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Commits
| Author | SHA1 | Message | Date | |
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 JesseMarkowitzandClaude Opus 5
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ef25b0a876 |
Stop re-reading the whole prompt every turn, and let a lost run carry on
M01, the hundred-turn campaign, is the one REQUIRED test still outstanding. Everything here is about it finishing, and being worth believing when it does. No requirement changed, no acceptance test was retired or relaxed, and M11 §P.1's "no performance requirement" still stands: what changed is the cost of a turn, not what a turn contains. An inference server caches a prompt by its prefix. The history window gave up its oldest action every turn, which changed the prompt near the front and threw that cache away, so nearly the whole prompt was reprocessed every turn however little had actually changed. The window now snaps the oldest depth to a block and holds it, stepping every few turns. Measured on real builder output at an 8,192-token budget: 124.0s per turn against 362.4s. The cost is history depth, bounded by TRIM_FRACTION at a quarter of the window, which is the dial between recent history and speed. A run that dies no longer starts again from turn one. m11_long_run checkpoints resume.json after the prologue, after every scheduled step and after every turn, and --resume reattaches to the same campaign. A finished run deletes it, so the file's presence means an unfinished run and starting fresh over one is refused. The model timeout is an option rather than a hard-coded 600s, a turn that overruns is a failed turn instead of an unhandled exception that ends the run with no summary, and a run that has stopped producing turns writes its evidence and stops. Two checks could not fail. M04's planted clue went into an add_fact "detail" key that the event does not define, so it was dropped and fact_still_in_state could never be true; it is now in "value" and proved at turn one, which stops a run measuring nothing for hours. m11_browser degraded silently without a narrator into two failures that read exactly like a product regression, and now requires one, with --no-narrator as an explicit opt-out that marks the run partial. Window discovery speaks Ollama's native API, so against vLLM or llama.cpp's own server the window goes unverified and the budget uncapped -- M11's own failure mode reached by another route. context_window_override lets the operator state what they launched the server with, and is used only where discovery left a hole: a verified window always wins, so a declaration can lower an unknown ceiling into existence and never raise a known one. "verified" still means the server answered, so window_verified in a turn's provenance keeps the meaning M11's report counts on. planning/README.md said the M11 tree was staged rather than committed, in two places; it was committed and signed. Planning package v3.8. Backend 1,376 passed, 17 skipped, 0 failed; frontend 161; lint and build clean. Every M11 harness re-run on this tree: browser 38/0/0, offline 23/0, identity clean, contrast unchanged, recovery 14/0 on a small bundle. M01 itself has not been run. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01E9LiyxBxnMTXV2wRjdyDGB |
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JesseMarkowitzandClaude Opus 5
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fedb7144d0 |
Say where release evidence must be written, and what the crash took
The M11 harness examples wrote to /tmp, which a reboot clears. One 100-turn campaign was lost that way at 97 turns. The examples now write under $HOME, which is also the only place the browser harness works. G.0 records what the run reached, that its evidence is gone, and that M01 must be re-run before acceptance. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015aH3G73fEdh4qTQdZNUwty |
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JesseMarkowitzandClaude Opus 5
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144406cd48 |
M11: what the server will actually read
The release-validation milestone, and the thing it had to settle first was whether any of the earlier evidence meant what it said. M8 measured a deployment enforcing a 4,096-token input window while the application budgeted 16,384. Every request returned 200. What Ollama does with the excess is drop the oldest tokens, and the oldest tokens here are the system block — the narrator's rules and the campaign canon. A hundred-turn certification against that server would have looked perfect and proved nothing, which is why this milestone could not begin with a hundred turns. So the application asks now. Ollama's window is a property of how a model was loaded rather than of the request — sending num_ctx is accepted, ignored, and worse, reloads the model at the server's own default — so the only honest move is to find out and then tell the truth about it. /api/ps reports what a resident model is being served with, /api/show what an unloaded one will load with, both on the same host inference already uses, through the same endpoint policy and the same TLS trust store. A verified window is a ceiling on the budget; an unverified one leaves the budget alone and is recorded as unverified in the turn's own provenance, so an old turn can be asked afterwards whether it was built against a checked window. There is no third behaviour, and in particular no hard-coded 4,096: a number the server did not say would be right on one machine and wrong on the next. The proof that this is doing something is a campaign whose canon sits at the front of the prompt, 120 turns of history, and a 4,096-token window. The canon is still there afterwards and the oldest history is gone. The same campaign built the old way produces a prompt more than twice the window — the defect, reproduced, so the fix is measured against it rather than asserted. Two defects the validation found on its own, and they are the same defect twice: something was true and nobody was told. A manual state correction of four changes with one bad reference applied three, returned 201, and said nothing — while recording the refusal on the audit row nobody reads. It came to light because the identity diagnostic's own fixture was refused that way and the whole run proceeded on a campaign with no scene, which would have read as a model failure. And the narration-length setting moved no number: brief, medium and long each became one English sentence, while the numeric hint the model actually reads was derived from the global reply cap and said the same thing for all three. Both now say what they did. The other two post-M8 findings are closed as well. The tab said AI D&D, which no document had ever claimed it did not; it says Interactive Story now, with the open campaign first, and the name is the owner's decision rather than a find-and-replace to something narrower than the engine. After an Undo the reader could not tell where they had landed; the control row now ends with "Moment 11 · later story ahead", from the server's own answer, in the word the transcript already uses, with none of head, branch or depth anywhere near it. The identity diagnostic exists and the root cause does not. That campaign was destroyed, so no cause can be established — what M11 owes the finding is something that can classify the next occurrence, and a diagnostic that makes only the judgements a program can honestly make: duplicate keys, shared names, protagonist drift, state and context disagreeing. Whether prose