178 lines
6.5 KiB
Python
178 lines
6.5 KiB
Python
import json
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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_secret, save_to_sf
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from io import StringIO, BytesIO
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from sf_conn import get_client_names, insert_upload_logs
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create_batch_url = 'https://lfksus2t62.execute-api.us-east-2.amazonaws.com/dev/create-batch'
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REDIRECT_URI = 'https://doczy.aarete.com:8500'
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user_list = ['maamseek@aarete.com', 'smahdavian@aarete.com', 'ahinge@aarete.com', 'akadam@aarete.com', 'pkatariya@aarete.com'
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, 'piragavarapu@aarete.com', 'umistry@aarete.com', 'ahutchison@aarete.com', 'bgrunst@aarete.com', 'ddimeglio@aarete.com'
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, 'vnair@aarete.com', 'kminhas@aarete.com', 'fmohiuddin@aarete.com']
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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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st.write("Session Expired.")
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st.stop()
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if user_mail in user_list:
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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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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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# This is the list of client fetched from Snowflake
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# TODO: Need to update the streamlit code to use the client names from this list
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# And use the s3 paths to save the objects for the respective client
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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 = 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 = 'doczy-ai-client-1'
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file_row = st.columns([0.1, 0.8])
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with file_row[0]:
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st.write("**Upload Files**")
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with file_row[1]:
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file_list = st.file_uploader("Upload", type=None, accept_multiple_files=True, label_visibility = "collapsed")
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add_vertical_space(2)
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df = pd.DataFrame(columns=['Contract Name'])
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df['Contract Name'] = file_list
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file_names = []
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buttons = st.columns([0.4, 0.4, 0.2])
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with buttons[1]:
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if st.button("Create Batch"):
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myobj = { "client-bucket-name": client }
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response = requests.post(create_batch_url, json = myobj)
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if response.status_code >= 200 and response.status_code < 300:
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try:
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batch_id = json.loads(json.loads(response.text)['body'])['batch_id']
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landing_zone = json.loads(json.loads(response.text)['body'])['landing_zone']
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except:
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st.write(myobj)
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st.write(response.text)
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batch_id = 'failed_cases'
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landing_zone = 'contracts_landing_zone'
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else:
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st.write("Failed")
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for uploaded_file in file_list:
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stringio = BytesIO(uploaded_file.getvalue())
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stringio.seek(0)
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# s3_client.put_object(Bucket='doczy-dev-infra-raw-data-ingestion', Body=stringio.getvalue(), Key=
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# 'config_interface/'+str(uploaded_file.name))
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s3_client.put_object(Bucket=client, Body=stringio.getvalue(), Key=
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batch_id+'/'+landing_zone+'/'+str(uploaded_file.name))
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# TODO: Test this insert function with snowflake
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upload_log = insert_upload_logs(batch_id, client, str(uploaded_file.name), datetime.now().strftime("%Y-%m-%d %H:%M:%S"), user_mail)
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st.write(upload_log)
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file_names.append(str(uploaded_file.name))
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st.write(f"{batch_id} created")
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st.write(f"Files uploaded to s3://{client}/{batch_id}/{landing_zone}")
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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(df)
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# df = df.reset_index() # make sure indexes pair with number of rows
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# contract_list = []
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# for index, row in 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": "batches/batch_1/"+client+"/"+row['Contract Name']
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# }
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# contract_list.append(entry_dict)
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# contract_list = list(df['Contract Name'])
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# myobj = {
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# "s3_bucket": 'doczy-dev-infra-textract',
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# "batch_id": "1",
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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("Upload to DB"):
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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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# else:
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# st.write("Failed")
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# # st.write(response.text)
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else:
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st.write("Access Denied")
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