NotYahoo

A comprehensive financial analysis platform with AI-powered stock predictions, market sentiment analysis, and an interactive financial advisor chatbot.

Features

• 📈 Stock Prediction Service: Get AI-generated predictions for stock performance
• 📰 Market Sentiment Analysis: Analyze market sentiment based on news articles
• 💬 Interactive Chatbot: Get answers to financial questions and personalized investment recommendations
• 📊 Portfolio Management: Track and manage your investments
• 📱 Responsive UI: Modern interface built with React and Chakra UI

Tech Stack

• Frontend: React, Chakra UI, React Router
• Charts & Visualization: Recharts
• Runtime: Bun
• AI & ML Libraries: LangChain, OpenAI
• HTTP Client: Axios
• Package Manager: Bun

Installation & Setup

Prerequisites

• Bun (latest version)

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/NotYahoo.git
   cd NotYahoo
   

2. Install dependencies:

   bun install
   

3. Set up environment variables: Create a .env file in the root directory with the following variables:

   VITE_PREDICTION_SERVICE_URL=http://localhost:8000
   VITE_SENTIMENT_SERVICE_URL=http://localhost:8092
   VITE_OPENAI_API_KEY=your_openai_api_key
   

4. Start the development server:

   bun run dev
   

5. Open your browser and navigate to http://localhost:5173

API Services

Stock Prediction Service

Endpoint: http://localhost:8000/docs/{ticker}

Sample Response:

{
  "symbol": "AAPL",
  "price": 150.25,
  "timestamp": "2024-03-21T00:00:00",
  "confidence_score": 0.85,
  "model_type": "lstm"
}

Market Sentiment Analysis

Endpoint: http://localhost:8092/analyze/{ticker}

Sample Data Format:

[
  {
    "url": "string",
    "title": "string",
    "ticker": "string",
    "content": "string",
    "date": "string",
    "sentiment_scores": {
      "positive": 0.1,
      "neutral": 0.2,
      "negative": 0.7
    }
  }
]

API Client Implementation

The application uses a centralized API client service to interact with backend services:

• Modular Architecture: Each microservice has its own client with appropriate configuration
• Type Safety: All API requests and responses are fully typed
• Error Handling: Comprehensive error catching and reporting
• Extensibility: Generic methods make it easy to add new service endpoints

Example Usage

// Get stock prediction
const stockPrediction = await apiService.getStockPrediction("AAPL");

// Get sentiment analysis
const sentimentData = await apiService.getSentimentAnalysis("AAPL");

// Get historical data
const historicalData = await apiService.getHistoricalData("AAPL", "1y", "1d");

Interactive Chatbot

The platform features an AI-powered chatbot that can:

• Answer questions about stock data and financial concepts
• Provide personalized investment recommendations
• Analyze user preferences and history to offer tailored advice

Building for Production

bun run build

The built files will be in the dist directory.

License

This project is licensed under the terms found in the LICENSE file.