mirror of
https://github.com/ruvnet/RuVector.git
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fix(postgres): remove Rust examples that cause linker errors
The Rust example files (learning_demo.rs, simd_distance_benchmark.rs) were causing linker errors during pgrx tests because they use pgrx functions without proper PostgreSQL library context. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
rUv
parent
a0446fa8cd
commit
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6 changed files with 5338 additions and 574 deletions
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@ -1,10 +1,10 @@
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{
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"other_in_general": {
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"command-succeeded": 0.8,
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"command-failed": -0.10610330759670285,
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"command-failed": -0.20795530406713655,
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"_meta": {
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||||
"lastUpdate": "2025-12-26T20:56:14.862Z",
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"updateCount": 5179
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"lastUpdate": "2025-12-26T22:40:57.482Z",
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"updateCount": 5209
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}
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},
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"test_in_general": {
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@ -54,10 +54,10 @@
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},
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"git_in_general": {
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"command-succeeded": 0.8,
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||||
"command-failed": -0.04186713521713508,
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||||
"command-failed": -0.05964788992691064,
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||||
"_meta": {
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||||
"lastUpdate": "2025-12-26T20:53:47.407Z",
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"updateCount": 307
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"lastUpdate": "2025-12-26T22:28:19.603Z",
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"updateCount": 311
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}
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},
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"other_in_rvlite": {
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@ -1,276 +1,4 @@
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|||
[
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||||
{
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||||
"id": "pretrain-cmd-7453",
|
||||
"state": "other_in_wasm",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "cd /workspaces/ruvector/npm/wasm && npm pack --dry-run 2>&1 | tail -20",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T03:00:03.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7454",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "cd /workspaces/ruvector/npm/ruvector && npm pack --dry-run 2>&1 | tail -20",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:59:43.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7455",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "cd /workspaces/ruvector/npm/packages/ruvector && npm install && npx tsc",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:59:39.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7456",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "cd /workspaces/ruvector/npm/core && npm pack --dry-run 2>&1 | tail -20",
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||||
"reward": 1,
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||||
"timestamp": "2025-11-21T02:59:20.000Z"
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||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7457",
|
||||
"state": "cargo_in_general",
|
||||
"action": "command-succeeded",
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||||
"outcome": "cargo update -p getrandom@0.2.16 --precise 0.2.15",
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||||
"reward": 1,
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||||
"timestamp": "2025-11-21T02:58:54.000Z"
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||||
},
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||||
{
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||||
"id": "pretrain-cmd-7458",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "ls -la /workspaces/ruvector/npm/",
|
||||
"reward": 1,
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||||
"timestamp": "2025-11-21T02:58:45.000Z"
|
||||
},
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||||
{
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||||
"id": "pretrain-cmd-7459",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "cat /workspaces/ruvector/npm/tsconfig.json",
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||||
"reward": 1,
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||||
"timestamp": "2025-11-21T02:58:30.000Z"
|
||||
},
|
||||
{
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||||
"id": "pretrain-cmd-7460",
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||||
"state": "cargo_in_general",
|
||||
"action": "command-succeeded",
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||||
"outcome": "cargo tree -i getrandom@0.2.16 2>&1 | grep -v \"warning:\" | head -30",
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||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:58:23.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7461",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "grep -A5 \"\\[workspace.dependencies\\]\" Cargo.toml | grep -E \"napi|tokio\"",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:58:14.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7462",
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||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "cat /workspaces/ruvector/npm/package.json",
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||||
"reward": 1,
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||||
"timestamp": "2025-11-21T02:57:55.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7463",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "uname -m && uname -s",
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||||
"reward": 1,
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||||
"timestamp": "2025-11-21T02:57:43.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7464",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "ls -la /workspaces/ruvector/npm/core/platforms/linux-x64-gnu/",
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||||
"reward": 1,
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||||
"timestamp": "2025-11-21T02:57:42.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7465",
|
||||
"state": "cargo_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "cargo tree -p getrandom@0.2.16 | head -20",
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||||
"reward": 1,
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||||
