mirror of
https://github.com/open-compass/opencompass.git
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8e55c9c6ee
* stash files * compassbench subjective evaluation added * evaluation update * fix lint * update docs * Update lint * changes saved * changes saved * CompassBench subjective summarizer added (#1349) * subjective summarizer added * fix lint [Fix] Fix MathBench (#1351) Co-authored-by: liuhongwei <liuhongwei@pjlab.org.cn> [Update] Update model support list (#1353) * fix pip version * fix pip version * update model support subjective summarizer updated knowledge, math objective done (data need update) remove secrets objective changes saved knowledge data added * secrets removed * changed added * summarizer modified * summarizer modified * compassbench coding added * fix lint * objective summarizer updated * compass_bench_v1.3 updated * update files in config folder * remove unused model * lcbench modified * removed model evaluation configs * remove duplicated sdk implementation --------- Co-authored-by: zhangsongyang <zhangsongyang@pjlab.org.cn>
111 lines
3.6 KiB
Python
111 lines
3.6 KiB
Python
import time
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from concurrent.futures import ThreadPoolExecutor
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from typing import Dict, List, Optional, Union
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from opencompass.utils.prompt import PromptList
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from .base_api import BaseAPIModel
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PromptType = Union[PromptList, str]
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class Doubao(BaseAPIModel):
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def __init__(
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self,
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path: str,
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endpoint_id: str,
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access_key: str,
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secret_key: str,
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query_per_second: int = 2,
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max_seq_len: int = 2048,
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meta_template: Optional[Dict] = None,
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retry: int = 2,
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): # noqa E125
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super().__init__(
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path=path,
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max_seq_len=max_seq_len,
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query_per_second=query_per_second,
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meta_template=meta_template,
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retry=retry,
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)
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self.endpoint_id = endpoint_id
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self.access_key = access_key
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self.secret_key = secret_key
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try:
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from volcenginesdkarkruntime import Ark
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except ImportError:
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self.logger.error(
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'To use the Doubao API, you need to install sdk with '
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'`pip3 install volcengine-python-sdk`')
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self.client = Ark(ak=self.access_key, sk=self.secret_key)
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def generate(self,
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inputs: List[PromptType],
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max_out_len: int = 512) -> List[str]:
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"""Generate results given a list of inputs.
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Args:
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inputs (List[PromptType]): A list of strings or PromptDicts.
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The PromptDict should be organized in OpenCompass'
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API format.
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max_out_len (int): The maximum length of the output.
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Returns:
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List[str]: A list of generated strings.
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"""
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with ThreadPoolExecutor() as executor:
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results = list(
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executor.map(self._generate, inputs,
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[max_out_len] * len(inputs)))
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self.flush()
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return results
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def _generate(self, input: PromptType, max_out_len: int = 512) -> str:
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"""Generate results given an input.
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Args:
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inputs (PromptType): A string or PromptDict.
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The PromptDict should be organized in OpenCompass'
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API format.
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max_out_len (int): The maximum length of the output.
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Returns:
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str: The generated string.
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"""
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assert isinstance(input, (str, PromptList))
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if isinstance(input, str):
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messages = [{'role': 'user', 'content': input}]
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else:
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messages = []
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for item in input:
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msg = {'content': item['prompt']}
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if item['role'] == 'HUMAN':
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msg['role'] = 'user'
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elif item['role'] == 'BOT':
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msg['role'] = 'assistant'
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elif item['role'] == 'SYSTEM':
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msg['role'] = 'system'
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else:
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raise ValueError(f'Invalid role: {item["role"]}')
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messages.append(msg)
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data = dict(model=self.endpoint_id, messages=messages)
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for _ in range(self.retry):
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try:
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completion = self.client.chat.completions.create(**data)
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except Exception as e:
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print(e)
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time.sleep(1)
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continue
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generated = completion.choices[0].message.content
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self.logger.debug(f'Generated: {generated}')
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return completion.choices[0].message.content
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self.logger.debug(f'Failed to generate answer for query: {input}')
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raise RuntimeError(f'Failed to respond in {self.retry} retrys')
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