README.md

metadata

title: AI News Sentiment Analyzer
emoji: 🤖
colorFrom: blue
colorTo: purple
sdk: streamlit
sdk_version: 1.28.0
app_file: src/streamlit_app.py
pinned: false

🤖 AI News Sentiment Analyzer

An interactive web application that fetches the latest AI-related news and analyzes the sentiment of headlines and articles. Built with Python, Streamlit, and powered by NewsAPI.

🚀 Live Demo

🌐 Try it live: https://huggingface.co/spaces/ai-sentiment-group/BootcampFinalProject

🛠️ Installation

Prerequisites

• Python 3.9+
• NewsAPI key (get free at newsapi.org)

Setup Instructions

1. Clone the repository

   git clone https://github.com/alexoh2bd/BootcampFinalProject
   cd BootcampFinalProject
   

2. Create virtual environment

   # macOS/Linux
   python3 -m venv .venv
   source .venv/bin/activate
   

3. Install dependencies

   pip install -r requirements.txt
   

4. Set up environment variables

   Create a .env file in the project root:

   NEWSAPI_KEY=your_newsapi_key_here
   

🎯 Usage

Web Application

Run the Streamlit app:

streamlit run src/streamlit_app.py

Then open your browser to http://localhost:8501

Command Line Interface

For quick sentiment analysis:

# Basic usage
python src/cli_demo.py

# Custom search query
python src/cli_demo.py --query "ChatGPT" --days 3

# Filter to specific sources
python src/cli_demo.py --sources "techcrunch,wired" --max-articles 5

# Show only positive articles
python src/cli_demo.py --positive-only

# Show detailed sentiment analysis
python src/cli_demo.py --sentiment-only

CLI Options

• --query, -q: Search query (default: "artificial intelligence")
• --days, -d: Days to look back (default: 7)
• --sources, -s: Comma-separated news sources
• --max-articles, -m: Maximum articles to display (default: 10)
• --positive-only: Show only positive sentiment articles
• --negative-only: Show only negative sentiment articles
• --sentiment-only: Show only sentiment analysis summary

🔧 Technical Architecture

flowchart TB
    subgraph Frontend["🎨 Frontend Layer"]
        A["🌐 Streamlit UI"]
        B["💻 CLI Interface"]
    end
    
    subgraph Application["⚙️ Application Layer"]
        C["api_handler.py<br/>🔧 Core Logic"]
        D["streamlit_app.py<br/>📊 Web Framework"]
        E["cli_demo.py<br/>⌨️ Command Line"]
    end
    
    subgraph Processing["🧠 Data Processing"]
        F["TextBlob + VADER<br/>Sentiment Engines"]
        G["Plotly<br/>Visualizations"]
        H["Pandas<br/>Data Processing"]
    end
    
    subgraph External["🌐 External Services"]
        I["📡 NewsAPI<br/>TechCrunch, Wired, etc."]
        J["🔐 Environment<br/>API Keys"]
    end
    
    A --> D
    B --> E
    D --> C
    E --> C
    C --> F
    C --> H
    D --> G
    C --> I
    C --> J
    
    classDef frontend fill:#1f6feb,stroke:#58a6ff,stroke-width:2px,color:#f0f6fc
    classDef application fill:#2ea043,stroke:#3fb950,stroke-width:2px,color:#f0f6fc
    classDef processing fill:#a371f7,stroke:#d2a8ff,stroke-width:2px,color:#f0f6fc
    classDef external fill:#f85149,stroke:#ff7b72,stroke-width:2px,color:#f0f6fc
    
    class A,B frontend
    class C,D,E application
    class F,G,H processing
    class I,J external

📈 Example Output

CLI Example

🤖 AI News Sentiment Analyzer
==================================================

🔍 Searching for: "artificial intelligence"
📅 Looking back: 7 days

📰 Found 43 articles

Sentiment Distribution:
  😊 Positive: 18 articles (41.9%)
  😐 Neutral: 15 articles (34.9%)
  😞 Negative: 10 articles (23.2%)

📄 Top 10 Articles:
--------------------------------------------------------------------------------
 1. 😊 [TechCrunch] 2024-01-20 14:30
    AI startup raises $50M for breakthrough in healthcare diagnosis
    Sentiment: Positive (Score: 0.45)
    📝 Revolutionary AI technology promises to transform medical diagnosis...
    🔗 https://techcrunch.com/...

 2. 😞 [Reuters] 2024-01-20 12:15
    Concerns grow over AI job displacement in manufacturing
    Sentiment: Negative (Score: -0.32)
    📝 Labor unions express worry about automation replacing workers...
    🔗 https://reuters.com/...

🤝 Contributing

This project was built as part of the Duke AIPI 503 Bootcamp.

Development Setup

1. Fork the repository
2. Create a feature branch: git checkout -b feature/some-feature
3. Make your changes and commit: git commit -m 'Add some feature'
4. Push to the branch: git push origin feature/some-feature
5. Open a Pull Request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.