boladeE
82fe3608d2
- Introduced a Config dataclass in config.py to manage API keys, RSS feeds, and directory paths more effectively. - Updated the NewsFetcher class to include retry logic for fetching articles from RSS feeds. - Modified the EmbeddingGenerator and NewsRecommender classes to utilize the new configuration structure. - Enhanced main.py to implement API token verification for secure access to news fetching and recommendations.
107 lines
3.1 KiB
Markdown
107 lines
3.1 KiB
Markdown
# DS Task AI News
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An AI-powered news application that fetches, processes, and recommends news articles based on your interests.
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## Overview
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DS Task AI News is a web application that uses AI technologies to fetch, analyze, and recommend news articles. The application fetches news from various RSS feeds, processes them using AI, and provides personalized insights and recommendations.
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## Features
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- **Latest News**: View the latest news articles fetched from various RSS feeds.
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- **News Recommendations**: Get personalized news recommendations based on your interests.
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- **AI Insights**: Receive AI-generated insights about news articles.
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- **Article Summaries**: Get concise summaries of individual articles.
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## Technologies Used
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- **FastAPI**: Web framework for building APIs.
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- **Jinja2**: Template engine for rendering HTML.
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- **Tailwind CSS**: Utility-first CSS framework for styling.
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- **feedparser**: Library for parsing RSS feeds.
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- **BeautifulSoup**: Library for parsing HTML.
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- **Cohere**: API for generating embeddings.
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- **Pinecone**: Vector database for storing and retrieving embeddings.
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- **Groq**: API for generating insights and summaries.
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## Getting Started
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### Prerequisites
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- Python 3.8 or higher
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- pip (Python package manager)
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- Internet connection
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### Installation
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1. Clone the repository:
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```
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git clone https://github.com/yourusername/ds_task_ai_news.git
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cd ds_task_ai_news
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```
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2. Install the required dependencies:
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```
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pip install -r requirements.txt
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```
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3. Set up the required environment variables:
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- Create a `.env` file in the root directory with the following content:
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```
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GROQ_API_KEY=your_groq_api_key
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PINECONE_API_KEY=your_pinecone_api_key
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PINECONE_ENVIRONMENT=your_pinecone_environment
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PINECONE_INDEX=your_pinecone_index
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```
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4. Run the application:
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``` python backend/main.py
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```
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5. Open your web browser and navigate to `http://localhost:8000`.
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## Documentation
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- [API Documentation](docs/API_Documentation.md): Detailed documentation of the API endpoints.
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- [Technical Documentation](docs/Technical_Documentation.md): Technical details of the application architecture and components.
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- [User Guide](docs/User_Guide.md): Guide for using the application.
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## Project Structure
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```
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ds_task_ai_news/
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├── backend/
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│ ├── main.py
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│ ├── news_fetcher.py
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│ ├── embeddings.py
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│ ├── vector_store.py
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│ ├── recommender.py
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│ ├── config.py
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│ └── templates/
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│ ├── base.html
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│ ├── home.html
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│ ├── news.html
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│ └── recommendations.html
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├── data/
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│ ├── raw_news/
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│ └── processed_news/
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├── docs/
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│ ├── API_Documentation.md
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│ ├── Technical_Documentation.md
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│ └── User_Guide.md
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└── requirements.txt
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```
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## License
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This project is licensed under the MIT License - see the LICENSE file for details.
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## Acknowledgments
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- [FastAPI](https://fastapi.tiangolo.com/)
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- [Tailwind CSS](https://tailwindcss.com/)
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- [Cohere](https://cohere.ai/)
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- [Pinecone](https://www.pinecone.io/)
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- [Groq](https://groq.com/)
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