misattributed a line is left to a person reading it beside its prompt, because a regex cannot read dialogue and one that pretended to would produce exactly the confident wrong answer this finding is about. Its detectors are proved to fire against a planted second Alice. Two entities may still share a display name. That was checked first, as the finding asked, and left permitted: a mother and a daughter, or a stranger giving a false name, are ordinary fiction, and refusing them to guard against a model mistake would refuse the wrong thing. What was missing was that it happened silently. It is reported now. Evidence, not inference: a hundred accepted turns against a real narrator with genuine process restarts; a real browser against the built SPA; a container with no network at all; a campaign moved into a data directory that never existed. Each was discarded and re-run whenever the product changed under it, and the runs that were thrown away are listed in the report with the reason, along with ten defects in the harnesses themselves — because a harness that has only ever agreed with itself is not evidence, and two of M8's five harness defects were masking real ones. No dependency was added, removed or upgraded. No acceptance test was retired, relaxed or reclassified. M11 is implemented and verified; it is not accepted, and there is no release tag. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Qyn3oRd4D6pi72nKBG725B |
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JesseMarkowitzandClaude Opus 5
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1013c94eb1 |
M10: the seam for media, and no media
The media extension contract asks for a scene snapshot a future image or video provider could be handed: location, who is present, what they hold, what must stay true, and where in the story it sits. Building one was the milestone's obvious first task, and it was the wrong one. That snapshot has existed since M5. `narrative_state["scene"]` holds the summary, the location, the cast and the coordinate it was written at; a validated `set_scene` event writes it, every position snapshots it, and every head move restores it. It survives Undo, Redo, Retry, divergence, Save Point restore and a process restart because it is the authoritative state rather than a copy of it. So there is no scenes table here. A second scene store would have been a second answer to "where is the story now", with its own lineage rules to get wrong — and the lineage rules are the expensive part, which is the argument for reusing the ones that already work rather than against it. The Scene Packet is derived on read, and its identity is computed from the campaign and the position rather than allocated: the same position yields the same id in another process, after a restart, and after the packet is thrown away and rebuilt, with no row to keep in step. That is the part of a future media_assets table that would be expensive to retrofit, so it is fixed now even though the table is not built. One table, then: visual_profiles, the only thing the contract's scene list asks for that nothing already stored. Campaign-scoped and not per-position, because a character does not change appearance when the story forks — a reader who diverged would otherwise lose their cast, and the same descriptors would land in every per-position snapshot, measured at 245 copies of 367 bytes in a 120-turn campaign to say something that never varies. Keyed by the M5 entity key rather than a new identity namespace, and one table for characters, locations and items alike, because a location is an entity with a type and splitting them would reintroduce the genre shape M5 spent a milestone removing. What the packet leaves out is the more interesting half. Not the transcript, and not imported knowledge — none of it, not merely the sources marked hidden. The rule is what the story established at this position, not everything the narrator was told, and drawing it by class is what makes it hold for a secret nobody thought to mark. A hidden Canon source proves it, with a positive control showing the narrator did receive the sentinel the packet does not carry. Once a validated event puts the observer in the room, the observer is in the packet: that is no longer narrator-only knowledge, and a packet that hid it would be hiding the story from itself. The providers are contracts and nothing else. Protocols for image, video, audio, speech and transcription, an empty registry, no adapter, no dependency, no socket, and no media setting to point anywhere — a setting that exists can be pointed at a cloud by mistake. A future provider endpoint must be loopback, stricter than narration's trusted-LAN allowance, because a picture of a scene carries the scene with it. Transcription returns an editable draft with no commit method, so STT structurally cannot bypass the authoritative path. Nothing here can write the story. Not by convention: no module under media/ imports the code that writes state, no media event type exists in the state vocabulary, and every test in the authority suite compares the authoritative document byte for byte either side of a media operation — including one where a provider insists Alice is in a red coat in a corridor, and the campaign goes on disagreeing. One defect, found by the milestone's own tests. M10 first added a migration creating an index that create_all already builds from the column, so an upgraded database ended up with two indexes and a fresh install with one. Comparing the two schemas is what caught it; neither database examined alone would have. The migration is gone rather than renamed, and the right number of migrations for a new table whose indexes are declared on its columns is zero. Backend 1,191 passed / 14 skipped / 0 failed, 89 of them M10's. Frontend 145 passed. Lint, production build and Docker build clean. No frontend file changed: M10 adds no reader-facing surface, and ordinary play — turns, state, memory, knowledge, Undo, Redo, Retry, Save Point restore, restart — runs with no media configuration, no warning, no connection attempt and no media row written. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Qyn3oRd4D6pi72nKBG725B |
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JesseMarkowitzandClaude Opus 5
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44edece67e |
M9: a campaign you can actually get back
A campaign could already be exported and imported. What could not survive the trip was everything that explains it: the state events behind the authoritative document, the prompt each turn was actually given, the passages it was shown, the summaries that carry long-story continuity, and which take belonged to which turn. An imported campaign could be read and could no longer say why it was what it was — and a manual correction, the one state change no narration explains, was indistinguishable from something the story had established. The bundle is now `ai-dnd-adventure-v3`, and the version is the design rather than a side effect. Everything added here could have been another optional key, the way persona, Save Points, narrative state and imported knowledge each were. That mechanism stops working at exactly this addition: a v2 file with no prompt provenance is ambiguous between "written before M9" and "written by M9 from a campaign that has none", and those are different facts about a campaign. A version number is how a recovery file states what it was capable of recording. v1 and v2 still import, and every seam from pre-active-head onward is tested for the rule that an older file is