ai-api

Multi-provider LLM access without hardcoding requires dynamic model discovery via live catalogs. This approach enables deterministic routing and capability-aware selection to optimize provider choices across software engineering tasks.

Dynamic model discovery for LLM routing is the process of using live catalogs to find available models. It replaces static lists with live tiered selection to optimize model choices for tasks like code review and debugging.

Performance benchmarking can curate LLM providers for code review by tracking and aggregating results. This logging mechanism supports data-driven model curation, ensuring deterministic routing selects optimal providers.

Multi-provider LLM routing works for debugging and documentation tasks through capability-aware selection. It applies deterministic routing to match specific software engineering task requirements with optimal models.

The best way to benchmark LLM performance across multiple providers is using deterministic routing with logging. This enables performance tracking and aggregation to support data-driven model curation without maintaining hard-coded lists.

Static LLM provider selection fails during software engineering tasks due to scattered model catalogs and brittleness. Dynamic discovery via live catalogs solves this by enabling performance-based curation and deterministic routing.