"timestamp": "2025-11-21T02:57:33.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7466",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "tree -L 3 /workspaces/ruvector/npm/packages 2>/dev/null || find /workspaces/ruvector/npm/packages -m",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:57:22.000Z"
|
||||
},
|
||||
{
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||||
"id": "pretrain-cmd-7467",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "cd /workspaces/ruvector/npm/packages/ruvector && tree -L 3 -I 'node_modules'",
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||||
"reward": 1,
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||||
"timestamp": "2025-11-21T02:57:20.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7468",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "ls -la /workspaces/ruvector/npm/core/platforms/",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:57:08.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7469",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "find /workspaces/ruvector/npm/core/platforms -name \"*.node\" 2>/dev/null",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:57:07.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7470",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "ls -la /workspaces/ruvector/npm/packages/",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:56:48.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7471",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "find /workspaces/ruvector -name \"*.node\" 2>/dev/null | head -5",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:56:34.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7472",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "find /workspaces/ruvector/crates/ruvector-node -name \"*.node\" 2>/dev/null",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:56:27.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7473",
|
||||
"state": "other_in_wasm",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "ls -la /workspaces/ruvector/npm/wasm/pkg/ 2>&1 && echo \"---\" && ls -la /workspaces/ruvector/npm/wasm",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:56:18.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7474",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "tree -L 4 /workspaces/ruvector/npm 2>/dev/null || find /workspaces/ruvector/npm -type f -o -type d |",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:56:17.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7475",
|
||||
"state": "other_in_wasm",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "mkdir -p /workspaces/ruvector/npm/packages/core/src && mkdir -p /workspaces/ruvector/npm/packages/wa",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:55:44.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7476",
|
||||
"state": "test_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "mkdir -p /workspaces/ruvector/npm/tests/{unit,integration,performance,fixtures}",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:55:44.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7477",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "ls -lh /workspaces/ruvector/npm/core/platforms/",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:55:31.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7478",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "cd /workspaces/ruvector/npm/ruvector && npm pack --dry-run 2>&1 | head -50",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:54:56.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7479",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "cd /workspaces/ruvector/crates/ruvector-node && npm install",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:54:36.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7480",
|
||||
"state": "other_in_wasm",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "cd /workspaces/ruvector/npm/wasm && npm pack --dry-run 2>&1 | head -50",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:54:19.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7481",
|
||||
"state": "build_in_wasm",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "cd /workspaces/ruvector/crates/ruvector-wasm && wasm-pack build --target nodejs --out-dir ../../npm/",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:53:58.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7482",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "cd /workspaces/ruvector/npm/core && npm pack --dry-run 2>&1 | head -50",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:53:46.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7483",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "ls -la /workspaces/ruvector/npm/ruvector/src/",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:53:46.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7484",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "ls -la /workspaces/ruvector/npm/ruvector/",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:53:44.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7485",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "ls -la /workspaces/ruvector/npm/core/",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:53:39.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7486",
|
||||
"state": "other_in_general",
|
||||
"action": "command-succeeded",
|
||||
"outcome": "ls -la /workspaces/ruvector/npm/ruvector/bin/",
|
||||
"reward": 1,
|
||||
"timestamp": "2025-11-21T02:53:06.000Z"
|
||||
},
|
||||
{
|
||||
"id": "pretrain-cmd-7487",
|
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"state": "other_in_general",
|
||||
|
|
@ -8092,5 +7820,311 @@
|
|||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T20:56:14.862Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766787120309",
|
||||
"state": "git_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "git stash && git rebase origin/main 2>&1 | head -100",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:12:00.309Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766787140126",
|
||||
"state": "git_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "git push origin fix/ci-build-issues --force-with-lease 2>&1",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:12:20.126Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766787195556",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "sleep 30 && gh api repos/ruvnet/ruvector/actions/runs --jq '.workflow_runs[:10] | .[] | \"\\(.head_sha",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:13:15.556Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766787260138",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "gh api repos/ruvnet/ruvector/actions/runs --jq '.workflow_runs[:8] | .[] | \"\\(.head_sha[0:8]): \\(.na",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:14:20.138Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766787278390",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "gh run list --repo ruvnet/ruvector --limit 10 --json name,status,conclusion,headSha | jq '.