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| import streamlit as st | |
| import pandas as pd | |
| import numpy as np | |
| #from src.Surveyor import Surveyor | |
| def run_survey(surveyor, research_keywords, max_search, num_papers): | |
| zip_file_name, survey_file_name = surveyor.survey(research_keywords, | |
| max_search=max_search, | |
| num_papers=num_papers | |
| ) | |
| with open(str(zip_file_name), "rb") as file: | |
| btn = st.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 = st.download_button( | |
| label="Download detailed generated survey file", | |
| data=file, | |
| file_name=str(zip_file_name) | |
| ) | |
| with open(str(survey_file_name), "rb") as file: | |
| btn = st.download_button( | |
| label="Download detailed generated survey file", | |
| data=file, | |
| file_name=str(zip_file_name) | |
| ) | |
| st.write(file.readlines()) | |
| def survey_space(): | |
| st.title('Automated Survey generation from research keywords - Auto-Research V0.1') | |
| form = st.sidebar.form(key='survey_form') | |
| research_keywords = form.text_input("What would you like to research in today?") | |
| max_search = form.number_input("num_papers_to_search", help="maximium number of papers to glance through - defaults to 20", | |
| min_value=1, max_value=60, value=20, step=1, key='max_search') | |
| num_papers = form.number_input("num_papers_to_select", help="maximium number of papers to select and analyse - defaults to 8", | |
| min_value=1, max_value=25, value=8, step=1, key='num_papers') | |
| submit = form.form_submit_button('Submit') | |
| if submit: | |
| st.write("hello") | |
| #if surveyor_obj is None: | |
| # surveyor_obj = Surveyor() | |
| #run_survey(surveyor_obj, research_keywords, max_search, num_papers) | |
| if __name__ == '__main__': | |
| global surveyor_obj | |
| surveyor_obj = None | |
| survey_space() | |