Phases 16.2 + L2 + 17 VRAM gate + MySQL + 18 Lance hybrid milestone
Five threads of work landing as one milestone — all individually
verified end-to-end against real data, full release build clean,
46 unit tests pass.
## Phase 16.2 / 16.5 — autotune agent + ingest triggers
`vectord::agent` is a long-running tokio task that watches the trial
journal and autonomously proposes + runs new HNSW configs. Distinct
from `autotune::run_autotune` (synchronous one-shot grid). Triggered
on POST /vectors/agent/enqueue/{idx} or by the periodic wake; ingest
paths now push DatasetAppended events when an index's source dataset
gets re-ingested. Rate-limited (max_trials_per_hour) and cooldown-
gated so it can't saturate Ollama under live load.
The proposer is ε-greedy around the current champion: with prob 0.25
sample random from full bounds, otherwise perturb champion ± small
delta on both axes. Dedup against history. Deterministic — RNG seeded
from history.len() so the same journal state proposes the same next
config (helps offline replay debugging).
`[agent]` config section in lakehouse.toml; opt-in via enabled=true.
## Federation Layer 2 — runtime bucket lifecycle + per-index scoping
`BucketRegistry.buckets` moved to `std::sync::RwLock<HashMap>` so
buckets can be added/removed after startup. POST /storage/buckets
provisions at runtime; DELETE /storage/buckets/{name} unregisters
(refuses primary/rescue with 403). Local-backend buckets get their
root directory auto-created.
`IndexMeta.bucket` (default "primary" via serde) records each index's
home bucket. `TrialJournal` and `PromotionRegistry` now hold
Arc<BucketRegistry> + IndexRegistry; they resolve target store per-
index via IndexMeta.bucket. PromotionRegistry::list_all scans every
bucket and dedups by index_name. Pre-federation indexes keep working
unchanged — they just default to primary.
`ModelProfile.bucket: Option<String>` declares per-profile artifact
home. POST /vectors/profile/{id}/activate auto-provisions the
profile's bucket under storage.profile_root if not yet registered.
EvalSets stay primary-only for now — noted gap, low-risk to extend
later with the same resolver pattern.
## Phase 17 — VRAM-aware two-profile gate
Sidecar gains POST /admin/unload (Ollama keep_alive=0 trick — forces
immediate VRAM release), POST /admin/preload (keep_alive=5m with
empty prompt, takes the slot warm), and GET /admin/vram (combines
nvidia-smi snapshot with Ollama /api/ps). Exposed via aibridge as
unload_model / preload_model / vram_snapshot.
`VectorState.active_profile` is the GPU-slot singleton —
Arc<RwLock<Option<ActiveProfileSlot>>>. activate_profile checks for
a previous profile with a different ollama_name and unloads it
before preloading the new one; same-model reactivations skip the
unload (Ollama no-ops). New routes: POST /vectors/profile/{id}/
deactivate (unload + clear slot), GET /vectors/profile/active.
Verified live: staffing-recruiter (qwen2.5) → docs-assistant
(mistral) swap freed qwen2.5 from VRAM and loaded mistral. nomic-
embed-text persists across swaps because both profiles use it —
free optimization that fell out of the design. Scoped search
correctly 403s cross-profile in both directions.
## MySQL streaming connector
`crates/ingestd/src/my_stream.rs` mirrors pg_stream.rs for MySQL.
Pure-rust `mysql_async` driver (default-features=false to avoid C
deps). Same OFFSET pagination, same Parquet-streaming write shape.
Type mapping per ADR-010: int/bigint → Int32/Int64, decimal/float
→ Float64, tinyint(1)/bool → Boolean, everything else → Utf8 with
fallback parsers for date/time/json/uuid via Display.
POST /ingest/mysql parallel to /ingest/db. Same PII auto-detection,
same lineage capture (source_system="mysql"), same agent-trigger
hook. `redact_dsn` generalized — was hardcoded to "postgresql://"
length, now works for any scheme://user:pass@host/path URL (latent
PII leak fix for MySQL DSNs).
Verified live against MariaDB on localhost: 10 rows × 9 columns of
test data round-tripped through datatypes int/varchar/decimal/
tinyint/datetime/text. PII detection auto-flagged name + email.
Aggregation queries through DataFusion match the source values
exactly.
## Phase 18 — Hybrid Parquet+HNSW ⊕ Lance backend (ADR-019)
`vectord-lance` is a new firewall crate. Lance pulls Arrow 57 and
DataFusion 52 — incompatible with the rest of the workspace's
Arrow 55 / DataFusion 47. The firewall isolates that dep tree:
public API uses only std types (Vec<f32>, Vec<String>, Hit, Row,
*Stats), so no Arrow types cross the crate boundary and nothing
propagates to vectord. The ADR-019 path that didn't ship until now.
`vectord::lance_backend::LanceRegistry` lazy-creates a
LanceVectorStore per index, resolving bucket → URI via the
conventional local-bucket layout. `IndexMeta.vector_backend` and
`ModelProfile.vector_backend` carry the choice (default Parquet so
existing indexes unchanged).
Six routes under /vectors/lance/*:
- migrate/{idx}: convert binary-blob Parquet → Lance FixedSizeList
- index/{idx}: build IVF_PQ
- search/{idx}: vector search (embed via sidecar)
- doc/{idx}/{doc_id}: random row fetch
- append/{idx}: native fragment append
- stats/{idx}: row count + index presence
Verified live on the real resumes_100k_v2 corpus (100K × 768d):
- Migrate: 0.57s
- Build IVF_PQ index: 16.2s (matches ADR-019 bench; 14× faster than
HNSW's 230s for the same data)
- Search end-to-end (Ollama embed + Lance scan): 23-53ms
- Random doc_id fetch: 5-7ms (filter scan; faster than Parquet's
~35ms full-file scan, slower than the bench's 311us positional
take — would close that gap with a scalar btree on doc_id)
- Append 100 rows: 3.3ms / +320KB on disk vs Parquet's required
full ~330MB rewrite — the structural win
- Index survives append; both backends coexist cleanly
## Known follow-ups not in this milestone
- ModelProfile.vector_backend doesn't yet auto-route /vectors/profile/
{id}/search to Lance; callers go through /vectors/lance/* directly
- Scalar btree on doc_id (closes the 5-7ms → ~300us gap)
- vectord-lance built default-features=false → no S3 yet
- IVF_PQ recall not measured (ADR-019 caveat) — needs a Lance-aware
variant of the eval harness
- Watcher-path ingest doesn't push agent triggers (HTTP paths do)
- EvalSets still primary-only (federation gap)
- No PATCH endpoint to move an existing index between buckets
- The pre-existing storaged::append_log doctest fails to compile
(malformed `{prefix}/` parses as code fence) — pre-existing bug,
left for a focused fix
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
root
@@ -134,4 +134,47 @@ impl AiClient {
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}
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resp.json().await.map_err(|e| format!("rerank parse error: {e}"))
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}
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/// Force Ollama to unload the named model from VRAM (keep_alive=0).
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/// Used for predictable profile swaps — without this, Ollama holds a
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/// model for its configured TTL (default 5min) and the previous
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/// profile's model can linger in VRAM next to the new one.
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pub async fn unload_model(&self, model: &str) -> Result<serde_json::Value, String> {
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let resp = self.client
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.post(format!("{}/admin/unload", self.base_url))
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.json(&serde_json::json!({ "model": model }))
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.send().await
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.map_err(|e| format!("unload request failed: {e}"))?;
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if !resp.status().is_success() {
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let text = resp.text().await.unwrap_or_default();
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return Err(format!("unload error: {text}"));
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}
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resp.json().await.map_err(|e| format!("unload parse error: {e}"))
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}
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/// Ask Ollama to load the named model into VRAM proactively. Makes
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/// the first real request after profile activation fast (no cold-load
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/// latency).
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pub async fn preload_model(&self, model: &str) -> Result<serde_json::Value, String> {
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let resp = self.client
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.post(format!("{}/admin/preload", self.base_url))
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.json(&serde_json::json!({ "model": model }))
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.send().await
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.map_err(|e| format!("preload request failed: {e}"))?;
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if !resp.status().is_success() {
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let text = resp.text().await.unwrap_or_default();
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return Err(format!("preload error: {text}"));
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}
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resp.json().await.map_err(|e| format!("preload parse error: {e}"))
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}
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/// GPU + loaded-model snapshot from the sidecar. Combines nvidia-smi
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/// output (if available) with Ollama's /api/ps.
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pub async fn vram_snapshot(&self) -> Result<serde_json::Value, String> {
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let resp = self.client
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.get(format!("{}/admin/vram", self.base_url))
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.send().await
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.map_err(|e| format!("vram request failed: {e}"))?;
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resp.json().await.map_err(|e| format!("vram parse error: {e}"))
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}
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}
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@@ -16,9 +16,17 @@ pub fn router(client: AiClient) -> Router {
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.route("/embed", post(embed))
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.route("/generate", post(generate))
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.route("/rerank", post(rerank))
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.route("/vram", get(vram))
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.with_state(client)
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}
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async fn vram(State(client): State<AiClient>) -> impl IntoResponse {
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match client.vram_snapshot().await {
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Ok(snap) => Ok(Json(snap)),
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Err(e) => Err((StatusCode::BAD_GATEWAY, e)),
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}
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}
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async fn health(State(client): State<AiClient>) -> impl IntoResponse {
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match client.health().await {
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Ok(info) => Ok(Json(info)),
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@@ -357,6 +357,14 @@ struct CreateProfileRequest {
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embed_model: String,
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#[serde(default)]
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created_by: String,
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/// Federation: optional per-profile bucket (`profile:{id}` by convention).
