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import gradio as gr | |
import json | |
import re | |
import sqlite3 | |
import logging | |
from collections import defaultdict | |
from typing import Tuple, Dict, List | |
# Assuming you have these files in your project | |
from util import process_json_files | |
from gematria import calculate_gematria | |
from deep_translator import GoogleTranslator, exceptions | |
from urllib.parse import quote_plus | |
from tqdm import tqdm | |
# Constants | |
DATABASE_FILE = 'gematria.db' | |
MAX_PHRASE_LENGTH_LIMIT = 20 | |
BATCH_SIZE = 10000 | |
# Set up logging | |
logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s') | |
# Global variables | |
conn: sqlite3.Connection = None | |
translator: GoogleTranslator = None | |
book_names: Dict[int, str] = {} | |
gematria_cache: Dict[Tuple[int, int], List[Tuple[str, str, int, int, int, str]]] = {} | |
translation_cache: Dict[str, str] = {} | |
total_word_count: int = 0 # Global counter for word position | |
def initialize_database() -> None: | |
"""Initializes the SQLite database.""" | |
global conn | |
conn = sqlite3.connect(DATABASE_FILE) | |
cursor = conn.cursor() | |
cursor.execute(''' | |
CREATE TABLE IF NOT EXISTS results ( | |
gematria_sum INTEGER, | |
words TEXT, | |
translation TEXT, | |
book TEXT, | |
chapter INTEGER, | |
verse INTEGER, | |
phrase_length INTEGER, | |
word_position TEXT, | |
PRIMARY KEY (gematria_sum, words, book, chapter, verse, word_position) | |
) | |
''') | |
cursor.execute(''' | |
CREATE INDEX IF NOT EXISTS idx_results_gematria | |
ON results (gematria_sum) | |
''') | |
cursor.execute(''' | |
CREATE TABLE IF NOT EXISTS processed_books ( | |
book TEXT PRIMARY KEY, | |
max_phrase_length INTEGER | |
) | |
''') | |
conn.commit() | |
def initialize_translator() -> None: | |
"""Initializes the Google Translator.""" | |
global translator | |
translator = GoogleTranslator(source='iw', target='en') | |
logging.info("Translator initialized.") | |
def process_book(book_id: int, max_phrase_length: int, cursor): | |
"""Processes a single book and returns phrases to insert.""" | |
global book_names, total_word_count | |
book_data = process_json_files(book_id, book_id) | |
phrases_to_insert = [] | |
if book_id in book_data: | |
book_data = book_data[book_id] | |
if 'title' not in book_data or not isinstance(book_data['title'], str): | |
logging.warning(f"Skipping book {book_id} due to missing 'title' field.") | |
return phrases_to_insert | |
title = book_data['title'] | |
book_names[book_id] = title | |
# Check if this book has already been processed for this phrase length | |
cursor.execute('''SELECT max_phrase_length FROM processed_books WHERE book = ?''', (title,)) | |
result = cursor.fetchone() | |
if result and result[0] >= max_phrase_length: | |
logging.info(f"Skipping book {title}: Already processed with max_phrase_length {result[0]}") | |
return phrases_to_insert | |
if 'text' not in book_data or not isinstance(book_data['text'], list): | |
logging.warning(f"Skipping book {book_id} due to missing 'text' field.") | |
return phrases_to_insert | |
chapters = book_data['text'] | |
for chapter_id, chapter in enumerate(chapters): | |
for verse_id, verse in enumerate(chapter): | |
verse_text = flatten_text(verse) | |
verse_text = re.sub(r'\[.*?\]', '', verse_text) | |
verse_text = re.sub(r"[^\u05D0-\u05EA ]+", "", verse_text) | |
verse_text = re.sub(r" +", " ", verse_text) | |
words = verse_text.split() | |
for length in range(1, max_phrase_length + 1): | |
for start in range(len(words) - length + 1): | |
phrase_candidate = " ".join(words[start:start + length]) | |
gematria_sum = calculate_gematria(phrase_candidate.replace(" ", "")) | |
word_position_range = f"{total_word_count + start + 1}-{total_word_count + start + length}" | |
phrases_to_insert.append( | |
(gematria_sum, phrase_candidate, None, title, chapter_id + 1, verse_id + 1, length, | |
word_position_range)) | |
total_word_count += len(words) | |
return phrases_to_insert | |
def populate_database(start_book: int, end_book: int, max_phrase_length: int = 1) -> None: | |
"""Populates the database with phrases from the Tanach.""" | |
global conn, book_names, total_word_count | |
logging.info(f"Populating database with books from {start_book} to {end_book}...") | |
with sqlite3.connect(DATABASE_FILE) as conn: | |
cursor = conn.cursor() | |
for book_id in tqdm(range(start_book, end_book + 1), desc="Processing Books"): | |
