agentsite 0.0.12

AI-Powered Website Builder using Prompture agent orchestration

AgentSite

An AI-powered website builder that uses multi-agent orchestration to generate complete, production-ready websites from a single text prompt. Nine specialized agents — four core and five specialists — collaborate to plan, design, build, and review your site.

PyPI Package: pypi.org/project/agentsite

---

Why This Tool?

Most AI website builders give you a single LLM call that dumps out a generic template. The result is usually a wall of code with no real structure, inconsistent styling, and no quality checks. You end up spending more time fixing the output than you saved by generating it.

AgentSite takes a different approach: nine specialized AI agents collaborate in a pipeline, each handling what they're best at. A PM agent plans the site structure and selects the build strategy. A Designer agent defines the visual system. In monolithic mode, a single Developer agent writes all the code; in specialist mode, dedicated Markup, Style, Script, and Image agents work in parallel for faster builds. A Reviewer agent evaluates quality and can send work back for revision — just like a real team would.

The entire pipeline is model-agnostic. You can use OpenAI, Claude, Google, Groq, Ollama, LM Studio, or any provider supported by Prompture. Swap models without changing anything else.

You get two ways to work: a full Web UI with live preview, chat input, and real-time progress tracking — or a CLI for generating sites directly from the terminal. Both produce the same output: clean, semantic HTML with proper accessibility baked in.

Under the hood, the pipeline enforces quality gates. The Reviewer agent scores every page against criteria like accessibility, semantic markup, and visual consistency. If the score is too low, the Developer gets feedback and iterates — up to two revision loops — before the site is finalized.

---

Table of Contents

• Quick Start
• How It Works
• Features
• CLI Reference
• Web UI
• Configuration
• Project Structure
• Tech Stack
• Development
• Troubleshooting
• Contributing

---

Quick Start

# 1. Install from PyPI
pip install agentsite

# 2. Set up your API keys
cp .env.copy .env
# Edit .env with your provider keys (OPENAI_API_KEY, CLAUDE_API_KEY, etc.)

# 3. Generate a website
agentsite generate "A portfolio website for a photographer"

That's it! A complete multi-page website will be generated in your output directory.

Prefer a UI? Launch the web interface instead:

agentsite serve
# Open http://127.0.0.1:6391

---

How It Works

AgentSite supports two build modes, chosen automatically by the PM agent based on site complexity:

Monolithic mode — a single Developer agent handles all code:

Prompt --> PM --> Designer --> Developer <--> Reviewer --> Website

Specialist mode — dedicated agents work in parallel for faster builds:

Prompt --> PM --> Designer --> Image -----> Reviewer --> Website
                              Markup --/
                              Style --/
                              Script -/

Core Agents

Agent	Role	Output
PM	Analyzes the prompt, plans site structure, selects build strategy and agents	SitePlan
Designer	Defines colors, typography, spacing, and the visual system	StyleSpec
Developer	Writes semantic HTML, CSS, and vanilla JS for each page (monolithic mode)	PageOutput
Reviewer	Evaluates quality, accessibility, and correctness (score >= 7 = approved)	ReviewFeedback

Specialist Agents

Agent	Role	Output
Markup	Writes HTML/JSX markup with semantic structure and ARIA labels	MarkupOutput
Style	Writes CSS or SCSS stylesheets with custom properties and responsive design	StyleOutput
Script	Writes vanilla JavaScript for interactivity and animations	ScriptOutput
Image	Generates images and manages the asset library	ImageOutput

The Reviewer can trigger revision loops, sending feedback back to the Developer or specialists until quality meets the approval threshold. This runs up to two iterations per page.

---

Features

Multi-Agent Pipeline

Nine agents with distinct personas coordinate through Prompture groups. Four core agents handle planning, design, development, and QA. Five specialist agents (Markup, Style, SCSS, Script, Image) can run in parallel for faster builds. Each agent has a focused role and structured output — no single monolithic prompt trying to do everything.

Real-Time Progress

WebSocket-based live updates during generation. Watch each agent work in real time through the Web UI with per-agent status, token usage, and timing.

Multi-Provider LLM Support

Use any model from any provider: OpenAI, Claude, Google, Groq, Grok, Ollama, LM Studio, OpenRouter, and more. Switch models per-generation without changing configuration.

Accessible Output

Agents enforce WCAG AA contrast, semantic HTML, ARIA labels, and keyboard navigation. Accessibility is built into the generation pipeline, not bolted on after.

Export

Download generated sites as ZIP archives or browse them directly through the built-in preview server.

---

CLI Reference

agentsite generate <prompt>       # Generate a website from a text prompt
  -m, --model <provider/model>    # LLM model to use (default: openai/gpt-4o)
  -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: 6391)
  --reload                        # Enable auto-reload for development

agentsite models                  # List available LLM models

---

Web UI

Launch the browser-based interface for a full visual experience:

agentsite serve

The Web UI includes:

• Dashboard — manage projects, create new sites
• Page Builder — chat-based generation with live preview
• Agent Monitoring — see each agent's status, metrics, and activity
• Analytics — token usage, cost breakdown, and generation history

For development, run the backend and frontend separately with hot-reload:

# Terminal 1: Backend
agentsite serve --reload

# Terminal 2: Frontend (Vite dev server)
cd frontend && npm run dev

---

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	6391

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      # All agent persona definitions (core + specialists)
    orchestrator.py  # Pipeline wiring, dynamic mode selection, parallel groups
    registry.py      # Centralized agent registry with auto-discovery
    specialists/     # Specialist agents (markup, style, script, image)
  api/               # FastAPI application
    routes/          # REST endpoints (projects, generate, models, assets, preview)
    websocket.py     # WebSocket manager for real-time progress
  engine/            # Core generation logic
    pipeline.py      # Orchestrates agents, handles file output and events
  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/            # React 19 + Vite 6 + Tailwind CSS 4 SPA
tests/               # pytest test suite

---

Tech Stack

Layer	Technology
Agent orchestration	Prompture
API server	FastAPI + Uvicorn
Database	SQLite via aiosqlite
CLI	Click
Config	Pydantic Settings
Frontend	React 19 + Vite 6 + Tailwind CSS 4
Linting	Ruff

---

Development

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

# Run tests
pytest

# Lint
ruff check .

# Format
ruff format .

# Build frontend
cd frontend && npm install && npm run build

---

Troubleshooting

Common Issues

Generation fails immediately?

• Check that your .env has valid API keys for the provider you're using
• Run agentsite models to verify your provider is reachable

Empty or broken output?

• Try a different model — some smaller models struggle with structured output
• Check the Reviewer feedback in the Web UI for specific issues

Frontend not loading?

• Make sure you've built the frontend: cd frontend && npm run build
• For development, run npm run dev separately on port 5173

WebSocket disconnects?

• The generation is still running server-side — refresh the page to reconnect
• Check the terminal output for any backend errors

---

Contributing

Contributions welcome! Here's how:

1. Report bugs — GitHub Issues
2. Improve docs — PRs for documentation improvements
3. Submit PRs — Bug fixes and features
4. Add providers — Extend LLM provider support via Prompture

---

License

This project is licensed under the MIT License. See the LICENSE file for full details.

---

Get Help

• PyPI Package — pypi.org/project/agentsite
• Issues — GitHub Issues
• Prompture — pypi.org/project/prompture

---

Built by Juan Denis