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import gradio as gr
import os
import time
import shutil
import base64
from pdfquery import PDFQuery
pquery = PDFQuery()
def openai_create(s):
global pquery
return pquery.ask(s)
def chatgpt_clone(input, history, chatbot):
if input == "":
return chatbot, history, ""
history = history or []
s = list(sum(history, ()))
s.append(input)
inp = ' '.join(s)
output = openai_create(input)
history.append((inp, output))
chatbot.append((input, output))
return chatbot, history, ""
title_html = f"<h1 align=\"center\">Chat With Pdf</h1>"
gr_L1 = lambda: gr.Row().style()
gr_L2 = lambda scale, elem_id: gr.Column(scale=scale, elem_id=elem_id)
def pdf_to_markdown(file_obj):
try:
shutil.rmtree('./private_upload/')
except:
pass
time_tag = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
os.makedirs(f'private_upload/{time_tag}', exist_ok=True)
file_name = os.path.basename(file_obj.name)
destination = f'private_upload/{time_tag}/{file_name}'
shutil.copy(file_obj.name, destination)
global pquery
pquery.ingest(destination)
with open(destination, "rb") as f:
pdf = base64.b64encode(f.read()).decode('utf-8')
pdf_display = f'<embed src="data:application/pdf;base64,{pdf}" ' \
f'width="700" height="800" type="application/pdf">'
return [pdf_display, gr.update(visible=False),gr.update(visible=True),gr.update(visible=True),gr.update(visible=True),
gr.update(visible=True),gr.update(visible=True)]
# 清空
cle = lambda :""
with gr.Blocks(title="Chat With Pdf") as demo:
gr.HTML(title_html)
file = gr.File()
with gr_L1():
with gr_L2(scale=1.5, elem_id="gpt-chat"):
out = gr.Markdown()
with gr_L2(scale=1, elem_id="gpt-chat"):
title = gr.Markdown("""<h1><center><strong>文档问答 </strong></center></h1>
""", visible=False)
chatbot = gr.Chatbot(scale=3, height=600, visible=False)
with gr_L1():
message = gr.Textbox(placeholder="Input question here.", scale=10, visible=False)
state = gr.State([])
submit = gr.Button("发送", scale=1, visible=False)
file.upload(pdf_to_markdown, file, [out, file, out, title, chatbot, message, submit])
submit.click(chatgpt_clone, inputs=[message, state, chatbot], outputs=[chatbot, state, message])
demo.launch()
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