lessismore/lessismore.py
type-two 493c3e912a Public-prep: MIT license, pip packaging, --budget, --serve, infra scrub
- LICENSE (MIT) and pyproject.toml: pip install . gives lessismore + lm
  commands; [tokens] and [ml] extras
- budget(): middle-out hard cap, the only guaranteed-bounded pass; --budget N
  runs after compression as the backstop; char-slicing fallback for single
  giant lines
- serve(): stdlib paste-in demo page, localhost only; lm --serve
- Scrubbed internal hostnames/IPs from samples and README; benchmarks
  re-measured after scrub (interleaved now 54,999 -> 4,585, 12.0x; dedupe
  alone 1.6x on same input)
- 30-assert suite, green on system python and tiktoken venv

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-07 14:53:53 +10:00

363 lines
14 KiB
Python

"""lessismore — squeeze text before it hits an LLM.
Deterministic passes first (free, safe, cacheable). Optional ML pruning
(LLMLingua-2) only when installed and only worth it on big inputs.
from lessismore import compress
small = compress(big_log, level=2)
$ python3 lessismore.py dump.log -l 2 > small.log
$ tail -5000 app.log | python3 lessismore.py -l 2 | llm ...
"""
import json
import re
import sys
from collections import Counter
from functools import lru_cache
# ---------------------------------------------------------------- tokens
@lru_cache(maxsize=1)
def _encoder():
try:
import tiktoken
return tiktoken.get_encoding("o200k_base")
except ImportError:
return None
def count_tokens(text: str) -> int:
enc = _encoder()
if enc:
return len(enc.encode(text))
return max(1, len(text) // 4) # ponytail: chars/4 heuristic; pip install tiktoken for real counts
# ---------------------------------------------------------------- passes
# Each pass is (str) -> str. Order matters: whitespace before dedupe.
def collapse_whitespace(text: str) -> str:
text = re.sub(r"[ \t]+$", "", text, flags=re.M) # trailing whitespace
text = re.sub(r"(?<=\S)[ \t]{2,}", " ", text) # interior runs (leading indent kept: code-safe)
text = re.sub(r"\n{3,}", "\n\n", text) # blank-line runs
return text
def dedupe_lines(text: str) -> str:
"""Collapse runs of identical lines — the classic log killer."""
lines = text.split("\n")
out, i = [], 0
while i < len(lines):
j = i
while j < len(lines) and lines[j] == lines[i]:
j += 1
run = j - i
# marker must actually be shorter than the lines it replaces
if run >= 4 and lines[i].strip() and (run - 1) * (len(lines[i]) + 1) > 45:
out.append(lines[i])
out.append(f"[previous line repeated {run - 1} more times]")
else:
out.extend(lines[i:j])
i = j
# ponytail: only consecutive repeats; add block-level dedupe (repeated stack traces) if logs demand it
return "\n".join(out)
# no '/' in the class: URL paths are ≥64-char alnum+slash runs and they ARE the content
_BLOB = re.compile(r"\b(?:[A-Za-z0-9+]{64,}={0,2}|[0-9a-fA-F]{48,})\b")
def squash_blobs(text: str) -> str:
"""Base64/hex runs are token-dense and semantically opaque — keep head and tail.
The tail suffix keeps two different blobs from squashing to the same stub
and then being falsely merged as "repeated" by dedupe_lines.
"""
return _BLOB.sub(lambda m: f"{m.group()[:12]}[+{len(m.group()) - 16} chars]{m.group()[-4:]}", text)
_TIMESTAMP = re.compile(
r"\b\d{4}-\d{2}-\d{2}[T ]\d{2}:\d{2}:\d{2}(?:[.,]\d+)?(?:Z|[+-]\d{2}:?\d{2})?\b ?"
)
def strip_timestamps(text: str) -> str:
"""Line order already encodes sequence; per-line ISO timestamps are ~8 tokens each."""
# ponytail: ISO-8601 only; add syslog/other formats when a real log needs them
return _TIMESTAMP.sub("", text)
def minify_json(text: str) -> str:
"""Whole-input pretty JSON → minified. Lossless when it fires, untouched when not."""
try:
return json.dumps(json.loads(text), separators=(",", ":"), ensure_ascii=False)
except ValueError:
return text
def collapse_cr(text: str) -> str:
"""Keep only the final state of \\r-overwritten progress lines (pip/tqdm/wget)."""
text = text.replace("\r\n", "\n")
return "\n".join(l.rsplit("\r", 1)[-1] for l in text.split("\n"))
_ANSI = re.compile(r"\x1b\[[0-9;?]*[A-Za-z]") # ponytail: CSI only; add OSC if titles show up
def strip_ansi(text: str) -> str:
"""Color codes carry nothing for an LLM, and they make identical lines differ."""
return _ANSI.sub("", text)
_UUID = re.compile(r"\b[0-9a-fA-F]{8}-(?:[0-9a-fA-F]{4}-){3}[0-9a-fA-F]{12}\b")
def squash_uuids(text: str) -> str:
"""36 chars → 8-hex prefix, git-short-hash style; cross-references still resolve."""
