Multi-Agent Collaboration in Axion Framework

from axion.collaboration.agent_framework import CollaborationFramework

# Initialize the Collaboration Framework
collaboration = CollaborationFramework()

# Delegate a task from Agent 1 to Agent 2
collaboration.delegate_task(
    sender_id=1,
    recipient_id=2,
    task_description="Analyze IPFS data and generate a report"
)

# Send a message from Agent 1 to Agent 2
collaboration.send_message(sender_id=1, recipient_id=2, message="Start processing task.")

# Agent 2 retrieves messages
messages = collaboration.receive_message(recipient_id=2)
for msg in messages:
    print(f"Received message from Agent {msg['sender_id']}: {msg['message']}")

from axion.utils.redis_task_queue import RedisTaskQueue

# Initialize the Redis Task Queue
redis_queue = RedisTaskQueue()

# Add a new task to the queue
redis_queue.push_task({
    "agent_id": 1,
    "task_description": "Perform sentiment analysis on dataset."
})

# Retrieve a task from the queue
task = redis_queue.pop_task()
print(f"Task retrieved: {task}")

from axion.collaboration.agent_framework import CollaborationFramework
from axion.utils.redis_task_queue import RedisTaskQueue

# Initialize components
collaboration = CollaborationFramework()
redis_queue = RedisTaskQueue()

# Step 1: Delegate tasks
collaboration.delegate_task(
    sender_id=1,
    recipient_id=3,
    task_description="Train machine learning model on dataset A"
)

# Step 2: Send instructions via messages
collaboration.send_message(
    sender_id=1,
    recipient_id=3,
    message="Please start the training and provide regular updates."
)

# Step 3: Add tasks to the queue for distribution
redis_queue.push_task({
    "agent_id": 4,
    "task_description": "Run model validation on dataset B."
})

# Step 4: Process queued tasks
task = redis_queue.pop_task()
print(f"Processing task: {task}")

# Step 5: Retrieve messages for updates
messages = collaboration.receive_message(recipient_id=3)
for msg in messages:
    print(f"Message for Agent 3: {msg['message']}")