Claude/add palantir dashboard 3 mn on - #16
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- Copy aiwar_graph.json (221 nodes, 356 edges) to cockpit/public/ - Generate aiwar_weapons.json (51 weapons from CSV) for table view - useAiwarData now fetches from /aiwar_graph.json and /aiwar_weapons.json - PalantirApp shows loading spinner during data fetch - AiwarExplorer shows actual CSV weapons in table view (Weapon, Year, Used By, Military Purpose, Source) — the "innocent" academic data - Graph view shows full 221-node graph with vis-network - Selecting a weapon and clicking "Reason About This" surfaces enrichment data through NARS inference display https://claude.ai/code/session_01CSQk1MF3fbRxGf9r4WfEpa
Instead of a sparse card-based landing page, / now renders the same Palantir glass morphism cockpit (topbar, left rail, graph, table, cells, status bar) — just loaded with the 221-node aiwar graph instead of the 24-node infrastructure seed data. The Inspector panel is replaced with NarsPanel for NARS reasoning. Select any weapon system and click "Reason About This" to surface enrichment connections. Link to /demo in the top bar for the infrastructure demo. https://claude.ai/code/session_01CSQk1MF3fbRxGf9r4WfEpa
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AdaWorldAPI
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…he prototype
Ports scripts/garmin_proto.py — the validated Grand Canyon decoder — into a
dep-free, pure-std `geo/src/garmin/` module. Four stages, one submodule each:
- container.rs — the IMG container: XOR de-obfuscation, the 512-byte FAT from
0x600, and multi-part subfile reassembly (blocks concatenated in part*240+i
order) → named `name.TYPE` byte slices.
- tre.rs — the TRE: N/E/S/W int24 bbox, the LOD level pyramid, and the
subdivision tree (16-byte records, 14-byte on the most-detailed level).
- rgn.rs — the RGN: points / indexed-points / polylines / polygons, including
the LSB-first delta bitstream with QMapShack CShiftReg continuation +
sign semantics (the marker naive decoders drop, which turns fine levels into
random-walk mush — the plan's documented level-4 bug).
- lbl.rs — the LBL: 6-bit-packed and 8-bit-latin1 label text (road names,
elevation-labelled contours).
Public API in mod.rs: `Img::{parse,read,decode}`, `Feature`, `Kind`, `Decoded`,
plus shared bounds-checked little-endian byte readers.
Parity is proven, not asserted: an in-module test folds every decoded
coordinate through FNV-1a-64 and matches the Python golden
(0xadb368a3b063c74d) over all 120,174 features of the village tile 47505316,
with exact per-kind (line 114616 / poly 3185 / point 2373) and per-level
counts, a concrete first-feature check, and a decoded road name ("US Hwy 180").
Three more banked tiles decode to their exact prototype feature counts.
This replaces raster colour-guessing with typed lookups for the geo bake
pipeline (tasks #13-#16): every polygon/polyline carries a Garmin type code
(building / water / forest / street / path / contour) plus contour elevations.
geo is its own cargo workspace (isolated from the q2 workspace); clippy
(-D warnings) and rustfmt clean on the new files.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012jEwwaT5JZ5x8qWvcnaMYC
AdaWorldAPI
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…ather path main.rs's boot sequence converted the .chains sidecar to Lance but discarded the returned OrdinalIndex (bound to `_index`), so CHAINS_INDEX was never populated. gather_chains()'s `CHAINS_INDEX.get()?.as_ref()?` therefore always short-circuited to None, and every tile/feature request needing chain geometry permanently fell back to the eager open_chains() singleton — a OnceLock populated once on first use and never freed. Live-confirmed on maps.oga.red: cgroup memory sat at ~850MB baseline, jumped to ~5.7GB after the first chains-touching request, and never came back down — matching the reported symptom (memory doesn't go down again after opening the map in browser). Add osm_chains_books_lance::publish_chains_conversion(), the one call site responsible for turning an ensure_chains_lance_local() result into a set_chains_index() call, with its own unit tests covering both the Some (wires the index) and None (fails open, no panic) arms. main.rs now calls it instead of its old broken inline match. Also corrected the now-stale "not yet consumed by the read path" log wording for both chains and books (task #16 already wired the Lance-first-with-eager-fallback read path for both). Verified: cargo check -p cockpit-server --bin q2-cockpit --tests passes clean (0 errors; 33/18 warnings, at or below the pre-existing baseline). Full `cargo test`/nextest for this binary is not runnable in this environment (transitively links most of the workspace, exceeds the container's disk allowance) — documented per prior sessions' practice rather than claimed. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01NMeiLmtDKhomJNSo2ecbJw
4 tasks
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