243a1b0276
Co-authored-by: Zhuohan Li <zhuohan@openai.com> Co-authored-by: Maratyszcza <marat@openai.com> Co-authored-by: Volodymyr Kyrylov <vol@wilab.org.ua>
94 lines
3.4 KiB
Python
94 lines
3.4 KiB
Python
import time
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from typing import Any
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import openai
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from openai import OpenAI
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from .types import MessageList, SamplerBase, SamplerResponse
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class ResponsesSampler(SamplerBase):
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"""
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Sample from OpenAI's responses API
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"""
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def __init__(
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self,
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model: str,
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developer_message: str | None = None,
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temperature: float = 1.0,
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max_tokens: int = 1024,
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reasoning_model: bool = False,
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reasoning_effort: str | None = None,
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base_url: str = "http://localhost:8000/v1",
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):
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self.api_key_name = "OPENAI_API_KEY"
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self.client = OpenAI(base_url=base_url, timeout=24*60*60)
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self.model = model
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self.developer_message = developer_message
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self.temperature = temperature
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self.max_tokens = max_tokens
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self.image_format = "url"
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self.reasoning_model = reasoning_model
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self.reasoning_effort = reasoning_effort
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def _pack_message(self, role: str, content: Any) -> dict[str, Any]:
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return {"role": role, "content": content}
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def __call__(self, message_list: MessageList) -> SamplerResponse:
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if self.developer_message:
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message_list = [
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self._pack_message("developer", self.developer_message)
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] + message_list
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trial = 0
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while True:
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try:
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if self.reasoning_model:
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reasoning = (
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{"effort": self.reasoning_effort}
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if self.reasoning_effort
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else None
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)
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response = self.client.responses.create(
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model=self.model,
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input=message_list,
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reasoning=reasoning,
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)
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else:
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response = self.client.responses.create(
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model=self.model,
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input=message_list,
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temperature=self.temperature,
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max_output_tokens=self.max_tokens,
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)
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for output in response.output:
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if hasattr(output, "text"):
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message_list.append(self._pack_message(getattr(output, "role", "assistant"), output.text))
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elif hasattr(output, "content"):
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for c in output.content:
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# c.text handled below
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pass
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return SamplerResponse(
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response_text=response.output_text,
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response_metadata={"usage": response.usage},
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actual_queried_message_list=message_list,
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)
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except openai.BadRequestError as e:
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print("Bad Request Error", e)
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return SamplerResponse(
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response_text="",
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response_metadata={"usage": None},
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actual_queried_message_list=message_list,
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)
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except Exception as e:
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exception_backoff = 2**trial # expontial back off
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print(
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f"Rate limit exception so wait and retry {trial} after {exception_backoff} sec",
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e,
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)
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time.sleep(exception_backoff)
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trial += 1
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# unknown error shall throw exception
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