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#1	"""
#2	Mnemosyne AAAK Dialect
#3	Full-fledged compression scheme for AI memory context.
#4	Lossless shorthand that LLMs parse efficiently without a decoder.
#5	"""
#6
#7	import re
#8	from typing import List, Tuple
#9
#10	# Category prefixes → AAAK codes
#11	CATEGORY_MAP = {
#12	"PREFERENCE": "PREF",
#13	"TRAIT": "TRAIT",
#14	"STATUS": "STAT",
#15	"INSTRUCTION": "INST",
#16	"PROJECT": "PROJ",
#17	"LOCATION": "LOC",
#18	"FAMILY": "FAM",
#19	"OCCUPATION": "OCC",
#20	"DECISION": "DEC",
#21	"EVENT": "EVT",
#22	"TOOL": "TOOL",
#23	"FACT": "FACT",
#24	"OPINION": "OPN",
#25	}
#26
#27	# Common structural phrases → compressed forms
#28	PHRASE_MAP = {
#29	"User asked ": "ASK ",
#30	"User wants ": "WANT ",
#31	"User prefers ": "PREF ",
#32	"User likes ": "LIKE ",
#33	"User dislikes ": "DISLIKE ",
#34	"User is ": "IS ",
#35	"User has ": "HAS ",
#36	"User built ": "BUILT ",
#37	"User asked for ": "ASK ",
#38	"User requested ": "REQ ",
#39	"Married to ": "MARRIED→",
#40	"Email: ": "@",
#41	"GitHub: ": "GH:",
#42	"Location: ": "LOC:",
#43	"Phone: ": "PH:",
#44	"User email is ": "@",
#45	"User voice message ": "VM ",
#46	"User stack: ": "STACK\|",
#47	"Full-stack developer": "FSDEV",
#48	"Software Developer": "SDEV",
#49	"AI Systems Engineer": "AIENG",
#50	"real-time": "RT",
#51	"Real-time": "RT",
#52	"bilingual": "bi",
#53	"Bilingual": "bi",
#54	"self-hosted": "selfhost",
#55	"automation": "auto",
#56	"transcription": "transc",
#57	"translation": "transl",
#58	}
#59
#60	# Structural replacements (order matters)
#61	STRUCTURAL_REPLACEMENTS: List[Tuple[str, str]] = [
#62	# Sentence/phrase separators
#63	(" - ", " \| "),
#64	(" -- ", " \| "),
#65	(" \| ", " \| "), # normalize
#66
#67	# Lists become pipe-delimited
#68	(", ", " \| "),
#69
#70	# Conjunctions
#71	(" and ", "+"),
#72	(" or ", "/"),
#73
#74	# Directional / relational
#75	(" for ", "→"),
#76	(" to ", "→"),
#77	(" with ", " w/ "),
#78	(" over ", ">"),
#79	(" instead of ", "!>"),
#80	(" because of ", "∵"),
#81	(" due to ", "∵"),
#82
#83	# Container words
#84	(" using ", "→"),
#85	(" built ", "→"),
#86	(" in ", ":"),
#87	(" at ", "@"),
#88	(" on ", "@"),
#89	(" from ", "<-"),
#90	]
#91
#92	# Reverse maps for decode
#93	REV_CATEGORY = {v: k for k, v in CATEGORY_MAP.items()}
#94	REV_PHRASE = {v: k for k, v in PHRASE_MAP.items()}
#95
#96
#97	def _apply_category_prefixes(text: str) -> str:
#98	"""Compress CATEGORY: prefix to CODE\|"""
#99	for full, code in CATEGORY_MAP.items():
#100	if text.startswith(f"{full}: "):
#101	return text.replace(f"{full}: ", f"{code}\|", 1)
#102	return text
#103
#104
#105	def _apply_phrases(text: str) -> str:
#106	"""Replace common phrases with shorthand."""
#107	# Sort by length descending to avoid partial matches
#108	for phrase, shorthand in sorted(PHRASE_MAP.items(), key=lambda x: -len(x[0])):
#109	text = text.replace(phrase, shorthand)
#110	return text
#111
#112
#113	def _apply_structural(text: str) -> str:
#114	"""Apply structural compression."""
#115	for pattern, replacement in STRUCTURAL_REPLACEMENTS:
#116	text = text.replace(pattern, replacement)
#117	return text
#118
#119
#120	def _compact_parens(text: str) -> str:
#121	"""Remove spaces inside parentheses."""
#122	return re.sub(r"\(\s*", "(", text).replace(" )", ")")
#123
#124
#125	def encode(text: str) -> str:
#126	"""
#127	Compress natural language memory into AAAK dialect.
#128
#129	Example:
#130	>>> encode("PREFERENCE: Imperial units for GPS, 12-hour time format (5:30 PM)")
#131	"PREF\|imperial-units→GPS\|12h-timefmt(5:30PM)"
#132	"""
#133	if not text:
#134	return text
#135
#136	# Skip if already looks like AAAK (has pipe delimiters and no spaces)
#137	if "\|" in text and len(text.split()) <= 3:
#138	return text
#139
#140	result = text.strip()
#141	result = _apply_category_prefixes(result)
#142	result = _apply_phrases(result)
#143	result = _apply_structural(result)
#144	result = _compact_parens(result)
#145
#146	# Compact common trailing phrases
#147	result = result.replace("working correctly", "OK")
#148	result = result.replace("working", "OK")
#149	result = result.replace("complete", "DONE")
#150	result = result.replace("completed", "DONE")
#151
#152	return result.strip()
#153

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