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/// Omitting keeps artifacts in primary.
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#[serde(default)]
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bucket: Option<String>,
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/// ADR-019 hybrid: which vector backend to route this profile's
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/// indexes to. Defaults to Parquet+HNSW.
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#[serde(default)]
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vector_backend: shared::types::VectorBackend,
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}
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fn default_embed_model_req() -> String { "nomic-embed-text".to_string() }
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@@ -374,6 +382,8 @@ async fn create_profile(
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embed_model: req.embed_model,
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created_at: chrono::Utc::now(),
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created_by: req.created_by,
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bucket: req.bucket,
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vector_backend: req.vector_backend,
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};
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match registry.put_profile(profile).await {
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Ok(p) => Ok((StatusCode::CREATED, Json(p))),
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+53
-14
@@ -75,6 +75,41 @@ async fn main() {
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// AI sidecar client
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let ai_client = aibridge::client::AiClient::new(&config.sidecar.url);
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// Vector service components — built before the router because both the
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// /vectors service AND ingestd need the agent handle to enqueue triggers.
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let index_reg = vectord::index_registry::IndexRegistry::new(store.clone());
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let _ = index_reg.rebuild().await;
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let hnsw = vectord::hnsw::HnswStore::new();
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let emb_cache = vectord::embedding_cache::EmbeddingCache::new(store.clone());
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// Phase B (federation layer 2): trial journals + promotion files now
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// live in each index's recorded bucket (IndexMeta.bucket), not always
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// primary. Journal / registry resolve per-call via the bucket registry.
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let tj = vectord::trial::TrialJournal::new(bucket_registry.clone(), index_reg.clone());
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let pr = vectord::promotion::PromotionRegistry::new(bucket_registry.clone(), index_reg.clone());
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// Phase 16.2: spawn the autotune agent. When config.agent.enabled=false
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// this returns a handle that drops triggers silently — no surprise load.
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let agent_cfg = vectord::agent::AgentConfig {
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enabled: config.agent.enabled,
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cycle_interval_secs: config.agent.cycle_interval_secs,
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cooldown_between_trials_secs: config.agent.cooldown_between_trials_secs,
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min_recall: config.agent.min_recall,
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max_trials_per_hour: config.agent.max_trials_per_hour,
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};
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let agent_handle = vectord::agent::spawn(
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agent_cfg,
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vectord::agent::AgentDeps {
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store: store.clone(),
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ai_client: ai_client.clone(),
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catalog: registry.clone(),
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index_registry: index_reg.clone(),
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hnsw_store: hnsw.clone(),
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embedding_cache: emb_cache.clone(),
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trial_journal: tj.clone(),
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promotion_registry: pr.clone(),
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},
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);
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// HTTP router
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let mut app = Router::new()
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.route("/health", get(health))
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@@ -87,21 +122,25 @@ async fn main() {
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store: store.clone(),
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registry: registry.clone(),
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buckets: bucket_registry.clone(),
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agent_handle: agent_handle.clone(),
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index_registry: index_reg.clone(),
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}))
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.nest("/vectors", vectord::service::router({
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let index_reg = vectord::index_registry::IndexRegistry::new(store.clone());
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let _ = index_reg.rebuild().await;
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vectord::service::VectorState {
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store: store.clone(),
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ai_client: ai_client.clone(),
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job_tracker: vectord::jobs::JobTracker::new(),
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index_registry: index_reg,
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hnsw_store: vectord::hnsw::HnswStore::new(),
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embedding_cache: vectord::embedding_cache::EmbeddingCache::new(store.clone()),
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trial_journal: vectord::trial::TrialJournal::new(store.clone()),
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catalog: registry.clone(),
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promotion_registry: vectord::promotion::PromotionRegistry::new(store.clone()),
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}
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.nest("/vectors", vectord::service::router(vectord::service::VectorState {
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store: store.clone(),
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ai_client: ai_client.clone(),
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job_tracker: vectord::jobs::JobTracker::new(),
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index_registry: index_reg.clone(),
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hnsw_store: hnsw,
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embedding_cache: emb_cache,
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trial_journal: tj,
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catalog: registry.clone(),
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promotion_registry: pr,
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agent_handle,
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bucket_registry: bucket_registry.clone(),
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active_profile: std::sync::Arc::new(tokio::sync::RwLock::new(None)),
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lance: vectord::lance_backend::LanceRegistry::new(
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bucket_registry.clone(), index_reg.clone(),
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),
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}))
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.nest("/workspaces", queryd::workspace_service::router(workspace_mgr))
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.nest("/journal", journald::service::router(journal))
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@@ -7,6 +7,7 @@ edition = "2024"
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shared = { path = "../shared" }
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storaged = { path = "../storaged" }
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catalogd = { path = "../catalogd" }
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vectord = { path = "../vectord" }
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tokio = { workspace = true }
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axum = { workspace = true, features = ["multipart"] }
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lopdf = { workspace = true }
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@@ -21,4 +22,5 @@ csv = { workspace = true }
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chrono = { workspace = true }
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object_store = { workspace = true }
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tokio-postgres = { workspace = true }
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mysql_async = { workspace = true }
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uuid = { workspace = true }
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@@ -1,4 +1,5 @@
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pub mod db_ingest;
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pub mod my_stream;
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pub mod pg_stream;
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pub mod detect;
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pub mod csv_ingest;
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@@ -0,0 +1,410 @@
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/// Streaming MySQL ingest.
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///
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/// Mirrors `pg_stream` for MySQL sources. Same OFFSET-paginated strategy,
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/// same Parquet-streaming shape. Uses `mysql_async` (pure-rust) so we
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/// don't need a C client library at build time.
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///
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/// Type mapping follows ADR-010 (default to string on ambiguity):
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/// - Booleans (TINYINT(1)) and integer types map to Arrow Int32/Int64
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/// - Floating point and decimals → Float64
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/// - Everything else (text, varchar, json, date, timestamp) → Utf8
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///
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/// What's deliberately not supported (yet):
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/// - TLS connections — `minimal` feature is plain TCP only. Upgrade
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/// when a tenant actually needs it.
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/// - Keyset pagination — OFFSET scans are O(N²) at multi-million-row
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/// scale; same caveat as `pg_stream`.
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/// - BINARY/BLOB columns — currently rendered as base64 or empty string
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/// via Display-fallback.
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use arrow::array::{ArrayRef, BooleanArray, Float64Array, Int32Array, Int64Array, RecordBatch, StringArray};
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use arrow::datatypes::{DataType, Field, Schema};
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use mysql_async::prelude::*;
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use mysql_async::{Conn, Opts, Row, Value};
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use parquet::arrow::ArrowWriter;
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use std::sync::Arc;
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/// Request shape for MySQL streaming ingest.
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#[derive(Debug, Clone, serde::Deserialize)]
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pub struct MyStreamRequest {
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/// mysql://user:pass@host:port/db
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pub dsn: String,
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pub table: String,
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#[serde(default)]
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pub dataset_name: Option<String>,
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/// Rows per fetch. Default 10_000.
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#[serde(default)]
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pub batch_size: Option<usize>,
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/// Column to ORDER BY for stable pagination. If omitted, the first
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/// column returned by the schema probe is used.
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#[serde(default)]
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pub order_by: Option<String>,
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/// Hard cap on total rows (for sampling / previews).
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#[serde(default)]
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pub limit: Option<usize>,
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}
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#[derive(Debug, Clone, serde::Serialize)]
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pub struct MyStreamResult {
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pub table: String,
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pub rows: usize,
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pub batches: usize,
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pub columns: usize,
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pub schema: Vec<String>,
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pub parquet_bytes: u64,
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pub duration_secs: f32,
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}
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/// Parsed DSN pieces. Kept local (rather than reusing pg's DbConfig) so
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/// the MySQL connector doesn't depend on the PG path.
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#[derive(Debug, Clone)]
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pub struct MyConfig {
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pub host: String,
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pub port: u16,
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pub user: String,
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pub password: String,
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pub database: String,
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}
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impl MyConfig {
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/// Build a mysql_async `Opts` from the parsed config.
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pub fn to_opts(&self) -> Opts {
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let url = if self.password.is_empty() {
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format!(
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"mysql://{}@{}:{}/{}",
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percent(&self.user), percent(&self.host), self.port, percent(&self.database),
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)
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} else {
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format!(
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"mysql://{}:{}@{}:{}/{}",
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percent(&self.user), percent(&self.password),
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percent(&self.host), self.port, percent(&self.database),
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)
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};
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Opts::from_url(&url).expect("MyConfig.to_opts: rebuilt URL should parse")
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}
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}
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/// Minimal URL-encoder for the few characters that commonly appear in
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/// MySQL passwords. mysql_async's URL parser expects valid URL-encoded
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/// components.
