Kye
11 months ago
parent
d23884d5d3
commit
f3e27dbdf1
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import os
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from dotenv import load_dotenv
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from swarms import Agent, OpenAIChat
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from swarms.agents.multion_agent import MultiOnAgent
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from swarms.memory.chroma_db import ChromaDB
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from swarms.tools.tool import tool
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from swarms.utils.code_interpreter import SubprocessCodeInterpreter
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# Load the environment variables
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load_dotenv()
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# Memory
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chroma_db = ChromaDB()
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# MultiOntool
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@tool
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def multion_tool(
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task: str,
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api_key: str = os.environ.get("MULTION_API_KEY"),
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):
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"""
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Executes a task using the MultiOnAgent.
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Args:
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task (str): The task to be executed.
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api_key (str, optional): The API key for the MultiOnAgent. Defaults to the value of the MULTION_API_KEY environment variable.
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Returns:
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The result of the task execution.
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"""
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multion = MultiOnAgent(multion_api_key=api_key)
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return multion(task)
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# Execute the interpreter tool
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@tool
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def execute_interpreter_tool(code: str,):
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"""
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Executes a single command using the interpreter.
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Args:
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task (str): The command to be executed.
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Returns:
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None
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"""
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out = SubprocessCodeInterpreter(debug_mode=True)
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out = out.run(code)
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return code
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# Get the API key from the environment
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api_key = os.environ.get("OPENAI_API_KEY")
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# Initialize the language model
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llm = OpenAIChat(
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temperature=0.5,
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openai_api_key=api_key,
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)
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# Initialize the workflow
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agent = Agent(
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agent_name="Research Agent",
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agent_description="An agent that performs research tasks.",
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system_prompt="Perform a research task.",
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llm=llm,
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max_loops=1,
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dashboard=True,
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# tools=[multion_tool, execute_interpreter_tool],
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verbose=True,
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long_term_memory=chroma_db,
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stopping_token="done",
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)
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# Run the workflow on a task
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out = agent.run(
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"Generate a 10,000 word blog on health and wellness, and say done"
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" when you are done"
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)
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print(out)
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from swarms.structs.agent import Agent
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from swarms.structs.message_pool import MessagePool
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from swarms import OpenAIChat
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agent1 = Agent(llm=OpenAIChat(), agent_name="agent1")
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agent2 = Agent(llm=OpenAIChat(), agent_name="agent2")
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agent3 = Agent(llm=OpenAIChat(), agent_name="agent3")
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moderator = Agent(agent_name="moderator")
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agents = [agent1, agent2, agent3]
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message_pool = MessagePool(
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agents=agents, moderator=moderator, turns=5
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)
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message_pool.add(agent=agent1, content="Hello, agent2!", turn=1)
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message_pool.add(agent=agent2, content="Hello, agent1!", turn=1)
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message_pool.add(agent=agent3, content="Hello, agent1!", turn=1)
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message_pool.get_all_messages()
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message_pool.get_visible_messages(agent=agent1, turn=1)
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message_pool.get_visible_messages(agent=agent2, turn=1)
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import os
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import multion
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from swarms.models.base_llm import AbstractLLM
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from dotenv import load_dotenv
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# Load environment variables
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load_dotenv()
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# Muliton key
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MULTION_API_KEY = os.getenv("MULTION_API_KEY")
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class MultiOnAgent(AbstractLLM):
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"""
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Represents a multi-on agent that performs browsing tasks.
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Args:
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max_steps (int): The maximum number of steps to perform during browsing.
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starting_url (str): The starting URL for browsing.
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Attributes:
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max_steps (int): The maximum number of steps to perform during browsing.
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starting_url (str): The starting URL for browsing.