phrases_to_insert = process_book(book_id, max_phrase_length, cursor) | |
if phrases_to_insert: | |
cursor.executemany(''' | |
INSERT OR IGNORE INTO results (gematria_sum, words, translation, book, chapter, verse, phrase_length, word_position) | |
VALUES (?, ?, ?, ?, ?, ?, ?, ?) | |
''', phrases_to_insert) | |
# Update processed_books after processing each book | |
cursor.execute(''' | |
INSERT OR REPLACE INTO processed_books (book, max_phrase_length) | |
VALUES (?, ?) | |
''', (book_names[book_id], max_phrase_length)) | |
conn.commit() | |
total_word_count = 0 # Reset for the next set of phrase lengths | |
def get_translation(phrase: str) -> str: | |
"""Retrieves or generates the English translation of a Hebrew phrase | |
and caches it in the database. | |
""" | |
global conn, translator, translation_cache | |
# Check if the translation exists in the database | |
with sqlite3.connect(DATABASE_FILE) as conn: | |
cursor = conn.cursor() | |
cursor.execute("SELECT translation FROM results WHERE words = ? LIMIT 1", (phrase,)) | |
result = cursor.fetchone() | |
if result and result[0]: # If a translation exists, use it | |
return result[0] | |
# If no translation in the database, translate and store it | |
translation = translate_and_store(phrase) | |
translation_cache[phrase] = translation | |
# Update the database with the new translation | |
with sqlite3.connect(DATABASE_FILE) as conn: | |
cursor = conn.cursor() | |
cursor.execute("UPDATE results SET translation = ? WHERE words = ?", (translation, phrase)) | |
conn.commit() | |
return translation | |
def translate_and_store(phrase: str) -> str: | |
"""Translates a Hebrew phrase to English using Google Translate.""" | |
global translator | |
max_retries = 3 | |
retries = 0 | |
while retries < max_retries: | |
try: | |
translation = translator.translate(phrase) | |
return translation | |
except (exceptions.TranslationNotFound, exceptions.NotValidPayload, | |
exceptions.ServerException, exceptions.RequestError) as e: | |
retries += 1 | |
logging.warning(f"Error translating phrase '{phrase}': {e}. Retrying... ({retries}/{max_retries})") | |
logging.error(f"Failed to translate phrase '{phrase}' after {max_retries} retries.") | |
return "[Translation Error]" | |
def search_gematria_in_db(gematria_sum: int, max_words: int) -> List[Tuple[str, str, int, int, int, str]]: | |
"""Searches the database for phrases with a given Gematria value.""" | |
global conn | |
with sqlite3.connect(DATABASE_FILE) as conn: | |
cursor = conn.cursor() | |
cursor.execute(''' | |
SELECT words, book, chapter, verse, phrase_length, word_position | |
FROM results | |
WHERE gematria_sum = ? AND phrase_length <= ? | |
''', (gematria_sum, max_words)) | |
results = cursor.fetchall() | |
return results | |
def gematria_search_interface(phrases: str, max_words: int, show_translation: bool) -> str: | |
"""The main function for the Gradio interface, handling multiple phrases.""" | |
global conn, book_names, gematria_cache | |
results = [] | |
all_results = [] # Store results for each phrase | |
middle_words_results = [] # Store middle word results for all books | |
all_names_average_position = 0 # Initialize variable for average position across all names and books | |
total_name_count = 0 # Initialize counter for the total number of names processed | |
phrases = phrases.strip().splitlines() | |
if not phrases: | |
return "Please enter at least one phrase." | |
for phrase in phrases: | |
if not phrase.strip(): | |
continue # Skip empty lines | |
numbers = re.findall(r'\d+', phrase) | |
text_without_numbers = re.sub(r'\d+', '', phrase) | |
phrase_gematria = calculate_gematria(text_without_numbers.replace(" ", "")) | |
phrase_gematria += sum(int(number) for number in numbers) | |
if (phrase_gematria, max_words) in gematria_cache: | |
matching_phrases = gematria_cache[(phrase_gematria, max_words)] | |
else: | |
matching_phrases = search_gematria_in_db(phrase_gematria, max_words) | |
gematria_cache[(phrase_gematria, max_words)] = matching_phrases | |
if not matching_phrases: | |
results.append(f"No matching phrases found for: {phrase}") | |
continue | |
sorted_phrases = sorted(matching_phrases, | |
key=lambda x: (int(list(book_names.keys())[list(book_names.values()).index(x[1])]), x[2], | |
x[3])) | |
results_by_book = defaultdict(list) | |
for words, book, chapter, verse, phrase_length, word_position in sorted_phrases: | |
