sankalp
407458149b
The debug argument is used internally by devgen but is not accepted by the OpenAI API client. This change filters it out from kwargs before the API call to prevent TypeError.
52 lines
2.2 KiB
Python
52 lines
2.2 KiB
Python
from openai import OpenAI
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class OpenaiProvider:
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"""Generates a response string using the OpenAI ChatCompletion API based on the provided prompt and parameters. This method initializes an OpenAI client with the given API key, sends a chat completion request with specified model and additional parameters, and returns the content of the generated message.
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Args:
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prompt (str): The input prompt to generate a response for.
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api_key (str): The API key used to authenticate with the OpenAI service.
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model (str, optional): The model to use for generation; defaults to "gpt-4o".
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**kwargs: Additional keyword arguments to customize the API request (e.g., temperature).
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Returns:
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str: The content of the generated response message.
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"""
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DEFAULT_MODEL = "gpt-4o"
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def generate(
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self, prompt: str, api_key: str, model: str | None = None, **kwargs
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) -> str:
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"""Generates a response from the OpenAI ChatCompletion API based on the provided prompt and parameters.
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Creates a client instance with the specified API key, sends a chat completion request using the selected model and additional parameters, and returns the generated message content as a string.
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Args:
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prompt (str): Prompt input.
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api_key (str): OpenAI API key.
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model (str, optional): Model to use (default: gpt-4o).
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**kwargs: Additional OpenAI ChatCompletion parameters (e.g., temperature).
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Returns:
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str: Generated response content.
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"""
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# 1. Create a client instance with the API key.
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try:
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client = OpenAI(api_key=api_key)
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except Exception as e:
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# Add error handling if the client fails to initialize
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raise RuntimeError(f"Failed to initialize OpenAI client: {e}")
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# Remove debug from kwargs if present
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kwargs.pop("debug", None)
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# 2. Use the modern API syntax: client.chat.completions.create
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response = client.chat.completions.create(
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model=model or self.DEFAULT_MODEL,
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messages=[{"role": "user", "content": prompt}],
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**kwargs,
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)
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return response.choices[0].message.content.strip()
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