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import gradio as gr | |
from modelscope.pipelines import pipeline | |
from modelscope.utils.constant import Tasks | |
from huggingface_hub import snapshot_download | |
import os | |
# Step 1: Download the model | |
model_dir = snapshot_download('opendatalab/PDF-Extract-Kit-1.0') | |
# Step 2: Initialize pipeline | |
pipe = pipeline( | |
task=Tasks.document_segmentation, | |
model=model_dir | |
) | |
# Step 3: Define inference function | |
def extract_info_from_pdf(pdf_file): | |
result = pipe({'file': pdf_file.name}) | |
return str(result) | |
# Step 4: Gradio UI | |
gr.Interface( | |
fn=extract_info_from_pdf, | |
inputs=gr.File(type="binary", label="Upload PDF"), | |
outputs="text", | |
title="PDF Extractor (PDF-Extract-Kit)" | |
).launch() | |