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fn percent(s: &str) -> String {
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let mut out = String::with_capacity(s.len());
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for c in s.chars() {
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match c {
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'@' | ':' | '/' | '?' | '#' | '[' | ']' | ' ' | '%' => {
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out.push_str(&format!("%{:02X}", c as u32));
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}
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_ => out.push(c),
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}
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}
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out
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}
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/// Parse a mysql:// DSN.
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/// Supports: mysql://[user[:password]@]host[:port][/db]
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pub fn parse_dsn(dsn: &str) -> Result<MyConfig, String> {
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let rest = dsn
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.strip_prefix("mysql://")
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.ok_or_else(|| "DSN must start with mysql://".to_string())?;
|
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|
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let (auth_host, database) = match rest.split_once('/') {
|
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Some((ah, db)) => (ah, db.split('?').next().unwrap_or(db).to_string()),
|
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None => (rest, String::new()),
|
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};
|
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|
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let (userpass, hostport) = match auth_host.rsplit_once('@') {
|
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Some((up, hp)) => (Some(up), hp),
|
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None => (None, auth_host),
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};
|
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|
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let (user, password) = match userpass {
|
||||
Some(up) => match up.split_once(':') {
|
||||
Some((u, p)) => (u.to_string(), p.to_string()),
|
||||
None => (up.to_string(), String::new()),
|
||||
},
|
||||
None => ("root".to_string(), String::new()),
|
||||
};
|
||||
|
||||
let (host, port) = match hostport.rsplit_once(':') {
|
||||
Some((h, p)) => (
|
||||
h.to_string(),
|
||||
p.parse::<u16>().map_err(|_| format!("invalid port in DSN: {p}"))?,
|
||||
),
|
||||
None => (hostport.to_string(), 3306),
|
||||
};
|
||||
|
||||
if host.is_empty() {
|
||||
return Err("DSN has no host".into());
|
||||
}
|
||||
if database.is_empty() {
|
||||
return Err("DSN has no database path (mysql://... /db)".into());
|
||||
}
|
||||
|
||||
Ok(MyConfig { host, port, user, password, database })
|
||||
}
|
||||
|
||||
/// Stream a MySQL table as Parquet bytes.
|
||||
pub async fn stream_table_to_parquet(
|
||||
req: &MyStreamRequest,
|
||||
) -> Result<(bytes::Bytes, MyStreamResult), String> {
|
||||
let t0 = std::time::Instant::now();
|
||||
let config = parse_dsn(&req.dsn)?;
|
||||
let batch_size = req.batch_size.unwrap_or(10_000).max(1);
|
||||
|
||||
let mut conn = Conn::new(config.to_opts()).await
|
||||
.map_err(|e| format!("mysql connect: {e}"))?;
|
||||
|
||||
// Probe columns via information_schema — gives real type names that
|
||||
// we can map to Arrow dtypes without needing to fetch a row first.
|
||||
let columns = probe_columns(&mut conn, &config.database, &req.table).await?;
|
||||
if columns.is_empty() {
|
||||
return Err(format!("table '{}' not found or has no columns", req.table));
|
||||
}
|
||||
|
||||
let arrow_fields: Vec<Field> = columns
|
||||
.iter()
|
||||
.map(|(name, ty)| Field::new(name, mysql_type_to_arrow(ty), true))
|
||||
.collect();
|
||||
let schema = Arc::new(Schema::new(arrow_fields));
|
||||
let schema_report: Vec<String> = columns
|
||||
.iter()
|
||||
.map(|(n, t)| format!("{}:{}", n, t))
|
||||
.collect();
|
||||
|
||||
let order_col = req.order_by.clone().unwrap_or_else(|| columns[0].0.clone());
|
||||
|
||||
let mut buf: Vec<u8> = Vec::with_capacity(1024 * 1024);
|
||||
let mut writer = ArrowWriter::try_new(&mut buf, schema.clone(), None)
|
||||
.map_err(|e| format!("ArrowWriter init: {e}"))?;
|
||||
|
||||
let mut total_rows: usize = 0;
|
||||
let mut batch_count: usize = 0;
|
||||
let row_cap = req.limit.unwrap_or(usize::MAX);
|
||||
|
||||
loop {
|
||||
let remaining = row_cap.saturating_sub(total_rows);
|
||||
if remaining == 0 { break; }
|
||||
let fetch = remaining.min(batch_size);
|
||||
|
||||
// Backticks are MySQL's identifier quote. Forbid backticks in
|
||||
// table/column names to prevent injection — neither pg nor us
|
||||
// should be accepting those anyway.
|
||||
if req.table.contains('`') || order_col.contains('`') {
|
||||
return Err("table or order_by column contains backticks — refused".into());
|
||||
}
|
||||
let sql = format!(
|
||||
"SELECT * FROM `{}` ORDER BY `{}` LIMIT {} OFFSET {}",
|
||||
req.table, order_col, fetch, total_rows,
|
||||
);
|
||||
|
||||
let rows: Vec<Row> = conn.query(&sql).await
|
||||
.map_err(|e| format!("fetch batch at offset {total_rows}: {e}"))?;
|
||||
|
||||
if rows.is_empty() { break; }
|
||||
let n = rows.len();
|
||||
|
||||
let arrays: Vec<ArrayRef> = columns
|
||||
.iter()
|
||||
.enumerate()
|
||||
.map(|(idx, (_, ty))| rows_to_column(&rows, idx, ty))
|
||||
.collect::<Result<_, _>>()?;
|
||||
let batch = RecordBatch::try_new(schema.clone(), arrays)
|
||||
.map_err(|e| format!("RecordBatch: {e}"))?;
|
||||
writer.write(&batch).map_err(|e| format!("ArrowWriter::write: {e}"))?;
|
||||
|
||||
total_rows += n;
|
||||
batch_count += 1;
|
||||
tracing::info!(
|
||||
"mysql stream '{}': fetched batch {} ({} rows, total {})",
|
||||
req.table, batch_count, n, total_rows,
|
||||
);
|
||||
|
||||
if n < fetch { break; }
|
||||
}
|
||||
|
||||
writer.close().map_err(|e| format!("ArrowWriter::close: {e}"))?;
|
||||
conn.disconnect().await.ok();
|
||||
|
||||
let result = MyStreamResult {
|
||||
table: req.table.clone(),
|
||||
rows: total_rows,
|
||||
batches: batch_count,
|
||||
columns: columns.len(),
|
||||
schema: schema_report,
|
||||
parquet_bytes: buf.len() as u64,
|
||||
duration_secs: t0.elapsed().as_secs_f32(),
|
||||
};
|
||||
|
||||
Ok((bytes::Bytes::from(buf), result))
|
||||
}
|
||||
|
||||
async fn probe_columns(
|
||||
conn: &mut Conn,
|
||||
schema: &str,
|
||||
table: &str,
|
||||
) -> Result<Vec<(String, String)>, String> {
|
||||
let sql = format!(
|
||||
"SELECT COLUMN_NAME, DATA_TYPE FROM information_schema.columns \
|
||||
WHERE table_schema = '{}' AND table_name = '{}' \
|
||||
ORDER BY ORDINAL_POSITION",
|
||||
schema.replace('\'', "''"),
|
||||
table.replace('\'', "''"),
|
||||
);
|
||||
let rows: Vec<(String, String)> = conn.query(&sql).await
|
||||
.map_err(|e| format!("probe columns: {e}"))?;
|
||||
Ok(rows)
|
||||
}
|
||||
|
||||
/// MySQL data type string → Arrow DataType. Conservative: anything we
|
||||
/// don't recognize becomes Utf8 (ADR-010).
|
||||
fn mysql_type_to_arrow(ty: &str) -> DataType {
|
||||
match ty.to_lowercase().as_str() {
|
||||
"tinyint" | "smallint" | "mediumint" | "int" | "integer" => DataType::Int32,
|
||||
"bigint" => DataType::Int64,
|
||||
"float" | "double" | "decimal" | "numeric" | "real" => DataType::Float64,
|
||||
"bit" | "bool" | "boolean" => DataType::Boolean,
|
||||
_ => DataType::Utf8,
|
||||
}
|
||||
}
|
||||
|
||||
/// Convert a single column slice of MySQL rows into an Arrow array.
