list_pages gains an opt-in `tree` parameter on both surfaces (the
@docmost/mcp server tool and the AI-chat agent tool), which share the
same DocmostClient.listPages. Default behavior (recent-by-updatedAt flat
list) is unchanged.
- client.ts: listPages(spaceId?, limit=50, tree=false); when tree is
true it requires spaceId (throws a specific error otherwise), walks the
sidebar tree via the existing bounded/cycle-safe enumerateSpacePages,
and returns a nested tree; limit is ignored in tree mode.
- lib/tree.ts: new pure buildPageTree() — lean nodes { id, slugId, title,
children? }, children sorted by position (code-unit order), orphans
promoted to roots, cycle-safe.
- index.ts + ai-chat-tools.service.ts: expose `tree` in the tool schemas
and descriptions; docmost-client.loader.ts: mirror the new signature.
- tests: add packages/mcp/test/unit/tree.test.mjs (nesting, ordering,
lean shape, orphan promotion, cycle/self-reference safety).
- rebuild @docmost/mcp (build/ is tracked and loaded at runtime).
Wrap the logo link and the APP_VERSION text into a single bottom-aligned
Group so they read as one lockup ("gitmost v0.9..."). Move the version
styling into a new .brandVersion CSS class: shrink it from 12px to 10px,
keep the dimmed color and selectability, and lift it via margin-bottom so
its text baseline sits on the wordmark baseline of the 30px desktop logo
(derived from the logo SVG geometry). Drop the redundant lh prop.
Remove outdated process sections from several backlog markdown files and add new backlog items for AI chat step limits, endpoint status config, and API key field UI improvements.
The transcript force-scrolled to the bottom on every streamed delta because
the auto-scroll effect ran unconditionally whenever the messages array identity
changed. Scrolling up to read earlier messages was impossible — each token
yanked the view back down.
Implement a "stick to bottom" pattern in MessageList:
- track whether the viewport is pinned to the bottom via a scroll listener
(pinnedToBottomRef, BOTTOM_THRESHOLD = 40px);
- only auto-scroll while pinned; a freshly sent user message always re-pins;
- attach the scroll listener via a [hasScrollArea] dependency so a brand-new
empty chat (whose ScrollArea mounts only after the first message) wires it up;
- guard the effect's own scrollTop write (programmaticScrollRef) so it is not
misread as a user scroll.
The floating AI-chat header badge summed metadata.usage (AI SDK
totalUsage, all steps) across every assistant row, showing the
cumulative tokens SPENT — which grows each turn as history is re-sent.
Replace it with the conversation's CURRENT context size.
- server: persist metadata.contextTokens in streamText onFinish from the
final-step `usage` (inputTokens + outputTokens ≈ current context
window occupancy); keep usage: totalUsage for back-compat/fallback
- client: derive the badge from the most recent assistant row's
contextTokens (fallback to that row's usage total for older chats)
instead of summing all rows
- types: add metadata.contextTokens to IAiChatMessageRow
- i18n: rename badge label "Tokens used in this chat" -> "Current
context size" (en-US)
No DB migration needed (metadata is a JSON column).
Add docs/backlog/stt-providers-and-async.md: how to add new synchronous STT
request formats (Deepgram, native Gemini, ElevenLabs) via the explicit
sttApiStyle axis, which providers are inherently async and don't fit the
current sync model, and a target job-based async architecture (BullMQ job
table, sync+async unification, polling -> push -> live streaming) with the
migration path and security/cleanup considerations.
Add docs/streaming-dictation-plan.md — a design document for true
"text appears as you speak" dictation via the OpenAI Realtime API.
- Maps the current batch dictation flow (client MediaRecorder -> single
blob -> POST /ai-chat/transcribe) and why streaming is impossible there.
- Documents the Realtime API contract (transcription session, ephemeral
token, pcm16 audio, input_audio_buffer.append, input_audio_transcription
delta/completed events, server_vad).
- Recommends a server-side WS proxy transport (key stays server-side,
SSRF-guarded, provider-agnostic via sttBaseUrl) over direct browser
WebRTC, and a ProseMirror decoration for interim text with final-only
commit to avoid polluting Yjs collab/history.