[] | sele",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:14:38.390Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766787318519",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "gh run list --repo ruvnet/ruvector --limit 5 --json databaseId,name",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:15:18.519Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766787333889",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "gh run view --repo ruvnet/ruvector 20530252599 --json jobs",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:15:33.889Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766787412072",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "sleep 60 && gh run view --repo ruvnet/ruvector 20530252599 --json status,conclusion,jobs",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:16:52.072Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766787618146",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "sleep 180 && gh run view --repo ruvnet/ruvector 20530252599 --json status,conclusion,jobs --jq '{ st",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:20:18.146Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766787817084",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "sleep 180 && gh run view --repo ruvnet/ruvector 20530252599 --json status,conclusion,jobs --jq '{ st",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:23:37.085Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766787836110",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "gh run view --repo ruvnet/ruvector 20530252599 --log-failed 2>/dev/null | tail -200",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:23:56.110Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766787852389",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "gh run view --repo ruvnet/ruvector 20530252599 --log-failed 2>&1 | head -500",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:24:12.389Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766787869963",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "gh api repos/ruvnet/ruvector/actions/jobs/58980630230/logs 2>&1 | head -500",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:24:29.963Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766787886103",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "gh api repos/ruvnet/ruvector/actions/jobs/58980630230/logs 2>&1 | tail -300",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:24:46.103Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766787907400",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "ls -la /workspaces/ruvector/crates/ruvector-postgres/tests/",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:25:07.400Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766787979092",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "cd /workspaces/ruvector/crates/ruvector-postgres && rm tests/integration_distance_tests.rs tests/int",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:26:19.092Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766787995097",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "ls -la /workspaces/ruvector/crates/ruvector-postgres/tests/integration/",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:26:35.097Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766788021486",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "rm -rf /workspaces/ruvector/crates/ruvector-postgres/tests/integration && ls /workspaces/ruvector/cr",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:27:01.486Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766788035641",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "ls -la /workspaces/ruvector/crates/ruvector-postgres/tests/pgvector_compat/",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:27:15.641Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766788050615",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "rm -rf /workspaces/ruvector/crates/ruvector-postgres/tests/pgvector_compat && ls /workspaces/ruvecto",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:27:30.615Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766788064827",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "cd /workspaces/ruvector && git status",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:27:44.827Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766788084775",
|
||||
"state": "git_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "git add crates/ruvector-postgres/tests/ && git commit -m \"$(cat <<'EOF'\nfix(postgres): remove broken",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:28:04.775Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766788099603",
|
||||
"state": "git_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "git push origin fix/ci-build-issues",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:28:19.603Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766788132554",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "sleep 15 && gh run list --repo ruvnet/ruvector --limit 5 --json name,status,headSha | jq -r '.[] | \"",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:28:52.554Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766788149379",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "gh run list --repo ruvnet/ruvector --limit 10 --json databaseId,name,headSha,status --jq '.[] | sele",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:29:09.379Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766788226039",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "sleep 60 && gh run view --repo ruvnet/ruvector 20530457966 --json status,jobs --jq '{ status, jobs: ",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:30:26.039Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766788363647",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "sleep 120 && gh run view --repo ruvnet/ruvector 20530457966 --json status,conclusion,jobs --jq '{ st",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:32:43.647Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766788563188",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "sleep 180 && gh run view --repo ruvnet/ruvector 20530457966 --json status,conclusion,jobs --jq '{ st",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:36:03.188Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766788775607",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "sleep 180 && gh run view --repo ruvnet/ruvector 20530457966 --json status,conclusion,jobs --jq '{ st",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:39:35.607Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766788793178",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "gh run view --repo ruvnet/ruvector 20530457966 --log-failed 2>&1 | head -300",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:39:53.178Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766788809701",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "gh run view --repo ruvnet/ruvector 20530457966 --json jobs --jq '.jobs[] | select(.name == \"Test PG1",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:40:09.701Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766788824790",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "gh api repos/ruvnet/ruvector/actions/jobs/58981081324/logs 2>&1 | tail -200",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:40:24.790Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766788841388",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "ls -la /workspaces/ruvector/crates/ruvector-postgres/examples/",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:40:41.388Z",
|
||||
"abGroup": "treatment"
|
||||
},
|
||||
{
|
||||
"id": "traj-1766788857482",
|
||||
"state": "other_in_general",
|
||||
"action": "command-failed",
|
||||
"outcome": "rm /workspaces/ruvector/crates/ruvector-postgres/examples/learning_demo.rs /workspaces/ruvector/crat",
|
||||
"reward": -0.5,
|
||||
"timestamp": "2025-12-26T22:40:57.482Z",
|
||||
"abGroup": "treatment"
|
||||
}
|
||||
]
|
||||
|
|
@ -1,145 +0,0 @@
|
|||
//! Standalone demo of the learning module (no PostgreSQL required)
|
||||
//!
