arxivgpt / utils.py
bishmoy's picture
Added experimental Arxiv Support
777c2c7 verified
import datetime
import string
import nltk
nltk.download('stopwords')
from nltk.corpus import stopwords
stop_words = stopwords.words('english')
import arxiv
def get_md_text_abstract(rag_answer, source = ['Arxiv Search', 'Semantic Search'][1], return_prompt_formatting = False):
if 'Semantic Search' in source:
title = rag_answer['document_metadata']['title'].replace('\n','')
#score = round(rag_answer['score'], 2)
date = rag_answer['document_metadata']['_time']
paper_abs = rag_answer['content']
authors = rag_answer['document_metadata']['authors'].replace('\n','')
doc_id = rag_answer['document_id']
paper_link = f'''https://arxiv.org/abs/{doc_id}'''
download_link = f'''https://arxiv.org/pdf/{doc_id}'''
elif 'Arxiv' in source:
title = rag_answer.title
date = rag_answer.updated.strftime('%d %b %Y')
paper_abs = rag_answer.summary.replace('\n',' ') + '\n'
authors = ', '.join([author.name for author in rag_answer.authors])
paper_link = rag_answer.links[0].href
download_link = rag_answer.links[1].href
else:
raise Exception
paper_title = f'''### {date} | [{title}]({paper_link}) | [⬇️]({download_link})\n'''
authors_formatted = f'*{authors}*' + ' \n\n'
md_text_formatted = paper_title + authors_formatted + paper_abs + '\n---------------\n'+ '\n'
if return_prompt_formatting:
prompt_formatted = f"<b> {title} </b> \n Abstract: {paper_abs}"
return md_text_formatted, prompt_formatted
return md_text_formatted
def remove_punctuation(text):
punct_str = string.punctuation
punct_str = punct_str.replace("'", "")
return text.translate(str.maketrans("", "", punct_str))
def remove_stopwords(text):
text = ' '.join(word for word in text.split(' ') if word not in stop_words)
return text
def search_cleaner(text):
new_text = text.lower()
new_text = remove_stopwords(new_text)
new_text = remove_punctuation(new_text)
return new_text
q = '(cat:cs.CV OR cat:cs.LG OR cat:cs.CL OR cat:cs.AI OR cat:cs.NE OR cat:cs.RO)'
def get_arxiv_live_search(query, client, max_results = 10):
clean_text = search_cleaner(query)
search = arxiv.Search(
query = clean_text + " AND "+q,
max_results = max_results,
sort_by = arxiv.SortCriterion.Relevance
)
results = client.results(search)
all_results = list(results)
return all_results