return _UUID.sub(lambda m: m.group()[:8] + "", text)
_PKGPATH = re.compile(r'[^\s"\']+/(?:site-packages|dist-packages|lib/python3\.\d+)/')
def squash_pkgpaths(text: str) -> str:
"""Traceback path spam: …/httpx/_client.py:1054 is still unique without the venv prefix."""
return _PKGPATH.sub("…/", text)
# the lookbehinds keep "not just X" from becoming "not X" — meaning inversion
_FILLER = re.compile(
r"(?<!\bnot )(?<!n't )"
r"\b(?:could you please|can you please|i would like you to|i want you to|"
r"go ahead and|hey there,?|please|kindly|basically|actually|currently|"
r"really|simply|just|very|quite)\b ?",
re.I,
)
def strip_filler(text: str) -> str:
"""Aggressive: eats words like 'just' anywhere, including inside strings. Prose only."""
return _FILLER.sub("", text)
# caveman-style word dropping: every function word is a whole token.
# NEVER add negations (not/no/never), modals (must/should), or order words
# (before/after) — dropping those changes meaning, not just style.
_STICKS = re.compile(
r"\b(?:the|a|an|is|are|was|were|be|been|being|am|i|we|you|they|it|"
r"that|which|who|have|has|had|do|does|did|there)\b ?",
re.I,
)
def two_sticks(text: str) -> str:
"""Gist-only: strips text to caveman. Fine for articles/transcripts, never instructions."""
# keep IT/US-style acronyms that case-insensitively collide with function words
return _STICKS.sub(lambda m: m.group() if m.group().strip().isupper()
and len(m.group().strip()) > 1 else "", text)
_SKEL = re.compile(r"[^A-Za-z]+")
def dedupe_similar(text: str) -> str:
"""Collapse runs of lines identical after masking non-letters — 'same words,
different numbers' (progress lines, per-item CI steps). Keeps first and last
so progression endpoints survive."""
lines = text.split("\n")
out, i = [], 0
while i < len(lines):
k, j = _SKEL.sub(" ", lines[i]).strip(), i
while j < len(lines) and _SKEL.sub(" ", lines[j]).strip() == k:
j += 1
if j - i >= 4 and k:
out += [lines[i], f"[{j - i - 2} similar lines omitted]", lines[j - 1]]
else:
out.extend(lines[i:j])
i = j
return "\n".join(out)
_REF = re.compile(r"@\d+")
def alias_repeats(text: str, min_count: int = 4, min_len: int = 30) -> str:
"""Dictionary-code scattered duplicate lines that consecutive dedupe can't reach.
Lossless — the legend keeps every line verbatim. A code only pays when it
replaces a repeated multi-token sequence; single words are already 1 BPE
token each, so word-level codebooks lose (measured, see README).
"""
lines = text.split("\n")
if any(_REF.fullmatch(l) for l in lines): # already aliased, or real @N content — bail
return text
counts = Counter(l for l in lines if len(l) >= min_len)
# ponytail: c*len>200 chars is the payoff heuristic; tune if legends ever dominate
worth = [l for l, c in counts.items() if c >= min_count and c * len(l) > 200]
if not worth:
return text
ref = {l: f"@{i}" for i, l in enumerate(worth, 1)}
legend = [f"@{i} = {l}" for i, l in enumerate(worth, 1)]
return "\n".join(["[repeated lines aliased:]"] + legend + [""] +
[ref.get(l, l) for l in lines])
# order: strippers leave doubled spaces, so collapse_whitespace runs after them;
# normalized lines then match better in alias_repeats/dedupe_lines/dedupe_similar
_STRIP2 = [minify_json, collapse_cr, strip_ansi, strip_timestamps,
squash_blobs, squash_uuids, squash_pkgpaths]
_MERGE = [collapse_whitespace, alias_repeats, dedupe_lines, dedupe_similar]
LEVELS = {
1: [collapse_whitespace, dedupe_lines], # code-safe
2: _STRIP2 + _MERGE, # logs/dumps/tool output
3: _STRIP2 + [strip_filler] + _MERGE, # prose
4: _STRIP2 + [strip_filler, two_sticks] + _MERGE, # gist-only
}
def compress(text: str, level: int = 1) -> str:
for f in LEVELS[level]:
text = f(text)
return text
def budget(text: str, max_tokens: int) -> str:
"""Hard cap: keep head and tail lines, drop the middle with a marker.
The only pass with GUARANTEED bounded output — run it after compression,
as the backstop, never instead of it.
