parent
868a9c9c38
commit
c93de1f84e
@ -0,0 +1,24 @@
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import datetime
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class Message:
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"""
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Represents a message with timestamp and optional metadata.
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Usage
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--------------
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mes = Message(
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sender = "Kye",
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content = "message"
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)
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print(mes)
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"""
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def __init__(self, sender, content, metadata=None):
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self.timestamp = datetime.datetime.now()
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self.sender = sender
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self.content = content
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self.metadata = metadata or {}
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def __repr__(self):
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return f"{self.timestamp} - {self.sender}: {self.content}"
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@ -1,33 +1,69 @@
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from agent_protocol import Agent, Step, Task
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from swarms.agents.muti_modal_workers.multi_modal_agent import MultiModalVisualAgent
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from swarms.agents.multi_modal_workers.multi_modal_agent import MultiModalVisualAgent
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class MultiModalVisualAgent:
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def __init__(
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self,
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agent: MultiModalVisualAgent
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):
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self.agent = agent
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async def run(self, text: str) -> str:
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#run the multi-modal visual agent with the give task
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return self.agent.run_text(text)
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class MultiModalAgent:
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"""
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A user-friendly abstraction over the MultiModalVisualAgent that provides a simple interface
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to process both text and images.
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async def __call__(self, text: str) -> str:
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return self.agent.run(text)
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Initializes the MultiModalAgent.
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Parameters:
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load_dict (dict, optional): Dictionary of class names and devices to load. Defaults to a basic configuration.
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temperature (float, optional): Temperature for the OpenAI model. Defaults to 0.
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default_language (str, optional): Default language for the agent. Defaults to "English".
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Usage
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async def plan(self, step: Step) -> Step:
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task = Agent
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pass
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"""
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def __init__(
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self,
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load_dict,
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temperature,
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language: str = "english"
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):
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self.load_dict = load_dict
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self.temperature = temperature
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self.langigage = language
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if load_dict is None:
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load_dict = {
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"ImageCaptioning": "default_device"
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}
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async def task_handler(self, task: Task):
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await self.agent.run()
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self.agent = MultiModalVisualAgent(
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load_dict,
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temperature
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)
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self.language = language
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async def step_handler(self, step: Step):
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if step.name == "plan":
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await self.plan(step)
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else:
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await self.agent.run(step)
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def run_text(self, text, language=None):
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"""Run text through the model"""
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if language is None:
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language = self.language
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return step
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try:
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self.agent.init_agent(language)
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return self.agent.run_text(text)
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except Exception as e:
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return f"Error processing text: {str(e)}"
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def run_img(self, image_path: str, language=None):
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"""If language is None"""
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if language is None:
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language = self.default_language
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try:
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return self.agent.run_image(
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image_path,
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language
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)
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except Exception as error:
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return f"Error processing image: {str(error)}"
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def clear(self):
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try:
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self.agent.clear_memory()
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except Exception as e:
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return f"Error cleaning memory: {str(e)}"
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