330 lines
10 KiB
Python
330 lines
10 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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import time
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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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st.session_state["user_info"] = {
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"mail": "maamseek@aarete.com",
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"displayName": "Mayank Aamseek",
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}
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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(
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"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 = [
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"doczy-ai-client-1",
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"Delaware First Health, Inc.",
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"Community Health Choice, Inc",
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"CareSource Network Partners LLC",
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"HealthNet of Cali",
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"Oklahoma Complete Health, Inc",
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"HealthFirst",
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"Molina Healthcare of TX",
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"AvMed",
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"Arizona Care1st",
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"WellCare New Jersey",
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]
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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(
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"Client Name", (client_list), label_visibility="collapsed", index=None
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) # MODIFIED for Ticket DOC-344
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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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batch_list = [
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"batch_020524103737",
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"batch_090524131433",
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"batch_090524131607",
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"batch_100524123000",
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"batch_130524064322",
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"batch_160524071331",
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"batch_200524213550",
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"batch_250424112237",
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"batch_280524120530",
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"batch_280524121721",
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"batch_280524144222",
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"batch_290524123926",
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"batch_290524164044",
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"batch_310524102029",
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"batch_310524124050",
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"batch_310524162346",
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"batch_310524162631",
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]
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if "sorted_list" not in st.session_state:
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st.session_state.sorted_list = batch_list
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def sort_list(ex_list, sort_by, order):
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if sort_by == "Alphabetical":
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ex_list = sorted(ex_list, reverse=(order == "Descending"))
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elif sort_by == "Create Date":
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ex_list = ex_list if order == "Ascending" else list(reversed(ex_list))
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return ex_list
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col1, col2, col3, col4 = st.columns([0.5, 0.5, 0.5, 0.5])
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with col1:
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sort_by = st.radio("**Sort Batch_IDs**", ("Alphabetical", "Create Date"))
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with col2:
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order = st.radio("", ("Ascending", "Descending"))
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with col3:
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add_vertical_space(2)
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if st.button("Apply"):
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st.session_state.sorted_list = sort_list(batch_list, sort_by, order)
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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(
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"**Batch ID**",
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st.session_state.sorted_list,
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label_visibility="collapsed",
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index=None,
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) # MODIFIED for Ticket DOC-344
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if not batch_id:
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batch_id = "None"
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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), args="Unique")
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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(
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columns=[
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"Contract Name",
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"Unique Key",
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"Pricing Before Carveouts",
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"Contract Related",
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"Provider",
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"Timeline",
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"Carveout Indicator",
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"Carveout Methodology",
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]
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)
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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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file_list = [
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"Boilerplate_TX Amendment Mission Health Network effective_040114 MU.pdf",
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"Custom_TX - MP AMENDMENT - MISSION HEALTH NETWORK - MU.pdf",
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"Delaware First Health_First State Homecare Agency_212260_7 MU.pdf",
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"Molina Healthcare of Texas, Inc. Amendment 4 - HIX ACA__EFF 01012016_MU.pdf",
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]
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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(
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columns=["CLIENT_NAME", "BATCH_ID", "REQUEST_USERNAME", "REQUEST_DATETIME"]
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)
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additional_info.loc[0] = [
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client,
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batch_id,
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st.session_state.user_info["mail"],
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datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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]
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st.write(additional_info)
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st.session_state.contract_count = 0
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contract_list = []
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for index, row in edited_df.iterrows():
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allow_run_for_contract = False
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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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allow_run_for_contract = True
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if row["Pricing Before Carveouts"]:
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group_list.append("Pricing Before Carveouts")
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allow_run_for_contract = True
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if row["Contract Related"]:
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group_list.append("Contract Related")
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allow_run_for_contract = True
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if row["Provider"]:
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group_list.append("Provider")
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allow_run_for_contract = True
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if row["Timeline"]:
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group_list.append("Timeline")
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allow_run_for_contract = True
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if row["Carveout Indicator"]:
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group_list.append("Carveout Indicator")
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allow_run_for_contract = True
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if row["Carveout Methodology"]:
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group_list.append("Carveout Methodology")
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allow_run_for_contract = True
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if allow_run_for_contract:
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st.session_state.contract_count += 1
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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/"
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+ batch_id
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+ "/"
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+ 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(
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"Download Table", csv, "file.csv", "text/csv", key="download-csv"
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)
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with buttons[1]:
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if st.button("Run Doczy.AI Pipeline"):
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if not st.session_state.contract_count == len(edited_df):
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st.error("Select at least one Group No. for every Contract")
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else:
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with st.spinner(
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"Running..."
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): # Feedback to User while API endpoint sends response for DOC-342
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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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time.sleep(5)
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st.write("Success!")
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