Update app.py
Browse files
app.py
CHANGED
@@ -5,7 +5,7 @@ from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
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# Function to extract text from PDF
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def extract_text_from_pdf(pdf_path):
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text = ""
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document = fitz.open(pdf_path)
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for page_num in range(len(document)):
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page = document.load_page(page_num)
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text += page.get_text()
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@@ -22,7 +22,7 @@ qa_pipeline = pipeline("question-answering", model=model, tokenizer=tokenizer)
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# Function to answer questions based on the PDF content
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def answer_question(pdf_file, question):
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# Extract text from the uploaded PDF file
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content = extract_text_from_pdf(pdf_file
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# Get the answer using the question-answering pipeline
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result = qa_pipeline(question=question, context=content)
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return result['answer']
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@@ -30,7 +30,7 @@ def answer_question(pdf_file, question):
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# Define the Gradio interface
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iface = gr.Interface(
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fn=answer_question,
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inputs=[gr.
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outputs="text",
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title="DistilBERT Question Answering",
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description="Upload a PDF and ask questions based on the content of the PDF."
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# Function to extract text from PDF
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def extract_text_from_pdf(pdf_path):
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text = ""
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document = fitz.open(pdf_path.name)
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for page_num in range(len(document)):
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page = document.load_page(page_num)
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text += page.get_text()
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# Function to answer questions based on the PDF content
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def answer_question(pdf_file, question):
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# Extract text from the uploaded PDF file
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content = extract_text_from_pdf(pdf_file)
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# Get the answer using the question-answering pipeline
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result = qa_pipeline(question=question, context=content)
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return result['answer']
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# Define the Gradio interface
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iface = gr.Interface(
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fn=answer_question,
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inputs=[gr.File(label="PDF File", file_types=[".pdf"]), gr.Textbox(lines=2, placeholder="Ask a question...")],
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outputs="text",
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title="DistilBERT Question Answering",
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description="Upload a PDF and ask questions based on the content of the PDF."
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