Files
doczyai-pipelines/streamlit/local/local_interface_2.py
T

229 lines
8.8 KiB
Python

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'])
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)
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")