File size: 2,537 Bytes
caea4d0
3949b67
caea4d0
 
 
 
 
 
 
 
 
 
 
 
64ad522
baf7042
64ad522
 
caea4d0
 
 
 
 
 
fe48e22
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
---
license: cc0-1.0
dataset_info:
  features:
  - name: Domain
    dtype: string
  - name: File
    dtype: string
  - name: URL
    dtype: string
  - name: Content
    dtype: string
  splits:
  - name: train
    num_bytes: 53303182
    num_examples: 172
  download_size: 19143824
  dataset_size: 53303182
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

## Context & Motivation

https://llmstxt.org/ is a project from Answer.AI which proposes to "standardise on using an `/llms.txt` file to provide information to help LLMs use a website at inference time." 

I've noticed many tool providers begin to offer `/llms.txt` files for their websites and documentation. This includes developer tools and platforms like Perplexity, Anthropic, Hugging Face, Vercel, and others.

I've also come across https://directory.llmstxt.cloud/, a directory of websites that have `/llms.txt` files which is curated by these folks: https://x.com/llmsdottxt. I thought it would be fun to use this awesome resource to collect all of the files into a single dataset. They're simply markdown files. This dataset can then be used to build cool applications.

Thank you to Answer.AI and Jeremy Howard, the providers that are adopting this standard, and the maintainers of https://directory.llmstxt.cloud/. 

## How this dataset was made

[This is the notebook](https://www.kaggle.com/code/mrisdal/generate-a-dataset-of-llms-txt-files) that fetches files that linked to from https://directory.llmstxt.cloud/ and uses the `kagglehub` Python client library to publish the resulting output as this dataset. 

## Inspiration

* Give your LLM application access to this dataset to enhance its interactions with these tools, e.g., for code-generation tasks
* Search and knowledge retrieval
* Extract and summarize common developer tasks to generate novel benchmarks for LLM evaluation
* Validate the correctness of the llms.txt files

## Contributing

I'd love if anyone is interested in contributing to improving the notebook that extracts the `llms.txt` files. Leave a comment on this dataset or on the notebook. Feel free to also ping me with interesting demos or applications you create with this dataset. 

Photo by <a href="https://unsplash.com/@solenfeyissa?utm_content=creditCopyText&utm_medium=referral&utm_source=unsplash">Solen Feyissa</a> on <a href="https://unsplash.com/photos/a-person-holding-a-cell-phone-in-their-hand-hWSNT_Pp4x4?utm_content=creditCopyText&utm_medium=referral&utm_source=unsplash">Unsplash</a>