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import os
import gradio as gr
import pandas as pd
from tools.config import (
AWS_LLM_PII_OPTION,
AWS_PII_OPTION,
CHOSEN_COMPREHEND_ENTITIES,
CHOSEN_LLM_ENTITIES,
CHOSEN_REDACT_ENTITIES,
DEFAULT_PII_DETECTION_MODEL,
INFERENCE_SERVER_PII_OPTION,
LOCAL_OCR_MODEL_TEXT_EXTRACT_OPTION,
LOCAL_PII_OPTION,
LOCAL_TRANSFORMERS_LLM_PII_OPTION,
NO_REDACTION_PII_OPTION,
SHOW_AWS_TEXT_EXTRACTION_OPTIONS,
SHOW_INFERENCE_SERVER_VLM_MODEL_OPTIONS,
SHOW_OCR_GUI_OPTIONS,
SHOW_PII_IDENTIFICATION_OPTIONS,
TEXTRACT_TEXT_EXTRACT_OPTION,
)
from tools.helper_functions import put_columns_in_df
def is_data_file_type_walkthrough(files):
"""Check if files are data file types (xlsx, xls, csv, parquet, docx)."""
if not files:
return False
data_file_extensions = {".xlsx", ".xls", ".csv", ".parquet", ".docx"}
for file in files:
if file:
file_path = file.name if hasattr(file, "name") else str(file)
file_ext = os.path.splitext(file_path)[1].lower()
if file_ext in data_file_extensions:
return True
return False
def route_walkthrough_files(files):
"""Route files from walkthrough to appropriate component and determine if data file.
Also returns visibility updates for step 2 text extraction components: when the
upload is CSV/Excel (data file), those are hidden; when it is a document, they
follow SHOW_OCR_GUI_OPTIONS (radio) and accordions are left unchanged.
"""
if not files:
show_text_extract = SHOW_OCR_GUI_OPTIONS
return (
None,
None,
False,
gr.Walkthrough(selected=2),
gr.update(visible=show_text_extract),
gr.update(),
gr.update(),
)
is_data = is_data_file_type_walkthrough(files)
doc_files = []
data_files = []
data_file_extensions = {".xlsx", ".xls", ".csv", ".parquet", ".docx"}
for file in files:
if file:
file_path = file.name if hasattr(file, "name") else str(file)
file_ext = os.path.splitext(file_path)[1].lower()
if file_ext in data_file_extensions:
data_files.append(file)
else:
doc_files.append(file)
# Hide text extraction options on step 2 when CSV/Excel (data file) was uploaded
show_text_extract = (not is_data) and SHOW_OCR_GUI_OPTIONS
if is_data:
text_extract_updates = (
gr.update(visible=False),
gr.update(visible=False),
gr.update(visible=False),
)
else:
# Document: show radio if enabled; leave accordions unchanged (they follow radio selection)
text_extract_updates = (
gr.update(visible=show_text_extract),
gr.update(),
gr.update(),
)
if is_data:
return None, data_files, True, gr.Walkthrough(selected=2), *text_extract_updates
else:
return doc_files, None, False, gr.Walkthrough(selected=2), *text_extract_updates
def handle_step_2_next(
files,
is_data_file,
walkthrough_colnames_val,
walkthrough_excel_sheets_val,
text_extract_method_val,
):
"""Handle step 2 next button - populate dropdowns if data files and sync with main components."""
