import streamlit as st from streamlit_extras.add_vertical_space import add_vertical_space import os import streamlit as st import pandas as pd from io import StringIO from datetime import datetime import boto3 # import util import requests import time # from sf_conn import get_client_names, get_secret, save_to_sf # from constants import USER_LIST, DOCZY_PIPELINE_URL_DEV # doczy_pipeline = DOCZY_PIPELINE_URL_DEV # REDIRECT_URI = 'https://doczydev.aarete.com:8501' # user_list = USER_LIST st.set_page_config(layout = "wide") # # # Sidebar contents # # with st.sidebar: # # st.title("Doczy.AI ™") # # st.markdown( # # """ # # ## About # # This app extracts data from contracts # # """ # # ) # # add_vertical_space(15) # # # st.write("Doczy") _,c1= st.columns([5,1]) # try: # util.setup_page(REDIRECT_URI) # except: # st.write("SSO Failed") # st.session_state['user_info'] = {'mail': 'maamseek@aarete.com', 'displayName': 'Mayank Aamseek'} st.session_state['user_info'] = {'mail': 'maamseek@aarete.com', 'displayName': 'Mayank Aamseek'} try: c1.write(f"User: **{st.session_state.user_info['displayName']}**") user_mail = st.session_state.user_info['mail'] except KeyError as e: # Do we add a link to get to the login page here? st.write("Session Expired.") st.stop() s3_client = boto3.client('s3', region_name="us-east-2", ) # # to be replaced with snowflake data client_list = ['doczy-ai-client-1', 'Delaware First Health, Inc.', 'Community Health Choice, Inc','CareSource Network Partners LLC', 'HealthNet of Cali', 'Oklahoma Complete Health, Inc', 'HealthFirst', 'Molina Healthcare of TX', 'AvMed', 'Arizona Care1st', 'WellCare New Jersey'] # client_list, s3_paths = get_client_names() # client_s3_paths = dict(zip(client_list, s3_paths)) client_row = st.columns([0.1, 0.8]) with client_row[0]: st.write("**Client Name**") with client_row[1]: client = st.selectbox('Client Name',(client_list), label_visibility = "collapsed", index = None) # MODIFIED for Ticket DOC-344 # client_bucket = client_s3_paths.get(client) # # to be deleted when buckets for different clients are ready; below line is added only for testing the corresponding DAG client_bucket = 'doczy-ai-client-1' # batch_objects = s3_client.list_objects_v2(Bucket=client_bucket # , Prefix="contracts_landing_zone/", Delimiter='/') # batch_list = [] # for prefix in batch_objects['CommonPrefixes']: # batch_list.append(prefix['Prefix'][:-1].split('/')[-1]) batch_list = ['batch_020524103737', 'batch_090524131433', 'batch_090524131607', 'batch_100524123000', 'batch_130524064322', 'batch_160524071331', 'batch_200524213550', 'batch_250424112237', 'batch_280524120530', 'batch_280524121721', 'batch_280524144222', 'batch_290524123926', 'batch_290524164044', 'batch_310524102029', 'batch_310524124050', 'batch_310524162346', 'batch_310524162631'] if 'sorted_list' not in st.session_state: st.session_state.sorted_list = batch_list def sort_list(ex_list, sort_by, order): if sort_by == 'Alphabetical': ex_list = sorted(ex_list, reverse=(order == 'Descending')) elif sort_by == 'Create Date': ex_list = ex_list if order == 'Ascending' else list(reversed(ex_list)) return ex_list col1, col2, col3, col4 = st.columns([0.5, 0.5, 0.5, 0.5]) with col1: sort_by = st.radio("**Sort Batch_IDs**", ('Alphabetical', 'Create Date')) with col2: order = st.radio('', ('Ascending','Descending')) with col3: add_vertical_space(2) if st.button('Apply'): st.session_state.sorted_list = sort_list(batch_list, sort_by, order) path_row = st.columns([0.1, 0.8]) with path_row[0]: st.write("**Batch ID**") with path_row[1]: batch_id = st.selectbox('**Batch ID**', st.session_state.sorted_list, label_visibility = "collapsed", index = None) # MODIFIED for Ticket DOC-344 if not batch_id: batch_id = "None" checks = st.columns([0.1, 0.12, 0.12, 0.12, 0.12, 0.12, 0.12, 0.12]) with checks[0]: st.write("**Group No.