Building a Multi-Agent Question-Answering System with Claude 3 Sonnet

In the evolving landscape of artificial intelligence, multi-agent systems have become pivotal in creating robust and efficient applications. The multi-agent-starter project offers a sophisticated foundation for developing such systems, particularly focusing on intelligent question routing using Claude 3 Sonnet. This tutorial will guide you through setting up and understanding this starter kit to build a multi-agent question-answering system.

Overview of the Multi-Agent Starter

The multi-agent-starter is designed to intelligently classify and route questions to specialized agents. It distinguishes between technical and general inquiries, directing each to the appropriate agent for processing. This modular approach not only streamlines responses but also allows for easy expansion by integrating additional specialized agents or tools.

Key Features:

• Intelligent Question Classification: Automatically determines the nature of a question (technical or general) and routes it accordingly.

• Specialized Agents: Utilizes dedicated agents tailored to handle specific types of questions, enhancing response accuracy and relevance.

• Robust Error Handling: Implements exponential backoff strategies to manage errors effectively, ensuring system reliability.

• Structured Responses: Provides responses in a structured format, facilitating easy interpretation and further processing.

• Interactive Command-Line Interface (CLI): Offers an interactive CLI for seamless interaction and testing.

• JSON Output Support: Supports JSON-formatted outputs, enabling integration with other systems and applications.

Prerequisites

Before diving into the setup, ensure you have the following:

• Python 3.8 or Higher: The project is built using Python, so version 3.8 or above is required.

• Anthropic API Key: Access to Claude 3 Sonnet necessitates an API key from Anthropic.

• Required Python Packages: All necessary packages are listed in the requirements.txt file within the repository.

Installation

Follow these steps to set up the multi-agent-starter on your local machine:

1. Clone the Repository:

git clone https://github.com/evuori/multi-agent-starter.git
cd multi-agent-starter

2. Set Up a Virtual Environment:

It’s recommended to use a virtual environment to manage dependencies.

python -m venv venv
source venv/bin/activate  # On Windows, use 'venv\Scripts\activate'

3. Install Dependencies:

Install the required Python packages using pip.

pip install -r requirements.txt

4. Configure Environment Variables:

Rename the .env-example file to .env and insert your Anthropic API key.

mv .env-example .env

Edit the .env file to include your API key:

ANTHROPIC_API_KEY=your_api_key_here

Understanding the Code Structure

The project comprises several key files:

• agents.py: Contains the definitions of the specialized agents responsible for handling different types of questions.

• graph.py: Manages the routing logic, determining which agent should process a given question.

• main.py: Serves as the entry point, facilitating user interaction and orchestrating the question-answering process.

Running the Application

To start the application, execute the following command:

python main.py

You will be prompted to enter your questions, and the system will route them to the appropriate agent, providing structured responses based on the input.

Extending the System

The modular design of the multi-agent-starter allows for easy extension. To add a new specialized agent:

1. Define the Agent:

Create a new class in agents.py inheriting from a base agent class, implementing the necessary methods to process specific question types.

2. Update the Routing Logic:

Modify graph.py to include the new agent in the routing logic, specifying the criteria for directing questions to this agent.

3. Integrate Tools (Optional):

Enhance existing agents by incorporating additional tools or APIs to augment their capabilities, such as external databases or machine learning models.

Conclusion

The multi-agent-starter project provides a robust foundation for developing intelligent, multi-agent question-answering systems. By leveraging specialized agents and intelligent routing, it ensures accurate and efficient responses to diverse inquiries. Its extensible architecture allows developers to tailor the system to specific needs, integrating additional agents and tools as required.

Embarking on this project equips you with a versatile platform to explore and implement advanced multi-agent AI solutions, harnessing the power of Claude 3 Sonnet for sophisticated natural language processing tasks.