Spaces:
Running
Running
added feature to parse all text from paper pdf
Browse files
app.py
CHANGED
@@ -1,24 +1,84 @@
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import re
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import gradio as gr
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import requests
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import xmltodict
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from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
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from transformers.pipelines.question_answering import QuestionAnsweringPipeline
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QA_MODEL_NAME = "ixa-ehu/SciBERT-SQuAD-QuAC"
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def clean_text(text: str) -> str:
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text = re.sub("\
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return text
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def get_qa_pipeline(qa_model_name: str = QA_MODEL_NAME) -> QuestionAnsweringPipeline:
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demo = gr.Blocks()
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with demo:
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gr.Markdown("#
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label="arXiv Paper
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)
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fetch_document_button.click(
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fn=
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)
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question = gr.Textbox(label="Ask a question about the paper:")
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answer = gr.Textbox("Answer:")
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ask_button = gr.Button("Ask me π€")
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ask_button.click(fn=get_answer, inputs=[question, paper_summary], outputs=answer)
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from __future__ import annotations
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import re
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from dataclasses import dataclass
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from typing import Tuple
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import gradio as gr
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import requests
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import xmltodict
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from PyPDF2 import PdfReader
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from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
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from transformers.pipelines.question_answering import QuestionAnsweringPipeline
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QA_MODEL_NAME = "ixa-ehu/SciBERT-SQuAD-QuAC"
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TEMP_PDF_PATH = "/tmp/arxiv_paper.pdf"
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ARXIV_URL_PATTERN = r"(http|https)://(arxiv.org/pdf/)+([0-9]+\.[0-9]+)\.pdf"
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def is_valid_url(url: str) -> bool:
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return re.fullmatch(ARXIV_URL_PATTERN, url) is not None
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@dataclass
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class PaperMetaData:
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arxiv_id: str
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title: str
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summary: str
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text: str
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@staticmethod
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def _clean_field(text: str) -> str:
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text = re.sub(r"\n", " ", text)
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text = re.sub(r"\s+", " ", text)
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return text
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@classmethod
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def from_api(cls, arxiv_id: str, text: str) -> PaperMetaData:
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paper_url = f"http://export.arxiv.org/api/query?id_list={arxiv_id}"
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response = requests.get(paper_url)
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paper_dict = xmltodict.parse(response.content)["feed"]["entry"]
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return PaperMetaData(
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arxiv_id=arxiv_id,
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title=cls._clean_field(paper_dict["title"]),
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summary=cls._clean_field(paper_dict["summary"]),
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text=text,
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)
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def clean_text(text: str) -> str:
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text = re.sub(r"\x03|\x02", "", text)
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text = re.sub(r"-\s+", "", text)
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text = re.sub(r"\n", " ", text)
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return text
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class PDFPaper:
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def __init__(self, url: str):
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if not is_valid_url(url):
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raise ValueError("The URL provided is not a valid arxiv PDF url.")
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self.url = url
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self.arxiv_id = re.fullmatch(ARXIV_URL_PATTERN, url).group(3)
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def _download(self, download_path: str = TEMP_PDF_PATH) -> None:
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pdf_r = requests.get(self.url)
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pdf_r.raise_for_status()
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with open(download_path, "wb") as pdf_file:
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pdf_file.write(pdf_r.content)
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def read_text(self, pdf_path: str = TEMP_PDF_PATH) -> str:
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self._download(pdf_path)
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reader = PdfReader(pdf_path)
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pdf_text = " ".join([page.extract_text() for page in reader.pages])
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return clean_text(pdf_text)
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def get_paper_full_data(self) -> PaperMetaData:
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return PaperMetaData.from_api(arxiv_id=self.arxiv_id, text=self.read_text())
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def get_paper_data(url: str) -> Tuple[str, str, str]:
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paper_data = PDFPaper(url=url).get_paper_full_data()
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return paper_data.title, paper_data.summary, paper_data.text
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def get_qa_pipeline(qa_model_name: str = QA_MODEL_NAME) -> QuestionAnsweringPipeline:
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demo = gr.Blocks()
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with demo:
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gr.Markdown("# arXiv Paper Q&A\nImport an arXiv paper and ask questions about it!")
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gr.Markdown("## π Import the paper on arXiv")
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arxiv_url = gr.Textbox(
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label="arXiv Paper URL", placeholder="Insert here the URL of a paper on arXiv"
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)
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fetch_document_button = gr.Button("Import Paper")
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paper_title = gr.Textbox(label="Paper Title")
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paper_summary = gr.Textbox(label="Paper Summary")
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paper_text = gr.Textbox(label="Paper Text")
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fetch_document_button.click(
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fn=get_paper_data,
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inputs=arxiv_url,
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outputs=[paper_title, paper_summary, paper_text],
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)
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gr.Markdown("## π€¨ Ask a question about the paper")
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question = gr.Textbox(label="Ask a question about the paper:")
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ask_button = gr.Button("Ask me π€")
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answer = gr.Textbox(label="Answer:")
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ask_button.click(fn=get_answer, inputs=[question, paper_summary], outputs=answer)
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