logging -> loguru: final stage
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@@ -1,16 +1,18 @@
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from loguru import logger
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from toolbox import update_ui, promote_file_to_downloadzone, gen_time_str
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from toolbox import CatchException, report_exception
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from toolbox import write_history_to_file, promote_file_to_downloadzone
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from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
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from .crazy_utils import read_and_clean_pdf_text
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from .crazy_utils import input_clipping
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from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
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from crazy_functions.crazy_utils import read_and_clean_pdf_text
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from crazy_functions.crazy_utils import input_clipping
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def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
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file_write_buffer = []
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for file_name in file_manifest:
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print('begin analysis on:', file_name)
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logger.info('begin analysis on:', file_name)
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############################## <第 0 步,切割PDF> ##################################
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# 递归地切割PDF文件,每一块(尽量是完整的一个section,比如introduction,experiment等,必要时再进行切割)
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# 的长度必须小于 2500 个 Token
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@@ -38,7 +40,7 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
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last_iteration_result = paper_meta # 初始值是摘要
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MAX_WORD_TOTAL = 4096 * 0.7
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n_fragment = len(paper_fragments)
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if n_fragment >= 20: print('文章极长,不能达到预期效果')
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if n_fragment >= 20: logger.warning('文章极长,不能达到预期效果')
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for i in range(n_fragment):
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NUM_OF_WORD = MAX_WORD_TOTAL // n_fragment
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i_say = f"Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} Chinese characters: {paper_fragments[i]}"
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