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ai42
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Parent(s):
e0a9079
Update app.py
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app.py
CHANGED
@@ -1,15 +1,17 @@
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import os
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os.environ["TOKENIZERS_PARALLELISM"] = "false"
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from PIL import Image, ImageDraw
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import traceback
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import gradio as gr
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import torch
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from docquery import pipeline
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from docquery.document import load_document,
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from docquery.ocr_reader import get_ocr_reader
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@@ -86,9 +88,10 @@ examples = [
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"What are net sales for 2020?",
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],
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[
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"
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# [
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# "docquery.png",
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# "How many likes does the space have?",
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@@ -103,6 +106,8 @@ question_files = {
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"What are net sales for 2020?": "statement.pdf",
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"How many likes does the space have?": "https://huggingface.co/spaces/impira/docquery",
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"What is the title of post number 5?": "https://news.ycombinator.com",
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}
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@@ -145,6 +150,10 @@ def process_upload(file):
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gr.update(visible=False, value=None),
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None,
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)
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colors = ["#64A087", "green", "black"]
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@@ -227,7 +236,7 @@ CSS = """
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padding-bottom: 2px !important;
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padding-left: 8px !important;
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padding-right: 8px !important;
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}
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.gradio-container .gr-button-primary {
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background: linear-gradient(180deg, #CDF9BE 0%, #AFF497 100%);
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@@ -293,19 +302,15 @@ gradio-app h2, .gradio-app h2 {
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"""
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with gr.Blocks(css=CSS) as demo:
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gr.Markdown("#
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"DocQuery (created by [Impira](https://impira.com?utm_source=huggingface&utm_medium=referral&utm_campaign=docquery_space))"
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" uses LayoutLMv1 fine-tuned on DocVQA, a document visual question"
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" answering dataset, as well as SQuAD, which boosts its English-language comprehension."
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" To use it, simply upload an image or PDF, type a question, and click 'submit', or "
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" click one of the examples to load them."
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" DocQuery is MIT-licensed and available on [Github](https://github.com/impira/docquery)."
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)
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document = gr.Variable()
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example_question = gr.Textbox(visible=False)
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example_image = gr.Image(visible=False)
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with gr.Row(equal_height=True):
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with gr.Column():
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@@ -429,5 +434,6 @@ with gr.Blocks(css=CSS) as demo:
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outputs=[document, question, image, img_clear_button, output, output_text],
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)
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if __name__ == "__main__":
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demo.launch(enable_queue=False)
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import os
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import io
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os.environ["TOKENIZERS_PARALLELISM"] = "false"
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from PIL import Image, ImageDraw
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import traceback
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import gradio as gr
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import torch
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from docquery import pipeline
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from docquery.document import load_document, ImageDocumenta
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from docquery.ocr_reader import get_ocr_reader
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"What are net sales for 2020?",
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],
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[
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"saleData.pdf",
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"What is the highest sale amount of televsion in east region?",
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]
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# [
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# "docquery.png",
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# "How many likes does the space have?",
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"What are net sales for 2020?": "statement.pdf",
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"How many likes does the space have?": "https://huggingface.co/spaces/impira/docquery",
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"What is the title of post number 5?": "https://news.ycombinator.com",
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"What is the highest sale amount of television in east region?": "SaleData.pdf", # Add the PDF file here
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}
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gr.update(visible=False, value=None),
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None,
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)
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colors = ["#64A087", "green", "black"]
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padding-bottom: 2px !important;
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padding-left: 8px !important;
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padding-right: 8px !important;
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margin-top: 10px;
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}
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.gradio-container .gr-button-primary {
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background: linear-gradient(180deg, #CDF9BE 0%, #AFF497 100%);
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"""
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with gr.Blocks(css=CSS) as demo:
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gr.Markdown("# Document Query Engine")
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document = gr.Variable()
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example_question = gr.Textbox(visible=False)
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example_image = gr.Image(visible=False)
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excel_upload = gr.File(label="Upload Excel", type="xlsx", elem_id="excel-upload-box")
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excel_process_button = gr.Button("Process Excel", variant="primary", elem_id="excel-process-button")
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with gr.Row(equal_height=True):
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with gr.Column():
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outputs=[document, question, image, img_clear_button, output, output_text],
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)
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if __name__ == "__main__":
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demo.launch(enable_queue=False)
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