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import gradio as gr
import os
import json
import base64
import tempfile
from pathlib import Path
EXTRACTORS = ['pdf_plumber', 'py_pdf', 'docling', 'extractous', 'pypdfium2', 'pymupdf', 'pymupdf_llm']
def add_page_breaks(text, page_offsets):
"""Add page break markers to text based on page_offsets."""
if not page_offsets:
return text
result = []
last_offset = 0
for offset in page_offsets:
result.append(text[last_offset:offset])
result.append("\n<---page-break--->\n")
last_offset = offset
# Add any remaining text
if last_offset < len(text):
result.append(text[last_offset:])
return "".join(result)
class ExtractorComparer:
def __init__(self):
self.json_files = []
self.current_index = 0
self.current_data = None
self.temp_pdf_path = None
self.current_pdf_bytes = None
def load_files(self, directory_path):
"""Load all JSON files from the specified directory."""
self.json_files = []
try:
for filename in os.listdir(directory_path):
if filename.endswith('.json') or filename.endswith('.jsonl'):
self.json_files.append(os.path.join(directory_path, filename))
if self.json_files:
self.current_index = 0
file_progress, annotation_status = self.get_progress_info()
return file_progress, annotation_status
else:
return "No JSON files found", "No files loaded"
except Exception as e:
return f"Error loading files: {str(e)}", "Error"
def load_current_file(self):
"""Load the current JSON file data."""
if not self.json_files:
return None, "N/A", "N/A"
try:
with open(self.json_files[self.current_index], 'r') as f:
self.current_data = json.load(f)
# Extract PDF bytes from pdf_plumber
pdf_bytes = None
debug_info = ""
if 'pdf_plumber' in self.current_data:
plumber_data = self.current_data['pdf_plumber']
if 'media' in plumber_data and plumber_data['media'] and isinstance(plumber_data['media'], list) and len(plumber_data['media']) > 0:
media_item = plumber_data['media'][0]
if 'media_bytes' in media_item and media_item['media_bytes']:
try:
pdf_bytes = base64.b64decode(media_item['media_bytes'])
self.current_pdf_bytes = pdf_bytes
except Exception as e:
debug_info = f"Error decoding media_bytes: {str(e)}"
# Create temporary file for the PDF if we have bytes
if pdf_bytes:
if self.temp_pdf_path:
try:
os.remove(self.temp_pdf_path)
except:
pass
with tempfile.NamedTemporaryFile(delete=False, suffix='.pdf') as temp_file:
temp_file.write(pdf_bytes)
self.temp_pdf_path = temp_file.name
# Convert to base64 for passing to the frontend
base64_pdf = base64.b64encode(pdf_bytes).decode('utf-8')
# Generate progress information
file_progress, annotation_status = self.get_progress_info()
return base64_pdf, file_progress, annotation_status
else:
file_progress, annotation_status = self.get_progress_info()
return None, file_progress, annotation_status
except Exception as e:
return None, "Error loading file", "No annotation"
def get_progress_info(self):
"""Generate progress information and annotation status."""
if not self.json_files:
return "No files loaded", "No annotation"
current_file = self.json_files[self.current_index]
filename = Path(current_file).name
# File progress information
file_progress = f"File {self.current_index + 1} of {len(self.json_files)}: {filename}"
# Check if this file has been annotated with a best extractor
best_extractor_file = os.path.splitext(current_file)[0] + "_best.txt"
annotation_status = "Not annotated"
if os.path.exists(best_extractor_file):
try:
with open(best_extractor_file, 'r') as f:
best_extractor = f.read().strip()
annotation_status = f"Best extractor: {best_extractor}"
except:
pass
# Count total annotated files
annotated_count = 0
for json_file in self.json_files:
best_file = os.path.splitext(json_file)[0] + "_best.txt"
if os.path.exists(best_file):
annotated_count += 1
file_progress = f"{file_progress} (Annotated: {annotated_count}/{len(self.json_files)})"
return file_progress, annotation_status
def get_extractor_text(self, extractor_name):
"""Get text with page breaks for the specified extractor."""
if not self.current_data or extractor_name not in self.current_data:
return ""
extractor_data = self.current_data[extractor_name]
if 'text' not in extractor_data:
return f"No text found for {extractor_name}"
text = extractor_data.get('text', '')
# Get page offsets
page_offsets = []
if 'media' in extractor_data and extractor_data['media'] and len(extractor_data['media']) > 0:
media_item = extractor_data['media'][0]
if 'metadata' in media_item and 'pdf_metadata' in media_item['metadata'] and 'page_offsets' in media_item['metadata']['pdf_metadata']:
page_offsets = media_item['metadata']['pdf_metadata']['page_offsets']
return add_page_breaks(text, page_offsets)
def next_pdf(self):
"""Load the next PDF in the list."""
if not self.json_files:
return None, "N/A", "N/A"
self.current_index = (self.current_index + 1) % len(self.json_files)
return self.load_current_file()
def prev_pdf(self):
"""Load the previous PDF in the list."""
