semvec/pypi-packages huggingface dataset:
ankillins 0.0.1
Anki cards generating from CollinsDictionary pages
Keywords: anki card generation collins

Generates Anki cards from Collins pages.
# ankillins
Ankillins is a Command Line Application that generates Anki cards from collinsdictionary.com pages.
![generated card example](https://i.imgur.com/dDps8GU.png)
## Features 
* Generating cloze card for every definition
* Word pronounce in cards 
* Examples pronounce support (locked because of high memory usage)
* Words search support
* Original site styles
## Usage
```shell script
➜ ankillins search "At the end of the day"
at the end of the day
➜ ankillins gen-cards "At the end of the day"
Word "At the end of the day" processed successfully
➜ ankillins gen-cards hello knife spider "so on" kek does_not_exists "sort of" kind
Word "hello" processed successfully
Word "knife" processed successfully
Word "spider" processed successfully
Word "so on" processed successfully
[Error] Word kek not found
Similar words: keck, keek, keks, kike, eek, kak, keV, kea, keb, ked, kef, keg, ken, kep, ket, kex, key, lek, nek, zek
[Error] Word does_not_exists not found
Similar words: dentists, kenoticists
Word "sort of" processed successfully
Word "kind" processed successfully
➜ ls -lh
total 32K
-rw-r--r-- 1 hairygeek hairygeek 31K Jul 26 12:56 ankillins-result.csv
```
Ankillins doesn't add cards to Anki itself. Instead, it generates `ankillins-result.csv` file which you need to import. 
### Important details
* When you import result file click on the "fields separated by" and type `~`
* It is better to create your own card type with styles located in `card_styles.css` to get card style close to collinsdictionary page style.

## Installation
*Will be available sooner*
source-analyzer 0.1.6
Application for analysis of similarities between separate files. Currently with '*.py' and '*.txt' file checking capability
Requires Python: >=3.6

# SourceAnalyzer 

[GitHub Repo Link](https://github.com/dcaust1n/SourceAnalyzer.git)

- A locally run application that demonstrates different matching algorithms 
- Current release compares files as a one to one connection
- Outputs given percentage of similarity and highlighted visualization of the matching sections of input documents
- Supports, raw text files and python files currently, with C++ and java planned in the future releases

## Getting Started

#### STEP 1 

it is recommended to create and navigate to virtual environemnt using python to run script

    python3.8 -m venv <dir> 
    source <dir>/bin/activate

#### STEP 2

install source_analyzer python package from Python Package Index.
**Note:** must be running python version 3.8 or greater

    pip install source_analyzer


###### OR

Download the latest built compressed file release from [source_analyzer-X.X.X.tar.gz](https://github.com/dcaust1n/SourceAnalyzer/tree/master/dist)



then install downloaded file

    pip3 install /<path_to_file>/source_analyzer-0.1.18.tar.gz


#### STEP 3
(make sure xlaunch is running)
run script

    source_analyzer

## Known Errors/Issues
Errors- 
Multiple of the same substring found in file B will return only the first instance of that substring. 

Issues- 
Python files featuring a heavy amount of print statements may cause skewed data. 

## Test Files
Test files can be found in: 
    <dir>/lib/python3.8/site-packages/source/test_file
there are python files and .txt files, make sure to change the file filter down below to be able to see either of them.

## Project Group: Codalyzers
- Djoni Austin | @dcaust1n
- Jared Dawson | @lukinator1
- Shane Eising | @seising99
- Julian Marott | @jmmoratta

## References: 
https://theory.stanford.edu/~aiken/publications/papers/sigmod03.pdf
gpt-scrolls 0.0.9
A collaborative collection of open-source safe GPT-3 prompts that work well
Requires Python: >=3.6

# gpt-scrolls
A collaborative collection of open-source safe GPT-3 prompts that work well

Feel free to contribute your prompts!


## Getting Started
To use gpt-scrolls, you'll need access to the OpenAI API. If you haven't, [sign up for the beta](http://beta.openai.com/).

```
$ pip install gpt-scrolls
$ export OPENAI_API_KEY=...
$ python -c "import scrolls; print(scrolls.run('creative/philosopher'))"

I perused with interest and some confusion the very detailed description of autonomous society as envisioned by the creators of this simulation, for it reminded me of the doomed civilization of the Onos; they too desired self-replicating programs, a necessary foundation in real-space for artificial intelligence; and the created what they thought was self-replicating, except that they had no command over the experiment; it was uncontrollable, and indeed uncontrollable in about 90 minutes.

$ python -c "import scrolls; print(scrolls.run('creative/business-ideas'))"
Last Mile - Same day delivery service that picks and takes out the trash and delivers
```

## Running scrolls in your own app
```
import scrolls

idea = scrolls.run('creative/business-ideas')
print(idea)
```

## Running locally
If you want to use gpt-scrolls without `pip` by cloning the repo:

```
$ git clone git@github.com:maraoz/gpt-scrolls.git
$ cd gpt-scrolls/
$ python3 -m venv .scrolls-env
$ source .scrolls-env/bin/activate
(.scrolls-env) $ pip install -r requirements.txt
(.scrolls-env) $ export OPENAI_API_KEY=...
(.scrolls-env) $ python scrolls/run.py "top10/women"
~~~Rosa Parks

2. ~~~Cleopatra

3. ~~~Joan of Arc

4. ~~~Madonna

5. ~~~Queen Elizabeth I

6. ~~~Elizabeth II

7. ~~~Tamar

8. ~~~Billie Jean King

9. ~~~Catherine the Great

10. ~~~Elizabeth I
```

*Note*: I'm planning to turn this into a easy-to-use CLI tool.

## Design goals
gpt-scroll prompts should aim to be:
- **effective**: they should reliably produce desired classes of outpupts
- **efficient**: they should be as short as possible
- **safe**: they should minimize appearance of toxic/harmful output

Have this in mind for any contribution. (eg: if you find that a prompt works equally well without one example, you might submit a PR to remove that example, citing efficiency)