# Show text extraction method radio in Step 2 if SHOW_OCR_GUI_OPTIONS is True
show_text_extract_method = SHOW_OCR_GUI_OPTIONS
if is_data_file and files:
# Use put_columns_in_df to populate dropdowns
colnames_dropdown, excel_sheets_dropdown = put_columns_in_df(files)
# Use the selected values from walkthrough if available, otherwise use the populated values
if (
walkthrough_colnames_val
and len(walkthrough_colnames_val) > 0
and walkthrough_colnames_val[0] != "Choose columns to anonymise"
):
main_colnames_update = gr.Dropdown(value=walkthrough_colnames_val)
else:
main_colnames_update = colnames_dropdown
if (
walkthrough_excel_sheets_val
and len(walkthrough_excel_sheets_val) > 0
and walkthrough_excel_sheets_val[0] != "Choose Excel sheets to anonymise"
):
main_excel_sheets_update = gr.Dropdown(
value=walkthrough_excel_sheets_val, visible=True
)
else:
main_excel_sheets_update = excel_sheets_dropdown
# Preserve user's column selection in walkthrough_colnames; do not overwrite with colnames_dropdown
# (colnames_dropdown has value=all columns, which would reset a one-column selection to all four)
if (
walkthrough_colnames_val
and len(walkthrough_colnames_val) > 0
and walkthrough_colnames_val[0] != "Choose columns to anonymise"
):
walkthrough_colnames_update = gr.update(
value=walkthrough_colnames_val, visible=True
)
else:
walkthrough_colnames_update = colnames_dropdown
# Preserve user's sheet selection in walkthrough_excel_sheets when they have made one
if (
walkthrough_excel_sheets_val
and len(walkthrough_excel_sheets_val) > 0
and walkthrough_excel_sheets_val[0] != "Choose Excel sheets to anonymise"
):
walkthrough_excel_sheets_update = gr.update(
value=walkthrough_excel_sheets_val, visible=True
)
else:
walkthrough_excel_sheets_update = excel_sheets_dropdown
# Return updates for both walkthrough and main components, and advance walkthrough
# Note: walkthrough_local_ocr_method_radio and walkthrough_handwrite_signature_checkbox visibility
# are controlled by event handler on walkthrough_text_extract_method_radio
# Note: Step 3 PII components visibility is controlled by event handler on walkthrough_redaction_method_dropdown
return (
walkthrough_colnames_update, # walkthrough_colnames
walkthrough_excel_sheets_update, # walkthrough_excel_sheets
main_colnames_update, # in_colnames
main_excel_sheets_update, # in_excel_sheets (defined in "Word or Excel/CSV files" tab)
gr.Radio(
visible=show_text_extract_method
), # walkthrough_text_extract_method_radio
gr.Walkthrough(selected=3), # walkthrough
)
else:
# Return unchanged dropdowns and advance
# Note: walkthrough_local_ocr_method_radio and walkthrough_handwrite_signature_checkbox visibility
# are controlled by event handler on walkthrough_text_extract_method_radio
# Note: Step 3 PII components visibility is controlled by event handler on walkthrough_redaction_method_dropdown
return (
gr.Dropdown(visible=False), # walkthrough_colnames
gr.Dropdown(visible=False), # walkthrough_excel_sheets
gr.Dropdown(), # in_colnames (no change)
gr.Dropdown(visible=False), # in_excel_sheets (no change)
gr.Radio(
visible=show_text_extract_method
), # walkthrough_text_extract_method_radio
gr.Walkthrough(selected=3), # walkthrough
)
def _data_files_fingerprint(files):
"""Return a stable key for the current file list to detect redundant updates."""
if not files:
return ()
return tuple(getattr(f, "name", str(f)) for f in files if f is not None)
def update_step_2_on_data_file_upload(files, is_data_file, last_processed_keys=None):
"""Update Step 2 components when data files are uploaded.
When last_processed_keys is provided (from gr.State), returns (colnames, sheets, new_keys)
and skips recomputation if files are unchanged to avoid Gradio re-firing change and
causing an infinite loading loop on the column dropdown.
"""
keys = _data_files_fingerprint(files)
if last_processed_keys is not None and keys == last_processed_keys:
return gr.update(), gr.update(), last_processed_keys
if is_data_file and files:
colnames_dropdown, excel_sheets_dropdown = put_columns_in_df(files)
if last_processed_keys is not None:
return colnames_dropdown, excel_sheets_dropdown, keys
return colnames_dropdown, excel_sheets_dropdown, keys
else:
no_op = gr.Dropdown(visible=False), gr.Dropdown(visible=False), keys
if last_processed_keys is not None:
return *no_op, () if not keys else keys
return no_op
def handle_text_extract_method_selection(text_extract_method: str):
"""Handle text extraction method selection - show local OCR radio only if Local OCR model is selected,
and show AWS Textract settings only if AWS Textract is selected.
Args:
text_extract_method: Selected text extraction method
Returns:
Tuple of visibility updates for local OCR radio, and AWS Textract accordion
"""
# Normalize (Gradio can send None when .change() fires before sync); default so something stays visible
if isinstance(text_extract_method, str):
text_extract_method = text_extract_method.strip()
if text_extract_method is None or text_extract_method == "":
text_extract_method = LOCAL_OCR_MODEL_TEXT_EXTRACT_OPTION
# Show local OCR method radio only if "Local OCR model - PDFs without selectable text" is selected
# When "AWS Bedrock VLM OCR" is selected, the local OCR method is automatically set to "bedrock-vlm" but the component is hidden
show_local_ocr = text_extract_method == LOCAL_OCR_MODEL_TEXT_EXTRACT_OPTION
# Show AWS Textract settings accordion only if "AWS Textract service - all PDF types" is selected
show_aws_textract = (
text_extract_method == TEXTRACT_TEXT_EXTRACT_OPTION
and SHOW_AWS_TEXT_EXTRACTION_OPTIONS
)
return (
gr.update(visible=show_local_ocr), # walkthrough_local_ocr_method_radio
gr.update(
visible=show_aws_textract
), # walkthrough_handwrite_signature_checkbox
)
def _is_llm_pii_method_shown_for_redaction(redaction_method, pii_method):
"""Whether LLM PII controls (entity dropdown + custom instructions accordion) should be visible.