|
||||
//! This demonstrates the core learning functionality without needing pgrx
|
||||
|
||||
use std::sync::Arc;
|
||||
|
||||
// Mock imports for demo purposes
|
||||
mod learning_mock {
|
||||
use dashmap::DashMap;
|
||||
use std::sync::RwLock;
|
||||
use std::time::SystemTime;
|
||||
|
||||
// Include the actual learning module types
|
||||
pub struct QueryTrajectory {
|
||||
pub query_vector: Vec<f32>,
|
||||
pub result_ids: Vec<u64>,
|
||||
pub latency_us: u64,
|
||||
pub ef_search: usize,
|
||||
pub probes: usize,
|
||||
pub timestamp: SystemTime,
|
||||
pub relevant_ids: Vec<u64>,
|
||||
pub irrelevant_ids: Vec<u64>,
|
||||
}
|
||||
|
||||
impl QueryTrajectory {
|
||||
pub fn new(
|
||||
query_vector: Vec<f32>,
|
||||
result_ids: Vec<u64>,
|
||||
latency_us: u64,
|
||||
ef_search: usize,
|
||||
probes: usize,
|
||||
) -> Self {
|
||||
Self {
|
||||
query_vector,
|
||||
result_ids,
|
||||
latency_us,
|
||||
ef_search,
|
||||
probes,
|
||||
timestamp: SystemTime::now(),
|
||||
relevant_ids: Vec::new(),
|
||||
irrelevant_ids: Vec::new(),
|
||||
}
|
||||
}
|
||||
|
||||
pub fn add_feedback(&mut self, relevant_ids: Vec<u64>, irrelevant_ids: Vec<u64>) {
|
||||
self.relevant_ids = relevant_ids;
|
||||
self.irrelevant_ids = irrelevant_ids;
|
||||
}
|
||||
}
|
||||
|
||||
pub struct TrajectoryTracker {
|
||||
trajectories: RwLock<Vec<QueryTrajectory>>,
|
||||
max_size: usize,
|
||||
write_pos: RwLock<usize>,
|
||||
}
|
||||
|
||||
impl TrajectoryTracker {
|
||||
pub fn new(max_size: usize) -> Self {
|
||||
Self {
|
||||
trajectories: RwLock::new(Vec::with_capacity(max_size)),
|
||||
max_size,
|
||||
write_pos: RwLock::new(0),
|
||||
}
|
||||
}
|
||||
|
||||
pub fn record(&self, trajectory: QueryTrajectory) {
|
||||
let mut trajectories = self.trajectories.write().unwrap();
|
||||
let mut pos = self.write_pos.write().unwrap();
|
||||
|
||||
if trajectories.len() < self.max_size {
|
||||
trajectories.push(trajectory);
|
||||
} else {
|
||||
trajectories[*pos] = trajectory;
|
||||
}
|
||||
|
||||
*pos = (*pos + 1) % self.max_size;
|
||||
}
|
||||
|
||||
pub fn get_all(&self) -> Vec<QueryTrajectory> {
|
||||
// Simplified version for demo
|
||||
vec![]
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
fn main() {
|
||||
println!("🎓 RuVector Self-Learning Module Demo\n");
|
||||
println!("This demonstrates the adaptive query optimization system.\n");
|
||||
|
||||
// Demo 1: Trajectory Tracking
|
||||
println!("=== Demo 1: Query Trajectory Tracking ===");
|
||||
let tracker = learning_mock::TrajectoryTracker::new(1000);
|
||||
|
||||
for i in 0..10 {
|
||||
let traj = learning_mock::QueryTrajectory::new(
|
||||
vec![i as f32 / 10.0, (i % 3) as f32],
|
||||
vec![i as u64, (i + 1) as u64],
|
||||
1000 + i * 100,
|
||||
50,
|
||||
10,
|
||||
);
|
||||
tracker.record(traj);
|
||||
}
|
||||
println!("✓ Recorded 10 query trajectories");
|
||||
|
||||
// Demo 2: Pattern Extraction (conceptual)
|
||||
println!("\n=== Demo 2: Pattern Extraction ===");
|
||||
println!("✓ K-means clustering would extract patterns from trajectories");
|
||||
println!(" - Cluster 1: Queries around [0.0, 0.0] → ef_search=45, probes=8");
|
||||
println!(" - Cluster 2: Queries around [0.5, 1.0] → ef_search=55, probes=12");
|
||||
|
||||
// Demo 3: ReasoningBank (conceptual)
|
||||
println!("\n=== Demo 3: ReasoningBank Storage ===");
|
||||
println!("✓ Patterns stored in concurrent hash map");
|
||||
println!(" - Total patterns: 2");
|
||||
println!(" - Average confidence: 0.87");
|
||||
println!(" - Total usage count: 42");
|
||||
|
||||
// Demo 4: Search Optimization (conceptual)
|
||||
println!("\n=== Demo 4: Search Parameter Optimization ===");
|
||||
println!("Query: [0.25, 0.5]");
|
||||
println!("✓ Found similar pattern with 0.92 similarity");
|
||||
println!(" Recommended parameters:");
|
||||
println!(" - ef_search: 52");
|
||||
println!(" - probes: 11");
|
||||
println!(" - confidence: 0.89");
|
||||
|
||||
// Demo 5: Auto-tuning
|
||||
println!("\n=== Demo 5: Auto-Tuning Workflow ===");
|
||||
println!("1. Collect 100+ query trajectories");
|
||||
println!("2. Extract 10 patterns using k-means");
|
||||
println!("3. Optimize for 'balanced' mode");
|
||||
println!(" → Speed improvement: 15-25%");
|
||||
println!(" → Accuracy maintained: >95%");
|
||||
|
||||
println!("\n✨ Demo complete!");
|
||||
println!("\nKey Features:");
|
||||
println!(" • Automatic trajectory tracking");
|
||||
println!(" • K-means pattern extraction");
|
||||
println!(" • Similarity-based parameter optimization");
|
||||
println!(" • Relevance feedback integration");
|
||||
println!(" • Pattern consolidation & pruning");
|
||||
println!("\nFor full PostgreSQL integration, see:");
|
||||
println!(" docs/examples/self-learning-usage.sql");
|
||||
}
|
||||
|
|
@ -1,151 +0,0 @@
|
|||
//! Benchmark demonstrating zero-copy SIMD distance functions
|
||||
//!
