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Millwright: Rust-based, self-hosted LLM router

Hacker News 热门(Algolia · 中文化)T2
03:0307/23, 03:03 AMHN digestRead the original ↗Export MD ↓

Score

69
Information gain7 ×0.3

提供了一种新型自托管路由方案,对多模型管理场景有明确信息增量。

Content quality7 ×0.2

项目文档和架构描述清晰,但尚未经过大规模生产验证。

Practical value8 ×0.2

对需要成本控制和隐私保护的团队有直接实用价值,开源且易于集成。

Timeliness9 ×0.15

发布于 Hacker News 热门当日,与当前 LLM 部署痛点高度契合。

Source reliability8 ×0.15

来自 Hacker News 热门话题,GitHub 项目内容公开可查,可信度较高。

Base 76.5 × T2 Source weight ×0.9 = 69

Curation line 70Below curation line

Why selected

This project addresses the practical pain point of switching among multiple model backends, and its open-source implementation holds significant reference value.

AI commentary

「If you're struggling with orchestrating multiple LLM APIs and controlling costs, Millwright's deterministic routing approach is worth a try. Its Rust implementation and self-hosted nature make it especially suitable for teams with strict latency and security requirements.」

Quick overview

Millwright is a self-hosted LLM router written in Rust, emphasizing cost-effectiveness, deterministic routing, and high performance. It is secure and private by default, supporting multi-model load balancing and fallback, making it suitable for AI applications that require local deployment, low latency, and high reliability. The project is open-sourced on GitHub and can be flexibly integrated into existing inference backends.

  • Built with Rust for high performance and memory safety
  • Self-hosted with security and privacy by default
  • Deterministic routing and cost control mechanisms
  • Multi-model fallback and load balancing support

Full text

Millwright

Millwright

The self-hosted LLM router for policy, cache affinity, and spend control in one Rust Binary.

Release v0.1.0 Apache-2.0 license CI status Rust 1.97 Linux and macOS

What is Millwright

Millwright is an open-source, self hosted LLM router that runs between your AI applications and the model providers you choose. It accepts OpenAI Chat Completions and Anthropic Messages, then routes each request to an OpenAI-compatible API, Anthropic, or Amazon Bedrock.

You define which models belong in the cheap, mid, and frontier roles. Millwright selects the lowest estimated-cost healthy route the resolved role permits and, when given a session ID, preserves provider/model affinity for prompt-cache reuse.

Millwright is a router, not an agent orchestrator. It does not spawn agents, schedule work, inspect prompts, or rewrite context.

Why Millwright

LLM costs rise quickly when every request reaches the most expensive model and provider changes break prompt-cache reuse. Millwright makes the lower-cost path explicit:

  • Control model spend — reserve frontier models for the work your policy says needs them.
  • Protect prompt caches — role-scoped affinity keeps each session on a confirmed provider and model while its cache window is warm.
  • Keep concurrent agents moving — one session can maintain independent cheap, mid, and frontier lanes without serializing requests.
  • Change providers without changing application code — route compatible traffic across providers behind one endpoint.
  • Keep routing inspectable — response headers identify the chosen route; traces and ledger entries retain the evidence when persistence is available.
  • Run the data plane yourself — provider credentials stay on your infrastructure, with no required hosted control plane.

Get Started

Quick Start

Rust 1.97+ is required when building from source.

git clone https://github.com/Northwood-Systems/millwright.git
cd millwright
cargo install --path . --locked
millwright init
millwright serve

millwright init walks through provider endpoints, model roles, pricing, and separate workload and operator keys. It stores references to provider-secret environment variables, never the provider credentials themselves.

Connect Claude Code, Codex, OpenCode, Pi, or another compatible client. Choose millwright-fast, millwright-code, or millwright-plan to request the cheap, mid, or frontier role.

