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from swarms import Agent
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from swarms.models.base_llm import BaseLLM
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# Define a custom LLM class
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class ExampleLLM(BaseLLM):
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def __init__(self):
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pass
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def run(self, task: str, *args, **kwargs):
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# Your LLM logic here
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pass
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# Initialize the workflow
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agent = Agent(
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llm=ExampleLLM(), # Instantiate the ExampleLLM class
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max_loops="auto", # Set the maximum number of loops to "auto"
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autosave=True, # Enable autosave feature
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dashboard=False, # Disable the dashboard
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streaming_on=True, # Enable streaming
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verbose=True, # Enable verbose mode
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stopping_token="<DONE>", # Set the stopping token to "<DONE>"
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interactive=True, # Enable interactive mode
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)
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# Run the workflow on a task
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agent(
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"Generate a transcript for a youtube video on what swarms are!" # Specify the task
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" Output a <DONE> token when done." # Specify the stopping condition
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)
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