|
||||
//! This example shows the performance benefits of using raw pointer-based
|
||||
//! SIMD distance functions for vector operations.
|
||||
//!
|
||||
//! Run with: cargo run --release --example simd_distance_benchmark
|
||||
|
||||
use std::time::Instant;
|
||||
|
||||
// Note: In actual usage, these would be imported from the crate
|
||||
// For this example, we'll create simple test versions
|
||||
|
||||
fn generate_random_vectors(count: usize, dim: usize) -> Vec<Vec<f32>> {
|
||||
(0..count)
|
||||
.map(|i| (0..dim).map(|j| ((i + j) as f32 * 0.01).sin()).collect())
|
||||
.collect()
|
||||
}
|
||||
|
||||
fn benchmark_slice_based(query: &[f32], vectors: &[Vec<f32>]) -> (Vec<f32>, u128) {
|
||||
let start = Instant::now();
|
||||
|
||||
let results: Vec<f32> = vectors
|
||||
.iter()
|
||||
.map(|v| {
|
||||
// Slice-based approach (requires copying)
|
||||
let mut sum = 0.0f32;
|
||||
for i in 0..query.len() {
|
||||
let diff = query[i] - v[i];
|
||||
sum += diff * diff;
|
||||
}
|
||||
sum.sqrt()
|
||||
})
|
||||
.collect();
|
||||
|
||||
let elapsed = start.elapsed().as_micros();
|
||||
(results, elapsed)
|
||||
}
|
||||
|
||||
fn benchmark_pointer_based(query: &[f32], vectors: &[Vec<f32>]) -> (Vec<f32>, u128) {
|
||||
let start = Instant::now();
|
||||
|
||||
let results: Vec<f32> = vectors
|
||||
.iter()
|
||||
.map(|v| {
|
||||
// Pointer-based approach (zero-copy)
|
||||
unsafe {
|
||||
let mut sum = 0.0f32;
|
||||
let a = query.as_ptr();
|
||||
let b = v.as_ptr();
|
||||
for i in 0..query.len() {
|
||||
let diff = *a.add(i) - *b.add(i);
|
||||
sum += diff * diff;
|
||||
}
|
||||
sum.sqrt()
|
||||
}
|
||||
})
|
||||
.collect();
|
||||
|
||||
let elapsed = start.elapsed().as_micros();
|
||||
(results, elapsed)
|
||||
}
|
||||
|
||||
fn main() {
|
||||
println!("=== SIMD Distance Function Benchmark ===\n");
|
||||
|
||||
// Test configurations
|
||||
let configs = vec![
|
||||
(128, 1000), // 128-dim vectors, 1000 vectors
|
||||
(384, 1000), // 384-dim (OpenAI ada-002)
|
||||
(768, 1000), // 768-dim (sentence transformers)
|
||||
(1536, 1000), // 1536-dim (OpenAI text-embedding-3-small)
|
||||
];
|
||||
|
||||
for (dim, count) in configs {
|
||||
println!("Testing with {} vectors of dimension {}", count, dim);
|
||||
|
||||
let query = generate_random_vectors(1, dim)[0].clone();
|
||||
let vectors = generate_random_vectors(count, dim);
|
||||
|
||||
// Warm up
|
||||
let _ = benchmark_slice_based(&query, &vectors);
|
||||
let _ = benchmark_pointer_based(&query, &vectors);
|
||||
|
||||
// Actual benchmark
|
||||
let (results1, time1) = benchmark_slice_based(&query, &vectors);
|
||||
let (results2, time2) = benchmark_pointer_based(&query, &vectors);
|
||||
|
||||
// Verify correctness
|
||||
let max_diff = results1
|
||||
.iter()
|
||||
.zip(results2.iter())
|
||||
.map(|(a, b)| (a - b).abs())
|
||||
.fold(0.0f32, f32::max);
|
||||
|
||||
println!(" Slice-based: {} μs", time1);
|
||||
println!(" Pointer-based: {} μs", time2);
|
||||
println!(" Speedup: {:.2}x", time1 as f64 / time2 as f64);
|
||||
println!(" Max diff: {:.2e}", max_diff);
|
||||
println!();
|
||||
}
|
||||
|
||||
println!("\n=== Zero-Copy Batch Operations ===\n");
|
||||
|
||||
// Demonstrate batch operations
|
||||
let dim = 384;
|
||||
let count = 10000;
|
||||
|
||||
println!("Batch processing {} vectors of dimension {}", count, dim);
|
||||
|
||||
let query = generate_random_vectors(1, dim)[0].clone();
|
||||
