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""" | |
utils.py - Utility functions for the project. | |
""" | |
from pathlib import Path | |
import re | |
def truncate_word_count(text, max_words=512): | |
""" | |
truncate_word_count - a helper function for the gradio module | |
Parameters | |
---------- | |
text : str, required, the text to be processed | |
max_words : int, optional, the maximum number of words, default=512 | |
Returns | |
------- | |
dict, the text and whether it was truncated | |
""" | |
# split on whitespace with regex | |
words = re.split(r"\s+", text) | |
processed = {} | |
if len(words) > max_words: | |
processed["was_truncated"] = True | |
processed["truncated_text"] = " ".join(words[:max_words]) | |
else: | |
processed["was_truncated"] = False | |
processed["truncated_text"] = text | |
return processed | |
def load_examples(src): | |
""" | |
load_examples - a helper function for the gradio module to load examples | |
Returns: | |
list of str, the examples | |
""" | |
src = Path(src) | |
src.mkdir(exist_ok=True) | |
examples = [f for f in src.glob("*.txt")] | |
# load the examples into a list | |
text_examples = [] | |
for example in examples: | |
with open(example, "r") as f: | |
text = f.read() | |
text_examples.append([text, "large", 2, 512, 0.7, 3.5, 3]) | |
return text_examples | |