (11 files total), not just individual files. When systematic issues like this are identified during PR review, they should be addressed as separate comprehensive issues rather than individual file fixes, especially when they're outside the scope of the current PR. Issue #1402 was created to track this systematic problem.
Learnt from: atheo89
PR: #1401
File: manifests/overlays/additional/runtime-datascience-imagestream-beta.yaml:8-10
Timestamp: 2025-07-16T10:44:40.023Z
Learning: atheo89 pointed out that the doubled slash issue in runtime-image-url annotations affects multiple imagestream files repository-wide, not just individual files. When systematic issues like this are identified during PR review, they should be addressed as separate comprehensive issues rather than individual file fixes, especially when they're outside the scope of the current PR.
Learnt from: jiridanek
PR: #1258
File: codeserver/ubi9-python-3.11/Dockerfile.cpu:55-56
Timestamp: 2025-07-03T08:22:25.348Z
Learning: jiridanek directs security concerns raised during PR reviews to existing comprehensive security issues rather than addressing them in individual PRs. Issue #1241 "Security: Add checksum verification for downloaded binaries in Python 3.12 images" serves as the central tracking issue for all binary download security concerns across the opendatahub-io/notebooks repository.
Learnt from: jiridanek
PR: #1230
File: jupyter/minimal/ubi9-python-3.12/Dockerfile.rocm:43-55
Timestamp: 2025-07-01T06:48:21.070Z
Learning: When jiridanek encounters security feedback during PR reviews in opendatahub-io/notebooks, he creates dedicated GitHub issues to track them as follow-up improvements rather than blocking the current PR. This demonstrates effective project management by separating immediate deliverables from security enhancements that require dedicated testing and validation.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Dockerfile.rocm:56-66
Timestamp: 2025-07-02T18:19:49.397Z
Learning: jiridanek consistently creates comprehensive follow-up GitHub issues for security concerns raised during PR reviews in opendatahub-io/notebooks, ensuring systematic tracking and resolution of supply-chain security improvements like GPG signature verification for package repositories.
Learnt from: jiridanek
PR: #1230
File: jupyter/minimal/ubi9-python-3.12/Dockerfile.cpu:21-24
Timestamp: 2025-07-01T06:48:13.154Z
Learning: jiridanek creates comprehensive follow-up issues from review comments that expand scope appropriately, include clear acceptance criteria, proper backlinks, and structured implementation guidance. Issue #1241 demonstrates this by turning a specific oc client checksum concern into a thorough security enhancement plan covering all downloaded binaries across the Python 3.12 implementation.
Learnt from: jiridanek
PR: #1333
File: runtimes/datascience/ubi9-python-3.12/Pipfile:33-34
Timestamp: 2025-07-08T19:26:17.140Z
Learning: jiridanek requested GitHub issue creation for jupyter-client dependency pinning inconsistency during PR #1333 review, specifically asking to note the implications of breaking changes in 9.x versions. Issue #1343 was created with comprehensive problem description covering inconsistent pinning style across all Python 3.12 runtime images, detailed breaking changes analysis (kernel protocol, session management, connection security, API changes, async/await modifications), reproducibility and security impact assessment, multiple solution options with code examples, phased acceptance criteria, implementation guidance, testing approach, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb (57)
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:44-50
Timestamp: 2025-07-03T16:18:59.234Z
Learning: In the opendatahub-io/notebooks repository, the expected_versions.json file referenced in test notebooks (like test_notebook.ipynb) is generated during test execution, not included as a static file in the PR. This is an established testing pattern that should not be flagged as a missing file issue. The pattern is actively managed through issues like #1243 "Improve error handling in get_expected_version() functions across test notebooks" and #1254 "Fix undefined variable error in ROCm PyTorch Python 3.12 test notebook".
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:59:15.788Z
Learning: jiridanek creates targeted GitHub issues for specific test quality improvements identified during PR reviews in opendatahub-io/notebooks. Issue #1268 demonstrates this by converting a review comment about insufficient tf2onnx conversion test validation into a comprehensive improvement plan with clear acceptance criteria, code examples, and ROCm-specific context.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-23T16:18:42.922Z
Learning: The TensorFlow ROCm Python 3.12 compatibility issue in opendatahub-io/notebooks PR #1259 was caused by using tensorflow-rocm==2.14.0.600 in Pipfile.lock which lacks Python 3.12 wheels, while the Pipfile specifies tensorflow_rocm=~=2.18.1. The solution requires updating Pipfile sources to include https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4/ repository which contains tensorflow_rocm-2.18.1-cp312-cp312-manylinux_2_28_x86_64.whl and regenerating Pipfile.lock using the piplock-refresh GitHub Action.
Learnt from: jiridanek
PR: #1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-09T08:07:24.937Z
Learning: jiridanek requested GitHub issue creation for tensorflow_rocm Python 3.12 compatibility problem during PR #1333 review. Issue #1354 was successfully created with comprehensive problem description covering missing cp312 wheels causing build failures, three solution options (upstream TensorFlow, Python 3.11 only, custom build), clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: The Python 3.11 infrastructure for ROCm TensorFlow images in opendatahub-io/notebooks is already properly configured in the Makefile with both BASE_DIRS entries for Pipfile lock renewals and all-images targets for CI builds, requiring only commenting out the corresponding Python 3.12 entries when downgrading due to wheel availability issues.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: tensorflow_rocm package versions 2.12.1.570 through 2.14.0.600 do not provide Python 3.12 wheels (cp312) on PyPI, causing Pipfile lock failures when attempting to create Python 3.12-based ROCm TensorFlow notebook images in opendatahub-io/notebooks.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:71-76
Timestamp: 2025-07-04T06:04:43.085Z
Learning: jiridanek requested GitHub issue creation for duplicate CSV loading and validation problem in jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb during PR #1306 review. Issue #1322 was created with comprehensive problem description covering code redundancy, runtime failure risks, network inefficiency, and test reliability concerns, along with detailed solution including duplicate line removal, data validation implementation, repository-wide audit, acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1247
File: .github/workflows/build-notebooks-TEMPLATE.yaml:50-53
Timestamp: 2025-07-01T14:36:52.852Z
Learning: In the opendatahub-io/notebooks repository, the test runner's Python version (configured in GitHub Actions UV setup) intentionally doesn't need to match the Python version of the container images being tested. jiridanek's team uses Python 3.12 for running tests while images may use different Python versions (like 3.11), and this approach works fine since the test code is separate from the application code running inside the containers.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:44-50
Timestamp: 2025-07-03T16:18:59.234Z
Learning: In the opendatahub-io/notebooks repository, the expected_versions.json file referenced in test notebooks (like test_notebook.ipynb) is generated during test execution, not included as a static file in the PR. This is an established testing pattern that should not be flagged as a missing file issue.
Learnt from: jiridanek
PR: #1333
File: runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py:1-769
Timestamp: 2025-07-08T19:35:49.482Z
Learning: jiridanek requested GitHub issue creation for bootstrapper code duplication problem in runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py during PR #1333 review. After an initial failed attempt, issue #1349 was successfully created with comprehensive problem description covering maintenance overhead and consistency risks from duplicate implementations across 5 Python 3.12 runtime environments, four solution options (symlinks, import-based, template-based, direct shared import) with pros/cons analysis, clear acceptance criteria for consolidation and maintainability, step-by-step implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:71-88
Timestamp: 2025-07-04T06:05:30.580Z
Learning: jiridanek requested GitHub issue creation for TrustyAI test notebook URL configurability and network error handling improvements during PR #1306 review. Issue #1323 was created with
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1333
File: runtimes/datascience/ubi9-python-3.12/Pipfile:33-34
Timestamp: 2025-07-08T19:26:17.140Z
Learning: jiridanek requested GitHub issue creation for jupyter-client dependency pinning inconsistency during PR #1333 review, specifically asking to note the implications of breaking changes in 9.x versions. Issue #1343 was created with comprehensive problem description covering inconsistent pinning style across all Python 3.12 runtime images, detailed breaking changes analysis (kernel protocol, session management, connection security, API changes, async/await modifications), reproducibility and security impact assessment, multiple solution options with code examples, phased acceptance criteria, implementation guidance, testing approach, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:102-102
Timestamp: 2025-07-03T16:26:18.718Z
Learning: jiridanek requested GitHub issue creation for improving hardcoded threshold constants in TrustyAI test notebook during PR #1306 review. Issue #1317 was created with comprehensive problem description covering both bias detection threshold (-0.15670061634672994) and fairness threshold (0.0036255104824703954), multiple solution options with code examples, clear acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1333
File: runtimes/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-08T19:29:32.006Z
Learning: jiridanek requested GitHub issue creation for investigating TensorFlow "and-cuda" extras usage patterns during PR #1333 review. Issue #1340 was created with comprehensive investigation framework covering platform-specific analysis, deployment scenarios, TensorFlow version compatibility, clear acceptance criteria, testing approach, and implementation timeline, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1333
File: runtimes/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-08T19:29:32.006Z
Learning: jiridanek requested GitHub issue creation for investigating TensorFlow "and-cuda" extras usage patterns during PR #1333 review. Issue #1345 was created with comprehensive investigation framework covering platform-specific analysis, deployment scenarios, TensorFlow version compatibility, clear acceptance criteria, and testing approach, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Dockerfile.rocm:50-50
Timestamp: 2025-07-08T19:30:01.738Z
Learning: jiridanek requested GitHub issue creation for multi-architecture support in ROCm TensorFlow image during PR #1333 review. Issue #1346 was created with comprehensive problem description covering hardcoded x86_64 architecture breaking multi-arch support, detailed impact analysis, three solution options (runtime detection, BuildKit TARGETARCH integration, hybrid approach) with pros/cons analysis, comprehensive acceptance criteria covering core requirements and testing, phased implementation guidance, related files identification, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1325
File: jupyter/pytorch/ubi9-python-3.12/Pipfile:42-42
Timestamp: 2025-07-09T14:22:14.553Z