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"""
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def __init__(
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self,
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multion_api_key: str = MULTION_API_KEY,
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max_steps: int = 4,
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starting_url: str = "https://www.google.com",
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*args,
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**kwargs,
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):
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super().__init__(*args, **kwargs)
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self.multion_api_key = multion_api_key
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self.max_steps = max_steps
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self.starting_url = starting_url
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self.multion = multion.login(
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use_api=True,
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multion_api_key=str(multion_api_key),
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*args,
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**kwargs,
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)
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def run(self, task: str, *args, **kwargs):
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"""
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Runs a browsing task.
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Args:
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task (str): The task to perform during browsing.
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*args: Additional positional arguments.
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**kwargs: Additional keyword arguments.
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Returns:
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dict: The response from the browsing task.
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"""
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response = self.multion.browse(
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{
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"cmd": task,
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"url": self.starting_url,
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"maxSteps": self.max_steps,
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},
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*args,
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**kwargs,
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)
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return response.result, response.status, response.lastUrl
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@ -0,0 +1,214 @@
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import hashlib
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from time import time_ns
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from typing import Callable, List, Optional, Sequence, Union
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from swarms.structs.agent import Agent
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from swarms.structs.base_swarm import BaseSwarm
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from swarms.utils.loguru_logger import logger
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def _hash(input: str):
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"""
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Hashes the input string using SHA256 algorithm.
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Args:
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input (str): The string to be hashed.
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Returns:
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str: The hexadecimal representation of the hash value.
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"""
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hex_dig = hashlib.sha256(input.encode("utf-8")).hexdigest()
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return hex_dig
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def msg_hash(
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agent: Agent, content: str, turn: int, msg_type: str = "text"
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):
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"""
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Generate a hash value for a message.
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Args:
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agent (Agent): The agent sending the message.
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content (str): The content of the message.
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turn (int): The turn number of the message.
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msg_type (str, optional): The type of the message. Defaults to "text".
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Returns:
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int: The hash value of the message.
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"""
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time = time_ns()
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return _hash(
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f"agent: {agent.agent_name}\ncontent: {content}\ntimestamp:"
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f" {str(time)}\nturn: {turn}\nmsg_type: {msg_type}"
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)
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class MessagePool(BaseSwarm):
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"""
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A class representing a message pool for agents in a swarm.
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Attributes:
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agents (Optional[Sequence[Agent]]): The list of agents in the swarm.
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moderator (Optional[Agent]): The moderator agent.
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turns (Optional[int]): The number of turns.
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routing_function (Optional[Callable]): The routing function for message distribution.
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show_names (Optional[bool]): Flag indicating whether to show agent names.
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messages (List[Dict]): The list of messages in the pool.
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Examples:
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>>> from swarms.structs.agent import Agent
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>>> from swarms.structs.message_pool import MessagePool
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>>> agent1 = Agent(agent_name="agent1")
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>>> agent2 = Agent(agent_name="agent2")
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>>> agent3 = Agent(agent_name="agent3")
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>>> moderator = Agent(agent_name="moderator")
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>>> agents = [agent1, agent2, agent3]
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>>> message_pool = MessagePool(agents=agents, moderator=moderator, turns=5)
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>>> message_pool.add(agent=agent1, content="Hello, agent2!", turn=1)
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>>> message_pool.add(agent=agent2, content="Hello, agent1!", turn=1)
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>>> message_pool.add(agent=agent3, content="Hello, agent1!", turn=1)
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>>> message_pool.get_all_messages()
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[{'agent': Agent(agent_name='agent1'), 'content': 'Hello, agent2!', 'turn': 1, 'visible_to': 'all', 'logged': True}, {'agent': Agent(agent_name='agent2'), 'content': 'Hello, agent1!', 'turn': 1, 'visible_to': 'all', 'logged': True}, {'agent': Agent(agent_name='agent3'), 'content': 'Hello, agent1!', 'turn': 1, 'visible_to': 'all', 'logged': True}]