Mirrors the logic in handle_redaction_method_selection for is_llm_method_init.
"""
if isinstance(redaction_method, str):
redaction_method = redaction_method.strip()
if redaction_method is None or redaction_method == "":
redaction_method = "Redact all PII"
if isinstance(pii_method, str):
pii_method = pii_method.strip()
if pii_method is None or pii_method == "":
pii_method = DEFAULT_PII_DETECTION_MODEL
is_redact_all_pii = redaction_method == "Redact all PII"
is_redact_selected_terms = redaction_method == "Redact selected terms"
is_redact_all_pii_or_selected_terms = is_redact_all_pii or is_redact_selected_terms
show_pii_method = (
is_redact_all_pii_or_selected_terms
) and SHOW_PII_IDENTIFICATION_OPTIONS
pii_method_for_visibility = pii_method
if is_redact_all_pii_or_selected_terms and pii_method == NO_REDACTION_PII_OPTION:
pii_method_for_visibility = DEFAULT_PII_DETECTION_MODEL
return show_pii_method and (
pii_method_for_visibility == LOCAL_TRANSFORMERS_LLM_PII_OPTION
or pii_method_for_visibility == INFERENCE_SERVER_PII_OPTION
or pii_method_for_visibility == AWS_LLM_PII_OPTION
)
def handle_redaction_method_selection(redaction_method: str, pii_method: str):
"""Handle redaction method selection in Step 3 - show appropriate components based on selection."""
# Normalize inputs (Gradio can send whitespace or None when .change() fires before sync)
if isinstance(redaction_method, str):
redaction_method = redaction_method.strip()
if redaction_method is None or redaction_method == "":
redaction_method = "Redact all PII"
if isinstance(pii_method, str):
pii_method = pii_method.strip()
if pii_method is None or pii_method == "":
pii_method = DEFAULT_PII_DETECTION_MODEL
# Check which redaction method is selected
is_redact_all_pii = redaction_method == "Redact all PII"
is_redact_selected_terms = redaction_method == "Redact selected terms"
is_redact_all_pii_or_selected_terms = is_redact_all_pii or is_redact_selected_terms
is_extract_text_only = (
isinstance(redaction_method, str)
and redaction_method.strip() == "Extract text only"
)
# When switching from "Extract text only", the PII dropdown may still be
# NO_REDACTION_PII_OPTION; use DEFAULT_PII_DETECTION_MODEL so exactly one
# entity dropdown is visible and the UI doesn’t show all three or none.
pii_method_for_visibility = pii_method
if is_redact_all_pii_or_selected_terms and pii_method == NO_REDACTION_PII_OPTION:
pii_method_for_visibility = DEFAULT_PII_DETECTION_MODEL
# Show PII detection settings if "Redact all PII" OR "Redact selected terms" is selected
# Both options need PII detection method to determine what to redact
show_pii_method = (
is_redact_all_pii_or_selected_terms
) and SHOW_PII_IDENTIFICATION_OPTIONS
# Determine visibility of entity dropdowns based on PII method
show_local_entities_init = show_pii_method and (
pii_method_for_visibility == LOCAL_PII_OPTION
)
show_comprehend_entities_init = show_pii_method and (
pii_method_for_visibility == AWS_PII_OPTION
)
is_llm_method_init = _is_llm_pii_method_shown_for_redaction(
redaction_method, pii_method
)
# For "Extract text only", hide all components
# For "Redact all PII", show PII detection components
# For "Redact selected terms", show both PII detection components AND deny/allow/fully redacted list components
# When we overrode pii_method for visibility, also update the PII dropdown value
pii_drop_value = None
if is_redact_all_pii_or_selected_terms and pii_method == NO_REDACTION_PII_OPTION:
pii_drop_value = DEFAULT_PII_DETECTION_MODEL
# Set entity values based on redaction method
if is_redact_selected_terms:
# For "Redact selected terms", only show CUSTOM entity
local_entities_update = gr.Dropdown(
visible=show_local_entities_init, value=["CUSTOM"]
)
