Full ActivityPub implementation wired to cf-core.activitypub module:
Endpoints (root-level, not under /api/v1):
GET /.well-known/webfinger — WebFinger JRD (AP_ENABLED only)
GET /ap/actor — Instance actor document
POST /ap/actor/inbox — Incoming Follow/Undo (dedup + Accept dispatch)
GET /ap/outbox — OrderedCollection of community posts
GET /ap/posts/{slug} — Individual AP Note
GET /ap/followers — Follower count collection
GET /ap/following — Empty following collection
Mastodon OAuth (under /api/v1/social/mastodon/):
POST /connect — Dynamic app registration + OAuth flow start
GET /callback — Code exchange + token storage (Fernet-encrypted)
DELETE /disconnect — Token revocation
GET /status — Connection status
Config: AP_ENABLED, AP_HOST, AP_KEY_PATH, AP_TOKEN_ENCRYPTION_KEY
Migration 042: ap_followers, ap_deliveries, ap_received, mastodon_tokens tables
Key manager: auto-generates RSA-2048 keypair on first boot if AP_ENABLED
Delivery service: deliver_to_followers() with 3-retry exponential backoff + DB log
Post publish: background fan-out to AP followers + Mastodon when opted-in
All AP endpoints gracefully degrade (404) when AP_ENABLED=false.
Multiple concurrent users browsing the 3.2M recipe corpus would cause FTS5 page
cache contention and slow per-request queries. Solution: pre-compute counts for
all category/subcategory keyword sets into a small SQLite cache.
- browse_counts_cache.py: refresh(), load_into_memory(), is_stale() helpers
- config.py: BROWSE_COUNTS_PATH setting (default DATA_DIR/browse_counts.db)
- main.py: warms in-memory cache on startup; runs nightly refresh task every 24h
- infer_recipe_tags.py: auto-refreshes cache after a successful tag run so the
app picks up updated FTS counts without a restart
Switches to OrchestratedScheduler in cloud mode so concurrent recipe_llm
jobs fan out across all registered cf-orch GPU nodes instead of serializing
on one. Under load this eliminates poll timeouts from queue backup.
USE_ORCH_SCHEDULER env var gives explicit control independent of CLOUD_MODE:
unset follow CLOUD_MODE (cloud=orch, local=local)
true OrchestratedScheduler always (e.g. multi-GPU local rig)
false LocalScheduler always (e.g. cloud single-GPU dev instance)
ImportError fallback: if circuitforge_orch is not installed and orch is
requested, logs a warning and falls back to LocalScheduler gracefully.
Add E2E_TEST_USER_ID setting (opt-in via env); session bootstrap logs
at DEBUG instead of INFO for the known test user so test runs don't
inflate session counts. Still visible with DEBUG=true.
- .env.example: document ANTHROPIC_API_KEY, OPENAI_API_KEY, OLLAMA_HOST,
OLLAMA_MODEL, CF_ORCH_URL, CF_LICENSE_KEY with usage comments
- config.py: expose CF_LICENSE_KEY in Settings for startup visibility
- pyproject.toml: pin circuitforge-core >= 0.6.0 (env-var auto-config +
CFOrchClient bearer auth land in 0.6.0)
Bare-metal self-hosters can now run Kiwi with only OLLAMA_HOST set and
zero yaml config. Paid+ users set CF_ORCH_URL + CF_LICENSE_KEY for
managed cloud GPU inference.