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>>> message_pool.get_visible_messages(agent=agent1, turn=1)
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[{'agent': Agent(agent_name='agent1'), 'content': 'Hello, agent2!', 'turn': 1, 'visible_to': 'all', 'logged': True}, {'agent': Agent(agent_name='agent2'), 'content': 'Hello, agent1!', 'turn': 1, 'visible_to': 'all', 'logged': True}, {'agent': Agent(agent_name='agent3'), 'content': 'Hello, agent1!', 'turn': 1, 'visible_to': 'all', 'logged': True}]
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>>> message_pool.get_visible_messages(agent=agent2, turn=1)
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[{'agent': Agent(agent_name='agent1'), 'content': 'Hello, agent2!', 'turn': 1, 'visible_to': 'all', 'logged': True}, {'agent': Agent(agent_name='agent2'), 'content': 'Hello, agent1!', 'turn': 1, 'visible_to': 'all', 'logged': True}, {'agent': Agent(agent_name='agent3'), 'content': 'Hello, agent1!', 'turn': 1, 'visible_to': 'all', 'logged': True}]
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"""
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def __init__(
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self,
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agents: Optional[Sequence[Agent]] = None,
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moderator: Optional[Agent] = None,
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turns: Optional[int] = 5,
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routing_function: Optional[Callable] = None,
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show_names: Optional[bool] = False,
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autosave: Optional[bool] = False,
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*args,
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**kwargs,
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):
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super().__init__()
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self.agent = agents
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self.moderator = moderator
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self.turns = turns
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self.routing_function = routing_function
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self.show_names = show_names
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self.autosave = autosave
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self.messages = []
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logger.info("MessagePool initialized")
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logger.info(f"Number of agents: {len(agents)}")
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logger.info(
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f"Agents: {[agent.agent_name for agent in agents]}"
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)
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logger.info(f"moderator: {moderator.agent_name} is available")
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logger.info(f"Number of turns: {turns}")
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def add(
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self,
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agent: Agent,
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content: str,
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turn: int,
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visible_to: Union[str, List[str]] = "all",
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logged: bool = True,
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):
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"""
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Add a message to the pool.
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Args:
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agent (Agent): The agent sending the message.
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content (str): The content of the message.
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turn (int): The turn number.
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visible_to (Union[str, List[str]], optional): The agents who can see the message. Defaults to "all".
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logged (bool, optional): Flag indicating whether the message should be logged. Defaults to True.
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"""
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self.messages.append(
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{
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"agent": agent,
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"content": content,
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"turn": turn,
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"visible_to": visible_to,
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"logged": logged,
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}
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)
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logger.info(f"Message added: {content}")
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def reset(self):
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"""
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Reset the message pool.
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"""
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self.messages = []
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logger.info("MessagePool reset")
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def last_turn(self):
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"""
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Get the last turn number.
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Returns:
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int: The last turn number.
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"""
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if len(self.messages) == 0:
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return 0
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else:
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return self.messages[-1]["turn"]
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@property
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def last_message(self):
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"""
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Get the last message in the pool.
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Returns:
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dict: The last message.
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"""
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if len(self.messages) == 0:
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return None
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else:
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return self.messages[-1]
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def get_all_messages(self):
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"""
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Get all messages in the pool.
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Returns:
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List[Dict]: The list of all messages.
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"""
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return self.messages
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def get_visible_messages(self, agent: Agent, turn: int):
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"""
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Get the visible messages for a given agent and turn.
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Args:
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agent (Agent): The agent.
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turn (int): The turn number.
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Returns:
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List[Dict]: The list of visible messages.
