AI-Research-Agent

📰 Multi-Agent HackerNews Research Assistant

This Streamlit app enables powerful AI-driven research on top HackerNews stories and users using a team of LLM-based assistants. Built with GPT-4o and the Agno agent framework, it's your go-to tool for content discovery, blogging, and trend analysis.

🚀 Features

• 📖 Research top HackerNews stories
• 👤 Analyze influential users and their activity
• 🧠 Use a multi-agent system with story/user specialists and a coordination assistant
• ✍️ Generate blog posts, social media content, or summary reports

🛠️ Quickstart

1. Clone the Repository

git clone https://github.com/CodeWithHarshAI/AI-Research-Agent.git
cd AI-Research-Agent

2. Install Dependencies

pip install -r requirements.txt

Or install manually:

pip install streamlit agno openai

3. Setup OpenAI API Key

You can:

• Set it as an environment variable:

  export OPENAI_API_KEY=your-key-here

• Or store it in a .env file in the project root:

  OPENAI_API_KEY=your-key-here
  

4. Run the App

streamlit run research_agent.py

⚙️ How It Works

• The app initializes three agents:
  • story_researcher: Extracts insights from HackerNews stories.
  • user_researcher: Digs into HackerNews user behavior.
  • hn_assistant: Delegates tasks and synthesizes responses.
• You enter a research question or topic.
• Agents coordinate to pull real-time data and generate insightful responses via GPT-4o.
• The result can be saved or shared as a report or blog post.

📄 File Structure

.
├── research_agent.py             # Main streamlit interface
├── research_agent_llama3.py      # Optional variant with LLaMA3 support
├── requirements.txt              # Project dependencies
└── README.md                     # You're here!

📚 License

MIT License

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Made with 🤖 by Harsh
GitHub: CodeWithHarshAI