Learning: jiridanek requested GitHub issue creation for Pipfile.lock verification script implementation during PR #1325 review, specifically to systematize the manual verification process for dependency version consistency across all lock files using jq. Issue #1367 was created with comprehensive problem description covering manual verification challenges, detailed solution with jq-based verification script, enhanced features for CI integration, clear acceptance criteria, implementation areas breakdown, benefits analysis, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-24T12:01:45.188Z
Learning: jiridanek requested verification of 2024.2 tag package versions against corresponding Pipfiles during PR #1496 review. The analysis revealed that 2024.2 tags contain intentionally frozen older versions (N-1 behavior) while the current PR correctly updates only the N (latest) tags to match Python 3.11 Pipfiles, demonstrating proper understanding of the repository's N-1 version freezing policy.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:33:55.209Z
Learning: jiridanek requested GitHub issue creation for smart-open library S3/GCS backend compatibility concern in PR #1269. Issue #1296 was successfully created with comprehensive problem description, acceptance criteria, implementation guidance, testing approach, and proper context linking, following the established pattern of systematic issue tracking for technical improvements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T12:44:00.167Z
Learning: jiridanek requested GitHub issue creation for smart-open library S3/GCS backend compatibility concern in PR #1269. Issue #1289 was successfully created with comprehensive problem description, acceptance criteria, implementation guidance, testing approach, and proper context linking, following the established pattern of systematic issue tracking for technical improvements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T12:44:00.167Z
Learning: jiridanek requested GitHub issue creation for smart-open library compatibility concern in PR #1269, specifically about potential S3/GCS backend functionality loss due to smart-open dropping implicit extras since version 6.x. Issue creation follows established pattern of comprehensive problem descriptions, acceptance criteria, implementation guidance, and proper context linking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:01:18.625Z
Learning: jiridanek requested GitHub issue creation for markdown linting improvements in PR #1269, specifically addressing MD014 violations in README files and suggesting repository-wide markdown linter integration. Issue #1290 was created with comprehensive tooling recommendations, implementation phases, acceptance criteria, and systematic approach to documentation quality improvements.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/requirements.txt:435-444
Timestamp: 2025-07-03T13:59:55.040Z
Learning: jiridanek requested GitHub issue creation for numpy/scipy compatibility investigation in PR #1269, specifically for cases where theoretical version conflicts don't manifest as actual build failures. Issue #1297 was created with comprehensive investigation framework, acceptance criteria, runtime testing approach, and proper context linking, demonstrating the pattern of creating investigation-type issues for apparent but non-blocking technical concerns that require deeper understanding.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/root/usr/share/container-scripts/nginx/common.sh:1-3
Timestamp: 2025-07-03T12:07:19.365Z
Learning: jiridanek consistently requests GitHub issue creation for technical improvements identified during code reviews in opendatahub-io/notebooks, ensuring systematic tracking of code quality enhancements like shell script portability issues with comprehensive descriptions, solution options, and acceptance criteria.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:01:18.625Z
Learning: jiridanek requested GitHub issue creation for markdown linting improvements in PR #1269, specifically addressing MD014 violations in README files while also suggesting repository-wide markdown linter integration. Issue #1290 was successfully created with comprehensive tooling recommendations, phased implementation plan, clear acceptance criteria, and systematic approach to documentation quality improvements, continuing the established pattern of systematic code quality enhancements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-11T11:16:05.131Z
Learning: jiridanek requested GitHub issue creation for RStudio py311 Tekton push pipelines during PR #1379 review. Issue #1384 was successfully created covering two RStudio variants (CPU and CUDA) found in manifests/base/params-latest.env, with comprehensive problem description, implementation requirements following the same pattern as other workbench pipelines, clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1379
File: .tekton/odh-workbench-jupyter-datascience-cpu-py312-ubi9-push.yaml:14-17
Timestamp: 2025-07-11T11:15:47.424Z
Learning: jiridanek requested GitHub issue creation for CEL filter problem in datascience workbench Tekton pipelines during PR #1379 review. Issue #1383 was successfully created with comprehensive problem description covering both Python 3.11 and 3.12 pipelines incorrectly watching jupyter/minimal directories instead of jupyter/datascience directories, detailed impact analysis of pipeline execution failures, complete solution with before/after code examples, thorough acceptance criteria for path updates and pipeline triggering verification, implementation notes about repository structure alignment, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb:22-29
Timestamp: 2025-07-02T18:27:51.097Z
Learning: jiridanek consistently creates comprehensive follow-up GitHub issues from PR review comments in opendatahub-io/notebooks, turning specific code quality concerns into systematic improvements tracked with proper context, acceptance criteria, and cross-references. Issue #1266 demonstrates this pattern by expanding a specific error handling concern in load_expected_versions() into a repository-wide improvement initiative.
Learnt from: jiridanek
PR: #1230
File: jupyter/minimal/ubi9-python-3.12/Dockerfile.rocm:43-55
Timestamp: 2025-07-01T06:48:21.070Z
Learning: When security concerns are raised during PR reviews in opendatahub-io/notebooks, comprehensive follow-up issues are created (often by CodeRabbit) to track all related security enhancements with clear acceptance criteria and implementation guidance. This ensures security improvements are systematically addressed in dedicated efforts rather than blocking current deliverables.
Learnt from: jiridanek
PR: #1230
File: jupyter/minimal/ubi9-python-3.12/Dockerfile.cpu:21-24
Timestamp: 2025-07-01T06:48:13.154Z
Learning: jiridanek creates comprehensive follow-up issues from review comments that expand scope appropriately, include clear acceptance criteria, proper backlinks, and structured implementation guidance. Issue #1241 demonstrates this by turning a specific oc client checksum concern into a thorough security enhancement plan covering all downloaded binaries across the Python 3.12 implementation.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/api/kernels/access.cgi:8-10
Timestamp: 2025-07-03T14:01:27.789Z
Learning: jiridanek requested GitHub issue creation for JSON parsing robustness improvement in codeserver/ubi9-python-3.12/nginx/api/kernels/access.cgi during PR #1269 review, specifically for replacing fragile grep/awk/date chain with jq-based JSON parsing to improve reliability and maintainability. Issue #1299 was successfully created with comprehensive problem description, solution details, acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/api/kernels/access.cgi:8-10
Timestamp: 2025-07-03T14:01:27.789Z
Learning: jiridanek requested GitHub issue creation for JSON parsing robustness improvement in codeserver/ubi9-python-3.12/nginx/api/kernels/access.cgi during PR #1269 review, specifically for replacing fragile grep/awk/date chain with jq-based JSON parsing to improve reliability and maintainability. Issue was created with comprehensive problem description, solution details, acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:31:35.667Z
Learning: jiridanek requested GitHub issue creation for comprehensive shell scripting improvements in codeserver image during PR #1269 review, covering process management, JSON parsing robustness, variable quoting security, and sed pattern fixes. Issue #1295 was created with systematic phased approach, detailed problem descriptions, implementation guidance, acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:27:38.813Z
Learning: jiridanek requested GitHub issue creation for comprehensive shell scripting improvements in codeserver image during PR #1269 review, covering process management, JSON parsing robustness, variable quoting security, and sed pattern fixes. Issue #1293 was created with systematic phased approach, detailed problem descriptions, implementation guidance, acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:27:38.813Z
Learning: jiridanek requested GitHub issue creation for comprehensive shell scripting improvements in codeserver image during PR #1269 review, covering process management, JSON parsing robustness, variable quoting security, and sed pattern fixes. Issue #1293 was created with systematic phased approach, detailed problem descriptions, implementation guidance, acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/root/usr/share/container-scripts/nginx/common.sh:4-11
Timestamp: 2025-07-03T16:04:22.695Z
Learning: jiridanek requested GitHub issue creation for shell script quality improvements in codeserver/ubi9-python-3.12/nginx/root/usr/share/container-scripts/nginx/common.sh during PR #1269 review. Issue #1307 was created with comprehensive problem description covering variable scoping issues, POSIX compliance concerns, multiple solution options, acceptance criteria, implementation guidance with code examples, testing approaches, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: #1397
File: .github/workflows/piplock-renewal.yaml:16-26
Timestamp: 2025-07-15T16:09:15.689Z
Learning: jiridanek confirmed that GitHub Actions' fromJSON() function is more lenient than expected and can parse JSON-like strings with single quotes and spaces (e.g., "['3.11', '3.12']") in workflow_dispatch inputs, even though this is not valid JSON syntax. However, he agrees that following valid JSON syntax is still recommended for code quality.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/root/opt/app-root/etc/generate_container_user:4-9
Timestamp: 2025-07-03T16:05:35.448Z
Learning: jiridanek requested GitHub issue creation for shell script error handling improvements in codeserver/ubi9-python-3.12/nginx/root/opt/app-root/etc/generate_container_user during PR #1269 review. A comprehensive issue was created covering silent failures, unquoted variable expansions, missing template validation, and strict mode implementation with detailed problem descriptions, phased acceptance criteria, implementation guidance with code examples, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/run-code-server.sh:20-40
Timestamp: 2025-07-03T12:27:09.739Z
Learning: jiridanek requested GitHub issue creation for shell script error handling improvements in codeserver/ubi9-python-3.12/run-code-server.sh create_dir_and_file function during PR #1269 review. Issue #1284 was created with comprehensive problem description, acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: #1426
File: tests/browser/tests/codeserver.spec.ts:5-7
Timestamp: 2025-07-22T06:05:14.887Z
Learning: jiridanek requested GitHub issue creation for testcontainers internal API import fix during PR #1426 review. Issue #1428 was successfully created covering replacement of fragile internal build file imports with public Wait.forHttp() builder API to ensure compatibility across testcontainers version updates, affecting both 2024b and main branches with comprehensive problem description, solution with code examples, and acceptance criteria for systematic tracking of technical improvements.
