npm install -g tingly-box@latest   # --registry=<mirror> works here too

tb start   # tb = tingly-box; runs in the background (--no-daemon for foreground)
tb open    # open the web UI

# update: reinstall, then restart to apply
npm install -g tingly-box@latest
tb restart

if any trouble, please check tingly-box output, or call for an issue to help.

# One command: fetch, restart the server in the background, migrate and open the web UI
# (a golang binary release; npx wraps the cli for convenience)
npx tingly-box@latest

# or -y for convenience
npx -y tingly-box@latest

# the binary for your platform comes from npm too (no GitHub download),
# so an npm mirror is all you need for CN (one of below)
npx --registry=https://registry.npmmirror.com -y tingly-box@latest
npx --registry=https://mirrors.huaweicloud.com/repository/npm/ -y tingly-box@latest
npx --registry=http://mirrors.tencent.com/npm/ -y tingly-box@latest

# MacOS & Linux
## Install Node.js LTS via nvm
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/master/install.sh | bash

## Restart terminal or load nvm
source ~/.nvm/nvm.sh

## Install Node.js LTS
nvm install --lts

## Verify installation
node -v
npx -v

# Windows
## Powershell with Winget
winget install OpenJS.NodeJS.LTS

## Restart terminal, then verify installation
node -v
npx -v

## Or download and install Node.js LTS manually:
https://nodejs.org/en/download

mkdir tingly-data
docker run -d \
  --name tingly-box \
  -p 12580:12580 \
  -v `pwd`/tingly-data:/home/tingly/.tingly-box \
  ghcr.io/tingly-dev/tingly-box

• Claude Code (support 1-click config)
• OpenCode (support 1-click config)
• Xcode (require manual config)
• ……

Any application is ready to use.

We've provided detailed config guide in application

Give your whole team one endpoint backed by centrally managed model rules. Each member gets a dedicated Team Key, and usage is tracked per user.

1. Open Web UI like http://localhost:12580
2. Navigate to Team, configure the model rules, then hand out keys via Team Keys
3. Track per-user consumption under Dashboard → Team usage

Route image generation and editing through the same gateway. Point any OpenAI-compatible image client at http://localhost:12580/tingly/imagegen and pick the upstream image models with rules, like any other scenario. Try prompts right away in Image → Playground.

DeepSeek is optimized for mainstream agent workflows, offering broad compatibility across protocol adapters, agent clients, extended context, vision, web search, and cache optimization.

Supports one-click configuration where available. For applications that require manual setup, detailed in-app configuration guides are provided.

Any compatible application is ready to use.

Detailed configuration guides are available inside each application.

Tingly Box now supports remote control through popular IM platforms. Interact with your AI agents remotely without direct server access.

Supported Platforms

• ✅ Telegram
• ✅ DingTalk
• ✅ Feishu
• ✅ Lark
• ✅ Weixin
• ✅ WeCom

Quick Setup

1. Open Web UI like http://localhost:12580
2. Navigate to Remote section
3. Configure your preferred IM platform bot
4. Start interacting with your agents remotely

Use Cases

• Execute tasks and queries from your phone or any device
• Team collaboration with shared agent access
• Monitor and control agents while away from your workstation

from openai import OpenAI

client = OpenAI(
    api_key="your-tingly-model-token",
    base_url="http://localhost:12580/tingly/openai/v1"
)

response = client.chat.completions.create(
    model="tingly-gpt",
    messages=[{"role": "user", "content": "Hello!"}]
)
print(response)

from anthropic import Anthropic

client = Anthropic(
    api_key="your-tingly-model-token",
    base_url="http://localhost:12580/tingly/anthropic"
)

response = client.messages.create(
    model="tingly",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response)

Tingly Box proxies requests transparently for SDKs and CLI tools.

You can also add OAuth providers (like Claude Code) and use your existing quota in any OpenAI-compatible tool:

# 1. Add Claude Code via OAuth in Web UI (http://localhost:12580)
# 2. Configure your tool with Tingly Box endpoint

Requests route through your OAuth-authorized provider, using your existing Claude Code quota instead of requiring a separate API key.

This works with any tool that supports OpenAI-compatible endpoints: Cherry Studio, VS Code extensions, or custom AI agents.

Already running your own inference server? Tingly Box connects to it like any other provider and exposes it through the same unified gateway.

Supported out of the box

• vLLM
• SGLang
• Ollama
• LM Studio
• LocalAI
• Jan

Anything else that speaks an OpenAI/Anthropic-compatible API still works via Custom endpoint.

Quick Setup

1. Open Web UI like http://localhost:12580
2. Click Connect AI → pick your engine from the Self-hosted section (default URL and key are pre-filled)
3. Test Connection, then save — it's now usable like any other provider

Launch the web management interface:

npx tingly-box@latest

Then open http://localhost:12580 in your browser.

Prerequisites

Tip: you can also copy individual shell commands out of Taskfile.yml and run them directly if you prefer not to install task.

1. Clone and init submodules

git clone https://github.com/tingly-dev/tingly-box.git
cd tingly-box
git submodule update --init --recursive

2. Frontend development

The frontend is a React + Vite app located in frontend/. You can work on it independently of the Go backend.

Login token: the frontend requires an auth token to log in. When the backend starts it prints the full login URL (e.g. Web UI: http://localhost:12580/login/<token>). If you need to retrieve it later, run:

tingly-box token view auth --reveal

Mock mode – no running backend required, uses built-in fixture data:

task web:mock
# or directly:
cd frontend && pnpm install && pnpm dev:mock

Open http://localhost:9245 in your browser. Use the token obtained above to log in.

Dev mode – proxies API calls to a local backend (start the backend first, see step 3):

task web
# or directly:
cd frontend && pnpm install && pnpm dev

3. Backend development

Run the Go server (hot-reload via go run):

task start
# or directly:
go run ./cli/tingly-box --verbose start --debug --port 12580 --browser=false

Open http://localhost:12580 in your browser (serves the last built frontend bundle).

4. Full build (frontend + backend binary)

Builds the frontend, embeds it into the binary, then compiles Go:

task build

The output binary is written to ./build/tingly-box.

5. GUI binary (Wails) (optional)

The GUI build is not yet publicly released. Skip this step unless you are specifically working on the desktop app.

task wails:build

Other useful commands

task swagger        # Regenerate openapi.json from Go source
task codegen        # Regenerate frontend API client from openapi.json
task go:test        # Run Go unit tests