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Gambi - LLM Club

Share local LLMs across your network, effortlessly.

Gambi is short for gambiarra: a Brazilian Portuguese idea of creative improvisation under constraints.

Install
curl (recommended)
npm
bun
Features
[ ]

Local-First

Your data stays on your network. No cloud dependencies, no external APIs.

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Resource Sharing

Pool LLM endpoints across your team. Share expensive GPU resources efficiently.

[+]

Universal

Works with Ollama, LM Studio, LocalAI, vLLM, and any endpoint exposing OpenResponses or chat/completions.

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AI SDK Ready

Drop-in replacement for Vercel AI SDK workflows. Same API, shared resources.

How It Works
┌─────────────────────────────────────────────────────────────┐
│                       GAMBI HUB (HTTP)                  │
│                                                             │
│  Your LLM Pool:                                             │
│  ┌────────────────────────────────────────────────────┐    │
│  │ joao  → Ollama llama3    @ 192.168.1.50:11434      │    │
│  │ maria → LM Studio mistral @ 192.168.1.51:1234      │    │
│  │ pedro → vLLM qwen        @ 192.168.1.52:8000       │    │
│  └────────────────────────────────────────────────────┘    │
└─────────────────────────────────────────────────────────────┘
       ▲                    ▲                      ▲
       │ HTTP               │ HTTP                 │ SSE
       │                    │                      │
  ┌────┴────┐    ┌─────────┴────────┐      ┌──────┴─────┐
  │   SDK   │    │  Participants    │      │    TUI     │
  └─────────┘    └──────────────────┘      └────────────┘
      
1 Start the hub with gambi serve
2 Create a room with gambi create
3 Join with your LLM endpoint
4 Use the SDK in your apps
Use Cases

Dev Teams

Share expensive LLM endpoints across your team

Hackathons

Pool resources for AI projects in 24-48h events

Research Labs

Coordinate LLM access across workstations

Home Labs

Share your gaming PC's LLM with your laptop

Education

Classroom environments where students share compute

SDK Example
import { createGambi } from "gambi-sdk";
import { generateText } from "ai";

const gambi = createGambi({
  roomCode: "ABC123",
  hubUrl: "http://localhost:3000",
});

// Use any available participant
const result = await generateText({
  model: gambi.any(),
  prompt: "Hello, Gambi!",
});

// Explicit chat completions mode is still available
const legacy = createGambi({
  roomCode: "ABC123",
  defaultProtocol: "chatCompletions",
});

console.log(result.text);