llms-generator 0.1.0

Crawl any website and generate llms.txt — the AI-ready site map standard.

llms-generator

Crawl any website and generate llms.txt — the AI-ready site map standard.

llms.txt is a markdown file placed at a website's root (/llms.txt) that helps AI assistants like ChatGPT, Claude, and Perplexity understand your site's content structure. Think of it as robots.txt for AI.

This tool crawls your site, extracts page metadata, groups pages into logical sections, and outputs a spec-compliant llms.txt file.

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Why llms.txt?

AI systems struggle to navigate large, noisy websites. An llms.txt file gives them a curated map of your most important content — leading to:

• Accurate citations in AI-generated responses
• Better brand representation in ChatGPT, Perplexity, Google AI Overviews
• Less server load from AI crawlers wandering your site
• Control over how AI systems reference your content

The llms.txt specification was proposed by Jeremy Howard in 2024 and is actively supported by Perplexity, Anthropic, and other AI platforms.

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Installation

pip install llms-generator

For JavaScript-heavy sites (optional):

pip install llms-generator[js]
playwright install chromium

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Usage

llms-gen https://example.com

That's it. The tool crawls your site and creates llms.txt in the current directory.

Options

Flag	Default	Description
URL	required	Target website URL
--depth	2	Maximum crawl depth
--output	llms.txt	Output file path
--full	False	Also generate llms-full.txt with full page content
--no-js	False	Skip Playwright JavaScript rendering fallback
--delay	1.0	Seconds between requests (be polite)

Examples

# Basic crawl (2 levels deep)
llms-gen https://example.com

# Crawl deeper, output to custom path
llms-gen https://docs.example.com --depth 3 --output site-llms.txt

# Generate both standard and full versions
llms-gen https://example.com --full

# Fast crawl without JS rendering
llms-gen https://example.com --no-js --delay 0.5

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How it works

Per-page robot check

Every page is checked against three layers before being included or followed:

robots.txt ──┬── disallowed? → skip
             └── allowed? ──→ check HTTP X-Robots-Tag header
                                     │
                           noindex? ──→ skip
                           nofollow? ──→ still analyze, don't follow links
                                     │
                           absent ──→ check <meta name="robots">
                                     │
                           noindex? ──→ skip
                           nofollow? ──→ still analyze, don't follow links
                                     │
                           absent/index,follow ──→ analyze + follow links

Pages with noindex are excluded from llms.txt. Pages with nofollow are still analyzed for their content but their child links are not crawled.

Crawl strategy

1. Parse robots.txt — respect Disallow and Crawl-Delay
2. BFS from the start URL up to --depth levels
3. For each page:
   • Fetch with requests (handles most sites)
   • If content is empty (JS-rendered), fall back to Playwright headless browser
   • Extract: <title>, <h1>, <meta name="description">, first meaningful paragraph, directory path
4. Group pages into sections (directory-based, with H1 fallback)
5. Assemble llms.txt per the spec

Section grouping

Pages are grouped into ## sections by their top-level directory path:

/docs/getting-started   → ## Docs
/blog/hello-world       → ## Blog
/api/v1/users           → ## Api

Pages without a clear directory path use their <h1> as the section name.

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Output format

The generated llms.txt follows the llmstxt.org specification:

# Example Site

> A great example site with documentation and blog content.

This file provides AI systems with a structured summary of this website.

## Docs

- [Getting Started](https://example.com/docs/getting-started): How to get started with our platform.
- [API Reference](https://example.com/docs/api): Complete API documentation.

## Blog

- [Hello World](https://example.com/blog/hello): Our first blog post.

llms-full.txt

With --full, an expanded version is also generated that includes the full text content of each page inline — useful for providing complete context to LLMs in a single file.

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Development

git clone https://github.com/aouwalitshikkha/llms-generator.git
cd llms-generator
pip install -e .
pip install -e ".[js]"   # with Playwright support

Run tests:

pip install pytest
pytest

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License

MIT