Learnt from: jiridanek
PR: #1258
File: codeserver/ubi9-python-3.11/Dockerfile.cpu:55-56
Timestamp: 2025-07-03T08:22:25.348Z
Learning: jiridanek directs security concerns raised during PR reviews to existing comprehensive security issues rather than addressing them in individual PRs. Issue #1241 "Security: Add checksum verification for downloaded binaries in Python 3.12 images" serves as the central tracking issue for all binary download security concerns across the opendatahub-io/notebooks repository.
Learnt from: jiridanek
PR: #1230
File: jupyter/minimal/ubi9-python-3.12/Dockerfile.rocm:43-55
Timestamp: 2025-07-01T06:48:21.070Z
Learning: When jiridanek encounters security feedback during PR reviews in opendatahub-io/notebooks, he creates dedicated GitHub issues to track them as follow-up improvements rather than blocking the current PR. This demonstrates effective project management by separating immediate deliverables from security enhancements that require dedicated testing and validation.
Learnt from: jiridanek
PR: #1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: #1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: StatefulSet selector issue with empty spec.selector: {} is a known systemic problem across multiple images in opendatahub-io/notebooks repository, tracked in issue #1236. This affects multiple StatefulSet manifests and is being addressed centrally rather than in individual PRs.
Learnt from: jiridanek
PR: #1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22
Timestamp: 2025-06-30T14:36:53.890Z
Learning: The pod-patch.yaml file in jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/ is used only for running tests, not production deployments. This affects the risk assessment for resource management configurations like sizeLimit on emptyDir volumes.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-02T18:29:07.858Z
Learning: jiridanek consolidates systematic issues across multiple affected components into single comprehensive tracking issues rather than maintaining separate issues for each affected item. When the StatefulSet selector problem was identified across 13 different Jupyter image configurations, he requested merging issues #1236 and #1264 to track the entire scope systematically.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-02T18:29:07.858Z
Learning: jiridanek consolidates systematic issues across multiple affected components into single comprehensive tracking issues rather than maintaining separate issues for each affected item. When the StatefulSet selector problem was identified across 13 different Jupyter image configurations, he requested merging issues #1236 and #1264 to track the entire scope systematically.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/kustomize/base/pod.yaml:11-11
Timestamp: 2025-07-03T16:17:17.301Z
Learning: jiridanek requested GitHub issue creation for renaming placeholder image reference in codeserver/ubi9-python-3.12/kustomize/base/pod.yaml during PR #1269 review to improve code self-documentation. Issue #1313 was created with comprehensive problem description, multiple implementation options (UPPERCASE_WITH_UNDERSCORES, lowercase-with-dashes, environment variable style), acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1418
File: tests/browser/README.md:14-18
Timestamp: 2025-07-21T12:58:43.996Z
Learning: In the opendatahub-io/notebooks repository, upstream project testing framework references in README files serve as informational context about the broader ecosystem, not as recommendations for the current project. These references help contributors understand what other related projects use and should be retained even when the current project doesn't use those frameworks.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: Test failures in opendatahub-io/notebooks should be categorized as either repository bugs (code/configuration issues) or infrastructure issues (CI platform problems) for proper diagnosis and resolution.
Learnt from: jiridanek
PR: #1218
File: jupyter/rocm/pytorch/ubi9-python-3.11/requirements.txt:987-989
Timestamp: 2025-06-28T15:06:03.344Z
Learning: In the opendatahub-io/notebooks repository, checks for broken links and missing files in kustomization manifests are already performed by ci/kustomize.sh, which is invoked from .github/workflows/code-quality.yaml (lines 112–116). No additional pytest is needed for this purpose.
🪛 Checkov (3.2.334)
jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml
[MEDIUM] 2-60: Containers should not run with allowPrivilegeEscalation
(CKV_K8S_20)
[MEDIUM] 2-60: Minimize the admission of root containers
(CKV_K8S_23)
🪛 Ruff (0.12.2)
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
7-7: tensorboard imported but unused
Remove unused import: tensorboard
(F401)
13-13: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
13-13: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
17-17: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
20-20: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
23-23: Trailing whitespace
Remove trailing whitespace
(W291)
28-28: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
28-28: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
29-29: Trailing whitespace
Remove trailing whitespace
(W291)
33-33: Blank line contains whitespace
Remove whitespace from blank line
(W293)
35-35: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
36-36: Trailing whitespace
Remove trailing whitespace
(W291)
38-38: Blank line contains whitespace
Remove whitespace from blank line
(W293)
40-40: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
41-41: Trailing whitespace
Remove trailing whitespace
(W291)
43-43: Blank line contains whitespace
Remove whitespace from blank line
(W293)
48-48: Blank line contains whitespace
Remove whitespace from blank line
(W293)
58-58: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
63-63: Found useless expression. Either assign it to a variable or remove it.
(B018)
67-67: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
67-67: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
69-69: Multiple spaces after comma
Replace with single space
(E241)
79-79: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
83-83: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
83-83: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
88-88: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
🔇 Additional comments (3)
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb (3)
36-46: Version validation tests look good.The Python and TensorFlow version tests appropriately validate the environment against expected versions.
48-53: tf2onnx conversion test appropriately validates package functionality.The test creates a simple model and converts it to ONNX format, which adequately validates that the tf2onnx package is working correctly in the ROCm environment.
97-100: Test execution setup follows established patterns.The test suite loading and execution using
unittest.TextTestRunner()appropriately runs all tests and provides output in the notebook environment.
jiridanek
changed the title
something's wrong with the url, are you sure it's a good one? |
[rhoai-2.22] Update N-1 image references with the new builds and update manifest package information
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Actionable comments posted: 0
♻️ Duplicate comments (5)
jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml (2)
12-16: Emptyspec.selector&template.metadata.labelsmake the StatefulSet invalid
Issue already tracked centrally in #1236; no further action required here.
18-60: MissingsecurityContext– container may run as root / allow privilege escalation
This concern is covered by existing repository-wide hardening issue #1212.jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb (3)
31-46: Existing error handling issue already tracked.The
get_expected_version()function error handling improvement is already covered by issue #1243.Minor formatting improvements can be applied:
def get_expected_version(dependency_name: str) -> str: raw_value = expected_versions.get(dependency_name) - raw_version = re.sub(r'^\\D+', '', raw_value) + raw_version = re.sub(r"^\\D+", "", raw_value) return get_major_minor(raw_version) class TestTensorflowNotebook(unittest.TestCase): - + def test_python_version(self): - expected_major_minor = get_expected_version('Python') + expected_major_minor = get_expected_version("Python") actual_major_minor = get_major_minor(python_version()) - self.assertEqual(actual_major_minor, expected_major_minor, \"incorrect version\") + self.assertEqual(actual_major_minor, expected_major_minor, "incorrect version") - + def test_tensorflow_version(self): - expected_major_minor = get_expected_version('ROCm-TensorFlow') + expected_major_minor = get_expected_version("ROCm-TensorFlow") actual_major_minor = get_major_minor(tf.__version__) - self.assertEqual(actual_major_minor, expected_major_minor, \"incorrect version\") + self.assertEqual(actual_major_minor, expected_major_minor, "incorrect version")
48-78: MNIST test improvements already tracked; fix useless expressions.The MNIST test assertion improvements are already covered by the existing discussion in past review comments.
Fix the useless expressions and formatting issues:
def test_tf2onnx_conversion(self): # Replace this with an actual TensorFlow model conversion using tf2onnx model = tf.keras.Sequential([tf.keras.layers.Dense(1, input_shape=(10,))]) onnx_model = tf2onnx.convert.from_keras(model) - + self.assertTrue(onnx_model is not None) def test_mnist_model(self): # A basic test from the official tensorflow webpage https://www.tensorflow.org/tutorials/quickstart/beginner mnist = tf.keras.datasets.mnist (x_train, y_train), (x_test, y_test) = mnist.load_data() x_train, x_test = x_train / 255.0, x_test / 255.0 model = tf.keras.models.Sequential([ tf.keras.layers.Flatten(input_shape=(28, 28)), - tf.keras.layers.Dense(128, activation='relu'), + tf.keras.layers.Dense(128, activation="relu"), tf.keras.layers.Dropout(0.2), tf.keras.layers.Dense(10) ]) predictions = model(x_train[:1]).numpy() - predictions + # Verify prediction shape + self.assertEqual(predictions.shape, (1, 10)) tf.nn.softmax(predictions).numpy() loss_fn = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True) loss_fn(y_train[:1], predictions).numpy() - model.compile(optimizer='adam', loss=loss_fn, metrics=['accuracy']) + model.compile(optimizer="adam", loss=loss_fn, metrics=["accuracy"]) model.fit(x_train, y_train, epochs=5) - model.evaluate(x_test, y_test, verbose=2) + model.evaluate(x_test, y_test, verbose=2) probability_model = tf.keras.Sequential([ model, tf.keras.layers.Softmax() ]) - probability_model(x_test[:5]) + probabilities = probability_model(x_test[:5]) + # Verify probability shape + self.assertEqual(probabilities.shape, (5, 10))
80-100: TensorBoard test improvements already tracked; fix formatting.The TensorBoard test verification improvements are already covered by the existing discussion in past review comments.
Apply formatting fixes:
def test_tensorboard(self): # Create a simple model model = tf.keras.Sequential([ - tf.keras.layers.Dense(10, input_shape=(5,), activation='relu'), + tf.keras.layers.Dense(10, input_shape=(5,), activation="relu"), tf.keras.layers.Dense(1) ]) # Compile the model - model.compile(optimizer='adam', loss='mse') + model.compile(optimizer="adam", loss="mse") # Generate some example data x_train = tf.random.normal((100, 5)) y_train = tf.random.normal((100, 1)) # Create a TensorBoard callback - log_dir = './logs' + log_dir = "./logs" tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir) # Train the model model.fit(x_train, y_train, epochs=2, callbacks=[tensorboard_callback])
🧹 Nitpick comments (1)
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb (1)
10-29: Remove unused import and address formatting issues.The
tensorboardimport is unused and should be removed. Several formatting inconsistencies are also present.from pathlib import Path import json import re import unittest import tensorflow as tf -import tensorboard import tf2onnx from platform import python_version def get_major_minor(s): - return '.'.join(s.split('.')[:2]) + return ".".join(s.split(".")[:2]) def load_expected_versions() -> dict: - lock_file = Path('./expected_versions.json') + lock_file = Path("./expected_versions.json") data = {} - with open(lock_file, 'r') as file: + with open(lock_file, "r") as file: data = json.load(file) - return data + return dataNote: Error handling improvements for
load_expected_versions()are already tracked in issue #1243.
