One API consolidates API keys and distributes LLM requests across multiple model providers under a standard OpenAI-compatible API format. It targets developers and operations teams who need centralized key management and request routing for upstream LLM services.
Project overview
It addresses the operational challenge of managing divergent LLM provider APIs by normalizing incoming requests into a standard OpenAI format and distributing them across multiple configured channels.
Project type
Model Runtime · Infrastructure
Use cases
Chat Assistants
Deployment
Docker / Docker Compose
License
MIT
Best for
Developers and enterprise or operations teams needing an OpenAI-compatible interface to route and proxy requests across multiple configured upstream LLM providers.
Key capabilities
Distributes incoming requests across multiple upstream channels using load balancing.
Limitations and risks
The MIT license requires maintaining attribution and a link to the project in the footer.
Data loss on container restart will occur if the SQLite volume is not mounted.
Getting started
Setup difficulty is rated as easy due to out-of-the-box functionality with the SQLite default, requiring no coding; users deploy the binary or container and configure upstream channels via the web GUI.
Alternatives and comparisons
Provides a proxy server and Python SDK that routes requests to over 100 LLM providers in the OpenAI format, including features for virtual keys and cost tracking.
Serves models directly for high-throughput inference rather than proxying requests to external upstream API providers.
Serves open models locally using an OpenAI-compatible REST API with optimized compute performance.
GitHub project description: LLM API management & key redistribution system, unifying multiple providers under a single API. Single binary, Docker-ready, with an English UI.