Changelog¶

All notable changes to this project are documented here. The format follows Keep a Changelog, and this project follows Semantic Versioning.

[0.3.6] — 2026-09-09¶

Changed¶

A document that never uses the words is not asked about them. The mirror of the record answer, on the refusal path: a question naming one document and one of the corpus's own field heads, where that document never uses the head's words anywhere — record or prose — has no answer in the only source it may be answered from, so the three candidates and the three judgements that would refuse them are not paid for. Measured before it was written: the condition holds for zero of 123 factual questions across three corpora, and for 24 of 25 traps at a thousand documents. The fifty-question run over that store takes 109 s, from 205 s and from 620 s at the start of the day; quality is unchanged everywhere (field set 40/40 · 15/15 · 7/8 · 10/10, scale 25/25 · 25/25, NIST 11/13, EN 17/17), and the mechanically-derived set rises to 56/58 factual.

[0.3.5] — 2026-09-09¶

The release where the commonest question stopped costing anything, and the field set went to a full card.

Measured, three runs, medians, zero flips in every category. 62-document field set (73 q): factual 40/40, comparisons 15/15, frontier 7/8, traps 10/10 — and a factual question that names a document now takes 0.01 s instead of 10.4 s. Twelve hardware specifications the system has never seen, with no adaptation: 8/8 · 4/4 · 3/3 · 4/4. A thousand generated specifications (50 q): 25/25 · 25/25. NIST 11/13, EN 17/17; 151 invariants.

Added¶

A field of a named document is read, not generated. The commonest question a document store is asked needs no engine: the row exists, the source is named, the head is named. On the question door it is read before the router as well, because ask() is asked a question by contract. Tried once before and reverted for firing on one question in twelve — the cause was the naming underneath it, and a bullet being read as part of a head, both fixed here.

Fixed¶

A value belongs to the field it was written under. A specification carrying MEMORY: 128 GB and no STORAGE line was asked for its storage and answered "128 GB", stamped with that document — and every gate agreed, because the source was right, the number was in the evidence, and the sentence answered the shape of the question. Only the FIELD was wrong. A local veto now requires a claim's digits to appear on a line that carries the asked head. On the thousand- document set, traps 23/25 → 25/25.
A bullet is not part of a head. Documents open list items with "·", so the record reader saw "· DURATION" as a second field beside DURATION — the same rows twice in the corpus's own vocabulary, and no head ever unique.
A source stamp survives the space in a document's name. Answer.sources was read by splitting the answer on whitespace and keeping words that start with '#', so "#docx:Course 02" arrived as "#docx:Course" — a stamp two siblings share, which is not provenance.
A head is easier to recognise beside one of its values. Shown a bare list of field names, the engine could not see that a question about a SCREEN means DISPLAY; shown "DISPLAY (e.g. 13 inches)" it could. The values are the documents' own, and a question no field fits still returns NONE.

[0.3.4] — 2026-09-09¶

The release where the readings were measured above sixty documents for the first time, and where the comparison category — the one this project kept calling its weakest — went to 15/15 with zero flips.

Measured, three runs, medians. 62-document field set (73 q): factual 37→39/40, comparisons 10→15/15, frontier 7/8, traps 10/10. Twelve hardware specifications the system had never seen (19 q): 8/8, 4/4, 3/3, 4/4 — a complete card on a corpus with no adaptation. 1,000 generated specifications (50 q): factual 25/25, traps 23/25. NIST 11/13 and EN 17/17 unchanged; 148 invariants.

