MeetingnoteParser

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MeetingnoteParser / app.py

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	# AI Meeting note parser
	# Author：Dr. Alec Li
	# Date：2024-01-26
	# Location: Richmond Hospital Canada

	import os

	os.system("sudo apt-get install xclip")


	import gradio as gr
	import nltk
	import pyclip
	import pytesseract
	from nltk.tokenize import sent_tokenize
	from transformers import MarianMTModel, MarianTokenizer
	import openai


	nltk.download('punkt')


	OCR_TR_DESCRIPTION = '''
	<div id="content_align">
	<span style="color:darkred;font-size:32px;font-weight:bold">
	模多多会议记录总结神器
	</span>
	</div>

	<div id="content_align">
	<span style="color:blue;font-size:16px;font-weight:bold">
	会议记录拍照/文本录入 -> 转文字 -> 翻译 -> 提炼会议纪要 -> 识别待办事项 -> 分配任务
	</div>

	<div id="content_align" style="margin-top: 10px;">
	作者: Dr. Alec Li
	</div>
	'''


	# Image path
	img_dir = "./data"

	# Get tesseract language list
	choices = os.popen('tesseract --list-langs').read().split('\n')[1:-1]



	# Translation model selection
	def model_choice(src="en", trg="zh"):
	# https://huggingface.co/Helsinki-NLP/opus-mt-zh-en
	# https://huggingface.co/Helsinki-NLP/opus-mt-en-zh
	model_name = f"Helsinki-NLP/opus-mt-{src}-{trg}" # Model name

	tokenizer = MarianTokenizer.from_pretrained(model_name) # Tokenizer
	model = MarianMTModel.from_pretrained(model_name) # model

	return tokenizer, model


	# Convert tesseract language list to pytesseract language
	def ocr_lang(lang_list):
	lang_str = ""
	lang_len = len(lang_list)
	if lang_len == 1:
	return lang_list[0]
	else:
	for i in range(lang_len):
	lang_list.insert(lang_len - i, "+")

	lang_str = "".join(lang_list[:-1])
	return lang_str


	#import pytesseract


	# Set Tesseract executable path in Colab virtal environment
	#pytesseract.pytesseract.tesseract_cmd = "/usr/bin/tesseract"

	# Set up the Tesseract data directory
	#os.environ["TESSDATA_PREFIX"] = "/usr/share/tesseract-ocr/4.00/tessdata"

	#def ocr_tesseract(img, languages):
	# custom_config = f'--oem 3 --psm 6 -l {ocr_lang(languages)}'
	# ocr_str = pytesseract.image_to_string(img, config=custom_config)
	# return ocr_str

	# ocr tesseract
	def ocr_tesseract(img, languages):
	ocr_str = pytesseract.image_to_string(img, lang=ocr_lang(languages))
	return ocr_str


	# Clear content
	def clear_content():
	return None


	# copy to clipboard
	def cp_text(input_text):
	# sudo apt-get install xclip
	try:
	pyclip.copy(input_text)
	except Exception as e:
	print("sudo apt-get install xclip")
	print(e)


	# 清除剪贴板
	def cp_clear():
	pyclip.clear()


	# 翻译
	def translate(input_text, inputs_transStyle):
	# 参考：https://huggingface.co/docs/transformers/model_doc/marian
	if input_text is None or input_text == "":
	return "System prompt: There is no content to translate!"

	# 选择翻译模型
	trans_src, trans_trg = inputs_transStyle.split("-")[0], inputs_transStyle.split("-")[1]
	tokenizer, model = model_choice(trans_src, trans_trg)

	translate_text = ""
	input_text_list = input_text.split("\n\n")

	translate_text_list_tmp = []
	for i in range(len(input_text_list)):
	if input_text_list[i] != "":
	translate_text_list_tmp.append(input_text_list[i])

	for i in range(len(translate_text_list_tmp)):
	translated_sub = model.generate(
	**tokenizer(sent_tokenize(translate_text_list_tmp[i]), return_tensors="pt", truncation=True, padding=True))
	tgt_text_sub = [tokenizer.decode(t, skip_special_tokens=True) for t in translated_sub]
	translate_text_sub = "".join(tgt_text_sub)
	translate_text = translate_text + "\n\n" + translate_text_sub

	return translate_text[2:]


