Depricated Working on Docs-pdf

Table of Contents

• Description
• Requirements
• Installation
• Running the App Locally with Git
• Running the App Locally with Docker
• Startup Script
• Demo | Deployment
• Details
  • Client-side
  • Server-side

Description

This assignment aims to design and implement a full-stack web application that facilitates the uploading and parsing of a W-2 form. The web application should let users chat and ask specific questions about their W-2 data.

Requirements

• Node

• python

• docker

• supabase account database

• enable auth email in supabase dashboard.

  • also disable email verification for ease of testing.

• enable storage bucket name TaxGPT

• supabase database schema

  create table public.profiles (
    id uuid not null references auth.users on delete cascade,
    file_name text,
    file_content text,
    primary key (id)
  );
  

• get llama api key llama-api

• get llama index api key llama-index

Installation

client .env file

VITE_API_URL=http://127.0.0.1:5555/api
VITE_SUPABASE_URL=<In Supabase Dashboard>
VITE_SUPABASE_ID=<In Supabase Dashboard>
VITE_SUPABASE_ANON_KEY=<In Supabase Dashboard>

server .env file

SUPABASE_URL=<In Supabase Dashboard>
SUPABASE_ANON=<In Supabase Dashboard>
SUPABASE_JWT=<In Supabase Dashboard>
SUPABASE_KEY=<<In Supabase Dashboard>>
LLAMA_API=<llama-api>
LLAMA_PARSE=<llama-index>

Running the app locally with git

client

git clone https://github.com/ZafeerMahmood/taxgptAssignment.git
cd client
npm install
npm run dev

server

cd server
pip install -r requirements.txt
python3 server.py | py server.py

Running the app locally with docker

does not require any environment setup

git clone https://github.com/ZafeerMahmood/taxgptAssignment.git
docker-compose up -d

requires selenium to run auto logins in the user and wait for file input

startup script

cd start
pip install selenium
python3 main.py | py main.py

Demo | Deployment

no longer available

• client demo
• server demo

details

• The client is built using vite react and the server is built using flask.
• for llm i used llama-2b-chat model.
• for parsing w2 form i used llama-index model.
• for database i used supabase.
• for deployment i used google cloud run and cloudflare pages.
• thought process is in ./TODO.md
• requirements are in ./Requirements.md

client-side

• use zustand for state management.
• daisyUI for tailwindcss components.
• supabase-js for auth services.

server-side

• flask for api.
• supabase for database.
• llama for llm.
• llama-index for parsing w2 form.