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https://github.com/top-on/llmask
A command-line tool for masking authorship of text, by changing the writing style with a Large Language Model.
https://github.com/top-on/llmask
anonymity llm privacy stylometry
Last synced: 3 days ago
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A command-line tool for masking authorship of text, by changing the writing style with a Large Language Model.
- Host: GitHub
- URL: https://github.com/top-on/llmask
- Owner: top-on
- License: mit
- Created: 2024-01-17T22:00:09.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2024-11-23T22:03:08.000Z (about 2 months ago)
- Last Synced: 2024-11-23T23:17:33.203Z (about 2 months ago)
- Topics: anonymity, llm, privacy, stylometry
- Language: Python
- Homepage:
- Size: 220 KB
- Stars: 6
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
- awesome_ai_agents - Llmask - A command-line tool for masking authorship of text, by changing the writing style with a Large Language Model. (Building / Tools)
- awesome_ai_agents - Llmask - A command-line tool for masking authorship of text, by changing the writing style with a Large Language Model. (Building / Tools)
README
# LLMask [ɛl ɛl 'ma:sk]
A command-line tool for masking authorship of text,
by changing the writing style with a Large Language Model.
The main use cases of masking an author's writing style are:
* anonymizing the author of a text
* protecting the identity of whistleblowers and activists
* see more use cases at [Adversarial Stylometry](https://en.wikipedia.org/wiki/Adversarial_stylometry)
## Disclaimer
⚠️ This project currently is just a demo of what LLMs can do for authorship anonymization.
⚠️ There is no strong evidence yet that this tool can beat state of the art de-anonymization methods!
### Known Limitations
Despite it's pre-production status, this library has several known limitations:
1. Only a limited number of transformations are implemented (see `transform.py`).
2. Long chains of transformations have observed to make the LLM output artifacts.
3. Sensitive content can trigger an LLMs censoring, and thus ruin the output.
In this case it is advised to try uncensored LLMs, e.g. of the [`wizard-vicuna-uncensored`](https://registry.ollama.ai/library/wizard-vicuna-uncensored) type.
4. Currently, unique names of places or persons are not removed/anonymized.
## Example workflows
1. Locally serve a Large Language Model server with [ollama](https://ollama.com/):
```
$ ollama serve
```
2. Make sure a potent model is served, e.g. a version of [`nous-hermes2`](https://registry.ollama.ai/library/nous-hermes2):
```
$ ollama run nous-hermes2:10.7b-solar-q6_K
```
3. Mask your writing style by transforming it into a different one:
```
$ llmask -v -i "this was a triumph. i'm making a note here: huge success."
User-provided input:
> this was a triumph. i'm making a note here: huge success.
Result after applying transformation 'thesaurus':
> This was an astonishing achievement. I'll jot down: extraordinary victory.
Result after applying transformation 'simplify':
> This was a great success. I'll write down: wonderful win.
```
### Piping input and output
For larger-scale text work, the text input and output can also be piped:
```
$ cat input.txt | llmask > output.txt
```
## Getting started
### System requirements
LLMs can run on ordinary CPUs, e.g. with `ollama`.
However, GPU acceleration greatly accelerates execution speed.
Please note that this project is tested most thoroughly on Apple Silicon hardware.
### Installation
This command line tool can be installed with: `pipx install llmask`
### Usage options
```
$ llmask --help
Usage: llmask [OPTIONS]
Transform input text with chained transformations by a Large Language Model.
Options:
-t, --transformations TEXT Sequence of transformations to apply in order,
e.g. 'tsp' for the steps 'thesaurus ->
simplify -> persona', where 't' applies
thesaurus, 's' simplifies, and 'p' imitates a
persona. [default: ts]
-i, --input TEXT Input text that will be transformed.
-p, --persona TEXT Name of persona whose writing style to
imitate. [default: Ernest Hemingway]
-m, --model TEXT Name of model to use (as known to model
server). [default: nous-
hermes2:10.7b-solar-q6_K]
-u, --url TEXT URL of Open AI compatible model API.
[default: http://localhost:11434/v1]
-v, --verbose Verbosity level. At default, only the final
output is returned. [default: 0]
-r, --randomness FLOAT RANGE Higher values make the output more
random.Parameter value is passes as 'sampling
temperature' to language model. [default:
0.5; 0.0<=x<=2.0]
-s, --seed INTEGER Repeated requests with the same `seed` and
parameters should return the same result.
[default: 42]
-h, --help Show this message and exit.
```
## Development setup
### Install development environment
The development environment can be installed via: `poetry install`.
## Roadmap
* support transformations from and into text files
* measure success of obfuscation
* measure success of anonymzation with de-anonymization tools (e.g. `faststylometry`)
* check with GPTZero if suspected author is an LLM
* re-introduce test suite