"""
total = count_tokens(text)
if total <= max_tokens:
return text
lines = text.split("\n")
limit = max(0, max_tokens - 8) # reserve for the marker line
head, tail = [], []
h_tok = t_tok = 0
hi, ti = 0, len(lines) - 1
while hi <= ti:
take_head = h_tok <= t_tok
line = lines[hi] if take_head else lines[ti]
tok = count_tokens(line) + 1
if h_tok + t_tok + tok > limit:
break
if take_head:
head.append(line); h_tok += tok; hi += 1
else:
tail.append(line); t_tok += tok; ti -= 1
if not head and not tail: # one giant line (e.g. minified JSON): slice by chars
keep = limit * 2 # ~4 chars/token, half per side
head, tail = [text[:keep]], [text[-keep:]]
h_tok = count_tokens(head[0]); t_tok = count_tokens(tail[0])
omitted = max(0, total - h_tok - t_tok)
return "\n".join(head + ["[~%d tokens omitted]" % omitted] + list(reversed(tail)))
def serve(port=7777):
"""Paste-in demo page on localhost. Zero deps, binds 127.0.0.1 only."""
import html
import http.server
import urllib.parse
page = ("<!doctype html><meta charset=utf-8><title>lessismore</title>"
"<style>body{font-family:system-ui;max-width:900px;margin:2rem auto;padding:0 1rem;"
"background:#10141a;color:#e6edf3}textarea{width:100%;height:35vh;font-family:monospace;"
"background:#1a2028;color:#e6edf3;border:1px solid #2d3743;border-radius:8px;padding:8px}"
"select,button{font-size:16px;padding:8px 14px;border-radius:8px;border:1px solid #2d3743;"
"background:#1f6feb;color:#fff;cursor:pointer}select{background:#1a2028}</style>"
"<h1>lessismore \U0001F4C9</h1>"
"<form method=post><textarea name=text placeholder='paste your ugliest log here'></textarea>"
"<p>level <select name=level><option>1<option selected>2<option>3<option>4</select> "
"<button>squeeze</button></p></form>{result}")
class Handler(http.server.BaseHTTPRequestHandler):
def log_message(self, *args):
pass
def _page(self, result=""):
body = page.replace("{result}", result).encode("utf-8")
self.send_response(200)
self.send_header("Content-Type", "text/html; charset=utf-8")
self.send_header("Content-Length", str(len(body)))
self.end_headers()
self.wfile.write(body)
def do_GET(self):
self._page()
def do_POST(self):
n = int(self.headers.get("Content-Length", 0))
q = urllib.parse.parse_qs(self.rfile.read(n).decode("utf-8", "replace"))
text = q.get("text", [""])[0]
level = min(4, max(1, int(q.get("level", ["2"])[0])))
out = compress(text, level)
b, a = count_tokens(text), count_tokens(out)
self._page("<p><b>{:,}{:,} tokens ({}% saved)</b></p>"
"<textarea readonly>{}</textarea>".format(
b, a, round(100 * (1 - a / max(b, 1))), html.escape(out)))
print("lessismore UI on http://localhost:%d (Ctrl+C to stop)" % port)
http.server.ThreadingHTTPServer(("127.0.0.1", port), Handler).serve_forever()
# ---------------------------------------------------------------- optional ML pass
@lru_cache(maxsize=1)
def _llmlingua():
from llmlingua import PromptCompressor # pip install llmlingua
return PromptCompressor(
model_name="microsoft/llmlingua-2-xlm-roberta-large-meetingbank",
use_llmlingua2=True,
)
def compress_ml(text: str, rate: float = 0.5) -> str:
"""Perplexity-based token pruning (LLMLingua-2).
Runs a local classifier model — only pays for itself on multi-KB inputs.
Run the deterministic passes first; never feed it code you need verbatim.
"""
return _llmlingua().compress_prompt(text, rate=rate)["compressed_prompt"]
# ---------------------------------------------------------------- CLI
def main():
import argparse
p = argparse.ArgumentParser(prog="lessismore", description=__doc__.splitlines()[0])
p.add_argument("file", nargs="?", help="input file (default: stdin)")
p.add_argument("-l", "--level", type=int, default=1, choices=sorted(LEVELS),
help="1=code-safe 2=logs/dumps 3=prose 4=gist-only caveman (default 1)")
p.add_argument("--ml", type=float, metavar="RATE",
help="also run LLMLingua-2 keeping RATE of tokens (needs: pip install llmlingua)")
p.add_argument("--budget", type=int, metavar="N",
help="hard cap output at ~N tokens: keep head+tail, drop the middle")
p.add_argument("--serve", nargs="?", const=7777, type=int, metavar="PORT",
help="serve a paste-in demo page on localhost (default port 7777)")
a = p.parse_args()
if a.serve:
return serve(a.serve)
# newline="" / buffer.read(): keep \r intact for collapse_cr
raw = (open(a.file, encoding="utf-8", errors="replace", newline="").read() if a.file
else sys.stdin.buffer.read().decode("utf-8", "replace"))
out = compress(raw, a.level)
if a.ml:
try:
out = compress_ml(out, a.ml)
except ImportError:
sys.exit("--ml needs: pip install llmlingua")
if a.budget:
out = budget(out, a.budget)
sys.stdout.write(out)
before, after = count_tokens(raw), count_tokens(out)
print(f"lessismore: {before}{after} tokens ({1 - after / max(before, 1):.0%} saved)",
file=sys.stderr)
if __name__ == "__main__":
main()