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A lightweight self-hosted LLM routing gateway with OpenAI & Anthropic dual-protocol support

Project description

Keyway

A lightweight self-hosted LLM routing gateway with OpenAI & Anthropic dual-protocol support.

English | 中文


English

Keyway lets you route LLM requests from any OpenAI/Anthropic-compatible client (Claude Code, Cursor, OpenAI SDK, etc.) to multiple upstream providers (DeepSeek, OpenAI, Anthropic, Volcengine, Zhipu GLM, Qwen, and more) — all through a single self-issued db_sk_ API key.

Features

  • Dual-protocol proxy: OpenAI /v1/chat/completions + Anthropic /v1/messages — both work out of the box
  • Model aliases: map a client-facing name (e.g. deepseek-v4-pro) to any upstream model
  • Group isolation: keys are bound to groups; a client's key can only access its group's providers/routes
  • Self-issued API keys: generate db_sk_ keys for your team; plaintext is retrievable by admin
  • Encrypted at rest: all upstream API keys and self-issued key plaintexts are Fernet-encrypted
  • Built-in tools: Tavily web search auto-injected into OpenAI tool-use loops
  • Request logging: every upstream call is logged with status, latency, and token counts
  • E2E testing: one-click probe of all enabled routes
  • Generation forwarding: image/video/3D endpoints via configurable upstream_path
  • No external dependencies: just Python + SQLite — no database server, no Redis
  • Web admin UI: full CRUD management interface included

Quick Start

Option 1: pip install

pip install keyway-router

# Generate a secret and create .env
python -c "import secrets; print('KEYWAY_SECRET=' + secrets.token_urlsafe(48))" > .env
echo "KEYWAY_ADMIN_TOKEN=my-admin-token" >> .env

# Run
keyway
# → Server starts on http://localhost:9233

Option 2: Docker

cd docker
cp .env.example .env
# Edit .env: set KEYWAY_SECRET and KEYWAY_ADMIN_TOKEN
docker compose up -d
# → Server at http://localhost:9233

Option 3: From source

git clone https://github.com/keyway-gateway/keyway.git
cd keyway
pip install -e ".[dev]"

cp .env.example .env
# Edit .env: set KEYWAY_SECRET (required) and KEYWAY_ADMIN_TOKEN

python -m keyway

Configuration

All settings are via environment variables (or .env file):

Variable Default Description
KEYWAY_SECRET (required) Fernet encryption key for at-rest secrets. Generate with python -c "import secrets; print(secrets.token_urlsafe(48))"
KEYWAY_ADMIN_TOKEN (auto-generated) Admin token for the management UI. If empty, a random token is printed to console on startup
KEYWAY_HOST 127.0.0.1 Bind address
KEYWAY_PORT 9233 Bind port
KEYWAY_DATA_DIR ./data SQLite database location
KEYWAY_CORS_ORIGINS http://127.0.0.1:9233,... CORS allowed origins
KEYWAY_PUBLIC_BASE_URL (auto-inferred) Base URL shown in admin UI for key setup
KEYWAY_LOG_LEVEL info Log level

Usage Guide

1. Access the admin UI

Open http://localhost:9233/ in your browser. Log in with your KEYWAY_ADMIN_TOKEN.

2. Add an upstream provider

In the "default" group, scroll to "Upstream Providers", fill in:

  • ID: e.g. deepseek
  • Name: e.g. DeepSeek
  • Protocol: openai or anthropic
  • Base URL: e.g. https://api.deepseek.com/v1
  • API Key: your upstream provider key

3. Create a model route

Scroll to "Model Routes", fill in:

  • Alias: the name clients will use, e.g. deepseek-v4-pro
  • Provider: select the provider you just created
  • Upstream Model: the real model name at the provider, e.g. deepseek-chat

4. Create an API key

Scroll to "Self-issued API Keys", create a key. The plaintext db_sk_... is shown once — save it. You can re-retrieve it later from the key list.

