Customer Service Agent Example

This is an example of a customer service agent built using crewAI. The agent leverages AI to handle customer inquiries and support requests in a natural and helpful way, demonstrating the power of reactive agents in customer service scenarios.

Overview

This example showcases how to:

• Create an intelligent customer service agent that understands and responds to customer queries
• Handle common customer service scenarios like product returns, complaints, and general inquiries
• Implement reactive agent behavior for real-time customer interactions
• Integrate with FastAPI for a production-ready REST API

Features

• Natural language understanding and generation
• Context-aware responses based on customer history
• Configurable knowledge base for FAQs and policies
• Real-time streaming responses
• REST API endpoints for chat integration

Requirements

• Python 3.8+
• crewAI library (>=0.11.0)
• FastAPI
• uvicorn
• Other dependencies listed in requirements.txt

Installation

1. Clone the repository:

   git clone https://github.com/joaomdmoura/crewAI.git
   cd crewAI/examples/CustomerServiceAgent

2. Install dependencies:

   pip install -r requirements.txt

3. Set up environment variables: Create a .env file in the src directory with your API keys:

   OPENAI_API_KEY=your_openai_api_key
   

Usage

1. Start the API server:

   uvicorn src.api:app --reload

2. Send requests to the API:

   # Chat endpoint
   curl -X POST "http://localhost:8000/chat" \
        -H "Content-Type: application/json" \
        -d '{"message": "What is your return policy?"}'
   
   # Streaming chat endpoint
   curl -X POST "http://localhost:8000/chat/stream" \
        -H "Content-Type: application/json" \
        -d '{"message": "Tell me about shipping"}'

Customization

You can customize the agent's behavior by:

1. Modifying the knowledge base in src/api.py
2. Adjusting agent configuration in src/agent/agent_config.py
3. Extending agent capabilities in src/agent/customer_service.py

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.