Pin the NL->structured translation to a small, fast model that can stay
co-resident with CLIP (and the chat model) so it never evicts them on a tight
VRAM budget. Precedence: UNIFIED_SEARCH_MODEL env > client-selected model >
configured default. Logs the effective model (backend.model()) so model A/B
tests are visible. Documented in .env.example.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Nothing reaped reels before, so the on-disk cache and ledger grew
unbounded — each night's daily reel is a new ~4MB file + ledger row that's
stale within ~26h.
- Pre-gen self-prune: after recording a reel, prune_superseded keeps the
newest PREGEN_KEEP_PER_SCOPE (2) rows per (span, library) and unlinks the
superseded reels' mp4+sidecar. Caps the ledger/disk at ~spans×libraries×2.
- On-disk sweeper (spawn_reel_cache_sweeper): every 24h, removes reel mp4s
with no ledger row and no live job older than REEL_CACHE_MAX_AGE_DAYS (7) —
bounding the on-demand cache, which has no ledger row and otherwise grows
forever — plus crashed-render cruft (.mp4.tmp/.concat.txt/orphan sidecars).
Runs regardless of REEL_PREGEN_ENABLED; disable with REEL_CACHE_SWEEP_ENABLED=0.
- New DAO methods prune_superseded + all_cache_keys (with tests); env knobs
documented in .env.example.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Implement end-to-end nightly pre-generation of memory reels with agentic
scripting that grounds narration in calendar, location, messages, and RAG.
Sections A-E from the plan:
A. Extract produce_reel pipeline core from run_reel_job with
ScripterMode::Fast/Agentic and progress callbacks.
B. Agentic scripter: factor run_readonly_tool_loop from the insight
generator, build read-only tool gate, prompt builder with GPS, and
generate_script_agentic with fallback to fast path.
C. Precomputed reels ledger (SQLite table + DAO), GET /reels/precomputed
handler with validity gate, GET /reels/by-key/{key}/video streaming,
and normalize_library_key helper.
D. Nightly scheduler: spawn_pregen_scheduler with configurable hour,
run_pregen_batch (day/week/month spans), pregen_one with dedup and
disk-check, secs_until_next_run_hour time math.
E. user_ai_prefs passive mirror table + DAO for param capture in
create_reel_handler and replay in the scheduler.
Also fixes resolve_library_param signature to take &[Library] and adds
resolve_library_param_state wrapper for AppState callers.
New files: migrations/2026-06-13-000000_add_precomputed_reels/,
migrations/2026-06-13-000010_add_user_ai_prefs/,
src/database/precomputed_reel_dao.rs,
src/database/user_ai_prefs_dao.rs
Long insights are chunked + synthesized server-side and can run past the shared
180s chat/embedding client timeout, causing spurious timeouts. /tts/speech now
uses a per-request timeout from LLAMA_SWAP_TTS_REQUEST_TIMEOUT_SECONDS
(default 600), overriding the client default without affecting chat/embeddings.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Chatterbox validates the reference clip by file extension and rejects formats
like .aac/.opus. Always transcode the reference (upload bytes and library
files alike) to mono 24 kHz WAV with ffmpeg before forwarding, so any source
format is accepted and the from-library audio/video paths are unified.
The reference length cap is now configurable via LLAMA_SWAP_TTS_REF_SECONDS
(default 30) — Chatterbox is zero-shot, so a clean ~10-20s clip is the sweet
spot. Drops the now-unused mime guesser.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Adds the /tts/speech and /tts/voices* endpoints plus LLAMA_SWAP_TTS_MODEL /
LLAMA_SWAP_TTS_VOICE (TTS only needs LLAMA_SWAP_URL, not LLM_BACKEND=llamacpp).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
llamacpp models now receive images directly instead of
describe-then-inline. LLAMA_SWAP_VISION_MODEL defaults to the
primary model. Document the ResolvedBackend dispatch pattern.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Reverts the per-request backend="llamacpp" value. Chat/vision/embedding
backend is now a deploy-time decision (LLM_BACKEND=ollama|llamacpp),
applied globally across chat, vision describe, and embeddings — so
embedding vectors stay in one space across the index.
- Per-request backend whitelist back to "local"|"hybrid". A request
arriving with backend="llamacpp" is rejected.
- LLM_BACKEND=llamacpp swaps the entire local stack to llama-swap:
chat hits the chat slot, describe hits the vision slot, embeddings
hit the embed slot. Hybrid mode still routes chat to OpenRouter
but uses LLM_BACKEND for the describe pass.
- Drops env vars HYBRID_VISION_BACKEND, LLAMA_SWAP_VISION_MODELS,
EMBEDDING_BACKEND (the last never shipped). Drops the
LlamaCppClient.vision_models allowlist — capability inference now
reports has_vision only for the configured vision_model slot.
- Drops the /insights/llamacpp/models handler. /insights/models is
the single endpoint; returns Ollama servers under LLM_BACKEND=ollama
and llama-swap slots (from LLAMA_SWAP_ALLOWED_MODELS) under
LLM_BACKEND=llamacpp. Same envelope shape either way.
- New ai::embed_one helper routes embeddings through llama-swap when
LLM_BACKEND=llamacpp (else Ollama). Wires it into the four
insight_generator embedding sites.
- Cross-replay matrix simplifies to pre-llamacpp shape (local↔local,
hybrid↔hybrid, hybrid→local allowed; local→hybrid rejected).
APOLLO_CLIP_API_BASE_URL (falls back to APOLLO_API_BASE_URL),
CLIP_BACKLOG_MAX_PER_TICK, CLIP_ENCODE_CONCURRENCY, and
CLIP_REQUEST_TIMEOUT_SEC — all of which the code already reads.
Apollo's side was documented earlier; this closes the parity gap.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The face-recognition plan and CLAUDE.md document the full env-var
surface (face detection knobs, Apollo / Ollama / OpenRouter / SMS
integrations, watch intervals, RAG flags), but no example file
existed — operators copying the project to a new deploy had nothing
to start from. Group by section, comment out optional integrations
so a minimal copy boots without external services.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Cameron Cordes