{"id":115407,"date":"2026-09-03T01:08:23","date_gmt":"2026-09-03T01:08:23","guid":{"rendered":"https:\/\/youzum.net\/meet-switchyard-a-rust-proxy-and-library-that-routes-and-translates-llm-traffic-across-openai-and-anthropic-apis\/"},"modified":"2026-09-03T01:08:23","modified_gmt":"2026-09-03T01:08:23","slug":"meet-switchyard-a-rust-proxy-and-library-that-routes-and-translates-llm-traffic-across-openai-and-anthropic-apis","status":"publish","type":"post","link":"https:\/\/youzum.net\/it\/meet-switchyard-a-rust-proxy-and-library-that-routes-and-translates-llm-traffic-across-openai-and-anthropic-apis\/","title":{"rendered":"Meet Switchyard: A Rust Proxy and Library That Routes and Translates LLM Traffic Across OpenAI and Anthropic APIs"},"content":{"rendered":"

Teams running coding agents hit the same wall. Claude Code speaks the Anthropic Messages API, Codex CLI speaks OpenAI, and the model a team actually wants to serve sits behind vLLM, NVIDIA NIM<\/a>, or Ollama. Rewriting the agent is not an option, so the translation layer has to live somewhere else.<\/p>\n

Switchyard<\/a> is NVIDIA\u2019s answer: a Rust proxy and library for LLM traffic that routes requests across providers, translates between OpenAI and Anthropic formats, records operational metrics, and exposes typed, composable routing algorithms. It is released under Apache 2.0<\/a> with documentation at docs.nvidia.com\/nemo\/switchyard<\/a>.<\/p>\n

Is it deployable?<\/strong> Yes, but for evaluation only. The binary installs from crates.io and the launcher from PyPI, and it self-hosts anywhere, but NVIDIA labels Switchyard pre-alpha and experimental<\/a>, warns it is not for production use, and expects the API and algorithms to change significantly before v1.0.<\/p>\n

What Switchyard does<\/strong><\/h2>\n

Clients keep their native API. Switchyard decodes the inbound request into provider-neutral Rust types, runs a routing algorithm to pick a backend, re-encodes the request in that backend\u2019s own wire format, calls it, and translates the response, including streaming events, back into the shape the client expects.<\/p>\n

The server<\/a> accepts three inbound formats: OpenAI Chat Completions, OpenAI Responses, and Anthropic Messages. Any of the three can address any route, and each configured LLM client selects one upstream format of its own. That decoupling is the point: the agent\u2019s API and the backend\u2019s API no longer have to match.<\/p>\n

\n<\/div>\n

\n

Three ways to run it<\/strong><\/h2>\n<\/p>

The launcher path<\/strong> targets coding agents. Install the published tool with uv tool install --python 3.12 \"nemo-switchyard[cli]\"<\/code>, then run switchyard launch claude<\/code>, switchyard launch codex<\/code>, or switchyard launch openclaw<\/code> against a packaged deployment or your own TOML file.<\/p>\n

The server path<\/strong> installs the standalone proxy with cargo install --locked switchyard-server<\/code>, validates a config with --dry-run<\/code>, and serves on a host and port you choose.<\/p>\n

The library path<\/strong> uses switchyard-libsy<\/code>, which embeds the routing algorithms in a Rust application without owning an HTTP stack. It never calls a model itself; the algorithm decides which target to use and hands every model call back to the caller.<\/p>\n

Routing algorithms<\/strong><\/h2>\n

A route<\/a> is one client-visible model ID plus the algorithm behind it. The server supports:<\/strong><\/p>\n