comprehend_entities_update = gr.Dropdown(
visible=show_comprehend_entities_init, value=["CUSTOM"]
)
llm_entities_update = gr.Dropdown(visible=is_llm_method_init, value=["CUSTOM"])
walkthrough_pii_identification_method_drop_update = (
gr.update(visible=show_pii_method, value=pii_drop_value)
if pii_drop_value is not None
else gr.update(visible=show_pii_method)
)
elif is_redact_all_pii:
# For "Redact all PII", use default entities
# Ensure entities are lists (they should already be parsed in config.py)
local_entities_val = (
CHOSEN_REDACT_ENTITIES
if isinstance(CHOSEN_REDACT_ENTITIES, list)
else ["CUSTOM"]
)
comprehend_entities_val = (
CHOSEN_COMPREHEND_ENTITIES
if isinstance(CHOSEN_COMPREHEND_ENTITIES, list)
else ["CUSTOM"]
)
llm_entities_val = (
CHOSEN_LLM_ENTITIES if isinstance(CHOSEN_LLM_ENTITIES, list) else ["CUSTOM"]
)
local_entities_update = gr.Dropdown(
visible=show_local_entities_init, value=local_entities_val
)
comprehend_entities_update = gr.Dropdown(
visible=show_comprehend_entities_init, value=comprehend_entities_val
)
llm_entities_update = gr.Dropdown(
visible=is_llm_method_init, value=llm_entities_val
)
walkthrough_pii_identification_method_drop_update = (
gr.update(visible=show_pii_method, value=pii_drop_value)
if pii_drop_value is not None
else gr.update(visible=show_pii_method)
)
elif is_extract_text_only:
# For "Extract text only", just update visibility without changing value
local_entities_update = gr.Dropdown(visible=show_local_entities_init)
comprehend_entities_update = gr.Dropdown(visible=show_comprehend_entities_init)
llm_entities_update = gr.Dropdown(visible=is_llm_method_init)
walkthrough_pii_identification_method_drop_update = gr.update(
visible=show_pii_method, value=NO_REDACTION_PII_OPTION
)
return (
walkthrough_pii_identification_method_drop_update, # walkthrough_pii_identification_method_drop
local_entities_update, # walkthrough_in_redact_entities
comprehend_entities_update, # walkthrough_in_redact_comprehend_entities
gr.update(visible=is_llm_method_init), # walkthrough_llm_entities_accordion
llm_entities_update, # walkthrough_in_redact_llm_entities
gr.update(
visible=is_redact_all_pii_or_selected_terms
), # walkthrough_list_accordion
gr.update(
visible=is_redact_all_pii_or_selected_terms
), # walkthrough_max_fuzzy_spelling_mistakes_num
)
# Update visibility of PII-related components and accordions when general redaction method is selected
def handle_main_redaction_method_selection(redaction_method, pii_method):
"""Wrapper that applies handle_redaction_method_selection and updates accordion visibility.
handle_redaction_method_selection returns (for walkthrough): pii_drop, local_entities,
comprehend_entities, llm_accordion_visible, llm_entities, list_accordion, checkbox, num.
The main app expects: pii_drop, local_entities, comprehend_entities, llm_entities,
custom_llm_entities_accordion, list_accordion, checkbox, num, entity_accordion, terms_accordion.
So we remap: use inner[4] for in_redact_llm_entities and set custom_llm_entities_accordion
visibility (same rule as handle_main_pii_method_selection; inner gr.update() would hide the box).
"""
raw = list(handle_redaction_method_selection(redaction_method, pii_method))
is_redact_all_pii = redaction_method == "Redact all PII"
is_redact_selected_terms = redaction_method == "Redact selected terms"
is_extract_text_only = (
isinstance(redaction_method, str)
and redaction_method.strip() == "Extract text only"
)
show_pii_method = (
is_redact_all_pii or is_redact_selected_terms
) and SHOW_PII_IDENTIFICATION_OPTIONS
show_selected_terms_lists = is_redact_selected_terms
is_llm_method_for_custom_instructions = _is_llm_pii_method_shown_for_redaction(
redaction_method, pii_method
)
