Upload a recording (audio, or video with the camera off), get a private Swedish transcript, and chat about it.
- ADR-033: RLS-scoped private transcript store; ffprobe/ffmpeg intake; gateway transcription (iguana kb-whisper, berget fallback); in-process single-replica worker; chat over the transcript (local models only).
- ADR-034: optional two-engine mode (pianissimo + kb-whisper) reconciled by a LOCAL model; off unless TAPIR_RECONCILE_BASE_MODEL is set.
- ADR-035: real progress (phases, running/quiet/lost), phase logging, every judged spot stored, merged segments.
- Hardening from four adversarial reviews: errors logged and stored as kinds never text; per-engine deadlines; converted-length check; bounded queue; client hang-ups are not errors; strict local-alias check.
- Dockerfile: static ffmpeg/ffprobe 7.0.2 pinned by sha256 (#34). Built and inspected by hand; CI does not build the image on a PR, so its first CI build is this merge.
Uploads stay OFF until TAPIR_UPLOADS_ENABLED is set in the deployment.
Closes#33, #34, #42, #43, #44.
Co-authored-by: Mathias <mthbqv@gmail.com>
WithUsageHook callback fires with model + prompt/completion tokens parsed from the
response usage block. Keeps the copied stdlib-only llm package decoupled from
metrics (ADR-004) — the caller wires it to internal/metrics. TDD covered.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The first friendly-pilot live run produced zero summaries: koala/phi4-mini hit
three silent failure modes — 8k context overflow on long transcripts (HTTP 400),
intermittent malformed JSON (highlights as a bare string), and no fallback wired
at all (summarizer.New(primary, nil)).
Keep phi4-mini as the fast primary and add resilience around it:
- Ordered endpoint chain (summarizer.NewChain): phi4-mini → koala/phi4-14b
(local) → berget/mistral-small (worst-case external). All reached through the
one LiteLLM gateway by alias.
- A parse failure now advances the chain like a transport error — the old
Primary→Fallback shape returned the parse error without trying anyone else.
- Tolerant parse: highlights/takeaways coerce string→[]string, absorbing the
common small-model quirk without spending a fallback round-trip.
- Transcript truncation (TAPIR_MAX_TRANSCRIPT_CHARS=18000) prevents the overflow
rather than recovering from it; validated to fit phi4-mini's 8k window.
- Bounded completion budget (TAPIR_SUMMARY_MAX_TOKENS=1500) — the old 8192 budget
itself contributed to the overflow.
Local-first guarantee preserved by ordering: external endpoint is tried only
after every local one fails. TAPIR_CLOUD_FALLBACK_MODEL="" disables it entirely
for client/NDA deployments.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The copied OpenAI-compatible client sent no max_tokens. Thinking models
(qwen3, deepseek-r1) spend their budget on the reasoning trace and return
EMPTY content when max_tokens is unset, which the summarizer treats as an
error. ADR-004 says change Tapir's copy rather than the hyperguild upstream,
so set a generous default (8192) leaving room for both reasoning and output.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Copy hyperguild/ingestion/internal/llm into internal/adapters/llm and own it.
Tapir owes that repo nothing at the dependency level — no module dep added.
Router gives the local-Primary -> BYO-Fallback path needed for ai_routing.feature.
Copied tests rewritten from testify to stdlib testing to keep go.mod
dependency-free (repo has zero deps; acceptance tests are stdlib too).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
mathiasandClaude Sonnet 5.5