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import json | |
import logging | |
import argparse | |
import sys | |
import os | |
import re | |
import math | |
import pickle | |
from deep_translator import GoogleTranslator | |
from gematria import calculate_gematria | |
# --- Konfiguration --- | |
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') | |
BOOK_RANGE = range(1, 40) | |
INDICES_DIR = "indices_by_book" | |
CACHE_FILE = "tanakh_oracledata.cache" # Eigene Cache-Datei für dieses Skript | |
# --- Kernfunktionen --- | |
def xor_with_highest_power(total_sum, query_value): | |
"""Ihre XOR-Logik.""" | |
if total_sum <= 0 or query_value <= 1: return None | |
if query_value > total_sum: power = 1 | |
else: | |
try: | |
exponent = int(math.floor(math.log(total_sum, query_value))) | |
power = query_value ** exponent | |
except ValueError: return None | |
return total_sum ^ power | |
def load_or_create_phrase_dictionary(use_cache=True): | |
""" | |
Lädt oder erstellt das universelle Phrasen-Wörterbuch (Gematria-Tabelle). | |
Struktur: { gematria_value: [phrase_obj_1, ...], ... } | |
""" | |
if use_cache and os.path.exists(CACHE_FILE): | |
logging.info(f"Lade Phrasen-Wörterbuch aus Cache: {CACHE_FILE}") | |
with open(CACHE_FILE, 'rb') as f: | |
return pickle.load(f) | |
logging.info("Erstelle universelles Phrasen-Wörterbuch aus allen Indizes (dies dauert einen Moment)...") | |
phrase_dict = {} | |
all_indices = {} | |
for i in BOOK_RANGE: | |
index_path = os.path.join(INDICES_DIR, f"book_{i:02}_index.json") | |
if os.path.exists(index_path): | |
with open(index_path, 'r', encoding='utf-8') as f: | |
all_indices[i] = json.load(f) | |
if not all_indices: | |
sys.exit("Keine Index-Dateien gefunden. Bitte 'build_indices.py' ausführen.") | |
for book_num, index in all_indices.items(): | |
for gematria_val_str, data in index.items(): | |
gematria_val = int(gematria_val_str) | |
if gematria_val not in phrase_dict: | |
phrase_dict[gematria_val] = [] | |
pagerank = data.get('pagerank', 0) | |
for phrase_data in data.get('phrases', []): | |
count = phrase_data.get('count', 1) | |
score = pagerank / count if count > 0 else 0 | |
# Speichere nur Phrasen mit einem minimalen Score, um Rauschen zu reduzieren | |
if score > 0: | |
phrase_dict[gematria_val].append({ | |
"text": phrase_data['text'], | |
"score": score, | |
"source": f"B{book_num:02d}" | |
}) | |
# Sortiere die Phrasenlisten innerhalb jedes Eintrags nach Score | |
for gematria_val in phrase_dict: | |
phrase_dict[gematria_val].sort(key=lambda x: x['score'], reverse=True) | |
logging.info(f"{len(phrase_dict)} einzigartige Gematria-Werte im Wörterbuch.") | |
if use_cache: | |
logging.info(f"Speichere Phrasen-Wörterbuch in Cache: {CACHE_FILE}") | |
with open(CACHE_FILE, 'wb') as f: | |
pickle.dump(phrase_dict, f) | |
return phrase_dict | |
def find_most_meaningful_phrase(target_sum, phrase_dictionary): | |
"""Findet die eine, bedeutungsvollste Phrase für eine gegebene Summe.""" | |
if target_sum in phrase_dictionary and phrase_dictionary[target_sum]: | |
# Gibt die Phrase mit dem höchsten Score zurück (da die Liste vorsortiert ist) | |
return phrase_dictionary[target_sum][0] | |
return None | |
# --- Hauptprogramm --- | |
def main(args): | |
# 1. Lade das universelle Phrasen-Wörterbuch | |
phrase_dictionary = load_or_create_phrase_dictionary(use_cache=not args.no_cache) | |
# 2. Berechne Gematria-Wert der Anfrage | |
query_value = calculate_gematria(args.query) | |
if query_value <= 1: | |
sys.exit(f"Anfrage '{args.query}' hat einen ungültigen Gematria-Wert ({query_value}).") | |
# Initialisiere den Übersetzer | |
try: | |
translator = GoogleTranslator(source='iw', target='en') | |
except Exception as e: | |
logging.error(f"Konnte Übersetzer nicht initialisieren: {e}") | |
translator = None | |
# 3. Iteriere durch jeden Vers des Tanach | |
logging.info(f"Starte Orakel-Analyse für '{args.query}' (Gematria: {query_value})...") | |
print("\n" + "="*20 + f" ORAKEL-ANTWORTEN FÜR '{args.query}' " + "="*20) | |
resonance_count = 0 | |
for book_num in BOOK_RANGE: | |
filepath = f"texts/torah/{book_num:02}.json" | |
try: | |
with open(filepath, 'r', encoding='utf-8') as file: | |
data = json.load(file) | |
for chap_idx, chapter in enumerate(data.get("text", []), start=1): | |
for verse_idx, verse_text in enumerate(chapter, start=1): | |
verse_sum = calculate_gematria(verse_text) | |
if verse_sum <= 1: continue | |
# Führe die XOR-Operation durch | |
target_sum = xor_with_highest_power(verse_sum, query_value) | |
if target_sum is None: continue | |
# Finde die beste Resonanz-Phrase | |
best_match = find_most_meaningful_phrase(target_sum, phrase_dictionary) | |
if best_match: | |
resonance_count += 1 | |
verse_ref = f"B{book_num:02d}, K{chap_idx}, V{verse_idx}" | |
# Übersetze die gefundene Phrase | |
translation = "" | |
if translator: | |
try: | |
translation = translator.translate(best_match['text']) | |
except Exception: | |
translation = "[Übersetzung fehlgeschlagen]" | |
print(f"\n--- Resonanz in [{verse_ref}] (G_sum:{verse_sum}) ---") | |
print(f"Originalvers: {verse_text.strip()}") | |
print(f" ↳ Orakel-Antwort (G_ziel:{target_sum}): {best_match['text']} (aus {best_match['source']})") | |
if translation: | |
print(f" ↳ Englische Interpretation: \"{translation}\"") | |
if resonance_count >= args.limit: | |
logging.info(f"Ausgabelimit von {args.limit} Resonanzen erreicht.") | |
return | |
except FileNotFoundError: | |
continue | |
logging.info(f"Analyse abgeschlossen. {resonance_count} Resonanzen gefunden.") | |
if __name__ == "__main__": | |
parser = argparse.ArgumentParser(description="Tanakh Numerological Oracle Engine.") | |
parser.add_argument("query", type=str, help="Die Abfragephrase (z.B. 'יהוה').") | |
parser.add_argument("--limit", type=int, default=10, help="Maximale Anzahl der auszugebenden Orakel-Antworten.") | |
parser.add_argument("--no-cache", action="store_true", help="Erzwingt das Neuerstellen des Phrasen-Wörterbuchs.") | |
args = parser.parse_args() | |
main(args) | |