📜 Review details
Configuration used: .coderabbit.yaml
Review profile: CHILL
Plan: Pro
⛔ Files ignored due to path filters (2)
jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile.lockis excluded by!**/*.lockruntimes/rocm-tensorflow/ubi9-python-3.12/Pipfile.lockis excluded by!**/*.lock
📒 Files selected for processing (9)
Makefile(2 hunks)jupyter/datascience/ubi9-python-3.12/mssql-2022.repo-x86_64(1 hunks)jupyter/rocm/tensorflow/ubi9-python-3.12/Dockerfile.rocm(1 hunks)jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile(1 hunks)jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/kustomization.yaml(1 hunks)jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml(1 hunks)jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml(1 hunks)jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb(1 hunks)runtimes/rocm-tensorflow/ubi9-python-3.12/requirements.txt(11 hunks)
✅ Files skipped from review due to trivial changes (2)
- jupyter/datascience/ubi9-python-3.12/mssql-2022.repo-x86_64
- Makefile
🚧 Files skipped from review as they are similar to previous changes (5)
- jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml
- jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/kustomization.yaml
- jupyter/rocm/tensorflow/ubi9-python-3.12/Dockerfile.rocm
- jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile
- runtimes/rocm-tensorflow/ubi9-python-3.12/requirements.txt
🧰 Additional context used
🧠 Learnings (3)
📓 Common learnings
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-09T08:07:24.937Z
Learning: jiridanek requested GitHub issue creation for tensorflow_rocm Python 3.12 compatibility problem during PR #1333 review. Issue #1354 was successfully created with comprehensive problem description covering missing cp312 wheels causing build failures, three solution options (upstream TensorFlow, Python 3.11 only, custom build), clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-23T16:18:42.922Z
Learning: The TensorFlow ROCm Python 3.12 compatibility issue in opendatahub-io/notebooks PR #1259 was caused by using tensorflow-rocm==2.14.0.600 in Pipfile.lock which lacks Python 3.12 wheels, while the Pipfile specifies tensorflow_rocm=~=2.18.1. The solution requires updating Pipfile sources to include https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4/ repository which contains tensorflow_rocm-2.18.1-cp312-cp312-manylinux_2_28_x86_64.whl and regenerating Pipfile.lock using the piplock-refresh GitHub Action.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Dockerfile.rocm:50-50
Timestamp: 2025-07-08T19:30:01.738Z
Learning: jiridanek requested GitHub issue creation for multi-architecture support in ROCm TensorFlow image during PR #1333 review. Issue #1346 was created with comprehensive problem description covering hardcoded x86_64 architecture breaking multi-arch support, detailed impact analysis, three solution options (runtime detection, BuildKit TARGETARCH integration, hybrid approach) with pros/cons analysis, comprehensive acceptance criteria covering core requirements and testing, phased implementation guidance, related files identification, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/pytorch/ubi9-python-3.12/utils/bootstrapper.py:619-626
Timestamp: 2025-07-08T19:33:14.340Z
Learning: jiridanek requested GitHub issue creation for Python 3.12 version check bug in bootstrapper.py during PR #1333 review. Issue #1348 was created with comprehensive problem description covering version check exclusion affecting all Python 3.12 runtime images, detailed impact analysis of bootstrapper execution failures, clear solution with code examples, affected files list including all 6 runtime bootstrapper copies, acceptance criteria for testing and verification, implementation notes about code duplication and upstream reporting, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: jupyter/pytorch/ubi9-python-3.12/Dockerfile.cuda:65-66
Timestamp: 2025-07-09T12:31:02.033Z
Learning: jiridanek requested GitHub issue creation for MSSQL repo file hardcoding problem during PR #1320 review. Issue #1363 was created and updated with comprehensive problem description covering hardcoded x86_64 MSSQL repo files breaking multi-architecture builds across 10 affected Dockerfiles (including datascience, CUDA, ROCm, and TrustyAI variants), detailed root cause analysis, three solution options with code examples, clear acceptance criteria for all image types, implementation guidance following established multi-architecture patterns, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: The Python 3.11 infrastructure for ROCm TensorFlow images in opendatahub-io/notebooks is already properly configured in the Makefile with both BASE_DIRS entries for Pipfile lock renewals and all-images targets for CI builds, requiring only commenting out the corresponding Python 3.12 entries when downgrading due to wheel availability issues.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py:1-769
Timestamp: 2025-07-08T19:35:49.482Z
Learning: jiridanek requested GitHub issue creation for bootstrapper code duplication problem in runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py during PR #1333 review. After an initial failed attempt, issue #1349 was successfully created with comprehensive problem description covering maintenance overhead and consistency risks from duplicate implementations across 5 Python 3.12 runtime environments, four solution options (symlinks, import-based, template-based, direct shared import) with pros/cons analysis, clear acceptance criteria for consolidation and maintainability, step-by-step implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/datascience/ubi9-python-3.12/Pipfile:33-34
Timestamp: 2025-07-08T19:26:17.140Z
Learning: jiridanek requested GitHub issue creation for jupyter-client dependency pinning inconsistency during PR #1333 review, specifically asking to note the implications of breaking changes in 9.x versions. Issue #1343 was created with comprehensive problem description covering inconsistent pinning style across all Python 3.12 runtime images, detailed breaking changes analysis (kernel protocol, session management, connection security, API changes, async/await modifications), reproducibility and security impact assessment, multiple solution options with code examples, phased acceptance criteria, implementation guidance, testing approach, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-14T15:36:29.815Z
Learning: ROCm is not supported by upstream TensorFlow, unlike CUDA. ROCm support requires the specialized tensorflow_rocm package, which creates a dependency challenge for Python 3.12 environments since tensorflow_rocm lacks Python 3.12 wheels while regular TensorFlow lacks ROCm support.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:05:33.329Z
Learning: tensorflow_rocm package has no Python 3.12 or 3.13 wheel support as of July 2025, with the latest version 2.14.0.600 only supporting Python 3.9, 3.10, and 3.11. The tensorflow-rocm upstream project appears abandoned with the last release in 2019. For Python 3.12+ ROCm TensorFlow environments, regular TensorFlow 2.18+ with runtime ROCm configuration is the recommended and industry-standard approach, as modern TensorFlow automatically detects and utilizes ROCm when properly installed.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: tensorflow_rocm package versions 2.12.1.570 through 2.14.0.600 do not provide Python 3.12 wheels (cp312) on PyPI, causing Pipfile lock failures when attempting to create Python 3.12-based ROCm TensorFlow notebook images in opendatahub-io/notebooks.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:05:33.329Z
Learning: tensorflow_rocm package has no Python 3.12 or 3.13 wheel support as of July 2025, with the latest version 2.14.0.600 only supporting Python 3.9, 3.10, and 3.11. For Python 3.12+ ROCm TensorFlow environments, regular TensorFlow with runtime ROCm configuration is the recommended alternative approach.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T10:41:56.419Z
Learning: jiridanek's team uses containerized dependency locking for cross-platform compatibility in opendatahub-io/notebooks. They run `pipenv lock` inside UBI9 containers with specific platform arguments (`--platform=linux/amd64 --python-version 3.12`) to avoid host OS dependency conflicts when generating Pipfile.lock files.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T10:41:56.419Z
Learning: In the opendatahub-io/notebooks repository, TensorFlow packages with `extras = ["and-cuda"]` can cause build conflicts on macOS due to platform-specific CUDA packages. When the Dockerfile installs CUDA system-wide, removing the extras and letting TensorFlow find CUDA at runtime resolves these conflicts.
Learnt from: grdryn
PR: opendatahub-io/notebooks#1320
File: rstudio/rhel9-python-3.11/Dockerfile.cuda:34-35
Timestamp: 2025-07-04T10:41:13.061Z
Learning: In the opendatahub-io/notebooks repository, when adapting NVIDIA CUDA Dockerfiles, the project intentionally maintains consistency with upstream NVIDIA patterns even when it might involve potential risks like empty variable expansions in package installation commands. This is considered acceptable because the containers only run on RHEL 9 with known yum/dnf behavior, and upstream consistency is prioritized over defensive coding practices.
jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml (47)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-01T07:11:44.903Z
Learning: Resource limits in StatefulSet manifests in opendatahub-io/notebooks are configured for testing purposes, not production deployments. This affects risk assessment when reviewing resource configurations like memory and CPU limits.
Learnt from: jiridanek
PR: #1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: #1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: StatefulSet selector issue with empty spec.selector: {} is a known systemic problem across multiple images in opendatahub-io/notebooks repository, tracked in issue #1236. This affects multiple StatefulSet manifests and is being addressed centrally rather than in individual PRs.
Learnt from: jiridanek
PR: #1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22
Timestamp: 2025-06-30T14:36:53.890Z
Learning: The pod-patch.yaml file in jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/ is used only for running tests, not production deployments. This affects the risk assessment for resource management configurations like sizeLimit on emptyDir volumes.
