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neuralworm
commited on
Commit
·
cb87c06
1
Parent(s):
63ae283
els cache with function parameters
Browse files- app.py +82 -28
- els_cache.db +0 -3
- els_cache.db.initial +0 -3
app.py
CHANGED
@@ -44,6 +44,20 @@ MAX_PHRASE_LENGTH_LIMIT = 20
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ELS_CACHE_DB = "els_cache.db"
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DATABASE_TIMEOUT = 60
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# --- Database Initialization ---
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def initialize_database():
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global conn
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@@ -58,7 +72,7 @@ def initialize_database():
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chapter INTEGER,
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verse INTEGER,
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phrase_length INTEGER,
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word_position TEXT,
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PRIMARY KEY (gematria_sum, words, book, chapter, verse, word_position)
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)
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''')
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@@ -80,25 +94,53 @@ initialize_database()
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# --- ELS Cache Functions ---
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def create_els_cache_table():
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with sqlite3.connect(ELS_CACHE_DB) as conn:
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return hashlib.sha256(json.dumps(key).encode()).hexdigest()
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def cached_process_json_files(func, *args, **kwargs):
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try:
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with sqlite3.connect(ELS_CACHE_DB, timeout=DATABASE_TIMEOUT) as conn:
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cursor = conn.cursor()
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cursor.execute(
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result = cursor.fetchone()
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if result:
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logger.info(f"Cache hit for query: {query_hash}")
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@@ -112,13 +154,15 @@ def cached_process_json_files(func, *args, **kwargs):
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try:
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with sqlite3.connect(ELS_CACHE_DB, timeout=DATABASE_TIMEOUT) as conn:
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cursor = conn.cursor()
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cursor.execute("INSERT INTO els_cache (query_hash, results) VALUES (?, ?)",
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conn.commit()
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except sqlite3.Error as e:
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logger.error(f"Database error caching results: {e}")
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return results
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# --- Helper Functions (from Network app.py) ---
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def flatten_text(text: List) -> str:
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if isinstance(text, list):
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@@ -130,8 +174,8 @@ def search_gematria_in_db(gematria_sum: int, max_words: int) -> List[Tuple[str,
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with sqlite3.connect(DATABASE_FILE) as conn:
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cursor = conn.cursor()
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cursor.execute('''
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SELECT words, book, chapter, verse, phrase_length, word_position
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FROM results
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WHERE gematria_sum = ? AND phrase_length <= ?
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''', (gematria_sum, max_words))
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results = cursor.fetchall()
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@@ -174,40 +218,50 @@ def perform_els_search(step, rounds_combination, tlang, strip_spaces, strip_in_b
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length = 0
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selected_language_long = tlang # From the Gradio dropdown (long form)
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tlang = "en"
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logger.warning(
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if include_torah:
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logger.debug(
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-
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else:
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results["Torah"] = []
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if include_bible:
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results["Bible"] = cached_process_json_files(bible.process_json_files, 40, 66, step, rounds_combination, length,
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else:
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results["Bible"] = []
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if include_quran:
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results["Quran"] = cached_process_json_files(quran.process_json_files, 1, 114, step, rounds_combination, length,
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else:
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results["Quran"] = []
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if include_hindu:
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results["Rig Veda"] = cached_process_json_files(
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else:
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results["Rig Veda"] = []
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if include_tripitaka:
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results["Tripitaka"] = cached_process_json_files(
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else:
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results["Tripitaka"] = []
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return results
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def add_24h_projection(results_dict): #Now takes a dictionary of results
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for book_name, results in results_dict.items(): # Iterate per book
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num_results = len(results)
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@@ -304,14 +358,14 @@ with gr.Blocks() as app:
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with gr.Row():
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step = gr.Number(label="Jump Width (Steps) for ELS")
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float_step = gr.Number(visible=False, value=1)
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half_step_btn = gr.Button("Steps / 2")
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double_step_btn = gr.Button("Steps * 2")
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with gr.Column():
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round_x = gr.Number(label="Round (1)", value=1)
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round_y = gr.Number(label="Round (2)", value=-1)
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rounds_combination = gr.Textbox(label="Combined Rounds", value="1,-1")
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with gr.Row():
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@@ -320,7 +374,7 @@ with gr.Blocks() as app:
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include_quran_chk = gr.Checkbox(label="Include Quran", value=True)
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include_hindu_chk = gr.Checkbox(label="Include Rigveda", value=False)
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include_tripitaka_chk = gr.Checkbox(label="Include Tripitaka", value=False)
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strip_spaces = gr.Checkbox(label="Strip Spaces from Books", value=True)
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strip_in_braces = gr.Checkbox(label="Strip Text in Braces from Books", value=True)
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strip_diacritics_chk = gr.Checkbox(label="Strip Diacritics from Books", value=True)
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ELS_CACHE_DB = "els_cache.db"
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DATABASE_TIMEOUT = 60
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# --- ELS Cache Functions ---
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def create_els_cache_table():
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if not os.path.exists(ELS_CACHE_DB):
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with sqlite3.connect(ELS_CACHE_DB) as conn:
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conn.execute('''
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CREATE TABLE els_cache (
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query_hash TEXT PRIMARY KEY,
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function_name TEXT,
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args TEXT,
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kwargs TEXT,
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results TEXT
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)
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''')
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# --- Database Initialization ---
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def initialize_database():
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global conn
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chapter INTEGER,
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verse INTEGER,
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phrase_length INTEGER,
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word_position TEXT,
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PRIMARY KEY (gematria_sum, words, book, chapter, verse, word_position)
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)
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''')
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# --- ELS Cache Functions ---
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def create_els_cache_table():
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with sqlite3.connect(ELS_CACHE_DB) as conn:
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try:
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conn.execute('''
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CREATE TABLE IF NOT EXISTS els_cache (
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query_hash TEXT PRIMARY KEY,
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function_name TEXT,
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args TEXT,
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kwargs TEXT,
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results TEXT
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)
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''')
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except sqlite3.OperationalError as e:
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logger.error(f"Error creating table: {e}")
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def get_query_hash(func, args, kwargs):
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key = (func.__name__, args, kwargs)
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return hashlib.sha256(json.dumps(key).encode()).hexdigest()
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def cached_process_json_files(func, *args, **kwargs):
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# Create a dictionary to store the parameters
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params = {
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"function": f"{func.__module__}.{func.__name__}"
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}
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# Add the positional arguments with their names
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arg_names = func.__code__.co_varnames[:func.__code__.co_argcount]
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for name, value in zip(arg_names, args):
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params[name] = value
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# Add the keyword arguments
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for name, value in kwargs.items():
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params[name] = value
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# Convert the parameters to a JSON string
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params_json = json.dumps(params)
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# Use the parameters JSON string to generate the query hash
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query_hash = get_query_hash(func, params_json, "")
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# Ensure the table exists before any operations
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create_els_cache_table()
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try:
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with sqlite3.connect(ELS_CACHE_DB, timeout=DATABASE_TIMEOUT) as conn:
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cursor = conn.cursor()
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cursor.execute(
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"SELECT results FROM els_cache WHERE query_hash = ?", (query_hash,))
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result = cursor.fetchone()
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if result:
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logger.info(f"Cache hit for query: {query_hash}")
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try:
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with sqlite3.connect(ELS_CACHE_DB, timeout=DATABASE_TIMEOUT) as conn:
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cursor = conn.cursor()
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cursor.execute("INSERT INTO els_cache (query_hash, function_name, args, kwargs, results) VALUES (?, ?, ?, ?, ?)",
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(query_hash, params["function"], params_json, json.dumps({}), json.dumps(results)))
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conn.commit()
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except sqlite3.Error as e:
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logger.error(f"Database error caching results: {e}")
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return results
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+
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# --- Helper Functions (from Network app.py) ---
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def flatten_text(text: List) -> str:
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if isinstance(text, list):
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with sqlite3.connect(DATABASE_FILE) as conn:
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cursor = conn.cursor()
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cursor.execute('''
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SELECT words, book, chapter, verse, phrase_length, word_position
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FROM results
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WHERE gematria_sum = ? AND phrase_length <= ?
