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Control panel for VLLM, Sglang, llama.cpp, exllamav3
| Date | Stars |
|---|---|
| 2026-07-24 | 1493 |
| 2026-07-25 | 1497 |
| 2026-07-28 | 1515 |
| 2026-07-30 | 1515 |
| 2026-08-06 | 1515 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
35.0
growth rate 0.00%/day
# Local Studio
Local Studio is a local-first workstation for running, managing, and using
self-hosted LLM backends. One machine can launch models, watch GPU/runtime
state, chat with OpenAI-compatible endpoints, and run agent sessions against
local or remote controllers. Version 2.0 unifies day-to-day operation around
Status, Workbench, Configure, and Usage instead of separate model, integration,
and server surfaces.
It is built from two modules that share one controller API:
- [`controller/`](controller/README.md) — Bun/Hono backend. Owns model lifecycle
(launch, evict, recipes, downloads, runtime process coordination), an
OpenAI-compatible proxy (chat, models, tokenization, audio), system state
(GPU metrics, logs, usage, settings, SSE), and controller integrations.
- [`frontend/`](frontend/README.md) — Next.js 16 + React 19 UI and the macOS
Electron desktop shell. Hosts the Workbench (`/agent`), consolidated
Configure surface, settings, usage, logs, and browser-facing API routes.
## What is a controller?
A controller is the backend process the UI talks to — the Bun/Hono
server in `controller/`. You can run one locally or point the frontend at a
remote controller on a GPU host. The controller owns model lifecycle, the
OpenAI-compatible proxy, system state, and SSE event streams.
## Architecture
```mermaid
flowchart LR
User["User"] --> Desktop["Electron desktop app"]
User --> Web["Next.js web UI"]
Desktop --> Frontend["Frontend server / API routes"]
Web --> Frontend
Frontend --> Controller["Controller API (Bun + Hono)"]
Controller --> Runtime["Inference runtime process"]
Runtime --> Backends["vLLM / SGLang / llama.cpp / MLX recipes"]
Controller --> Data["Local data directory"]
Controller --> Events["SSE status and runtime events"]
Frontend --> Agent["Pi coding agent runtime"]
```
```mermaid
flowchart TB
subgraph Frontend["frontend/"]
AgentPage["/agent"]
Configure["/configure"]
Settings["/settings"]
Usage["/usage"]
ProxyRoutes["/api/* proxy and agent routes"]
DesktopMain["desktop/ Electron shell"]
end
subgraph Controller["controller/"]
HttpApp["src/http/app.ts"]
Engines["src/modules/engines"]
Models["src/modules/models"]
Proxy["src/modules/proxy"]
Studio["src/modules/studio"]
System["src/modules/system"]
Audio["src/modules/audio"]
Stores["src/stores"]
end
ProxyRoutes --> HttpApp
HttpApp --> Engines
HttpApp --> Models
HttpApp --> Proxy
HttpApp --> Studio
HttpApp --> System
HttpApp --> Audio
System --> Stores
```
## Quick start
Prerequisites: Bun 1.x (controller), Node.js 22.19+ and npm (frontend),
Python 3.10+ on `PATH` (`uv` strongly recommended; engine installs fall back to
pip), Git. vLLM/SGLang serving on Linux needs NVIDIA driver + CUDA; Apple
Silicon uses the MLX backend.
Run the preflight check first (toolchain, ports, directories, network):
```bash
npm run doctor
```
Start the controller (listens on `127.0.0.1:8080`, data dir + SQLite created
automatically, model weights in `LOCAL_STUDIO_MODELS_DIR`, default `/models`):
```bash
cd controller && bun install && bun src/main.ts
```
Start the frontend in a second terminal, then open
<http://localhost:3000/setup>:
```bash
cd frontend && npm ci && npm run dev
```
`npm ci` runs a postinstall patch against `@earendil-works/pi-ai`. If that step
prints a warning, agent streaming may misrender. The setup wizard walks through
choosing a models directory, installing an engine, downloading a model,
launching it, and benchmarking. Engine installs (vLLM/SGLang/MLX) land in
`<data dir>/runtime/venvs/<backend>-latest`.
## Agent runtime
The agent surface lives at `/agent` in the frontend. It uses
`@earendil-works/pi-coding-agent` through the frontend runtime rather than
shelling out to a separate agent process for normal turns. Agent skills and
extensions are disExcerpt of 10,535 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:09df61c10a1dd754, topic:vllm, topic:llamacpp
