Enable @coderabbitai reviews on the 2024b branch

[jiridanek]

Investigate editing .coderabbit.yaml to enable automatic reviews on main and 2024b branches.

[jiridanek]

@coderabbitai please prepare a PR

[coderabbitai]

Tip

For best results, initiate chat on the files or code changes.

🧩 Analysis chain

I'll help you prepare a PR! Let me first examine the issue to understand what needs to be implemented.

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🏁 Script executed:

#!/bin/bash
# Fetch the details of issue #1490 to understand what PR needs to be prepared
gh issue view 1490 --repo opendatahub-io/notebooks

Length of output: 305

---

Perfect! I can see that issue #1490 is about enabling CodeRabbit reviews on the 2024b branch by editing the .coderabbit.yaml configuration file. Let me examine the current configuration to understand what changes are needed.

---

🏁 Script executed:

#!/bin/bash
# Check if .coderabbit.yaml exists and examine its contents
if [ -f ".coderabbit.yaml" ]; then
    echo "Found .coderabbit.yaml file:"
    cat .coderabbit.yaml
else
    echo "No .coderabbit.yaml file found"
fi

# Also check for .coderabbit.yml (alternative extension)
if [ -f ".coderabbit.yml" ]; then
    echo "Found .coderabbit.yml file:"
    cat .coderabbit.yml
fi

Length of output: 261

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Now I can see the current configuration. Let me check the CodeRabbit configuration schema to understand the correct format for enabling reviews on specific branches.

---

🏁 Script executed:

#!/bin/bash
# Fetch the CodeRabbit configuration schema to understand the correct format
curl -s "https://coderabbit.ai/integrations/schema.v2.json" | jq '.properties.reviews.properties' | head -50

Length of output: 106

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Let me try a different approach to get the configuration information:

---

🏁 Script executed:

#!/bin/bash
# Try fetching the schema with a different approach
curl -s "https://coderabbit.ai/integrations/schema.v2.json" > schema.json

# Check if the file was created and examine its structure
if [ -f "schema.json" ] && [ -s "schema.json" ]; then
    echo "Schema downloaded successfully"
    # Look for branch-related configuration
    grep -i -A5 -B5 "branch" schema.json | head -20
else
    echo "Schema download failed or empty"
fi

# Let's also check what branches exist in the repository
git branch -r | grep -E "(main|2024b)"

Length of output: 266

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Let me check for the 2024b branch more thoroughly and then prepare the configuration:

---

🏁 Script executed:

#!/bin/bash
# Check all branches to see if 2024b exists
echo "All remote branches:"
git branch -r

echo -e "\nChecking for 2024b branch specifically:"
git branch -r | grep 2024b || echo "2024b branch not found"

echo -e "\nCurrent branch:"
git branch --show-current

# Let's also check if there are any existing CodeRabbit configurations in other repositories for reference
echo -e "\nLooking for common CodeRabbit configuration patterns..."

Length of output: 506

---

Perfect! Now I understand the situation. The 2024b branch doesn't exist yet, but we need to prepare the configuration for when it does. I'm currently on the coderabbit_1490 branch which appears to be the PR branch for this issue. Let me prepare the code changes:

Task: Enable CodeRabbit reviews on main and 2024b branches

• Update the .coderabbit.yaml configuration file to specify which branches should have automatic reviews enabled
• Add branch filtering to restrict reviews to only the main and 2024b branches

@jiridanek, I've prepared the PR to enable CodeRabbit reviews on the main and 2024b branches!

The changes will update the .coderabbit.yaml configuration file to add an include_branches section that specifies exactly which branches should have automatic reviews enabled. This will ensure that CodeRabbit only reviews pull requests targeting the main and 2024b branches, even when the 2024b branch is created in the future.

The configuration change is simple but effective - it adds branch filtering while preserving all your existing CodeRabbit settings like language preference and feature toggles.

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🧠 Learnings used

Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/utils/process.sh:17-19
Timestamp: 2025-07-03T14:00:00.909Z
Learning: jiridanek efficiently identifies when CodeRabbit review suggestions are already covered by existing comprehensive issues, demonstrating excellent issue management and avoiding duplicate tracking of the same improvements across multiple locations.

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Learnt from: jiridanek
PR: opendatahub-io/notebooks#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.

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Learnt from: jiridanek
PR: opendatahub-io/notebooks#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: 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: 2025-07-03T13:33:55.209Z
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: 2025-07-03T13:01:18.625Z
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: 2025-07-03T13:01:18.625Z
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: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:112-126
Timestamp: 2025-07-08T13:21:09.150Z
Learning: jiridanek requested GitHub issue creation for notebook linting and formatting improvements during PR #1306 review, specifically to address inconsistent metadata across .ipynb files and implement systematic quality standards. This continues the established pattern of comprehensive issue creation for code quality improvements with detailed problem descriptions, multiple solution options, phased acceptance criteria, and proper context linking.

---

Learnt from: jiridanek
PR: opendatahub-io/notebooks#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: 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#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.

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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.

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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#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: opendatahub-io/notebooks#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: opendatahub-io/notebooks#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: opendatahub-io/notebooks#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.

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Learnt from: jiridanek
PR: opendatahub-io/notebooks#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.

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Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb:31-34
Timestamp: 2025-07-01T07:03:05.385Z
Learning: jiridanek demonstrates excellent pattern recognition for identifying duplicated code issues across the opendatahub-io/notebooks repository. When spotting a potential problem in test notebooks, he correctly assesses that such patterns are likely replicated across multiple similar files rather than being isolated incidents, leading to more effective systematic solutions.

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⏳ Preparing changes...

[coderabbitai]

A summary of the changes CodeRabbit can apply:

• Modify the .coderabbit.yaml file to add branch filtering by inserting an include_branches section specifying the main and 2024b branches.

• Executed edits - (🔄 Check again to try again)

[coderabbitai]

Creating a PR to execute the edits....

The changes have been created in this pull request: View PR