Gambit is an open-source, developer-first framework that helps you build
reliable LLM workflows by composing small, typed “decks”
with clear inputs/outputs and guardrails. Run decks locally, stream traces, and
debug with a built-in UI.

Watch the demo video.

Quickstart

Requirements: Node.js 18+ and OPENROUTER_API_KEY (set OPENROUTER_BASE_URL if you proxy OpenRouter-style APIs).

Run the CLI directly with npx (no install):

export OPENROUTER_API_KEY=...
npx @bolt-foundry/gambit demo

Downloads example files (hello decks plus the examples/ gallery) and sets environment variables.

To scaffold a starter project that you can customize, run:

npx @bolt-foundry/gambit init my-project

This creates a structured skeleton (decks/, actions/, graders/, tests/, schemas/, .gambit/) with README guides so you can start authoring your own workflows immediately.

Run an example in the terminal (repl):

npx @bolt-foundry/gambit repl gambit/hello.deck.md

This example just says "hello" and repeats your message back to you.

Run an example in the browser (serve):

npx @bolt-foundry/gambit serve gambit/hello.deck.md
open http://localhost:8000/debug

---

Status quo

• Most teams wire one long prompt to several tools and hope the model routes
  correctly.
• Context often arrives as a single giant fetch or RAG blob, so costs climb and
  hallucinations slip in.
• Input/outputs are rarely typed, which makes orchestration brittle and hard to
  test offline.
• Debugging leans on provider logs instead of local traces, so reproducing
  failures is slow.

Our vision

• Treat each step as a small deck with explicit inputs/outputs and guardrails;
  model calls are just one kind of action.
• Mix LLM and compute tasks interchangeably and effortlessly inside the same
  deck tree.
• Feed models only what they need per step; inject references and cards instead
  of dumping every document.
• Keep orchestration logic local and testable; run decks offline with
  predictable traces.
• Ship with built-in observability (streaming, REPL, debug UI) so debugging
  feels like regular software, not guesswork.

---

Using the CLI

Use the CLI to run decks locally, stream output, and capture traces/state.

Run with npx (no install):

npx @bolt-foundry/gambit <command>

Run a deck once:

npx @bolt-foundry/gambit run <deck> --context <json|string> --message <json|string>

--context replaces the old --init flag. The CLI still accepts --init as a deprecated alias for now so existing scripts keep working.

Drop into a REPL (streams by default):

npx @bolt-foundry/gambit repl <deck>

Run a persona against a root deck (test bot):

npx @bolt-foundry/gambit test-bot <root-deck> --test-deck <persona-deck>

Grade a saved session:

npx @bolt-foundry/gambit grade <grader-deck> --state <file>

Start the Debug UI server:

npx @bolt-foundry/gambit serve <deck> --port 8000

Tracing and state: 

--trace <file> for JSONL traces
--verbose to print events
--state <file> to persist a session.

Using the Simulator

The simulator is the local Debug UI that streams runs and renders traces.

Run with npx (no install):

npx @bolt-foundry/gambit <command>

Start it:

npx @bolt-foundry/gambit serve <deck> --port 8000

Then open:

http://localhost:8000/

It also serves:

http://localhost:8000/test
http://localhost:8000/grade

The Debug UI shows transcript lanes plus a trace/tools feed. If the deck has an
contextSchema, the UI renders a schema-driven form with defaults and a raw JSON
tab. Local-first state is stored under .gambit/ (sessions, traces, notes).

Using the Library

Use the library when you want TypeScript decks/cards or custom compute steps.

Import the helpers from JSR:

import { defineDeck, defineCard } from "jsr:@bolt-foundry/gambit";

Define contextSchema/responseSchema with Zod to validate IO, and implement
run/execute for compute decks. To call a child deck from code, use
ctx.spawnAndWait({ path, input }). Emit structured trace events with
ctx.log(...).

---

Author your first deck

Minimal Markdown deck (model-powered): hello_world.deck.md

+++
label = "hello_world"

[modelParams]
model = "openai/gpt-4o-mini"
temperature = 0
+++

You are a concise assistant. Greet the user and echo the input.

Run it:

npx @bolt-foundry/gambit run ./hello_world.deck.md --context '"Gambit"' --stream

Compute deck in TypeScript (no model call): echo.deck.ts

// echo.deck.ts
import { defineDeck } from "jsr:@bolt-foundry/gambit";
import { z } from "zod";

export default defineDeck({
  label: "echo",
  contextSchema: z.object({ text: z.string() }),
  responseSchema: z.object({ text: z.string(), length: z.number() }),
  run(ctx) {
    return { text: ctx.input.text, length: ctx.input.text.length };
  },
});

Run it:

npx @bolt-foundry/gambit run ./echo.deck.ts --context '{"text":"ping"}'

Deck with a child action (calls a TypeScript tool): agent_with_time.deck.md

+++
label = "agent_with_time"
modelParams = { model = "openai/gpt-4o-mini", temperature = 0 }
[[actionDecks]]
name = "get_time"
path = "./get_time.deck.ts"
description = "Return the current ISO timestamp."
+++

A tiny agent that calls get_time, then replies with the timestamp and the input.

And the child action: get_time.deck.ts

// get_time.deck.ts
import { defineDeck } from "jsr:@bolt-foundry/gambit";
import { z } from "zod";

export default defineDeck({
  label: "get_time",
  contextSchema: z.object({}), // no args
  responseSchema: z.object({ iso: z.string() }),
  run() {
    return { iso: new Date().toISOString() };
  },
});

Run it:

npx @bolt-foundry/gambit run ./agent_with_time.deck.md --context '"hello"' --stream

Respond flow demo (non-root decks + grading)

Need a turnkey scenario that hits personas → init → non-root gambit_respond payloads → graders? Use the example in packages/gambit/examples/respond_flow/.

cd packages/gambit
npx @bolt-foundry/gambit serve ./examples/respond_flow/decks/root.deck.ts --port 8000

Then:

1. Open http://localhost:8000/test, pick the Escalation persona, and run it. Leave the “Use test deck input for init” toggle on to see persona data seed the init form automatically.
2. Switch to the Debug tab to inspect the session—the child deck emits a gambit_respond payload that now shows up as a structured assistant turn.
3. Head to the Calibrate tab and run the Respond payload grader to exercise grading on the non-root respond output.

Deno

If you prefer Deno, use the Deno commands below.

Quickstart:

export OPENROUTER_API_KEY=...
deno run -A jsr:@bolt-foundry/gambit/cli demo

Starter project:

deno run -A jsr:@bolt-foundry/gambit/cli init my-project

Run a deck:

deno run -A jsr:@bolt-foundry/gambit/cli run <deck> --context <json|string> --message <json|string>

Start the Debug UI:

deno run -A jsr:@bolt-foundry/gambit/cli serve <deck> --port 8000