|
||||
fn rows_to_column(
|
||||
rows: &[Row],
|
||||
idx: usize,
|
||||
ty: &str,
|
||||
) -> Result<ArrayRef, String> {
|
||||
let arrow_ty = mysql_type_to_arrow(ty);
|
||||
match arrow_ty {
|
||||
DataType::Boolean => {
|
||||
let v: Vec<Option<bool>> = rows.iter().map(|r| cell_as_bool(r, idx)).collect();
|
||||
Ok(Arc::new(BooleanArray::from(v)))
|
||||
}
|
||||
DataType::Int32 => {
|
||||
let v: Vec<Option<i32>> = rows.iter().map(|r| cell_as_i64(r, idx).map(|n| n as i32)).collect();
|
||||
Ok(Arc::new(Int32Array::from(v)))
|
||||
}
|
||||
DataType::Int64 => {
|
||||
let v: Vec<Option<i64>> = rows.iter().map(|r| cell_as_i64(r, idx)).collect();
|
||||
Ok(Arc::new(Int64Array::from(v)))
|
||||
}
|
||||
DataType::Float64 => {
|
||||
let v: Vec<Option<f64>> = rows.iter().map(|r| cell_as_f64(r, idx)).collect();
|
||||
Ok(Arc::new(Float64Array::from(v)))
|
||||
}
|
||||
_ => {
|
||||
let v: Vec<Option<String>> = rows.iter().map(|r| cell_as_string(r, idx)).collect();
|
||||
Ok(Arc::new(StringArray::from(v)))
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
fn cell(r: &Row, idx: usize) -> &Value { r.as_ref(idx).unwrap_or(&Value::NULL) }
|
||||
|
||||
fn cell_as_bool(r: &Row, idx: usize) -> Option<bool> {
|
||||
match cell(r, idx) {
|
||||
Value::NULL => None,
|
||||
Value::Int(n) => Some(*n != 0),
|
||||
Value::UInt(n) => Some(*n != 0),
|
||||
Value::Bytes(b) => std::str::from_utf8(b).ok().and_then(|s| {
|
||||
match s.to_ascii_lowercase().as_str() {
|
||||
"true" | "1" | "y" | "yes" => Some(true),
|
||||
"false" | "0" | "n" | "no" => Some(false),
|
||||
_ => None,
|
||||
}
|
||||
}),
|
||||
_ => None,
|
||||
}
|
||||
}
|
||||
|
||||
fn cell_as_i64(r: &Row, idx: usize) -> Option<i64> {
|
||||
match cell(r, idx) {
|
||||
Value::NULL => None,
|
||||
Value::Int(n) => Some(*n),
|
||||
Value::UInt(n) => i64::try_from(*n).ok(),
|
||||
Value::Float(f) => Some(*f as i64),
|
||||
Value::Double(f) => Some(*f as i64),
|
||||
Value::Bytes(b) => std::str::from_utf8(b).ok().and_then(|s| s.parse().ok()),
|
||||
_ => None,
|
||||
}
|
||||
}
|
||||
|
||||
fn cell_as_f64(r: &Row, idx: usize) -> Option<f64> {
|
||||
match cell(r, idx) {
|
||||
Value::NULL => None,
|
||||
Value::Int(n) => Some(*n as f64),
|
||||
Value::UInt(n) => Some(*n as f64),
|
||||
Value::Float(f) => Some(*f as f64),
|
||||
Value::Double(f) => Some(*f),
|
||||
Value::Bytes(b) => std::str::from_utf8(b).ok().and_then(|s| s.parse().ok()),
|
||||
_ => None,
|
||||
}
|
||||
}
|
||||
|
||||
fn cell_as_string(r: &Row, idx: usize) -> Option<String> {
|
||||
match cell(r, idx) {
|
||||
Value::NULL => None,
|
||||
Value::Bytes(b) => Some(String::from_utf8_lossy(b).into_owned()),
|
||||
Value::Int(n) => Some(n.to_string()),
|
||||
Value::UInt(n) => Some(n.to_string()),
|
||||
Value::Float(f) => Some(f.to_string()),
|
||||
Value::Double(f) => Some(f.to_string()),
|
||||
Value::Date(y, mo, d, h, mi, s, _us) => {
|
||||
Some(format!("{:04}-{:02}-{:02} {:02}:{:02}:{:02}", y, mo, d, h, mi, s))
|
||||
}
|
||||
Value::Time(neg, days, h, mi, s, _us) => {
|
||||
let sign = if *neg { "-" } else { "" };
|
||||
Some(format!("{}{}d {:02}:{:02}:{:02}", sign, days, h, mi, s))
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
|
||||
#[test]
|
||||
fn parse_dsn_full() {
|
||||
let c = parse_dsn("mysql://daisy:secret@db.example.com:3307/my_db").unwrap();
|
||||
assert_eq!(c.host, "db.example.com");
|
||||
assert_eq!(c.port, 3307);
|
||||
assert_eq!(c.user, "daisy");
|
||||
assert_eq!(c.password, "secret");
|
||||
assert_eq!(c.database, "my_db");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn parse_dsn_default_port() {
|
||||
let c = parse_dsn("mysql://root@localhost/shop").unwrap();
|
||||
assert_eq!(c.port, 3306);
|
||||
assert_eq!(c.user, "root");
|
||||
assert_eq!(c.password, "");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn parse_dsn_no_auth() {
|
||||
let c = parse_dsn("mysql://127.0.0.1:3306/analytics").unwrap();
|
||||
assert_eq!(c.user, "root");
|
||||
assert_eq!(c.host, "127.0.0.1");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn parse_dsn_rejects_non_mysql() {
|
||||
assert!(parse_dsn("postgresql://host/db").is_err());
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn parse_dsn_requires_db() {
|
||||
assert!(parse_dsn("mysql://localhost:3306").is_err());
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn type_map_basics() {
|
||||
assert_eq!(mysql_type_to_arrow("int"), DataType::Int32);
|
||||
assert_eq!(mysql_type_to_arrow("BIGINT"), DataType::Int64);
|
||||
assert_eq!(mysql_type_to_arrow("decimal"), DataType::Float64);
|
||||
assert_eq!(mysql_type_to_arrow("varchar"), DataType::Utf8);
|
||||
assert_eq!(mysql_type_to_arrow("json"), DataType::Utf8);
|
||||
assert_eq!(mysql_type_to_arrow("bool"), DataType::Boolean);
|
||||
}
|
||||
}
|
||||
+152
-13
@@ -11,7 +11,7 @@ use serde::Deserialize;
|
||||
use std::sync::Arc;
|
||||
|
||||
use catalogd::registry::Registry;
|
||||
use crate::{db_ingest, pg_stream, pipeline};
|
||||
use crate::{db_ingest, my_stream, pg_stream, pipeline};
|
||||
use shared::arrow_helpers::record_batch_to_parquet;
|
||||
use shared::types::{ObjectRef, SchemaFingerprint};
|
||||
use storaged::ops;
|
||||
@@ -23,6 +23,36 @@ pub struct IngestState {
|
||||
pub registry: Registry,
|
||||
/// Federation layer 2: lookup target bucket from request headers.
|
||||
pub buckets: Arc<BucketRegistry>,
|
||||
/// Phase 16.5: when ingest marks a dataset's embeddings stale, push
|
||||
/// a `DatasetAppended` trigger so the autotune agent can schedule
|
||||
/// re-trials. Holds the agent handle (no-op when agent disabled).
|
||||
pub agent_handle: vectord::agent::AgentHandle,
|
||||
/// Used to look up which HNSW indexes are attached to the
|
||||
/// just-ingested dataset. Each matching index gets one trigger.
|
||||
pub index_registry: vectord::index_registry::IndexRegistry,
|
||||
}
|
||||
|
||||
/// Push `DatasetAppended` triggers for every HNSW index bound to this
|
||||
/// dataset. Called after a successful ingest. Logs failures but never
|
||||
/// fails the ingest — the agent is best-effort, not load-bearing.
|
||||
async fn notify_agent_on_append(state: &IngestState, dataset_name: &str) {
|
||||
let indexes = state.index_registry.list(Some(dataset_name), None).await;
|
||||
if indexes.is_empty() {
|
||||
return;
|
||||
}
|
||||
for meta in indexes {
|
||||
let event = vectord::agent::TriggerEvent::dataset_appended(
|
||||
meta.index_name.clone(), dataset_name,
|
||||
);
|
||||
if let Err(e) = state.agent_handle.enqueue(event).await {
|
||||
tracing::warn!("agent enqueue failed for '{}': {}", meta.index_name, e);
|
||||
} else {
|
||||
tracing::info!(
|
||||
"agent: enqueued DatasetAppended({}) for index '{}'",
|
||||
dataset_name, meta.index_name,
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Resolve the target bucket from `X-Lakehouse-Bucket` header.
|
||||
@@ -55,6 +85,7 @@ pub fn router(state: IngestState) -> Router {
|
||||
.route("/postgres/tables", post(list_pg_tables))
|
||||
.route("/postgres/import", post(import_pg_table))
|
||||
.route("/db", post(ingest_db_stream))
|
||||
.route("/mysql", post(ingest_mysql_stream))
|
||||
.with_state(state)
|
||||
}
|
||||
|
||||
@@ -94,6 +125,9 @@ async fn ingest_file(
|
||||
|
||||
match pipeline::ingest_file_to_bucket(&filename, &content, dataset_name, &bucket, &store, &state.registry).await {
|
||||
Ok(result) => {
|
||||
if !result.deduplicated {
|
||||
notify_agent_on_append(&state, &result.dataset_name).await;
|
||||
}
|
||||
if result.deduplicated {
|
||||
Ok((StatusCode::OK, Json(result)))
|
||||
} else {
|
||||
@@ -309,6 +343,9 @@ async fn ingest_db_stream(
|
||||
// index. No-op for newly-created datasets.
|
||||
let _ = state.registry.mark_embeddings_stale(&dataset_name).await;
|
||||
|
||||
// Phase 16.5: notify autotune agent. No-op if no indexes attached.
|
||||
notify_agent_on_append(&state, &dataset_name).await;
|
||||
|
||||
Ok((StatusCode::CREATED, Json(serde_json::json!({
|
||||
"dataset_name": dataset_name,
|
||||
"table": stream_result.table,
|
||||
@@ -322,17 +359,119 @@ async fn ingest_db_stream(
|
||||
}))))
|
||||
}
|
||||
|
||||
/// Redact the password in a postgresql:// DSN for logging / lineage.