Learnt from: jiridanek
PR: #1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/base/statefulset.yaml:54-60
Timestamp: 2025-06-30T14:43:08.138Z
Learning: Issue #1212 in opendatahub-io/notebooks demonstrates that missing securityContext configuration (allowPrivilegeEscalation, runAsNonRoot, seccompProfile) causes runtime pods to fail reaching ready state and timeout after 300s on OpenShift due to PodSecurity policy violations.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-02T18:29:07.858Z
Learning: jiridanek consolidates systematic issues across multiple affected components into single comprehensive tracking issues rather than maintaining separate issues for each affected item. When the StatefulSet selector problem was identified across 13 different Jupyter image configurations, he requested merging issues #1236 and #1264 to track the entire scope systematically.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-02T18:29:07.858Z
Learning: jiridanek consolidates systematic issues across multiple affected components into single comprehensive tracking issues rather than maintaining separate issues for each affected item. When the StatefulSet selector problem was identified across 13 different Jupyter image configurations, he requested merging issues #1236 and #1264 to track the entire scope systematically.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: Runtime deployment tests in opendatahub-io/notebooks may show PodSecurity warnings about allowPrivilegeEscalation, capabilities, runAsNonRoot, and seccompProfile settings. These warnings occur on OpenShift but not on GitHub Actions because GitHub Actions uses upstream Kubernetes without SecurityContextConstraints (SCC).
Learnt from: grdryn
PR: #1320
File: rstudio/rhel9-python-3.11/Dockerfile.cuda:34-35
Timestamp: 2025-07-04T10:41:13.061Z
Learning: In the opendatahub-io/notebooks repository, when adapting NVIDIA CUDA Dockerfiles, the project intentionally maintains consistency with upstream NVIDIA patterns even when it might involve potential risks like empty variable expansions in package installation commands. This is considered acceptable because the containers only run on RHEL 9 with known yum/dnf behavior, and upstream consistency is prioritized over defensive coding practices.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/kustomize/base/pod.yaml:11-11
Timestamp: 2025-07-03T16:17:17.301Z
Learning: jiridanek requested GitHub issue creation for renaming placeholder image reference in codeserver/ubi9-python-3.12/kustomize/base/pod.yaml during PR #1269 review to improve code self-documentation. Issue #1313 was created with comprehensive problem description, multiple implementation options (UPPERCASE_WITH_UNDERSCORES, lowercase-with-dashes, environment variable style), acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1333
File: runtimes/pytorch/ubi9-python-3.12/Dockerfile.cuda:17-25
Timestamp: 2025-07-09T08:07:30.628Z
Learning: jiridanek requested GitHub issue creation for oc client installation permission problem in PyTorch CUDA runtime Dockerfile during PR #1333 review. Issue #1356 was created with comprehensive problem description covering USER 1001 permission conflicts with root-owned /opt/app-root/bin directory, detailed impact analysis of build failures and non-executable binaries, current problematic code snippet, complete solution with user switching approach, clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/root/usr/share/container-scripts/nginx/common.sh:4-11
Timestamp: 2025-07-03T12:08:47.691Z
Learning: jiridanek requests GitHub issue creation for shell script quality improvements identified during PR #1269 review, specifically for POSIX compliance and security issues in codeserver/ubi9-python-3.12/nginx/root/usr/share/container-scripts/nginx/common.sh. Issue #1275 was created with comprehensive problem descriptions, acceptance criteria, implementation guidance, and proper context linking.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/root/opt/app-root/etc/passwd.template:14-14
Timestamp: 2025-07-03T16:28:55.757Z
Learning: jiridanek requested GitHub issue creation for passwd template validation in codeserver/ubi9-python-3.12/nginx/root/opt/app-root/etc/passwd.template during PR #1269 review. Issue #1318 was created with comprehensive analysis of nss_wrapper approach advantages over OpenShift's native user management, including consistent user identity, application compatibility, and debugging benefits. The current approach works with OpenShift's random UID assignment by dynamically setting USER_ID and GROUP_ID to actual runtime values while providing enhanced user attributes through nss_wrapper.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/run-nginx.sh:18-23
Timestamp: 2025-07-03T16:17:23.065Z
Learning: jiridanek requested GitHub issue creation for shell script variable quoting security concern in codeserver/ubi9-python-3.12/run-nginx.sh during PR #1269 review. The issue covers unquoted variables NB_PREFIX, NOTEBOOK_ARGS, and BASE_URL that pose security risks including command injection, word-splitting vulnerabilities, and globbing issues. A comprehensive issue was created with detailed problem description, security concerns, solution with code examples, acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/root/opt/app-root/etc/generate_container_user:4-9
Timestamp: 2025-07-03T16:05:35.448Z
Learning: jiridanek requested GitHub issue creation for shell script error handling improvements in codeserver/ubi9-python-3.12/nginx/root/opt/app-root/etc/generate_container_user during PR #1269 review. A comprehensive issue was created covering silent failures, unquoted variable expansions, missing template validation, and strict mode implementation with detailed problem descriptions, phased acceptance criteria, implementation guidance with code examples, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/run-code-server.sh:7-10
Timestamp: 2025-07-03T14:01:22.819Z
Learning: jiridanek requested GitHub issue creation for container startup robustness and lifecycle management improvements in codeserver/ubi9-python-3.12/run-code-server.sh during PR #1269 review. A comprehensive issue was created covering race conditions, failure detection, process lifecycle coupling, and signal handling with detailed problem descriptions, multiple solution options, phased acceptance criteria, testing approach, and proper context linking, following the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:33:55.209Z
Learning: jiridanek requested GitHub issue creation for smart-open library S3/GCS backend compatibility concern in PR #1269. Issue #1296 was successfully created with comprehensive problem description, acceptance criteria, implementation guidance, testing approach, and proper context linking, following the established pattern of systematic issue tracking for technical improvements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T12:44:00.167Z
Learning: jiridanek requested GitHub issue creation for smart-open library S3/GCS backend compatibility concern in PR #1269. Issue #1289 was successfully created with comprehensive problem description, acceptance criteria, implementation guidance, testing approach, and proper context linking, following the established pattern of systematic issue tracking for technical improvements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T12:44:00.167Z
Learning: jiridanek requested GitHub issue creation for smart-open library compatibility concern in PR #1269, specifically about potential S3/GCS backend functionality loss due to smart-open dropping implicit extras since version 6.x. Issue creation follows established pattern of comprehensive problem descriptions, acceptance criteria, implementation guidance, and proper context linking.
Learnt from: jiridanek
PR: #1333
File: runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py:1-769
Timestamp: 2025-07-08T19:35:49.482Z
Learning: jiridanek requested GitHub issue creation for bootstrapper code duplication problem in runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py during PR #1333 review. After an initial failed attempt, issue #1349 was successfully created with comprehensive problem description covering maintenance overhead and consistency risks from duplicate implementations across 5 Python 3.12 runtime environments, four solution options (symlinks, import-based, template-based, direct shared import) with pros/cons analysis, clear acceptance criteria for consolidation and maintainability, step-by-step implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:01:18.625Z
Learning: jiridanek requested GitHub issue creation for markdown linting improvements in PR #1269, specifically addressing MD014 violations in README files and suggesting repository-wide markdown linter integration. Issue #1290 was created with comprehensive tooling recommendations, implementation phases, acceptance criteria, and systematic approach to documentation quality improvements.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/requirements.txt:435-444
Timestamp: 2025-07-03T13:59:55.040Z
Learning: jiridanek requested GitHub issue creation for numpy/scipy compatibility investigation in PR #1269, specifically for cases where theoretical version conflicts don't manifest as actual build failures. Issue #1297 was created with comprehensive investigation framework, acceptance criteria, runtime testing approach, and proper context linking, demonstrating the pattern of creating investigation-type issues for apparent but non-blocking technical concerns that require deeper understanding.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/root/usr/share/container-scripts/nginx/common.sh:1-3
Timestamp: 2025-07-03T12:07:19.365Z
Learning: jiridanek consistently requests GitHub issue creation for technical improvements identified during code reviews in opendatahub-io/notebooks, ensuring systematic tracking of code quality enhancements like shell script portability issues with comprehensive descriptions, solution options, and acceptance criteria.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:71-76
Timestamp: 2025-07-04T06:04:43.085Z
Learning: jiridanek requested GitHub issue creation for duplicate CSV loading and validation problem in jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb during PR #1306 review. Issue #1322 was created with comprehensive problem description covering code redundancy, runtime failure risks, network inefficiency, and test reliability concerns, along with detailed solution including duplicate line removal, data validation implementation, repository-wide audit, acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:01:18.625Z
Learning: jiridanek requested GitHub issue creation for markdown linting improvements in PR #1269, specifically addressing MD014 violations in README files while also suggesting repository-wide markdown linter integration. Issue #1290 was successfully created with comprehensive tooling recommendations, phased implementation plan, clear acceptance criteria, and systematic approach to documentation quality improvements, continuing the established pattern of systematic code quality enhancements.
Learnt from: jiridanek
PR: #1333
File: runtimes/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-08T19:29:32.006Z
Learning: jiridanek requested GitHub issue creation for investigating TensorFlow "and-cuda" extras usage patterns during PR #1333 review. Issue #1345 was created with comprehensive investigation framework covering platform-specific analysis, deployment scenarios, TensorFlow version compatibility, clear acceptance criteria, and testing approach, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:59:15.788Z
Learning: jiridanek creates targeted GitHub issues for specific test quality improvements identified during PR reviews in opendatahub-io/notebooks. Issue #1268 demonstrates this by converting a review comment about insufficient tf2onnx conversion test validation into a comprehensive improvement plan with clear acceptance criteria, code examples, and ROCm-specific context.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-11T11:16:05.131Z
Learning: jiridanek requested GitHub issue creation for RStudio py311 Tekton push pipelines during PR #1379 review. Issue #1384 was successfully created covering two RStudio variants (CPU and CUDA) found in manifests/base/params-latest.env, with comprehensive problem description, implementation requirements following the same pattern as other workbench pipelines, clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1320
File: jupyter/pytorch/ubi9-python-3.12/Dockerfile.cuda:65-66
Timestamp: 2025-07-09T12:31:02.033Z
Learning: jiridanek requested GitHub issue creation for MSSQL repo file hardcoding problem during PR #1320 review. Issue #1363 was created and updated with comprehensive problem description covering hardcoded x86_64 MSSQL repo files breaking multi-architecture builds across 10 affected Dockerfiles (including datascience, CUDA, ROCm, and TrustyAI variants), detailed root cause analysis, three solution options with code examples, clear acceptance criteria for all image types, implementation guidance following established multi-architecture patterns, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1379
File: .tekton/odh-workbench-jupyter-datascience-cpu-py312-ubi9-push.yaml:14-17
Timestamp: 2025-07-11T11:15:47.424Z
Learning: jiridanek requested GitHub issue creation for CEL filter problem in datascience workbench Tekton pipelines during PR #1379 review. Issue #1383 was successfully created with comprehensive problem description covering both Python 3.11 and 3.12 pipelines incorrectly watching jupyter/minimal directories instead of jupyter/datascience directories, detailed impact analysis of pipeline execution failures, complete solution with before/after code examples, thorough acceptance criteria for path updates and pipeline triggering verification, implementation notes about repository structure alignment, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb:22-29
Timestamp: 2025-07-02T18:27:51.097Z
Learning: jiridanek consistently creates comprehensive follow-up GitHub issues from PR review comments in opendatahub-io/notebooks, turning specific code quality concerns into systematic improvements tracked with proper context, acceptance criteria, and cross-references. Issue #1266 demonstrates this pattern by expanding a specific error handling concern in load_expected_versions() into a repository-wide improvement initiative.