5. Connect your client

Claude Code

Create .claude/settings.local.json in your project:

{
  "env": {
    "ANTHROPIC_BASE_URL": "http://localhost:9233",
    "ANTHROPIC_AUTH_TOKEN": "db_sk_your-key-here",
    "ANTHROPIC_MODEL": "deepseek-v4-pro",
    "ANTHROPIC_DEFAULT_HAIKU_MODEL": "deepseek-v4-pro",
    "ANTHROPIC_DEFAULT_SONNET_MODEL": "deepseek-v4-pro",
    "ANTHROPIC_DEFAULT_OPUS_MODEL": "deepseek-v4-pro"
  }
}
OpenAI SDK (Python)
from openai import OpenAI

client = OpenAI(
    base_url="http://localhost:9233/v1",
    api_key="db_sk_your-key-here",
)

resp = client.chat.completions.create(
    model="deepseek-v4-pro",
    messages=[{"role": "user", "content": "Hello!"}],
)

Usage Example: Multi-Provider Setup

This example configures four upstream models through Keyway, then connects Claude Code with the CC Switch helper to switch between them on the fly.

Step 1: Add four providers

Open the admin UI (http://localhost:9233/), go to the "default" group, and create these providers:

Provider ID Name Protocol Base URL Where to get API Key
deepseek DeepSeek openai https://api.deepseek.com/v1 https://platform.deepseek.com/
zhipu Zhipu GLM openai https://open.bigmodel.cn/api/paas/v4 https://open.bigmodel.cn/
minimax MiniMax openai https://api.minimaxi.com/v1 https://platform.minimaxi.com/
moonshot Moonshot (Kimi) openai https://api.moonshot.cn/v1 https://platform.moonshot.cn/

Step 2: Create four model routes

In the same group, go to "Model Routes" and create:

Alias (client-facing) Provider Upstream Model
deepseek-v4-pro deepseek deepseek-chat
glm-5.2 zhipu glm-4-plus
minimax-m3 minimax MiniMax-M3
kimi-k2.7-code moonshot kimi-k2-0905-preview

Model IDs change frequently — verify the exact upstream model name on each provider's console.

Step 3: Create an API key

Go to "Self-issued API Keys", create a key (e.g. named "claude-code"). You'll get a db_sk_... plaintext. Save it.

Step 4: Connect Claude Code

Create .claude/settings.local.json in your project root (add it to .gitignore!):

{
  "env": {
    "ANTHROPIC_BASE_URL": "http://localhost:9233",
    "ANTHROPIC_AUTH_TOKEN": "db_sk_your-key-here",
    "ANTHROPIC_MODEL": "deepseek-v4-pro",
    "ANTHROPIC_DEFAULT_HAIKU_MODEL": "deepseek-v4-pro",
    "ANTHROPIC_DEFAULT_SONNET_MODEL": "deepseek-v4-pro",
    "ANTHROPIC_DEFAULT_OPUS_MODEL": "deepseek-v4-pro"
  }
}

Base URL rules (local):

  • Anthropic SDK / Claude Code: http://localhost:9233 (no trailing slash; SDK auto-appends /v1/messages)
  • OpenAI SDK: http://localhost:9233/v1 (SDK appends /chat/completions)

Switch models in-session with /model glm-5.2 or /model kimi-k2.7-code.

Step 5 (optional): Use CC Switch for model switching

CC Switch is a desktop GUI for managing Claude Code model profiles. With Keyway, you can create a profile per alias — all pointing to the same ANTHROPIC_BASE_URL and ANTHROPIC_AUTH_TOKEN, just changing ANTHROPIC_MODEL:

Profile ANTHROPIC_MODEL
DeepSeek deepseek-v4-pro
GLM glm-5.2
MiniMax minimax-m3
Kimi kimi-k2.7-code

Switch between them with one click in CC Switch — no server restart, no key rotation.