never reinterpreted under a newer assumption. Two categories became three. "Chosen travels, derived is recomputed" was enough until stored prompts had to be decided: they are derived, and they must travel anyway. The test that separates evidence from cache is not "could this be recomputed" but "would a recomputation answer the same question" — a rebuilt search index answers the same question, a rebuilt prompt says what the turn would be told *now*, which is the opposite of what the inspector is for. Also here: a real SQLite backup, through the online backup API rather than a file copy, taken while the application is running and verified before it is kept; story cards settled as compatibility-only legacy data and taken out of the narrator's prompt, because they were the untracked path around knowledge authority that IMPORTED-KNOWLEDGE-DESIGN §73 already forbade; and no schema change at all, proved against a database M8's own code wrote. Three defects, found by running the milestone's own tests rather than by reading them. Deleting a campaign leaked its FTS index rows, and SQLite then handed the freed ids to the next source imported into any campaign, which failed with an integrity error that Reindex could not repair — both ends are closed, and a database already carrying the damage now repairs itself. An imported node with no state snapshot was being stamped with the campaign's head state, so an Undo to turn 2 showed what the story knew at turn 20. And the snapshot relink did not persist at all, because it mutated a dict in place on a column SQLAlchemy tracks by assignment: it looked correct in memory and wrote the wrong ids to disk. Carrying per-turn prompts looked like it would halve the length of campaign that can be restored. Measured — and after compressing them inside the file — everything M9 added costs 12% of it: the import ceiling moves from about 318 turns to about 279, against a 100-turn certification target. The dominant cost is not M9's at all. The per-position narrative state document is 74% of a bundle, and v2 already carried it. Backend 1,102 passed / 14 skipped / 0 failed. Frontend 145 passed. Lint, production build and Docker build clean. Verified across two server processes with two data directories, and in a real browser against a real narrator. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Qyn3oRd4D6pi72nKBG725B |
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JesseMarkowitzandClaude Opus 5
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1ce9972760 |
M8: the browser becomes the storyteller
The interface was AI-DnD's with this product's features bolted into it. The
navigation read Home · Adventures · Scenarios · Settings · AI Chat; starting a
story meant first picking a *world*, and making a world meant a JSON stat-schema
form, a story-card table and an art picker. The play screen had a Branches tab.
The input had three modes. Sixteen of the sixteen controls on a two-turn story
had no accessible name — they were single glyphs with a tooltip.
All of that was measured in a real browser before anything was changed, and the
measurements are in planning/reports/M8-IMPLEMENTATION-REPORT.md §C. Almost
nothing underneath was wrong: the play loop, the history controls, the takes,
the Save Points, the state correction and the knowledge library all worked. What
was wrong was what a reader was asked to understand in order to use them.
So the shape now is one entry point and one screen:
Campaigns -> Campaign -> Story
State · Knowledge · Context · Save Points · Settings
Everything that is not the story lives in a panel that starts closed. The
top navigation bar is hidden on the story screen entirely, because on that one
screen the story is the interface.
Play is one natural-language field. An action and a piece of quoted dialogue are
both just what the reader wrote, and B01/B02 confirmed against a real narrator
that the model reads the quotes without being told which kind of turn it is.
What survives from the old Story mode is a Story direction toggle, which is not
a fourth mode: it changes who is being spoken to, not what kind of action is
taken, and the box is visibly marked while it is on.
Branch, fork, node, merge and head appear nowhere a reader can see them. The
branch panel and the tree overlay are gone from the browser. The mechanism is
untouched — takes, divergence, retained futures and Save Points all still work,
and their endpoints are still tested. This is a decision about what a reader is
asked to understand, not a reduction of what the product can do.
The two defects worth the space:
A player action is stored with AI Dungeon's "> You " prefix. That was right when
the Do mode asked for a bare verb phrase. With one field the spec tells the
reader to write "I enter the tavern", and the result was "> You I enter the
tavern." — in the transcript, in the replayed history, and therefore in the
narration, where a small model imitates it and writes "You I thank her". M8's
own design surfaced it, so M8 fixed it: the prefix is added only when the reader
has not already written a subject. The ">" marker, which is what actually
identifies a player turn in the prompt, is unchanged in every case.
And a stale `.input-bar { display: flex }` in play.css overrode the new
composer, because that sheet is imported after the new one. The direction row
and the input row laid out side by side and the box was unusably narrow. Found
by opening the product in a browser, not by reading the CSS — which is the
argument for having done that first.
Failures now have the taxonomy the spec asked for rather than one toast: model,
generation, state, knowledge, server, each with the thing to do about it. A
failed turn leaves the reader's words in the box and says so. The classification
reads backend strings, so it is a fallback ladder rather than a lookup — an
unrecognised message still classifies, still shows the server's own words and
still offers Retry.
`Settings.model` could be empty with nothing saying so until the first turn
failed with a provider error. The header now reports Ollama in five states, and
an unconfigured or missing model offers the models actually installed on the
endpoint, from the connection test that already knew them. Nothing is chosen
automatically: an endpoint's first model may be an embedding model, which cannot
narrate at all.
Narrator prose is rendered as safe Markdown — headings, emphasis, lists,
blockquotes, code. The safety is structural rather than filtered: every node is
a React element built from parsed text, and there is no dangerouslySetInnerHTML
in the file. A sanitizer is not needed to make markup safe if markup is never
produced from input. Link schemes are checked with the URL parser rather than a
pattern, because the bypasses are all in the parsing. A remote image is a
placeholder naming the blocked address; the knowledge and context panels
deliberately do not use this renderer at all, because they exist to show a
reader exactly what is in their file.
Backend, and only what the browser could not otherwise reach:
AdventureCreate.opening a start action could only come from a Scenario, so
every campaign made in the new setup flow opened on
a blank page. Same node, same code path.
canon_rules campaign_canon has been the highest authority in a
campaign since M5, read by the prompt builder and
the state validator, and had no API at all — a
fixture had to write it with SQL.
a 401 and a 429 message the last user-facing text describing a hosted
deployment. One told the reader to check an API key
that has not existed since M2.