results_by_book[book].append((words, chapter, verse, phrase_length, word_position)) | |
results.append(f"<h2>Results for: {phrase} (Gematria: {phrase_gematria})</h2>") | |
results.append("<div class='results-container'>") | |
for book, phrases in results_by_book.items(): | |
for words, chapter, verse, phrase_length, word_position in phrases: | |
translation = get_translation(words) if show_translation else "" | |
link = f"https://www.biblegateway.com/passage/?search={quote_plus(book)}+{chapter}%3A{verse}&version=CJB" | |
results.append(f""" | |
<div class='result-item'> | |
<p><b>Book:</b> {book}</p> | |
<p><b>Chapter:</b> {chapter}, <b>Verse:</b> {verse}</p> | |
<p class='hebrew-phrase'><b>Hebrew Phrase:</b> {words}</p> | |
<p><b>Translation:</b> {translation}</p> | |
<p><b>Phrase Length:</b> {phrase_length} words</p> | |
<p><b>Phrase Gematria:</b> {phrase_gematria}</p> | |
<p><b>Word Position in the Tanach:</b> {word_position}</p> | |
<a href='{link}' target='_blank' class='bible-link'>[See on Bible Gateway]</a> | |
</div> | |
""") | |
# Calculate average position for the current name across all books | |
name_average_position = calculate_average_position_for_name(results_by_book) | |
if name_average_position is not None: | |
results.append(f"<p><b>Average Word Position for '{phrase}' across all books:</b> {name_average_position:.2f}</p>") | |
all_names_average_position += name_average_position | |
total_name_count += 1 | |
results.append("</div>") | |
all_results.append(results_by_book) # Store results by book without the phrase | |
# Calculate the average word position across all names and all their books | |
if total_name_count > 0: | |
all_names_average_position /= total_name_count | |
results.append(f"<h2>Average Word Position Across All Names and Books: {all_names_average_position:.2f}</h2>") | |
# Calculate middle words for all input lines (common books) | |
if len(all_results) >= 2: | |
results.append("<h2>Middle Words (Common Books):</h2>") | |
results.append("<div class='results-container'>") | |
common_books = set.intersection(*[set(results.keys()) for results in all_results]) | |
logging.debug(f"Common books: {common_books}") | |
for book in common_books: | |
logging.debug(f"Processing book: {book}") | |
# Find nearest positions for all phrases in the current book | |
nearest_positions = find_nearest_positions([results[book] for results in all_results]) | |
logging.debug(f"Nearest positions in {book}: {nearest_positions}") | |
if nearest_positions: | |
middle_word_position = sum(nearest_positions) / len(nearest_positions) | |
logging.debug(f"Calculated middle word position in {book}: {middle_word_position}") | |
start_position = int(middle_word_position) | |
end_position = start_position + 1 if middle_word_position % 1 != 0 else start_position | |
logging.debug(f"Middle word position range in {book}: {start_position}-{end_position}") | |
middle_words_data = get_words_from_db(book, start_position, end_position) | |
logging.debug(f"Middle words data fetched from database: {middle_words_data}") | |
if middle_words_data: | |
# Store middle word data along with book name for sorting | |
middle_words_results.extend([(book, data) for data in middle_words_data]) | |
else: | |
# Handle edge case: fetch words independently for start and end positions | |
logging.debug(f"No middle words found for range {start_position}-{end_position}. " | |
f"Fetching words independently.") | |
middle_words_data_start = get_words_from_db(book, start_position, start_position) | |
middle_words_data_end = get_words_from_db(book, end_position, end_position) | |
if middle_words_data_start or middle_words_data_end: | |
middle_words_results.extend([(book, data) for data in middle_words_data_start + middle_words_data_end]) | |
# Sort middle words results by book order before displaying | |
middle_words_results.sort(key=lambda x: int(list(book_names.keys())[list(book_names.values()).index(x[0])])) | |
for book, (words, chapter, verse, phrase_length, word_position) in middle_words_results: | |
translation = get_translation(words) if show_translation else "" | |
link = f"https://www.biblegateway.com/passage/?search={quote_plus(book)}+{chapter}%3A{verse}&version=CJB" | |
results.append(f""" | |
<div class='result-item'> | |
<p><b>Book:</b> {book}</p> | |
<p><b>Chapter:</b> {chapter}, <b>Verse:</b> {verse}</p> | |
<p class='hebrew-phrase'><b>Hebrew Phrase:</b> {words}</p> | |