if not self.json_files:
return None, "N/A", "N/A"
self.current_index = (self.current_index - 1) % len(self.json_files)
return self.load_current_file()
def set_best_extractor(self, extractor_name):
"""Record that this extractor is the best for the current file."""
if not self.json_files or not self.current_data:
return "N/A", "N/A"
try:
# Create a record about the best extractor
result_file = os.path.splitext(self.json_files[self.current_index])[0] + "_best.txt"
with open(result_file, 'w') as f:
f.write(extractor_name)
# Get updated progress info after annotation
file_progress, annotation_status = self.get_progress_info()
return file_progress, annotation_status
except Exception as e:
return "Error saving annotation", "No annotation"
def create_interface():
comparer = ExtractorComparer()
# Custom CSS for basic font in text areas
custom_css = """
.extraction-text textarea {
font-family: Arial, Helvetica, sans-serif !important;
font-size: 14px !important;
line-height: 1.5 !important;
}
"""
with gr.Blocks(title="PDF Extractor Comparer", theme="soft", css=custom_css) as demo:
gr.Markdown("## PDF Extractor Comparer")
with gr.Row():
directory_input = gr.Textbox(
label="Path to JSON Directory",
placeholder="e.g., /path/to/your/json/files"
)
load_button = gr.Button("Load PDFs", variant="primary")
# Main layout: PDF viewer on left, status and controls on right
with gr.Row():
# Left column: PDF viewer
with gr.Column(scale=3):
# PDF viewer using iframe with JavaScript handling
pdf_viewer_html = gr.HTML(
label="PDF Document",
value='''
<div style="width:100%; height:700px; position:relative; border:1px solid #ddd;">
<iframe id="pdf-iframe" width="100%" height="100%" style="border:none;" src="about:blank"></iframe>
<div id="pdf-fallback" style="position:absolute; top:0; left:0; width:100%; height:100%;
display:flex; align-items:center; justify-content:center; padding:20px; text-align:center;">
Click "Load PDFs" to start viewing documents.
</div>
</div>
'''
)
# Hidden component to store the Base64 PDF data
pdf_data_hidden = gr.Textbox(visible=False, elem_id="pdf_base64_data")
# Right column: Progress and controls
with gr.Column(scale=1):
# Progress information
file_progress_output = gr.Textbox(label="File Progress", interactive=False)
annotation_status_output = gr.Textbox(label="Annotation Status", interactive=False)
# Navigation
with gr.Row():
prev_button = gr.Button("⬅️ Previous", elem_id="prev_button")
next_button = gr.Button("Next ➡️", elem_id="next_button")
# Best extractor selection
gr.Markdown("### Select Best Extractor")
extractor_buttons = []
for extractor in EXTRACTORS:
button = gr.Button(extractor, variant="secondary")
extractor_buttons.append(button)
button.click(
comparer.set_best_extractor,
inputs=[gr.Textbox(value=extractor, visible=False)],
outputs=[file_progress_output, annotation_status_output]
)
# Extractors section below the PDF
gr.Markdown("### Extractor Comparison")
# Extractor dropdowns
with gr.Row():
extractor1_dropdown = gr.Dropdown(
choices=EXTRACTORS,
label="Extractor 1",
value=EXTRACTORS[0] if EXTRACTORS else None
)
extractor2_dropdown = gr.Dropdown(
choices=EXTRACTORS,
label="Extractor 2",
value=EXTRACTORS[1] if len(EXTRACTORS) > 1 else EXTRACTORS[0] if EXTRACTORS else None
)
# Extractor text outputs with applied class for styling
with gr.Row():
extractor1_text = gr.Textbox(
label="Extractor 1 Output",
lines=15,
elem_classes=["extraction-text"]
)
extractor2_text = gr.Textbox(
label="Extractor 2 Output",
lines=15,
elem_classes=["extraction-text"]
)
# Event handlers
load_button.click(
comparer.load_files,
inputs=[directory_input],
outputs=[file_progress_output, annotation_status_output]
).then(
comparer.load_current_file,
outputs=[pdf_data_hidden, file_progress_output, annotation_status_output]
).then(
comparer.get_extractor_text,
inputs=[extractor1_dropdown],
outputs=[extractor1_text]
).then(
comparer.get_extractor_text,
inputs=[extractor2_dropdown],
outputs=[extractor2_text]
)
prev_button.click(
comparer.prev_pdf,
outputs=[pdf_data_hidden, file_progress_output, annotation_status_output]
).then(
comparer.get_extractor_text,
inputs=[extractor1_dropdown],
outputs=[extractor1_text]
).then(
comparer.get_extractor_text,
inputs=[extractor2_dropdown],
outputs=[extractor2_text]
)
next_button.click(
comparer.next_pdf,
outputs=[pdf_data_hidden, file_progress_output, annotation_status_output]
).then(
comparer.get_extractor_text,
inputs=[extractor1_dropdown],
outputs=[extractor1_text]
).then(
comparer.get_extractor_text,
inputs=[extractor2_dropdown],