	# 在 https://platform.openai.com/signup 注册并获取 API 密钥

	openai.api_key = os.getenv('OPENAI_API_KEY')



	def generate_summary(text_input):
	response = openai.ChatCompletion.create(
	model="gpt-3.5-turbo",
	messages=[
	{"role": "system", "content": "你是一个非常能干的办公助手. 请把会议记录再此总结成会议纪要，根据时间线详细识别出不同的会议主题，并进行总结。请识别出待办事项，并根据时间点进行任务分配，并在最后总结出决策点给领导决策。"},
	{"role": "user", "content": text_input}
	]
	)
	summary = response["choices"][0]["message"]["content"].strip()
	return summary


	def main():

	with gr.Blocks(css='style.css') as ocr_tr:
	gr.Markdown(OCR_TR_DESCRIPTION)

	# -------------- OCR 文字提取 --------------
	with gr.Column():

	with gr.Row():
	gr.Markdown("### 第一步: 文本总结")

	# Add a text box for direct input of text
	with gr.Row():
	inputs_direct_text = gr.Textbox(label="直接输入文本", lines=10)

	# Text box to display the generated summary from direct input
	with gr.Row():
	outputs_direct_summary_text = gr.Textbox(label="生成的概要", lines=10)

	with gr.Row():
	with gr.Row():
	# Button to generate summary from directly input text
	generate_direct_summary_btn = gr.Button('生成概要', variant="primary")
	with gr.Row():
	clear_direct_summary_btn = gr.Button('清除概要')


	with gr.Row():
	gr.Markdown("### 第二步: 文本抽取")

	with gr.Row():
	with gr.Column():
	with gr.Row():
	inputs_img = gr.Image(image_mode="RGB", type="pil", label="image")
	with gr.Row():
	inputs_lang = gr.CheckboxGroup(choices=["chi_sim", "eng"],
	type="value",
	value=['eng'],
	label='language')

	with gr.Row():
	clear_img_btn = gr.Button('清除')
	ocr_btn = gr.Button(value='图片文本抽取', variant="primary")

	with gr.Column():
	with gr.Row():
	outputs_text = gr.Textbox(label="抽取的文本", lines=10)
	with gr.Row():
	inputs_transStyle = gr.Radio(choices=["zh-en", "en-zh"],
	type="value",
	value="zh-en",
	label='翻译模式')
	with gr.Row():
	clear_text_btn = gr.Button('清除')
	translate_btn = gr.Button(value='翻译', variant="primary")

	# Add a text box to display the generated summary
	with gr.Row():
	outputs_summary_text = gr.Textbox(label="生成的摘要", lines=20)


	with gr.Row():
	with gr.Row():
	generate_summary_btn = gr.Button('生成摘要', variant="primary")
	with gr.Row():
	clear_summary_btn = gr.Button('清除摘要')

	with gr.Row():
	example_list = [["./data/test.png", ["eng"]], ["./data/test02.png", ["eng"]],
	["./data/test03.png", ["chi_sim"]]]
	gr.Examples(example_list, [inputs_img, inputs_lang], outputs_text, ocr_tesseract, cache_examples=False)

	# -------------- 翻译 --------------
	with gr.Column():

	with gr.Row():
	gr.Markdown("### 第三步: 翻译")

	with gr.Row():
	outputs_tr_text = gr.Textbox(label="Translate Content", lines=20)

	with gr.Row():
	cp_clear_btn = gr.Button(value='清除剪贴板')
	cp_btn = gr.Button(value='复制到剪贴板', variant="primary")

	# ---------------------- OCR Tesseract ----------------------
	ocr_btn.click(fn=ocr_tesseract, inputs=[inputs_img, inputs_lang], outputs=[
	outputs_text,])
	clear_img_btn.click(fn=clear_content, inputs=[], outputs=[inputs_img])

	# ---------------------- Direct Text Summarization ----------------------
	generate_direct_summary_btn.click(fn=generate_summary, inputs=[inputs_direct_text],
	outputs=[outputs_direct_summary_text])
	clear_direct_summary_btn.click(fn=clear_content, inputs=[], outputs=[inputs_direct_text, outputs_direct_summary_text])

	# ---------------------- Summarization ----------------------
	# To update the click event of the button, use generate_summary directly
	generate_summary_btn.click(fn=generate_summary, inputs=[outputs_text],
	outputs=[outputs_summary_text])
	clear_summary_btn.click(fn=clear_content, inputs=[], outputs=[outputs_summary_text])


	# ---------------------- Translate ----------------------
	translate_btn.click(fn=translate, inputs=[outputs_text, inputs_transStyle], outputs=[outputs_tr_text])
	clear_text_btn.click(fn=clear_content, inputs=[], outputs=[outputs_text])

	# ---------------------- Copy to clipboard ----------------------
	cp_btn.click(fn=cp_text, inputs=[outputs_tr_text], outputs=[])
	cp_clear_btn.click(fn=cp_clear, inputs=[], outputs=[])

	ocr_tr.launch(inbrowser=True)


	if __name__ == '__main__':
	main()