|
||||
fn redact_dsn(dsn: &str) -> String {
|
||||
// Simple approach: find @...: and replace password between : and @.
|
||||
if let Some(at_idx) = dsn.rfind('@') {
|
||||
let prefix = &dsn[..at_idx];
|
||||
if let Some(colon_idx) = prefix.rfind(':') {
|
||||
// But only if the colon is after the scheme colons (postgresql://)
|
||||
if colon_idx > "postgresql://".len() {
|
||||
return format!("{}:***{}", &dsn[..colon_idx], &dsn[at_idx..]);
|
||||
}
|
||||
}
|
||||
/// Streaming MySQL ingest. Mirrors `ingest_db_stream` — same pagination +
|
||||
/// Parquet-footer schema recovery + PII/lineage metadata. Different driver,
|
||||
/// otherwise identical.
|
||||
async fn ingest_mysql_stream(
|
||||
State(state): State<IngestState>,
|
||||
headers: HeaderMap,
|
||||
Json(req): Json<my_stream::MyStreamRequest>,
|
||||
) -> Result<(StatusCode, Json<serde_json::Value>), (StatusCode, String)> {
|
||||
let (bucket, store) = resolve_bucket(&headers, &state.buckets)?;
|
||||
tracing::info!(
|
||||
"mysql stream ingest: table='{}' dataset='{:?}' bucket='{}' batch_size={:?}",
|
||||
req.table, req.dataset_name, bucket, req.batch_size,
|
||||
);
|
||||
|
||||
let (parquet, stream_result) = my_stream::stream_table_to_parquet(&req)
|
||||
.await
|
||||
.map_err(|e| (StatusCode::BAD_GATEWAY, e))?;
|
||||
|
||||
if stream_result.rows == 0 {
|
||||
return Ok((StatusCode::OK, Json(serde_json::json!({
|
||||
"table": req.table,
|
||||
"rows": 0,
|
||||
"message": "table is empty",
|
||||
}))));
|
||||
}
|
||||
dsn.to_string()
|
||||
|
||||
let (schema, _) = shared::arrow_helpers::parquet_to_record_batches(&parquet)
|
||||
.map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, format!("reparse parquet: {e}")))?;
|
||||
|
||||
let dataset_name = req.dataset_name.clone().unwrap_or_else(|| req.table.clone());
|
||||
let storage_key = format!("datasets/{}.parquet", dataset_name);
|
||||
let size_bytes = parquet.len() as u64;
|
||||
|
||||
ops::put(&store, &storage_key, parquet)
|
||||
.await
|
||||
.map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, e))?;
|
||||
|
||||
let schema_fp = shared::arrow_helpers::fingerprint_schema(&schema);
|
||||
let now = chrono::Utc::now();
|
||||
state.registry.register(
|
||||
dataset_name.clone(),
|
||||
SchemaFingerprint(schema_fp.0),
|
||||
vec![ObjectRef {
|
||||
bucket: bucket.clone(),
|
||||
key: storage_key.clone(),
|
||||
size_bytes,
|
||||
created_at: now,
|
||||
}],
|
||||
).await.map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, e))?;
|
||||
|
||||
let col_names: Vec<&str> = schema.fields().iter().map(|f| f.name().as_str()).collect();
|
||||
let sensitivity = shared::pii::detect_dataset_sensitivity(&col_names);
|
||||
let columns: Vec<shared::types::ColumnMeta> = schema.fields().iter().map(|f| {
|
||||
let sens = shared::pii::detect_sensitivity(f.name());
|
||||
shared::types::ColumnMeta {
|
||||
name: f.name().clone(),
|
||||
data_type: f.data_type().to_string(),
|
||||
sensitivity: sens.clone(),
|
||||
description: String::new(),
|
||||
is_pii: matches!(sens, Some(shared::types::Sensitivity::Pii)),
|
||||
}
|
||||
}).collect();
|
||||
|
||||
let lineage = shared::types::Lineage {
|
||||
source_system: "mysql".to_string(),
|
||||
source_file: format!("dsn: {}", redact_dsn(&req.dsn)),
|
||||
ingest_job: format!("mysql-stream-{}", now.timestamp_millis()),
|
||||
ingest_timestamp: now,
|
||||
parent_datasets: vec![],
|
||||
};
|
||||
|
||||
let _ = state.registry.update_metadata(&dataset_name, catalogd::registry::MetadataUpdate {
|
||||
sensitivity,
|
||||
columns: Some(columns),
|
||||
lineage: Some(lineage),
|
||||
row_count: Some(stream_result.rows as u64),
|
||||
..Default::default()
|
||||
}).await;
|
||||
|
||||
// Phase C: mark stale + Phase 16.5: notify agent.
|
||||
let _ = state.registry.mark_embeddings_stale(&dataset_name).await;
|
||||
notify_agent_on_append(&state, &dataset_name).await;
|
||||
|
||||
Ok((StatusCode::CREATED, Json(serde_json::json!({
|
||||
"dataset_name": dataset_name,
|
||||
"table": stream_result.table,
|
||||
"rows": stream_result.rows,
|
||||
"batches": stream_result.batches,
|
||||
"columns": stream_result.columns,
|
||||
"schema": stream_result.schema,
|
||||
"storage_key": storage_key,
|
||||
"size_bytes": size_bytes,
|
||||
"duration_secs": stream_result.duration_secs,
|
||||
}))))
|
||||
}
|
||||
|
||||
/// Redact the password in any `scheme://user:pass@host/...` DSN. Works
|
||||
/// for postgres, mysql, and any other scheme using the same shape.
|
||||
fn redact_dsn(dsn: &str) -> String {
|
||||
let scheme_end = match dsn.find("://") {
|
||||
Some(i) => i + 3,
|
||||
None => return dsn.to_string(),
|
||||
};
|
||||
let at_idx = match dsn.rfind('@') {
|
||||
Some(i) if i > scheme_end => i,
|
||||
_ => return dsn.to_string(),
|
||||
};
|
||||
// Find the password separator (first `:` after scheme, before `@`).
|
||||
let userpass = &dsn[scheme_end..at_idx];
|
||||
let colon_offset = match userpass.find(':') {
|
||||
Some(i) => i,
|
||||
None => return dsn.to_string(), // no password in DSN
|
||||
};
|
||||
let colon_idx = scheme_end + colon_offset;
|
||||
format!("{}:***{}", &dsn[..colon_idx], &dsn[at_idx..])
|
||||
}
|
||||
|
||||
@@ -16,8 +16,46 @@ pub struct Config {
|
||||
pub auth: AuthConfig,
|
||||
#[serde(default)]
|
||||
pub observability: ObservabilityConfig,
|
||||
#[serde(default)]
|
||||
pub agent: AgentSettings,
|
||||
}
|
||||
|
||||
/// Phase 16.2 — background autotune agent settings.
|
||||
///
|
||||
/// Duplicated from `vectord::agent::AgentConfig` because `shared` can't
|
||||
/// depend on `vectord` (vectord already depends on shared). The gateway
|
||||
/// copies these into the vectord config at startup.
|
||||
#[derive(Debug, Clone, Deserialize)]
|
||||
pub struct AgentSettings {
|
||||
#[serde(default)]
|
||||
pub enabled: bool,
|
||||
#[serde(default = "default_cycle_interval_secs")]
|
||||
pub cycle_interval_secs: u64,
|
||||
#[serde(default = "default_cooldown_secs")]
|
||||
pub cooldown_between_trials_secs: u64,
|
||||
#[serde(default = "default_min_recall")]
|
||||
pub min_recall: f32,
|
||||
#[serde(default = "default_max_trials_per_hour")]
|
||||
pub max_trials_per_hour: u32,
|
||||
}
|
||||
|
||||
impl Default for AgentSettings {
|
||||
fn default() -> Self {
|
||||
Self {
|
||||
enabled: false,
|
||||
cycle_interval_secs: default_cycle_interval_secs(),
|
||||
cooldown_between_trials_secs: default_cooldown_secs(),
|
||||
min_recall: default_min_recall(),
|
||||
max_trials_per_hour: default_max_trials_per_hour(),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
fn default_cycle_interval_secs() -> u64 { 60 }
|
||||
fn default_cooldown_secs() -> u64 { 30 }
|
||||
fn default_min_recall() -> f32 { 0.9 }
|
||||
fn default_max_trials_per_hour() -> u32 { 30 }
|
||||
|
||||
#[derive(Debug, Clone, Deserialize)]
|
||||
pub struct GatewayConfig {
|
||||
#[serde(default = "default_host")]
|
||||
@@ -159,6 +197,7 @@ impl Default for Config {
|
||||
ai: AiConfig::default(),
|
||||
auth: AuthConfig::default(),
|
||||
observability: ObservabilityConfig::default(),
|
||||
agent: AgentSettings::default(),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -255,10 +255,55 @@ pub struct ModelProfile {
|
||||
pub created_at: chrono::DateTime<chrono::Utc>,
|
||||
#[serde(default)]
|
||||
pub created_by: String,
|
||||
/// Federation layer 2: which bucket this profile's artifacts
|
||||
/// (trial journals, promotions for its indexes) live in. If set and
|
||||
/// not yet registered, `POST /vectors/profile/{id}/activate` auto-
|
||||
/// provisions a local bucket under `storage.profile_root` and
|
||||
/// registers it before warming indexes. `None` = share the primary
|
||||
/// bucket (pre-federation behavior).