Learnt from: jiridanek
PR: #1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-09T08:07:24.937Z
Learning: jiridanek requested GitHub issue creation for tensorflow_rocm Python 3.12 compatibility problem during PR #1333 review. Issue #1354 was successfully created with comprehensive problem description covering missing cp312 wheels causing build failures, three solution options (upstream TensorFlow, Python 3.11 only, custom build), clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1230
File: jupyter/minimal/ubi9-python-3.12/Dockerfile.rocm:43-55
Timestamp: 2025-07-01T06:48:21.070Z
Learning: When security concerns are raised during PR reviews in opendatahub-io/notebooks, comprehensive follow-up issues are created (often by CodeRabbit) to track all related security enhancements with clear acceptance criteria and implementation guidance. This ensures security improvements are systematically addressed in dedicated efforts rather than blocking current deliverables.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/Dockerfile.cpu:4-4
Timestamp: 2025-07-04T05:49:10.314Z
Learning: jiridanek directs base image pinning security concerns to existing comprehensive issue #1242 "Improve Docker FROM image versioning by avoiding :latest tags" rather than addressing them in individual PRs, continuing the established pattern of systematic security and quality tracking in opendatahub-io/notebooks.
Learnt from: atheo89
PR: #1401
File: manifests/overlays/additional/runtime-datascience-imagestream-beta.yaml:8-10
Timestamp: 2025-07-16T10:44:40.023Z
Learning: atheo89 pointed out that the doubled slash issue in runtime-image-url annotations affects multiple imagestream files repository-wide (11 files total), not just individual files. When systematic issues like this are identified during PR review, they should be addressed as separate comprehensive issues rather than individual file fixes, especially when they're outside the scope of the current PR. Issue #1402 was created to track this systematic problem.
Learnt from: atheo89
PR: #1401
File: manifests/overlays/additional/runtime-datascience-imagestream-beta.yaml:8-10
Timestamp: 2025-07-16T10:44:40.023Z
Learning: atheo89 pointed out that the doubled slash issue in runtime-image-url annotations affects multiple imagestream files repository-wide, not just individual files. When systematic issues like this are identified during PR review, they should be addressed as separate comprehensive issues rather than individual file fixes, especially when they're outside the scope of the current PR.
Learnt from: jiridanek
PR: #1258
File: codeserver/ubi9-python-3.11/Dockerfile.cpu:55-56
Timestamp: 2025-07-03T08:22:25.348Z
Learning: jiridanek directs security concerns raised during PR reviews to existing comprehensive security issues rather than addressing them in individual PRs. Issue #1241 "Security: Add checksum verification for downloaded binaries in Python 3.12 images" serves as the central tracking issue for all binary download security concerns across the opendatahub-io/notebooks repository.
Learnt from: jiridanek
PR: #1230
File: jupyter/minimal/ubi9-python-3.12/Dockerfile.rocm:43-55
Timestamp: 2025-07-01T06:48:21.070Z
Learning: When jiridanek encounters security feedback during PR reviews in opendatahub-io/notebooks, he creates dedicated GitHub issues to track them as follow-up improvements rather than blocking the current PR. This demonstrates effective project management by separating immediate deliverables from security enhancements that require dedicated testing and validation.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Dockerfile.rocm:56-66
Timestamp: 2025-07-02T18:19:49.397Z
Learning: jiridanek consistently creates comprehensive follow-up GitHub issues for security concerns raised during PR reviews in opendatahub-io/notebooks, ensuring systematic tracking and resolution of supply-chain security improvements like GPG signature verification for package repositories.
Learnt from: jiridanek
PR: #1230
File: jupyter/minimal/ubi9-python-3.12/Dockerfile.cpu:21-24
Timestamp: 2025-07-01T06:48:13.154Z
Learning: jiridanek creates comprehensive follow-up issues from review comments that expand scope appropriately, include clear acceptance criteria, proper backlinks, and structured implementation guidance. Issue #1241 demonstrates this by turning a specific oc client checksum concern into a thorough security enhancement plan covering all downloaded binaries across the Python 3.12 implementation.
Learnt from: jiridanek
PR: #1333
File: runtimes/datascience/ubi9-python-3.12/Pipfile:33-34
Timestamp: 2025-07-08T19:26:17.140Z
Learning: jiridanek requested GitHub issue creation for jupyter-client dependency pinning inconsistency during PR #1333 review, specifically asking to note the implications of breaking changes in 9.x versions. Issue #1343 was created with comprehensive problem description covering inconsistent pinning style across all Python 3.12 runtime images, detailed breaking changes analysis (kernel protocol, session management, connection security, API changes, async/await modifications), reproducibility and security impact assessment, multiple solution options with code examples, phased acceptance criteria, implementation guidance, testing approach, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb (57)
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:44-50
Timestamp: 2025-07-03T16:18:59.234Z
Learning: In the opendatahub-io/notebooks repository, the expected_versions.json file referenced in test notebooks (like test_notebook.ipynb) is generated during test execution, not included as a static file in the PR. This is an established testing pattern that should not be flagged as a missing file issue. The pattern is actively managed through issues like #1243 "Improve error handling in get_expected_version() functions across test notebooks" and #1254 "Fix undefined variable error in ROCm PyTorch Python 3.12 test notebook".
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:59:15.788Z
Learning: jiridanek creates targeted GitHub issues for specific test quality improvements identified during PR reviews in opendatahub-io/notebooks. Issue #1268 demonstrates this by converting a review comment about insufficient tf2onnx conversion test validation into a comprehensive improvement plan with clear acceptance criteria, code examples, and ROCm-specific context.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-23T16:18:42.922Z
Learning: The TensorFlow ROCm Python 3.12 compatibility issue in opendatahub-io/notebooks PR #1259 was caused by using tensorflow-rocm==2.14.0.600 in Pipfile.lock which lacks Python 3.12 wheels, while the Pipfile specifies tensorflow_rocm=~=2.18.1. The solution requires updating Pipfile sources to include https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4/ repository which contains tensorflow_rocm-2.18.1-cp312-cp312-manylinux_2_28_x86_64.whl and regenerating Pipfile.lock using the piplock-refresh GitHub Action.
Learnt from: jiridanek
PR: #1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-09T08:07:24.937Z
Learning: jiridanek requested GitHub issue creation for tensorflow_rocm Python 3.12 compatibility problem during PR #1333 review. Issue #1354 was successfully created with comprehensive problem description covering missing cp312 wheels causing build failures, three solution options (upstream TensorFlow, Python 3.11 only, custom build), clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: The Python 3.11 infrastructure for ROCm TensorFlow images in opendatahub-io/notebooks is already properly configured in the Makefile with both BASE_DIRS entries for Pipfile lock renewals and all-images targets for CI builds, requiring only commenting out the corresponding Python 3.12 entries when downgrading due to wheel availability issues.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: tensorflow_rocm package versions 2.12.1.570 through 2.14.0.600 do not provide Python 3.12 wheels (cp312) on PyPI, causing Pipfile lock failures when attempting to create Python 3.12-based ROCm TensorFlow notebook images in opendatahub-io/notebooks.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:71-76
Timestamp: 2025-07-04T06:04:43.085Z
Learning: jiridanek requested GitHub issue creation for duplicate CSV loading and validation problem in jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb during PR #1306 review. Issue #1322 was created with comprehensive problem description covering code redundancy, runtime failure risks, network inefficiency, and test reliability concerns, along with detailed solution including duplicate line removal, data validation implementation, repository-wide audit, acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:44-50
Timestamp: 2025-07-03T16:18:59.234Z
Learning: In the opendatahub-io/notebooks repository, the expected_versions.json file referenced in test notebooks (like test_notebook.ipynb) is generated during test execution, not included as a static file in the PR. This is an established testing pattern that should not be flagged as a missing file issue.
Learnt from: jiridanek
PR: #1247
File: .github/workflows/build-notebooks-TEMPLATE.yaml:50-53
Timestamp: 2025-07-01T14:36:52.852Z
Learning: In the opendatahub-io/notebooks repository, the test runner's Python version (configured in GitHub Actions UV setup) intentionally doesn't need to match the Python version of the container images being tested. jiridanek's team uses Python 3.12 for running tests while images may use different Python versions (like 3.11), and this approach works fine since the test code is separate from the application code running inside the containers.
