togethercomputer/openapi
Apr 2025 – Apr 2026
3 Months active
Languages Used
YAML
Technical Skills
API DesignSchema DefinitionAPI DevelopmentBackend DevelopmentDocumentationOpenAPI Specification
connermanuel
PROFILE
Connermanuel
Manuel Conner contributed to the togethercomputer/openapi repository by evolving its API design and backend configuration over a three-month period. He refactored the training configuration schema, relocating and deprecating fields to align with actual SFT workflows and reduce misconfiguration risks. Manuel enhanced the fine-tuning API by adding endpoints for model listing and hyperparameter limits, while also improving documentation clarity and enforcing stricter input validation for loss computation. He introduced a new sequence-level loss aggregation type, expanding experimental flexibility. His work demonstrated depth in OpenAPI Specification, YAML schema definition, and backend development, resulting in a more robust and maintainable API surface.
Overall Statistics
Feature vs Bugs
75%Features
Repository Contributions
6Total
Bugs
1
Commits
6
Features
3
Lines of code
240
Activity Months3
Your Network
33 peopleShared Repositories
33
Work History
April 2026
1 Commits • 1 Features
Apr 1, 2026Month 2026-04 summary for togethercomputer/openapi: Delivered a new loss aggregation type GRPO_LOSS_AGGREGATION_TYPE_SEQUENCE_MEAN in the OpenAPI loss configuration. This addition provides users an extra method to aggregate losses over sequences, enhancing configurability for model evaluation and experimentation. The change was implemented via a focused commit and is tracked in the repository history.
1 Commits • 1 Features
Apr 1, 2026Month 2026-04 summary for togethercomputer/openapi: Delivered a new loss aggregation type GRPO_LOSS_AGGREGATION_TYPE_SEQUENCE_MEAN in the OpenAPI loss configuration. This addition provides users an extra method to aggregate losses over sequences, enhancing configurability for model evaluation and experimentation. The change was implemented via a focused commit and is tracked in the repository history.
April 2026
March 2026
4 Commits • 1 Features
Mar 1, 2026March 2026: Focused improvements to the fine-tuning API and its documentation, plus hardening of training data validation. Delivered new endpoints and OpenAPI refinements to simplify model listing, clarified hyperparameter visibility, and removed an outdated parameter to improve UX. Strengthened input validation by making target tokens mandatory in loss computation, reducing training-time errors and misconfigurations. Result: higher developer productivity, safer training pipelines, and better API consistency across the OpenAPI surface.
March 2026
4 Commits • 1 Features
Mar 1, 2026March 2026: Focused improvements to the fine-tuning API and its documentation, plus hardening of training data validation. Delivered new endpoints and OpenAPI refinements to simplify model listing, clarified hyperparameter visibility, and removed an outdated parameter to improve UX. Strengthened input validation by making target tokens mandatory in loss computation, reducing training-time errors and misconfigurations. Result: higher developer productivity, safer training pipelines, and better API consistency across the OpenAPI surface.
April 2025
1 Commits • 1 Features
Apr 1, 2025Month: 2025-04 — OpenAPI refactor for SFT training config. Delivered: relocated train_on_inputs to SFTType, made it required, and deprecated its general usage to improve clarity and correctness of training method definitions. This aligns API with the actual training workflow, reduces misconfiguration risks, and enables more reliable downstream tooling. No major bug fixes were reported this month; work focused on API evolution and config correctness to support future improvements in SFT pipelines. Technologies demonstrated: OpenAPI schema evolution, type-safe configuration, deprecation strategies, and commit-level traceability.
1 Commits • 1 Features
Apr 1, 2025Month: 2025-04 — OpenAPI refactor for SFT training config. Delivered: relocated train_on_inputs to SFTType, made it required, and deprecated its general usage to improve clarity and correctness of training method definitions. This aligns API with the actual training workflow, reduces misconfiguration risks, and enables more reliable downstream tooling. No major bug fixes were reported this month; work focused on API evolution and config correctness to support future improvements in SFT pipelines. Technologies demonstrated: OpenAPI schema evolution, type-safe configuration, deprecation strategies, and commit-level traceability.
April 2025
Activity
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Quality Metrics
Correctness96.6%
Maintainability96.6%
Architecture96.6%
Performance93.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
YAML
Technical Skills
API DesignAPI DevelopmentBackend DevelopmentDocumentationOpenAPI SpecificationSchema Definition
Repositories Contributed To
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