Financial AI Prompt

Deployed URL:

http://dinojump.online/ (using http for temporary)

Structure:

Express.js(Backend) + React.js(Frontend)

Functionality:

Sends a user-input prompt to the backend, processes it via OpenAI and FMP APIs, and displays the summary

Deployment Considerations:

.end setup required, run backend and frontend servers separately

License

This project is licensed under the MIT License - see the LICENSE file for details.

📂 Proejct Introduction

The application UI image

This project offers a seamless and interactive chat experience that can answer various financial-related questions with real-time AI responses and data fetching, helping users gain valuable insights into companies' financials and key management comments

Requirements:

• Backend Integration
  • Use the OpenAI API to generate summaries and responses
  • Use the FMP API to fetch financial data and metrics
• Frontend Interface
  • Build a basic UI chat interface (preferably with React/Next.js) that allows users to input queries
  • The UI should interact with the backend and display the AI-generated summaries and financial data responses

⏲️ Development Period

• Feb.13th.2025 ~ Feb.18th.2025

🚀 Tech Stack & Testing Tools

Backend

• Node.js: Backend runtime environment
• Express.js: Lightweight web framework
• dotenv: Environment variable management
• body-parser: Parses JSON and URL-encoded data
• CORS: Enables cross-origin resource sharing
• Axios: HTTP client for API requests
• Jest: JavaScript testing framework
• nodemon: Development tool for auto-reloading server during changes
• supertest: Testing library for HTTP assertions

Frontend

• React.js: JavaScript library for building user interfaces
• React Icons: Library for adding icons to React components
• react-scripts: Set of scripts for React development
• web-vitals: Measures vital performance metrics for web apps
• Sass (sass): CSS preprocessor for more dynamic and manageable styles
• Jest: Testing framework for JavaScript
• @testing-library/react: Library for testing React components
• @testing-library/jest-dom: Custom matchers for Jest tests with DOM elements
• @testing-library/user-event: Simulates user events for testing UI interactions

📂 Project Structure

Backend

backend/
│── node_modules/                   # Installed dependencies
│── src/
│   ├── controllers/                # Business logic for handling requests
│   │   ├── financialControllers.js
│   │   ├── openaiControllers.js
│   ├── routes/                     # Route definitions
│   │   ├── financialRoutes.js
│   │   ├── openaiRoutes.js
│   ├── services/                   # External API interaction & business logic
│   │   ├── fmpService.js           # Handles Financial Modeling Prep API calls
│   │   ├── openaiService.js        # Handles OpenAI API calls
│   ├── app.js                      # Express server configuration
│── tests/                          # Unit tests
│   ├── controllers/
│   │   ├── openaiControllers.test.js
│   ├── services/
│   │   ├── fmpService.test.js
│   │   ├── openaiService.test.js
│── .env                            # Environment variables
│── .gitignore                      # Git ignore file
│── package.json                    # Project dependencies and scripts
│── package-lock.json               # Lock file for dependency versions

Frontend

frontend/
│── node_modules/                   # Installed dependencies
│── public/                         # Static assets like index.html, icons, etc.
│── src/
│   ├── components/                 # Reusable UI components
│   │   ├── Footer.js
│   │   ├── Footer.scss
│   │   ├── Footer.test.js
│   ├── pages/prompt                # Pages for the prompt functionality
│   │   ├── input/                  # Components for input functionality
│   │   │  ├── InputPrompt.js
│   │   │  ├── InputPrompt.scss
│   │   │  ├── InputPrompt.test.js
│   │   ├── output/                 # Components for output functionality
│   │   │  ├── OutputPrompt.js
│   │   │  ├── OutputPrompt.scss
│   │   │  ├── OutputPrompt.test.js
│   ├── app.js                      # Main app component
│   ├── app.scss                    # Global styles
│   ├── app.test.js                 # Unit tests for the main app component
│── .env                            # Environment variables (e.g., backend API URL)
│── .gitignore                      # Git ignore file
│── package.json                    # Project dependencies and scripts
│── package-lock.json               # Lock file for dependency versions

⚙️ Environment Variables (.env)

This project uses .env to manage API keys and configuration. Before starting both backend & frontend, you need to create a .env file with the following format:

