lekkalar commited on
Commit
23330df
·
1 Parent(s): 8cbd512

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +9 -1
app.py CHANGED
@@ -256,7 +256,10 @@ def ocr_converter(input_file):
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  ocrmypdf.ocr(image_pdf, image_pdf, skip_text=True, language="eng")
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  ocrmypdf.ocr(image_pdf, image_pdf, redo_ocr=True, language="eng")
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  return image_pdf
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-
 
 
 
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  def answer_query(query):
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  question = query
@@ -290,6 +293,10 @@ with gr.Blocks(css=css,theme=gr.themes.Monochrome()) as demo:
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  status = gr.Textbox(label="Status", placeholder="", interactive=False)
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  load_pdf = gr.Button("Upload PDF and generate embeddings").style(full_width=False)
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  with gr.Row():
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  input = gr.Textbox(label="Type in your question")
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  output = gr.Textbox(label="Answer")
@@ -581,6 +588,7 @@ with gr.Blocks(css=css,theme=gr.themes.Monochrome()) as demo:
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  load_pdf.click(load_pdf_and_generate_embeddings, inputs=[pdf_doc, open_ai_key, relevant_pages], outputs=status)
 
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  load_csv.click(load_csv_and_store_questionset_into_sqlite, inputs=[csv_file, document_type_for_questionset, tag_for_questionset], outputs=status_for_loading_csv)
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  load_questionsets.click(retrieve_document_type_and_questionsettag_from_sqlite,outputs=questionsets)
 
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  ocrmypdf.ocr(image_pdf, image_pdf, skip_text=True, language="eng")
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  ocrmypdf.ocr(image_pdf, image_pdf, redo_ocr=True, language="eng")
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  return image_pdf
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+
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+ def summarize_contents():
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+ question = "Generate a short summary of the contents along with no more than 3 leading/example questions"
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+ return pdf_qa.run(question)
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  def answer_query(query):
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  question = query
 
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  status = gr.Textbox(label="Status", placeholder="", interactive=False)
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  load_pdf = gr.Button("Upload PDF and generate embeddings").style(full_width=False)
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+ with gr.Row():
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+ summary = gr.Textbox(label="Summary")
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+ summarize_pdf = gr.Button("Have Moli Summarize the Contents").style(full_width=False)
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+
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  with gr.Row():
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  input = gr.Textbox(label="Type in your question")
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  output = gr.Textbox(label="Answer")
 
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  load_pdf.click(load_pdf_and_generate_embeddings, inputs=[pdf_doc, open_ai_key, relevant_pages], outputs=status)
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+ summarize_pdf.click(summarize_contents,outputs=summary)
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  load_csv.click(load_csv_and_store_questionset_into_sqlite, inputs=[csv_file, document_type_for_questionset, tag_for_questionset], outputs=status_for_loading_csv)
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  load_questionsets.click(retrieve_document_type_and_questionsettag_from_sqlite,outputs=questionsets)