# Map to main app outputs: pii_drop, local_entities, comprehend_entities, llm_entities,
# custom_llm_entities_accordion, list_accordion, checkbox, num,
# then entity/terms accordions, then only_extract_text_radio.
# raw[3] is walkthrough llm accordion visibility (unused here); raw[4] is llm_entities.
# When "Extract text only" is selected, force "Only extract text (no redaction)" checkbox to True.
results = [
raw[0], # pii_identification_method_drop
raw[1], # in_redact_entities
raw[2], # in_redact_comprehend_entities
raw[
4
], # in_redact_llm_entities (was wrongly going to textbox as str(["CUSTOM"]) -> "['CUSTOM']")
gr.update(
visible=is_llm_method_for_custom_instructions
), # custom_llm_entities_accordion
raw[5], # walkthrough_list_accordion
raw[6], # max_fuzzy_spelling_mistakes_num
gr.update(visible=show_pii_method), # entity_types_to_redact_accordion
gr.update(visible=show_selected_terms_lists), # terms_accordion
gr.update(value=is_extract_text_only), # only_extract_text_radio
]
return results
def handle_pii_method_selection(pii_method: str):
"""Handle PII method selection - show appropriate entity dropdowns."""
# When value is None/empty (e.g. first .change() after loading an example sets the
# component programmatically), avoid hiding all entity selectors by defaulting to Local.
if pii_method is None or (isinstance(pii_method, str) and not pii_method.strip()):
show_local_entities = True
show_comprehend_entities = False
is_llm_method = False
else:
# Check if method is Local
show_local_entities = pii_method == LOCAL_PII_OPTION
# Check if method is AWS Comprehend
show_comprehend_entities = pii_method == AWS_PII_OPTION
# Check if method is an LLM option
is_llm_method = (
pii_method == LOCAL_TRANSFORMERS_LLM_PII_OPTION
or pii_method == INFERENCE_SERVER_PII_OPTION
or pii_method == AWS_LLM_PII_OPTION
)
# Use gr.update(visible=...) only to avoid value resets that can trigger change
# events on the target components and cause loading loops (e.g. tabular PII -> LLM).
# Only return to the two entity dropdowns and the accordion; components inside the
# accordion (walkthrough_in_redact_llm_entities, walkthrough_custom_llm_instructions_textbox)
# are shown/hidden by the accordion visibility.
return (
gr.update(visible=show_local_entities), # walkthrough_in_redact_entities
gr.update(
visible=show_comprehend_entities
), # walkthrough_in_redact_comprehend_entities
gr.update(visible=is_llm_method), # walkthrough_llm_entities_accordion
)
def handle_pii_method_selection_tabular(pii_method: str):
"""Handle tabular PII method selection. Updates only accordion visibility for the
LLM block; leaves walkthrough_in_redact_llm_entities and
walkthrough_custom_llm_instructions_textbox as no-ops to avoid loading spinners
hanging on those nested components when switching to LLM (AWS Bedrock).
"""
if pii_method is None or (isinstance(pii_method, str) and not pii_method.strip()):
show_local_entities = True
show_comprehend_entities = False
is_llm_method = False
else:
show_local_entities = pii_method == LOCAL_PII_OPTION
show_comprehend_entities = pii_method == AWS_PII_OPTION
is_llm_method = (
pii_method == LOCAL_TRANSFORMERS_LLM_PII_OPTION
or pii_method == INFERENCE_SERVER_PII_OPTION
or pii_method == AWS_LLM_PII_OPTION
)
return (
gr.update(visible=show_local_entities),
gr.update(visible=show_comprehend_entities),
gr.update(visible=is_llm_method), # accordion controls visibility of LLM block
)
def handle_step_3_next(
text_extract_method_val,
local_ocr_method_val,
handwrite_signature_val,
pii_method_val,
redact_entities_val,
redact_comprehend_entities_val,
redact_llm_entities_val,
custom_llm_instructions_val,
deny_list_val,
allow_list_val,
fully_redacted_list_val,
pii_method_tabular_val,
anon_strategy_val,
do_initial_clean_val,
redact_duplicate_pages_val,
max_fuzzy_spelling_mistakes_num_val,
):
"""Handle step 3 next button - write values to main components."""