Step 6: Verify with curl

# OpenAI protocol
curl http://localhost:9233/v1/chat/completions \
  -H "Authorization: Bearer db_sk_your-key" \
  -H "Content-Type: application/json" \
  -d '{"model":"glm-5.2","messages":[{"role":"user","content":"Hello!"}],"max_tokens":16}'

# Anthropic protocol (for Anthropic-protocol upstreams only)
curl http://localhost:9233/v1/messages \
  -H "Authorization: Bearer db_sk_your-key" \
  -H "anthropic-version: 2023-06-01" \
  -H "Content-Type: application/json" \
  -d '{"model":"deepseek-v4-pro","messages":[{"role":"user","content":"Hello!"}],"max_tokens":16}'

Protocol note: OpenAI-protocol clients (/v1/chat/completions) require OpenAI-protocol providers. Anthropic-protocol clients (/v1/messages) require Anthropic-protocol providers. All four providers in this example use OpenAI protocol, so use the OpenAI endpoint (/v1/chat/completions) for direct API calls. Claude Code uses the Anthropic endpoint (/v1/messages) — to use Claude Code with OpenAI-protocol upstreams, add an Anthropic-protocol provider (e.g. Anthropic itself) and create routes with the same aliases.

API Reference

Proxy endpoints (Bearer db_sk_ auth)

Method Path Description
POST /v1/chat/completions OpenAI-compatible chat completions (stream + non-stream)
GET /v1/models OpenAI-compatible model list (returns enabled route aliases)
POST /v1/messages Anthropic Messages-compatible (stream + non-stream)
POST /v1/messages/count_tokens Anthropic token count estimate
POST /v1/generations Generic generation forwarding (image/video/3D)

Admin endpoints (X-Admin-Token header or session cookie)

Method Path Description
POST /admin/login Login with admin token → session cookie
GET /admin/session Verify session
POST /admin/logout Logout
GET /admin/config Runtime config (base URL for key setup)
GET/POST /admin/llm/groups List / create groups
GET/PATCH/DELETE /admin/llm/groups/{id} Get / update / delete a group
POST /admin/llm/groups/{id}/copy Deep-copy a group (re-issues new keys)
GET/POST /admin/llm/groups/{id}/providers List / create providers in a group
GET/PATCH/DELETE /admin/llm/providers/{id} Get / update / delete a provider
GET/POST /admin/llm/groups/{id}/routes List / create routes in a group
GET/PATCH/DELETE /admin/llm/routes/{id} Get / update / delete a route
GET/POST /admin/llm/groups/{id}/keys List / create API keys in a group
GET /admin/llm/keys/{id}/plaintext Retrieve key plaintext (admin only)
PATCH/DELETE /admin/llm/keys/{id} Update / delete an API key
GET/POST /admin/llm/groups/{id}/tool-providers List / create tool providers
PATCH/DELETE /admin/llm/tool-providers/{id} Update / delete a tool provider
GET /admin/llm/logs Request logs (filter by api_key_id, group_id)
GET /admin/llm/stats Stats for a specific key
POST /admin/llm/test Probe a single provider or route
POST /admin/llm/e2e End-to-end test of all enabled routes

Development

pip install -e ".[dev]"
pytest -q

Architecture

  • Backend: FastAPI + uvicorn, 5 pip dependencies (fastapi, uvicorn, httpx, cryptography, pydantic)
  • Storage: SQLite (single file, keyway.db) — no external database
  • Auth: Admin token (single-admin) + self-issued db_sk_ API keys (group-scoped)
  • Encryption: Fernet (from cryptography) — SHA-256 of KEYWAY_SECRET derives the key
  • Frontend: Zero-dependency vanilla JS, served by FastAPI's StaticFiles

中文

Keyway 是一个轻量级的可自部署 LLM 路由网关,支持 OpenAI 和 Anthropic 双协议。通过一条自签发的 db_sk_ API Key,即可将 Claude Code、Cursor、OpenAI SDK 等客户端的请求路由到多个上游提供商(DeepSeek、OpenAI、Anthropic、火山方舟、智谱 GLM、千问等)。