|
||||
#[serde(default)]
|
||||
pub bucket: Option<String>,
|
||||
/// ADR-019 hybrid: which storage backend serves this profile's
|
||||
/// indexes. Default Parquet so pre-existing profiles unchanged.
|
||||
/// New profiles can opt into Lance for append-heavy / random-access
|
||||
/// / 5M+ vector workloads.
|
||||
#[serde(default)]
|
||||
pub vector_backend: VectorBackend,
|
||||
}
|
||||
|
||||
fn default_embed_model() -> String { "nomic-embed-text".to_string() }
|
||||
|
||||
/// Per-profile / per-index storage backend choice.
|
||||
///
|
||||
/// `Parquet` (default) — vectors as binary-blob in Parquet + in-RAM HNSW
|
||||
/// for ANN. Best when:
|
||||
/// - Index ≤ ~5M vectors (fits in RAM)
|
||||
/// - Search latency dominates (HNSW p50 < 1ms at 100K)
|
||||
/// - Workload is mostly read, not append
|
||||
///
|
||||
/// `Lance` — vectors as native FixedSizeList in a Lance dataset, IVF_PQ
|
||||
/// on-disk index. Best when:
|
||||
/// - Index will exceed RAM ceiling (5M+ vectors per index)
|
||||
/// - Heavy random-row access for RAG (Lance: 311us; Parquet: ~35ms full
|
||||
/// scan per fetch)
|
||||
/// - Append-heavy ingest (Lance: 0.08s for 10K rows; Parquet: full
|
||||
/// ~330MB rewrite per change)
|
||||
/// - Need to rebuild index frequently (Lance IVF_PQ: 16s; HNSW: 230s
|
||||
/// at the same scale)
|
||||
///
|
||||
/// Defaults to Parquet for backward compat with pre-ADR-019 indexes.
|
||||
/// See `docs/ADR-019-vector-storage.md` for the full scorecard.
|
||||
#[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq)]
|
||||
#[serde(rename_all = "lowercase")]
|
||||
pub enum VectorBackend {
|
||||
Parquet,
|
||||
Lance,
|
||||
}
|
||||
|
||||
impl Default for VectorBackend {
|
||||
fn default() -> Self { VectorBackend::Parquet }
|
||||
}
|
||||
|
||||
/// Soft-delete marker (Phase E).
|
||||
///
|
||||
/// Tombstones live beside the dataset in `_catalog/tombstones/{dataset}/`
|
||||
|
||||
@@ -13,10 +13,11 @@ use axum::{
|
||||
extract::{Path, Query, State},
|
||||
http::StatusCode,
|
||||
response::IntoResponse,
|
||||
routing::{get, put},
|
||||
routing::{delete, get, post, put},
|
||||
};
|
||||
use chrono::{DateTime, Utc};
|
||||
use serde::Deserialize;
|
||||
use shared::config::BucketConfig;
|
||||
use std::sync::Arc;
|
||||
|
||||
use crate::error_journal::BucketErrorEvent;
|
||||
@@ -24,16 +25,68 @@ use crate::registry::{BucketInfo, BucketRegistry};
|
||||
|
||||
pub fn router(registry: Arc<BucketRegistry>) -> Router {
|
||||
Router::new()
|
||||
.route("/buckets", get(list_buckets))
|
||||
.route("/buckets", get(list_buckets).post(add_bucket))
|
||||
.route("/buckets/{name}", delete(remove_bucket))
|
||||
.route("/errors", get(list_errors))
|
||||
.route("/errors/flush", axum::routing::post(flush_errors))
|
||||
.route("/errors/compact", axum::routing::post(compact_errors))
|
||||
.route("/errors/flush", post(flush_errors))
|
||||
.route("/errors/compact", post(compact_errors))
|
||||
.route("/bucket-health", get(get_health))
|
||||
.route("/buckets/{bucket}/objects/{*key}", put(put_bucket_object))
|
||||
.route("/buckets/{bucket}/objects/{*key}", get(get_bucket_object))
|
||||
.with_state(registry)
|
||||
}
|
||||
|
||||
/// Provision + register a bucket at runtime. Body is a `BucketConfig`.
|
||||
///
|
||||
/// Federation layer 2: profile buckets (`profile:alice`) and tenant
|
||||
/// buckets can be added after startup without a service restart.
|
||||
async fn add_bucket(
|
||||
State(reg): State<Arc<BucketRegistry>>,
|
||||
Json(bc): Json<BucketConfig>,
|
||||
) -> impl IntoResponse {
|
||||
// Safety net: local backends must land somewhere under the configured
|
||||
// profile_root (for profile:*) or be otherwise explicitly rooted.
|
||||
// Refuse empty / missing root to avoid "bucket created at ./" surprises.
|
||||
if bc.backend == "local" {
|
||||
match bc.root.as_deref() {
|
||||
Some(r) if !r.trim().is_empty() => {}
|
||||
_ => return Err((StatusCode::BAD_REQUEST,
|
||||
"local bucket requires a non-empty 'root' path".to_string())),
|
||||
}
|
||||
}
|
||||
match reg.add_bucket(bc).await {
|
||||
Ok(info) => Ok((StatusCode::CREATED, Json(info))),
|
||||
Err(e) => {
|
||||
let code = if e.contains("already registered") {
|
||||
StatusCode::CONFLICT
|
||||
} else {
|
||||
StatusCode::BAD_REQUEST
|
||||
};
|
||||
Err((code, e))
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Unregister a bucket. Refused for primary / rescue / unknown names.
|
||||
async fn remove_bucket(
|
||||
State(reg): State<Arc<BucketRegistry>>,
|
||||
Path(name): Path<String>,
|
||||
) -> impl IntoResponse {
|
||||
match reg.remove_bucket(&name) {
|
||||
Ok(()) => Ok((StatusCode::OK, format!("unregistered: {name}"))),
|
||||
Err(e) => {
|
||||
let code = if e.contains("cannot remove") {
|
||||
StatusCode::FORBIDDEN
|
||||
} else if e.contains("not registered") {
|
||||
StatusCode::NOT_FOUND
|
||||
} else {
|
||||
StatusCode::BAD_REQUEST
|
||||
};
|
||||
Err((code, e))
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
async fn list_buckets(State(reg): State<Arc<BucketRegistry>>) -> Json<Vec<BucketInfo>> {
|
||||
Json(reg.list().await)
|
||||
}
|
||||
|
||||
+111
-23
@@ -15,7 +15,7 @@ use serde::Serialize;
|
||||
use shared::config::{BucketConfig, StorageConfig};
|
||||
use shared::secrets::{BucketCredentials, SecretsProvider};
|
||||
use std::collections::HashMap;
|
||||
use std::sync::Arc;
|
||||
use std::sync::{Arc, RwLock};
|
||||
|
||||
use crate::error_journal::{BucketErrorEvent, ErrorJournal};
|
||||
|
||||
@@ -55,10 +55,16 @@ pub enum BucketRole {
|
||||
}
|
||||
|
||||
pub struct BucketRegistry {
|
||||
buckets: HashMap<String, Arc<BucketEntry>>,
|
||||
/// RwLock because federation layer 2 adds runtime bucket lifecycle
|
||||
/// (`POST /storage/buckets` / `DELETE /storage/buckets/{name}`).
|
||||
/// Almost all accesses are reads — writes happen at provision /
|
||||
/// deactivate time only.
|
||||
buckets: RwLock<HashMap<String, Arc<BucketEntry>>>,
|
||||
default: String,
|
||||
rescue: Option<String>,
|
||||
profile_root: String,
|
||||
/// Held so runtime `add_bucket` can resolve secret_ref handles.
|
||||
secrets: Arc<dyn SecretsProvider>,
|
||||
journal: ErrorJournal,
|
||||
}
|
||||
|
||||
@@ -113,10 +119,11 @@ impl BucketRegistry {
|
||||
let _ = journal.load_recent().await;
|
||||
|
||||
Ok(Self {
|
||||
buckets,
|
||||
buckets: RwLock::new(buckets),
|
||||
default: "primary".to_string(),
|
||||
rescue: cfg.rescue_bucket.clone(),
|
||||
profile_root: cfg.profile_root.clone(),
|
||||
secrets,
|
||||
journal,
|
||||
})
|
||||
}
|
||||
@@ -125,12 +132,19 @@ impl BucketRegistry {
|
||||
|
||||
pub fn rescue_name(&self) -> Option<&str> { self.rescue.as_deref() }
|
||||
|
||||
pub fn profile_root(&self) -> &str { &self.profile_root }
|
||||
|
||||
pub fn journal(&self) -> &ErrorJournal { &self.journal }
|
||||
|
||||
/// Resolve a bucket name to its object store. Existing call sites use
|
||||
/// this as a drop-in replacement for the old single-store pattern.
|
||||
///
|
||||
/// Uses `std::sync::RwLock` — every caller holds the guard for
|
||||
/// microseconds (clones an Arc and drops), so there's no async-
|
||||
/// blocking concern. Never hold across an await.
