BerriAI/litellm
Jan 2026 – Mar 2026
2 Months active
Languages Used
PythonJavaScript
Technical Skills
API developmentbackend developmenttestingMockingRefactoringUnit Testing
Aarish Alam
PROFILE
Aarish Alam
Contributed to BerriAI/litellm by developing and refining backend features focused on caching, data integrity, and testing reliability. Built a pagination mechanism for Vertex AI context caching, enabling efficient retrieval of cached items across multiple pages with a defined limit, and improved cache lookup stability by updating both synchronous and asynchronous cache checks. Enhanced Gemini model performance through prompt caching and addressed function-calling flag issues, while also implementing cascade deletion for user-linked invitation data to prevent foreign key violations. Leveraged JavaScript and Python for API development, backend refactoring, and comprehensive unit testing, resulting in more robust deployments and maintainable codebases.
Overall Statistics
Feature vs Bugs
75%Features
Repository Contributions
5Total
Bugs
1
Commits
5
Features
3
Lines of code
7,108
Activity Months2
Your Network
786 peopleWork History
March 2026
3 Commits • 2 Features
Mar 1, 2026March 2026 monthly summary for BerriAI/litellm focused on delivering performance, reliability, and testing improvements. Key deliverables include Gemini model enhancements (prompt caching and function-calling flag fixes) with UI/back-end stability refactors, a data-integrity fix for cascade deletion of invitation links tied to deleted users, and testing improvements for Anthropic skills (duplicate-import cleanup and HTTP method parameterization). These efforts reduced latency, eliminated potential FK violations, and raised test quality, enabling faster feature delivery and more robust deployments.
3 Commits • 2 Features
Mar 1, 2026March 2026 monthly summary for BerriAI/litellm focused on delivering performance, reliability, and testing improvements. Key deliverables include Gemini model enhancements (prompt caching and function-calling flag fixes) with UI/back-end stability refactors, a data-integrity fix for cascade deletion of invitation links tied to deleted users, and testing improvements for Anthropic skills (duplicate-import cleanup and HTTP method parameterization). These efforts reduced latency, eliminated potential FK violations, and raised test quality, enabling faster feature delivery and more robust deployments.
March 2026
January 2026
2 Commits • 1 Features
Jan 1, 2026Concise monthly summary for 2026-01 focusing on key accomplishments, major fixes, impact, and technical skills demonstrated for BerriAI/litellm.
January 2026
2 Commits • 1 Features
Jan 1, 2026Concise monthly summary for 2026-01 focusing on key accomplishments, major fixes, impact, and technical skills demonstrated for BerriAI/litellm.
Activity
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Quality Metrics
Correctness94.0%
Maintainability80.0%
Architecture78.0%
Performance76.0%
AI Usage28.0%
Skills & Technologies
Programming Languages
JavaScriptPython
Technical Skills
API developmentMockingRefactoringUnit Testingbackend developmentdatabase managementfrontend developmenttesting
Repositories Contributed To
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