Applies the FabledSword + Scribe iteration palette to theme.css end to
end: indigo (#7c3aed) → dusty violet (#5B4A8A) accent, cool grey →
Obsidian/Iron/Pewter dark surfaces, warm parchment (#F5F1E8) light
mode, Inter body + JetBrains Mono code loaded alongside Fraunces, and
neutral hairline scrollbars (chrome is structural, not branded).
Adds the action token set (--color-action-primary Moss,
--color-action-secondary Bronze, --color-action-destructive Oxblood,
--color-action-ghost-border Pewter) but does not yet reclassify any
buttons — surface-phase work. Buttons remain dusty-violet gradients in
the meantime, by design.
Removes deprecated --color-accent-warm; replaces concrete usages with
--color-text-secondary (dates, flavor copy) or --color-warning (paused
status). Sweeps hardcoded indigo literals in component scoped CSS so
they don't bypass the token system.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
The structured prep card was data-rich but voiceless. Replaced with an
LLM-generated conversational opener — same shape the briefing's compilation
slot had — that renders as a normal assistant chat bubble at the top of
the day's conversation.
Backend (services/journal_prep.py):
- Renamed generate_daily_prep -> gather_daily_sections (still pure data
fetching, no LLM); kept the old name as a backwards-compat alias.
- New _generate_prep_prose: hands the gathered sections to generate_completion
with a warm-conversational system prompt; returns prose. Falls back to a
plain greeting if the LLM call fails or no model is configured.
- ensure_daily_prep_message now persists the prep as role='assistant' with
the prose as content. Structured sections stay on msg_metadata for
provenance. Auto-upgrades legacy system-role preps in place on next call.
Frontend:
- Drop the <article class="daily-prep"> structured block from JournalView.
The prep is now just the first chat bubble — picks up the existing
Illuminated Transcript styling automatically.
- Drop dayMessages / prepMessage / prepSections / asArray helpers — no
longer needed.
- ChatMessage hideMessage filter: comment refined to clarify it only
catches LEGACY system-role prep rows. Current preps are assistant-role
and render normally.
Net effect: open /journal -> first thing you see is a warm assistant bubble
that talks about your day -> input bar below to reply.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
The journal UI was over-stripped earlier — weather panel, current-conditions
poll, and the upcoming-events sidebar were all dropped. Restored those (calls
the new /api/journal/weather, /api/journal/weather/current,
/api/journal/weather/refresh, /api/journal/weather/geocode endpoints).
Also: the daily-prep system message was rendering as flat text inside
ChatPanel because there's no .role-system bubble styling. Added a hideMessage
guard in ChatMessage so daily-prep system messages don't render in the chat
stream — they're already shown above as a structured prep card.
News / RSS reactions / article-discuss are intentionally NOT in the journal
(scoped out per user direction). The broader RSS infrastructure cleanup is
a separate, larger task.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Three visual improvements for the briefing conversation:
1. Intermediate tool-call messages (empty content, briefing_intermediate:
true) now render as a compact dashed status row with per-tool pills
showing result counts, instead of an empty assistant bubble followed
by a stack of ToolCallCards. Click to expand the full cards.
2. Slot badge on non-intermediate briefing messages — "Full Briefing"
for compilation, "Morning/Midday/Afternoon Update" for slot
injections. Slot updates get a softer bubble treatment (transparent
background, muted border, smaller text) so the compilation stays
visually dominant.
3. Slot separator now triggers on briefing_slot metadata (not the
compilation-only rss_item_ids), and uses a look-behind so it only
fires when there's a prior slot message — no separator above the
first briefing of the day.
New component: BriefingToolStatusRow.vue handles the intermediate
pill row and delegates to ToolCallCard when expanded.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Design direction: "Illuminated Transcript" — the AI response is the
primary artifact; user prompts are subordinate margin notes.
ChatMessage.vue:
- User bubble: ghosted background (rgba 3-4% opacity), muted text,
thin near-invisible border. De-emphasized, recessed.
- Assistant bubble: left indigo accent border (2px), elevated shadow
via --color-bubble-asst-shadow. Commands attention.
- Assistant role label: indigo (var(--color-primary)); user label muted.
- Removed old white-override content rules (no longer on dark bg).
- Thinking block: full border → left-only indigo accent bar (35% opacity),
removed inner top border.
ChatView.vue:
- Streaming bubble: same left accent + shadow as assistant bubbles.
- Streaming role label: indigo to match ChatMessage.
- Thinking block in streaming: same treatment as ChatMessage.
theme.css:
- Added --color-bubble-user-bg/border/text for light + dark.
- Added --color-bubble-asst-shadow for light + dark.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Ollama streams message.thinking tokens alongside message.content when
think=True — previously silently dropped. Now forwarded end-to-end.
