[MixtureOfAgents.reference_agents -> agents]

README.md

@@ -1201,7 +1201,7 @@ Your final report should be well-structured, easy to understand, and provide a h
 
 # Create the Mixture of Agents class
 moa = MixtureOfAgents(
-    reference_agents=[agent1, agent2, agent3],
+    agents=[agent1, agent2, agent3],
     aggregator_agent=aggregator_agent,
     aggregator_system_prompt="""As the 10-K Report Aggregator, your task is to synthesize the analyses provided by the Financial Statement Analyzer, Risk Assessment Specialist, and Business Strategy Evaluator into a comprehensive and coherent report. 
 

example_async_vs_multithread.py

@@ -0,0 +1,71 @@
+import os
+import asyncio
+import threading
+from swarms import Agent
+from swarm_models import OpenAIChat
+import time
+import psutil
+
+from swarms.prompts.finance_agent_sys_prompt import (
+    FINANCIAL_AGENT_SYS_PROMPT,
+)
+from dotenv import load_dotenv
+
+load_dotenv()
+
+# Get the OpenAI API key from the environment variable
+api_key = os.getenv("OPENAI_API_KEY")
+
+# Create an instance of the OpenAIChat class
+model = OpenAIChat(
+    openai_api_key=api_key, model_name="gpt-4o-mini", temperature=0.1
+)
+
+# Initialize the agent
+agent = Agent(
+    agent_name="Financial-Analysis-Agent",
+    system_prompt=FINANCIAL_AGENT_SYS_PROMPT,
+    llm=model,
+    max_loops=1,
+    autosave=True,
+    dashboard=False,
+    verbose=True,
+    dynamic_temperature_enabled=True,
+    saved_state_path="finance_agent.json",
+    user_name="swarms_corp",
+    retry_attempts=1,
+    context_length=200000,
+    return_step_meta=False,
+    output_type="string",
+    streaming_on=False,
+)
+
+# Function to measure time and memory usage
+def measure_time_and_memory(func):
+    def wrapper(*args, **kwargs):
+        start_time = time.time()
+        result = func(*args, **kwargs)
+        end_time = time.time()
+        memory_usage = psutil.Process().memory_info().rss / 1024 ** 2
+        print(f"Time taken: {end_time - start_time} seconds")
+        print(f"Memory used: {memory_usage} MB")
+        return result
+    return wrapper
+
+# Function to run the agent asynchronously
+@measure_time_and_memory
+async def run_agent_async():
+    await asyncio.gather(
+        agent.run(
+            "How can I establish a ROTH IRA to buy stocks and get a tax break? What are the criteria"
+        )
+    )
+
+# Function to run the agent on another thread
+@measure_time_and_memory
+def run_agent_thread():
+    asyncio.run(run_agent_async())
+
+# Run the agent asynchronously and on another thread to test the speed
+asyncio.run(run_agent_async())
+run_agent_thread()

pyproject.toml

@@ -5,7 +5,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "swarms"
-version = "6.2.8"
+version = "6.2.9"
 description = "Swarms - Pytorch"
 license = "MIT"
 authors = ["Kye Gomez <[email protected]>"]

swarms/structs/mixture_of_agents.py

@@ -20,7 +20,7 @@ class MixtureOfAgentsInput(BaseModel):
     description: str = (
         "A class to run a mixture of agents and aggregate their responses."
     )
-    reference_agents: List[Dict[str, Any]]
+    agents: List[Dict[str, Any]]
     aggregator_agent: Any = Field(
         ...,
         description="An aggregator agent to be used in the mixture.",
@@ -60,7 +60,7 @@ def __init__(
         self,
         name: str = "MixtureOfAgents",
         description: str = "A class to run a mixture of agents and aggregate their responses.",
-        reference_agents: List[Agent] = [],
+        agents: List[Agent] = [],
         aggregator_agent: Agent = None,
         aggregator_system_prompt: str = "",
         layers: int = 3,
@@ -71,23 +71,23 @@ def __init__(
         Args:
             name (str, optional): The name of the mixture of agents. Defaults to "MixtureOfAgents".
             description (str, optional): A description of the mixture of agents. Defaults to "A class to run a mixture of agents and aggregate their responses.".
-            reference_agents (List[Agent], optional): A list of reference agents to be used in the mixture. Defaults to [].
+            agents (List[Agent], optional): A list of reference agents to be used in the mixture. Defaults to [].
             aggregator_agent (Agent, optional): The aggregator agent to be used in the mixture. Defaults to None.
             aggregator_system_prompt (str, optional): The system prompt for the aggregator agent. Defaults to "".
             layers (int, optional): The number of layers to process in the mixture. Defaults to 3.
         """
         self.name = name
         self.description = description
-        self.reference_agents: List[Agent] = reference_agents
+        self.agents: List[Agent] = agents
         self.aggregator_agent: Agent = aggregator_agent
         self.aggregator_system_prompt: str = aggregator_system_prompt
         self.layers: int = layers
 
         self.input_schema = MixtureOfAgentsInput(
             name=name,
             description=description,
-            reference_agents=[
-                agent.to_dict() for agent in self.reference_agents
+            agents=[
+                agent.to_dict() for agent in self.agents
             ],
             aggregator_agent=aggregator_agent.to_dict(),
             aggregator_system_prompt=self.aggregator_system_prompt,
@@ -113,7 +113,7 @@ def reliability_check(self) -> None:
             "Checking the reliability of the Mixture of Agents class."
         )
 
-        if not self.reference_agents:
+        if not self.agents:
             raise ValueError("No reference agents provided.")
 
         if not self.aggregator_agent:
@@ -205,7 +205,7 @@ async def _run_async(self, task: str) -> None:
         results: List[str] = await asyncio.gather(
             *[
                 self._run_agent_async(agent, task)
-                for agent in self.reference_agents
+                for agent in self.agents
             ]
         )
 
@@ -216,7 +216,7 @@ async def _run_async(self, task: str) -> None:
                     self._run_agent_async(
                         agent, task, prev_responses=results
                     )
-                    for agent in self.reference_agents
+                    for agent in self.agents
                 ]
             )
 

swarms/structs/swarm_router.py

@@ -295,7 +295,7 @@ def _create_swarm(
             return MixtureOfAgents(
                 name=self.name,
                 description=self.description,
-                reference_agents=self.agents,
+                agents=self.agents,
                 aggregator_system_prompt=aggregator_system_prompt.get_prompt(),
                 aggregator_agent=self.agents[-1],
                 layers=self.max_loops,