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[rainbow2526]

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[gemini-code-assist]

Code Review

This pull request switches the default annotation backend from Nvidia to Huawei Ascend, reduces the number of few-shot examples from 100 to 50, and updates various file and model paths to absolute /root/ paths. Feedback focuses on avoiding hardcoded absolute paths to improve portability, and removing the unused task_id parameter from the annotate_ascend call and definition to prevent signature mismatch and runtime errors when switching backends.

[gemini-code-assist]

Hardcoding absolute paths like /root/OpenSeek/... makes the codebase non-portable and prone to failure when run in different environments or by other users. It is highly recommended to resolve these paths dynamically relative to the script's location using os.path utilities.

Suggested change

	1: '/root/OpenSeek/openseek/competition/LongContext-ICL-Annotation/data/openseek-1_closest_integers.json',
	2: '/root/OpenSeek/openseek/competition/LongContext-ICL-Annotation/data/openseek-2_count_nouns_verbs.json',
	3: '/root/OpenSeek/openseek/competition/LongContext-ICL-Annotation/data/openseek-3_collatz_conjecture.json',
	4: '/root/OpenSeek/openseek/competition/LongContext-ICL-Annotation/data/openseek-4_conala_concat_strings.json',
	5: '/root/OpenSeek/openseek/competition/LongContext-ICL-Annotation/data/openseek-5_semeval_2018_task1_tweet_sadness_detection.json',
	6: '/root/OpenSeek/openseek/competition/LongContext-ICL-Annotation/data/openseek-6_mnli_same_genre_classification.json',
	7: '/root/OpenSeek/openseek/competition/LongContext-ICL-Annotation/data/openseek-7_jeopardy_answer_generation_all.json',
	8: '/root/OpenSeek/openseek/competition/LongContext-ICL-Annotation/data/openseek-8_kernel_generation.json',
	1: os.path.join(os.path.dirname(__file__), '../data/openseek-1_closest_integers.json'),
	2: os.path.join(os.path.dirname(__file__), '../data/openseek-2_count_nouns_verbs.json'),
	3: os.path.join(os.path.dirname(__file__), '../data/openseek-3_collatz_conjecture.json'),
	4: os.path.join(os.path.dirname(__file__), '../data/openseek-4_conala_concat_strings.json'),
	5: os.path.join(os.path.dirname(__file__), '../data/openseek-5_semeval_2018_task1_tweet_sadness_detection.json'),
	6: os.path.join(os.path.dirname(__file__), '../data/openseek-6_mnli_same_genre_classification.json'),
	7: os.path.join(os.path.dirname(__file__), '../data/openseek-7_jeopardy_answer_generation_all.json'),
	8: os.path.join(os.path.dirname(__file__), '../data/openseek-8_kernel_generation.json'),

[gemini-code-assist]

Passing task_id to annotate breaks compatibility with annotate_nvidia, which only accepts a single argument (input_prompt). If a user switches to Nvidia GPU by uncommenting line 9, the code will raise a TypeError. Since task_id is not used inside annotate_ascend either, it should be removed from the call.

Suggested change

	# prediction = annotate(input_prompt, task_id)
	# test_record['prediction'] = prediction
	prediction = annotate(input_prompt)
	prediction = annotate(input_prompt, task_id)
	# prediction = annotate(input_prompt)
	# test_record['prediction'] = prediction
	prediction = annotate(input_prompt)

[gemini-code-assist]

The task_id parameter is unused in annotate_ascend and breaks signature compatibility with annotate_nvidia. It should be removed to maintain consistency and prevent runtime errors when switching between GPU backends.

Suggested change

	def annotate_ascend(input_prompt:str, task_id:int=None)->list[str]:
	def annotate_ascend(input_prompt:str)->list[str]:

[gemini-code-assist]

Hardcoding /root/Qwen3-4B as the default tokenizer path limits portability. Using an environment variable with a fallback makes it easier to configure across different environments.

Suggested change

	default='/root/Qwen3-4B')
	default=os.getenv("TOKENIZER_PATH", "/root/Qwen3-4B"))

[gemini-code-assist]

Hardcoding /root/Qwen3-4B as the tokenizer path limits portability. Using an environment variable with a fallback allows for easier configuration.

Suggested change

	tokenizer = AutoTokenizer.from_pretrained("/root/Qwen3-4B", trust_remote_code=True)
	import os
	tokenizer_path = os.getenv("TOKENIZER_PATH", "/root/Qwen3-4B")
	tokenizer = AutoTokenizer.from_pretrained(tokenizer_path, trust_remote_code=True)

[gemini-code-assist]

Hardcoding /root/Qwen3-4B as the model name/path limits portability. Using an environment variable with a fallback allows for easier configuration.

Suggested change

	model = "/root/Qwen3-4B"
	import os
	model = os.getenv("MODEL_PATH", "/root/Qwen3-4B")