
Worked on security and catalog enhancements for the BerriAI/litellm repository, focusing on per-user OAuth token storage and validation to support interactive MCP flows. Leveraged FastAPI, Python, and Redis to implement configurable token TTLs, improving access control, auditability, and system performance. Expanded the model catalog by integrating Kimi-K2.5 and MiniMax-M2.5 offerings, including pricing and context window configurations to enable cost-aware model selection and streamline onboarding. The work addressed both backend and frontend requirements, emphasizing robust API development and model integration. These contributions strengthened security, reduced token tampering risk, and improved the platform’s readiness for monetization and customer onboarding.
Month 2026-04: Security and catalog enhancements for BerriAI/litellm. Delivered per-user OAuth token storage and validation for interactive MCP flows with configurable TTL, strengthening access control and performance. Expanded model catalog with Kimi-K2.5 and MiniMax-M2.5 offerings, including pricing and context window configurations, enabling cost-aware model selection and faster onboarding. These changes improve security, auditability, and monetization readiness while reducing token tampering risk and accelerating go-to-market activities.
Month 2026-04: Security and catalog enhancements for BerriAI/litellm. Delivered per-user OAuth token storage and validation for interactive MCP flows with configurable TTL, strengthening access control and performance. Expanded model catalog with Kimi-K2.5 and MiniMax-M2.5 offerings, including pricing and context window configurations, enabling cost-aware model selection and faster onboarding. These changes improve security, auditability, and monetization readiness while reducing token tampering risk and accelerating go-to-market activities.

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