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"""
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# Get the messages before the current turn
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prev_messages = [
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message
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for message in self.messages
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if message["turn"] < turn
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]
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visible_messages = []
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for message in prev_messages:
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if (
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message["visible_to"] == "all"
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or agent.agent_name in message["visible_to"]
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):
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visible_messages.append(message)
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return visible_messages
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def query(self, query: str):
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"""
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Query a message from the messages list and then pass it to the moderator
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"""
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return [
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(mod, content)
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for mod, content in self.messages
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if mod == self.moderator
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]
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@ -0,0 +1,10 @@
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from loguru import logger
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logger = logger.add(
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"MessagePool.log",
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level="INFO",
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colorize=True,
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format="<green>{time}</green> <level>{message}</level>",
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backtrace=True,
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diagnose=True,
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)
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@ -0,0 +1,117 @@
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from swarms.structs.agent import Agent
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from swarms.structs.message_pool import MessagePool
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from swarms import OpenAIChat
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def test_message_pool_initialization():
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agent1 = Agent(llm=OpenAIChat(), agent_name="agent1")
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agent2 = Agent(llm=OpenAIChat(), agent_name="agent1")
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moderator = Agent(llm=OpenAIChat(), agent_name="agent1")
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agents = [agent1, agent2]
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message_pool = MessagePool(
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agents=agents, moderator=moderator, turns=5
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)
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assert message_pool.agent == agents
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assert message_pool.moderator == moderator
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assert message_pool.turns == 5
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assert message_pool.messages == []
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def test_message_pool_add():
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agent1 = Agent(llm=OpenAIChat(), agent_name="agent1")
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message_pool = MessagePool(
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agents=[agent1], moderator=agent1, turns=5
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)
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message_pool.add(agent=agent1, content="Hello, world!", turn=1)
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assert message_pool.messages == [
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{
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"agent": agent1,
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"content": "Hello, world!",
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"turn": 1,
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"visible_to": "all",
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"logged": True,
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}
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]
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def test_message_pool_reset():
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agent1 = Agent(llm=OpenAIChat(), agent_name="agent1")
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message_pool = MessagePool(
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agents=[agent1], moderator=agent1, turns=5
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)
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message_pool.add(agent=agent1, content="Hello, world!", turn=1)
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message_pool.reset()
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assert message_pool.messages == []
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def test_message_pool_last_turn():
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agent1 = Agent(llm=OpenAIChat(), agent_name="agent1")
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message_pool = MessagePool(
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agents=[agent1], moderator=agent1, turns=5
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)
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message_pool.add(agent=agent1, content="Hello, world!", turn=1)
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assert message_pool.last_turn() == 1
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def test_message_pool_last_message():
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agent1 = Agent(llm=OpenAIChat(), agent_name="agent1")
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message_pool = MessagePool(
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agents=[agent1], moderator=agent1, turns=5
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)
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message_pool.add(agent=agent1, content="Hello, world!", turn=1)
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assert message_pool.last_message == {
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"agent": agent1,
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"content": "Hello, world!",
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"turn": 1,
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"visible_to": "all",
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"logged": True,
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}
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def test_message_pool_get_all_messages():
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agent1 = Agent(llm=OpenAIChat(), agent_name="agent1")
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message_pool = MessagePool(
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agents=[agent1], moderator=agent1, turns=5
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)
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message_pool.add(agent=agent1, content="Hello, world!", turn=1)
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assert message_pool.get_all_messages() == [
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{
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"agent": agent1,
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"content": "Hello, world!",
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"turn": 1,
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"visible_to": "all",
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"logged": True,
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}
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]
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def test_message_pool_get_visible_messages():
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agent1 = Agent(llm=OpenAIChat(), agent_name="agent1")
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agent2 = Agent(agent_name="agent2")
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message_pool = MessagePool(
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agents=[agent1, agent2], moderator=agent1, turns=5
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)
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message_pool.add(
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agent=agent1,
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content="Hello, agent2!",
|
||||
turn=1,
|
||||
visible_to=[agent2.agent_name],
|
||||
)
|
||||
|
||||
assert message_pool.get_visible_messages(
|
||||
agent=agent2, turn=2
|
||||
) == [
|
||||
{
|
||||
"agent": agent1,
|
||||
"content": "Hello, agent2!",
|
||||
"turn": 1,
|
||||
"visible_to": [agent2.agent_name],
|
||||
"logged": True,
|
||||
}
|
||||
]
|
||||
Loading…
Reference in new issue