README: update to v0.1.5 live status, PPTX extraction, Gitea, ops notes

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

README.md

@@ -38,7 +38,7 @@ StartOS box (control plane, no GPU)            DGX Spark(s)
 ┌────────────────────────────────────┐         ┌───────────────────────────────┐
 │ FastAPI dashboard + job runner      │  SSH    │ per-job Docker network        │
 │  • inbox/<company-slug>/ (decks)    │ ───────▶│   (──internal in airgapped)   │
-│  • extract text (PDF/DOCX/TXT/MD)   │  rsync  │  ┌─────────┐  ┌────────────┐  │
+│  • extract text (PDF/PPTX/DOCX/…)   │  rsync  │  ┌─────────┐  ┌────────────┐  │
 │  • plan model "waves"               │ ───────▶│  │ vLLM(s) │◀─│ LiteLLM     │  │
 │  • extractor → graders → adjudicator│         │  └─────────┘  │ router      │  │
 │  • deterministic composite scorer   │◀─────── │  ┌──────────────┐  ▲         │  │
@@ -68,8 +68,18 @@ StartOS box (control plane, no GPU)            DGX Spark(s)
 Configure Sparks → Test Spark Connection → Configure Models → Configure Graders
 → Configure Grading (rubric, air-gap, weights) → Configure Companies (slugs,
 KPI aliases, pinned targets — especially profitability thresholds) → drop decks
-into `inbox/<company-slug>/2026-Q2-deck.pdf` → **Grade Decks** → watch the
+into `inbox/<company-slug>/` → **Grade Decks** → watch the dashboard.
-dashboard.
+
+Two operational notes:
+
+- **Deck filenames must contain the period with the year** — e.g.
+  `Board Deck - Q4 2025.pdf` parses; a bare `Q4` does not. Periods are
+  canonicalized (`2025-Q4`, `2026-H1`, `2026-05`, `FY2026`) and drive the
+  forecast-target chaining between consecutive decks.
+- If a Spark already runs resident vLLM containers, list their names in
+  **Configure Grading → `preJobStopContainers`** — they are docker-stopped on
+  the head Spark at job start to free GPU memory (and deliberately *not*
+  restarted afterward; re-warm them from whatever job owns them).
 
 ## Repo layout
 
@@ -82,7 +92,7 @@ orchestrator/       The control-plane app (Python)
   serving.py        vLLM + LiteLLM router on the Sparks, in waves
   graders.py        launch the grading panel
   adjudicator.py    the local lead grader
-  extraction.py     PDF/DOCX/TXT/MD → text (on the StartOS box)
+  extraction.py     PDF/PPTX/DOCX/TXT/MD → text (on the StartOS box)
   preflight.py      probe models before launching graders
   spark_client.py   SSH/rsync helpers
   bdef.md           the baked-in BDEF v1.1 rubric
@@ -93,17 +103,39 @@ sandbox/            grader image (built ON the Spark, not packed in the s9pk)
 
 ## Build
 
-GitHub CI (`.github/workflows/build.yml`) or a local build with `start-cli`
+Local build with `start-cli` (on a Mac: colima + start-cli in a VM — see the
-(see the s9pk-build-on-mac recipe). The vLLM and grader images are built **on
+s9pk-build-on-mac recipe). The vLLM and grader images are built **on the
-the Sparks**, not packed into the `.s9pk`.
+Sparks**, not packed into the `.s9pk`:
+
+- `boardroom-vllm:latest` — the vLLM serving image with `ENTRYPOINT []`
+  (serving.py passes the full `vllm serve …` command as the container CMD).
+- `boardroom-grader:latest` — from `sandbox/build.sh`.
 
 ```
 npm ci && npm run check && npm run build   # type-check + bundle
 make                                        # pack the .s9pk (needs start-cli)
 ```
 
+Canonical repo: `https://gitea.ten31.ai/Ten31AI/boardroom-map`.
+
 ## Status
 
-v0.1 — source complete, `tsc`-clean and Python-syntax-clean. Not yet validated
+**v0.1.5 — live in production.** Deployed on a StartOS box driving a DGX Spark
-against live Sparks. HF model pre-pull on the head Spark is required for
+in single-spark air-gapped mode (gemma-4-31B panel: munger-lens /
-air-gapped runs.
+girdley-operator / buffett-owner). First full grading run completed
+2026-07-29: a three-deck company history graded end-to-end into a running
+ledger with quarter-over-quarter forecast chaining.
+
+Version history: v0.1.1 fixed config persistence (absolute `/media/startos/…`
+paths — relative paths resolved into an ephemeral cwd); v0.1.2 added
+`preJobStopContainers`; v0.1.3 hardened preflight (authed model probes,
+poll-until-loaded, crash fast-fail); v0.1.4 fixed air-gapped serving
+(`HF_HUB_OFFLINE` — the `--internal` network has no DNS) and raised grader
+timeouts for ~3.6 tok/s local generation; v0.1.5 fixed the dashboard viewer
+(stays open across background refresh) and added report/JSON/scorecard
+downloads.
+
+Known optimization not yet done: the wave is torn down per deck, so the 31B
+reloads from disk (~6 min) between decks even when the model set is unchanged.
+
+HF model pre-pull on the head Spark is required for air-gapped runs.