outputs=[extractor2_text]
)
extractor1_dropdown.change(
comparer.get_extractor_text,
inputs=[extractor1_dropdown],
outputs=[extractor1_text]
)
extractor2_dropdown.change(
comparer.get_extractor_text,
inputs=[extractor2_dropdown],
outputs=[extractor2_text]
)
# Add JavaScript to handle PDF display
demo.load(
None, None, None,
js="""
() => {
console.log('Setting up PDF Blob handler...');
window.currentPdfBlobUrl = null; // Store previous blob url globally
function displayPdfBlob(base64Data) {
console.log('displayPdfBlob called - data length:', base64Data ? base64Data.length : 0);
const iframe = document.getElementById('pdf-iframe');
const fallbackDiv = document.getElementById('pdf-fallback');
if (!iframe) {
console.error('PDF iframe not found!');
return;
}
// Revoke previous Blob URL to free memory
if (window.currentPdfBlobUrl) {
console.log('Revoking previous Blob URL:', window.currentPdfBlobUrl);
URL.revokeObjectURL(window.currentPdfBlobUrl);
window.currentPdfBlobUrl = null;
}
if (base64Data && base64Data.length > 100) { // Ensure there's actual content
try {
// Hide fallback message
if (fallbackDiv) fallbackDiv.style.display = 'none';
// Decode Base64
const byteCharacters = atob(base64Data);
console.log('Base64 decoded successfully, length:', byteCharacters.length);
const byteNumbers = new Array(byteCharacters.length);
for (let i = 0; i < byteCharacters.length; i++) {
byteNumbers[i] = byteCharacters.charCodeAt(i);
}
const byteArray = new Uint8Array(byteNumbers);
// Create Blob and URL
const blob = new Blob([byteArray], {type: 'application/pdf'});
window.currentPdfBlobUrl = URL.createObjectURL(blob);
console.log('Created new Blob URL:', window.currentPdfBlobUrl);
// Update iframe source
iframe.src = window.currentPdfBlobUrl;
console.log('Iframe src updated to Blob URL');
} catch (e) {
console.error('Error processing Base64 data or creating Blob URL:', e);
if (fallbackDiv) {
fallbackDiv.innerHTML = '<div style="color:red;">Error loading PDF: ' + e.message + '</div>';
fallbackDiv.style.display = 'flex';
}
iframe.src = 'about:blank'; // Clear iframe on error
}
} else {
console.log('No valid Base64 data provided.');
if (fallbackDiv) {
fallbackDiv.innerHTML = '<div>No PDF loaded yet. Use the "Load PDFs" button.</div>';
fallbackDiv.style.display = 'flex';
}
iframe.src = 'about:blank'; // Clear iframe if no data
}
}
// MutationObserver to watch the hidden Textbox
const targetNode = document.getElementById('pdf_base64_data');
if (targetNode) {
// Find the actual textarea inside the Gradio component structure
const hiddenTextArea = targetNode.querySelector('textarea');
if(hiddenTextArea){
console.log('Found hidden textarea to observe.');
const observerConfig = { characterData: true, childList: true, subtree: true, attributes: true }; // Watch for all changes
const observer = new MutationObserver(function(mutationsList) {
console.log('Mutation detected, checking textarea value');
if (hiddenTextArea.value && hiddenTextArea.value.length > 100) {
console.log('Valid value found in textarea, displaying PDF');
displayPdfBlob(hiddenTextArea.value);
}
});
observer.observe(targetNode, observerConfig);
console.log('MutationObserver attached');
// Try to display any initial value
setTimeout(() => {
if(hiddenTextArea.value && hiddenTextArea.value.length > 100) {
console.log('Initial value found in textarea, displaying PDF');
displayPdfBlob(hiddenTextArea.value);
}
}, 1000);
} else {
console.error('Could not find the textarea within #pdf_base64_data!');
}
} else {
console.error('Hidden data element #pdf_base64_data not found!');
}
// Add keyboard shortcuts like in app.py
document.addEventListener('keydown', function(event) {
if (event.target.tagName === 'INPUT' || event.target.tagName === 'TEXTAREA') {
return; // Ignore inputs
}
let targetButtonId = null;
const key = event.key;
if (key === 'ArrowLeft') targetButtonId = 'prev_button';
else if (key === 'ArrowRight') targetButtonId = 'next_button';
if (targetButtonId) {
const targetButton = document.getElementById(targetButtonId);
if (targetButton) {
event.preventDefault();
targetButton.click();
}
}
});
console.log('Keydown listener added.');
// Additional style for basic font
const additionalStyle = document.createElement('style');
additionalStyle.textContent = `
.extraction-text textarea {
font-family: Arial, Helvetica, sans-serif !important;
font-size: 14px !important;
}
`;
document.head.appendChild(additionalStyle);
}
"""
)
return demo
if __name__ == "__main__":
demo = create_interface()
demo.launch() |