2 Repos
Systems that route requests to different AI models or providers based on workflow phase, cost, or quality requirements.
Distinct from Phase-Aware Schedulers: None of the candidates cover the routing of LLM requests across providers for different execution phases; they focus on training data, audio, or web requests.
Explore 2 awesome GitHub repositories matching artificial intelligence & ml · Model Routing Gateways. Refine with filters or upvote what's useful.
This project is an autonomous AI software development framework designed to plan, code, test, and commit software milestones without human intervention. It functions as a state-machine-driven agent loop that orchestrates development through a recurring cycle of research, execution, and verification. The system distinguishes itself through a git-isolated task runner that executes milestones in separate worktrees and branches, ensuring changes are squash-merged into a linear commit history. It features a multi-model routing gateway that assigns different LLM providers to specific workflow phase
Assigns different LLM providers or models to each development phase with automatic fallback and budget-aware cost control.
OptiLLM is an inference proxy and gateway router that directs prompts to specific language models based on cost, performance, and provider health. It functions as a middleware layer designed to optimize requests through intelligent routing, load balancing, and context management. The project provides specialized capabilities for data protection by anonymizing personally identifiable information before requests reach a model. It also acts as a reasoning orchestrator and tool integration layer, using inference-time loops and self-reflection to improve accuracy while connecting models to externa
Acts as a gateway that routes requests to different AI models based on cost and performance requirements.