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Financier

AI-powered personal finance management API

⚠️ Work in progress

As much as I love to work on this project fulltime, I still have a job that I love.

🧠 What is it?

Basically a glorified bookkeeper, financial coach, and financial manager. I wanted to leverage the use of OpenAI models to create an assistant that will:

  • keep track of my expenses
  • generate reports
  • remind me of a money-related event
  • make me feel good about my financial health (or not)

Features

  1. 📃 Create, list, read, update, delete income and expense items.
  2. 📸 Upload a photo of a receipt and let the assistant book it for you.
  3. 📈 Generate daily, monthly, yearly reports of your finances.
  4. 💪🏽Set budgets (daily and weekly).
  5. 📨 Receive emails about alerts and notifications.
  6. ⛰️ Set financial goals.
  7. 👨🏽 Ask the assistant about your finances.

Installation

  1. Use poetry for the project.
  2. Define .env with the following contents:
STAGE=<stage>
APP_NAME=<name>
PYTHON_PATH=${workspaceDirectory}

Creating the Lambda layers

All the requirements are found in the financier/functions_stack/layers folder. We are using pydantic and there is a special build needed for it to make it working with Lambda.

pip install --platform manylinux2014_x86_64 --implementation cp --python-version 3.12 --only-binary=:all: --upgrade pydantic --target <directory>

Make sure to update this when you are using a new python package.

Running Local Development

  1. Enable your environment.
  2. Go to financier/functions_stack/
  3. Run local FastAPI development server,
fastapi dev fastapi_lambda.py

Quality

The project uses: isort, ruff, and black for code formatting. I've created a .bat file to run the necessary steps.

runner.bat

This will be improved in the future as I am trying to make tox work for the project.

🛣️ Roadmap

Phase 1

Initial setup.

  • Initialize project structure
  • Setup project
  • Setup tests

Phase 2

Simple proof of concept for data management.

  • Data modelling
    • Expense
  • Database stack
    • DynamoDB setup
  • API stack
    • Create
    • Read
    • List
    • Update
    • Delete
  • Lambda stack
    • Setup lambda layers
    • Create lambda layer creation script
    • Create
    • List
    • Read
    • Update
    • Delete
  • Convert function creations to use YAML loading

Phase 3

Securing our application.

  • Stardardize IAM roles
  • Cognito setup
    • Identity pools
  • API Gateway authorizer

Phase 4

Setup the assistant

  • Write OpenAI model code for the assistant.
  • Interface for the Financier API and the assistant API.

Phase 5

Assistant features

  • Tools for the assistant
    • Reports generator
    • Chat
    • Photo manager

Phase 6

More assistant features

  • Budget
  • Alarms
  • Goals