Future-House/ldp
Oct 2025 – Nov 2025
2 Months active
Languages Used
Python
Technical Skills
API IntegrationBackend DevelopmentCode RefactoringTestingAPI developmentbackend development
Gabriel Zaccak
PROFILE
Gabriel Zaccak
Jabra Zaccak contributed to the Future-House/ldp repository by developing and refining backend systems focused on cost tracking and optimization for LLM usage. Over two months, Jabra implemented cached token tracking and updated cost calculation logic, enabling more accurate budgeting and cost control for model operations. Using Python and leveraging skills in API integration, backend development, and data processing, Jabra also addressed a critical bug in streaming cost tracking by ensuring cost callbacks only fired on the final chunk containing usage data. The work demonstrated a thoughtful approach to scalable, cost-aware deployment and improved the reliability of billing signals within the system.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
1
Lines of code
5,083
Activity Months2
Your Network
11 people
Work History
November 2025
1 Commits • 1 Features
Nov 1, 2025Monthly summary for 2025-11: Future-House/ldp — LLM Usage Token Caching and Cost Optimization. Implemented cached token tracking and updated LLM usage cost calculation to improve efficiency, cost visibility, and budgeting for model operations. Changes align with scalable, cost-aware LLM usage and provide clearer token accounting.
1 Commits • 1 Features
Nov 1, 2025Monthly summary for 2025-11: Future-House/ldp — LLM Usage Token Caching and Cost Optimization. Implemented cached token tracking and updated LLM usage cost calculation to improve efficiency, cost visibility, and budgeting for model operations. Changes align with scalable, cost-aware LLM usage and provide clearer token accounting.
November 2025
October 2025
1 Commits
Oct 1, 2025In October 2025, I worked on the Future-House/ldp repository and delivered a critical bug fix to streaming cost tracking. The cost calculation previously fired for multiple streaming chunks, causing duplicate or premature cost events. I implemented a guard that triggers cost callbacks only on the final chunk that contains usage, by checking for the presence of 'usage' on the response object. This prevented duplicate cost calculations and ensured accurate billing signals. The change is tracked in commit 8d4aab9ec1711a8c6296b59fe0bf1d1ff046d0b4 with message 'fix: cost callbacks fire only on final chunk with usage (#340)'.
October 2025
1 Commits
Oct 1, 2025In October 2025, I worked on the Future-House/ldp repository and delivered a critical bug fix to streaming cost tracking. The cost calculation previously fired for multiple streaming chunks, causing duplicate or premature cost events. I implemented a guard that triggers cost callbacks only on the final chunk that contains usage, by checking for the presence of 'usage' on the response object. This prevented duplicate cost calculations and ensured accurate billing signals. The change is tracked in commit 8d4aab9ec1711a8c6296b59fe0bf1d1ff046d0b4 with message 'fix: cost callbacks fire only on final chunk with usage (#340)'.
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
API IntegrationAPI developmentBackend DevelopmentCode RefactoringTestingbackend developmentdata processingmachine learning
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