docs: refresh droplet runbook for May 9 state

- Mark scripts/update_hf_env.sh + scripts/redeploy.sh as landed (was a 'gap')
- Add RIPRAP_NYCHA_REGISTERS=1 to the post-redeploy env block (without
it the FSM never attaches step_nycha / step_doe_schools / step_doh_hospitals)
- Document the May 9 source-committed droplet fixes:
* _build_chip_tensor 5-D handling for eo_chip_cache chips
* TerraMind synthesis adapter via /v1/terramind dispatch
Both inherit on destroy + redeploy via scripts/deploy_droplet.sh
- Bump 'Last verified' to 2026-05-09 with all three terramind paths
+ prithvi_eo_live confirmed firing in the live trace

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

docs/DROPLET-RUNBOOK.md

@@ -1,6 +1,13 @@
 # Droplet Runbook
 
-_Last verified: 2026-05-06 (live introspection of droplet 569363721)_
+_Last verified: 2026-05-09 (terramind synthesis + LoRA adapters confirmed firing live)_
+
+> **Quick redeploy:** `HF_TOKEN=<write-token> scripts/redeploy.sh <new-droplet-ip>`
+> generates a fresh bearer token, builds + brings up vLLM + riprap-models, updates
+> the HF Space env vars, restarts the Space, and runs the end-to-end probe.
+> Source-committed fixes (e.g. the May 9 terramind chip-tensor + synthesis
+> patches) are inherited automatically because `deploy_droplet.sh` tars
+> `services/riprap-models/` from this repo at run time.
 
 ## Spec
 
@@ -44,9 +51,11 @@ be a leftover placeholder, not load-bearing for Riprap.
 | `scripts/save_droplet_image.sh` | Commits the running container, saves + compresses to a local tarball via scp. Useful as a fallback if the public-base Dockerfile rebuild fails. | Complete but **moot** once the bootstrap droplet is destroyed — requires a live droplet to extract from. |
 | `scripts/probe_addresses.py` | End-to-end test against `/api/agent/stream` on the HF Space. 5/5 must pass before merging. | Not a droplet-setup script; it tests the full system end-to-end. |
 
-**Gap:** No `update_hf_env.sh` exists. Updating HF Space env vars after a redeploy (new IP
-or new token) is a manual `huggingface-cli space variables` command — see §Required
-secrets below. This would be a good script to add.
+_Previously a gap; now landed:_ `scripts/update_hf_env.sh` automates updating HF
+Space variables (`RIPRAP_LLM_BASE_URL`, `RIPRAP_ML_BASE_URL`, `RIPRAP_NYCHA_REGISTERS`,
+etc.) and restarting the Space. `scripts/redeploy.sh` orchestrates the three-step
+sequence (deploy droplet → update HF Space env → run end-to-end probe) into one
+command.
 
 **Gap:** No `redeploy.sh` wrapper exists. `deploy_droplet.sh` handles bring-up on a fresh
 droplet but does not handle the HF Space variable update or the post-deploy probe run.
@@ -354,11 +363,17 @@ huggingface-cli space variables \
   RIPRAP_LLM_API_KEY="$TOKEN" \
   RIPRAP_ML_BACKEND=remote \
   RIPRAP_ML_BASE_URL="http://${NEW_IP}:${MODELS_PORT}" \
-  RIPRAP_ML_API_KEY="$TOKEN"
+  RIPRAP_ML_API_KEY="$TOKEN" \
+  RIPRAP_NYCHA_REGISTERS=1
 
 huggingface-cli space restart lablab-ai-amd-developer-hackathon/riprap-nyc
 ```
 
+`RIPRAP_NYCHA_REGISTERS=1` is required for the FSM to attach `step_nycha`,
+`step_doe_schools`, `step_doh_hospitals` — without it, the Keystone Stone is
+missing those three specialists in the per-query trace. (`scripts/update_hf_env.sh`
+sets this automatically.)
+
 ## Health check
 
 Two curl commands that confirm both services are live:
@@ -390,12 +405,32 @@ For a full end-to-end check via the HF Space:
 # Want: 5/5 PASS
 ```
 
-## Gaps in existing scripts
+## Source-committed droplet fixes (May 9 2026)
+
+Two patches landed in `services/riprap-models/main.py` after a live debugging
+session against a running droplet. They are committed to source, so the next
+`scripts/deploy_droplet.sh` (or `scripts/redeploy.sh`) bring-up will inherit
+them automatically — the build context is tarred from this repo at run time.
+
+| Patch | Problem | Fix |
+|-------|---------|-----|
+| `_build_chip_tensor` shape handling | The HF Space's `eo_chip_cache` ships chips at `(B, C, T, H, W)` 5-D; the droplet assumed `(C, H, W)` 3-D and called `.unsqueeze(1).repeat(1, 4, 1, 1)`, raising `RuntimeError: Number of dimensions of repeat dims can not be smaller than number of dimensions of tensor`. Every TerraMind LoRA request silently failed. | `_build_chip_tensor` now branches on `ndim`: 5-D passes through, 4-D adds batch, 3-D expands to T=4 and adds batch. |
+| TerraMind synthesis remote dispatch | `_terramind_inference` only knew `lulc` / `buildings` adapters. `synthesis` (the IBM/NASA v1 base DEM→LULC generative path) had no remote handler, so the HF specialist always fell through to its local terratorch path and crashed on `torchvision::nms` (HF's CPU torch can't load torchvision's C extension). | `_TERRAMIND_SPECS["synthesis"]` + `_load_terramind_synthesis` (FULL_MODEL_REGISTRY build of `terratorch_terramind_v1_base_generate`) + `_terramind_synthesis_inference` (DEM-only 4-D input, 10-class ESRI LULC output). `TerramindIn` schema relaxed so `s2` is optional. |
+
+After a destroy + redeploy you can verify both with:
+
+```bash
+# Beach Channel single-address — single_address full activation
+.venv/bin/python scripts/probe_addresses.py \
+  --base https://lablab-ai-amd-developer-hackathon-riprap-nyc.hf.space \
+  --addresses "2508 Beach Channel Drive, Queens" \
+  --timeout 240
+```
 
-| Missing script | What it needs to do |
-|----------------|---------------------|
-| `scripts/update_hf_env.sh` | Accept `<ip> <token>` args, run `huggingface-cli space variables` to update `RIPRAP_LLM_BASE_URL`, `RIPRAP_LLM_API_KEY`, `RIPRAP_ML_BASE_URL`, `RIPRAP_ML_API_KEY`, then restart the Space. Called as the last step after a successful `deploy_droplet.sh`. |
-| `scripts/redeploy.sh` | Thin orchestrator: generate a fresh token, call `deploy_droplet.sh <ip> <token>`, then call `update_hf_env.sh <ip> <token>`, then run `probe_addresses.py` against the live Space to confirm 5/5. Reduces a 4-step redeploy to one command. |
+Want all three TerraMind paths firing in the trace (`terramind_lulc`,
+`terramind_buildings`, `terramind_synthesis`) along with `prithvi_eo_live`
+and `eo_chip_fetch`. All four EO specialists lazy-load on first request,
+so the first probe pays cold-load (~30-90 s); subsequent probes are warm.
 
 `save_droplet_image.sh` is complete but only useful while a working droplet is alive.
 The bootstrap droplet was destroyed 2026-05-06; this script cannot recover from that.