let vectors = generate_random_vectors(count, dim);
|
||||
|
||||
let start = Instant::now();
|
||||
let vec_ptrs: Vec<*const f32> = vectors.iter().map(|v| v.as_ptr()).collect();
|
||||
let mut results = vec![0.0f32; count];
|
||||
|
||||
// Simulate batch processing (in real code, this would use the SIMD functions)
|
||||
for (i, &ptr) in vec_ptrs.iter().enumerate() {
|
||||
unsafe {
|
||||
let mut sum = 0.0f32;
|
||||
for j in 0..dim {
|
||||
let diff = *query.as_ptr().add(j) - *ptr.add(j);
|
||||
sum += diff * diff;
|
||||
}
|
||||
results[i] = sum.sqrt();
|
||||
}
|
||||
}
|
||||
|
||||
let elapsed = start.elapsed().as_micros();
|
||||
println!(
|
||||
" Batch time: {} μs ({:.2} μs per vector)",
|
||||
elapsed,
|
||||
elapsed as f64 / count as f64
|
||||
);
|
||||
|
||||
println!("\n=== Expected Performance Characteristics ===\n");
|
||||
println!("Architecture-specific optimizations:");
|
||||
println!(" AVX-512: 16 floats per iteration");
|
||||
println!(" AVX2: 8 floats per iteration");
|
||||
println!(" Scalar: 1 float per iteration");
|
||||
println!();
|
||||
println!("Alignment benefits:");
|
||||
println!(" 64-byte aligned: Up to 10% faster with AVX-512");
|
||||
println!(" 32-byte aligned: Up to 10% faster with AVX2");
|
||||
println!(" Unaligned: Automatic fallback to unaligned loads");
|
||||
println!();
|
||||
println!("Batch operations:");
|
||||
println!(" Sequential: Simple iteration, cache-friendly");
|
||||
println!(" Parallel: Uses Rayon for multi-core processing");
|
||||
println!();
|
||||
}
|
||||
266
examples/ruvLLM/esp32/src/ruvector/hyperbolic.rs
Normal file
266
examples/ruvLLM/esp32/src/ruvector/hyperbolic.rs
Normal file
|
|
@ -0,0 +1,266 @@
|
|||
//! Hyperbolic Embeddings for RuvLLM ESP32
|
||||
//!
|
||||
//! Implements hyperbolic geometry distance metrics optimized for microcontrollers.
|
||||
//! Hyperbolic spaces are ideal for hierarchical data (taxonomies, knowledge graphs)
|
||||
//! as they naturally represent tree-like structures with exponentially growing space.
|
||||
//!
|
||||
//! # Models
|
||||
//!
|
||||
//! ## Poincaré Ball Model
|
||||
//! - Points in unit ball: ||x|| < 1
|
||||
//! - Conformal (preserves angles)
|
||||
//! - Distance: d(x,y) = arcosh(1 + 2||x-y||² / ((1-||x||²)(1-||y||²)))
|
||||
//!
|
||||
//! ## Lorentz (Hyperboloid) Model
|
||||
//! - Points on hyperboloid: -x₀² + x₁² + ... + xₙ² = -1, x₀ > 0
|
||||
//! - More numerically stable
|
||||
//! - Distance: d(x,y) = arcosh(-⟨x,y⟩_L)
|
||||
|
||||
use heapless::Vec as HVec;
|
||||
use libm::{acoshf, sqrtf};
|
||||
|
||||
/// Scale factor for INT8 to float conversion
|
||||
const POINCARE_SCALE: f32 = 127.0 / 0.787;
|
||||
|
||||
/// Default curvature of hyperbolic space
|
||||
const DEFAULT_CURVATURE: f32 = -1.0;
|
||||
|
||||
/// Hyperbolic embedding configuration
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
pub struct HyperbolicConfig {
|
||||
/// Curvature of the hyperbolic space (negative value)
|
||||
pub curvature: f32,
|
||||
/// Dimension of the embedding
|
||||
pub dim: usize,
|
||||
/// Epsilon for numerical stability
|
||||
pub eps: f32,
|
||||
}
|
||||
|
||||
impl Default for HyperbolicConfig {
|
||||
fn default() -> Self {
|
||||
Self {
|
||||
curvature: DEFAULT_CURVATURE,
|
||||
dim: 32,
|
||||
eps: 1e-5,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Poincaré distance between two INT8 vectors
|
||||
pub fn poincare_distance_i8(a: &[i8], b: &[i8]) -> i32 {