Fixed¶

The extremes of a field are the corpus's, not the block's. The first measurement above sixty documents found the worst kind of bug this system can have: a confident wrong answer with a source stamp on it. The census lays one row per source and stops at sixty, and the extremes row was computed from the rows that fitted — so on a corpus of a thousand the memory reported the highest price among the first sixty documents in alphabetical order. Every word was attested; only the superlative was false, and the superlative is the part nobody can check by reading one line. What is shown may be capped; what is claimed may not.
One question over a thousand documents took 315 seconds. The record rider rebuilt the head index — a read of every sentence — once per source. Built when the store changes and kept otherwise: same reading, 315 s → 11 s, and a 50-question run 620 s → 348 s.
The verdict speaks before the lines it is drawn from. The comparison's verdict row was appended after every line the two documents contributed, so the engine answered off two raw lines ("1 full day" versus "1 day"), concluded they differ, and the jury refused it — the turn abstaining with the answer two lines below where the reader stopped. The census learned this months ago; the comparison layout now has it too.
A sibling is not the document you named. Sibling programmes share their opening phrase and differ only in a tail, so a question about ONE of them was read as naming six, and the comparison layout fired for a question that compares nothing. Among the sources a question calls, the one whose name it accounts for most completely is the one it names; a tie keeps everyone, because two names matched in full is what a comparison is.
A missing engine says which engine is missing. pip install living-memory-model pulls in nothing, so a first learn() on a fresh machine reached the default local engine and reported ModuleNotFoundError: No module named 'torch' — a sentence that names neither the choice to be made nor the four ways to make it. The name in the message is the distribution name, kept in one place, because telling someone to install lmm[local] sends them to a different project.
CI had been red since the 0.3.2 rename, and nothing in the repository showed it. The dependency-free check struck out the package's old name from pip's list and so reported the package itself as a dependency; three consultation tests reached the engine through the small helpers a turn asks on its way, and failed on a machine with nothing installed. The suite's own claim — no model, no network — is now verified the only way it can be, in a virtualenv with neither.

Changed¶

The question door does not gamble on a chat. Every question was paying for a full chat completion that was thrown away: the speculation buys latency in a consultation, where the router's verdict and the chat reply are wanted at once, and ask() inherited it only because it passes teach=False. Same for the delivery bridge, which offers a composed catalogue when a consultation cannot answer — the question door has compose() for that. Factual questions 12.0 → 9.0 calls and 18,800 → 16,300 prompt tokens; traps 12.0 → 8.0 calls. Session.respond takes conversational= for callers that want the consultation behaviour explicitly.
The documentation site follows main. Publishing was a command someone had to remember, and the site had been serving 0.3.2 while the sources for 0.3.3 sat in the repository. It builds with --strict, so a broken link fails in CI rather than in a reader's tab.

[0.3.3] — 2026-09-08¶

The release where the memory leaves the process. A question asked in other words now reaches the documents' own vocabulary, a document that argues with itself says so, and the same three verbs are available over HTTP, in LangChain and in TypeScript — each with the audit intact.

Measured, three runs, medians. On a corpus of English hardware specifications this system had never seen, with no adaptation: frontier 0/3 → 2/3, factual 8/8, comparisons 4/4, traps 4/4. On the 73-question Turkish field set: frontier 5/8 → 7/8, factual 38/40, traps 10/10, comparisons 12/15. NIST 11/13 and EN 17/17 unchanged; 142 invariants.

Added¶

The same three verbs over HTTP, one memory per user (lmm.serve). A memory that lives in one process is a library; it becomes a product the moment a second person asks it something. Every user's store is chosen by their id and nothing else, no route reads across users, an id that could climb a path is refused before it becomes a filename, and each memory holds its own lock so different users answer in parallel. It is a transport, not a second brain: the abstention and the source stamps cross the wire intact. Localhost by default; LMM_TOKEN adds a bearer check. Zero dependencies.
LangChain adapters (lmm.adapters.langchain). A retriever whose passages carry their document stamps, and an agent tool that returns the answer that was AUDITED — with its sources, and with the refusal as itself, because an agent handed an empty string writes its own answer over the silence. LangChain is not a dependency: without langchain_core the same calls return duck-typed equivalents.
A TypeScript client (sdk/typescript). ask resolves to the same four fields a Python caller receives; a client returning a bare string would discard the only property that separates this from a chat completion. No dependencies. Its wire test starts the real Python server and checks across the two languages that what one user teaches, another cannot read.

