New end-to-end pipeline that walks every markers.json in the reach and
fills empty `name` fields using the Gemma 2 voice pipeline via
`sr-voice serve --stdio`. Per D-191 §4: the same Gemma 2 pipeline the
client uses for NPC voicing also produces the atlas content, which is
dual-purposed as a quality test of the LLM plumbing.
Pipeline per body (hop-ordered, core-first):
1. Load markers.json; identify feature records whose `name` is
blank (null or ""). Hand-authored names are never overwritten;
the 6 template bodies and any partial authoring stay put.
2. Look up body context (planet_class, settlement_pattern,
cultural_corridor, population, economic_role) from systems.db.
3. Build a short corridor-aware few-shot prompt per feature type.
Prompts carry 3 concrete `Style: X. Answer: Y` examples so
Gemma 2 2B completes a pattern instead of generating to an
open-ended instruction — this is the single biggest lever
against placeholder echoes on a small model.
4. Stream the prompt into a long-lived sr-voice subprocess, read
the JSONL response, post-process (strip markdown, label
prefixes, brackets, reject 5+ word outputs and placeholder
tokens), check the earth-name blocklist, check per-(corridor,
feature_type) + per-body dedup, check the per-stem cap, retry
up to 3 times with a bumped seed.
5. On persistent failure, fall back to a deterministic palette
generator so every feature ends up with a name.
6. Write markers.json atomically and refresh atlas_* DB rows via
sync_markers_to_db. Commit the DB per body so a crash loses
at most one body of state.
7. Restart the sr-voice subprocess every `--refresh` requests
(default: 200) to prevent KV-cache context bleed.
Core design decisions:
- Determinism: per-(world_seed, body_id, feature_local_id, attempt)
seed so the full run is reproducible.
- Ordering: bodies are processed in ascending `hop_distance_from_gateway`
so core bodies get first pick at every unique Gemma output and
outer sectors fall into the palette fallback when they lose the
dedup race.
- Dedup scope: (cultural_corridor, feature_type) across the run,
PLUS a per-body cross-type set so the same name can't be a river
AND an ocean AND a mountain on the same world. Hand-authored names
are seeded into both sets on load so templates win priority.
- Stem cap: each non-generic root token (e.g. 'Arcturus', 'Meridian')
may appear at most `--stem-cap` times across the full run (default
20), preventing single-word runaway. Fallback names bypass the cap.
- Earth blocklist: 181 curated entries covering major Earth cities,
mountains, rivers, oceans, historical/colonial spellings, and
Greek/Roman mythology that reads too literally. Prefixed variants
('Nouveau Paris', 'New Tokyo') explicitly allowed per the product
intent that Earth-echo names are fine but must not dominate.
Leading 'The ' is stripped before comparison so 'The Great Divide'
also matches.
Operational features:
- `--shard N/M` slices the body list into M partitions for parallel
runs. Two terminals × `--shard 0/2` + `--shard 1/2` fits the
~2.5 GB/instance VRAM footprint twice under the 50% cap on a
16 GB AMD GPU and roughly halves wall time.
- `--log PATH` writes a timestamped tee of every status line to a
file. Default: `.tmp/gemma_naming.shard{N}of{M}.log` when a
non-trivial shard is in use.
- SQLite `PRAGMA journal_mode=WAL` + `busy_timeout=15000` so two
concurrent shards serialize writes without lock errors.
- Per-body progress lines report `body K/N`, `sys K/N`, and
`hop=H` so the user can watch core sectors finish first.
- Each body logs the new names it produced per feature type so the
user can eyeball quality as the run progresses.
- Checkpoint summary every 25 bodies: cumulative names, rate,
ETA — gives the log regular scroll points.
- `--mock` uses `server/sr-voice/mock-stdio.sh` for dry-fire
pipeline validation without a model load (tested end-to-end).
Supporting files:
- `tooling/planet-gen/earth_blocklist.txt` — 181 curated entries.
- `tooling/db/backfill_cultural_corridor.py` — one-off migration
that fills the `cultural_corridor` column on both `star_systems`
and `bodies` from the `geographic_sector` values. Before this
pass, 99.4% of rows (3221/3240) had a NULL cultural_corridor
despite `wiki_sync.py` being aware of the column — the wiki
index.md files only carry the sector header, which was never
propagated to the DB column. Idempotent, safe to re-run after
any wiki_sync rebuild, explicit transaction wrapper with
rollback on failure.
Full batch runtime estimate: ~20 hours single-shard / ~10 hours
double-shard on this hardware. Smoke tests across five hardened
iterations (v1–v5) on GJ71b/c/d/d-1/e confirm the pipeline produces
clean, varied, culturally-coherent names with zero post-processing
residue.
jpmschweitzer
1efbbcaea9