No schema change and no migration: proved by building a database with a server
running the M7 commit's own code and opening it with this one.
The project had no frontend tests. It has 132 now, across ten files, running
in about six seconds — the enabled state of every history control, the take
selector, the confirmations, the panels, the five model states, the failure
taxonomy, the focus trap, accessibility, and that the reserved dictation control
never touches the microphone. Writing them found a real defect: the focus trap
filtered candidates with offsetParent, which is null inside the fixed-position
ancestor the dialog has and which jsdom never computes — it would have behaved
differently in the tests from the browser.
They do not replace the real-browser runs, and both kinds of evidence are in the
report. The browser suites drive the production build served by the real backend
with a real local narrator, including a genuine process restart.
A verification pass over all of it then found three more, each by driving the
product rather than reading it:
Stepping between alternate takes did nothing. The pager asked whether a take
lived on another line by comparing `target.branch_id !== action.branch_id`, and
`ActionOut` has never carried `branch_id` — so the comparison was permanently
`number !== undefined`, always true, and every step took the branch-switch path.
For two takes of an ordinary retry, which share a line until one is written
below, that meant switching to the line already being read: the same window came
back and nothing moved. D07 is a required v1 acceptance test. The fix needed no
new field — the variants list already carries every attempt's branch and marks
the live one.
The first regression test for that passed against the broken code, because its
fixture gave the action a `branch_id` the real payload never sends. That is the
exact failure M7's review was about, so the fixture was corrected, the tests were
re-run against the reverted code and failed for the right reason, and the
fixture now carries a docstring saying why the field must never come back.
And the knowledge panel pointed readers at an "embedding model" while the
setting is called "Model for meaning-based search" — a reader sent looking for a
field that does not exist by that name.
Campaign canon was measured rather than assumed. Editing it after play is a
configuration change: every turn already played keeps the canon it was actually
given, in its own context snapshot, and the accepted story, the state document
and the state audit log are byte-identical across an edit. It is not routed
through M5's state audit, because canon is not narrative state and doing so
would create the second representation the spec forbids. What the editor does
now is say so, once a campaign has moments.
`BROWSER-UX-SPEC.md` §38 asked for a "Show Hidden Story State" toggle. There is
no hidden story state — a secret lives in a narrator-only knowledge source and
never enters the state document. The section is rewritten to require what it
actually meant: ordinary surfaces must not carry narrator-only information,
advanced inspection must withhold it by default behind an explicit warned
choice, and no second store may be invented to give a toggle something to
reveal. The protection is stricter than before, not weaker.
Closeout. An independent review returned M8 IMPLEMENTATION: PASS subject to
evidence and documentation cleanup, and this commit carries that cleanup:
The report named two frontend bundles as the artifact behind its acceptance
evidence. The saved run logs settle it. index-Ii-lARp9.js, built at 18:53:02
from this tree, is the one final frozen artifact behind all 157 browser checks;
index-C6E5Uvtu.js is superseded — it predates the D09 fix and its acceptance
suite ended 54/55 on exactly that defect. No tracked file under backend/app or
frontend/src has a modification time after the freeze, so the whole final
campaign describes one build. §P sets the two side by side.
Finding 14 — the app budgets 16,384 prompt tokens while an Ollama that sees no
VRAM enforces 4,096 — is resolved operationally, with no application change.
The OpenAI-compatible endpoint this app speaks accepts num_ctx and ignores it,
and reloads the model at its own default, so a native call cannot prime it
either. A model derived with POST /api/create carries the parameter, is honoured
through the app's own OpenAI-compatible path, and appears in /v1/models — which
is the listing the Settings model picker already reads. Measured end to end.
The procedure is in DEVELOPMENT.md; nothing in the repository depends on any
particular derived model existing. Adding provider code to work around this was
declined deliberately: it would mean either a second native request path,
against ADR 011, or a parameter the endpoint provably ignores.
The §38 rewrite is ratified as a requirement clarification aligned with the
implemented architecture, and the spec gains the clause finding 3 was really
about: withheld material must be absent from the rendered DOM, not merely
collapsed in it.
The report's §U carries the M9 handoff — what a portable campaign has to include,
whether historical context snapshots belong in the bundle, what happens to
inherited story cards, and that a restored campaign may meet a different context
window than the one that wrote it. None of it is implemented here.
Final: backend 950 passed / 14 skipped; frontend 132 passed; lint, production
build and Docker build clean; 157 browser checks across six suites, zero
failures. M8 is implemented, verified, reviewed and accepted (2026-09-06).
