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82 lines
2.5 KiB
82 lines
2.5 KiB
import requests
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import json
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from swarms import BaseLLM
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class llama3Hosted(BaseLLM):
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"""
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A class representing a hosted version of the Llama3 model.
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Args:
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model (str): The name or path of the Llama3 model to use.
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temperature (float): The temperature parameter for generating responses.
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max_tokens (int): The maximum number of tokens in the generated response.
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system_prompt (str): The system prompt to use for generating responses.
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*args: Variable length argument list.
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**kwargs: Arbitrary keyword arguments.
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Attributes:
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model (str): The name or path of the Llama3 model.
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temperature (float): The temperature parameter for generating responses.
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max_tokens (int): The maximum number of tokens in the generated response.
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system_prompt (str): The system prompt for generating responses.
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Methods:
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run(task, *args, **kwargs): Generates a response for the given task.
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"""
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def __init__(
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self,
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model: str = "meta-llama/Meta-Llama-3-8B-Instruct",
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temperature: float = 0.8,
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max_tokens: int = 4000,
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system_prompt: str = "You are a helpful assistant.",
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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.model = model
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self.temperature = temperature
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self.max_tokens = max_tokens
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self.system_prompt = system_prompt
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def run(self, task: str, *args, **kwargs) -> str:
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"""
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Generates a response for the given task.
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Args:
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task (str): The user's task or input.
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Returns:
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str: The generated response from the Llama3 model.
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"""
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url = "http://34.204.8.31:30001/v1/chat/completions"
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payload = json.dumps(
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{
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"model": self.model,
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"messages": [
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{"role": "system", "content": self.system_prompt},
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{"role": "user", "content": task},
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],
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"stop_token_ids": [128009, 128001],
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"temperature": self.temperature,
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"max_tokens": self.max_tokens,
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}
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)
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headers = {"Content-Type": "application/json"}
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response = requests.request(
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"POST", url, headers=headers, data=payload
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)
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response_json = response.json()
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assistant_message = response_json["choices"][0]["message"][
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"content"
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]
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return assistant_message
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