FyraFinlyze A smart personal finance assistant chatbot using Groq LLM and Python.

--Features

Upload .xlsx or .csv files Chat with your financial data in natural language Get automated insights and summaries Powered by Groq’s high-speed inference API Simple and elegant Streamlit UI with dark mode API-key based configuration (safe for future model changes)

--Tech Stack

Python 3.10+ Streamlit – UI Framework Pandas – Data processing Groq API – LLM engine for fast response generation OpenAI-compatible models via Groq

--Set Your Groq API Key

Visit https://console.groq.com Sign in → Navigate to API Keys Generate a new key and copy it. code : setx GROQ_API_KEY "your_api_key_here" (for windows) code: export GROQ_API_KEY="your_api_key_here" (for macbook)

--Run the Application

--How It Works

User uploads a .xlsx or .csv financial file The app reads it using Pandas User asks natural questions like: “What’s my total spending this month?” “Which category has the highest expense?” The query is sent to Groq’s LLM API The model processes the question and data, returning a clean answer Streamlit displays the result beautifully in the chat UI.

--About the Groq API

Groq provides ultra-fast inference using their LPU (Language Processing Unit) technology. The Groq API works just like the OpenAI API. Current models include: mixtral-8x7b llama3-8b-8192 gemma-7b-it

--If a model gets deprecated in the future:

Go to https://console.groq.com/docs/models Choose a new available model name Replace it in your code Restart the app That’s it — no further code change needed!

--Future Model Decommissioning – What to Do

Groq (like OpenAI) may retire old models. If your current model stops working: Visit the Groq API Models page Pick a new active model (e.g., llama3-70b if available) Update this line in your code: model = "new_model_name"

--Author

Milan Manoj Jain University, Bangalore Data Science & Analytics Student