- Covers config additions, AudioWorklet PCM16 capture, security per repo
conventions, edge cases, phased rollout, risks, and impacted files.
Replace the implicit `hostname endsWith openrouter.ai` detection with an
explicit, admin-chosen provider field `sttApiStyle` ('multipart' = OpenAI-
compatible multipart /audio/transcriptions; 'json' = OpenRouter-style JSON +
base64 input_audio). The transcription path now branches on the stored field,
not on the URL — nothing hidden from the admin.
- ai.types: add SttApiStyle + STT_API_STYLES; field on AiProviderSettings and
MaskedAiSettings (resolved via ResolvedAiConfig).
- update-ai-settings.dto: validate sttApiStyle with @IsIn(STT_API_STYLES).
- ai-settings.service: plumb sttApiStyle through resolve()/getMasked() and the
non-secret update whitelist; workspace.repo: add it to the ALLOWED array so it
persists.
- ai.service: drop isOpenRouter(); transcribe() branches on cfg.sttApiStyle;
rename helper to transcribeJsonBase64 with provider-neutral error text and a
BadRequestException (400) when the base URL is missing for the JSON style.
- client: SttApiStyle type on IAiSettings/IAiSettingsUpdate; "Request format"
Select on the Voice/STT settings card; i18n.
- ai.service: route *.openrouter.ai STT to its JSON+base64
/audio/transcriptions API; keep the OpenAI multipart path (AI SDK) for
OpenAI/self-hosted whisper. Unify transcription behind transcribe().
- /transcribe controller: surface the real provider/transport reason
(describeProviderError) instead of an opaque 500; preserve HttpException.
- testConnection: add an 'stt' capability (silent-WAV probe) + DTO; client
gets a Test endpoint button and status dot on the Voice/STT card.
- useDictation: log full errors to the console and show the real reason
(mic start + transcription paths); handle NotReadable/Abort and missing
mediaDevices.
- docs(CLAUDE.md): require full error logging + specific user-facing messages.
Add a documentation bullet that enforces comprehensive error logging and user‑facing messages, ensuring caught errors are fully logged and presented with specific, human‑readable explanations rather than generic messages.
The README files now list Voice dictation as a completed feature (✅) instead of an upcoming one (🔭). Consequently, the detailed `voice-dictation-plan.md` documentation has been removed. This reflects that the feature is ready and no longer merely a plan.
Add a section describing how Kysely runs migrations in alphabetical (timestamp) order and the need to verify migration timestamps when merging branches. This helps prevent migration ordering errors and boot failures.
Update the README files to list newly planned features on the roadmap, including page templates, a public‑share AI assistant, and academic‑style footnotes. This improves documentation of upcoming functionality.
Add a detailed design and implementation plan for an AI assistant that
operates on publicly shared document trees. The document outlines the
feature scope, architecture, security considerations, and remaining work,
providing context for future development.
Add docs/page-templates-plan.md describing a whole-page live
transclusion feature: pages flagged is_template, a new pageEmbed
node referencing a source page, a whole-page lookup endpoint reusing
the existing transclusion access-control and share paths, reference
sync, duplicate remap, and cycle/deletion/access/export edge cases.
Decision: separate pageEmbed node over extending transclusionReference.
Add push-to-talk voice dictation that transcribes recorded audio on the
server via the workspace's OpenAI-compatible AI provider (Whisper /
gpt-4o-transcribe / self-hosted whisper), then inserts the text.
Backend:
- New `stt_api_key_enc` column + migration; STT creds parity with chat/
embeddings (sttModel/sttBaseUrl/sttApiKey, write-only key, fallbacks to
chat baseUrl/key). Both provider whitelists updated (service + repo).
- AiService.getTranscriptionModel + AiTranscriptionService.
- Gated POST /ai-chat/transcribe (dictation flag → 403, JWT + workspace
scope + throttle, 25MB cap, MIME whitelist, never logs audio/key).
- New `settings.ai.dictation` workspace flag (DTO + service + audit).
Frontend:
- Wire up the Voice/STT settings card (model/base URL/key) and the
Voice-dictation toggle.
