FINSAGE: AI-Powered Personal Finance Chatbot

FinSage is an advanced personal finance chatbot designed to empower users by offering personalized financial guidance and dynamic visualizations. By utilizing AI-driven insights, FinSage helps users make informed financial decisions, build sustainable savings habits, and reach both short- and long-term financial goals. With features such as personalized savings plans, interactive financial projections, and educational content tailored to each user's needs, FinSage enhances financial literacy. The chatbot also delivers real-time financial advice, tracks user progress, and offers easy-to-understand visualizations of spending, saving, and investment patterns, all while fostering financial confidence and independence.

Features

• Personalized Financial Advice: Tailored guidance to help manage finances and reach goals.

• Dynamic Visualizations: Interactive charts (pie, scatter, bar, box) for deeper insights.

• NLP Integration: Efficiently processes and understands user queries.

• RAG (Retrieval-Augmented Generation): Uses Together AI’s RAG for accurate, context-aware responses.

• Embeddings with SentenceTransformers: Provides relevant answers via semantic similarity.

• Streamlit Interface: Easy-to-use web interface for seamless interaction.

• ReactJS Frontend: Modern, responsive design for a better user experience.

Screenshots

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Setup Guide

Follow these steps to set up and run the project locally:

1. Clone the repository

First, clone the repository to your local machine:

git clone https://github.com/RonitJariwala/FinSage.git
cd FinSage

2. Set up the backend

Navigate to the backend directory:

cd backend

Install the required dependencies using pip:

pip install -r requirements.txt

Run the backend server:

streamlit run app.py

3. Set up the frontend:

Navigate to the frontend directory:

cd ../frontend

Install dependencies:

npm install

Start the development server:

npm start

Tech Stack

• Python: Used for backend development and data processing.
• Streamlit: For building interactive web applications with the backend.
• ReactJS: For frontend development, creating dynamic and responsive UIs.
• SentenceTransformers: Utilized for natural language processing and generating sentence embeddings.
• Together AI’s RAG Pipeline: Used for the retrieval-augmented generation (RAG) pipeline in the chatbot for efficient question-answering.