doczyai-pipelines/streamlit/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
import os
import pandas as pd
import numpy as np
import util
import anthropic
from pydantic import BaseModel
from typing import List
import re
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'}
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")

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)]

# 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'])

contract_list = sorted(file_list)

if user_mail in user_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', contract_list + ['All'], label_visibility = "collapsed")

    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")
    
    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)

    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")

else:
    st.write("Access Denied")