penguin-harness/packages/docs/content/quickstart.en.md

title, description

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Quickstart	Install PenguinHarness, configure a model, and run your first Task.

Install

One-liner for Linux / macOS:

curl -fsSL https://penguin.ooo/install.sh | sh

For other options (npm, from source), see Installation.

Configure a model

PenguinHarness ships with no built-in model credentials, so configure a model first. Use the Models page in the Web UI, or the CLI:

penguin config model add --provider deepseek --model-id deepseek-v4-flash --api-key sk-... --set-default

• A model is always referenced as a (provider, model_id) pair, so --provider and --model-id are both required — the Provider is never inferred from the model id. See Models & Providers for the built-in groups.
• The API key can also come from environment variables: when a model entry has no inline api_key, AgentHub (the LLM gateway library) reads variables such as DEEPSEEK_API_KEY, ANTHROPIC_API_KEY, OPENAI_API_KEY, and GEMINI_API_KEY. A .env file in the working directory is loaded automatically.

Start the Web App

penguin web

The service runs at http://127.0.0.1:7364 and opens your browser (--no-open to skip). First login is admin / penguin-2026 — change it right away. penguin server starts the same process headless.

One-shot run

penguin run -m "Create hello.txt containing Hello, Penguin"

The Workspace defaults to the current directory; pass --workspace /path to change it. The target directory must already exist.

Interactive chat

penguin chat

• Each input line starts a Task.
• /compact compacts the context; /exit or /quit quits; Ctrl-C interrupts the running Task.
• On exit it prints a penguin chat --resume <sessionId> hint for resuming this Session; --resume without an id resumes the Agent's latest Session.

SDK hello

After installing @prismshadow/penguin-core:

import { createAgent, isCompleteModelMessage, userText } from "@prismshadow/penguin-core";

const agent = await createAgent({ agentId: "default_agent" });
const session = await agent.createSession({ workspaceDir: process.cwd() });

for await (const output of session.run([userText("Create hello.txt containing hi")], {
  approve: async () => "allow",
})) {
  if (isCompleteModelMessage(output) && output.payload.type === "text") {
    console.log(output.payload.text);
  }
}

Next steps

• Web App Guide: use PenguinHarness from the browser.
• CLI Reference: the full list of commands and options.
• Architecture Overview: how the pieces fit together.