Spaces:
Build error
Build error
disallow special token + limit num of file < 512
Browse files
crazy_functions/Latex全文润色.py
CHANGED
@@ -14,7 +14,7 @@ class PaperFileGroup():
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import tiktoken
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from toolbox import get_conf
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enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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-
def get_token_num(txt): return len(enc.encode(txt))
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self.get_token_num = get_token_num
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def run_file_split(self, max_token_limit=1900):
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import tiktoken
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from toolbox import get_conf
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enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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self.get_token_num = get_token_num
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def run_file_split(self, max_token_limit=1900):
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crazy_functions/Latex全文翻译.py
CHANGED
@@ -14,7 +14,7 @@ class PaperFileGroup():
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import tiktoken
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from toolbox import get_conf
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enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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-
def get_token_num(txt): return len(enc.encode(txt))
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self.get_token_num = get_token_num
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def run_file_split(self, max_token_limit=1900):
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import tiktoken
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from toolbox import get_conf
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enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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self.get_token_num = get_token_num
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def run_file_split(self, max_token_limit=1900):
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crazy_functions/crazy_utils.py
CHANGED
@@ -6,7 +6,7 @@ def input_clipping(inputs, history, max_token_limit):
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import numpy as np
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from toolbox import get_conf
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enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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def get_token_num(txt): return len(enc.encode(txt))
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mode = 'input-and-history'
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# 当 输入部分的token占比 小于 全文的一半时,只裁剪历史
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@@ -23,7 +23,7 @@ def input_clipping(inputs, history, max_token_limit):
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while n_token > max_token_limit:
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where = np.argmax(everything_token)
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encoded = enc.encode(everything[where])
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clipped_encoded = encoded[:len(encoded)-delta]
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everything[where] = enc.decode(clipped_encoded)[:-1] # -1 to remove the may-be illegal char
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everything_token[where] = get_token_num(everything[where])
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import numpy as np
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from toolbox import get_conf
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enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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mode = 'input-and-history'
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# 当 输入部分的token占比 小于 全文的一半时,只裁剪历史
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while n_token > max_token_limit:
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where = np.argmax(everything_token)
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encoded = enc.encode(everything[where], disallowed_special=())
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clipped_encoded = encoded[:len(encoded)-delta]
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everything[where] = enc.decode(clipped_encoded)[:-1] # -1 to remove the may-be illegal char
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everything_token[where] = get_token_num(everything[where])
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crazy_functions/代码重写为全英文_多线程.py
CHANGED
@@ -62,7 +62,7 @@ def 全项目切换英文(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys_
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import tiktoken
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from toolbox import get_conf
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enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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def get_token_fn(txt): return len(enc.encode(txt))
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# 第6步:任务函数
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import tiktoken
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from toolbox import get_conf
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enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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def get_token_fn(txt): return len(enc.encode(txt, disallowed_special=()))
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# 第6步:任务函数
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crazy_functions/批量Markdown翻译.py
CHANGED
@@ -14,7 +14,7 @@ class PaperFileGroup():
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import tiktoken
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from toolbox import get_conf
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enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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-
def get_token_num(txt): return len(enc.encode(txt))
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self.get_token_num = get_token_num
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def run_file_split(self, max_token_limit=1900):
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import tiktoken
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from toolbox import get_conf
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enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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self.get_token_num = get_token_num
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def run_file_split(self, max_token_limit=1900):
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crazy_functions/批量翻译PDF文档_多线程.py
CHANGED
@@ -70,7 +70,7 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
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from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
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from toolbox import get_conf
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enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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def get_token_num(txt): return len(enc.encode(txt))
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paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
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txt=file_content, get_token_fn=get_token_num, limit=TOKEN_LIMIT_PER_FRAGMENT)
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page_one_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
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from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
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from toolbox import get_conf
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enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
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txt=file_content, get_token_fn=get_token_num, limit=TOKEN_LIMIT_PER_FRAGMENT)
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page_one_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
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crazy_functions/理解PDF文档内容.py
CHANGED
@@ -19,7 +19,7 @@ def 解析PDF(file_name, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
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from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
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from toolbox import get_conf
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enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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def get_token_num(txt): return len(enc.encode(txt))
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paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
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txt=file_content, get_token_fn=get_token_num, limit=TOKEN_LIMIT_PER_FRAGMENT)
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page_one_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
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from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
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from toolbox import get_conf
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enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
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paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
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txt=file_content, get_token_fn=get_token_num, limit=TOKEN_LIMIT_PER_FRAGMENT)
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page_one_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
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crazy_functions/解析项目源代码.py
CHANGED
@@ -11,7 +11,8 @@ def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
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history_array = []
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sys_prompt_array = []
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report_part_1 = []
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############################## <第一步,逐个文件分析,多线程> ##################################
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for index, fp in enumerate(file_manifest):
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with open(fp, 'r', encoding='utf-8', errors='replace') as f:
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history_array = []
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sys_prompt_array = []
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report_part_1 = []
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assert len(file_manifest) <= 512, "源文件太多, 请缩减输入文件的数量, 或者删除此行并拆分file_manifest以保证结果能被分批存储。"
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############################## <第一步,逐个文件分析,多线程> ##################################
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for index, fp in enumerate(file_manifest):
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with open(fp, 'r', encoding='utf-8', errors='replace') as f:
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