Fixed¶

A refusal is spoken in the language it was asked in. Hidden behind a Turkish corpus: six English questions with no answer in the store were refused in Dutch, French and Spanish — never once in English. The question is now handed back as a language sample inside the instruction, the rule is repeated as the last thing read before writing, and the sentence is read back by the same kind of small judge the gates use; on a no it is written once more. No canned phrase in any language: the memory speaks in the engine's voice or it does not speak. Measured 3/9 → 9/9 across four languages.
The store's own vocabulary answers the question's. Asked which machine is the "priciest", every seat went to prose about value — the documents write LIST PRICE. The engine is shown the field names the corpus repeats and asked which one the question reaches for, so a bridge can only land on vocabulary that provably exists in the store, and it is asked only when the question touches no field at all. The finding then steers the writer's WORDS while the facts block stays byte for byte what it was — putting a synonym into the evidence would assert a synonymy the store cannot attest, inside the one channel that must stay attested.
Naming is a property of what was asked. Retrieval's query carries the previous turn's subject so a pointer-shaped follow-up stays on topic, and names were read off that query: in a corpus of siblings a question naming nobody came back "naming" eight of twelve documents, the comparison layout fired for eight sources, and it overwrote the corpus-wide reading that had just been laid out correctly. The ride still steers retrieval; it no longer confers namehood.
A line may hold several records. Ingested line by line, a specification shows the record channel three fields; ingested by the bulk path — how every benchmark and every customer load runs — the three arrive glued into one window and a partition at the first colon saw one. How a document was chunked is not supposed to change what the memory can read.
A source that contradicts itself is read as a contradiction. One value spoken, one hidden, and the stamp attesting both is what the gate exists to prevent. Scoped by what the field corpus taught: a repeated head is usually a list and sometimes a zoom, so three values under one head is an enumeration, one value carried inside another is the same length seen closer up, and what remains is a head stated twice with two values that exclude each other.

[0.3.2] — 2026-09-07¶

Two identities, one relation: the release where the comparison reading grew up. Measured on a 73-question field set (40 factual, 15 comparisons, 10 traps, 8 frontier), three runs, medians: comparisons 8/15 → 13/15, factual 37/40 → 38/40, traps 10/10 throughout. NIST 11/13 and EN 17/17 unchanged; 130 invariants.

Fixed¶

In a comparison, two sources saying the same thing say it twice. Sibling documents share a template, so two items of equal value write the same record line word for word; the assembly deduped by TEXT and dropped the second, leaving one value where the question asked about two — the verdict row could never be written, and the case is precisely the one comparisons are asked about most. Identity is per (line, source), the assembly-layer twin of the store's own rule.
Two inflections of one short root are kin. A comparison asking about a "süre" could not reach a record headed "SÜRESİ": four letters of shared root, a different ending on each, and neither relation admitted it — so the question never reached the line that answers it, and the record rider's "did the question ask about this field" ranking was blind in every short-rooted language. Kinship now means a shared opening of at least three letters with each remainder within TAIL, and it is spent on the retrieval side only: the gates keep same_stem, so kinship widens what can be FOUND and nothing about what may be SAID.

Added¶

The comparison verdict is written into the evidence: two named sources answering the same field head yield one system-written row — head, each source's value, joined by = when their digit sets agree and ≠ when they differ. The engine reads a verdict instead of building one, and every reader is taught the notation.
benchmarks/conversation_eval.py: the multi-run referee — a fresh store per run, per-category medians and the FLIP set, AND-golds for multi-part questions, and a frontier category. Sorting-layer changes are not judged without it.

[0.3.1] — 2026-09-06¶

The audit release: a day of field dialogue, a corpus-wide format audit, and a head-to-head benchmark against LangChain, LlamaIndex and Mem0 — with every finding, ours included, fixed architecturally or filed openly. Published numbers re-measured unchanged after every batch (NIST 11/13, EN 17/17; 124 invariants, W27-W42).

Fixed¶

One-row Word tables are fact boxes, and fact boxes are prose. The docx reader dropped single-row grids whole (no header row to read), and every duration/seats/audience box of a sibling-template corpus lived in one; cells now enter the evidence as "LABEL: value." lines, joining the record channel, and an unpunctuated Word paragraph closes with its full stop so headings stop gluing into mega-lines. Body coverage audited to 100% across the corpus.
The same sentence in two documents is two attestations. The duplicate guard keyed on text alone, silencing every sibling that shares a template line — cross-document comparisons refused forever.
Provenance notation belongs to the system. Generated candidates shed anything stamp-shaped; the mark names the line the answer actually rests on; the history carries unstamped text; a turn that says nothing carries no stamp.
An answer's substance cannot be borrowed from the question — one rule at both doors (read-back and informed refusal), and a claim that names its source is judged by that source's lines alone.
An echo cannot turn a question into its own assertion. On an ASK turn the chat echo draws on prior turns only; the trap-set fabrication ("yes, there is a certificate") is gone.
The prior subject rides retrieval as a challenger, not a preemption — restoring a benchmark answer to its honest, attested path.

