Ollama's /api/tags returns whatever casing was used at pull time
(e.g. 'gemma3:12B' if the user ran 'ollama pull gemma3:12B'), but
/api/chat rejects mixed-case tags with a 400. The two code paths
are inconsistent, which surfaces the capitalized tag in the model
dropdown and then silently kills every chat request against it.
Lowercase on read (get_installed_models), on settings write
(update_settings_route), and on ensure_model() input so a legacy
mixed-case user setting can't trigger a spurious re-pull at
startup. The dropdown and stored settings are now always in the
form Ollama will actually accept.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Three related fixes uncovered while benchmarking qwen3:14b against 8b:
- pick_num_ctx was only counting message content, missing the ~15K
tokens of tool schemas. num_ctx=8192 was being selected while actual
prompt_tokens hit 14K+, causing silent prompt truncation on every
tool-using request. Now includes json.dumps(tools) in the estimate.
KV cache priming in app.py and routes/settings.py also fetches tools
so the primed num_ctx matches what real chat requests will use.
- _should_think's heuristic classifier was overriding explicit
think=true requests from the frontend toggle and MCP, gating on
message length and regex patterns. Now a pass-through — the caller
is the source of truth. quick_capture hardcodes think=False since
it's a fast classification path that was relying on the old gating.
- delete_note description only mentioned "note or task", so the model
refused to call it for entries created by save_person / save_place /
create_list. Description now explicitly lists all five note_types it
handles.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replace the hardcoded "2h" keep_alive everywhere with a helper that
returns OLLAMA_KEEP_ALIVE_MAIN (default 30m) for the interactive model
and OLLAMA_KEEP_ALIVE_BACKGROUND (default 10m) for the background
model. Lets the main model release VRAM during long idle periods
while keeping it warm enough for bursty chat use, and stops the
sporadic background model from camping VRAM it rarely needs.
Seven call sites updated to route through llm.keep_alive_for(model):
the streaming helpers, generate_completion, the two startup warmers,
the settings KV-cache primer, and the chat warmer endpoint.
Override via env vars: OLLAMA_KEEP_ALIVE_MAIN, OLLAMA_KEEP_ALIVE_BACKGROUND.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
When user_timezone is saved via PUT /api/settings, immediately call
update_user_schedule if briefing is enabled so the scheduler picks up
the new timezone without requiring a restart.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Startup now pulls Config.OLLAMA_MODEL (system default chat model) — previously only
embedding and background models were pulled; the primary chat model was skipped
- _warm_user_models expanded to also pull user-configured default_model and
background_model overrides that are missing from Ollama, rather than logging and
skipping them; pulls run before warm/KV-cache priming
- Add background_model to _MODEL_KEYS in settings route so clearing the dropdown
deletes the DB row instead of saving "", which caused Ollama failures in tag
suggestions, title generation, project summaries, and RSS classification
- Add http/https scheme validation to PUT /api/admin/base-url matching the CalDAV
route pattern; a bad value no longer silently breaks invite/password-reset links
- Update admin voice config description: "Reload models" button exists to avoid
a server restart, so the old "restart required" text was misleading
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Adds pick_num_ctx() which selects the smallest context window tier
(8192, 16384, 32768) that fits the current messages with 25% headroom,
capped at OLLAMA_NUM_CTX. Threads num_ctx through generation_task.py so
every chat request uses the computed tier rather than a fixed 16384.
Fixes a critical cache miss bug: KV cache priming in app.py and
settings.py was sending requests without num_ctx, so Ollama sized the
cache at its model default (different from the 16384 real requests used),
forcing a full model reload on the first real user message. Both priming
sites now call pick_num_ctx() and pass the matching value.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
When a user saves a new default_model in Settings, fire a background
cache-prime request so the first message with the new model is fast
rather than paying the full cold-start prefill cost.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
The separate intent model (OLLAMA_INTENT_MODEL / qwen2.5:7b) is removed
from every part of the system. All classification now uses the primary model.
Changes:
- config.py: remove OLLAMA_INTENT_MODEL
- intent.py: remove classify_intent() and all supporting infrastructure
(_SYSTEM_PROMPT_TEMPLATE, _RESEARCH_PREFIX, _PRIOR_WORK_REFS); file now
only contains the quick-capture classifier
- quick_capture.py: classify_capture_intent() now called with Config.OLLAMA_MODEL
- generation_task.py: remove intent_model_setting DB lookup and get_setting import;
history summarization and research pipeline use the primary model directly
- research.py: remove intent_model parameter from run_research_pipeline() and
_generate_sub_queries(); both use the model param throughout
- routes/settings.py: remove intent_model from model-key validation and response
- app.py: remove intent model pre-warming at startup
- SettingsView.vue: remove Intent Model selector and related refs/state
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
When a user selected the 'Default' option in Settings, the dropdown
sent an empty string "" to the backend. The route saved it as a DB row,
which caused get_setting() to return "" instead of falling back to
Config defaults. The chat status endpoint then tried to match "" against
installed model names — always failing — resulting in model: "not_found"
and a permanently failing readiness indicator.
services/settings.py:
- Add delete_setting() helper: removes a setting row so get_setting()
correctly falls back to its hardcoded default argument
routes/settings.py:
- Import delete_setting
- When default_model or intent_model are saved as empty string, delete
the DB row instead of storing "" — cleanly restores Config fallback
routes/chat.py:
- chat_status_route: add explicit `or Config.OLLAMA_MODEL` guard for
any existing "" rows written before this fix (migration safety net)
- send_message and summarize routes: same guard on model resolution
so empty settings never cause silent generation failures
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Default OLLAMA_INTENT_MODEL to qwen2.5:1.5b in code instead of empty
- Add GET /api/settings/models endpoint returning installed models and defaults
- Validate intent_model against installed models on save (same as default_model)
- Replace intent model text input with a dropdown of installed models
- Add chat model dropdown to Assistant settings section
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- CalDAV integration: per-user calendar config, create/list/search events
via caldav library, LLM tools for calendar operations from chat
- LLM-suggested tags: new tag_suggestions service prompts LLM with existing
tags and note content to suggest 3-5 relevant tags; exposed via API
endpoints (suggest-tags, append-tag); integrated into editor views
(suggest button + clickable pills) and chat tool calls (pills in
ToolCallCard with one-click apply)
- Settings/model UI refinements, generation task improvements
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Rewrite get_all_tags() with SQL unnest instead of loading all notes
- Consolidate convert_note_to_task/convert_task_to_note to single-session ops
- Add search_notes_for_context() with single OR-keyword query for build_context()
- Drop selectinload from list_conversations(), use correlated subquery for message_count
- Add set_settings_batch() for single-transaction multi-setting upserts
- Extract get_installed_models() shared helper into services/llm.py
- Delete services/tasks.py pass-through wrapper; routes/tasks.py imports from services.notes
- Add B-tree indexes on notes.title and conversations.updated_at (migration 0007)
- Add logging to services/notes.py, services/chat.py, services/settings.py
- Safe Conversation.to_dict() when messages relationship is not loaded
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>
bvandeusen
Bryan Van Deusen