Borye/openpi
Jun 2025 – Jun 2025
1 Month active
Languages Used
MarkdownPythonTOML
Technical Skills
Cloud StorageConfiguration ManagementDependency ManagementDocumentation
Adrian Li
PROFILE
Adrian Li
Worked on the Borye/openpi repository to migrate the storage backend from AWS S3 to Google Cloud Storage, focusing on updating code, documentation, and configuration files. This migration aimed to reduce vendor lock-in and streamline asset hosting for models and checkpoints within Google’s cloud ecosystem. The process involved removing dependencies such as s3fs and boto3, cleaning up related configuration, and updating asset references to ensure consistency. Utilized Python, TOML, and Markdown to implement these changes, emphasizing cloud storage management and dependency cleanup. The work laid the foundation for scalable, region-agnostic asset delivery while simplifying ongoing maintenance and build processes.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
1
Lines of code
569
Activity Months1
Your Network
24 peopleShared Repositories
24
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Davide De BenedittisMember
Ikko Eltociear AshimineMember
Haohuan WangMember
Jimmy TannerMember
Karl PertschMember
Karl PertschMember
karlMember
Work History
June 2025
3 Commits • 1 Features
Jun 1, 2025Monthly summary for 2025-06 focusing on the migration of storage backend from AWS S3 to Google Cloud Storage (GCS) for Borye/openpi, including code, docs, and configurations. This effort reduces vendor lock-in, simplifies maintenance, and aligns asset hosting (models and checkpoints) with Google's cloud stack. Key outcomes include dependency cleanup, updated asset references, and groundwork for scalable asset delivery.
3 Commits • 1 Features
Jun 1, 2025Monthly summary for 2025-06 focusing on the migration of storage backend from AWS S3 to Google Cloud Storage (GCS) for Borye/openpi, including code, docs, and configurations. This effort reduces vendor lock-in, simplifies maintenance, and aligns asset hosting (models and checkpoints) with Google's cloud stack. Key outcomes include dependency cleanup, updated asset references, and groundwork for scalable asset delivery.
June 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture93.4%
Performance100.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPythonTOML
Technical Skills
Cloud StorageConfiguration ManagementDependency ManagementDocumentation
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline