Umang Mistry
207 lines
7.2 KiB
Python
207 lines
7.2 KiB
Python
import streamlit as st
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from streamlit_extras.add_vertical_space import add_vertical_space
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import os
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import streamlit as st
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import pandas as pd
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from io import StringIO
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from datetime import datetime
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import boto3
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import util
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import requests
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from sf_conn import get_client_names, get_secret, save_to_sf
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from constants import USER_LIST, DOCZY_PIPELINE_URL_DEV
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doczy_pipeline = DOCZY_PIPELINE_URL_DEV
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REDIRECT_URI = 'https://doczydev.aarete.com:8501'
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user_list = USER_LIST
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st.set_page_config(layout = "wide")
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# # Sidebar contents
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# with st.sidebar:
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# st.title("Doczy.AI ™")
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# st.markdown(
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# """
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# ## About
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# This app extracts data from contracts
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# """
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# )
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# add_vertical_space(15)
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# # st.write("Doczy")
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_,c1= st.columns([5,1])
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try:
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util.setup_page(REDIRECT_URI)
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except:
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st.write("SSO Failed")
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st.session_state['user_info'] = {'mail': 'maamseek@aarete.com', 'displayName': 'Mayank Aamseek'}
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try:
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c1.write(f"User: **{st.session_state.user_info['displayName']}**")
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user_mail = st.session_state.user_info['mail']
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except KeyError as e:
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# Do we add a link to get to the login page here?
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st.write("Session Expired.")
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st.stop()
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s3_client = boto3.client('s3',
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region_name="us-east-2",
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)
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# # to be replaced with snowflake data
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# client_list = ['doczy-ai-client-1', 'Delaware First Health, Inc.', 'Community Health Choice, Inc','CareSource Network Partners LLC',
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# 'HealthNet of Cali', 'Oklahoma Complete Health, Inc', 'HealthFirst', 'Molina Healthcare of TX', 'AvMed', 'Arizona Care1st',
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# 'WellCare New Jersey']
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client_list, s3_paths = get_client_names()
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client_s3_paths = dict(zip(client_list, s3_paths))
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client_row = st.columns([0.1, 0.8])
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with client_row[0]:
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st.write("**Client Name**")
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with client_row[1]:
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client = st.selectbox('Client Name',(client_list), label_visibility = "collapsed")
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client_bucket = client_s3_paths.get(client)
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# # to be deleted when buckets for different clients are ready; below line is added only for testing the corresponding DAG
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client_bucket = 'doczy-ai-client-1'
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batch_objects = s3_client.list_objects_v2(Bucket=client_bucket
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, Prefix="contracts_landing_zone/", Delimiter='/')
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batch_list = []
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for prefix in batch_objects['CommonPrefixes']:
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batch_list.append(prefix['Prefix'][:-1].split('/')[-1])
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path_row = st.columns([0.1, 0.8])
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with path_row[0]:
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st.write("**Batch ID**")
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with path_row[1]:
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batch_id = st.selectbox('**Batch ID**', batch_list, label_visibility = "collapsed")
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checks = st.columns([0.1, 0.12, 0.12, 0.12, 0.12, 0.12, 0.12, 0.12])
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with checks[0]:
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st.write("**Group No.**")
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with checks[1]:
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a = st.checkbox('Unique Key', key = str(1))
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with checks[2]:
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b = st.checkbox('Pricing Before Carveouts', key = str(2))
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with checks[3]:
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c = st.checkbox('Contract Related', key = str(3))
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with checks[4]:
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d = st.checkbox('Provider', key = str(4))
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with checks[5]:
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e = st.checkbox('Timeline', key = str(5))
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with checks[6]:
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f = st.checkbox('Carveout Indicator', key = str(6))
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with checks[7]:
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g = st.checkbox('Carveout Methodology', key = str(7))
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add_vertical_space(1)
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df = pd.DataFrame(columns=['Contract Name', 'Unique Key','Pricing Before Carveouts'
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, 'Contract Related', 'Provider', 'Timeline', 'Carveout Indicator', 'Carveout Methodology'])
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file_list = []
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file_objects = s3_client.list_objects_v2(Bucket=client_bucket
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, Prefix="contracts_landing_zone/"+batch_id+"/", Delimiter='/')