|
||||
pub fn get(&self, bucket: &str) -> Result<Arc<dyn ObjectStore>, String> {
|
||||
self.buckets
|
||||
let guard = self.buckets.read().expect("bucket registry lock poisoned");
|
||||
guard
|
||||
.get(bucket)
|
||||
.map(|e| e.store.clone())
|
||||
.ok_or_else(|| format!("unknown bucket: {bucket}"))
|
||||
@@ -139,22 +153,34 @@ impl BucketRegistry {
|
||||
/// The default bucket's store — use for code paths that don't yet know
|
||||
/// about buckets.
|
||||
pub fn default_store(&self) -> Arc<dyn ObjectStore> {
|
||||
self.buckets.get(&self.default).unwrap().store.clone()
|
||||
let guard = self.buckets.read().expect("bucket registry lock poisoned");
|
||||
guard.get(&self.default).unwrap().store.clone()
|
||||
}
|
||||
|
||||
/// True if this bucket name is registered.
|
||||
pub fn contains(&self, bucket: &str) -> bool {
|
||||
let guard = self.buckets.read().expect("bucket registry lock poisoned");
|
||||
guard.contains_key(bucket)
|
||||
}
|
||||
|
||||
/// List all registered buckets. Checks reachability by doing a trivial
|
||||
/// `list` with limit 1 on each.
|
||||
pub async fn list(&self) -> Vec<BucketInfo> {
|
||||
let mut out = Vec::with_capacity(self.buckets.len());
|
||||
for (name, entry) in &self.buckets {
|
||||
let reachable = probe(&entry.store).await;
|
||||
let role = self.classify(name);
|
||||
out.push(BucketInfo {
|
||||
name: name.clone(),
|
||||
backend: entry.backend.clone(),
|
||||
reachable,
|
||||
role,
|
||||
});
|
||||
// Snapshot (name, backend, store_clone) under the lock, then probe
|
||||
// outside — probing can be slow (network), don't hold the lock.
|
||||
let snapshot: Vec<(String, String, Arc<dyn ObjectStore>)> = {
|
||||
let guard = self.buckets.read().expect("bucket registry lock poisoned");
|
||||
guard
|
||||
.iter()
|
||||
.map(|(n, e)| (n.clone(), e.backend.clone(), e.store.clone()))
|
||||
.collect()
|
||||
};
|
||||
|
||||
let mut out = Vec::with_capacity(snapshot.len());
|
||||
for (name, backend, store) in snapshot {
|
||||
let reachable = probe(&store).await;
|
||||
let role = self.classify(&name);
|
||||
out.push(BucketInfo { name, backend, reachable, role });
|
||||
}
|
||||
out.sort_by(|a, b| a.name.cmp(&b.name));
|
||||
out
|
||||
@@ -167,14 +193,69 @@ impl BucketRegistry {
|
||||
else { BucketRole::Tenant }
|
||||
}
|
||||
|
||||
/// Provision + register a bucket at runtime (federation layer 2).
|
||||
/// Returns Err if the name is already registered. Local backends get
|
||||
/// their root directory created automatically.
|
||||
pub async fn add_bucket(&self, bc: BucketConfig) -> Result<BucketInfo, String> {
|
||||
if self.contains(&bc.name) {
|
||||
return Err(format!("bucket '{}' already registered", bc.name));
|
||||
}
|
||||
let store = build_store(&bc, self.secrets.as_ref()).await?;
|
||||
let reachable = probe(&store).await;
|
||||
let entry = Arc::new(BucketEntry {
|
||||
name: bc.name.clone(),
|
||||
backend: bc.backend.clone(),
|
||||
store,
|
||||
config: bc.clone(),
|
||||
});
|
||||
let role = self.classify(&bc.name);
|
||||
let info = BucketInfo {
|
||||
name: bc.name.clone(),
|
||||
backend: bc.backend.clone(),
|
||||
reachable,
|
||||
role,
|
||||
};
|
||||
{
|
||||
let mut guard = self.buckets.write().expect("bucket registry lock poisoned");
|
||||
guard.insert(bc.name.clone(), entry);
|
||||
}
|
||||
tracing::info!("registered bucket '{}' backend={} reachable={}",
|
||||
bc.name, bc.backend, reachable);
|
||||
Ok(info)
|
||||
}
|
||||
|
||||
/// Unregister a bucket. Refuses to remove `primary` or the configured
|
||||
/// rescue bucket — those are load-bearing. Caller is responsible for
|
||||
/// any final flush of bucket-local state before calling this.
|
||||
pub fn remove_bucket(&self, name: &str) -> Result<(), String> {
|
||||
if name == self.default {
|
||||
return Err("cannot remove primary bucket".into());
|
||||
}
|
||||
if Some(name) == self.rescue.as_deref() {
|
||||
return Err(format!("cannot remove rescue bucket '{name}'"));
|
||||
}
|
||||
let removed = {
|
||||
let mut guard = self.buckets.write().expect("bucket registry lock poisoned");
|
||||
guard.remove(name)
|
||||
};
|
||||
if removed.is_none() {
|
||||
return Err(format!("bucket '{name}' not registered"));
|
||||
}
|
||||
tracing::info!("unregistered bucket '{}'", name);
|
||||
Ok(())
|
||||
}
|
||||
|
||||
/// Read with rescue-bucket fallback. If the target bucket fails and a
|
||||
/// rescue is configured, retries against rescue. Records every failure
|
||||
/// in the error journal.
|
||||
pub async fn read_smart(&self, bucket: &str, key: &str) -> Result<ReadOutcome, String> {
|
||||
let target = self.buckets.get(bucket)
|
||||
.ok_or_else(|| format!("unknown bucket: {bucket}"))?;
|
||||
let target_store = {
|
||||
let guard = self.buckets.read().expect("bucket registry lock poisoned");
|
||||
guard.get(bucket).map(|e| e.store.clone())
|
||||
.ok_or_else(|| format!("unknown bucket: {bucket}"))?
|
||||
};
|
||||
|
||||
match crate::ops::get(&target.store, key).await {
|
||||
match crate::ops::get(&target_store, key).await {
|
||||
Ok(data) => Ok(ReadOutcome {
|
||||
data, rescued: false,
|
||||
original_bucket: bucket.to_string(),
|
||||
@@ -187,8 +268,12 @@ impl BucketRegistry {
|
||||
// Try rescue, if any.
|
||||
if let Some(rescue_name) = &self.rescue {
|
||||
if rescue_name != bucket {
|
||||
if let Some(rescue) = self.buckets.get(rescue_name) {
|
||||
match crate::ops::get(&rescue.store, key).await {
|
||||
let rescue_store = {
|
||||
let guard = self.buckets.read().expect("bucket registry lock poisoned");
|
||||
guard.get(rescue_name).map(|e| e.store.clone())
|
||||
};
|
||||
if let Some(rescue_store) = rescue_store {
|
||||
match crate::ops::get(&rescue_store, key).await {
|
||||
Ok(data) => {
|
||||
self.journal.mark_rescued_last(bucket, key).await;
|
||||
return Ok(ReadOutcome {
|
||||
@@ -219,9 +304,12 @@ impl BucketRegistry {
|
||||
key: &str,
|
||||
data: bytes::Bytes,
|
||||
) -> Result<(), String> {
|
||||
let target = self.buckets.get(bucket)
|
||||
.ok_or_else(|| format!("unknown bucket: {bucket}"))?;
|
||||
match crate::ops::put(&target.store, key, data).await {
|
||||
let target_store = {
|
||||
let guard = self.buckets.read().expect("bucket registry lock poisoned");
|
||||
guard.get(bucket).map(|e| e.store.clone())
|
||||
.ok_or_else(|| format!("unknown bucket: {bucket}"))?
|
||||
};
|
||||
match crate::ops::put(&target_store, key, data).await {
|
||||
Ok(()) => Ok(()),
|
||||
Err(err) => {
|
||||
self.journal.append(BucketErrorEvent::new_write(bucket, key, &err)).await;
|
||||
|
||||
@@ -0,0 +1,31 @@
|
||||
[package]
|
||||
name = "vectord-lance"
|
||||
version = "0.1.0"
|
||||
edition = "2024"
|
||||
|
||||
# Firewall crate: the Lance stack (Arrow 57, DataFusion 52) is isolated
|
||||
# from the rest of vectord (Arrow 55, DataFusion 47). Public API uses
|
||||
# only std types — no Arrow types cross the crate boundary — so no
|
||||
# version conflict propagates outward.
|
||||
#
|
||||
# See docs/ADR-019-vector-storage.md for the rationale: "productionizing
|
||||
# will need either workspace-wide upgrade or a firewall via a dedicated
|
||||
# vectord-lance crate." This is that firewall.
|
||||
|
||||
[dependencies]
|
||||
lance = { version = "4.0", default-features = false }
|
||||
lance-index = { version = "4.0", default-features = false }
|
||||
lance-linalg = { version = "4.0", default-features = false }
|
||||
|
||||
# These Arrow/Parquet versions MUST match Lance's expectations — Lance
|
||||
# re-exports their types through its API so any mismatch is a hard
|
||||
# compile error. Keep in sync with lance-bench.
|
||||
arrow = "57"
|
||||
arrow-array = "57"
|
||||
arrow-schema = "57"
|
||||
parquet = "57"
|
||||
|
||||
tokio = { version = "1", features = ["full"] }
|
||||
futures = "0.3"
|
||||
serde = { version = "1", features = ["derive"] }
|
||||
bytes = "1"
|
||||
@@ -0,0 +1,528 @@
|
||||
//! Production Lance vector backend (ADR-019 — hybrid architecture).
