bvandeusen 4806c34a3c refactor: Phase 10 — Ollama service, image cache, config, frontend orphans
Final cleanup phase of the MCP-first pivot.

docker-compose:
  - docker-compose.yml: drop ollama service + OLLAMA_URL/MODEL env vars +
    IMAGE_CACHE / VAPID env comments
  - docker-compose.prod.yml: drop ollama service + Ollama env + GPU
    reservation
  - docker-compose.quickstart.yml: drop ollama service + Ollama env +
    GPU-reservation comment; quickstart instructions now point at the
    MCP Access tab instead of model-pull

Config:
  - Drop OLLAMA_URL, OLLAMA_MODEL, OLLAMA_BACKGROUND_MODEL,
    OLLAMA_KEEP_ALIVE_*, OLLAMA_NUM_CTX, EMBEDDING_MODEL (fastembed
    is hard-coded inside services/embeddings.py)
  - Drop IMAGE_CACHE_DIR, IMAGE_MAX_BYTES (image cache subsystem
    deleted)
  - Drop VAPID_PRIVATE_KEY, VAPID_PUBLIC_KEY, VAPID_CLAIMS_SUB (push
    deleted in phase 8)
  - Drop VOICE_ENABLED, STT_BACKEND, STT_MODEL, TTS_BACKEND (voice
    deleted in phase 8)
  - Drop Config.validate() rules for those keys

Image cache deletion:
  - services/images.py, routes/images.py, models/image_cache.py
  - models/__init__.py: drop ImageCache import
  - app.py: drop images_bp registration
  - alembic/versions/0054_drop_image_cache.py: DROP TABLE image_cache

Frontend client.ts orphan exports stripped:
  - getVoiceStatus, getVoiceList, getVoiceLibrary, installVoice,
    uninstallVoice, transcribeAudio, synthesiseSpeech,
    VoiceStatusResult / VoiceEntry / VoiceLibraryEntry types
  - getJournalConfig, saveJournalConfig, getJournalToday/Day/Days,
    triggerJournalPrep, runJournalCurator, listPendingActions,
    approvePendingAction, rejectPendingAction, listJournalMoments,
    updateJournalMoment, deleteJournalMoment, geocodeAddress
  - JournalConfig / JournalLocation / JournalConversation /
    JournalMessage / JournalDayPayload / JournalMoment /
    CuratorRunResult / PendingCuratorAction types
  - consolidateProfile, clearProfileObservations, listProfileObservations
  - ProfileObservationEntry, learned_summary/observations_* fields on
    UserProfile
  - consolidateTask (cascading update to TaskEditorView)
  - getFableMcpInfo, getNewsItems, GetNewsItemsParams, NewsItem import

TaskEditorView:
  - Drop the auto-summary banner + Re-consolidate button
  - Drop isBodyAutoMaintained gate (editor is always user-controlled now)
  - Drop reconsolidate function + reconsolidating ref

SettingsView:
  - profile ref no longer initialises learned_summary /
    observations_count / observations_updated_at (those fields are
    gone from UserProfile type)

Surviving frontend composables/components flagged for likely future
cleanup but not deleted in this commit (no compile errors, just
unreferenced after Phase 7-8):
  - useAssist, useFloatingAssist, useTagSuggestions, useVad,
    useListenMode, useOnnxPreloader (composables)
  - WorkspaceNoteEditor, WorkspaceTaskPanel, WeatherCard, InlineAssistPanel
    (components)
  - api/client.ts still references /api/notes/assist/* and
    /api/notes/suggest-tags via useAssist + useTagSuggestions — those
    endpoints 404 now but no caller hits them; dead at runtime, harmless.

Compose stack collapses to two services: `app` + `db`. No Ollama, no
voice models, no fable-mcp wheel build. First-boot install reduces to:
  docker compose up -d
  → visit web UI → register → Settings → MCP Access → copy snippet
  → claude mcp add … → done.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-27 19:10:25 -04:00

Fabled Scribe

A self-hosted second brain and project management application with integrated LLM capabilities. Write, organise, and act on your notes and tasks with the help of a local AI assistant — all running on your own hardware.

Features

Notes and tasks with a Markdown editor, sub-tasks, milestones, and kanban project workspaces. AI chat with streaming responses, RAG over your notes, and tool use (web search, calendar, weather). A daily briefing that digests your tasks, RSS feeds, and weather on a schedule. Knowledge graph, per-user/group sharing, PWA with push notifications, an MCP server for external AI clients, and an Android companion app.

Quick Start

Prerequisites: Docker and Docker Compose. 8 GB+ RAM recommended for LLM inference.

Download docker-compose.quickstart.yml from this repo, then:

# Optional but recommended — set a secret key
export SECRET_KEY=your-random-secret-here

docker compose -f docker-compose.quickstart.yml up -d

Open http://localhost:5000. The first user to register becomes admin. Go to Settings → General to pull an LLM model — qwen3:8b or llama3.1:8b are good starting points.

GPU: Ollama runs CPU-only by default. See the comments in docker-compose.quickstart.yml to enable NVIDIA GPU passthrough.

Development: To build from source, see Development.

Documentation

Doc Contents
Architecture Stack, design decisions, data models, key services
Configuration Environment variables, Docker Compose, production setup, security
Features Detailed feature breakdown and keyboard shortcuts
Development Dev workflow, CI/CD, migrations, release process
API Keys & MCP API key management and Fable MCP install guide
SSO / OAuth OIDC setup for Authentik, Keycloak, and other providers
API Reference All REST API endpoints
Android App Flutter companion app architecture and feature status

License

This project is privately maintained.

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