- New `features/dictation`: useDictation (MediaRecorder state machine),
MicButton, transcribe service; integrated into the chat composer and a
new editor-toolbar dictation group, both gated by ai.dictation.
Add a "Cutting a release" subsection to CI / release: version selection
(SemVer), synchronized package.json bump (root + client + server; mcp is
independent), CHANGELOG update, lightweight v-tag, and push that triggers
release.yml. Document moving a misplaced tag via git tag -f + force-push,
and note the git tag (not package.json) is the source of truth for the
displayed version.
Make the floating AI chat window open at a larger default size and
allow stretching it further, plus shrink the fonts.
- ai-chat-window.tsx: DEFAULT_WIDTH 362->540, DEFAULT_HEIGHT 602->680;
clamp the default width to the viewport in computeInitialGeom()
(symmetric with the existing height clamp) to avoid overflow on
narrow screens.
- ai-chat-window.module.css: raise resize caps (max-width 560->900px,
max-height 880->1100px); base font-size 12->11px.
- ai-chat.module.css: chat content font .messages sm->xs.
Add a root CLAUDE.md describing the Gitmost project for Claude Code and
other AI-agent tooling. Covers: the AGPL-only/no-EE fork philosophy and the
"internal identifiers stay docmost" naming gotcha; the pnpm+Nx monorepo
layout; build/lint/test (incl. single-test) and migration commands; and the
big-picture architecture — the two server processes (API on PORT, collab on
COLLAB_PORT via Hocuspocus/Yjs), NestJS module layout, Kysely/Postgres+
pgvector/Redis persistence, the shared editor-ext (client + server; the MCP
package vendors its own schema mirror), and the two AI subsystems (embedded
/mcp server and the CASL-scoped AI chat agent with RAG).
Add a header button to the AI agent chat window that copies the active
conversation to the clipboard as Markdown, including the request
internals already persisted client-side — tool calls with their
input/output, per-message token usage, and finish/error info. No new
network call and no server/DB change: it serializes the already-loaded
persisted message rows.
- New util chat-markdown.ts (renamed from export-chat.ts): pure
buildChatMarkdown() serializer reusing the tool-parts helpers so tool
labels match the on-screen labels; fence() escapes embedded code
fences.
- ai-chat-window.tsx: Copy button (shown only for a saved chat with
loaded rows) using the project useClipboard hook; toggles a check
icon on success and shows the standard "Copied" notification. Drag is
unaffected (startDrag ignores button clicks).
- en-US: add "Copy chat" key, drop the obsolete "Export chat".
Move the AI-chat toggle icon (IconSparkles) from the page header menu
into the global top bar, placed next to the notifications icon. The
"AI chat enabled" gate (workspace.settings.ai.chat) is preserved, and
the icon style is aligned with the neighbouring notifications icon
(subtle, size sm). As a result the entry point is now available on all
routes instead of only on page routes.
- app-header.tsx: render the gated AI-chat ActionIcon before
NotificationPopover; wire it to aiChatWindowOpenAtom.
- page-header-menu.tsx: remove the old AI icon block and its now-unused
imports/locals.
Add autoFocus to the chat composer Textarea so a freshly created chat
(window open, "New chat", chat switch — all remount ChatThread via key)
lands with the cursor ready in the input field, letting the user type
immediately without clicking into it.
edit_page_text reported "success" when asked to change formatting (e.g. remove
strikethrough): the markdown-strip fallback matched the bare text, the replace
preserved marks, and the tool returned success — so the agent believed it had
fixed something that never changed.
Two fixes, both in the shared @docmost/mcp DocmostClient so they reach BOTH the
standalone MCP server and the in-app AI chat (which loads @docmost/mcp):
- Verifiable result for every content mutator: mutatePageContent now computes a
`verify` change-report (text inserted/deleted, blocks changed, per-mark-type
delta, integrity/structure delta) via summarizeChange() and returns it on all
mutators (incl. replaceImage via mutateLiveContentUnlocked). diffDocs is
text-only, so the mark/structure delta is what surfaces formatting changes.
