//Here's a conceptual example of how you might connect two AI agents using Python. This example uses a simple messaging system to simulate how two agents might communicate with each other in a controlled environment. We'll use a basic structure where one agent sends a message to another, and the second agent responds. This is a simplified version and doesn't include complex agent behaviors or actual AI model interactions, but it demonstrates the principle of agent-to-agent communication:
import threading
import time
from queue import Queue
class Agent:
def __init__(self, name):
self.name = name
self.messages = Queue()
def send_message(self, recipient, message):
recipient.messages.put((self.name, message))
print(f"[{self.name}] sent: {message}")
def receive_message(self):
if not self.messages.empty():
sender, message = self.messages.get()
print(f"[{self.name}] received from {sender}: {message}")
return sender, message
return None, None
def run(self):
while True:
sender, message = self.receive_message()
if message:
# Here, the agent would process the message.
# For demonstration, it simply responds.
response = f"Understood, {sender}. My response is: {message.upper()}"
self.send_message(sender, response)
time.sleep(1) # Simulate some processing time
# Create two agents
agent1 = Agent("Agent1")
agent2 = Agent("Agent2")
# Start threads for each agent
thread1 = threading.Thread(target=agent1.run)
thread2 = threading.Thread(target=agent2.run)
thread1.start()
thread2.start()
# Simulate interaction by sending an initial message from Agent1 to Agent2
agent1.send_message(agent2, "Hello, how are you?")
# Keep the main thread alive for a bit to see interactions
time.sleep(5)
# Clean up by stopping the threads (in a real scenario, you'd have better control over thread termination)
thread1.join()
thread2.join()
