Merge create_task into create_note (set status='todo' for tasks, omit
for notes), merge delete_task into delete_note, consolidate entity
tools (create/update_person → save_person, create/update_place →
save_place), rename get_note → read_note with clearer descriptions,
move calculate out of rag.py into utility.py, and extract shared
duplicate detection into check_duplicate() helper.
Updates all downstream references in generation_task.py, quick_capture.py,
ToolCallCard.vue, and WorkspaceView.vue.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Removes the custom classify_capture_intent + _process_note two-pass
approach. The LLM now picks the right tool directly via Ollama's native
tool_calls API (same path as the main chat pipeline). _should_think
decides whether extended reasoning is needed based on input length/
complexity. intent.py deleted — no longer needed.
Android app and response format unchanged.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Project view:
- Add inline status advance buttons on kanban task cards (todo→in_progress,
in_progress→done); buttons reveal on hover, stop link navigation
Task viewer:
- Back button navigates to task's project instead of /tasks when project_id set
- Esc key navigates to project (or /tasks); blurs focused element first
Quick capture:
- Use user's configured model instead of hardcoded Config.OLLAMA_MODEL
- Remove create_project from classifier prompt (tool not offered, caused
task-shaped inputs to silently fall through to note fallback)
Briefing scheduler:
- Fix get_event_loop() → get_running_loop() so background thread uses the
correct hypercorn event loop (jobs were scheduling but never executing)
- Suppress bare greeting when both LLM synthesis lanes return empty
RSS feed UI (SettingsView):
- Show last-fetched age, category badge, and feed URL per row
- Category input field when adding a feed
- Refresh all button: fetches latest items, reloads list, toasts with count
- Enter key submits add-feed form; better empty-state hint with example feeds
Weather tool:
- Accept any city/region name in addition to 'home'/'work'/'all'
- Geocodes via Nominatim + fetches live from Open-Meteo for arbitrary queries
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>
Add _process_note() — a second LLM pass using the main model that
transforms raw capture text into a well-formed note with a genuine
summary title and formatted body. Replaces the previous behaviour of
using the captured text verbatim as both title and body.
The processing prompt instructs the model to:
- Generate a 3-8 word summary title (never a verbatim copy)
- Format the body appropriately: bullet lists for items, clean prose
for stream-of-thought, organised paragraphs for raw notes/fragments
- Preserve all original information without inventing new facts
The enrichment pass runs for both the intent-classified create_note
path and the fallback path. On LLM/parse failure it degrades safely
to the old verbatim behaviour.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Remove all 6 CalDAV todo tools (create/list/update/complete/delete/search_todos)
from tools.py definitions, imports, execute_tool branches, intent routing rules,
generation_task labels/actions, and llm.py system prompt hints. CalDAV event
tools remain. Todo functions still exist in caldav.py but are no longer exposed.
- Quick-capture now uses a dedicated classify_capture_intent() with a focused
_CAPTURE_SYSTEM_PROMPT that always routes to a tool (never null). Tool set
expanded: create_note/task/event + update_note + research_topic.
- research_topic in quick-capture calls run_research_pipeline() directly (no SSE
buffer). run_research_pipeline() now accepts buf=None; all buf.append_event
calls are guarded so status events are skipped when no buffer is provided.
- Fallback note now always sets body=text (was empty for texts ≤80 chars).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Single POST that classifies natural-language text and creates the
appropriate item (note, task, event, or todo) in one synchronous
request — no SSE, no conversation context needed.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
bvandeusen