In an era where information is paramount, understanding the stock market can feel like navigating a dense and ever-shifting landscape. That's why I embarked on a fascinating project: building an intelligent stock analysis chatbot – a digital companion designed to make market insights more accessible and understandable to anyone, anywhere.
This Python project aims to build a stock analysis chatbot that can respond to user queries about stock market information. It fetches real-time or historical stock data using the Alpha Vantage API, analyzes trends and calculates technical indicators like Simple Moving Averages (SMA) and the Relative Strength Index (RSI). The analyzed data is then stored and retrieved from a ChromaDB instance, enabling Retrieval-Augmented Generation (RAG) to provide contextually relevant answers using a Gemini language model. The chatbot can handle queries for single stocks and also compare multiple stocks, providing concise analyses and interpretations of the data, with an additional evaluation mechanism to assess the quality of the chatbot's responses based on predefined criteria.
This stock analysis chatbot addresses the increasing demand for accessible and intelligent financial information. It empowers users, regardless of their technical expertise, to gain insights into stock market trends and key indicators through natural language interaction.
Watch the Video Walkthrough!
Access the notebook on Kaggle