M9 has not been started.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_017HdaXiFbscatQaLS7dJk6b
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JesseMarkowitzandClaude Opus 5
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480414efe0 |
M7: a first-class imported knowledge library
A campaign can import local .txt and .md files as Canon, Reference or Inspiration, and the class is load-bearing rather than a label: it decides the words a passage is framed with in the prompt, the weight it carries when passages are ranked, and which budget it competes in when the context is tight. This is a separate subsystem, which is the Phase 0B decision (IMPORTED-KNOWLEDGE-DESIGN.md §73). Story Cards do not carry classification, provenance, content identity, chunking, an index or a lifecycle, and they were not promoted into something that does. Nothing here reads or writes one. The subsystem, in backend/app/knowledge/: classes the three classes, their weights, and the prompt framing chunking deterministic, heading-aware, 60-800 tokens, no overlap fts SQLite FTS5 with porter stemming; scoped and bounded in SQL importer validate, hash, store, chunk, index — in one transaction embeddings local Ollama vectors through the shared provider retrieval query construction, hybrid merge, rerank inject the budgeted cut and the rendered prompt sections Relevance admission is a separate stage from ranking, and that separation is the milestone's most expensive lesson. An independent review found the first implementation deciding relevance with a floor expressed as a share of the best candidate — which the best clears by construction — so a passage was admitted on every turn regardless of the scene. A query about tide tables and container tonnage retrieved all five sources of a fantasy campaign, narrator-only hidden Canon among them. So the pipeline is now: candidate generation -> admission -> ranking -> class weighting -> budget Admission reads raw, candidate-set-independent signals: the cosine the model returned, and how many distinct meaningful query terms a passage contains. Ranking reads normalized ones, because bm25 has no fixed range and cosine's zero is not zero. Normalization decides order among things that matched; it can never decide whether anything matched. Authority is applied after admission, so a class orders what matched and never rescues what did not. Retrieval may therefore return nothing, and on a scene unrelated to the library it does. The other decisions that each replaced an obvious wrong one: - The class multiplies relevance rather than adding to it. An additive bonus satisfies "Canon outranks Reference" and makes "do not include irrelevant Canon" impossible, because a large enough constant wins on its own. - The semantic floor is measured, not guessed: 113 production-path pairs against nomic-embed-text put targeted matches at 0.55-0.85 and off-topic pairs at 0.36-0.56, and 0.58 sits between them. Because it is a property of that model and not of cosine similarity, it is keyed to the model rather than applied to whatever is configured: an embedding model with no measured calibration in this build does not borrow the number. Semantic admission is skipped, the campaign retrieves lexically, and the reason is stated in the knowledge status and in the turn's provenance. Degrading to lexical keeps the library usable; lending the threshold to an unmeasured model is how the admitted-everything defect would return. - One lexical term is not evidence. Two distinct meaningful terms, or one that is neither a standing campaign entity nor a negligible share of the query. The stop list grew from 42 words to 261, all function words — no subject matter, because a stop list that removes subject matter stops finding "The Silver Key". - Lexical retrieval is a production path, not a fallback. It finds the proper nouns and invented terms a setting bible is made of, and the library is fully usable with no embedding model configured. Safety is structural rather than filtered. Imported text reaches the prompt whole, inside a section that says what it is, under a rule stating the authority order in words and refusing every instruction inside it. No endpoint accepts a filesystem path, so H08 has no mechanism to escape from. Nothing renders imported content as HTML, so a script tag is five visible characters and a remote image is never fetched. Import, chunking, indexing, retrieval and a turn open no socket at all; only embeddings do, through the endpoint allowlist the memory bank already uses. Provenance is the rendered text, not a foreign key: deleting a source cannot turn a historical turn's evidence into dangling ids. Schema: knowledge_sources, knowledge_chunks, knowledge_embeddings, and an FTS5 virtual table attached to knowledge_chunks as a DDL hook so it is created and dropped with the table it indexes. Migration 92. A pre-M7 database opens unchanged and needs no sources to play. Bundle: the source content and the reader's judgements about it travel; the passages, index rows and vectors are rebuilt on import, so a restored campaign is searchable immediately without a reindex step. One runtime dependency: python-multipart, Starlette's multipart parser. It is what makes the upload surface possible, and the upload surface is why no pathname is ever accepted. The test doubles were the reason the defect shipped, so they were corrected too. The retrieval stub scored unrelated text at 0.06-0.20 where the real model scores it at 0.43-0.44, and its docstring said it had deliberately removed the constant component that "would put a similarity floor under every pair" — which is exactly the property real models have. The stub now has that floor, one test fails if it is ever removed, and another reproduces the superseded rule and asserts it is still fooled by the same fixture. Run against the pre-corrective implementation, the new suite fails 13 of 18. Tests: 939 passed, 14 skipped (836/7 at M6). 110 new across seven files, one of which mocks nothing between itself and Ollama and re-measures the similarity separation on every run. 43/43 checks in a real Firefox, reproduced. Docker build clean. Four other defects found by review or by the browser run were fixed here rather than carried: an unreachable relevance constant that appeared to enforce something and did not; acceptance tests using the wrong fixture files, so G07's trap was never exercised; a bidirectional override surviving into displayed filenames; and, from the implementation pass, the Insights panel showing M5's two state sections as raw keys and the source inspector refetching on every keystroke. M7 was independently reviewed, which returned PASS WITH CORRECTIVE WORK REQUIRED. Both blocking findings are closed, and closeout resolved the embedding-model calibration boundary the corrective pass had left as debt. planning/reports/M7-IMPLEMENTATION-REPORT.md carries the review, the corrective closeout and the closeout verification in sequence, none overwriting another. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_017HdaXiFbscatQaLS7dJk6b |
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JesseMarkowitzandClaude Opus 5
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b7005e6fdd |
M5: genre-neutral authoritative narrative state, with review corrections
Replaces AI-DnD's RPG relative-delta world state with the genre-neutral typed
narrative state of ADR 010: explicit, absolute, allowlisted events proposed by
the model, validated by the application, applied to one authoritative document,
and snapshotted per position so restore stays a row read.
This commit includes the corrective pass that followed the independent review
in planning/reports/M5-IMPLEMENTATION-REPORT.md. The invariant it exists to
hold is:
visible active transcript position == stored head == authoritative state
Narrator editing (D10, STORY-BRANCH-SEMANTICS §§14-15)
A narrator edit no longer rewrites a row. It returns to the state before the
turn, takes the reader's exact text as the accepted narration, re-derives the
state that text implies, and becomes a new active continuation — while the
original narration keeps its words, its live flag and its whole future as
retained history. At the tip the correction is another take; with story below
it, it forks. No new history machinery: this is the existing fork/take/head
path with the reader's text in place of a generated reply. The §14A refusal
is therefore gone for narrator turns, and remains only for player input.
Pre-M5 positions
Migration 88 backfills the empty narrative document onto every action written
before M5, and a missing snapshot now restores the empty document instead of
leaving the previous position's state standing. Restoring to an old Save
Point no longer leaves a later position's entities and facts on screen.