功能特性

  • 双协议代理:OpenAI /v1/chat/completions + Anthropic /v1/messages —— 开箱即用
  • 模型别名:将客户端可见的名称(如 deepseek-v4-pro)映射到任意上游模型
  • 分组隔离:Key 绑定到组;客户端持有的 Key 只能访问该组的 provider/route
  • 自签发 API Key:为团队生成 db_sk_ Key;管理员可随时取回明文
  • 加密存储:所有上游 API Key 和自签发 Key 明文均使用 Fernet 加密
  • 内置工具:Tavily 网络搜索自动注入 OpenAI 工具调用循环
  • 请求日志:每次上游调用均记录状态码、延迟和 token 数
  • 端到端测试:一键探测所有已启用路由
  • 生成式转发:通过可配置的 upstream_path 支持图片/视频/3D 端点
  • 零外部依赖:仅需 Python + SQLite —— 无需数据库服务器、无需 Redis
  • Web 管理界面:包含完整的图形化 CRUD 管理

快速开始

方式一:pip 安装

pip install keyway-router

# 生成密钥并创建 .env
python -c "import secrets; print('KEYWAY_SECRET=' + secrets.token_urlsafe(48))" > .env
echo "KEYWAY_ADMIN_TOKEN=my-admin-token" >> .env

# 启动
keyway
# → 服务启动在 http://localhost:9233

方式二:Docker

cd docker
cp .env.example .env
# 编辑 .env:设置 KEYWAY_SECRET 和 KEYWAY_ADMIN_TOKEN
docker compose up -d
# → 服务在 http://localhost:9233

方式三:从源码运行

git clone https://github.com/keyway-gateway/keyway.git
cd keyway
pip install -e ".[dev]"

cp .env.example .env
# 编辑 .env:设置 KEYWAY_SECRET(必填)和 KEYWAY_ADMIN_TOKEN

python -m keyway

配置项

所有配置通过环境变量(或 .env 文件)设置:

变量 默认值 说明
KEYWAY_SECRET (必填) Fernet 加密密钥,用于加密存储的秘密。用 python -c "import secrets; print(secrets.token_urlsafe(48))" 生成
KEYWAY_ADMIN_TOKEN (自动生成) 管理界面 token。留空则启动时随机生成并打印到控制台
KEYWAY_HOST 127.0.0.1 监听地址
KEYWAY_PORT 9233 监听端口
KEYWAY_DATA_DIR ./data SQLite 数据库存放目录
KEYWAY_CORS_ORIGINS http://127.0.0.1:9233,... CORS 允许的来源
KEYWAY_PUBLIC_BASE_URL (自动推断) 管理界面中显示给用户的 Base URL
KEYWAY_LOG_LEVEL info 日志级别

使用指南

1. 打开管理界面

浏览器访问 http://localhost:9233/,输入 KEYWAY_ADMIN_TOKEN 登录。

2. 添加上游 Provider

在"default"组中,找到"Upstream Providers",填写:

  • ID:如 deepseek
  • 名称:如 DeepSeek
  • 协议openaianthropic
  • Base URL:如 https://api.deepseek.com/v1
  • API Key:你的上游提供商密钥

3. 创建模型路由

找到"Model Routes",填写:

  • Alias:客户端使用的名称,如 deepseek-v4-pro
  • Provider:选择刚创建的 provider
  • Upstream Model:上游真实模型名,如 deepseek-chat

