LangLearnCopilot is a library to help you learn a 'human' language.
Project description
LangLearnCopilot
LangLearnCopilot is a collection of functions and tools, to generate content in a proper format, to help you learn a new language.
For now, I am focusing on French (my personal interesting) and Spanish (for friends).
While this is a standalone library, my advice is, for the best results, to use its outcomes hand-in-hand with the awesome flashcards application, Anki
The main two applications at the moment
Installation
pip install langlearncopilot
Usage
You can find examples in the ./examples
folder
Note: you need to set your OpenAI key first. If the OPENAI_API_KEY
is declared already as an environment variable, or exisiting in the current folder in a .env
file, then the package will find it.
Other wise, you can set it manually by calling
from langlearncopilot.llm_calls import set_openai_key
set_openai_key("ENTER KEY VALUE HERE")
Given a text, extract all the unique words and its translation from that text
from langlearncopilot import generators
generators.generate_unique_words(
article="Bonjour, je m'appelle Jean. Je suis un étudiant à l'université de Paris."
)
returns
{
'bonjour': 'hello',
'je': 'i',
"m'appelle": 'is called',
'suis': 'am',
'un': 'a',
'étudiant': 'student',
'à': 'at',
"l'université": 'university',
'de': 'of'
}
Given a word, generate 3 phrases that are using these words
from langlearncopilot import generators
generators.generate_phrases("combien")
returns
[
{'combien': {'phrase': 'Combien de personnes sont venues à la fête?', 'translation': ' How many people came to the party?'}},
{'combien': {'phrase': 'Combien coûte ce sac à dos?', 'translation': ' How much does this backpack cost?'}},
{'combien': {'phrase': "Il m'a demandé combien de temps cela prendrait.", 'translation': ' He asked me how long it would take.'}}
]
Extract unique words from URL, with their translation
from langlearncopilot.parsers import get_text_from_webpage
from langlearncopilot.generators import generate_unique_words
def main():
# Get text from a webpage
text = get_text_from_webpage(
url="https://www.lemonde.fr/planete/article/2023/08/27/comment-les-parcs-nationaux-americains-tentent-de-faire-face-aux-effets-du-rechauffement-climatique_6186696_3244.html"
)
# Generate unique words from the text
words = generate_unique_words(article=text, language="french")
print(words)
if __name__ == "__main__":
main()
returns
{
'comment': 'how',
'les': 'the',
'parcs': 'parks',
'nationaux': 'national',
'américains': 'american',
'tentent': 'try',
'de': 'of',
...
}
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for langlearncopilot-0.3.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 98894bb3368b2d8c59b2789dd536b2cb86e317a4d9784031901453c3340cf495 |
|
MD5 | b244175e1fbff1b50771b22be78b7058 |
|
BLAKE2b-256 | 291e79c4b9c139f9d5430c4b687a6b6a5887fa1b107e65c2caff10203bd473b4 |