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🔍 CrewAI Research Assistant

An advanced research assistant powered by CrewAI, Exa, and Streamlit, designed to explore any topic using AI agents.

CrewAI Logo

Open it Here!

Open it Here

App Screenshot

🌟 Highlights

  • 🤖 Support for multiple LLMs
  • 🔍 Enhanced response generation powered by Exa
  • 📊 Live tracking of research progress
  • 📝 Organized report generation
  • 🎯 Targeted topic exploration
  • 🔒 Secure API key handling
  • 📱 Sleek, user-friendly interface

📚 Code Structure

  • Main App (streamlit_app.py)

    • Manages Streamlit UI configuration
    • Coordinates research workflows
    • Displays final outcomes

  • Research Module (researcher.py)

    • Sets up LLM providers (OpenAI, GROQ, Ollama)
    • Initializes research agents with tools
    • Structures research tasks
    • Oversees execution flow

  • Sidebar Module (sidebar.py)

    • Handles model selection UI
    • Manages credential inputs
    • Connects to local Ollama
    • Offers customization settings

  • Output Manager (output_handler.py)

    • Formats and displays intermediate outputs
    • Updates UI in real-time

🛠️ Directory Layout

crewai-research-assistant/
├── app.py # Primary Streamlit app entry file  
├── requirements.txt # Dependency list  
└── source/  
├── components/  
│ ├── researcher.py # Core research logic  
│ │ # - LLM setup  
│ │ # - Task design  
│ │ # - Exa integration  
│ └── sidebar.py # Configuration panel  
│ # - Model switching  
│ # - API key handling  
│ # - Local Ollama setup  
└── utils/  
└── output_handler.py # Output processing  
   # - Live data capture  
   # - Formatting utilities

📋 Prerequisites

  • Python ≥3.10 and <3.13
  • OpenAI/GROQ API keys
  • Exa API key
  • Streamlit installation

🚀 Quick Start

  1. Clone repo:
git clone https://github.com/billy-enrizky/crewai-research-assistant/
cd crewai-research-assistant
  1. Set up virtual environment:
python -m venv .venv  
source .venv/bin/activate  # Windows: `.venv\Scripts\activate`
  1. Install packages:
pip install -r requirements.txt
  1. Launch app:
streamlit run streamlit_app.py

🔑 API Configuration

Required credentials:

  1. OpenAI or GROQ Key

  2. Exa Key

Input these keys in the application's sidebar when requested.

🎯 How to Use

  1. Launch the app in your browser
  2. Choose LLM provider (OpenAI/GROQ)
  3. Input API keys via sidebar
  4. Enter research question
  5. Click "Start Research"
  6. Monitor live progress and results

💡 Feature Breakdown

Research Agent

(src/components/researcher.py) utilizes CrewAI to:

  • Perform in-depth topic investigations
  • Synthesize and condense information
  • Deliver structured reports

Live Tracking

(src/utils/output_handler.py) offers:

  • Instant progress visualization
  • Well-formatted outputs
  • Step-by-step monitoring

Interface

Modern UI includes:

  • Intuitive configuration panel
  • Clear progress displays
  • Professional result formatting

🤝 Contributions

We welcome contributions! Feel free to submit PRs.

📄 Licensing

MIT Licensed - See LICENSE file.

🙏 Credits

Built with ❤️ using CrewAI, Exa, and Streamlit