# Update text extraction method with walkthrough value
text_extract_method_update = (
gr.Radio(value=text_extract_method_val)
if text_extract_method_val
else gr.Radio()
)
# Update OCR components with walkthrough values
local_ocr_update = (
gr.Radio(value=local_ocr_method_val) if local_ocr_method_val else gr.Radio()
)
handwrite_signature_update = (
gr.CheckboxGroup(value=handwrite_signature_val)
if handwrite_signature_val
else gr.CheckboxGroup()
)
# Update PII components with walkthrough values
pii_method_update = gr.Radio(value=pii_method_val) if pii_method_val else gr.Radio()
# Always update dropdowns with the value, even if it's an empty list
# This ensures that empty selections are correctly written to main components
redact_entities_update = (
gr.Dropdown(value=redact_entities_val)
if redact_entities_val is not None
else gr.Dropdown()
)
redact_comprehend_entities_update = (
gr.Dropdown(value=redact_comprehend_entities_val)
if redact_comprehend_entities_val is not None
else gr.Dropdown()
)
redact_llm_entities_update = (
gr.Dropdown(value=redact_llm_entities_val)
if redact_llm_entities_val is not None
else gr.Dropdown()
)
custom_llm_instructions_update = (
gr.Textbox(value=custom_llm_instructions_val)
if custom_llm_instructions_val is not None
else gr.Textbox()
)
# Update deny/allow/fully redacted list components with walkthrough values
# Convert DataFrame to list if needed (for backward compatibility)
# Ensure all items are strings for Dropdown components
if deny_list_val is not None:
if isinstance(deny_list_val, pd.DataFrame):
deny_list_val = (
deny_list_val.iloc[:, 0].tolist() if not deny_list_val.empty else []
)
# Ensure all items are strings
if isinstance(deny_list_val, list):
deny_list_val = (
[str(item) for item in deny_list_val if item] if deny_list_val else []
)
deny_list_update = (
gr.Dropdown(value=deny_list_val) if deny_list_val else gr.Dropdown()
)
else:
deny_list_update = gr.Dropdown()
if allow_list_val is not None:
if isinstance(allow_list_val, pd.DataFrame):
allow_list_val = (
allow_list_val.iloc[:, 0].tolist() if not allow_list_val.empty else []
)
# Ensure all items are strings
if isinstance(allow_list_val, list):
allow_list_val = (
[str(item) for item in allow_list_val if item] if allow_list_val else []
)
allow_list_update = (
gr.Dropdown(value=allow_list_val) if allow_list_val else gr.Dropdown()
)
else:
allow_list_update = gr.Dropdown()
if fully_redacted_list_val is not None:
if isinstance(fully_redacted_list_val, pd.DataFrame):
fully_redacted_list_val = (
fully_redacted_list_val.iloc[:, 0].tolist()
if not fully_redacted_list_val.empty
else []
)
# Ensure all items are strings
if isinstance(fully_redacted_list_val, list):
fully_redacted_list_val = (
[str(item) for item in fully_redacted_list_val if item]
if fully_redacted_list_val
else []
)
fully_redacted_list_update = (
gr.Dropdown(value=fully_redacted_list_val)
if fully_redacted_list_val
else gr.Dropdown()
)
else:
fully_redacted_list_update = gr.Dropdown()
# Update tabular data components with walkthrough values
pii_method_tabular_update = (
gr.Radio(value=pii_method_tabular_val)
if pii_method_tabular_val is not None
else gr.Radio()
)
anon_strategy_update = (
gr.Radio(value=anon_strategy_val)
if anon_strategy_val is not None
else gr.Radio()
)
do_initial_clean_update = (
gr.Checkbox(value=do_initial_clean_val)
if do_initial_clean_val is not None
else gr.Checkbox()
)
# Update redact duplicate pages checkbox with walkthrough value
redact_duplicate_pages_update = (
gr.Checkbox(value=redact_duplicate_pages_val)
if redact_duplicate_pages_val is not None
else gr.Checkbox()
)
# Update max fuzzy spelling mistakes number with walkthrough value
max_fuzzy_spelling_mistakes_num_update = (
gr.Number(value=max_fuzzy_spelling_mistakes_num_val)
if max_fuzzy_spelling_mistakes_num_val is not None
else gr.Number()
)
return (
text_extract_method_update, # text_extract_method_radio
local_ocr_update, # local_ocr_method_radio
handwrite_signature_update, # handwrite_signature_checkbox
pii_method_update, # pii_identification_method_drop
redact_entities_update, # in_redact_entities
redact_comprehend_entities_update, # in_redact_comprehend_entities
redact_llm_entities_update, # in_redact_llm_entities
custom_llm_instructions_update, # custom_llm_instructions_textbox
deny_list_update, # in_deny_list_state
allow_list_update, # in_allow_list_state
fully_redacted_list_update, # in_fully_redacted_list_state
pii_method_tabular_update, # pii_identification_method_drop_tabular
anon_strategy_update, # anon_strategy
do_initial_clean_update, # do_initial_clean
redact_duplicate_pages_update, # redact_duplicate_pages_checkbox
gr.Walkthrough(selected=4), # walkthrough
max_fuzzy_spelling_mistakes_num_update, # max_fuzzy_spelling_mistakes_num
)
def handle_step_4_next(
page_min_val,
page_max_val,
textract_output_found_val,
relevant_ocr_output_with_words_found_val,
total_pdf_page_count_val,
estimated_aws_costs_val,
estimated_time_taken_val,
cost_code_dataframe_val,
cost_code_choice_val,
):
"""Handle step 4 next button - write values to main components."""
