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from typing import List, Optional | |
import streamlit as st | |
import streamlit_pydantic as sp | |
from pydantic import BaseModel, Field | |
from PIL import Image | |
from src.Surveyor import Surveyor | |
def get_surveyor_instance(_print_fn, _survey_print_fn): | |
with st.spinner('Loading The-Surveyor ...'): | |
return Surveyor(print_fn=_print_fn, survey_print_fn=_survey_print_fn, high_gpu=True) | |
def run_survey(surveyor, download_placeholder, research_keywords=None, arxiv_ids=None, max_search=None, num_papers=None): | |
zip_file_name, survey_file_name = surveyor.survey(research_keywords, | |
arxiv_ids, | |
max_search=max_search, | |
num_papers=num_papers | |
) | |
show_survey_download(zip_file_name, survey_file_name, download_placeholder) | |
def show_survey_download(zip_file_name, survey_file_name, download_placeholder): | |
with open(str(zip_file_name), "rb") as file: | |
btn = download_placeholder.download_button( | |
label="Download extracted topic-clustered-highlights, images and tables as zip", | |
data=file, | |
file_name=str(zip_file_name) | |
) | |
with open(str(survey_file_name), "rb") as file: | |
btn = download_placeholder.download_button( | |
label="Download detailed generated survey file", | |
data=file, | |
file_name=str(survey_file_name) | |
) | |
class KeywordsModel(BaseModel): | |
research_keywords: Optional[str] = Field( | |
'', description="Enter your research keywords:" | |
) | |
max_search: int = Field( | |
10, ge=1, le=50, multiple_of=1, | |
description="num_papers_to_search:" | |
) | |
num_papers: int = Field( | |
3, ge=1, le=8, multiple_of=1, | |
description="num_papers_to_select:" | |
) | |
class ArxivIDsModel(BaseModel): | |
arxiv_ids: Optional[str] = Field( | |
'', description="Enter comma_separated arxiv ids for your curated set of papers (e.g. 2205.12755, 2205.10937, ...):" | |
) | |
if __name__ == '__main__': | |
st.sidebar.image(Image.open('logo_landscape.png'), use_column_width = 'always') | |
st.title('Auto-Research') | |
st.write('#### A no-code utility to generate a detailed well-cited survey with topic clustered sections' | |
'(draft paper format) and other interesting artifacts from a single research query or a curated set of papers(arxiv ids).') | |
st.write('##### Data Provider: arXiv Open Archive Initiative OAI') | |
st.write('##### GitHub: https://github.com/sidphbot/Auto-Research') | |
download_placeholder = st.container() | |
with st.sidebar.form(key="survey_keywords_form"): | |
session_data = sp.pydantic_input(key="keywords_input_model", model=KeywordsModel) | |
st.write('or') | |
session_data.update(sp.pydantic_input(key="arxiv_ids_input_model", model=ArxivIDsModel)) | |
submit = st.form_submit_button(label="Submit") | |
st.sidebar.write('#### execution log:') | |
run_kwargs = {'surveyor':get_surveyor_instance(_print_fn=st.sidebar.write, _survey_print_fn=st.write), | |
'download_placeholder':download_placeholder} | |
if submit: | |
if session_data['research_keywords'] != '': | |
run_kwargs.update({'research_keywords':session_data['research_keywords'], | |
'max_search':session_data['research_keywords'], | |
'num_papers':session_data['research_keywords']}) | |
elif session_data['arxiv_ids'] != '': | |
run_kwargs.update({'arxiv_ids':[id.strip() for id in session_data['arxiv_ids'].split(',')]}) | |
run_survey(**run_kwargs) | |