Learnt from: jiridanek
PR: #1333
File: runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py:1-769
Timestamp: 2025-07-08T19:35:49.482Z
Learning: jiridanek requested GitHub issue creation for bootstrapper code duplication problem in runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py during PR #1333 review. After an initial failed attempt, issue #1349 was successfully created with comprehensive problem description covering maintenance overhead and consistency risks from duplicate implementations across 5 Python 3.12 runtime environments, four solution options (symlinks, import-based, template-based, direct shared import) with pros/cons analysis, clear acceptance criteria for consolidation and maintainability, step-by-step implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:71-88
Timestamp: 2025-07-04T06:05:30.580Z
Learning: jiridanek requested GitHub issue creation for TrustyAI test notebook URL configurability and network error handling improvements during PR #1306 review. Issue #1323 was created with
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1333
File: runtimes/datascience/ubi9-python-3.12/Pipfile:33-34
Timestamp: 2025-07-08T19:26:17.140Z
Learning: jiridanek requested GitHub issue creation for jupyter-client dependency pinning inconsistency during PR #1333 review, specifically asking to note the implications of breaking changes in 9.x versions. Issue #1343 was created with comprehensive problem description covering inconsistent pinning style across all Python 3.12 runtime images, detailed breaking changes analysis (kernel protocol, session management, connection security, API changes, async/await modifications), reproducibility and security impact assessment, multiple solution options with code examples, phased acceptance criteria, implementation guidance, testing approach, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:102-102
Timestamp: 2025-07-03T16:26:18.718Z
Learning: jiridanek requested GitHub issue creation for improving hardcoded threshold constants in TrustyAI test notebook during PR #1306 review. Issue #1317 was created with comprehensive problem description covering both bias detection threshold (-0.15670061634672994) and fairness threshold (0.0036255104824703954), multiple solution options with code examples, clear acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1333
File: runtimes/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-08T19:29:32.006Z
Learning: jiridanek requested GitHub issue creation for investigating TensorFlow "and-cuda" extras usage patterns during PR #1333 review. Issue #1340 was created with comprehensive investigation framework covering platform-specific analysis, deployment scenarios, TensorFlow version compatibility, clear acceptance criteria, testing approach, and implementation timeline, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1333
File: runtimes/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-08T19:29:32.006Z
Learning: jiridanek requested GitHub issue creation for investigating TensorFlow "and-cuda" extras usage patterns during PR #1333 review. Issue #1345 was created with comprehensive investigation framework covering platform-specific analysis, deployment scenarios, TensorFlow version compatibility, clear acceptance criteria, and testing approach, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Dockerfile.rocm:50-50
Timestamp: 2025-07-08T19:30:01.738Z
Learning: jiridanek requested GitHub issue creation for multi-architecture support in ROCm TensorFlow image during PR #1333 review. Issue #1346 was created with comprehensive problem description covering hardcoded x86_64 architecture breaking multi-arch support, detailed impact analysis, three solution options (runtime detection, BuildKit TARGETARCH integration, hybrid approach) with pros/cons analysis, comprehensive acceptance criteria covering core requirements and testing, phased implementation guidance, related files identification, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1325
File: jupyter/pytorch/ubi9-python-3.12/Pipfile:42-42
Timestamp: 2025-07-09T14:22:14.553Z
Learning: jiridanek requested GitHub issue creation for Pipfile.lock verification script implementation during PR #1325 review, specifically to systematize the manual verification process for dependency version consistency across all lock files using jq. Issue #1367 was created with comprehensive problem description covering manual verification challenges, detailed solution with jq-based verification script, enhanced features for CI integration, clear acceptance criteria, implementation areas breakdown, benefits analysis, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-24T12:01:45.188Z
Learning: jiridanek requested verification of 2024.2 tag package versions against corresponding Pipfiles during PR #1496 review. The analysis revealed that 2024.2 tags contain intentionally frozen older versions (N-1 behavior) while the current PR correctly updates only the N (latest) tags to match Python 3.11 Pipfiles, demonstrating proper understanding of the repository's N-1 version freezing policy.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:33:55.209Z
Learning: jiridanek requested GitHub issue creation for smart-open library S3/GCS backend compatibility concern in PR #1269. Issue #1296 was successfully created with comprehensive problem description, acceptance criteria, implementation guidance, testing approach, and proper context linking, following the established pattern of systematic issue tracking for technical improvements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T12:44:00.167Z
Learning: jiridanek requested GitHub issue creation for smart-open library S3/GCS backend compatibility concern in PR #1269. Issue #1289 was successfully created with comprehensive problem description, acceptance criteria, implementation guidance, testing approach, and proper context linking, following the established pattern of systematic issue tracking for technical improvements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T12:44:00.167Z
Learning: jiridanek requested GitHub issue creation for smart-open library compatibility concern in PR #1269, specifically about potential S3/GCS backend functionality loss due to smart-open dropping implicit extras since version 6.x. Issue creation follows established pattern of comprehensive problem descriptions, acceptance criteria, implementation guidance, and proper context linking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:01:18.625Z
Learning: jiridanek requested GitHub issue creation for markdown linting improvements in PR #1269, specifically addressing MD014 violations in README files and suggesting repository-wide markdown linter integration. Issue #1290 was created with comprehensive tooling recommendations, implementation phases, acceptance criteria, and systematic approach to documentation quality improvements.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/requirements.txt:435-444
Timestamp: 2025-07-03T13:59:55.040Z
Learning: jiridanek requested GitHub issue creation for numpy/scipy compatibility investigation in PR #1269, specifically for cases where theoretical version conflicts don't manifest as actual build failures. Issue #1297 was created with comprehensive investigation framework, acceptance criteria, runtime testing approach, and proper context linking, demonstrating the pattern of creating investigation-type issues for apparent but non-blocking technical concerns that require deeper understanding.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/root/usr/share/container-scripts/nginx/common.sh:1-3
Timestamp: 2025-07-03T12:07:19.365Z
Learning: jiridanek consistently requests GitHub issue creation for technical improvements identified during code reviews in opendatahub-io/notebooks, ensuring systematic tracking of code quality enhancements like shell script portability issues with comprehensive descriptions, solution options, and acceptance criteria.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:01:18.625Z
Learning: jiridanek requested GitHub issue creation for markdown linting improvements in PR #1269, specifically addressing MD014 violations in README files while also suggesting repository-wide markdown linter integration. Issue #1290 was successfully created with comprehensive tooling recommendations, phased implementation plan, clear acceptance criteria, and systematic approach to documentation quality improvements, continuing the established pattern of systematic code quality enhancements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-11T11:16:05.131Z
Learning: jiridanek requested GitHub issue creation for RStudio py311 Tekton push pipelines during PR #1379 review. Issue #1384 was successfully created covering two RStudio variants (CPU and CUDA) found in manifests/base/params-latest.env, with comprehensive problem description, implementation requirements following the same pattern as other workbench pipelines, clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1379
File: .tekton/odh-workbench-jupyter-datascience-cpu-py312-ubi9-push.yaml:14-17
Timestamp: 2025-07-11T11:15:47.424Z
Learning: jiridanek requested GitHub issue creation for CEL filter problem in datascience workbench Tekton pipelines during PR #1379 review. Issue #1383 was successfully created with comprehensive problem description covering both Python 3.11 and 3.12 pipelines incorrectly watching jupyter/minimal directories instead of jupyter/datascience directories, detailed impact analysis of pipeline execution failures, complete solution with before/after code examples, thorough acceptance criteria for path updates and pipeline triggering verification, implementation notes about repository structure alignment, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb:22-29
Timestamp: 2025-07-02T18:27:51.097Z
Learning: jiridanek consistently creates comprehensive follow-up GitHub issues from PR review comments in opendatahub-io/notebooks, turning specific code quality concerns into systematic improvements tracked with proper context, acceptance criteria, and cross-references. Issue #1266 demonstrates this pattern by expanding a specific error handling concern in load_expected_versions() into a repository-wide improvement initiative.
Learnt from: jiridanek
PR: #1230
File: jupyter/minimal/ubi9-python-3.12/Dockerfile.rocm:43-55
Timestamp: 2025-07-01T06:48:21.070Z
Learning: When security concerns are raised during PR reviews in opendatahub-io/notebooks, comprehensive follow-up issues are created (often by CodeRabbit) to track all related security enhancements with clear acceptance criteria and implementation guidance. This ensures security improvements are systematically addressed in dedicated efforts rather than blocking current deliverables.
Learnt from: jiridanek
PR: #1230
File: jupyter/minimal/ubi9-python-3.12/Dockerfile.cpu:21-24
Timestamp: 2025-07-01T06:48:13.154Z
Learning: jiridanek creates comprehensive follow-up issues from review comments that expand scope appropriately, include clear acceptance criteria, proper backlinks, and structured implementation guidance. Issue #1241 demonstrates this by turning a specific oc client checksum concern into a thorough security enhancement plan covering all downloaded binaries across the Python 3.12 implementation.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/api/kernels/access.cgi:8-10
Timestamp: 2025-07-03T14:01:27.789Z
Learning: jiridanek requested GitHub issue creation for JSON parsing robustness improvement in codeserver/ubi9-python-3.12/nginx/api/kernels/access.cgi during PR #1269 review, specifically for replacing fragile grep/awk/date chain with jq-based JSON parsing to improve reliability and maintainability. Issue #1299 was successfully created with comprehensive problem description, solution details, acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/api/kernels/access.cgi:8-10
Timestamp: 2025-07-03T14:01:27.789Z
Learning: jiridanek requested GitHub issue creation for JSON parsing robustness improvement in codeserver/ubi9-python-3.12/nginx/api/kernels/access.cgi during PR #1269 review, specifically for replacing fragile grep/awk/date chain with jq-based JSON parsing to improve reliability and maintainability. Issue was created with comprehensive problem description, solution details, acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:31:35.667Z
Learning: jiridanek requested GitHub issue creation for comprehensive shell scripting improvements in codeserver image during PR #1269 review, covering process management, JSON parsing robustness, variable quoting security, and sed pattern fixes. Issue #1295 was created with systematic phased approach, detailed problem descriptions, implementation guidance, acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:27:38.813Z
Learning: jiridanek requested GitHub issue creation for comprehensive shell scripting improvements in codeserver image during PR #1269 review, covering process management, JSON parsing robustness, variable quoting security, and sed pattern fixes. Issue #1293 was created with systematic phased approach, detailed problem descriptions, implementation guidance, acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:27:38.813Z
Learning: jiridanek requested GitHub issue creation for comprehensive shell scripting improvements in codeserver image during PR #1269 review, covering process management, JSON parsing robustness, variable quoting security, and sed pattern fixes. Issue #1293 was created with systematic phased approach, detailed problem descriptions, implementation guidance, acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/root/usr/share/container-scripts/nginx/common.sh:4-11
Timestamp: 2025-07-03T16:04:22.695Z
Learning: jiridanek requested GitHub issue creation for shell script quality improvements in codeserver/ubi9-python-3.12/nginx/root/usr/share/container-scripts/nginx/common.sh during PR #1269 review. Issue #1307 was created with comprehensive problem description covering variable scoping issues, POSIX compliance concerns, multiple solution options, acceptance criteria, implementation guidance with code examples, testing approaches, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: #1397
File: .github/workflows/piplock-renewal.yaml:16-26
Timestamp: 2025-07-15T16:09:15.689Z
Learning: jiridanek confirmed that GitHub Actions' fromJSON() function is more lenient than expected and can parse JSON-like strings with single quotes and spaces (e.g., "['3.11', '3.12']") in workflow_dispatch inputs, even though this is not valid JSON syntax. However, he agrees that following valid JSON syntax is still recommended for code quality.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/nginx/root/opt/app-root/etc/generate_container_user:4-9
Timestamp: 2025-07-03T16:05:35.448Z
Learning: jiridanek requested GitHub issue creation for shell script error handling improvements in codeserver/ubi9-python-3.12/nginx/root/opt/app-root/etc/generate_container_user during PR #1269 review. A comprehensive issue was created covering silent failures, unquoted variable expansions, missing template validation, and strict mode implementation with detailed problem descriptions, phased acceptance criteria, implementation guidance with code examples, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/run-code-server.sh:20-40
Timestamp: 2025-07-03T12:27:09.739Z
Learning: jiridanek requested GitHub issue creation for shell script error handling improvements in codeserver/ubi9-python-3.12/run-code-server.sh create_dir_and_file function during PR #1269 review. Issue #1284 was created with comprehensive problem description, acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements.
