Implement Sophia MVP stages 4-7 (introspection, queries, persistence, polish)

Brings the system from "engrams cluster + form synapses" to a complete
end-to-end demo: ingest text, watch it cluster, ask questions, restart
with state intact.

- Stage 4: birth introspection (taxonomy/goals/open_questions via LLM,
  bounded by the global parallel-op semaphore), per-engram memory log,
  click-to-inspect side panel.
- Stage 5: queries as conversations. POST /api/galaxy/:id/query embeds
  the question, materializes a pinned Query-Engram at the donut center,
  runs broadcast retrieval (global cosine scan + 1-hop synaptic
  expansion with attenuation) and fans out responder LLM calls. The
  integrator runs every 2s on accumulated snippets and streams the
  refining answer back over SSE; responders briefly transition to
  Conversing on the WS bus so the right dots light up.
- Stage 6: snapshot persistence. sled-backed store keyed by galaxy id,
  JSON-encoded values (bincode chokes on internally-tagged enums like
  Manifest/MemoryKind), 60s periodic snapshot task, hydrate-on-boot,
  DELETE /api/galaxy/:id wired through. State survives kill -9.
- Stage 7: HUD additions (sim ticks/sec, LLM queue depth, FPS) via a
  new GET /api/stats polled at 1Hz. `sophia demo` subcommand boots the
  server then auto-ingests a 50-paragraph corpus baked into the binary
  with include_str!. README quickstart added.

Token caps for query_responder/integrator bumped (gemma-4-e4b is a
thinking model — output budget must cover hidden reasoning + visible
answer, otherwise content comes back empty). Pinned engrams skip
physics; their tick scheduling is also skipped at materialization so
they stay perfectly still at the donut center.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

config.toml

@@ -6,6 +6,14 @@ host       = "127.0.0.1"
 port       = 7777
 static_dir = "web/dist"
 
+# Persistence (Stage 6). `data_dir` is a directory; sled creates and manages
+# files inside it. Snapshots are written every `snapshot_interval_secs`
+# while the server runs; on boot any existing galaxy snapshots are loaded
+# and re-instantiated in the sim.
+[storage]
+data_dir              = "data"
+snapshot_interval_secs = 60
+
 [lm_studio]
 # LM Studio's OpenAI-compatible REST endpoint.
 base_url        = "http://127.0.0.1:1234/v1"
@@ -35,16 +43,21 @@ major_radius = 100.0
 minor_radius = 30.0
 
 # Caveman token caps per §13.5.
+# Note: gemma-4-e4b is a *thinking* model — it emits a hidden reasoning
+# stream before its visible content. Every `_out` cap therefore needs to
+# budget for the hidden reasoning *plus* the visible answer. Numbers
+# verified against logs: a 150-cap responder hit "response had no content"
+# every time (all budget eaten by reasoning).
 [token_caps]
-introspection_in    = 400
-introspection_out   = 200
+introspection_in    = 600
+introspection_out   = 900
 peer_msg_in         = 100
 peer_msg_out        = 100
 synthesis_in        = 300
 synthesis_out       = 80
-query_responder_in  = 200
-query_responder_out = 150
-query_integrator_in = 800
-query_integrator_out = 300
-hard_ceiling_in     = 1024
-hard_ceiling_out    = 400
+query_responder_in  = 400
+query_responder_out = 700
+query_integrator_in = 1200
+query_integrator_out = 1200
+hard_ceiling_in     = 1500
+hard_ceiling_out    = 1500