Backend:
- llm.py: ChatChunk type gains "thinking" variant; stream_chat_with_tools
yields ChatChunk(type="thinking") for msg.thinking chunks before content
- generation_task.py: thinking chunks emit "thinking_chunk" SSE events
(not added to content_so_far — not persisted to DB)
Frontend:
- types/chat.ts: Message.thinking?: string (session-only, not from DB)
- stores/chat.ts: streamingThinking ref; thinking_chunk handler accumulates
chunks; on done, thinking carried into committed Message object then cleared
- ChatMessage.vue: collapsible <details class="thinking-block"> shown for
messages that have .thinking content (collapsed by default)
- ChatView.vue + ChatPanel.vue: live thinking block in streaming bubble —
open while only thinking is flowing, auto-collapses when content arrives;
typing indicator hidden while thinking is active
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Context sidebar + note title:
- ChatView: replace ephemeral context pills with a persistent right-panel sidebar;
auto-found notes accumulate across turns; attached note shows with pin icon;
× button excludes a note from future auto-search; hidden on mobile
- routes/chat.py: batch-fetch note titles via get_notes_by_ids() and inject
context_note_title into each message dict at conversation load time
- notes.py: add get_notes_by_ids() batch fetch helper
- types/chat.ts: add context_note_title field to Message interface
- stores/chat.ts: sendMessage accepts optional 5th arg contextNoteTitle,
included in optimistic user message
- ChatMessage.vue: context badge shows note title instead of 'Note #N'
Expanded LLM tool suite (all with intent router rules + ToolCallCard display):
- delete_note / delete_task: permanent delete with user confirmation (write tool),
type-safe (refuse to delete wrong type), clears note context cache on success
- get_note: fetch full note body by query (search_notes returns only 200-char preview)
- list_notes: browse notes by recency/keyword/tags with limit; notes only
- update_note: add tags + tag_mode (replace/add/remove) parameters
- search_notes: add optional type filter ("note" | "task")
- search_todos (CalDAV): keyword-filter todos, companion to list_todos
- caldav.py: add search_todos() built on top of list_todos()
- generation_task.py: register new tools in _WRITE_TOOLS, _TOOL_LABELS, _TOOL_ACTIONS
- llm.py: update available actions list and guidance in system prompt
- intent.py: routing rules for all new tools
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Bug fix:
- ChatView.vue onMounted now skips fetchConversation when the conversation
is already loaded in the store (same guard that the convId watcher uses).
This prevents duplicate assistant messages when navigating from the
dashboard inline chat to /chat/:id after streaming completes.
Generation timing:
- logging.py: add log_generation() — persists per-generation timing
breakdown to app_logs (category=usage, action=generation) including
model, total_ms, intent_ms, ttft_ms, generation_ms, and per-tool timings.
Queryable via existing admin log viewer.
- generation_task.py: collect wall-clock timestamps at every pipeline stage:
intent classification, per-tool execution (both intent-routed and native),
time-to-first-token (measured from generation start to first content chunk),
LLM streaming round duration. Logs via log_generation() and includes timing
in the SSE 'done' event payload.
- types/chat.ts: add GenerationTiming interface; add optional timing field
to Message.
- chat.ts: capture timing from done event and attach to assistant message.
- ChatMessage.vue: show timing footer on assistant messages with breakdown:
"⏱ 4.2s total · first token 0.8s · analyzed 0.3s · created event 0.4s
· generated 3.5s". Visible this session; persisted to app_logs for
cross-session benchmarking.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Ollama tool/function calling integration allows the LLM to create tasks,
create notes, and search existing notes on behalf of the user during chat.
Multi-round tool loop (max 5 rounds) lets the model execute tools then
produce a natural language response. Tool results are persisted in a new
JSONB column on messages and rendered as compact cards with linked titles.
- Migration 0013: add tool_calls JSONB column to messages
- New services/tools.py: tool definitions + execute_tool dispatcher
- llm.py: ChatChunk dataclass, stream_chat_with_tools(), date in system prompt
- generation_task.py: multi-round tool call loop with SSE tool_call events
- Frontend: ToolCallRecord type, streamingToolCalls in store, ToolCallCard
component, rendering in ChatMessage and ChatView streaming bubble
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Improve chat context: build_context() now returns metadata about auto-found
notes, emitted as an SSE event so the frontend can display context pills
showing which notes influenced the response. Users can promote notes for
deeper context (+) or exclude irrelevant ones (x). A note picker lets users
manually attach notes. Multi-word search uses per-term AND matching, and
auto-search iterates keywords individually for broader OR-style coverage.
Standardize styling: introduce CSS design tokens (--radius-sm/md/lg/pill,
--color-success/warning/overlay, --focus-ring) and migrate all components
to use them. Fix header alignment to full-width, add active nav link state,
replace hardcoded colors with CSS variables, and normalize button padding.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Settings infrastructure: key-value settings table, GET/PUT API, Pinia store
- Configurable assistant name (default "Fable") in settings and LLM system prompt
- Model catalog with 18 models in 3 categories (General Purpose, Coding,
Uncensored / Creative Writing) with download/select/remove functionality
- Move Ollama status indicator from chat views to global nav bar
- Chat bubble layout: user messages right-aligned, assistant left-aligned
- Floating dark input bar with auto-focus and circular send button
- Fix HTML entity rendering (' apostrophe issue in marked/DOMPurify pipeline)
- Fix new chat button navigation (fetchConversation before router.push)
- Recent chats section on home page with "New Chat" button
- Update summary.md with Phase 4.5 changes
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Phase 4: Full chat system with SSE streaming, note-aware context, and
conversation persistence.
Backend:
- Migration 0005: conversations + messages tables with FKs and indexes
- Conversation/Message SQLAlchemy models with relationships
- LLM service: ensure_model (auto-pull on startup), stream_chat (NDJSON),
generate_completion, fetch_url_content (HTML stripping), build_context
(keyword extraction, related note search, URL content injection)
- Chat service: conversation CRUD, save_response_as_note,
summarize_conversation_as_note
- Chat routes blueprint: 9 endpoints including SSE streaming for messages,
save/summarize as note, Ollama model listing
- Auto-pull llama3.1 model on app startup (non-blocking)
Frontend:
- apiStreamPost: SSE client using fetch + ReadableStream
- Chat Pinia store with streaming state management
- ChatView: dedicated /chat page with conversation sidebar + message thread
- ChatPanel: slide-out panel with contextNoteId from current route
- ChatMessage: markdown-rendered message bubble with "Save as Note" action
- Updated AppHeader with Chat nav link + panel toggle button
- Updated App.vue to mount ChatPanel with route-derived context
- Added /chat and /chat/:id routes
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
bvandeusen
Bryan Van Deusen