Learnt from: jiridanek
PR: #1426
File: tests/browser/tests/codeserver.spec.ts:5-7
Timestamp: 2025-07-22T06:05:14.887Z
Learning: jiridanek requested GitHub issue creation for testcontainers internal API import fix during PR #1426 review. Issue #1428 was successfully created covering replacement of fragile internal build file imports with public Wait.forHttp() builder API to ensure compatibility across testcontainers version updates, affecting both 2024b and main branches with comprehensive problem description, solution with code examples, and acceptance criteria for systematic tracking of technical improvements.
Learnt from: jiridanek
PR: #1258
File: codeserver/ubi9-python-3.11/Dockerfile.cpu:55-56
Timestamp: 2025-07-03T08:22:25.348Z
Learning: jiridanek directs security concerns raised during PR reviews to existing comprehensive security issues rather than addressing them in individual PRs. Issue #1241 "Security: Add checksum verification for downloaded binaries in Python 3.12 images" serves as the central tracking issue for all binary download security concerns across the opendatahub-io/notebooks repository.
Learnt from: jiridanek
PR: #1230
File: jupyter/minimal/ubi9-python-3.12/Dockerfile.rocm:43-55
Timestamp: 2025-07-01T06:48:21.070Z
Learning: When jiridanek encounters security feedback during PR reviews in opendatahub-io/notebooks, he creates dedicated GitHub issues to track them as follow-up improvements rather than blocking the current PR. This demonstrates effective project management by separating immediate deliverables from security enhancements that require dedicated testing and validation.
Learnt from: jiridanek
PR: #1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: jiridanek manages StatefulSet selector issues systematically across multiple images in opendatahub-io/notebooks. When the same configuration issue (empty spec.selector and template.metadata.labels) appears in different images like jupyter/minimal and jupyter/tensorflow, he tracks them under a single coordinated effort rather than creating duplicate issues for each affected image.
Learnt from: jiridanek
PR: #1151
File: jupyter/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-01T06:50:37.115Z
Learning: StatefulSet selector issue with empty spec.selector: {} is a known systemic problem across multiple images in opendatahub-io/notebooks repository, tracked in issue #1236. This affects multiple StatefulSet manifests and is being addressed centrally rather than in individual PRs.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:32:05.701Z
Learning: jiridanek consolidates related issues systematically in opendatahub-io/notebooks. When multiple issues (#1265, #1264, #1251) stem from the same root cause (kustomize label/selector conflicts), he combines them into a single master issue (#1236) that addresses the problem comprehensively across all affected images rather than maintaining separate issues for each component.
Learnt from: jiridanek
PR: #1230
File: jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/pod-patch.yaml:11-22
Timestamp: 2025-06-30T14:36:53.890Z
Learning: The pod-patch.yaml file in jupyter/pytorch/ubi9-python-3.12/kustomize/components/accelerator/ is used only for running tests, not production deployments. This affects the risk assessment for resource management configurations like sizeLimit on emptyDir volumes.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-02T18:29:07.858Z
Learning: jiridanek consolidates systematic issues across multiple affected components into single comprehensive tracking issues rather than maintaining separate issues for each affected item. When the StatefulSet selector problem was identified across 13 different Jupyter image configurations, he requested merging issues #1236 and #1264 to track the entire scope systematically.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml:11-17
Timestamp: 2025-07-02T18:29:07.858Z
Learning: jiridanek consolidates systematic issues across multiple affected components into single comprehensive tracking issues rather than maintaining separate issues for each affected item. When the StatefulSet selector problem was identified across 13 different Jupyter image configurations, he requested merging issues #1236 and #1264 to track the entire scope systematically.
Learnt from: jiridanek
PR: #1269
File: codeserver/ubi9-python-3.12/kustomize/base/pod.yaml:11-11
Timestamp: 2025-07-03T16:17:17.301Z
Learning: jiridanek requested GitHub issue creation for renaming placeholder image reference in codeserver/ubi9-python-3.12/kustomize/base/pod.yaml during PR #1269 review to improve code self-documentation. Issue #1313 was created with comprehensive problem description, multiple implementation options (UPPERCASE_WITH_UNDERSCORES, lowercase-with-dashes, environment variable style), acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1418
File: tests/browser/README.md:14-18
Timestamp: 2025-07-21T12:58:43.996Z
Learning: In the opendatahub-io/notebooks repository, upstream project testing framework references in README files serve as informational context about the broader ecosystem, not as recommendations for the current project. These references help contributors understand what other related projects use and should be retained even when the current project doesn't use those frameworks.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: Test failures in opendatahub-io/notebooks should be categorized as either repository bugs (code/configuration issues) or infrastructure issues (CI platform problems) for proper diagnosis and resolution.
Learnt from: jiridanek
PR: #1218
File: jupyter/rocm/pytorch/ubi9-python-3.11/requirements.txt:987-989
Timestamp: 2025-06-28T15:06:03.344Z
Learning: In the opendatahub-io/notebooks repository, checks for broken links and missing files in kustomization manifests are already performed by ci/kustomize.sh, which is invoked from .github/workflows/code-quality.yaml (lines 112–116). No additional pytest is needed for this purpose.
🪛 Checkov (3.2.334)
jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/statefulset.yaml
[MEDIUM] 2-60: Containers should not run with allowPrivilegeEscalation
(CKV_K8S_20)
[MEDIUM] 2-60: Minimize the admission of root containers
(CKV_K8S_23)
🪛 Ruff (0.12.2)
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
7-7: tensorboard imported but unused
Remove unused import: tensorboard
(F401)
13-13: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
13-13: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
17-17: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
20-20: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
23-23: Trailing whitespace
Remove trailing whitespace
(W291)
28-28: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
28-28: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
29-29: Trailing whitespace
Remove trailing whitespace
(W291)
33-33: Blank line contains whitespace
Remove whitespace from blank line
(W293)
35-35: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
36-36: Trailing whitespace
Remove trailing whitespace
(W291)
38-38: Blank line contains whitespace
Remove whitespace from blank line
(W293)
40-40: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
41-41: Trailing whitespace
Remove trailing whitespace
(W291)
43-43: Blank line contains whitespace
Remove whitespace from blank line
(W293)
48-48: Blank line contains whitespace
Remove whitespace from blank line
(W293)
58-58: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
63-63: Found useless expression. Either assign it to a variable or remove it.
(B018)
67-67: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
67-67: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
69-69: Multiple spaces after comma
Replace with single space
(E241)
79-79: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
83-83: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
83-83: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
88-88: Single quotes found but double quotes preferred
Replace single quotes with double quotes
(Q000)
⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (10)
- GitHub Check: build (cuda-jupyter-pytorch-ubi9-python-3.12, 3.12, linux/amd64, false) / build
- GitHub Check: build (jupyter-datascience-ubi9-python-3.12, 3.12, linux/amd64, false) / build
- GitHub Check: build (cuda-jupyter-tensorflow-ubi9-python-3.12, 3.12, linux/arm64, false) / build
- GitHub Check: build (jupyter-trustyai-ubi9-python-3.11, 3.11, linux/amd64, false) / build
- GitHub Check: build (rocm-jupyter-pytorch-ubi9-python-3.12, 3.12, linux/amd64, false) / build
- GitHub Check: build (rocm-jupyter-tensorflow-ubi9-python-3.12, 3.12, linux/amd64, false) / build
- GitHub Check: build (cuda-jupyter-tensorflow-ubi9-python-3.12, 3.12, linux/amd64, false) / build
- GitHub Check: build (rocm-jupyter-tensorflow-ubi9-python-3.12, 3.12, linux/amd64, false) / build
- GitHub Check: build (jupyter-trustyai-ubi9-python-3.12, 3.12, linux/amd64, false) / build
- GitHub Check: build (rocm-jupyter-pytorch-ubi9-python-3.12, 3.12, linux/amd64, false) / build
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Fixes for https://issues.redhat.com/browse/RHOAIENG-27434
Description
Create Rocm Tensorflow Python 3.12
How Has This Been Tested?
Merge criteria:
Summary by CodeRabbit
Summary by CodeRabbit