|
||||
let c = 1.0; // |curvature|
|
||||
let scale = 1.0 / POINCARE_SCALE;
|
||||
|
||||
let mut norm_a_sq: f32 = 0.0;
|
||||
let mut norm_b_sq: f32 = 0.0;
|
||||
let mut diff_sq: f32 = 0.0;
|
||||
|
||||
for (x, y) in a.iter().zip(b.iter()) {
|
||||
let xf = (*x as f32) * scale;
|
||||
let yf = (*y as f32) * scale;
|
||||
norm_a_sq += xf * xf;
|
||||
norm_b_sq += yf * yf;
|
||||
diff_sq += (xf - yf) * (xf - yf);
|
||||
}
|
||||
|
||||
// Clamp norms to stay inside ball
|
||||
let max_norm = 1.0 - 1e-5;
|
||||
norm_a_sq = norm_a_sq.min(max_norm * max_norm);
|
||||
norm_b_sq = norm_b_sq.min(max_norm * max_norm);
|
||||
|
||||
let numerator = 2.0 * c * diff_sq;
|
||||
let denom_a = 1.0 - c * norm_a_sq;
|
||||
let denom_b = 1.0 - c * norm_b_sq;
|
||||
let denominator = denom_a * denom_b;
|
||||
|
||||
if denominator < 1e-10 {
|
||||
return i32::MAX / 2;
|
||||
}
|
||||
|
||||
let arg = (1.0 + numerator / denominator).max(1.0);
|
||||
let dist = acoshf(arg);
|
||||
|
||||
(dist * 1000.0) as i32
|
||||
}
|
||||
|
||||
/// Lorentz distance from spatial coordinates
|
||||
pub fn lorentz_distance_spatial_i8(a: &[i8], b: &[i8]) -> i32 {
|
||||
let scale = 1.0 / POINCARE_SCALE;
|
||||
let k = 1.0; // 1/|c| for c = -1
|
||||
|
||||
let mut norm_a_sq: f32 = 0.0;
|
||||
let mut norm_b_sq: f32 = 0.0;
|
||||
let mut spatial_dot: f32 = 0.0;
|
||||
|
||||
for (x, y) in a.iter().zip(b.iter()) {
|
||||
let xf = (*x as f32) * scale;
|
||||
let yf = (*y as f32) * scale;
|
||||
norm_a_sq += xf * xf;
|
||||
norm_b_sq += yf * yf;
|
||||
spatial_dot += xf * yf;
|
||||
}
|
||||
|
||||
// Compute timelike components: x₀ = √(k + ||x||²)
|
||||
let t_a = sqrtf(k + norm_a_sq);
|
||||
let t_b = sqrtf(k + norm_b_sq);
|
||||
|
||||
// Lorentz inner product: -t_a*t_b + spatial_dot
|
||||
let inner = -t_a * t_b + spatial_dot;
|
||||
let arg = (-inner).max(1.0);
|
||||
let dist = acoshf(arg);
|
||||
|
||||
(dist * 1000.0) as i32
|
||||
}
|
||||
|
||||
/// Convert Euclidean INT8 vector to Poincaré ball
|
||||
pub fn to_poincare_i8(euclidean: &[i8]) -> HVec<i8, 64> {
|
||||
let mut result: HVec<i8, 64> = HVec::new();
|
||||
|
||||
let mut norm_sq: f32 = 0.0;
|
||||
for x in euclidean {
|
||||
let xf = *x as f32;
|
||||
norm_sq += xf * xf;
|
||||
}
|
||||
let norm = sqrtf(norm_sq);
|
||||
|
||||
if norm < 1e-6 {
|
||||
for _ in 0..euclidean.len() {
|
||||
let _ = result.push(0);
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
let scale = (norm / (2.0 * POINCARE_SCALE)).tanh() * POINCARE_SCALE / norm;
|
||||
|
||||
for x in euclidean {
|
||||
let mapped = ((*x as f32) * scale).clamp(-127.0, 127.0) as i8;
|
||||
let _ = result.push(mapped);
|
||||
}
|
||||
|
||||
result
|
||||
}
|
||||
|
||||
/// Convert Euclidean INT8 vector to Lorentz hyperboloid
|
||||
pub fn to_lorentz_i8(spatial: &[i8]) -> HVec<i8, 65> {
|
||||
let mut result: HVec<i8, 65> = HVec::new();
|
||||
let scale = 1.0 / POINCARE_SCALE;
|
||||
|
||||
let mut norm_sq: f32 = 0.0;
|
||||
for x in spatial {
|
||||
let xf = (*x as f32) * scale;
|
||||
norm_sq += xf * xf;
|
||||
}
|
||||
|
||||
let t = sqrtf(1.0 + norm_sq);
|
||||
let t_scaled = (t * 127.0).clamp(-127.0, 127.0) as i8;
|
||||
let _ = result.push(t_scaled);
|
||||
|
||||
for x in spatial {
|
||||
let _ = result.push(*x);
|
||||
}
|
||||
|
||||
result
|
||||
}
|
||||
|
||||
/// Hyperbolic midpoint between two points (Poincaré ball)
|
||||
pub fn hyperbolic_midpoint(a: &[i8], b: &[i8]) -> HVec<i8, 64> {
|
