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Introduction

The llms.txt file spec is for files located in the path llms.txt of a website (or, optionally, in a subpath). llms-sample.txt is a simple example. A file following the spec contains the following sections as markdown, in the specific order:

An H1 with the name of the project or site. This is the only required section
A blockquote with a short summary of the project, containing key information necessary for understanding the rest of the file
Zero or more markdown sections (e.g. paragraphs, lists, etc) of any type, except headings, containing more detailed information about the project and how to interpret the provided files
Zero or more markdown sections delimited by H2 headers, containing “file lists” of URLs where further detail is available
- Each “file list” is a markdown list, containing a required markdown hyperlink [name](url), then optionally a : and notes about the file.

Here’s the start of a sample llms.txt file we’ll use for testing:

samp = Path('llms-sample.txt').read_text()
print(samp[:480])

# FastHTML

> FastHTML is a python library which brings together Starlette, Uvicorn, HTMX, and fastcore's `FT` "FastTags" into a library for creating server-rendered hypermedia applications.

Remember:

- Use `serve()` for running uvicorn (`if __name__ == "__main__"` is not needed since it's automatic)
- When a title is needed with a response, use `Titled`; note that that already wraps children in `Container`, and already includes both the meta title as well as the H1 element

Reading

We’ll implement parse_llms_file to pull out the sections of llms.txt into a simple data structure.

search

def search(
    pat, txt, flags:int=0
):

Dictionary of matched groups in pat within txt

named_re

def named_re(
    nm, pat
):

Pattern to match pat in a named capture group

opt_re

def opt_re(
    s
):

Pattern to optionally match s

We’ll work “outside in” so we can test the innermost matches as we go.

Parse links

link = '- [FastHTML quick start](https://fastht.ml/docs/tutorials/quickstart_for_web_devs.html.md): A brief overview of FastHTML features'

title = named_re('title', r'[^\]]+')
pat =  fr'-\s*\[{title}\]'
search(pat, samp)

{'title': 'FastHTML quick start'}

url = named_re('url', r'[^\)]+')
pat += fr'\({url}\)'
search(pat, samp)

{'title': 'FastHTML quick start',
 'url': 'https://fastht.ml/docs/tutorials/quickstart_for_web_devs.html.md'}

desc = named_re('desc', r'.*')
pat += opt_re(fr':\s*{desc}')
search(pat, link)

{'title': 'FastHTML quick start',
 'url': 'https://fastht.ml/docs/tutorials/quickstart_for_web_devs.html.md',
 'desc': 'A brief overview of FastHTML features'}

parse_link

def parse_link(
    txt
):

Parse a link section from llms.txt

parse_link(link)

{'title': 'FastHTML quick start',
 'url': 'https://fastht.ml/docs/tutorials/quickstart_for_web_devs.html.md',
 'desc': 'A brief overview of FastHTML features'}

parse_link('-[foo](http://foo)')

{'title': 'foo', 'url': 'http://foo', 'desc': None}

Parse sections

sections = '''First bit.

## S1

-[foo](http://foo)
- [foo2](http://foo2): stuff

## S2

- [foo3](http://foo3)'''

start,*rest = re.split(fr'^##\s*(.*?$)', sections, flags=re.MULTILINE)
start

'First bit.\n\n'

rest

['S1',
 '\n\n-[foo](http://foo)\n- [foo2](http://foo2): stuff\n\n',
 'S2',
 '\n\n- [foo3](http://foo3)']

d = dict(chunked(rest, 2))
d

{'S1': '\n\n-[foo](http://foo)\n- [foo2](http://foo2): stuff\n\n',
 'S2': '\n\n- [foo3](http://foo3)'}

links = d['S1']
links.strip()

'-[foo](http://foo)\n- [foo2](http://foo2): stuff'

_parse_links(links)

[{'title': 'foo', 'url': 'http://foo', 'desc': None},
 {'title': 'foo2', 'url': 'http://foo2', 'desc': 'stuff'}]

start, sects = _parse_llms(samp)
start

'# FastHTML\n\n> FastHTML is a python library which brings together Starlette, Uvicorn, HTMX, and fastcore\'s `FT` "FastTags" into a library for creating server-rendered hypermedia applications.\n\nRemember:\n\n- Use `serve()` for running uvicorn (`if __name__ == "__main__"` is not needed since it\'s automatic)\n- When a title is needed with a response, use `Titled`; note that that already wraps children in `Container`, and already includes both the meta title as well as the H1 element.'