- edit_page_text hard-refuses formatting edits: applyTextEdits rejects an edit
whose find/replace differ only in markdown markers (via stripBalancedWrappers,
which strips balanced wrappers/links without trimming whitespace/emoji, so
plain-text edits like trailing-space trims, snake_case, math are NOT refused).
A fully-refused batch errors instead of silently succeeding.
Also updated the model-facing edit_page_text descriptions in BOTH tool layers
(packages/mcp/src/index.ts and ai-chat-tools.service.ts) to drop the misleading
"strip-and-retry tolerated" wording and point formatting changes to patch_node.
New unit tests: test/unit/diff-verify.test.mjs, test/unit/json-edit-refuse.test.mjs.
The sidebar page tree previously kept its expanded/collapsed state in an
in-memory jotai atom, so it reset on every reload. Persist it in
localStorage instead, scoped by `${workspaceId}:${userId}` so multiple
accounts sharing a browser origin don't leak tree state into each other.
- open-tree-nodes-atom: replace the in-memory atom with a facade over an
atomFamily of atomWithStorage, scoped via currentUserAtom; keep the same
[OpenMap, functional-updater setter] public API so space-tree needs no
change.
- Use an explicit synchronous createJSONStorage + getOnInit: true so the
saved state is read at atom init — no collapse-then-expand flicker on
reload and no write against an un-hydrated empty map.
- README / README.ru: document persistent page-tree state in the
"What's different from Docmost" table.
Add an "Export chat" button to the AI agent chat window header that
downloads the active conversation as a Markdown file. The export is
client-only: it serializes the already-loaded persisted message rows
(no new network call, no server/DB change) and includes the request
internals the chat already holds — tool calls with their input/output,
per-message token usage, finish reason and error info.
- New util apps/client/src/features/ai-chat/utils/export-chat.ts:
buildChatMarkdown() + exportChatAsMarkdown(); reuses tool-parts
helpers so tool labels match the on-screen labels; fence() escapes
embedded code fences; slugify() yields a safe filename with a chatId
fallback; downloads via file-saver's saveAs.
- ai-chat-window.tsx: IconFileExport button in the header, shown only
for a saved chat with loaded rows (canExport); drag is unaffected.
- en-US: add "Export chat" and "You" i18n keys.
Display the app version (output of `git describe --tags`) in the header
beside the gitmost logo: a clean tag renders as `vX.Y.Z`, otherwise the
tag plus commits-since and short hash (e.g. v0.90.1-56-g25975acd).
- vite.config.ts: resolve APP_VERSION from env (Docker/CI) -> git describe
(local) -> package.json version fallback
- app-header.tsx: render APP_VERSION after the brand block (ml="md"),
nudge the Home nav group (ml={50} -> "xl")
- Dockerfile: accept APP_VERSION build-arg in the builder stage (.git is
excluded from the build context)
- CI: pass APP_VERSION build-arg — release.yml uses the tag, develop.yml
computes git describe with fetch-depth: 0
- nx.json: add APP_VERSION to the build target inputs so the cache
invalidates when the version changes
Extract the AI provider/endpoints settings and the MCP server section out
of the Workspace "General" settings page into their own "AI" settings page,
reachable from a new sidebar entry.
- add page apps/client/.../settings/workspace/ai-settings.tsx (AiProviderSettings
admin-gated + McpSettings), with its own Helmet title
- register the /settings/ai route in App.tsx and add SETTINGS.WORKSPACE.AI
to app-route.ts
- add an "AI" item (IconSparkles) to the Workspace group in settings-sidebar
- trim workspace-settings.tsx back to the General section and drop the
now-unused imports
Rebuild the workspace AI settings page into card-based "Endpoints"
(Chat / Embeddings / Voice) matching the new design, and split the
single connection test into independent per-endpoint Test buttons.
