Stock Price AI Chatbot

Overview

This project demonstrates how to build an AI-powered stock analysis chatbot using DeepSeek's language model, Python, and Streamlit. The chatbot provides real-time stock market insights and analysis through natural language interaction, making it easier for users to understand market trends and make informed decisions.

Key Features

AI-Powered Chat Interface: Natural language processing for stock market queries using DeepSeek's advanced language model
Real-time Data Integration: Live stock price data through Financial Modeling Prep API
Interactive Visualization: Candlestick charts showing 5 months of historical price data
KPI Metrics: Track current price, highs, lows, and volume
Multi-Stock Support: Analysis for popular stocks like AAPL, TSLA, and NVDA
Prebuilt Example Prompts: Suggested questions for quick analysis

Core Components

Frontend (Streamlit): Interactive web interface with stock selection, candlestick charts, and chat functionality
AI Integration (DeepSeek): Natural language processing for analyzing stock data and generating insights
Data Source (Financial Modeling Prep): Real-time and historical stock price data
Data Visualization (Plotly): Interactive candlestick charts and technical indicators

Key Technologies

Python for backend development and data processing
Streamlit for creating the web interface
DeepSeek's language model for AI-powered analysis
Financial APIs for real-time market data
Plotly for interactive data visualization
Pandas for data manipulation and analysis

Development Process

Environment Setup: Configuration of development environment and required dependencies
API Integration: Implementation of stock data fetching and AI model integration
Frontend Development: Creation of an intuitive user interface with Streamlit
Data Visualization: Implementation of interactive charts and metrics display
Testing & Optimization: Comprehensive testing and performance optimization
Deployment: Deployment to Streamlit Cloud for public access