title = named_re('title', r'.+?$')
summ = named_re('summary', '.+?$')
summ_pat = opt_re(fr"^>\s*{summ}$")
info = named_re('info', '.*')

pat = fr'^#\s*{title}\n+{summ_pat}\n+{info}'
search(pat, start, (re.MULTILINE|re.DOTALL))

{'title': 'FastHTML',
 'summary': 'FastHTML is a python library which brings together Starlette, Uvicorn, HTMX, and fastcore\'s `FT` "FastTags" into a library for creating server-rendered hypermedia applications.',
 'info': 'Remember:\n\n- Use `serve()` for running uvicorn (`if __name__ == "__main__"` is not needed since it\'s automatic)\n- When a title is needed with a response, use `Titled`; note that that already wraps children in `Container`, and already includes both the meta title as well as the H1 element.'}

parse_llms_file

def parse_llms_file(
    txt
):

Parse llms.txt file contents in txt to an AttrDict

llmsd = parse_llms_file(samp)
llmsd.summary

'FastHTML is a python library which brings together Starlette, Uvicorn, HTMX, and fastcore\'s `FT` "FastTags" into a library for creating server-rendered hypermedia applications.'

llmsd.sections.Examples

[{'title': 'Todo list application', 'url': 'https://raw.githubusercontent.com/AnswerDotAI/fasthtml/main/examples/adv_app.py', 'desc': 'Detailed walk-thru of a complete CRUD app in FastHTML showing idiomatic use of FastHTML and HTMX patterns.'}]

XML conversion

For some LLMs such as Claude, XML format is preferred, so we’ll provide a function to create that format.

get_doc_content

def get_doc_content(
    url
):

Fetch content from local file if in nbdev repo.

mk_ctx

def mk_ctx(
    d, optional:bool=True, n_workers:NoneType=None
):

Create a Project with a Section for each H2 part in d, optionally skipping the ‘optional’ section.

ctx = mk_ctx(llmsd)
print(to_xml(ctx, do_escape=False)[:260]+'...')

{'title': 'FastHTML quick start', 'url': 'https://fastht.ml/docs/tutorials/quickstart_for_web_devs.html.md', 'desc': 'A brief overview of FastHTML features'}{'title': 'HTMX reference', 'url': 'https://raw.githubusercontent.com/bigskysoftware/htmx/master/www/content/reference.md', 'desc': 'Brief description of all HTMX attributes, CSS classes, headers, events, extensions, js lib methods, and config options'}

{'title': 'Starlette quick guide', 'url': 'https://gist.githubusercontent.com/jph00/e91192e9bdc1640f5421ce3c904f2efb/raw/61a2774912414029edaf1a55b506f0e283b93c46/starlette-quick.md', 'desc': {}}
{'title': 'Todo list application', 'url': 'https://raw.githubusercontent.com/AnswerDotAI/fasthtml/main/examples/adv_app.py', 'desc': 'Detailed walk-thru of a complete CRUD app in FastHTML showing idiomatic use of FastHTML and HTMX patterns.'}
{'title': 'Starlette full documentation', 'url': 'https://gist.githubusercontent.com/jph00/809e4a4808d4510be0e3dc9565e9cbd3/raw/9b717589ca44cedc8aaf00b2b8cacef922964c0f/starlette-sml.md', 'desc': 'A subset of the Starlette documentation useful for FastHTML development.'}
<project title="FastHTML" summary='FastHTML is a python library which brings together Starlette, Uvicorn, HTMX, and fastcore&#39;s `FT` "FastTags" into a library for creating server-rendered hypermedia applications.'>Remember:

- Use `serve()` for running uvic...

get_sizes

def get_sizes(
    ctx
):

Get the size of each section of the LLM context

get_sizes(ctx)

{'docs': {'FastHTML quick start': 35321,
  'HTMX reference': 28365,
  'Starlette quick guide': 7936},
 'examples': {'Todo list application': 16032},
 'optional': {'Starlette full documentation': 48331}}

Path('../fasthtml.md').write_text(to_xml(ctx, do_escape=False))

create_ctx

def create_ctx(
    txt, optional:bool=False, n_workers:NoneType=None
):

A Project with a Section for each H2 part in txt, optionally skipping the ‘optional’ section.

llms_txt2ctx

def llms_txt2ctx(
    fname:str, # File name to read
    optional:bool_arg=False, # Include 'optional' section?
    n_workers:int=None, # Number of threads to use for parallel downloading
    save_nbdev_fname:str=None, # save output to nbdev `{docs_path}` instead of emitting to stdout
):

Print a Project with a Section for each H2 part in file read from fname, optionally skipping the ‘optional’ section.

!llms_txt2ctx llms-sample.txt > ../fasthtml.md

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