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Runtime error
更正bug
Browse files- crazy_functions/crazy_utils.py +1 -1
- crazy_functions/解析项目源代码.py +18 -2
crazy_functions/crazy_utils.py
CHANGED
@@ -76,7 +76,7 @@ def request_gpt_model_in_new_thread_with_ui_alive(
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try:
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# 【第一种情况】:顺利完成
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result = predict_no_ui_long_connection(
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inputs=inputs, llm_kwargs=llm_kwargs,
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history=history, sys_prompt=sys_prompt, observe_window=mutable)
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return result
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except ConnectionAbortedError as token_exceeded_error:
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try:
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# 【第一种情况】:顺利完成
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result = predict_no_ui_long_connection(
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inputs=inputs, llm_kwargs=llm_kwargs,
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history=history, sys_prompt=sys_prompt, observe_window=mutable)
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return result
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except ConnectionAbortedError as token_exceeded_error:
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crazy_functions/解析项目源代码.py
CHANGED
@@ -41,6 +41,22 @@ def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
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chatbot.append(("完成?", "逐个文件分析已完成。" + res + "\n\n正在开始汇总。"))
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yield from update_ui(chatbot=chatbot, history=history_to_return) # 刷新界面
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############################## <第二步,综合,单线程,分组+迭代处理> ##################################
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batchsize = 16 # 10个文件为一组
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report_part_2 = []
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@@ -53,14 +69,14 @@ def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
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file_rel_path = [os.path.relpath(fp, project_folder) for index, fp in enumerate(this_iteration_file_manifest)]
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# 把“请对下面的程序文件做一个概述” 替换成 精简的 "文件名:{all_file[index]}"
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for index, content in enumerate(this_iteration_gpt_response_collection):
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if index%2==0: this_iteration_gpt_response_collection[index] = f"
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previous_iteration_files.extend([os.path.relpath(fp, project_folder) for index, fp in enumerate(this_iteration_file_manifest)])
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previous_iteration_files_string = ', '.join(previous_iteration_files)
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current_iteration_focus = ', '.join([os.path.relpath(fp, project_folder) for index, fp in enumerate(this_iteration_file_manifest)])
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i_say = f'根据以上分析,对程序的整体功能和构架重新做出概括。然后用一张markdown表格整理每个文件的功能(包括{previous_iteration_files_string})。'
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inputs_show_user = f'根据以上分析,对程序的整体功能和构架重新做出概括,由于输入长度限制,可能需要分组处理,本组文件为 {current_iteration_focus} + 已经汇总的文件组。'
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this_iteration_history = copy.deepcopy(this_iteration_gpt_response_collection)
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this_iteration_history.
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result = yield from request_gpt_model_in_new_thread_with_ui_alive(
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inputs=i_say, inputs_show_user=inputs_show_user, llm_kwargs=llm_kwargs, chatbot=chatbot,
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history=this_iteration_history, # 迭代之前的分析
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chatbot.append(("完成?", "逐个文件分析已完成。" + res + "\n\n正在开始汇总。"))
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yield from update_ui(chatbot=chatbot, history=history_to_return) # 刷新界面
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############################## <存储中间数据进行调试> ##################################
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# def objdump(obj):
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# import pickle
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# with open('objdump.tmp', 'wb+') as f:
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# pickle.dump(obj, f)
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# return
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# def objload():
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# import pickle, os
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# if not os.path.exists('objdump.tmp'):
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# return
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# with open('objdump.tmp', 'rb') as f:
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# return pickle.load(f)
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# objdump([report_part_1, gpt_response_collection, history_to_return, file_manifest, project_folder, fp, llm_kwargs, chatbot])
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############################## <第二步,综合,单线程,分组+迭代处理> ##################################
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batchsize = 16 # 10个文件为一组
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report_part_2 = []
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file_rel_path = [os.path.relpath(fp, project_folder) for index, fp in enumerate(this_iteration_file_manifest)]
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# 把“请对下面的程序文件做一个概述” 替换成 精简的 "文件名:{all_file[index]}"
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for index, content in enumerate(this_iteration_gpt_response_collection):
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if index%2==0: this_iteration_gpt_response_collection[index] = f"{file_rel_path[index//2]}" # 只保留文件名节省token
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previous_iteration_files.extend([os.path.relpath(fp, project_folder) for index, fp in enumerate(this_iteration_file_manifest)])
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previous_iteration_files_string = ', '.join(previous_iteration_files)
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current_iteration_focus = ', '.join([os.path.relpath(fp, project_folder) for index, fp in enumerate(this_iteration_file_manifest)])
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i_say = f'根据以上分析,对程序的整体功能和构架重新做出概括。然后用一张markdown表格整理每个文件的功能(包括{previous_iteration_files_string})。'
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inputs_show_user = f'根据以上分析,对程序的整体功能和构架重新做出概括,由于输入长度限制,可能需要分组处理,本组文件为 {current_iteration_focus} + 已经汇总的文件组。'
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this_iteration_history = copy.deepcopy(this_iteration_gpt_response_collection)
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this_iteration_history.append(last_iteration_result)
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result = yield from request_gpt_model_in_new_thread_with_ui_alive(
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inputs=i_say, inputs_show_user=inputs_show_user, llm_kwargs=llm_kwargs, chatbot=chatbot,
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history=this_iteration_history, # 迭代之前的分析
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