# Update page selection components
page_min_update = (
gr.Number(value=page_min_val) if page_min_val is not None else gr.Number()
)
page_max_update = (
gr.Number(value=page_max_val) if page_max_val is not None else gr.Number()
)
# Update cost-related components (if SHOW_COSTS is True)
textract_output_found_update = (
gr.Checkbox(value=textract_output_found_val)
if textract_output_found_val is not None
else gr.Checkbox()
)
relevant_ocr_output_with_words_found_update = (
gr.Checkbox(value=relevant_ocr_output_with_words_found_val)
if relevant_ocr_output_with_words_found_val is not None
else gr.Checkbox()
)
total_pdf_page_count_update = (
gr.Number(value=total_pdf_page_count_val)
if total_pdf_page_count_val is not None
else gr.Number()
)
estimated_aws_costs_update = (
gr.Number(value=estimated_aws_costs_val)
if estimated_aws_costs_val is not None
else gr.Number()
)
estimated_time_taken_update = (
gr.Number(value=estimated_time_taken_val)
if estimated_time_taken_val is not None
else gr.Number()
)
# Update cost code components (if GET_COST_CODES or ENFORCE_COST_CODES is True)
cost_code_dataframe_update = (
gr.Dataframe(value=cost_code_dataframe_val)
if cost_code_dataframe_val is not None
else gr.Dataframe()
)
cost_code_choice_update = (
gr.Dropdown(value=cost_code_choice_val)
if cost_code_choice_val is not None
else gr.Dropdown()
)
return (
page_min_update, # page_min
page_max_update, # page_max
textract_output_found_update, # textract_output_found_checkbox
relevant_ocr_output_with_words_found_update, # relevant_ocr_output_with_words_found_checkbox
total_pdf_page_count_update, # total_pdf_page_count
estimated_aws_costs_update, # estimated_aws_costs_number
estimated_time_taken_update, # estimated_time_taken_number
cost_code_dataframe_update, # cost_code_dataframe
cost_code_choice_update, # cost_code_choice_drop
gr.Walkthrough(selected=5), # walkthrough
)
def sync_walkthrough_outputs_to_original(summary_text, output_file_value):
"""Sync walkthrough output components to original components.
This function takes the outputs from the redaction process and duplicates
them to both walkthrough and original output components.
Args:
summary_text: The output summary text
output_file_value: The output file value
Returns:
Tuple of (walkthrough_summary, walkthrough_file, original_summary, original_file)
"""
return (
summary_text, # walkthrough_redaction_output_summary_textbox
output_file_value, # walkthrough_output_file
summary_text, # redaction_output_summary_textbox (original)
output_file_value, # output_file (original)
)
def sync_walkthrough_tabular_outputs_to_original(summary_text, output_file_value):
"""Sync walkthrough tabular output components to original components.
This function takes the outputs from the tabular redaction process and duplicates
them to both walkthrough and original output components.
Args:
summary_text: The output summary text
output_file_value: The output file value
Returns:
Tuple of (walkthrough_summary, walkthrough_file, original_summary, original_file)
"""
return (
summary_text, # walkthrough_text_output_summary
output_file_value, # walkthrough_text_output_file
summary_text, # text_output_summary (original)
output_file_value, # text_output_file (original)
)
def update_step_3_tabular_visibility(is_data_file):
"""Update visibility of Step 3 components based on file type.
When a data file (CSV/Excel) is chosen: show tabular options, hide document-only options.
When a document is chosen: show document options (PII method, duplicate pages, etc.), hide tabular options.
Args:
is_data_file: Boolean indicating if uploaded file is a data file
Returns:
Tuple of visibility updates for document-only and tabular components
"""
show_doc = not is_data_file
return (
gr.update(visible=show_doc), # walkthrough_local_ocr_method_radio
gr.update(visible=show_doc), # walkthrough_pii_identification_method_drop
gr.update(visible=show_doc), # walkthrough_fully_redacted_list_state
gr.update(visible=show_doc), # walkthrough_redact_duplicate_pages_checkbox
gr.update(
visible=is_data_file
), # walkthrough_pii_identification_method_drop_tabular
gr.update(visible=is_data_file), # walkthrough_anon_strategy
gr.update(visible=is_data_file), # walkthrough_do_initial_clean
)
def update_step_4_visibility(is_data_file):
"""Update visibility of Step 4 components based on file type.