4. 创建 API Key

找到"Self-issued API Keys",创建 Key。明文 db_sk_... 仅显示一次——请妥善保存。管理员可随时从列表重新获取明文。

5. 连接客户端

Claude Code

在项目根目录创建 .claude/settings.local.json

{
  "env": {
    "ANTHROPIC_BASE_URL": "http://localhost:9233",
    "ANTHROPIC_AUTH_TOKEN": "db_sk_你的key",
    "ANTHROPIC_MODEL": "deepseek-v4-pro",
    "ANTHROPIC_DEFAULT_HAIKU_MODEL": "deepseek-v4-pro",
    "ANTHROPIC_DEFAULT_SONNET_MODEL": "deepseek-v4-pro",
    "ANTHROPIC_DEFAULT_OPUS_MODEL": "deepseek-v4-pro"
  }
}
OpenAI SDK(Python)
from openai import OpenAI

client = OpenAI(
    base_url="http://localhost:9233/v1",
    api_key="db_sk_你的key",
)

resp = client.chat.completions.create(
    model="deepseek-v4-pro",
    messages=[{"role": "user", "content": "你好!"}],
)

使用示例:多模型配置

本示例通过 Keyway 配置四个上游模型,然后用 Claude Code 配合 CC Switch 辅助工具实现一键切换。

第 1 步:添加四个 Provider

打开管理界面(http://localhost:9233/),进入"default"组,创建以下 Provider:

Provider ID 名称 协议 Base URL API Key 获取地址
deepseek DeepSeek openai https://api.deepseek.com/v1 https://platform.deepseek.com/
zhipu 智谱 GLM openai https://open.bigmodel.cn/api/paas/v4 https://open.bigmodel.cn/
minimax MiniMax openai https://api.minimaxi.com/v1 https://platform.minimaxi.com/
moonshot Moonshot (Kimi) openai https://api.moonshot.cn/v1 https://platform.moonshot.cn/

第 2 步:创建四条模型路由

在同一组中找到"Model Routes",创建:

Alias(客户端使用) Provider 上游模型
deepseek-v4-pro deepseek deepseek-chat
glm-5.2 zhipu glm-4-plus
minimax-m3 minimax MiniMax-M3
kimi-k2.7-code moonshot kimi-k2-0905-preview

模型 ID 更新频繁,配置前请到各家控制台核对确切的上游模型名。

第 3 步:创建 API Key

找到"Self-issued API Keys",创建一个 Key(如命名为"claude-code")。会得到 db_sk_... 明文,请妥善保存。

第 4 步:接入 Claude Code

在项目根目录创建 .claude/settings.local.json(记得加入 .gitignore!):

{
  "env": {
    "ANTHROPIC_BASE_URL": "http://localhost:9233",
    "ANTHROPIC_AUTH_TOKEN": "db_sk_你的key",
    "ANTHROPIC_MODEL": "deepseek-v4-pro",
    "ANTHROPIC_DEFAULT_HAIKU_MODEL": "deepseek-v4-pro",
    "ANTHROPIC_DEFAULT_SONNET_MODEL": "deepseek-v4-pro",
    "ANTHROPIC_DEFAULT_OPUS_MODEL": "deepseek-v4-pro"
  }
}

本地 Base URL 说明

  • Anthropic SDK / Claude Codehttp://localhost:9233(不带末尾斜杠;SDK 自动拼 /v1/messages
  • OpenAI SDKhttp://localhost:9233/v1(SDK 自动拼 /chat/completions

在会话中用 /model glm-5.2/model kimi-k2.7-code 切换模型。

第 5 步(可选):用 CC Switch 辅助切换

CC Switch 是一个管理 Claude Code 模型配置的桌面 GUI。配合 Keyway,可以为每个 alias 创建一个 profile——都指向同一个 ANTHROPIC_BASE_URLANTHROPIC_AUTH_TOKEN,只需改 ANTHROPIC_MODEL

Profile ANTHROPIC_MODEL
DeepSeek deepseek-v4-pro
GLM glm-5.2
MiniMax minimax-m3
Kimi kimi-k2.7-code

在 CC Switch 中一键切换——无需重启服务、无需轮换 Key。

第 6 步:用 curl 验证

# OpenAI 协议
curl http://localhost:9233/v1/chat/completions \
  -H "Authorization: Bearer db_sk_你的key" \
  -H "Content-Type: application/json" \
  -d '{"model":"glm-5.2","messages":[{"role":"user","content":"你好!"}],"max_tokens":16}'

