commit
7891e1aa5f
@ -35,3 +35,4 @@ DASHSCOPE_API_KEY = ''
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storage_interval = 10
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window_size = 8
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overlap_size = 2
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multi_process_num = 3
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@ -1,9 +1,11 @@
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import os
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import json
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import time
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from tqdm import tqdm
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import concurrent.futures
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from datetime import datetime
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from config.config import result_dir, storage_interval, window_size, overlap_size
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from config.config import result_dir, storage_interval, window_size, overlap_size, multi_process_num
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from model.qwen import call_qwen_single_turn
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from util.logger import get_logger
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from util.data_loader import get_file_list, get_txt_content, capture_qa
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@ -42,15 +44,28 @@ def generate_qa(
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storage_jsonl_path = os.path.join(
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result_dir, f'{current_time}-{file_name}-{model_name}.jsonl')
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logger.info(f'The generated QA will be stored in {storage_jsonl_path}.')
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for content in tqdm(contents):
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response = model_caller(content)
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# print(response) # 打印输出
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response_list = []
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logger.info("Begin generate QA data")
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with tqdm(total=len(contents)) as pbar:
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with concurrent.futures.ThreadPoolExecutor(max_workers=multi_process_num) as executor:
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# 创建一个Future列表,它们将对应每个worker_function的结果
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futures = {executor.submit(model_caller, content): content for content in contents}
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for future in concurrent.futures.as_completed(futures):
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try:
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response_list.append(future.result())
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pbar.update(1)
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except Exception as exc:
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logger.error("Item generated an exception: %s" % (exc))
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logger.info("Begin capture LLM response")
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for response in tqdm(response_list):
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captured_qa = capture_qa(response)
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# print(captured_qa) # 打印QA对
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if captured_qa is None:
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continue
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storage_list.extend(captured_qa)
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storage_counter += 1
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if storage_counter % interval == 0:
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