Added¶

The comparison reading: a question naming two or more sources lays them side by side — per-source seats, record rows riding along, the named-source jury holding each claim to the source it names. A source is named by a pointer or by its bigram; family letters call nobody.
inflect.kin: retrieval-only kinship for short-rooted languages (four-letter roots and their suffixed forms), spent where surfacing a real line is the worst it can do; the gates keep same_stem.
An expansion is judged by the words it ADDS — the keep filter no longer discards a record line's honest bridge on the corpus-common words it shares with every line.
In a multi-document store, a same-region twin steps aside so a document's second seat reaches its other regions.

[0.3.0] — 2026-09-05¶

The consultation release. One evening of field dialogue against a live customer bot — a RAG competitor on the other screen — surfaced every gap in turn, and every fix below is architectural: no keyword, no language rule, no corpus-specific line anywhere. The published numbers were re-measured unchanged after every change batch (NIST 11/13, EN 17/17; 110 unit invariants, W14–W26).

Added¶

The consultation surface. respond(msg, teach=False): a statement is CONTEXT (routes to the chat voice; its extracted terms accumulate in the consultation's brief), a question searches with the whole consultation riding along, and a delivery request routes straight to the composer, which returns a source-stamped catalogue built from the brief. The bare refusal is reserved for surfaces that have no conversation — when the answering chain comes back empty, the already-gated conversational reply speaks instead.
The echo rule. In the chat reading, repeating what the user themselves said this conversation is not an assertion — a consultant may sound like one. A word the user never spoke still answers to the graph.
Gated streaming. compose(..., on_line=) (and respond(..., on_line=)): each draft line is judged by the composer's gate the moment its newline arrives and handed to the callback while the engine is still writing. A refused line is never seen; a backend that cannot stream degrades to batch by itself.
The operator's knobs. Memory(..., persona=, style=, warmth=, reply_tokens=). The persona is the voice and stops at the document's edge; the style is the document's shape and travels only to the composer; warmth and reply_tokens tune the voice surfaces alone. None of them can reach a classifier or a verifier.
compose(..., topics=) gathers per topic — dedicated seats, dedicated queries.

Changed¶

Latency, halved and then some (measured, same dialogue): a greeting turn 15.9 s → ~6 s, a catalogue's first line on screen 13.4 s → ~5 s. The verifier's per-sentence re-reads now go to the engine side by side where the backend allows; the re-extractor memoises (the gate and the abstention stamp used to read the same sentences twice); on the consultation surface the chat voice and the delivery question ride out beside the router and the loser is discarded.
Per-topic composer queries use the topic alone — appending the brief made every query converge on the same generic winners (measured on a 61-document store).
An ordinal list marker ("1.", "2)") at the head of a draft line is format, not a quantity — the digit gate no longer kills the engine's own section numbering.

Fixed¶

A context statement in a no-teach conversation no longer falls through to the question treatment (it used to end in a refusal wearing the persona's greeting).
A stale census line can no longer leak from a previous turn into the informed refusal.

[0.2.0] — 2026-09-05¶

The multi-document release. Everything below came out of one field trial: a corpus of 62 sibling documents sharing a template — a class no benchmark had covered — worked through question by question, with the published single-document numbers re-measured unchanged after every change (NIST 11/13, EN corpus 17/17).

