chunzhi/chatgpt_academic
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Update crazy_functional.py with new functionality deal with PDF (#1500)

Browse Source
This commit is contained in:
Menghuan1918 2024-01-22 14:55:39 +08:00 committed by GitHub
parent 113067c6ab
commit 1506c19834
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
2 changed files with 23 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
crazy_functional.py
View File

@ -74,7 +74,7 @@ def get_crazy_functions():
"Group": "对话",
"Color": "stop",
"AsButton": False,
"Info" : "基于当前对话生成多种Mermaid图表,图表类型由对话模型自行判断",
"Info" : "基于当前对话或PDF生成多种Mermaid图表,图表类型由模型判断",
"Function": HotReload(生成多种Mermaid图表),
},
"批量总结Word文档": {

25
crazy_functions/生成多种Mermaid图表.py
View File

@ -1,5 +1,6 @@
from toolbox import CatchException, update_ui
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
from .crazy_utils import read_and_clean_pdf_text
import datetime
#暂时只写了这几种的PROMPT
@ -143,7 +144,7 @@ def 解析历史输入(history,llm_kwargs,chatbot):
from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
txt = breakdown_text_to_satisfy_token_limit(txt=txt, limit=TOKEN_LIMIT_PER_FRAGMENT, llm_model=llm_kwargs['llm_model'])
############################## <第 1 步，迭代地历遍整个文章，提取精炼信息> ##################################
i_say_show_user = f'首先你从历史记录中提取摘要。'; gpt_say = "[Local Message] 收到。" # 用户提示
i_say_show_user = f'首先你从历史记录或文件中提取摘要。'; gpt_say = "[Local Message] 收到。" # 用户提示
chatbot.append([i_say_show_user, gpt_say]); yield from update_ui(chatbot=chatbot, history=history) # 更新UI
results = []
MAX_WORD_TOTAL = 4096
@ -205,6 +206,21 @@ def 解析历史输入(history,llm_kwargs,chatbot):
history.append(gpt_say)
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
def 输入区文件处理(txt):
if txt == "": return False, txt
success = True
import glob
from .crazy_utils import get_files_from_everything
file_pdf,pdf_manifest,folder_pdf = get_files_from_everything(txt, '.pdf')
if not file_pdf or len(pdf_manifest) == 0:
return False, txt #如不是pdf文件则返回输入区内容
final_result = ""
for index, fp in enumerate(pdf_manifest):
file_content, page_one = read_and_clean_pdf_text(fp) # （尝试）按照章节切割PDF
file_content = file_content.encode('utf-8', 'ignore').decode() # avoid reading non-utf8 chars
final_result += file_content
return True, final_result
@CatchException
def 生成多种Mermaid图表(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
"""
@ -216,9 +232,12 @@ def 生成多种Mermaid图表(txt, llm_kwargs, plugin_kwargs, chatbot, history,
system_prompt 给gpt的静默提醒
web_port 当前软件运行的端口号
"""
import os
chatbot.append([
"函数插件功能？",
"根据当前聊天历史绘制多种mermaid图表的功能，将会首先判断适合的图表类型，随后绘制图表。函数插件贡献者: Menghuan1918"])
"根据当前聊天历史或PDF中绘制多种mermaid图表的功能，将会首先判断适合的图表类型，随后绘制图表。函数插件贡献者: Menghuan1918"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
if txt == "": txt = "空白的输入栏" # :)虽然暂时没用到输入栏内容
if os.path.exists(txt): #如输入区无内容则直接解析历史记录
file_exist, txt = 输入区文件处理(txt)
history.append(txt) #将解析后的txt传递加入到历史中
yield from 解析历史输入(history,llm_kwargs,chatbot)