autoscaler

swarms/swarms/autoscaler.py

@@ -1,7 +1,6 @@
 import queue
 import threading
 from time import sleep
-
 from swarms.utils.decorators import error_decorator, log_decorator, timing_decorator
 from swarms.workers.worker import Worker
 
@@ -14,7 +13,24 @@ class AutoScaler:
     # TODO: Missing, Task Assignment, Task delegation, Task completion, Swarm level communication with vector db
 
 
-    Example
+    Args:
+        
+        initial_agents (int, optional): Number of initial agents. Defaults to 10.
+        scale_up_factor (int, optional): Scale up factor. Defaults to 1.
+        idle_threshold (float, optional): Idle threshold. Defaults to 0.2.
+        busy_threshold (float, optional): Busy threshold. Defaults to 0.7.
+        agent ([type], optional): Agent. Defaults to None.
+    
+
+    Methods:
+        add_task: Add task to queue
+        scale_up: Scale up
+        scale_down: Scale down
+        monitor_and_scale: Monitor and scale
+        start: Start scaling
+        del_agent: Delete an agent
+    
+    Usage
     ```
     # usage of usage
     auto_scaler = AutoScaler(agent=YourCustomAgent)
@@ -44,18 +60,21 @@ def __init__(
         self.lock = threading.Lock()
 
     def add_task(self, task):
+        """Add tasks to queue"""
         self.tasks_queue.put(task)
 
     @log_decorator
     @error_decorator
     @timing_decorator
     def scale_up(self):
+        """Add more agents"""
         with self.lock:
             new_agents_counts = len(self.agents_pool) * self.scale_up_factor
             for _ in range(new_agents_counts):
                 self.agents_pool.append(Worker())
 
     def scale_down(self):
+        """scale down"""
         with self.lock:
             if len(self.agents_pool) > 10:  # ensure minmum of 10 agents
                 del self.agents_pool[-1]  # remove last agent
@@ -64,6 +83,7 @@ def scale_down(self):
     @error_decorator
     @timing_decorator
     def monitor_and_scale(self):
+        """Monitor and scale"""
         while True:
             sleep(60)  # check minute
             pending_tasks = self.task_queue.qsize()
@@ -78,6 +98,7 @@ def monitor_and_scale(self):
     @error_decorator
     @timing_decorator
     def start(self):
+        """Start scaling"""
         monitor_thread = threading.Thread(target=self.monitor_and_scale)
         monitor_thread.start()
 
@@ -89,6 +110,7 @@ def start(self):
                     available_agent.run(task)
 
     def del_agent(self):
+        """Delete an agent"""
         with self.lock:
             if self.agents_pool:
                 agent_to_remove = self.agents_poo.pop()

swarms/swarms/base.py

@@ -3,6 +3,10 @@
 from swarms.workers.base import AbstractWorker
 
 class AbstractSwarm(ABC):
+    """
+    Abstract class for swarm simulation architectures
+
+    """
     # TODO: Pass in abstract LLM class that can utilize Hf or Anthropic models, Move away from OPENAI
     # TODO: ADD Universal Communication Layer, a ocean vectorstore instance
     # TODO: BE MORE EXPLICIT ON TOOL USE, TASK DECOMPOSITION AND TASK COMPLETETION AND ALLOCATION
@@ -63,3 +67,9 @@ def direct_message(
     ):
         """Send a direct message to a worker"""
         pass
+
+    @abstractmethod
+    def autoscaler(self, num_workers: int, worker: ["AbstractWorker"]):
+        """Autoscaler that acts like kubernetes for autonomous agents"""
+        pass
+