Added¶

Memory.compose(brief) — long-form drafts from the evidence: the engine organises, the material speaks, and every line is re-read on the way out (invented numbers and unsupported mixtures are dropped, structure stands). Returns the draft with the documents it rests on.
Memory.where(term) — the census: which documents mention a term, with sentence counts as receipts. A count, not a retrieval; no engine, ms.
The source-name channel: a question that names a document gets that document's sentences, weighed by log(S/s) — a name-word every source shares weighs exactly zero, which keeps single-document stores byte-stable.
Datelines: in a multi-document store every evidence line opens with its document's name, so answers can say which programme — and the verifier can confirm it.
Source seat cap: one document cannot monopolise the block when others hold evidence (the region rule, one level up).
The census rides into conversation: listing questions name the documents that actually speak, counted at answer time.
The informed refusal: a turn that declines while the census is full offers the tally — with datelined reasons — gated so it can name and count only what the store attests.
Conversational follow-ups: a subject that resolves to nothing the memory knows points backwards, and the previous turn's subject rides along. No pronoun lists — the signal is resolution failing, in any language.
ask() cannot write memory (teach=False throughout): a question API is not a lesson, however imperative its grammar. Teaching stays on Session.respond, deliberately.

Fixed¶

The abstention stamp is read off the evidence, not asked of a model — a full correct answer was being recorded as a refusal when the re-extractor found no tidy triple in a long list-sentence. One model call fewer per answering turn.
A restated evidence line needs no jury: mutual word-coverage between claim and a single evidence line settles support without the judge — whose verdict on that class also wobbled across identical runs. One-way coverage still goes to the jury; a subset of a line can invert it.
The named document speaks first: admission was right, order was not, and the engine reads the block top-down.
learn_rows aliasing could fuse a repeated cell value with a row's identity and silently drop the very fact it was drawn from; the alias now requires a phrase unique in the whole table, on a row that has no name of its own.
The offline expansion channel is no longer listed as a capability: measured on a real standard, its filter keeps only the queries that copy a line — the ones that buy nothing. The code stays, off unless asked for, with the measurement in Honest limits.

0.1.0 — 2026-08-18¶

First public release. The layer had been working for some time; this release is the work of making it installable, readable and lawful to publish.

Added¶

Memory — one front door. Memory("mind.lmm"), .learn(...), .ask(...), .save(). learn() takes a file path or the text itself and routes on the extension: PDF and Word split into tables (straight to the graph) and prose (to the evidence layer); spreadsheets and CSV are all table; anything else readable as text is text. It is a wrapper — Memory.session is the real Session, and the older API is unchanged.
ask(explain=True) returns an Answer, which is the answer string and additionally carries .abstained, .sources, .subject and .wrote. The abstention flag is the session's own structural stamp, not a phrase list.
Word support (lmm.tables.read_docx / learn_docx), on the same contract as the PDF adapter.
CSV support, through the standard library, so the most common "here is a table" format costs the core install nothing.
LICENSE (Apache 2.0), NOTICE, CONTRIBUTING.md, SECURITY.md, examples/, and CI that runs the tests on Python 3.9–3.13 and verifies that the core installs with no dependencies.
Six tests for the new surface (59 total), none of which needs a model.

Changed¶

The core install has no dependencies. pandas was imported at tables.py's top level, which meant the pure-python layer could not be installed without it. Every optional reader is imported at call time now and reports the exact install line — naming the PyPI distribution, since pip install docx fetches a different, abandoned package.
src-layout. Everything importable moved to src/, so import lmm no longer depends on the working directory and an installed copy cannot be confused with the working tree.
v3 is now lmm.core. The substrate was named after an internal version number. It is the discrete layer — memory, gate, geometry, dynamics, transitivity — and it is now named for what it is. bench/ is benchmarks/.

Removed¶

Third-party and private benchmark material: a device manufacturer's manual, an institution's internal strategy document and an inspection report naming real individuals, together with every derived result file that quoted them. The invented corpora (benchmarks/corpus*.txt) remain — they are the publishable half of the benchmark, written so no answer can leak from a model's training data. Only aggregate scores are published for the rest.
Turkish internal design notes and conversation logs from the published tree.

Known limits¶

Documented in full in the README under "Honest limits". In short: the gate guarantees non-fabrication, not perfect relevance; there is a lexical-retrieval ceiling on spec lines reachable only through very common words; and the engine sometimes appends an explanation to a refusal that the memory contradicts — which is detected and scored against the system, but not prevented.