Narrator context
Replayed history carries prose only; the machine-readable block is no longer
reconstructed into past turns, where it contradicted the authoritative state
in the same prompt. A fact withdrawn by a manual correction is now named as
no longer true, with the reader's reason, rather than silently dropped.
Also
- state_changes joins the action-list bulk read, removing one query per row.
- Extraction takes only the application's own protocol payload: an ordinary
```json or ```python block in a story survives, and a mangled proposal
still does not reach the reader.
Planning: ADR 013 records the authoritative document shape; §§14-15/14A, D10,
C04 and BUILD-MILESTONES are updated to describe what exists. Debt is recorded
against M8 (scenario editor UX) and M9 (export of the audit trail).
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01PWU4gTfLYY6Qq9U7aa9Qw2
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JesseMarkowitzandClaude Opus 5
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62a997f364 |
M4: close out Save Points, with browser verification
Closes M4. The review's three findings are fixed, the durability rule the specification always implied is now enforced, and M3's and M4's browser behaviour has been verified in a real browser for the first time. B-1 -- the Save Point list was an N+1 that loaded whole Action rows, narration included, to answer "does a row exist here". It is now one bulk two-column coordinate query plus one lineage: 53 SELECTs for 25 Save Points became 5, and the count no longer grows with the list. The clause is an OR of exact (branch, depth) pairs rather than two IN lists, because the cross product would report a Save Point resolved on the strength of another one's depth existing on this one's branch. A test builds exactly that trap. B-2 -- reclassified during closeout from "missing warning" to a behaviour defect, and fixed as one. STORY-BRANCH-SEMANTICS §19 says a named checkpoint remains until explicitly deleted, and §28 already required future cleanup to retain checkpoint-referenced paths; a cascade that silently removed Save Points with a branch violated both, and a warning would only have documented the violation. A branch a Save Point names can no longer be deleted. The request is refused with the offending Save Points named, the user deletes them explicitly -- which deletes no story -- and the branch then goes. The scope is the subtree, because deleting a branch takes its descendants. Both delete controls disable and explain. Recorded as a new §19.1; models.py, TECHNICAL-DESIGN §8.8 and DATA-MODEL §8 had all recorded the cascade as the rule and now record the refusal. An earlier pass in this same closeout had kept the cascade and added a warning. That was the wrong fix and its tests were replaced rather than left standing, since they pinned the defect. B-3 -- the D11/L03 automation never left one process, so it could not distinguish durable state from a live Python object. It now spawns real server processes, kills the first, and reads the campaign back with the second. C-5 -- creating a Save Point takes the campaign's turn lock. "Save where I am" has to name one committed position, and the head is what a turn in flight is about to move. Rename and Delete deliberately do not take it. The architecture is untouched: a Save Point is still name + note + (branch, depth), and restore is still coordinate -> head.move_to_node -> head.move_to -> attempts.restore_state. No second restore path, no state copied into a checkpoint, no fork on restore. Browser verification -- the first in this project, and it covers both milestones. Firefox 154.0.1 through geckodriver over the W3C WebDriver protocol, driving the rendered DOM: 47/47 checks, twice, on independent databases, no console errors. M3's Undo/Redo enable states, transcript movement, Retry and the take pager, divergence retiring Redo; M4's whole Save Point lifecycle, both confirmations, and the new branch-delete refusal including its recovery. No dependency was added: the WebDriver client is stdlib HTTP. No application defect was found by the browser. Four failures occurred, all in the harness -- a wrong SPA route, a wait comparing transcript length when the empty-story placeholder is longer than the first turn, a fixture deleting the branch it was reading, and a reload assertion that sampled once instead of waiting. The last was checked against the app before being called a harness bug. Tests: 698 backend pass (was 680), 60 M4, 94 M3 history, 66 export/ migrations, 93 security/local-only. Frontend lint and build clean, Docker build clean, loopback binding unchanged. No assertion weakened, no skip added. Planning: STORY-BRANCH-SEMANTICS §19.1 is the only behavioural change and it strengthens §19. V1-ACCEPTANCE-TESTS records D11-D14, I04, L03 and the E-series, keeping automated, live-runtime and browser evidence distinct, and weakens no pass condition. DATA-MODEL records the coordinate with the retry measurement that settles it. BROWSER-UX-SPEC rules for Moment over Turn. BUILD-MILESTONES marks M4 COMPLETE, closes M3's browser condition, and lists what M5 inherits. VERSION adds v2.6. No new ADR: ADR 005 already decides that history is preserved rather than overwritten, and §19.1 is that decision applied to checkpoint-referenced history. M4 is closed. M5 may now be briefed; it has not been started. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PWU4gTfLYY6Qq9U7aa9Qw2 |
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JesseMarkowitzandClaude Opus 5
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e08d49c3eb |
M4: add durable named Save Points
A Save Point is a name for a story position, and restoring one is head movement. That is the whole architecture, and it is what ADR 012 and BUILD-MILESTONES' note on M4 asked for: M3 made the head a stored (branch, depth) and made arriving at one a row lookup plus a state restore, so a Save Point needs no restore machinery of its own. What the user gets: - Name the moment they are reading, keep playing, restart the app, and come back to it. Restoring moves the story back and deletes nothing: the later turns stay, Redo still walks forward into them, and writing something different is what starts a new line while the old one is kept. - Rename, delete, and a list, in a Save Points panel beside the branch panel, with a Save Point button next to Undo and Redo. Both confirmations say what is *not* destroyed, because that is the part the screen cannot show. - Save Points survive export and import. What was deliberately not built: - No second restore path. `head.move_to_node` is the only new movement: its depth half is M3's `head.move_to` unchanged, and its branch half is the single assignment `switch_branch` already makes. No head field is written in the checkpoint router, nothing reconstructs state, nothing prunes a memory, nothing copies or deletes a turn, and restore never forks — the first write below the restored head does, through `fork_if_behind_head`. - No automatic cleanup. A Save Point behind the head, or naming a line the story left, is doing its job (STORY-BRANCH-SEMANTICS §19). The one removal is a cascade: deleting a branch takes its Save Points, as it takes its memories, because the story they named went with it. - No new ADR. ADR 012 already decides the architecture, and a table is not a decision. The one call the planning package did not already make: restore moves the branch half of the head only when the coordinate is off the path being read. Doing it unconditionally would quietly hand back an abandoned continuation whenever a Save Point in a shared prefix was restored; never doing it would make a Save Point on a departed line unrestorable, which contradicts §19. TECHNICAL-DESIGN §8.8 records it. Schema: a `checkpoints` table holding a name, an optional note and a (branch, depth) coordinate — no copy of any story. `create_all` builds it as it did `memories` and `branches`; migration 80 adds the index. No backfill, because nobody had named a position before M4. The coordinate is deliberately not an action id: one coordinate holds every attempt at a turn and exactly one is live, so a coordinate follows a retry where a row id would pin a take the story no longer tells. Tests: 680 pass (638 before). 42 new in tests/test_save_points.py covering D11-D14, I04, L03, E-series lineage and memory isolation after restore and divergence, the edge cases, and an M3-database migration. One pre-existing fixture in test_tree_migration.py needed `checkpoints` added to its drop list — SQLite refuses to drop a table another table references. Not verified: the browser. No session has had a usable one, so the Save Point panel's DOM behaviour is unobserved — as M3's Redo control still is. The twenty-step sequence was driven over HTTP against a live server with a real process restart instead, and all seventeen checks pass. M4 is implemented, not accepted: no review has been written. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PWU4gTfLYY6Qq9U7aa9Qw2 |
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JesseMarkowitzandClaude Opus 5
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3c8e91f644 |
Docs: correct post-M3 status and Ollama configuration
Three stale claims found in active documentation after the post-M3 consolidation: - BUILD-MILESTONES.md still opened "M1 and M2 complete; M3 next", which contradicted its own M3 "Status: COMPLETE" block, planning/README.md and VERSION.md. It now states M1, M2 and M3 complete and accepted, M4 next. - DEVELOPMENT.md described the settings row as "endpoint, model and (unused) API key" and sent "api_key":"" in its curl example. M2 removed the field; schemas.SettingsUpdate has no api_key. The prose and the example now match the real request shape. No application code was changed. - README.md listed LM Studio as a supported local endpoint. ADR 002 and ADR 011 make Ollama the only v1 backend; LM Studio is a rejected alternative there. The row is removed and the surrounding wording now says Ollama is the supported backend, same-host is the default, trusted-LAN Ollama is supported, public/cloud is prohibited, and the OpenAI-compatible adapter is an implementation detail rather than a support promise. The claude_shim section stays, relabelled "(development only)". Documentation only; no code, schema or test changes. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PWU4gTfLYY6Qq9U7aa9Qw2 |
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JesseMarkowitzandClaude Opus 5
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d27ee34901 |
Docs: consolidate active planning and archive historical material
The planning package had grown to where a new agent could not tell what was authoritative. Phase 0 execution prompts sat beside the specification; four completed milestone reports sat beside the current one; and upstream AI-DnD's own `plan/` build log and `docs/` project site still described a hosted, scripted, multi-user product with accounts — every screenshot in it showed a Scripts tab and a Sign up button, none of which has existed since M2. `planning/archive/` now holds the history and says so in its own README: `phase0/` for the research that chose AI-DnD, `milestone-reports/` for M1 and M2, `decisions/` for ADR 008, the Phase-0-before-build gate Phase 0 satisfied. `planning/reports/` holds only the current milestone's report, because that is the one M4 planning has to read; it moves to the archive when M4's replaces it. Deleted rather than archived: the Phase 0B execution prompts and the handoff/status/summary documents, the Phase 0A discovery and triage reports, upstream's `plan/` and `docs/` trees, and `frontend/README.md`, which was Vite's template boilerplate. All of it is in Git history, and the two recommendation reports carry every conclusion the deleted research reached. Archived documents are kept verbatim. Paths written inside them point at where those files were when the document was written, which is the point: an evidence record that has been quietly edited is no longer evidence. Active documentation is corrected where it pointed at the removed trees or described removed capability as present. `DEVELOPMENT.md`'s "things M1 did not touch" list had gone stale at M2 and claimed QuickJS scripting was still tested; its test count was 604 against an actual 638. `README.md` loses the upstream CI badge, which reported upstream's pipeline rather than this fork's, and a reference to `backend/app/worldstate/engine.py`, a file that does not exist. `planning/README.md` is rewritten as the documentation index. New: `planning/PROJECT-SOURCES.md` and `planning/project-sources.txt`, the manifest of what belongs in the ChatGPT project's Sources. Source comments referring to the deleted trees are reworded; no behaviour changes. 638 backend tests pass, frontend lints and builds, and a reference scan over all 48 tracked Markdown files reports no unresolved path in active documentation. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01NCbwH7yLGKsj1rhXXzKSCu |
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JesseMarkowitz
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8c65ae99de |
M2: cut the hosted product away from the local one
