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add & update openai models
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@ -3,10 +3,13 @@ from mmengine.config import read_base
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with read_base():
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with read_base():
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from opencompass.configs.datasets.OpenHuEval.HuMatchingFIB.HuMatchingFIB import hu_matching_fib_datasets
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from opencompass.configs.datasets.OpenHuEval.HuMatchingFIB.HuMatchingFIB import hu_matching_fib_datasets
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from opencompass.configs.models.openai.gpt_4o_mini_20240718 import models as gpt_4o_mini_20240718_model
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# from opencompass.configs.models.openai.gpt_4o_mini_20240718 import models as gpt_4o_mini_20240718_model
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from opencompass.configs.models.qwen2_5.lmdeploy_qwen2_5_7b_instruct import models as lmdeploy_qwen2_5_7b_instruct_model
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# from opencompass.configs.models.qwen2_5.lmdeploy_qwen2_5_7b_instruct import models as lmdeploy_qwen2_5_7b_instruct_model
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from opencompass.configs.models.hf_internlm.lmdeploy_internlm3_8b_instruct import models as lmdeploy_internlm3_8b_instruct_model
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# from opencompass.configs.models.hf_internlm.lmdeploy_internlm3_8b_instruct import models as lmdeploy_internlm3_8b_instruct_model
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# from opencompass.configs.models.qwq.lmdeploy_qwq_32b_preview import models as lmdeploy_qwq_32b_preview_model
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# from opencompass.configs.models.qwq.lmdeploy_qwq_32b_preview import models as lmdeploy_qwq_32b_preview_model
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from opencompass.configs.models.openai.o1_mini_2024_09_12 import models as o1_mini_2024_09_12_model
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# from opencompass.configs.models.openai.o3_mini_2025_01_31 import models as o3_mini_2025_01_31_model
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datasets = hu_matching_fib_datasets
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datasets = hu_matching_fib_datasets
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models = sum([v for k, v in locals().items() if k.endswith('_model')], [])
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models = sum([v for k, v in locals().items() if k.endswith('_model')], [])
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@ -12,6 +12,7 @@ models = [
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path='gpt-4o-mini-2024-07-18',
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path='gpt-4o-mini-2024-07-18',
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key=
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key=
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'ENV', # The key will be obtained from $OPENAI_API_KEY, but you can write down your key here as well
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'ENV', # The key will be obtained from $OPENAI_API_KEY, but you can write down your key here as well
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openai_proxy_url='ENV',
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meta_template=api_meta_template,
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meta_template=api_meta_template,
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query_per_second=1,
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query_per_second=1,
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max_out_len=2048,
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max_out_len=2048,
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@ -12,6 +12,8 @@ models = [
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path='o1-mini-2024-09-12',
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path='o1-mini-2024-09-12',
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key=
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key=
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'ENV', # The key will be obtained from $OPENAI_API_KEY, but you can write down your key here as well
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'ENV', # The key will be obtained from $OPENAI_API_KEY, but you can write down your key here as well
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openai_proxy_url='ENV',
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verbose=True,
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meta_template=api_meta_template,
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meta_template=api_meta_template,
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query_per_second=1,
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query_per_second=1,
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batch_size=1,
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batch_size=1,
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@ -12,6 +12,7 @@ models = [
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path='o1-preview-2024-09-12',
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path='o1-preview-2024-09-12',
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key=
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key=
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'ENV', # The key will be obtained from $OPENAI_API_KEY, but you can write down your key here as well
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'ENV', # The key will be obtained from $OPENAI_API_KEY, but you can write down your key here as well
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openai_proxy_url='ENV',
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meta_template=api_meta_template,
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meta_template=api_meta_template,
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query_per_second=1,
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query_per_second=1,
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batch_size=1,
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batch_size=1,
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22
opencompass/configs/models/openai/o3_mini_2025_01_31.py
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opencompass/configs/models/openai/o3_mini_2025_01_31.py
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@ -0,0 +1,22 @@
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from opencompass.models import OpenAISDK
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api_meta_template = dict(round=[
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dict(role='HUMAN', api_role='HUMAN'),
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dict(role='BOT', api_role='BOT', generate=True),
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], )
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models = [
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dict(
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abbr='o3-mini-2025-01-31',
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type=OpenAISDK,
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path='o3-mini-2025-01-31',
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key=
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'ENV', # The key will be obtained from $OPENAI_API_KEY, but you can write down your key here as well
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openai_proxy_url='ENV',
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verbose=True,
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meta_template=api_meta_template,
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query_per_second=1,
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batch_size=1,
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temperature=1,
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max_completion_tokens=8192), # you can change it for large reasoning inference cost, according to: https://platform.openai.com/docs/guides/reasoning
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]
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@ -30,6 +30,7 @@ O1_MODEL_LIST = [
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'o1-mini-2024-09-12',
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'o1-mini-2024-09-12',
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'o1-preview',
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'o1-preview',
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'o1-mini',
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'o1-mini',
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'o3-mini-2025-01-31',
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]
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]
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@ -579,6 +580,7 @@ class OpenAISDK(OpenAI):
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verbose=verbose,
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verbose=verbose,
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max_completion_tokens=max_completion_tokens,
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max_completion_tokens=max_completion_tokens,
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)
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)
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key = random.choice(self.keys)
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from openai import OpenAI
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from openai import OpenAI
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# support multiple api_base for acceleration
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# support multiple api_base for acceleration
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