doczyai-pipelines/archive/streamlit/local/local_interface_2.py

import json

import boto3
from langchain.prompts import PromptTemplate
from langchain.embeddings.bedrock import BedrockEmbeddings
from langchain.llms.bedrock import Bedrock
from langchain_community.vectorstores import Chroma

# from constants import CHROMA_SETTINGS, EMBEDDING_MODEL_NAME, PERSIST_DIRECTORY, MODEL_ID, MODEL_BASENAME, SOURCE_DIRECTORY, USER_LIST
from langchain.chains import RetrievalQA

import streamlit as st
from streamlit_extras.add_vertical_space import add_vertical_space
from streamlit_pdf_viewer import pdf_viewer  # needs to be installed on the server
import os
import pandas as pd
import numpy as np

# import util
import anthropic
from pydantic import BaseModel
from typing import List
import re
import base64

# from sf_conn import get_snowflake_conn

REDIRECT_URI = "https://doczydev.aarete.com:8502"
# 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:
    st.write("Session Expired.")
    st.stop()

# remove below try except statement if comparison with actual vales is not required
# try:
#     conn = get_snowflake_conn('STG')
#     cur = conn.cursor()
#     query = 'select * from "TRAINING_DATA_RAW"'
#     cur.execute(query)
#     field_values = pd.DataFrame.from_records(iter(cur), columns=[x[0] for x in cur.description])
#     field_values['Document_Name'] = field_values['DOCUMENT_NAME']
# except:
#     # field_values = pd.read_csv('contract_field_values.csv', encoding='unicode_escape', skipinitialspace=True)
#     # field_values = field_values.loc[:, ~field_values.columns.str.contains('Unnamed:')]
#     st.write("Conn failed, unable to fetch data from training data table in Snowflake")

field_values = pd.read_csv(
    "contract_field_values.csv", encoding="unicode_escape", skipinitialspace=True
)
field_values = field_values.loc[:, ~field_values.columns.str.contains("Unnamed:")]

# try:
#     query = 'select * from "PROMPT_CONFIG"'
#     cur.execute(query)
#     fields = pd.DataFrame.from_records(iter(cur), columns=[x[0] for x in cur.description])

#     fields.rename(columns={'FIELD_DESC': 'Field Name'}, inplace = True)
#     fields.rename(columns={'PROMPT': 'Interrogation Question?'}, inplace = True)
#     fields.rename(columns={'GROUP_ID': 'PRIORITY'}, inplace = True)
#     fields.rename(columns={'FIELD_NAME': 'SF_DB_COL_NAME'}, inplace = True)
#     fields.rename(columns={'FM_MODEL_ID': 'llm_selected'}, inplace = True)
# except Exception as e:
#     st.write("Unable to fetch data from Snowflake: ",e)
#     # fields = pd.read_csv('contract_fields.csv', encoding='unicode_escape', skipinitialspace=True)
#     # fields = fields[~fields['SF_COL_NAME'].str.endswith('_PG', na=None)]

fields = pd.read_csv(
    "contract_fields.csv", encoding="unicode_escape", skipinitialspace=True
)
# fields = fields[fields['SF_DB_COL_NAME'].str.endswith('_PG', na=None)]

# change the code below if contract list is fetched from snowflake
s3_client = boto3.client("s3", region_name="us-east-2")
bucket = "doczy-dev-infra-textract"
# objects = s3_client.list_objects_v2(Bucket=bucket, Prefix="training-data/")
# file_list = []
# for obj in objects['Contents']:
#     if not obj['Key'].endswith('/'):
#         file_list.append(obj['Key'])

# # 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",
]

# Replace client_list with this to get client names from s3 buckets
# client_list, s3_paths = get_client_names()
# client_s3_paths = dict(zip(client_list, s3_paths))

client_row = st.columns([0.2, 0.7, 0.1])
with client_row[0]:
    st.write("**Client Name**")
with client_row[1]:
    client = st.selectbox(
        "Client Name", (client_list), label_visibility="collapsed", index=None
    )


# batch_objects = s3_client.list_objects_v2(Bucket=client_bucket
#     , Prefix="contracts_landing_zone/", Delimiter='/')

batch_list = ["d_12132", "d_13345", "i_23423", "i_72223", "b_12345", "b_33452"]


# for prefix in batch_objects['CommonPrefixes']:
#     batch_list.append(prefix['Prefix'][:-1].split('/')[-1])

path_row = st.columns([0.2, 0.7, 0.1])
with path_row[0]:
    st.write("**Batch ID**")
with path_row[1]:
    batch_id = st.selectbox(
        "**Batch ID**", batch_list, label_visibility="collapsed", index=None
    )


