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68 lines
1.9 KiB
Python
68 lines
1.9 KiB
Python
from opencompass.datasets import MedbulletsDataset, MedbulletsEvaluator
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from opencompass.openicl.icl_inferencer import GenInferencer
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from opencompass.openicl.icl_prompt_template import PromptTemplate
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from opencompass.openicl.icl_retriever import ZeroRetriever
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import os
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SYSTEM_PROMPT = 'You are a helpful medical assistant.\n\n' # Where to put this?
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ZERO_SHOT_PROMPT = 'Q: {question}\n Please select the correct answer from the options above and output only the corresponding letter (A, B, C, D, or E) without any explanation or additional text.\n'
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# 将相对于当前文件的相对路径转换为绝对路径
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def to_abs_path(relative_path: str) -> str:
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# 当前脚本所在目录
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base_dir = os.path.dirname(os.path.abspath(__file__))
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# 拼接并规范化绝对路径
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abs_path = os.path.abspath(os.path.join(base_dir, relative_path))
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return abs_path
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# Reader configuration
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reader_cfg = dict(
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input_columns=[
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'question',
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'options',
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'question_type',
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'prompt_mode',
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],
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output_column='label',
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)
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# Inference configuration
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infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template=dict(
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begin=[
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dict(role='SYSTEM', fallback_role='HUMAN', prompt=SYSTEM_PROMPT),
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],
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round=[
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dict(
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role='HUMAN',
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prompt=ZERO_SHOT_PROMPT, # prompt mode: zero-shot
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),
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],
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),
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),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer),
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)
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# Evaluation configuration
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eval_cfg = dict(
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evaluator=dict(type=MedbulletsEvaluator),
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pred_role='BOT',
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)
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medbullets_dataset = dict(
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type=MedbulletsDataset,
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abbr='medbullets',
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path=to_abs_path('data/medbullets.csv'),
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prompt_mode='zero-shot',
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reader_cfg=reader_cfg,
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infer_cfg=infer_cfg,
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eval_cfg=eval_cfg,
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)
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medbullets_datasets = [medbullets_dataset]
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