- server: testConnection(workspaceId, capability) probes only the
requested capability ('chat' | 'embeddings'); add TestAiConnectionDto
and wire it through the /workspace/ai-settings/test controller
- client: testAiConnection(capability) + capability-typed mutation; two
independent test mutation instances so Chat/Embeddings results are isolated
- client: full rewrite of ai-provider-settings into Endpoints section —
drop the provider dropdown (driver is always openai, base URL + key
always shown), move the "AI chat" and surface the "Semantic search"
feature toggles into card headers, system message behind an Edit modal,
pgvector/reindex footer, and a disabled Voice/STT stub
- client: restyle external MCP tools and the MCP server section; collapse
the AI sections in workspace-settings; remove the standalone
ai-chat-settings component
- toggles now surface the server error message (e.g. missing pgvector)
- i18n: add new English strings
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This document outlines the removal of non‑functional DOCX, PDF, and Confluence
import options that relied on a private EE module. It records the completed
frontend changes and lists the remaining backend cleanup tasks.
DOCX, PDF and Confluence import relied on a private EE module that was
dropped from this build, so those code paths only threw "enterprise
license" errors (DOCX/PDF) or silently did nothing (Confluence) while the
UI still presented them as working options.
- page-import-modal: drop the Word (DOCX), PDF and Confluence FileButtons
- remove the now-dead icon imports (IconFileTypeDocx, IconFileTypePdf,
ConfluenceIcon), the docx/pdf/confluence file refs and their input-reset
branches in handleFileUpload/handleZipUpload
- delete the orphaned confluence-icon.tsx component (no remaining importers)
Markdown, HTML, Notion and the generic zip upload remain unchanged.
Improve agent RAG quality with three changes, plus a roadmap doc for the rest.
- Indexer: prefix each chunk with its heading path ("Page > H1 > H2"), built by
walking the ProseMirror JSON (heading nodes) so a `#` inside a fenced code block
is never mistaken for a heading. Falls back to plain-text chunking on any error.
buildChunkRows: drop indexOf-against-source offsets (breadcrumb prefixes break
verbatim matching) for a cumulative cursor — offsets are provenance-only.
- Hybrid search: new migration adds a generated `fts` tsvector column + GIN index
to page_embeddings (same english+f_unaccent config as pages.tsv). New
PageEmbeddingRepo.hybridSearch fuses cosine + full-text rankings via Reciprocal
Rank Fusion (k=60, equal weights) in one SQL query at chunk granularity.
- Tools: collapse semanticSearch + searchPages into one hybrid `searchPages` tool
with a query-rewrite-oriented description; gracefully falls back to the REST
full-text path when embeddings are unconfigured. Access control (space scope +
page-permission post-filter) preserved. Add a query-rewrite hint to the default
system prompt.
- docs/rag-improvements-plan.md: record what shipped and the deferred backlog
(reranker, attachment indexing, eval harness, tuning).
Note: requires a corpus reindex to populate breadcrumbs on existing pages.
"Indexed N of M pages" stayed at e.g. "27 of 34" forever even after a
successful full reindex. The numerator counted pages that have embeddings
while the denominator counted ALL non-deleted pages, so empty / text-less
pages (which legitimately store zero embeddings) could never be reached.
Add PageRepo.countEmbeddablePages: counts non-deleted pages that have
non-empty textContent OR already have a stored embedding row, and use it as
the totalPages denominator in AiSettingsService.getMasked. The "has
embeddings" clause covers pages indexed from the content JSON (null
textContent) and guarantees indexedPages <= totalPages. No DB migration.
The floating AI chat window used a hard-coded border-radius of 14px,
larger than any other element and out of line with the rest of the UI.
Switch to the Mantine md radius token (8px) so the window corners blend
with the inner cards and message bubbles.
The bulk embedding reindex could hang on a single page forever
("Indexed 27 of 34 pages") with zero log output:
- all progress logs were debug-level, suppressed in production (pino info);
- embedMany() had no timeout, so a slow/hung embeddings endpoint blocked
the sequential per-page loop indefinitely.
Changes:
- ai.service.embedTexts: bound embedMany with AbortSignal.timeout
(configurable via AI_EMBEDDING_TIMEOUT_MS, default 120000ms); on timeout
throw a clear, greppable message, classified by both signal.aborted and
the error name (TimeoutError/AbortError/ResponseAborted) so a real
provider error racing the timer keeps its diagnostics.
- embedding-indexer.reindexWorkspace: promote lifecycle/progress logs to
info; log "[i/N] indexing page <id>" BEFORE the await so a hang names the
stuck page; warn on slow pages (>30s); add timing + final summary.
