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doczyai-pipelines/streamlit/local/local_interface_1.py
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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!")
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