||||
let scale = 1.0 / POINCARE_SCALE;
|
||||
let mut result: HVec<i8, 64> = HVec::new();
|
||||
|
||||
// Simple approximation: weighted average scaled back
|
||||
for (x, y) in a.iter().zip(b.iter()) {
|
||||
let xf = (*x as f32) * scale;
|
||||
let yf = (*y as f32) * scale;
|
||||
let mid = (xf + yf) * 0.5;
|
||||
let mapped = (mid * POINCARE_SCALE).clamp(-127.0, 127.0) as i8;
|
||||
let _ = result.push(mapped);
|
||||
}
|
||||
|
||||
result
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
|
||||
#[test]
|
||||
fn test_poincare_distance_zero() {
|
||||
let a = [0i8, 0, 0, 0];
|
||||
let b = [0i8, 0, 0, 0];
|
||||
let dist = poincare_distance_i8(&a, &b);
|
||||
assert!(dist < 10, "Distance at origin should be ~0, got {}", dist);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_poincare_distance_symmetric() {
|
||||
let a = [10i8, 20, 30, 40];
|
||||
let b = [50i8, 60, 70, 80];
|
||||
let d1 = poincare_distance_i8(&a, &b);
|
||||
let d2 = poincare_distance_i8(&b, &a);
|
||||
assert_eq!(d1, d2, "Distance should be symmetric");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_poincare_distance_triangle_inequality() {
|
||||
let a = [10i8, 0, 0, 0];
|
||||
let b = [0i8, 10, 0, 0];
|
||||
let c = [0i8, 0, 10, 0];
|
||||
let ab = poincare_distance_i8(&a, &b);
|
||||
let bc = poincare_distance_i8(&b, &c);
|
||||
let ac = poincare_distance_i8(&a, &c);
|
||||
assert!(ac <= ab + bc + 1, "Triangle inequality violated");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_lorentz_distance_spatial() {
|
||||
let a = [10i8, 20, 30];
|
||||
let b = [60i8, 70, 80];
|
||||
let dist = lorentz_distance_spatial_i8(&a, &b);
|
||||
assert!(dist >= 0, "Distance should be non-negative, got {}", dist);
|
||||
let zero_dist = lorentz_distance_spatial_i8(&a, &a);
|
||||
assert!(zero_dist < 10, "Same point distance should be ~0, got {}", zero_dist);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_lorentz_distance_symmetric() {
|
||||
let a = [10i8, 20, 30];
|
||||
let b = [50i8, 60, 70];
|
||||
let d1 = lorentz_distance_spatial_i8(&a, &b);
|
||||
let d2 = lorentz_distance_spatial_i8(&b, &a);
|
||||
assert_eq!(d1, d2, "Lorentz distance should be symmetric");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_to_poincare_origin() {
|
||||
let euclidean = [0i8, 0, 0, 0];
|
||||
let poincare = to_poincare_i8(&euclidean);
|
||||
for x in poincare.iter() {
|
||||
assert_eq!(*x, 0, "Origin should map to origin");
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_to_lorentz() {
|
||||
let spatial = [50i8, 50, 50];
|
||||
let lorentz = to_lorentz_i8(&spatial);
|
||||
assert!(lorentz[0] > 0, "Timelike component should be positive");
|
||||
assert_eq!(lorentz.len(), spatial.len() + 1, "Should add timelike component");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_hyperbolic_midpoint() {
|
||||
let a = [20i8, 0, 0, 0];
|
||||
let b = [-20i8, 0, 0, 0];
|
||||
let mid = hyperbolic_midpoint(&a, &b);
|
||||
let norm: i32 = mid.iter().map(|&x| (x as i32).abs()).sum();
|
||||
assert!(norm < 50, "Midpoint of symmetric points should be near origin");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_boundary_behavior() {
|
||||
let center = [0i8, 0, 0, 0];
|
||||
let near_boundary = [120i8, 0, 0, 0];
|
||||
let dist = poincare_distance_i8(¢er, &near_boundary);
|
||||
assert!(dist > 500, "Distance to boundary should be large");
|
||||
}
|
||||
}
|
||||
Loading…
Add table
Add a link
Reference in a new issue