ClarixMind 🔬

Multi-Agent AI Research System

ClarixMind is a sophisticated multi-agent AI system designed to automate comprehensive web research. Powered by LangChain, Groq (Llama-3.3-70b-versatile), and Tavily, four specialized AI agents collaborate to search, read, write, and critique content, delivering a highly polished research report on any given topic.

✨ Features

• Four Collaborative Agents:
  • 🔍 Search Agent: Gathers recent and relevant web information via the Tavily Search API.
  • 📄 Reader Agent: Scrapes and extracts in-depth contextual data from the top resources.
  • ✍️ Writer Agent: Drafts a detailed research report tailored to your chosen target audience.
  • 🧐 Critic Agent: Reviews, scores, and provides constructive feedback on the generated report.
• Interactive Chat Interface: Ask follow-up questions directly to the generated research report.
• Beautiful UI: Custom-styled Streamlit interface featuring dynamic progress tracking, pipeline visualization, and step-by-step result viewing.
• Export Formats: Seamlessly download the generated report in .md (Markdown) or .pdf format.

🎥 Demo

Watch the multi-agent AI pipeline in action:

🛠️ Tech Stack

• Framework: Streamlit
• AI & Orchestration: LangChain, LangGraph
• LLM Provider: Groq (llama-3.3-70b-versatile)
• Search API: Tavily API
• Web Scraping: BeautifulSoup4, Requests
• PDF Generation: WeasyPrint, Markdown

🚀 Getting Started

Prerequisites

Make sure you have Python installed (3.9+ recommended). You will also need API keys from:

• Groq
• Tavily

Installation

1. Clone the repository:

   git clone https://github.com/your-username/ClarixMind.git
   cd ClarixMind

2. Create a virtual environment (optional but recommended):

   python -m venv env
   source env/bin/activate  # On Windows use: env\Scripts\activate

3. Install the dependencies:

   pip install -r requirements.txt

4. Environment Variables: Create a .env file in the root directory and add your API keys:

   GROQ_API_KEY="your_groq_api_key_here"
   TAVILY_API_KEY="your_tavily_api_key_here"

Running the App

Run the Streamlit application with the following command:

streamlit run app.py

The application should now be live on http://localhost:8501/

💡 Usage

1. Enter a Topic: Type your desired research topic in the text input box (e.g., "Quantum computing breakthroughs in 2025").
2. Select an Audience: Choose your target audience (General Public, Academic, 5th Grader, or Executive Summary) to tailor the language and complexity of the report.
3. Run Pipeline: Hit "Run Research Pipeline" and watch as the pipeline stages execute dynamically on the UI.
4. Export or Chat: Once the Critic Agent finishes its job, you can download the report locally as a Markdown or PDF file, and use the chat section to ask interactive questions based strictly on the report findings.

📁 Repository Structure

• app.py: Main Streamlit application and UI logic.
• agents.py: LangChain setup involving prompts, models, and chains for all 4 agents.
• tools.py: Tool definitions mapped to the Tavily search and custom BeautifulSoup web scraper.
• requirements.txt: Python dependencies.

🤝 Contributing

Contributions, issues, and feature requests are welcome! Feel free to check the issues page if you want to contribute.

📄 License

This project is open-source and available under the MIT License.