<p><b>Translation:</b> {translation}</p> | |
<p><b>Phrase Length:</b> {phrase_length} words</p> | |
<p><b>Word Position in the Tanach:</b> {word_position}</p> | |
<a href='{link}' target='_blank' class='bible-link'>[See on Bible Gateway]</a> | |
</div> | |
""") | |
results.append("</div>") | |
# Style modified to position search on top and results below | |
style = """ | |
<style> | |
.results-container { | |
display: grid; | |
grid-template-columns: repeat(auto-fit, minmax(300px, 1fr)); | |
gap: 20px; | |
width: 100%; /* Make results container take full width */ | |
} | |
.result-item { | |
border: 1px solid #ccc; | |
padding: 15px; | |
border-radius: 5px; | |
box-shadow: 2px 2px 5px rgba(0, 0, 0, 0.1); | |
} | |
.hebrew-phrase { | |
font-family: 'SBL Hebrew', 'Ezra SIL', serif; | |
direction: rtl; | |
} | |
.bible-link { | |
display: block; | |
margin-top: 10px; | |
color: #007bff; | |
text-decoration: none; | |
} | |
</style> | |
""" | |
return style + "\n".join(results) | |
def calculate_average_position_for_name(results_by_book: Dict[str, List[Tuple]]) -> float: | |
"""Calculates the average word position for a single name across all books.""" | |
positions = [] | |
for book, phrases in results_by_book.items(): | |
for _, _, _, _, word_position in phrases: | |
start, end = map(int, word_position.split('-')) | |
positions.append((start + end) / 2) | |
return sum(positions) / len(positions) if positions else None | |
def find_nearest_positions(results_lists: List[List]) -> List[int]: | |
"""Finds the nearest word positions among multiple lists of results.""" | |
nearest_positions = [] | |
for i in range(len(results_lists)): | |
positions_i = [(int(pos.split('-')[0]) + int(pos.split('-')[1])) / 2 | |
for _, _, _, _, pos in results_lists[i]] # Get average of start and end positions | |
logging.debug(f"Positions for phrase {i+1}: {positions_i}") | |
# Calculate the average position for the current phrase | |
average_position = sum(positions_i) / len(positions_i) if positions_i else None | |
logging.debug(f"Average position for phrase {i+1}: {average_position}") | |
if average_position is not None: | |
nearest_positions.append(average_position) | |
return nearest_positions | |
def get_words_from_db(book: str, start_position: int, end_position: int) -> List[Tuple]: | |
"""Fetches words from the database based on the book and exact word position range.""" | |
global conn | |
logging.debug(f"Fetching words from database for {book} at positions {start_position}-{end_position}") | |
with sqlite3.connect(DATABASE_FILE) as conn: | |
cursor = conn.cursor() | |
cursor.execute(""" | |
SELECT words, chapter, verse, phrase_length, word_position | |
FROM results | |
WHERE book = ? AND word_position = ? | |
""", (book, f"{start_position}-{end_position}")) # Directly compare word_position | |
results = cursor.fetchall() | |
logging.debug(f"Words fetched from database: {results}") | |
return results | |
def flatten_text(text: List) -> str: | |
"""Flattens nested lists into a single list.""" | |
if isinstance(text, list): | |
return " ".join(flatten_text(item) if isinstance(item, list) else item for item in text) | |
return text | |
def run_app() -> None: | |
"""Initializes and launches the Gradio app.""" | |
global conn | |
initialize_database() | |
initialize_translator() | |
logging.info("Starting database population...") | |
for max_phrase_length in range(1, MAX_PHRASE_LENGTH_LIMIT + 1): | |
populate_database(1, 39, max_phrase_length=max_phrase_length) | |
logging.info("Database population complete.") | |
with gr.Blocks() as iface: # Use gr.Blocks() for layout control | |
with gr.Row(): # Place inputs in a row | |
textbox = gr.Textbox(label="Enter word(s) or numbers (one phrase per line)", lines=5) | |
slider = gr.Slider(label="Max Word Count in Result Phrases", minimum=1, | |
maximum=MAX_PHRASE_LENGTH_LIMIT, step=1, | |
value=1) | |
checkbox = gr.Checkbox(label="Show Translation", value=True) | |
with gr.Row(): # Place buttons in a row | |
clear_button = gr.Button("Clear") | |
submit_button = gr.Button("Submit", variant="primary") | |
html_output = gr.HTML(label="Results") # Output for the results | |
submit_button.click(fn=gematria_search_interface, | |
inputs=[textbox, slider, checkbox], | |
outputs=html_output) | |
clear_button.click(fn=lambda: "", inputs=None, outputs=html_output) # Clear the output | |
iface.launch() | |
if __name__ == "__main__": | |
run_app() |