# Anthropic 协议(仅限 Anthropic 协议的上游)
curl http://localhost:9233/v1/messages \
  -H "Authorization: Bearer db_sk_你的key" \
  -H "anthropic-version: 2023-06-01" \
  -H "Content-Type: application/json" \
  -d '{"model":"deepseek-v4-pro","messages":[{"role":"user","content":"你好!"}],"max_tokens":16}'

协议说明:OpenAI 协议客户端(/v1/chat/completions)需要 OpenAI 协议的 Provider;Anthropic 协议客户端(/v1/messages)需要 Anthropic 协议的 Provider。本示例的四个 Provider 均为 OpenAI 协议,直接调用 API 时请用 OpenAI 端点(/v1/chat/completions)。Claude Code 走 Anthropic 端点(/v1/messages)——若要让 Claude Code 接入 OpenAI 协议上游,需添加一个 Anthropic 协议的 Provider(如 Anthropic 官方),然后用相同的 alias 创建路由。

API 参考

代理端点(Bearer db_sk_ 鉴权)

Method Path Description
POST /v1/chat/completions OpenAI 兼容聊天补全(流式 + 非流式)
GET /v1/models OpenAI 兼容模型列表(返回已启用的路由 alias)
POST /v1/messages Anthropic Messages 兼容(流式 + 非流式)
POST /v1/messages/count_tokens Anthropic token 计数估算
POST /v1/generations 通用生成转发(图片/视频/3D)

管理端点(X-Admin-Token 头或 session cookie)

Method Path Description
POST /admin/login 管理员 token 登录 → session cookie
GET /admin/session 验证会话
POST /admin/logout 登出
GET /admin/config 运行时配置(Base URL)
GET/POST /admin/llm/groups 列出/创建组
GET/PATCH/DELETE /admin/llm/groups/{id} 查看/更新/删除组
POST /admin/llm/groups/{id}/copy 深拷贝组(重新签发新 key)
GET/POST /admin/llm/groups/{id}/providers 列出/创建组内 Provider
GET/PATCH/DELETE /admin/llm/providers/{id} 查看/更新/删除 Provider
GET/POST /admin/llm/groups/{id}/routes 列出/创建组内路由
GET/PATCH/DELETE /admin/llm/routes/{id} 查看/更新/删除路由
GET/POST /admin/llm/groups/{id}/keys 列出/创建组内 API Key
GET /admin/llm/keys/{id}/plaintext 取回 Key 明文(仅管理员)
PATCH/DELETE /admin/llm/keys/{id} 更新/删除 API Key
GET/POST /admin/llm/groups/{id}/tool-providers 列出/创建工具 Provider
PATCH/DELETE /admin/llm/tool-providers/{id} 更新/删除工具 Provider
GET /admin/llm/logs 请求日志(按 api_key_id、group_id 过滤)
GET /admin/llm/stats 指定 Key 的统计
POST /admin/llm/test 探测单个 Provider 或路由
POST /admin/llm/e2e 所有已启用路由的端到端测试

开发

pip install -e ".[dev]"
pytest -q

架构

  • 后端:FastAPI + uvicorn,5 个 pip 依赖(fastapiuvicornhttpxcryptographypydantic
  • 存储:SQLite(单文件 keyway.db)—— 无外部数据库
  • 鉴权:管理员 token(单管理员)+ 自签发 db_sk_ API Key(分组隔离)
  • 加密:Fernet(来自 cryptography)—— 用 KEYWAY_SECRET 的 SHA-256 派生密钥
  • 前端:零依赖原生 JS,由 FastAPI StaticFiles 提供服务

License

MIT — see LICENSE.

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MD5 faec3a1e36845a3c6fa2a31b90668c64
BLAKE2b-256 75f977008daa08248b5cdda3d704727c1f943b82ef64b0eb20c9a4bb18f0c4f9

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