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''', (gematria_sum, max_words))
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results = cursor.fetchall()
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length = 0
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selected_language_long = tlang # From the Gradio dropdown (long form)
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# Get the short code.
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tlang = LANGUAGES_SUPPORTED.get(selected_language_long)
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if tlang is None: # Handle unsupported languages
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tlang = "en"
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logger.warning(
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f"Unsupported language selected: {selected_language_long}. Defaulting to English (en).")
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# Cache Update: Pass parameters individually
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if include_torah:
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logger.debug(
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f"Arguments for Torah: {(1, 39, step, rounds_combination, length, tlang, strip_spaces, strip_in_braces, strip_diacritics_chk)}")
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results["Torah"] = cached_process_json_files(torah.process_json_files, 1, 39, step, rounds_combination, length,
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tlang, strip_spaces, strip_in_braces, strip_diacritics_chk)
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else:
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results["Torah"] = []
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if include_bible:
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results["Bible"] = cached_process_json_files(bible.process_json_files, 40, 66, step, rounds_combination, length,
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tlang, strip_spaces, strip_in_braces, strip_diacritics_chk)
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else:
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results["Bible"] = []
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if include_quran:
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results["Quran"] = cached_process_json_files(quran.process_json_files, 1, 114, step, rounds_combination, length,
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tlang, strip_spaces, strip_in_braces, strip_diacritics_chk)
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else:
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results["Quran"] = []
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if include_hindu:
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results["Rig Veda"] = cached_process_json_files(
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hindu.process_json_files, 1, 10, step, rounds_combination, length, tlang, False, strip_in_braces, strip_diacritics_chk)
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else:
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results["Rig Veda"] = []
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if include_tripitaka:
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results["Tripitaka"] = cached_process_json_files(
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tripitaka.process_json_files, 1, 52, step, rounds_combination, length, tlang, strip_spaces, strip_in_braces, strip_diacritics_chk)
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else:
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results["Tripitaka"] = []
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return results
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+
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def add_24h_projection(results_dict): #Now takes a dictionary of results
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for book_name, results in results_dict.items(): # Iterate per book
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num_results = len(results)
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with gr.Row():
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step = gr.Number(label="Jump Width (Steps) for ELS")
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float_step = gr.Number(visible=False, value=1)
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half_step_btn = gr.Button("Steps / 2")
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double_step_btn = gr.Button("Steps * 2")
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with gr.Column():
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round_x = gr.Number(label="Round (1)", value=1)
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round_y = gr.Number(label="Round (2)", value=-1)
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rounds_combination = gr.Textbox(label="Combined Rounds", value="1,-1")
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with gr.Row():
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include_quran_chk = gr.Checkbox(label="Include Quran", value=True)
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include_hindu_chk = gr.Checkbox(label="Include Rigveda", value=False)
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include_tripitaka_chk = gr.Checkbox(label="Include Tripitaka", value=False)
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strip_spaces = gr.Checkbox(label="Strip Spaces from Books", value=True)
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strip_in_braces = gr.Checkbox(label="Strip Text in Braces from Books", value=True)
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strip_diacritics_chk = gr.Checkbox(label="Strip Diacritics from Books", value=True)
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els_cache.db
DELETED
@@ -1,3 +0,0 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:66db30b6eccaaaed442d806a1c1300f62238946ecc0bf09b77e9e385a4ad3458
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size 12288
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els_cache.db.initial
DELETED
@@ -1,3 +0,0 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:66db30b6eccaaaed442d806a1c1300f62238946ecc0bf09b77e9e385a4ad3458
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-
size 12288
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