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if st.button("Read the contracts from Path"):
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for obj in file_objects.get('Contents',[]):
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if not obj['Key'].endswith('/'):
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file_list.append(obj['Key'].split('/')[-1])
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df['Contract Name'] = file_list
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# df['Request ID'] = range(len(file_list))
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# df['Contract ID'] = file_list
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df['Unique Key'] = a
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df['Pricing Before Carveouts'] = b
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df['Contract Related'] = c
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df['Provider'] = d
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df['Timeline'] = e
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df['Carveout Indicator'] = f
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df['Carveout Methodology'] = g
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dir_path = os.path.dirname(os.path.realpath(__file__))
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print(f'DEBUGGING: PWD= {dir_path}')
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df.to_csv('temp1.csv', index=False)
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add_vertical_space(1)
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df2 = pd.read_csv('temp1.csv')
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edited_df = st.data_editor(df2)
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edited_df['REQUEST_USER'] = user_mail
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edited_df['LATEST_FLAG BOOLEAN'] = True
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edited_df['PIPELINE_KICKOFF_DATETIME'] = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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edited_df['REQUEST_DATETIME'] = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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@st.cache_data
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def convert_df(df):
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return df.to_csv(index=False).encode('utf-8')
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csv = convert_df(edited_df)
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# edited_df = edited_df.reset_index() # make sure indexes pair with number of rows
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# additional_info = pd.DataFrame(columns=['REQUEST_ID','T_DRIVE_PATH','CLIENT_NAME'
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# , 'GROUP_NAME', 'REQUEST_USERNAME', 'REQUEST_DATETIME'])
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additional_info = pd.DataFrame(columns=['CLIENT_NAME', 'BATCH_ID', 'REQUEST_USERNAME', 'REQUEST_DATETIME'])
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additional_info.loc[0] = [client, batch_id, st.session_state.user_info['mail'], datetime.now().strftime("%Y-%m-%d %H:%M:%S")]
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st.write(additional_info)
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contract_list = []
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for index, row in edited_df.iterrows():
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group_list = []
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if row['Unique Key']:
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group_list.append('Unique Key')
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if row['Pricing Before Carveouts']:
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group_list.append('Pricing Before Carveouts')
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if row['Contract Related']:
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group_list.append('Contract Related')
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if row['Provider']:
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group_list.append('Provider')
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if row['Timeline']:
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group_list.append('Timeline')
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if row['Carveout Indicator']:
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group_list.append('Carveout Indicator')
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if row['Carveout Methodology']:
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group_list.append('Carveout Methodology')
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entry_dict = {
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"contract_name": row['Contract Name'],
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"groups": group_list,
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"contract_source_path": "contracts_landing_zone/"+batch_id+"/"+row['Contract Name']
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}
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contract_list.append(entry_dict)
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myobj = {
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"s3_bucket": client_bucket,
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"batch_id": batch_id,
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"client_name": client,
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"username": user_mail,
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"contract_list": contract_list
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}
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buttons = st.columns([0.8, 0.2])
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with buttons[0]:
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st.download_button("Download Table", csv, "file.csv", "text/csv", key='download-csv')
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with buttons[1]:
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if st.button("Run Doczy.AI Pipeline"):
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# csv_buf = StringIO()
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# additional_info.to_csv(csv_buf, header=True, index=False)
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# csv_buf.seek(0)
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# s3_client.put_object(Bucket='doczy-dev-infra-raw-data-ingestion', Body=csv_buf.getvalue(), Key='training_interface/request_submission.csv')
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# csv_buf = StringIO()
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# edited_df.to_csv(csv_buf, header=True, index=False)
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# csv_buf.seek(0)
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# s3_client.put_object(Bucket='doczy-dev-infra-raw-data-ingestion', Body=csv_buf.getvalue(), Key='training_interface/contract_config.csv')
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# try:
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# save_to_sf('load_request_and_contract_submissions', request_submission_file_name = "request_submission.csv", contract_config_file_name = "contract_config.csv")
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# except Exception as e:
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# st.write(e)
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response = requests.post(doczy_pipeline, json = myobj)
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if response.status_code >= 200 and response.status_code < 300:
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st.write("Success")
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# st.write(myobj)
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else:
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st.write("Failed")
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# st.write(response.text)
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