Args:
is_data_file: Boolean indicating if uploaded file is a data file
Returns:
Tuple of visibility updates for document and tabular components
"""
# For Row components, we need to update visibility of children
# Return updates for button and both output components in each row
return (
gr.update(visible=not is_data_file), # step_4_next_document_redact_btn
gr.update(visible=is_data_file), # step_4_next_tabular_redact_btn
)
def handle_main_text_extract_method_selection(text_extract_method: str):
"""Handle text extraction method selection for main components - show local OCR options only if Local OCR model is selected,
and show AWS Textract settings only if AWS Textract is selected.
Args:
text_extract_method: Selected text extraction method
Returns:
Tuple of visibility updates for local OCR accordion, inference server accordion, and AWS Textract accordion
"""
# Normalize (Gradio can send None when .change() fires before sync); default so something stays visible
if isinstance(text_extract_method, str):
text_extract_method = text_extract_method.strip()
if text_extract_method is None or text_extract_method == "":
text_extract_method = LOCAL_OCR_MODEL_TEXT_EXTRACT_OPTION
# Show local OCR method accordion only if "Local OCR model - PDFs without selectable text" is selected
# When "AWS Bedrock VLM OCR" is selected, the local OCR method is automatically set to "bedrock-vlm" but the component is hidden
show_local_ocr = text_extract_method == LOCAL_OCR_MODEL_TEXT_EXTRACT_OPTION
# Show AWS Textract settings accordion only if "AWS Textract service - all PDF types" is selected
show_aws_textract = (
text_extract_method == TEXTRACT_TEXT_EXTRACT_OPTION
and SHOW_AWS_TEXT_EXTRACTION_OPTIONS
)
# Show inference server VLM model accordion only if local OCR is selected (not Bedrock VLM) and the option is enabled
show_inference_server = (
text_extract_method == LOCAL_OCR_MODEL_TEXT_EXTRACT_OPTION
and SHOW_INFERENCE_SERVER_VLM_MODEL_OPTIONS
)
return (
gr.update(visible=show_local_ocr), # local_ocr_method_accordion
gr.update(
visible=show_inference_server
), # inference_server_vlm_model_accordion
gr.update(visible=show_aws_textract), # aws_textract_signature_accordion
)
def handle_main_pii_method_selection(pii_method):
"""Handle PII method selection for main components - show appropriate entity dropdowns and hide all if No PII redaction is selected.
Args:
pii_method: Selected PII detection method
Returns:
Tuple of visibility updates for PII method dropdown, local entities accordion, comprehend entities accordion,
LLM entities accordion, and LLM custom instructions accordion
"""
# Normalize string (Gradio can send whitespace)
if isinstance(pii_method, str):
pii_method = pii_method.strip()
# When value is None/empty (e.g. .change() fired before component synced), default to Local so at least one section is visible (e.g. when user clicked Local)
if pii_method is None or pii_method == "":
return (
gr.update(visible=True), # local_entities
gr.update(visible=False), # comprehend_entities
gr.update(visible=False), # llm_entities
gr.update(visible=False), # llm_custom_instructions
)
# Check if "No PII redaction" is selected
is_no_redaction = pii_method == NO_REDACTION_PII_OPTION
# If no redaction, hide all PII-related components
if is_no_redaction:
return (
gr.update(visible=False), # local_entities
gr.update(visible=False), # comprehend_entities
gr.update(visible=False), # llm_entities
gr.update(visible=False), # llm_custom_instructions
)
# Check if method is Local
show_local_entities = pii_method == LOCAL_PII_OPTION
# Check if method is AWS Comprehend
show_comprehend_entities = pii_method == AWS_PII_OPTION
# Check if method is an LLM option
is_llm_method = (
pii_method == LOCAL_TRANSFORMERS_LLM_PII_OPTION
or pii_method == INFERENCE_SERVER_PII_OPTION
or pii_method == AWS_LLM_PII_OPTION
)
return (
gr.update(visible=show_local_entities), # local_entities
gr.update(visible=show_comprehend_entities), # comprehend_entities
gr.update(visible=is_llm_method), # llm_entities
gr.update(visible=is_llm_method), # llm_custom_instructions
)
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