Reader + watch/skip/save (instruments the Stage-0 'acts on a summary' metric),
HTMX+Templ over the existing store, Dex OIDC login with single-user allowlist
authz (authn now, tenancy deferred), deployed at tapir.d-ma.be via Flux GitOps
with ESO secrets and in-cluster postgres18. Build decomposed into 4 gated lanes.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Vimeo texttracks API is owner-only (worse than YouTube, no public timedtext) → defer.
Whisper viable as a no-caption fallback; berget/whisper-large-v3 already on the gateway
(cloud), local options on iguana/koala carry setup+GPU-contention cost (ADR-007). Both
investigated inline (session sub-agents are network-sandboxed).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
main.go dispatches `tapir auth` (interactive OAuth → persist refresh token via
SecretStore) and `tapir run` (wire YouTube source + local summarizer + store
sink, build engine, run the dedup-aware loop). Config-driven so live creds plug
in at demo time; SIGINT stops the loop cleanly. Block kept minimal so Worker E's
list/show cases union cleanly at merge.
Add .env.example documenting every TAPIR_* var and a README demo runbook. Pin
the summarizer alias-as-config decision and record the max_tokens fix in
docs/homelab-integration.md (clears two `confirm` items).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Implement ports.Summarizer in internal/adapters/summarizer. It routes through a
local Primary endpoint first and an optional BYO Fallback, owning the routing
itself (not delegating to llm.Router) so it can record AIProvider, AIModel, and
FallbackUsed on domain.Summary. Prompt asks for JSON {summary, highlights,
takeaways}; the parser tolerates thinking-model fences/reasoning and rejects an
empty summary.
The summarizer is the single egress point for content toward an AI model, so it
enforces the local-first guarantee from ai_routing.feature: with no BYO
configured (nil fallback) there is no external endpoint, so content reaches the
local stack and nowhere else. Tests assert all four scenarios via a fake client.
Model alias is config (TAPIR_SUMMARIZER_MODEL, host/name) — not hardcoded;
docs/homelab-integration.md notes it stays `confirm` and that thinking models
need an explicit max_tokens or they return empty content.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Conductor verified against the live koala k3s cluster before launching the
adapter workers: LiteLLM is in ns ai-stack, ClusterIP 10.43.159.89:4000,
off-cluster NodePort 30401. The doc's 31234 was actually llama-swap. Also
flag that sk-local-123 now 401s — use LITELLM_MASTER_KEY from the vault.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Lists the egress the build assumes (Go module proxy, toolchain download,
raw.githubusercontent for golangci-lint, github for non-proxied modules) and the
runtime assumes (LiteLLM gateway, brain-mcp, YouTube/Vimeo APIs, per-user BYO-AI
hosts only on opt-in), so a locked-down koala act_runner or dev env knows what to
allow or which GOPROXY to set. Notes the claude.ai sandbox allowlist is separate
and unrelated.
Gherkin spec for connecting YouTube/Vimeo accounts and configuring optional
per-provider BYO AI credentials: connections sync subscriptions, tokens/keys are
stored only as secret references (never in the clear), revocation stops watching
but preserves history. Encodes the secrets-by-reference and data-isolation
guardrails (ADR-002, ADR-006, data-model).
Gherkin spec for the routing guardrail: local produces the summary by default;
on local failure, fall back only to a user-configured BYO provider; with no BYO,
queue for retry and never send content to a third-party model. Encodes the
local-first/user-owned principle (VISION) as executable behavior.
Gherkin spec for the core use case: captioned video is summarized and delivered;
no-transcript video is recorded as skipped; unsubscribed channels are ignored;
already-summarized videos are not reprocessed. These scenarios seed the use-case
test suite (Clean Architecture core tested through fake adapters).
Per-user-isolated entities (no global cross-tenant video table per the S5/grill
correction), secrets stored by reference only (ESO/1Password, never the token),
brain delivery modelled as a sink_delivery row rather than brain-specific tables.
fallback_used recorded per summary as the Stage 0 quality signal. Future C dedup
and sharding explicitly out of scope.
Context and container diagrams, sequence diagrams for the core summarize-new-video
use case and the local-first/BYO AI routing fallback, and the Clean Architecture
layering. Ports & adapters keep the engine provider- and sink-agnostic, making
standalone-vs-homelab a wiring choice (ADR-003), not two codebases.
mathiasandClaude Opus 4.8