94 files, +1,395 -6,578. Three files are new; twenty-four are gone. The milestone is subtraction, and what is left is the single-user local storyteller the specification describes. Removed in full: campaign scripting and its QuickJS sandbox; multi-user accounts, guest sessions, login, registration and the shared demo key; the visitor-analytics tables, dashboard and page beacon; the access log of sign-ins, addresses and devices; per-IP and per-user rate limiting and quotas; Render deployment config; Postgres and psycopg; cloud inference providers, the API-key field and the key encryption that existed to store it; session-cookie signing. None of it was hidden behind a flag — the routes are gone and answer 404. Two things were kept that the brief allowed keeping. The `users` table and its foreign keys stay as an internal ownership detail, because rewriting them out means a migration across most of the schema to delete a column that costs nothing; nothing creates a second user and no request carries an identity. Five inert tables and four inert columns stay for the same reason, so an M1 campaign database opens unchanged. The one addition is app/endpoints.py, which decides where a story may be sent. Loopback, RFC1918, link-local, unique-local and CGNAT — an explicit allowlist of networks, not a guess at what `ipaddress` means by "private", which calls the documentation ranges private and IPv6 loopback reserved. Every address a hostname resolves to must be in it, so a split answer does not squeak through, and the rule runs both when the endpoint is saved and before every outbound request, because a name that resolved to the LAN this morning can resolve elsewhere this afternoon. Known cloud hosts are named in the refusal so the error says why rather than looking like broken DNS. TLS is never traded against it: M1's shared trust context is intact on all four clients and there is no way to skip verification. The hardcoded 120-second model timeout is now a setting. That was not theoretical — on this GPU-less four-core host a cold load of qwen2.5:3b-instruct took 648.9 seconds to produce the first turn, while turns 2 to 5 of the same campaign took 3.6 to 13.1. Connect stays short at 10s so a wrong address still fails fast; the read timeout defaults to 300s and is bounded at 3600, because "wait longer" must stay a number. Two defects found while testing and fixed here. An unknown /api path fell through the SPA catch-all and came back as HTML with status 200, so a client asking for JSON parsed a web page instead of learning the route was gone. And AIDND_CORS_ORIGINS accepted "*", which on an unauthenticated loopback API would hand every page on the Internet a write handle on the campaign database; it now refuses to start. Verified rather than assumed. Offline, on a network with no route out and no DNS: five turns, retry with both takes retained, restart with an identical transcript digest, a failed model call leaving the accepted AI-turn count untouched, and a capture with zero non-loopback unicast packets. Against a real second machine on the LAN over HTTPS with a private CA: four turns, restart, and a capture showing 289 packets to the approved host, 344 loopback, zero anywhere else, zero DNS queries. Cloud and public endpoints refused with their reasons; no API key settable; every removed route 404. 604 backend tests pass, down from 648 by the fifteen retired with the subsystems they tested and up by the twenty-nine added for the endpoint policy and the removed surface. The scripting tests were not deleted: eight files used a JavaScript counter as instrumentation for the state snapshot and rollback machinery, which M2 does not touch, so the counter moved to the world-state engine and those tests still assert what they always did. Frontend lint and build are clean; the image builds, and its wheel-building stage is gone with quickjs. No M3 work. Undo is still destructive and there is still no Redo. |
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JesseMarkowitzandClaude Opus 5
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c1a73b3d77 |
M1: make the first story turn work with no Internet
Phase 0B ran the upstream application on a network with no route out and the first turn died in tiktoken, which downloads its BPE table the first time anything counts a token. The browser separately fetched three font families from Google on every page load. Neither is visible on a machine that has been online once, which is why both now have tests. The tokenizer table is vendored at backend/app/context/vendor/cl100k_base.tiktoken and backend/app/context/encoding.py builds the encoding from it directly, verifying its SHA-256 against the digest tiktoken itself pins for that URL. No code path in the tokenizer can reach the network any more — not a warm cache, not an environment variable a deployment could forget. The encoding was checked token for token against tiktoken's own. The three font families are self-hosted as variable fonts under frontend/public/fonts/ (343 KiB, Latin and Latin Extended), declared in frontend/src/styles/fonts.css, and re-vendored by frontend/tools/vendor_fonts.py. Their OFL licences ship beside them. With no remote asset left, the CSP drops both Google hosts and gains object-src, base-uri and form-action; woff2 also gets its real media type, which Python's table lacks on a slim image. A trusted-LAN Ollama turned out not to work at all over HTTPS. httpx verifies against the certifi bundle, so an endpoint whose certificate comes from a CA the user installed on their own machines — a StartOS server's Ollama, for one — was refused with CERTIFICATE_VERIFY_FAILED while curl and the browser on the same host accepted it. app/tlstrust.py builds one context that unions the platform CA store with certifi's, and all four outbound clients use it. A union rather than a swap, so an image with an empty system store cannot start failing on endpoints that worked before. Verification itself is untouched: CERT_REQUIRED, hostname checking on, and no insecure escape hatch. The storyteller listener is now loopback by explicit statement rather than by inheriting uvicorn's default: start.sh, start.ps1, and docker-compose.yml, which publishes to 127.0.0.1 rather than every interface. Reaching an Ollama on another machine is outbound and needs none of that inbound exposure. backend/requirements.lock pins the exact tested closure; requirements.txt keeps the ranges. DEVELOPMENT.md covers setup, the same-host and trusted-LAN Ollama configurations, and how to re-run the offline proof. PROVENANCE.md records the upstream commit, the MIT terms, and both vendored assets. Verified, not just compiled. On an --internal Docker network with 1.1.1.1 unreachable and no name resolving, a campaign was created and played for six turns through same-host Ollama, restarted, and resumed. A second run played ten turns through Ollama on a separate physical machine on the LAN over verified HTTPS, summaries and embeddings included, with the storyteller's default route deleted so the LAN was reachable and the Internet was not. Its capture: 893 packets to the approved host, 730 loopback, zero anywhere else, and zero DNS queries. Two induced model failures left the accepted story bit-identical. The inherited SPA was opened in a browser and a campaign read back from it. Evidence is in planning/reports/M1-BASELINE-REPORT.md, along with the findings that did not belong in this change. 648 backend tests pass, up from the inherited 632; frontend lint and build are clean; the image builds. No M2 work is included: the hosted, cloud, analytics, Postgres and scripting surfaces are untouched. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_017foPNqFjAJa2Ngebf5mEfL |