agentsite 0.1.0

AI-Powered Website Builder using Prompture agent orchestration

AgentSite

AI-Powered Website Builder using Multi-Agent Orchestration

Generate complete, production-ready websites from a single text prompt.
Four specialized AI agents collaborate to plan, design, build, and review your site.

---

How It Works

Prompt ──> PM Agent ──> Designer Agent ──> Developer Agent ──> Reviewer Agent ──> Website
           (plan)       (style)           (code)              (QA)

Agent	Role	Output
PM	Analyzes prompt, plans site structure and build order	SitePlan
Designer	Defines colors, typography, spacing, and visual system	StyleSpec
Developer	Writes semantic HTML, CSS, and vanilla JS for each page	PageOutput
Reviewer	Evaluates quality, accessibility, and correctness	ReviewFeedback

The reviewer can trigger revision loops, sending feedback back to the developer until quality meets the approval threshold.

Features

• Multi-agent pipeline — four agents with distinct personas coordinate through Prompture groups
• Real-time progress — WebSocket-based live updates during generation
• Web UI — browser interface with live preview, chat input, style controls, and usage dashboard
• CLI — generate sites directly from the terminal
• Multi-provider LLM support — OpenAI, Claude, Google, Groq, Grok, Ollama, LM Studio, OpenRouter, and more
• Export — download generated sites as ZIP archives
• Accessible output — agents enforce WCAG AA contrast, semantic HTML, ARIA labels, and keyboard navigation

Quick Start

Installation

pip install -e ".[dev]"

Configuration

cp .env.copy .env
# Edit .env with your API keys

Generate from the CLI

agentsite generate "A portfolio website for a photographer"

Start the Web UI

agentsite serve
# Open http://127.0.0.1:8000

CLI Reference

agentsite generate <prompt>       # Generate a website from a text prompt
  -m, --model <provider/model>    # LLM model to use (default: from settings)
  -o, --output <dir>              # Output directory
  -n, --name <name>               # Project name

agentsite serve                   # Start the web UI server
  --host <host>                   # Server host (default: 127.0.0.1)
  --port <port>                   # Server port (default: 8000)
  --reload                        # Enable auto-reload for development

agentsite models                  # List available LLM models

Configuration

Variable	Description	Default
AGENTSITE_DEFAULT_MODEL	LLM model for all agents	openai/gpt-4o
AGENTSITE_DATA_DIR	Project storage directory	~/.agentsite
AGENTSITE_HOST	Server bind address	127.0.0.1
AGENTSITE_PORT	Server port	8000

Provider API keys (OPENAI_API_KEY, CLAUDE_API_KEY, GOOGLE_API_KEY, etc.) are inherited from Prompture's configuration.

Project Structure

agentsite/
  agents/            # Agent factories, Prompture Personas, orchestration
    personas.py      # PM, Designer, Developer, Reviewer persona definitions
    orchestrator.py  # Pipeline wiring and group configuration
  api/               # FastAPI application
    routes/          # REST endpoints (projects, generate, models, assets, preview)
    websocket.py     # WebSocket manager for real-time progress
    app.py           # Application factory with CORS and lifespan
  engine/            # Core generation logic
    pipeline.py      # Orchestrates agents, handles file output and events
    project_manager.py  # Filesystem operations for project directories
    asset_handler.py    # Image upload and asset management
  storage/           # Persistence layer
    database.py      # Async SQLite via aiosqlite
    repository.py    # CRUD operations for projects and generations
  cli.py             # Click CLI entry point
  config.py          # Pydantic-settings (env vars, defaults)
  models.py          # Domain models (SitePlan, StyleSpec, PageOutput, etc.)
frontend/            # Browser UI (vanilla JS, no build step)
tests/               # pytest test suite

Tech Stack

Layer	Technology
Agent orchestration	Prompture (Agents, Personas, Groups)
API server	FastAPI + Uvicorn
Database	SQLite via aiosqlite
CLI	Click
Config	Pydantic Settings
Frontend	Vanilla JavaScript (no framework, no build step)
Linting	Ruff

Development

# Install with dev + test extras
pip install -e ".[dev]"

# Run tests
pytest

# Run tests with verbose output
pytest -v

# Lint
ruff check .

# Format
ruff format .

License

MIT

---

Built by Juan Denis