Backend

PORT= { 5000 }
FMP_API_KEY= { YOUR_FINANCIAL_MODELING_PREP_API_KEY }
FMP_URL= { FMP_URL }
CHATGPT_API_KEY= { YOUR_CHATGPT_API_KEY }
CHATGPT_URL= { CHAT_GPT_API_URL }

Frontend

REACT_APP_BACKEND_URL= { YOUR_LOCAL_BACKEND_URL }

📌 APIs & External Services

OpenAI API: Generates text summaries and responses using ChatGPT

Financial Modeling Prep API: Fetches and analyzes financial data

🏃Getting started in the local environment

Prerequisites

Before you begin, ensure you have the following installed: Node.js (Recommended version: v16 or higher) npm (Node package manager, comes with Node.js)

Setting Up

Clone the project repository to your local machine:

git clone https://github.com/TonyKim9401/FinancialPrompt.git

Backend

Navigate to the project directory

cd FinancialPrompt/backend

Install dependencies

npm install

Run test code

npx jest

Run the local development server

npm run dev

Send test curl request to check backend is running

curl -X POST http://localhost:5010/api/v1/finchat/openai/summarize \
     -H "Content-Type: application/json" \
     -d "{\"content\": \"Summarize Spotify's latest conference call.\"}"

This repository includes a Postman collection for interacting with the FinChat API. The Postman file has been attached; please use it for backend testing.

• see the Postman Collection file for details.

Frontend

Navigate to the project directory

cd FinancialPrompt/frontend

Install dependencies

npm install

Run the local development server

npm start

Run test code

npm test

Open application on browsers

Mac environment

open http://localhost:3000/contacts

Window environment

start http://localhost:3000/contacts

📌 API Endpoints

POST /api/v1/finchat/openai/summarize

• Description: Calls the OpenAI API to summarize user input
• Request Format

{
   "content": "What is Tesla's expected earnings next quarter?"
}

• Response Example

{
   "answer": "Based on the most recent data available from the financial modeling prep data (fmpData), Tesla's expected earnings for ..."
}

📑 Project Review

Strengths:

• The core requirements were met
• The UI was kept simple and non-complex
• Non-relevant financial or company-related queries were blocked upfront for faster response times
• BDD was applied to ensure readability and consistency of test code
• Different AI models were utilized based on the complexity of the questions to reduce costs when using the ChatGPT API

Highlights:

• The previous experience of using ChatGPT API for personal projects was very helpful
• First-time use of the React Icons library to componentize icons like GitHub, LinkedIn, and E-mail
• Realized the importance of test code beyond just testing purposes, as it can better reflect the nature and objectives of the application
• Gained more knowledge and experience with the ChatGPT API usage

Additional Areas for Improvement:

• The project direction was initially unclear, which led to wasting over a day in indecision
• Couldn’t implement CI/CD due to time constraints. It would have been ideal to at least run Lint checks and test code validation, and possibly Dockerize the project with AWS CD
• Both React and Express experience were limited, leading to a lack of detail across the code
• The backend and frontend lacked clear hierarchical structure; better modularization of features could have made future maintenance and modifications easier
• Discovered a bit late that the answers from ChatGPT API can vary depending on the API settings
• The response time is slow; if ChatGPT Functions had been used, the frequency of external API calls could have been reduced, improving performance
• Implementing the streaming answer feature from ChatGPT could enhance the professionalism of the UI
• There are many additional features I would like to add, such as user registration, recent search history, and data visualization
• Due to limited experience with writing Read.me files, I referred to many external resources, but I wish it had been more user-friendly and intuitive for someone encountering the project for the first time
• Merged everything directly into the master branch without branching by feature, which was a mistake in terms of version control.

Final Review:

• I found the topic to be interesting, and the requirements were clearly defined, making the goal very clear. However, I regret spending too much time overthinking the overall direction of the application while trying to structure and think through the more flexible aspects of the project. Once I clarified the direction, I was able to move forward with both the backend and frontend as planned. Although there were some challenges with utilizing ChatGPT, I was able to work around them and still achieve professional-level answers. I greatly enjoyed the opportunity to gain more experience using React and Express for this personal project.