Multi-Agent Research Assistant

A collaborative Agent-to-Agent (A2A) system built using LangChain and LangGraph, designed to generate detailed and well-structured research reports through intelligent agent cooperation.

System architecture built with LangGraph illustrating multi-agent collaboration.

Project Structure

multi_agent_researcher/
├── assets/
│   └── (graph visualizations saved here)
├── .env
├── requirements.txt
├── prompts.py
├── agents.py
├── graph.py
├── visualize_graph.py
├── app.py
└── README.md

Installation

Prerequisites

• Python 3.9 or higher
• pip package manager
• (Optional) Graphviz for graph visualization

Step 1: Clone or Create Project Directory

mkdir multi_agent_researcher
cd multi_agent_researcher

Step 2: Install Python Dependencies

pip install -r requirements.txt

Step 3: Configure Environment Variables

Create a .env file in the root directory:

# Get API key from https://www.together.ai/
TOGETHER_API_KEY=your_together_api_key_here

# Get API key from https://tavily.com/
TAVILY_API_KEY=your_tavily_api_key_here

Getting API Keys:

1. Together AI: Sign up at together.ai and create an API key
2. Tavily: Sign up at tavily.com and get your API key

Step 4: (Optional) Install Graphviz for Visualization

Ubuntu/Debian:

sudo apt-get install graphviz graphviz-dev

macOS:

brew install graphviz

Windows:

choco install graphviz

🎯 Usage

Generate Workflow Visualization (Optional)

python visualize_graph.py

This creates a visual diagram of the agent workflow in assets/research_graph.png

Run the Streamlit Application

streamlit run app.py

The app will open in your browser at http://localhost:8501

🤖 How It Works

The system uses four specialized AI agents that work together:

1. ** Supervisor Agent**

   • Coordinates the entire workflow
   • Decides which agent should work next
   • Manages task delegation

2. ** Researcher Agent**

   • Searches the web for relevant information
   • Uses Tavily search API
   • Gathers and compiles research findings

3. ** Writer Agent**

   • Creates research reports from findings
   • Revises drafts based on feedback
   • Ensures coherent and well-structured output

4. ** Critiquer Agent**

   • Reviews drafts for quality
   • Provides actionable feedback
   • Approves final reports

Workflow

Start → Supervisor → Researcher → Supervisor → Writer → Critiquer → Supervisor
                ↑                                                        ↓
                └────────────────── (loop until approved) ──────────────┘

Troubleshooting

Common Issues

1. Import Errors

# Reinstall all dependencies
pip install -r requirements.txt --upgrade

2. API Key Errors

• Verify your .env file is in the project root
• Check that API keys are correct and active
• Ensure no extra spaces in the .env file

3. Together AI Connection Issues

• The code uses Together AI's OpenAI-compatible endpoint
• Ensure your API key has sufficient credits
• Check network connectivity

4. Graphviz Installation Issues

• Graphviz is optional for visualization
• The app will work without it
• If needed, follow