- .env.example: document AI_EMBEDDING_TIMEOUT_MS.
A misconfigured embeddings endpoint failed the RAG indexer with an opaque
"Invalid JSON response" and was not caught by "Test connection" (which only
probed the chat model), so it only surfaced silently during background
indexing.
- add describeProviderError(): formats AI SDK errors as
"<statusCode>: <message> | response body: <truncated one-line snippet>"
(statusCode/message/responseBody never carry the API key)
- use it in the bulk-reindex catch and the embedding processor's formatter so
the real cause (e.g. an HTML 404 from a wrong base URL) is visible in logs
- testConnection now probes chat AND embeddings independently: skips a probe
when that capability is unconfigured, returns ok:false with a Chat:/Embeddings:
prefix on real failure, "not configured" when neither is set
The WORKSPACE_CREATE_EMBEDDINGS / WORKSPACE_DELETE_EMBEDDINGS jobs were
enqueued (on AI Search enable/disable) but had no AI_QUEUE handler, so
existing pages were never indexed ("Indexed 0 of N pages") and disabling
never purged embeddings.
- EmbeddingProcessor: handle WORKSPACE_CREATE_EMBEDDINGS (bulk reindex all
live pages) and WORKSPACE_DELETE_EMBEDDINGS (purge workspace embeddings)
- EmbeddingIndexerService: add reindexWorkspace() (skips when embeddings
unconfigured; per-page error isolation) and removeWorkspace()
- PageRepo.getIdsByWorkspace(), PageEmbeddingRepo.deleteByWorkspace()
- AiSettingsService.reindex() + admin-only POST /workspace/ai-settings/reindex
- Frontend: "Reindex now" button, service call and mutation
- Stable per-workspace jobId with remove-before-add so a stale job can't
block future reindexes; cancel the delayed purge on enable/reindex so it
can't wipe freshly-built embeddings
Add docs/mobile-app-plan.md capturing the mobile-app research: current
stack, existing responsive web inventory, why the editor must stay in a
WebView, comparison of native/Capacitor/hybrid paths, the recommended
Capacitor route, required backend changes (token-in-body login, CORS
whitelist, APNs/FCM push, optional Swagger), Android/iOS specifics, and
the offline outlook (referencing docs/offline-sync-plan.md).
Enrich the "Mobile app" roadmap entry in README.md and README.ru.md to
point to the new plan and correct the inaccurate "native" wording
(Capacitor wrapper of the existing web UI, iOS first, Android to follow).
Add docs/voice-dictation-plan.md — a ready-to-implement design covering
server-side Whisper transcription via the existing per-workspace AI provider,
with the mic button in both the AI agent chat and the page editor. The doc
consolidates four parts: STT provider credentials (full parity with the LLM
and embedding creds, incl. the encrypted stt_api_key_enc column and both
provider-field whitelists), the getTranscriptionModel builder + /transcribe
endpoint, the ai.dictation visibility toggle, and the client capture
(useDictation + MicButton). Includes edge cases, security notes, an
implementation order, and the full list of affected files.
Per-workspace AI provider config previously shared a single base URL and
a single API key between the chat model and the embedding model. Add
dedicated, optional embedding endpoint/token that fall back to the chat
values when empty, preserving backward compatibility.
- db: new migration adds nullable `embedding_api_key_enc` to
`ai_provider_credentials`; chat key stays in `api_key_enc`
- repo: add `upsertEmbeddingKey` / `clearEmbeddingKey` (on-conflict
touches only its own column, so chat/embedding keys never overwrite)
- ai-settings.service: store non-secret `embeddingBaseUrl`; resolve()
applies fallback (embeddingBaseUrl || baseUrl; embedding key || chat
key); getMasked() exposes raw `embeddingBaseUrl` + `hasEmbeddingApiKey`,
never the key; update() handles the embedding key write-only
- ai.service: getEmbeddingModel() builds openai/gemini/ollama with the
embedding-specific URL/key; chat path unchanged
- client: new "Embedding base URL" and "Embedding API key" fields with
fallback hints and a clear-key action
Requires running the DB migration on deploy.