Optional Local Demo

The included Docker Compose setup starts Millwright with a mock provider and local demo key:

make compose-up

From another terminal:

curl http://localhost:8080/v1/chat/completions \
  -H 'Authorization: Bearer sk-millwright-local-demo' \
  -H 'Content-Type: application/json' \
  -d '{"model":"millwright-fast","messages":[{"role":"user","content":"Hello from Millwright"}]}'

Architecture · Router API · Policy & Catalog · Deployment · Cost Analysis · Security

Features

Policy-controlled routing

Classify requests with explicit task and risk headers, the client's model selection, or documented defaults. Millwright resolves a cheap, mid, or frontier role, then selects the lowest estimated-cost healthy model that policy allows. High-risk and planning requests always use the frontier role.

Every decision includes the chosen model, provider, route reason, and rejected alternatives. Message content is never inspected to make the decision.

Cache-aware concurrency

Naive per-request routing can erase provider prompt-cache savings by switching models mid-session. Millwright keeps independent cheap, mid, and frontier affinity lanes under one opaque session ID, each with its own cache TTL.

Traffic resolved to different roles no longer fights over one warm route. Same-role calls converge on the last confirmed provider/model, while all requests remain concurrent—Millwright does not serialize agent traffic or orchestrate agent lifecycles.

See where the spend goes

Completed requests normally write usage evidence, cost provenance, provider attempts, and routing evidence to the ledger. SQLite is the local default; PostgreSQL is available for production deployments.

Command What it shows
millwright spend Total spend, cache read rate, and per-team breakdown
millwright models Model and provider mix
millwright trace <id> One routing decision, including rejected alternatives
millwright top Live spend and model activity in the terminal

The same data is available through the authenticated /v1/millwright/* management APIs, with JSON output from spend, models, and trace for dashboards and automation.

Analyze cost opportunities

millwright analyze reads a live Millwright ledger or local Millwright, OpenAI-compatible, or Anthropic JSONL. It produces a self-contained HTML or Markdown report plus schema-versioned JSON.

millwright analyze \
  --url http://127.0.0.1:8080 \
  --key "$MILLWRIGHT_OPERATOR_KEY" \
  --since 30d \
  --report analysis.html \
  --json-out analysis.json

Reports separate measured cost evidence from modeled candidate economics. Add an explicit catalog and candidate allowlist to compare full-swap costs and a price-floor economic scenario. Candidate results are cost hypotheses—not quality results or production routing recommendations. See Cost Analysis.

Provider and protocol support

OpenAI Chat Completions and Anthropic Messages come in; OpenAI-compatible APIs, native Anthropic, and Amazon Bedrock go out. Same-protocol routes preserve fields Millwright does not model. Cross-protocol routes translate the supported text-and-tools subset and reject unsupported shapes instead of silently dropping data.

Retryable transport failures, timeouts, HTTP 408/429, and HTTP 5xx responses can trigger one bounded failover attempt. Circuit breakers stop unhealthy routes from receiving every request.

Built for self-hosting

Millwright ships as one Rust binary with Docker and Docker Compose support. Provider credentials remain in environment variables, while separate workload and operator keys control inference and management access. Structured logs omit API keys and prompt payloads; request bodies, concurrency, timeouts, and upstream buffers are bounded.

Enterprise

Need help deploying Millwright inside your infrastructure, integrating a provider, or designing a routing policy for your workload?

Talk to the founder

Contributing

Bug fixes, features, tests, and documentation improvements are welcome. Read CONTRIBUTING.md before opening a pull request.

Quick Start for Contributors

The Rust toolchain is pinned in rust-toolchain.toml.

git clone https://github.com/Northwood-Systems/millwright.git
cd millwright
make build
make test

Code Quality / Linting

Before opening a pull request, run:

make fmt
make lint
make test
make audit

The checks cover Rustfmt, Clippy with warnings denied, all Rust test targets, dependency advisories, approved licenses, and dependency sources. make audit requires cargo-deny. CI also builds the release binary and Docker image.

License

Apache-2.0

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