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65 lines
2.1 KiB
65 lines
2.1 KiB
import os
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from deepsearcher.llm.base import BaseLLM
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class OpenAILLM(BaseLLM):
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"""
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OpenAI language model implementation.
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This class provides an interface to interact with OpenAI's language models
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through their API.
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Attributes:
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model (str): The OpenAI model identifier to use.
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client: The OpenAI client instance.
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"""
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def __init__(self, model: str = "o1-mini", **kwargs):
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"""
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Initialize an OpenAI language model client.
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Args:
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model (str, optional): The model identifier to use. Defaults to "o1-mini".
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**kwargs: Additional keyword arguments to pass to the OpenAI client.
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- api_key: OpenAI API key. If not provided, uses OPENAI_API_KEY environment variable.
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- base_url: OpenAI API base URL. If not provided, uses OPENAI_BASE_URL environment variable.
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"""
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from openai import OpenAI
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self.model = model
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if "api_key" in kwargs:
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api_key = kwargs.pop("api_key")
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else:
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api_key = os.getenv("OPENAI_API_KEY")
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if "base_url" in kwargs:
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base_url = kwargs.pop("base_url")
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else:
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base_url = os.getenv("OPENAI_BASE_URL")
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self.client = OpenAI(api_key=api_key, base_url=base_url, **kwargs)
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def chat(self, messages: list[dict], stream_callback = None) -> str:
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"""
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Send a chat message to the OpenAI model and get a response.
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Args:
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messages (List[Dict]):
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A list of message dictionaries, typically in the format
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[{"role": "system", "content": "..."}, {"role": "user", "content": "..."}]
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Returns:
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response (str)
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"""
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completion = self.client.chat.completions.create(
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model=self.model,
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messages=messages,
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stream=True
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)
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response = ""
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for chunk in completion:
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stream_response = chunk.choices[0].delta.content
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if stream_response:
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response += stream_response
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if stream_callback:
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stream_callback(stream_response)
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return response
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