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mzameshina
commited on
Update app.py
Browse files
app.py
CHANGED
@@ -686,40 +686,24 @@ with demo:
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########################## FHE processing Part ##########################
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gr.Markdown("<hr />")
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gr.Markdown("## Step 3: De-identify the
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gr.Markdown(
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"""Once the client encrypts the
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server to perform the de-identification on encrypted data. When the computation is done, the
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server will return the result to the client for decryption."""
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)
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run_fhe_btn = gr.Button("De-identify using FHE")
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with gr.Row():
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with gr.Column(scale=5):
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anonymized_doc_output = gr.Textbox(
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label="Decrypted and de-idenntified document", lines=10, interactive=True
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)
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with gr.Column(scale=5):
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anonymized_query_output = gr.Textbox(
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label="Decrypted and de-identified prompt", lines=10, interactive=True
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)
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identified_words_output_df = gr.Dataframe(label="Identified words:", visible=False)
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encrypt_doc_btn.click(
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fn=encrypt_doc_fn,
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inputs=[original_sentences_box],
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outputs=[encrypted_doc_box, anonymized_doc_output],
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)
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encrypt_query_btn.click(
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fn=encrypt_query_fn,
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inputs=[query_box],
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@@ -733,10 +717,9 @@ with demo:
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run_fhe_btn.click(
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anonymization_with_fn,
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inputs=[
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outputs=[
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)
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########################## Presidio ##########################
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gr.Markdown("<hr />")
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)
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########################## FHE processing Part ##########################
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gr.Markdown("<hr />")
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gr.Markdown("## Step 3: De-identify the prompt using FHE")
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gr.Markdown(
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"""Once the client encrypts the prompt locally, it will be sent to a remote
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server to perform the de-identification on encrypted data. When the computation is done, the
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server will return the result to the client for decryption."""
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)
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run_fhe_btn = gr.Button("De-identify using FHE")
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with gr.Row():
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with gr.Column(scale=5):
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anonymized_query_output = gr.Textbox(
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label="Decrypted and de-identified prompt", lines=10, interactive=True
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)
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identified_words_output_df = gr.Dataframe(label="Identified words:", visible=False)
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encrypt_query_btn.click(
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fn=encrypt_query_fn,
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inputs=[query_box],
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run_fhe_btn.click(
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anonymization_with_fn,
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inputs=[query_box],
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outputs=[anonymized_query_output, identified_words_output_df],
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)
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########################## Presidio ##########################
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gr.Markdown("<hr />")
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