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3.13+](https://img.shields.io/badge/python-3.13+-blue.svg)](https://www.python.org/downloads/)\n[![CrewAI](https://img.shields.io/badge/Framework-CrewAI-red.svg)](https://www.crewai.com/)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n\nA powerful multi-agent system built with **CrewAI** that automates the process of discovering, summarizing, and curating daily news reports on specific topics.\n\n---\n\n## 🔄 Workflow\n\nThe system employs a sequential multi-agent orchestration to transform a simple topic into a professional news briefing.\n\n```mermaid\ngraph TD\n    %% Styling Definitions\n    classDef agent node font-weight:bold\n    classDef hunter fill:#f9f,stroke:#333,stroke-width:2px,color:#000\n    classDef summarizer fill:#bbf,stroke:#333,stroke-width:2px,color:#000\n    classDef curator fill:#dfd,stroke:#333,stroke-width:2px,color:#000\n    classDef file fill:#fff,stroke:#333,stroke-dasharray: 5 5,color:#000\n\n    Start((Input: Topic)) --> Hunter\n\n    subgraph \"Phase 1: Discovery\"\n        Hunter[news_hunter_agent]:::hunter -->|SerperDev & Scrape| ContentHarvest[(content_harvest.md)]:::file\n    end\n\n    ContentHarvest --> Summarizer\n\n    subgraph \"Phase 2: Analysis\"\n        Summarizer[summarizer_agent]:::summarizer -->|Multi-tier Summarization| Summary[(summary.md)]:::file\n    end\n\n    Summary --> Curator\n\n    subgraph \"Phase 3: Editorial\"\n        Curator[curator_agent]:::curator -->|Final Assembly| FinalReport[(final_report.md)]:::file\n    end\n\n    FinalReport --> End((Final News Briefing))\n\n    %% Additional styling\n    style Start fill:#f5f5f5,stroke:#333\n    style End fill:#f5f5f5,stroke:#333\n```\n\n---\n\n## 🌟 Key Features\n\n- **Multi-Agent Orchestration**: Specialized agents for high-quality news delivery.\n- **Automated Web Search**: Uses **SerperDev** to find the most relevant and credible news articles.\n- **Intelligent Web Scraping**: High-performance scraping using **Playwright** and **BeautifulSoup** to extract clean content from article pages.\n- **Hierarchical Summarization**: Generates multi-tier summaries (Headline, Executive, and Comprehensive) for different reader needs.\n- **Publication-Ready Reports**: Assembles a professional final report in Markdown format.\n\n---\n\n## 🏗️ Architecture\n\n### 🤖 Agents\n\n1.  **Senior News Intelligence Specialist (`news_hunter_agent`)**:\n    *   **Goal**: Discover and collect relevant, credible news articles.\n    *   **Tools**: `SerperDevTool`, `scrape_tool`.\n2.  **Expert News Analyst (`summarizer_agent`)**:\n    *   **Goal**: Transform raw articles into clear, multi-level summaries.\n    *   **Tools**: `scrape_tool`.\n3.  **Senior News Editor (`curator_agent`)**:\n    *   **Goal**: Curate summaries into a cohesive, professional narrative.\n\n### 📋 Tasks\n\n- **Content Harvesting**: Searching for articles, filtering by credibility/relevance, and extracting full text.\n- **Multi-Tier Summarization**: Creating tweet-style headlines, executive summaries, and detailed analysis.\n- **Final Report Assembly**: Combining all work into a premium daily briefing.\n\n---\n\n## 📁 Project Structure\n\n```text\n.\n├── config/\n│   ├── agents.yaml      # Agent roles and backstories\n│   └── tasks.yaml       # Task definitions and process flow\n├── output/              # Generated markdown reports\n├── .env                 # Environment variables (API Keys)\n├── main.py              # Entry point & CrewAI orchestration\n├── tools.py             # Custom scraping & search tools\n└── pyproject.toml       # Project dependencies & metadata\n```\n\n---\n\n## 🛠️ Setup & Installation\n\n### Prerequisites\n\n- **Python**: 3.13 or higher.\n- **uv**: A fast Python package manager (recommended).\n- **Playwright**: For web scraping (will be installed automatically via dependencies).\n\n### 1. Clone the repository\n\n```bash\ngit clone <repository-url>\ncd AI-Agents.News_Reader_Agent\n```\n\n### 2. Install dependencies\n\nUsing `uv`:\n\n```bash\nuv sync\n```\n\n### 3. Environment variables\n\nCopy the example environment file and fill in your API keys:\n\n```bash\ncp .env.example .env\n```\n\nFill in the following:\n\n- `OPENAI_API_KEY`: Your OpenAI API key (for models like `o4-mini-2025-04-16`).\n- `SERPER_API_KEY`: Your Serper.dev API key for web search.\n\n### 4. Install Playwright browsers\n\n```bash\nuv run playwright install chromium\n```\n\n---\n\n## 🚀 Usage\n\nRun the agent simply by executing:\n\n```bash\nuv run python main.py\n```\n\nBy default, the agent searches for **\"Trends of Korea-Japan couples\"**. You can modify the input topic in `main.py`:\n\n```python\nresult = NewsReaderAgent().crew().kickoff(inputs={\"topic\": \"Your Topic Here\"})\n```\n\n---\n\n## 📈 Output\n\nGenerated reports are saved in the `output/` directory:\n\n- `content_harvest.md`: Raw collected articles and metadata.\n- `summary.md`: Multi-tier summaries for each article.\n- `final_report.md`: The curated, publication-ready news briefing.\n\n---\n\n## 🧰 Tech Stack\n\n- **Framework**: [CrewAI](https://www.crewai.com/)\n- **LLM**: OpenAI (o4-mini-2025-04-16)\n- **Search**: [Serper.dev](https://serper.dev/)\n- **Scraping**: [Playwright](https://playwright.dev/python/), [BeautifulSoup](https://www.crummy.com/software/BeautifulSoup/)\n- **Project Management**: [uv](https://github.com/astral-sh/uv)\n\n---\n","readmeExcerpt":"📰 News Reader AI Agent 🚀 $1 $1 $1 A powerful multi-agent system built with **CrewAI** that automates the process of discovering, summarizing, and curating daily news reports on specific topics. --- 🔄 Workflow The system employs a sequential multi-agent orchestration to transform a simple topic into a professional news briefing. --- 🌟 Key Features - 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