Jacpacks - Project Templates for Jac

Jacpacks are self-contained project templates that bundle everything you need to scaffold a full Jac application. Each .jacpack file is a portable archive containing source code, configuration, and setup hooks -- use them with jac create to spin up a working project in seconds.

This directory contains a collection of ready-to-use jacpacks showcasing different capabilities of the Jac ecosystem.

Prerequisites

Before using any jacpack, make sure you have the following installed:

• Python 3.12+
• Node.js 18+ with npm (for jacpacks that include a frontend)
• Jac -- install the full ecosystem bundle:

pip install jaseci

This installs jaclang along with all official plugins (byllm, jac-client, jac-scale, jac-super).

If you only need the language runtime:

pip install jaclang

Verify your installation:

jac version

IDE Setup

Install the Jac extension for VS Code (also works in Cursor) for syntax highlighting, diagnostics, and language server support.

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Quick Start

Every jacpack follows the same workflow:

# 1. Create a new project from a jacpack
jac create my-app --use <template>

# 2. Move into the project directory
cd my-app

# 3. Install dependencies
jac add

# 4. Set any required environment variables (see each jacpack's section below)

# 5. Start the application
jac start main.jac

The server runs at http://localhost:8000 by default.

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Available Jacpacks

AI Study Helper

An intelligent study companion that transforms text into structured educational material using specialized AI agents.

jac create my-study-app --use AI_Study_Helper.jacpack
cd my-study-app && jac add

Required environment variables:

export GEMINI_API_KEY=your_gemini_api_key
export TAVILY_API_KEY=your_tavily_api_key

Features:

• Agent-based architecture with dedicated Quiz, Summarizer, Explanation, and Flashcard agents
• Interactive assessment with multiple-choice question generation and progress tracking
• Web search integration via Tavily for real-time information retrieval
• Four-panel study workspace (quiz, summarize, explain, flashcards)

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TasteTalk

A restaurant feedback management system that collects, analyzes, and responds to customer feedback with AI-powered insights.

jac create my-tastetalk --use TasteTalk.jacpack
cd my-tastetalk && jac add

Required environment variables:

export GEMINI_API_KEY=your_gemini_api_key

Features:

• Customer portal for submitting feedback with AI-generated responses
• Admin dashboard with sentiment distribution charts, category tracking, and AI summaries
• Multi-language support (Sinhala/Tamil)
• Persistent storage with SQLite-backed TieredMemory
• Graph database backend via Jac-Scale

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Algo

A voice-enabled personal AI assistant with calendar, email, and GitHub integration.

jac create my-algo --use Algo.jacpack
cd my-algo && jac add

Required environment variables:

export OPENAI_API_KEY=your_openai_api_key

Features:

• Voice interface powered by OpenAI Realtime API
• Calendar and email management
• GitHub issue tracking integration
• Real-time task graph visualization
• Complete authentication system (register, login, protected routes)

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Jac Playground

An interactive browser-based code editor and runner for Jac. Runs entirely client-side using WebAssembly and Pyodide -- no backend required.

jac create my-playground --use jacplayground.jacpack
cd my-playground && jac add --npm
jac start

Features:

• Monaco editor with Jac syntax highlighting
• Real-time in-browser code execution via Pyodide
• Interactive graph visualizer for Jac data structures
• Bidirectional Jac/Python code conversion
• Debugging tools with breakpoint support
• Built-in example library
• Dark/light mode and mobile-responsive layout

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Jac GPT

A documentation assistant for the Jac language, built as a fullstack Jac application.

jac create my-jac-gpt --use jac-gpt.jacpack
cd my-jac-gpt && jac add

Required environment variables:

export OPENAI_API_KEY=your_openai_api_key

Features:

• Conversational interface for querying Jac documentation
• MongoDB-backed data persistence

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Jacpack CLI Reference

Listing available templates

# List all registered templates (from installed plugins and local files)
jac create --list-jacpacks

# Or use the jacpack subcommand
jac jacpack list

Inspecting a jacpack

jac jacpack info AI_Study_Helper.jacpack

Creating a project

Templates can be referenced by registered name, local file path, or URL:

# From a registered template name
jac create my-app --use client

# From a local .jacpack file
jac create my-app --use ./path/to/template.jacpack

# From a template directory (must contain a jac.toml with a [jacpack] section)
jac create my-app --use ./my-template-dir/

# From a remote URL
jac create my-app --use https://example.com/template.jacpack

Managing dependencies

# Install all dependencies defined in jac.toml
jac add

# Add a Python package
jac add requests

# Add an npm package (requires jac-client plugin)
jac add react --npm

# Install dependencies without adding new ones
jac install

Running a project

# Run a Jac file directly
jac run main.jac

# Start a server (for fullstack apps)
jac start main.jac

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Creating Your Own Jacpack

You can bundle any Jac project into a distributable jacpack.

1. Add a [jacpack] section to your jac.toml

[project]
name = "{{name}}"
version = "0.1.0"
entry-point = "main.jac"

[dependencies]
requests = ">=2.28.0"

[jacpack]
name = "my-template"
description = "A brief description of what this template provides"
jaclang = "0.9.0"

Use {{name}} as a placeholder in your jac.toml and source files -- it gets replaced with the project name during jac create.

2. Bundle it

jac jacpack pack ./my-template-dir

This produces a my-template.jacpack file.

3. Share it

Others can use your jacpack directly:

jac create cool-project --use ./my-template.jacpack

Or host it at a URL for remote access:

jac create cool-project --use https://example.com/my-template.jacpack

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Project Structure

A typical Jac project created from a jacpack looks like this:

my-app/
├── jac.toml          # Project config and dependencies
├── main.jac          # Application entry point
├── *.jac             # Additional Jac source files
├── .jac/             # Managed directory (venv, client builds, etc.)
│   └── venv/         # Isolated Python virtual environment
└── .gitignore

The .jac/ directory is auto-managed -- it holds the project's virtual environment and any plugin-generated artifacts (like client-side builds). It should be gitignored.

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Useful Links

• Jac Documentation
• CLI Reference
• GitHub Repository
• VS Code Extension