Understanding Agent Communication Protocol (ACP)
The Agent Communication Protocol (ACP) is a game-changer in the world of artificial intelligence. It provides a standardized way for AI agents, applications, and humans to communicate seamlessly. As AI systems often operate in silos, the lack of interoperability can hinder their effectiveness. ACP bridges this gap by offering a unified RESTful API that supports various communication modes, including:
- Multimodal communication
- Synchronous and asynchronous messaging
- Real-time streaming
- Stateful and stateless interactions
- Agent discovery, both online and offline
- Execution of long-running tasks
This tutorial will guide you through building a simple weather agent using Python and ACP, enabling you to fetch real-time weather data for London.
Setting Up Your Environment
Before diving into coding, you need to set up your development environment. Start by installing the necessary libraries. Open your terminal and run:
pip install acp acp-sdk beeai-framework httpxCreating the ACP Server
To create your weather agent, you’ll first need to set up the ACP server. Begin by creating a file named agent.py. In this file, you’ll import the required libraries and set up the server to fetch weather data from the Open-Meteo API.
Fetching Weather Data
Define an asynchronous function called get_london_weather that retrieves the current weather in London. This function will make an API call and return a formatted summary of the weather conditions:
async def get_london_weather() -> str:
# Function implementation here
Defining the Weather Agent
Next, you’ll define the weather agent using the @server.agent() decorator. This agent will handle incoming requests and return the current weather data:
@server.agent()
async def london_weather_agent(input: list[Message], context: Context) -> AsyncGenerator[RunYield, RunYieldResume]:
# Agent implementation here
Running the Server
Once you’ve set up the agent, you can run the server by executing the following command in your terminal:
python agent.pyTo verify that your server is running correctly, use the curl command to check the available agents:
curl http://localhost:8000/agentsCreating the ACP Client
Now that your server is up and running, it’s time to create a client that will interact with the weather agent. Create a new file named client.py and use the ACP SDK to connect to your server:
async def call_london_weather_agent() -> None:
# Client implementation here
Running the Client
To send a request to your ACP server, run the following command in another terminal:
python client.pyIf everything is set up correctly, you should see a response with the current weather in London:
Response from london_weather_agent: - Weather in London: 20.8 °C, wind 10.1 km/h, code 3.Conclusion
Building a weather agent using the Agent Communication Protocol is a straightforward process that showcases the power of seamless communication between AI agents. By following this tutorial, you’ve not only learned how to set up an ACP server and client but also how to fetch real-time data from an external API. This foundational knowledge can be applied to various applications, enhancing the interoperability of AI systems.
Frequently Asked Questions (FAQ)
1. What is the Agent Communication Protocol (ACP)?
ACP is an open standard that facilitates communication between AI agents, applications, and humans, allowing for seamless interaction across different systems.
2. How do I install the necessary libraries for ACP?
You can install the required libraries using the command: pip install acp acp-sdk beeai-framework httpx.
3. What does the weather agent do?
The weather agent retrieves and returns the current weather information for London, including temperature, wind speed, and weather conditions.
4. How can I verify that my ACP server is running?
You can verify the server by executing the command curl http://localhost:8000/agents in your terminal to see a list of available agents.
5. Can I modify the weather agent to fetch data for other cities?
Yes, you can modify the coordinates in the get_london_weather function to fetch weather data for any city supported by the Open-Meteo API.