# Need to populate file_list with the list of files from the selected client from client_list
# client_bucket = client_s3_paths.get(client)
# bucket = client_bucket
# objects = s3_client.list_objects_v2(Bucket=bucket, Prefix="training-data/")
# file_list = []
# for obj in objects['Contents']:
#     if not obj['Key'].endswith('/'):
#         file_list.append(obj['Key'])

file_list = [
    "Contract_Training_Exercise_Pricing.pdf",
    "Contract_Training_Exercise_SLA.pdf",
]
contract_list = sorted(file_list)

file_row = st.columns([0.2, 0.7, 0.1])
with file_row[0]:
    st.write("**Contract Name**")
with file_row[1]:
    file_name = st.selectbox(
        "Select a file",
        ["All"] + contract_list,
        label_visibility="collapsed",
        index=None,
    )  # MODIFIED - Append 'All' in the front instead of at the end

field_row = st.columns([0.2, 0.7, 0.1])
with field_row[0]:
    st.write("**Field Group**")
with field_row[1]:
    field_group = st.selectbox(
        "Field Group",
        (
            "Unique Key",
            "Contract Related",
            "Pricing Before Carveouts - I",
            "Pricing Before Carveouts - II",
            "Carveout Indicator, Code Type and Code #s - I",
            "Carveout Indicator, Code Type and Code #s - II",
            "Carveout Indicator, Code Type and Code #s - III",
            "Optimize Carving Indic.",
            "Carveout Method - I",
            "Carveout Method - II",
            "Provider",
            "Timeline",
        ),
        label_visibility="collapsed",
        index=None,
    )

if field_group == "Unique Key":
    fields = fields[fields["PRIORITY"] == "A"]
elif field_group == "Contract Related":
    fields = fields[fields["PRIORITY"] == "C"]
elif field_group == "Pricing Before Carveouts - I":
    fields = fields[fields["PRIORITY"] == "B"]
    fields = np.array_split(fields, 2)[0]
elif field_group == "Pricing Before Carveouts - II":
    fields = fields[fields["PRIORITY"] == "B"]
    fields = np.array_split(fields, 2)[1]
elif field_group == "Carveout Indicator, Code Type and Code #s - I":
    fields = fields[fields["PRIORITY"] == "F"]
    fields = np.array_split(fields, 3)[0]
elif field_group == "Carveout Indicator, Code Type and Code #s - II":
    fields = fields[fields["PRIORITY"] == "F"]
    fields = np.array_split(fields, 3)[1]
elif field_group == "Carveout Indicator, Code Type and Code #s - III":
    fields = fields[fields["PRIORITY"] == "F"]
    fields = np.array_split(fields, 3)[2]
elif field_group == "Carveout Methodology - I":
    fields = fields[fields["PRIORITY"] == "G"]
    fields = np.array_split(fields, 4)[0]
elif field_group == "Carveout Methodology - II":
    fields = fields[fields["PRIORITY"] == "G"]
    fields = np.array_split(fields, 4)[1]
elif field_group == "Carveout Method - III":
    fields = fields[fields["PRIORITY"] == "G"]
    fields = np.array_split(fields, 4)[2]
elif field_group == "Carveout Method - IV":
    fields = fields[fields["PRIORITY"] == "G"]
    fields = np.array_split(fields, 4)[3]
elif field_group == "Provider":
    fields = fields[fields["PRIORITY"] == "D"]
elif field_group == "Timeline":
    fields = fields[fields["PRIORITY"] == "E"]

if st.button("Show Results"):
    # query = 'select * from "DOCZY_PIPELINE_RAW_OUTPUT"'
    # cur.execute(query)
    # df2 = pd.DataFrame.from_records(iter(cur), columns=[x[0] for x in cur.description])

    # get this dataframe from snowflake table
    df2 = pd.DataFrame(
        columns=[
            "Contract Name",
            "Field Name",
            "SF_DB_COL_NAME",
            "Snippet",
            "Page Number",
            "Field Extracted Value",
            "Actual Value",
            "Imputed Value",
        ]
    )
    df2.to_csv("temp2.csv", index=False)
    st.subheader("Showing " + client + "  :  " + file_name)

if st.button("Show PDF"):
    if file_name == None or file_name == "All":
        st.error("Choose one specific file.")
    else:
        with st.sidebar:
            st.markdown(
                """
                <style>
                    section[data-testid="stSidebar"] {
                        width: 550px !important; # Set the width to your desired value
                    }
                </style>
                """,
                unsafe_allow_html=True,
            )
            pdf_viewer(file_name, width=1500)

# if st.button("Show PDF"):
#     if file_name == None or file_name == "All":
#         st.error("Choose one specific file.")
#     else:
#         with st.sidebar:
#             with open(file_name, "rb") as f:
#                 base64_pdf = base64.b64encode(f.read()).decode('utf-8')
#             # Embedding PDF in HTML
#             pdf_display = F'<iframe src="data:application/pdf;base64,{base64_pdf}" width="500" height="1000" type="application/pdf"></iframe>'
#             # Displaying File
#             st.markdown(
#                 """
#                 <style>
#                     section[data-testid="stSidebar"] {
#                         width: 600px !important; # Set the width to your desired value
#                     }
#                 </style>
#                 """,
#                 unsafe_allow_html=True,
#             )
#             st.markdown(pdf_display, unsafe_allow_html=True)

df2 = pd.read_csv("temp2.csv")
df2["Imputed Value"] = ""
edited_df = st.data_editor(df2)


@st.cache_data
def convert_df(df):
    return df.to_csv(index=False).encode("utf-8")


csv = convert_df(edited_df)

buttons = st.columns(3)
with buttons[0]:
    # st.button("Save All Imputations")
    st.download_button(
        "Download Table", csv, "file.csv", "text/csv", key="download-csv"
    )
with buttons[1]:
    # st.download_button("Download Table", csv, "file.csv", "text/csv", key='download-csv')
    st.write("")
with buttons[2]:
    if st.button("Kickoff Database Integration"):
        st.write("Stored in DB")