a hyper fast natural language proccesing module
Project description
how to use:
sentiment analysis:
from i_rly_like_lemons import sentiment
1: get_sentence_sentiment("your sentence here") <-- returns a single number which is the sentence's sentiment.
2: get_text_sentiment("i really like lemons, however pineapples are also good. and this is another sentence.") <--- returns a list of all sentiments from the sentences.
meaning extraction:
from i_rly_like_lemons import meaning
1: word_to_index("word") <--- returns the "meaning index" of a single word.
2: index_to_word(912873) <--- gets the "meaning index" of a word, and translates the index into the word.
3: sentence_to_index("your sentence here") <--- gets a sentence and returns the list of all meaning indexe's of the words inside.
4: index_to_sentence([129038, 238745, 39874,... 93824]) <--- gets a list of meaning indexe's and returns a sentence.
keyword detection:
from i_rly_like_lemons import keywords
1: detect_keywords("your sentence here") <--- will get a text prompt and return a list with all the keywords that it found.
extras:
from i_rly_like_lemons import extras
1: cleanup("you,r co<<rupte///d [tex]t he.re") <--- will get text and clean it up from unwanted characters (all special characters).
2: split_with_multiple_seperators("|", ",", " ", text = "this|is,a test") <--- just like normal split(" ") command but supports multiple seperators.
3: rephrase([238094, 78245, 879435, 38490], 2) <--- takes in a meaning list (from meaning extraction) and randomizes them with the "strength" value.
4: compare("word1", "werd2") <--- gets two strings and returns the % of their match: 0% > no matching characters, 100% > identical strings.
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