The insert_image and replace_image MCP tools previously uploaded only
local files (filePath), which an AI MCP client cannot provide — it has
no access to the server filesystem. Replace filePath with a required
imageUrl and download the image over http(s).
- client.ts: add fetchRemoteImage(url, maxBytes) — http/https-only scheme
allowlist, 20 MiB cap (maxContentLength + post-download length recheck),
30s timeout, Content-Type→MIME resolution with URL-extension fallback,
filename derivation with canonical extension
- client.ts: rewrite uploadImage(pageId, url) as URL-only; drop the
local-file branch, imageMimeFromPath and the fs import; insertImage/
replaceImage now take a url
- index.ts: drop filePath, add required imageUrl to both tools; update
tool descriptions and SERVER_INSTRUCTIONS
- README: document the web-URL behaviour
The EE-frontend removal (a88b3f77) deleted enable-ai-chat.tsx, the only UI
that set the workspace flag settings.ai.chat. The backend gates remained:
the header assistant icon (page-header-menu) and the /ai-chat/stream endpoint
both require settings.ai.chat === true, and the flag is auto-enabled only in
cloud mode. As a result, self-hosted community builds could configure an AI
provider but had no way to turn the chat on, so the assistant icon never
appeared.
Restore a single admin toggle wired to the already-existing backend `aiChat`
field, modeled on the adjacent MCP settings switch:
- add aiChat?: boolean to the client IWorkspace type
- add AiChatSettings component (optimistic update, revert-on-error,
workspaceAtom sync so the icon updates without reload)
- render it (admin-only) in workspace settings between AI / Models and
AI / External tools (MCP)
Generative AI and AI search toggles, removed in the same commit, are left
out of scope.
Replace the bare brand text on pages with the Gitmost logo lockup
(mark + "gitmost" wordmark) and use the mark as the favicon.
- add generated logo lockups (text outlined from Space Grotesk SemiBold)
in dark/light ink variants; add reusable theme-aware <BrandLogo> component
- use BrandLogo in the global header (mark-only on mobile, full lockup on
desktop) and on auth pages, dropping the old Docmost icon + plain text
- point favicon to /brand/gitmost-favicon.svg (SVG primary + PNG fallbacks);
regenerate favicon/app-icon PNGs from the brand SVGs
- rename app name Docmost -> Gitmost (getAppName, index.html title/apple
title, manifest name); use getAppName() in the 404 title
- align theme/background colors to the brand tile (#0E1117)
- move brand guide and logos into docs/brand/ (canonical home) with a README,
and serve runtime copies from apps/client/public/brand/
Document migrating an existing Docmost instance to Gitmost. The DB schema
is a strict superset (additive-only migrations that auto-apply on boot), so
the move is essentially two image swaps; the only hard requirement is the
pgvector DB image for the page_embeddings RAG table (CREATE EXTENSION vector).
- Primary path: clean in-place swap from a Docmost on postgres:18
(app -> ghcr.io/vvzvlad/gitmost, db -> pgvector/pgvector:pg18), no
dump/restore, volume reused as-is.
- Notes: pg_dump backup first, identical PGDATA layout, matching the
Postgres major (pg16 case), managed-Postgres caveat, AI opt-in.
- Added to both README.md and README.ru.md.
Read tools (getPage, getPageJson, getNode, diffPageVersions,
exportPageMarkdown) return whole pages with no size cap. Their outputs
were stored verbatim in metadata.parts and the tool_calls column, and
metadata.parts is replayed to the provider on every later turn via
convertToModelMessages. After reading a couple of large pages the prompt
grew by full page bodies each turn — rising token cost, latency and DB
row size.
Add compactToolOutput(): a pure, recursive, size-bounded compactor used
in assistantParts() and serializeSteps(). It preserves the value's kind
and small scalar fields (id/title/pageId, which the client reads to build
citations on reload) while truncating long strings, capping long arrays
with a marker, and collapsing subtrees past a depth limit. Small outputs
are returned unchanged by identity. Tool inputs are left intact so
replayed tool_use arguments keep their object shape.
Compaction runs only at persistence time (onFinish/onAbort), so the live
stream and the current turn's multi-step reasoning still see full bodies.
Add unit tests for compactToolOutput.