**") with checks[1]: a = st.checkbox('Unique Key', key = str(1), args="Unique") with checks[2]: b = st.checkbox('Pricing Before Carveouts', key = str(2)) with checks[3]: c = st.checkbox('Contract Related', key = str(3)) with checks[4]: d = st.checkbox('Provider', key = str(4)) with checks[5]: e = st.checkbox('Timeline', key = str(5)) with checks[6]: f = st.checkbox('Carveout Indicator', key = str(6)) with checks[7]: g = st.checkbox('Carveout Methodology', key = str(7)) add_vertical_space(1) df = pd.DataFrame(columns=['Contract Name', 'Unique Key','Pricing Before Carveouts' , 'Contract Related', 'Provider', 'Timeline', 'Carveout Indicator', 'Carveout Methodology']) # file_list = [] # file_objects = s3_client.list_objects_v2(Bucket=client_bucket # , Prefix="contracts_landing_zone/"+batch_id+"/", Delimiter='/') file_list = ['Boilerplate_TX Amendment Mission Health Network effective_040114 MU.pdf', 'Custom_TX - MP AMENDMENT - MISSION HEALTH NETWORK - MU.pdf', 'Delaware First Health_First State Homecare Agency_212260_7 MU.pdf', 'Molina Healthcare of Texas, Inc. Amendment 4 - HIX ACA__EFF 01012016_MU.pdf'] if st.button("Read the contracts from Path"): # for obj in file_objects.get('Contents',[]): # if not obj['Key'].endswith('/'): # file_list.append(obj['Key'].split('/')[-1]) df['Contract Name'] = file_list # df['Request ID'] = range(len(file_list)) # df['Contract ID'] = file_list df['Unique Key'] = a df['Pricing Before Carveouts'] = b df['Contract Related'] = c df['Provider'] = d df['Timeline'] = e df['Carveout Indicator'] = f df['Carveout Methodology'] = g dir_path = os.path.dirname(os.path.realpath(__file__)) print(f'DEBUGGING: PWD= {dir_path}') df.to_csv('temp1.csv', index=False) add_vertical_space(1) df2 = pd.read_csv('temp1.csv') edited_df = st.data_editor(df2) edited_df['REQUEST_USER'] = user_mail edited_df['LATEST_FLAG BOOLEAN'] = True edited_df['PIPELINE_KICKOFF_DATETIME'] = datetime.now().strftime("%Y-%m-%d %H:%M:%S") edited_df['REQUEST_DATETIME'] = datetime.now().strftime("%Y-%m-%d %H:%M:%S") @st.cache_data def convert_df(df): return df.to_csv(index=False).encode('utf-8') csv = convert_df(edited_df) # edited_df = edited_df.reset_index() # make sure indexes pair with number of rows # additional_info = pd.DataFrame(columns=['REQUEST_ID','T_DRIVE_PATH','CLIENT_NAME' # , 'GROUP_NAME', 'REQUEST_USERNAME', 'REQUEST_DATETIME']) additional_info = pd.DataFrame(columns=['CLIENT_NAME', 'BATCH_ID', 'REQUEST_USERNAME', 'REQUEST_DATETIME']) additional_info.loc[0] = [client, batch_id, st.session_state.user_info['mail'], datetime.now().strftime("%Y-%m-%d %H:%M:%S")] st.write(additional_info) st.session_state.contract_count = 0 contract_list = [] for index, row in edited_df.iterrows(): allow_run_for_contract = False group_list = [] if row['Unique Key']: group_list.append('Unique Key') allow_run_for_contract = True if row['Pricing Before Carveouts']: group_list.append('Pricing Before Carveouts') allow_run_for_contract = True if row['Contract Related']: group_list.append('Contract Related') allow_run_for_contract = True if row['Provider']: group_list.append('Provider') allow_run_for_contract = True if row['Timeline']: group_list.append('Timeline') allow_run_for_contract = True if row['Carveout Indicator']: group_list.append('Carveout Indicator') allow_run_for_contract = True if row['Carveout Methodology']: group_list.append('Carveout Methodology') allow_run_for_contract = True if allow_run_for_contract: st.session_state.contract_count += 1 entry_dict = { "contract_name": row['Contract Name'], "groups": group_list, "contract_source_path": "contracts_landing_zone/"+batch_id+"/"+row['Contract Name'] } contract_list.append(entry_dict) myobj = { "s3_bucket": client_bucket, "batch_id": batch_id, "client_name": client, "username": user_mail, "contract_list": contract_list } buttons = st.columns([0.8, 0.2]) with buttons[0]: st.download_button("Download Table", csv, "file.csv", "text/csv", key='download-csv') with buttons[1]: if st.button("Run Doczy.AI Pipeline"): if not st.session_state.contract_count == len(edited_df): st.error("Select at least one Group No. for every Contract") else: with st.spinner('Running...'): # Feedback to User while API endpoint sends response for DOC-342 # csv_buf = StringIO() # additional_info.to_csv(csv_buf, header=True, index=False) # csv_buf.seek(0) # s3_client.put_object(Bucket='doczy-dev-infra-raw-data-ingestion', Body=csv_buf.getvalue(), Key='training_interface/request_submission.csv') # csv_buf = StringIO() # edited_df.to_csv(csv_buf, header=True, index=False) # csv_buf.seek(0) # s3_client.put_object(Bucket='doczy-dev-infra-raw-data-ingestion', Body=csv_buf.getvalue(), Key='training_interface/contract_config.csv') # try: # save_to_sf('load_request_and_contract_submissions', request_submission_file_name = "request_submission.csv", contract_config_file_name = "contract_config.csv") # except Exception as e: # st.write(e) # response = requests.post(doczy_pipeline, json = myobj) # if response.status_code >= 200 and response.status_code < 300: # st.write("Success") # # st.write(myobj) # else: # st.write("Failed") # st.write(response.text) time.sleep(5) st.write("Success!")