Update app.py
Browse files
app.py
CHANGED
@@ -814,7 +814,7 @@ def analyze_text(text: str, mode: str, classifier: TextClassifier) -> tuple:
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# Modified Gradio interface setup function to include file upload
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def setup_gradio_interface(classifier):
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"""
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Set up Gradio interface with
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Args:
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classifier: The TextClassifier instance
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@@ -830,71 +830,78 @@ def setup_gradio_interface(classifier):
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def handle_file_upload_wrapper(file_obj, mode):
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if file_obj is None:
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return (
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"No file uploaded",
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"Please upload a file to analyze",
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"No file uploaded for analysis"
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)
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return handle_file_upload_and_analyze(file_obj, mode, classifier)
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with gr.Blocks(title="AI Text Detector") as demo:
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gr.Markdown("# AI Text Detector")
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gr.Markdown("Analyze text to detect if it was written by a human or AI. You can paste text directly or upload an image, PDF, or Word document.")
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# Text input
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text_input = gr.Textbox(
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lines=8,
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placeholder="Enter text to analyze...",
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label="Input Text"
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)
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with gr.Row():
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# Left
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with gr.Column(
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label="
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info="Quick mode for faster analysis, Detailed mode for sentence-level analysis"
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)
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# Right
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with gr.Column(
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# Action buttons row
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with gr.Row():
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text_submit_button = gr.Button("Analyze Text", variant="primary")
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upload_submit_button = gr.Button("Process Uploaded File", variant="primary")
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# Output areas
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output_html = gr.HTML(label="Highlighted Analysis")
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output_sentences = gr.Textbox(label="Sentence-by-Sentence Analysis", lines=10)
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output_result = gr.Textbox(label="Overall Result", lines=4)
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# Connect buttons to functions
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text_submit_button.click(
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analyze_text_wrapper,
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inputs=[text_input, mode_selection],
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outputs=[output_html, output_sentences, output_result]
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)
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handle_file_upload_wrapper,
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inputs=[file_upload, mode_selection],
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outputs=[output_html, output_sentences, output_result]
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)
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# Add file upload
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gr.Markdown("""
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-
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- Maximum file size: 1MB
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- PDF files: Maximum 3 pages (OCR.space API limitation)
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- Supported formats: Images (PNG, JPG, GIF), PDF, Word documents (DOCX, DOC)
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""")
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return demo
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# Modified Gradio interface setup function to include file upload
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def setup_gradio_interface(classifier):
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"""
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Set up Gradio interface with original layout plus a small file upload button
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Args:
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classifier: The TextClassifier instance
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def handle_file_upload_wrapper(file_obj, mode):
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if file_obj is None:
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return analyze_text_wrapper("", mode) # Return empty analysis
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return handle_file_upload_and_analyze(file_obj, mode, classifier)
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# Create layout with side-by-side content
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with gr.Blocks(title="AI Text Detector") as demo:
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gr.Markdown("# AI Text Detector")
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with gr.Row():
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# Left column - Input
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with gr.Column():
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text_input = gr.Textbox(
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lines=8,
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placeholder="Enter text to analyze...",
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label="Input Text"
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)
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with gr.Row():
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# Analysis mode selection
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mode_selection = gr.Radio(
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choices=["quick", "detailed"],
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value="quick",
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label="Analysis Mode",
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info="Quick mode for faster analysis, Detailed mode for sentence-level analysis"
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)
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# Small file upload button (similar to paperclip in Claude)
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file_upload = gr.File(
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label="",
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file_types=["image", "pdf", "doc", "docx"],
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type="binary",
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elem_id="file_upload_small"
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)
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# Original analyze button
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analyze_button = gr.Button("Analyze Text")
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# Right column - Results (same as original)
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with gr.Column():
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output_html = gr.HTML(label="Highlighted Analysis")
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output_sentences = gr.Textbox(label="Sentence-by-Sentence Analysis", lines=10)
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output_result = gr.Textbox(label="Overall Result", lines=4)
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# Connect original analyze button
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analyze_button.click(
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analyze_text_wrapper,
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inputs=[text_input, mode_selection],
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outputs=[output_html, output_sentences, output_result]
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)
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# Connect file upload changes to automatically process
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file_upload.change(
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handle_file_upload_wrapper,
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inputs=[file_upload, mode_selection],
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outputs=[output_html, output_sentences, output_result]
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)
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# Add CSS to make file upload button small and icon-like
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gr.HTML("""
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<style>
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#file_upload_small {
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max-width: 50px;
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margin-top: 25px;
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}
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#file_upload_small .label-wrap {
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display: none;
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}
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</style>
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""")
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# Small text about file upload (at bottom)
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gr.Markdown("""
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*You can also upload an image, PDF, or Word document (max 1MB) for OCR text extraction and analysis.*
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""")
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return demo
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