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import streamlit as st
from persist import persist, load_widget_state
#from pages.viewCardProgress import get_card
from modelcards import CardData, ModelCard
from markdownTagExtract import tag_checker,listToString,to_markdown
#from specific_extraction import extract_it
from modelcards import CardData, ModelCard
from jinja2 import Environment, FileSystemLoader
def is_float(value):
try:
float(value)
return True
except:
return False
## Handles parsing jinja variable templates
def parse_into_jinja_markdown():
env = Environment(loader=FileSystemLoader('.'), autoescape=True)
temp = env.get_template(st.session_state.markdown_upload)
# to add:
# - parent model
# to fix:
# citation on form: check box for bibtex or apa: then parse
return (temp.render(model_name = st.session_state["model_name"], model_version = st.session_state["model_version"],
icd10 = st.session_state["icd10"], treatment_modality = st.session_state["treatment_modality"], prescription_levels = st.session_state["prescription_levels"],
additional_information = st.session_state["additional_information"], motivation = st.session_state["motivation"], model_class = st.session_state["model_class"],
creation_date = st.session_state["creation_date"], architecture = st.session_state["architecture"],
model_developers=st.session_state["model_developers"],funded_by = st.session_state["funded_by"],shared_by = st.session_state["shared_by"],
license = st.session_state['license'],finetuned_from = st.session_state['finetuned_from'], research_paper = st.session_state["research_paper"], git_repo = st.session_state["git_repo"],
nb_parameters = st.session_state["nb_parameters"], input_channels = st.session_state["input_channels"],
loss_function = st.session_state["loss_function"], batch_size = st.session_state["batch_size"], patch_dimension = st.session_state["patch_dimension"],
architecture_filename = st.session_state["architecture_filename"], libraries = st.session_state["libraries"], hardware = st.session_state["hardware"],
inference_time = st.session_state["inference_time"], get_started_code = st.session_state["get_started_code"],
training_set_size = st.session_state["training_set_size"], validation_set_size = st.session_state["validation_set_size"],
age_fig_filename = st.session_state["age_fig_filename"], sex_fig_filename = st.session_state["sex_fig_filename"],
dataset_source = st.session_state["dataset_source"], acquisition_from = st.session_state["acquisition_from"], acquisition_to = st.session_state["acquisition_to"],
# direct_use = st.session_state["Direct_Use"], downstream_use = st.session_state["Downstream_Use"],out_of_scope_use = st.session_state["Out-of-Scope_Use"],
# bias_risks_limitations = st.session_state["Model_Limits_n_Risks"], bias_recommendations = st.session_state['Recommendations'],
# model_examination = st.session_state['Model_examin'],
# speeds_sizes_times = st.session_state['Speeds_Sizes_Times'],
# hardware= st.session_state['Model_hardware'], hours_used = st.session_state['hours_used'], cloud_provider = st.session_state['Model_cloud_provider'], cloud_region = st.session_state['Model_cloud_region'], co2_emitted = st.session_state['Model_c02_emitted'],
# citation_bibtex= st.session_state["APA_citation"], citation_apa = st.session_state['bibtex_citation'],
# training_data = st.session_state['training_Data'], preprocessing =st.session_state['model_preprocessing'],
# model_specs = st.session_state['Model_specs'], compute_infrastructure = st.session_state['compute_infrastructure'],software = st.session_state['technical_specs_software'],
# glossary = st.session_state['Glossary'],
# more_information = st.session_state['More_info'],
# model_card_authors = st.session_state['the_authors'],
# model_card_contact = st.session_state['Model_card_contact'],
# get_started_code =st.session_state["Model_how_to"],
# repo_link = st.session_state["github_url"],
# paper_link = st.session_state["paper_url"],
# blog_link = st.session_state["blog_url"],
# testing_data = st.session_state["Testing_Data"],
# testing_factors = st.session_state["Factors"],
# results = st.session_state['Model_Results'],
# testing_metrics = st.session_state["Metrics"]
))
################################################################
################################################################
################################################################
################## Below CURRENTLY Deprecated ##################
################################################################
################################################################
################################################################
def apply_view(page_state, not_code_pull,text_passed):
not_important_section = True
if st.session_state.legal_view == True:
#user_view = 'legal_view'
user_view_collapse={'Model_details_text','Model_uses','Model_Eval','Model_carbon','Model_cite', 'Glossary','Model_card_authors'}
elif st.session_state.researcher_view == True:
#user_view = 'researcher_view'
user_view_collapse={'Model_details_text','Model_how_to','Model_training','Model_Limits_n_Risks', 'Glossary', 'Model_card_contact', 'Citation'}
else:
#user_view = 'beginner_technical_view'
user_view_collapse={'Model_details_text','Model_how_to','Model_Eval','Model_uses', 'Glossary'} # Add Techical Spec
for value in user_view_collapse:
if value == page_state:
not_important_section = False
if not_important_section == True: #and st.session_state[user_view]:
#st.markdown("here")
text_return = out_text_out(not_code_pull,page_state,text_passed)
out_text = "<details> <summary> Click to expand </summary>" +text_return + "</details>"
return (out_text)
#out_text = "<details>" + out_text + "</details>"
else:
text_return = out_text_out(not_code_pull,page_state,text_passed)
out_text = text_return
return (out_text)
def out_text_out(not_code_pull,page_state,out_text):
if not_code_pull == True:
out_text = extract_it(page_state)
return(out_text)
else:
out_text = out_text
return(out_text)
def writingPrompt(page_state, help_text, out_text):
#st.session_state.check_box = False
#extracted_how_to= tag_checker(markdown,start_tag,end_tag)
#see_suggestion = column.checkbox("See Writing Prompt")
st.session_state.check_box = True
variable_output_prompt = st.text_area("Enter some text",height = 500, value =out_text, key=persist(out_text),
help=help_text)
st.session_state.page_state = persist(variable_output_prompt)
#out_text = extract_it(page_state)
#else:
#st.session_state.check_box = True
##st.session_state.check_box = False
#variable_output_prompt = st.text_area("Enter Text",value = ' ',key=persist(page_state),height = 500,help =help_text)
return variable_output_prompt
def extract_section(current_template, start_tag, end_tag):
current_Card_markdown= current_template
extracted_how_to= tag_checker(current_Card_markdown,start_tag,end_tag)
out_text = ' '.join(extracted_how_to)
return out_text
def main():
#card.save('current_card.md')
return |