|
||||
//!
|
||||
//! This is the firewall crate. It owns its own Arrow 57 / DataFusion 52
|
||||
//! / Lance 4 dependency tree. The public API uses only std types
|
||||
//! (`Vec<f32>`, `Vec<String>`, `String`, `bool`) so nothing Arrow-shaped
|
||||
//! crosses the crate boundary. That keeps vectord (Arrow 55) from
|
||||
//! picking up an incompatible dep.
|
||||
//!
|
||||
//! Responsibilities:
|
||||
//! - Migrate an existing binary-blob Parquet vector file into a Lance
|
||||
//! dataset with `FixedSizeList<Float32, dims>`. One-time cost.
|
||||
//! - Append new rows natively (no full-file rewrite — Lance's structural win).
|
||||
//! - Build an IVF_PQ ANN index on the vector column.
|
||||
//! - Vector search (`search`) using the IVF_PQ index when present,
|
||||
//! falling back to full scan otherwise.
|
||||
//! - Random-access row fetch by `doc_id` (`get_by_doc_id`) — the O(1)
|
||||
//! lookup that Parquet-on-object-store can't cheaply do.
|
||||
//! - Cheap count + stats introspection.
|
||||
|
||||
use arrow_array::{
|
||||
Array, ArrayRef, BinaryArray, FixedSizeListArray, Float32Array, Int32Array,
|
||||
RecordBatch, RecordBatchIterator, StringArray,
|
||||
};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
use futures::StreamExt;
|
||||
use serde::Serialize;
|
||||
use std::sync::Arc;
|
||||
use std::time::Instant;
|
||||
|
||||
// ================= Public types =================
|
||||
|
||||
/// One search result. Mirrors vectord's existing `SearchResult` shape
|
||||
/// structurally but carries simpler types so this crate stays firewalled.
|
||||
#[derive(Debug, Clone, Serialize)]
|
||||
pub struct Hit {
|
||||
pub doc_id: String,
|
||||
pub chunk_text: String,
|
||||
pub score: f32,
|
||||
/// Optional — set by search_with_vector, not by index-only search.
|
||||
pub distance: Option<f32>,
|
||||
}
|
||||
|
||||
/// A fully-hydrated row fetched by `get_by_doc_id` — includes the vector
|
||||
/// so callers can do downstream work (rerank, cite, etc.) without a
|
||||
/// second round trip.
|
||||
#[derive(Debug, Clone, Serialize)]
|
||||
pub struct Row {
|
||||
pub doc_id: String,
|
||||
pub chunk_text: String,
|
||||
pub vector: Vec<f32>,
|
||||
pub source: Option<String>,
|
||||
pub chunk_idx: Option<i32>,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Serialize)]
|
||||
pub struct MigrationStats {
|
||||
pub rows_written: usize,
|
||||
pub dimensions: usize,
|
||||
pub disk_bytes: u64,
|
||||
pub duration_secs: f32,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Serialize)]
|
||||
pub struct AppendStats {
|
||||
pub rows_appended: usize,
|
||||
pub disk_bytes_added: u64,
|
||||
pub duration_secs: f32,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Serialize)]
|
||||
pub struct IndexStats {
|
||||
pub name: String,
|
||||
pub num_partitions: u32,
|
||||
pub num_bits: u32,
|
||||
pub num_sub_vectors: u32,
|
||||
pub build_time_secs: f32,
|
||||
pub disk_bytes_added: u64,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Serialize)]
|
||||
pub struct DatasetStats {
|
||||
pub path: String,
|
||||
pub rows: usize,
|
||||
pub disk_bytes: u64,
|
||||
pub has_vector_index: bool,
|
||||
}
|
||||
|
||||
// ================= The backend =================
|
||||
|
||||
/// Thin wrapper around a Lance dataset path. Lance handles the heavy
|
||||
/// lifting — we just expose a narrow API.
|
||||
#[derive(Clone)]
|
||||
pub struct LanceVectorStore {
|
||||
/// Local filesystem path or object-store URI (file:///..., s3://...).
|
||||
/// Lance's internal URI parsing handles both.
|
||||
path: String,
|
||||
}
|
||||
|
||||
impl LanceVectorStore {
|
||||
pub fn new(path: impl Into<String>) -> Self {
|
||||
Self { path: path.into() }
|
||||
}
|
||||
|
||||
pub fn path(&self) -> &str { &self.path }
|
||||
|
||||
/// Row count via Lance's fast metadata path (no scan).
|
||||
pub async fn count(&self) -> Result<usize, String> {
|
||||
let dataset = open_or_err(&self.path).await?;
|
||||
let n = dataset.count_rows(None).await.map_err(e)?;
|
||||
Ok(n)
|
||||
}
|
||||
|
||||
/// True if the on-disk dataset exists AND has at least one `vector`
|
||||
/// column index attached.
|
||||
pub async fn has_vector_index(&self) -> Result<bool, String> {
|
||||
use lance_index::DatasetIndexExt;
|
||||
let dataset = match lance::dataset::Dataset::open(&self.path).await {
|
||||
Ok(d) => d,
|
||||
Err(_) => return Ok(false),
|
||||
};
|
||||
let indexes = dataset.load_indices().await.map_err(e)?;
|
||||
Ok(indexes.iter().any(|ix| {
|
||||
ix.fields.iter().any(|fid| {
|
||||
dataset.schema().field_by_id(*fid)
|
||||
.map(|f| f.name == "vector")
|
||||
.unwrap_or(false)
|
||||
})
|
||||
}))
|
||||
}
|
||||
|
||||
pub async fn stats(&self) -> Result<DatasetStats, String> {
|
||||
let rows = self.count().await.unwrap_or(0);
|
||||
let disk_bytes = dir_size_bytes(&strip_file_uri(&self.path));
|
||||
let has_vector_index = self.has_vector_index().await.unwrap_or(false);
|
||||
Ok(DatasetStats {
|
||||
path: self.path.clone(),
|
||||
rows,
|
||||
disk_bytes,
|
||||
has_vector_index,
|
||||
})
|
||||
}
|
||||
|
||||
/// Migrate a vectord-format Parquet file into a Lance dataset.
|
||||
///
|
||||
/// Input schema (vectord's binary-blob format):
|
||||
/// - source : Utf8
|
||||
/// - doc_id : Utf8
|
||||
/// - chunk_idx : Int32
|
||||
/// - chunk_text : Utf8
|
||||
/// - vector : Binary (raw f32 little-endian bytes)
|
||||
///
|
||||
/// Output schema (Lance-friendly):
|
||||
/// - source : Utf8
|
||||
/// - doc_id : Utf8
|
||||
/// - chunk_idx : Int32
|
||||
/// - chunk_text : Utf8
|
||||
/// - vector : FixedSizeList<Float32, dims>
|
||||
///
|
||||
/// Idempotent at the file level — if the target exists, it's
|
||||
/// overwritten. Caller must manage destination paths.
|
||||
pub async fn migrate_from_parquet_bytes(
|
||||
&self,
|
||||
parquet_bytes: &[u8],
|
||||
) -> Result<MigrationStats, String> {
|
||||
let t0 = Instant::now();
|
||||
let (schema, batches, rows) = read_parquet(parquet_bytes)?;
|
||||
let dims = detect_vector_dims(&batches)?;
|
||||
let (new_schema, new_batches) = convert_to_fixed_size_list(&schema, batches, dims)?;
|
||||
|
||||
// Overwrite any prior dataset at this path.
|
||||
let _ = std::fs::remove_dir_all(&strip_file_uri(&self.path));
|
||||
|
||||
write_dataset(&self.path, new_schema, new_batches).await?;
|
||||
let disk_bytes = dir_size_bytes(&strip_file_uri(&self.path));
|
||||
|
||||
Ok(MigrationStats {
|
||||
rows_written: rows,
|
||||
dimensions: dims,
|
||||
disk_bytes,
|
||||
duration_secs: t0.elapsed().as_secs_f32(),
|
||||
})
|
||||
}
|
||||
|
||||
/// Native Lance append — does NOT rewrite existing files. New rows
|
||||
/// land as a separate fragment; readers union across fragments at
|
||||
/// query time. Contrast: our Parquet path requires rewriting the
|
||||
/// entire vector file to add rows.
|
||||
pub async fn append(
|
||||
&self,
|
||||
source: Option<String>,
|
||||
doc_ids: Vec<String>,
|
||||
chunk_idxs: Vec<i32>,
|
||||
chunk_texts: Vec<String>,
|
||||
vectors: Vec<Vec<f32>>,
|
||||
) -> Result<AppendStats, String> {
|
||||
let n = doc_ids.len();
|
||||
if n == 0 {
|
||||
return Ok(AppendStats { rows_appended: 0, disk_bytes_added: 0, duration_secs: 0.0 });
|
||||
}
|
||||
if chunk_idxs.len() != n || chunk_texts.len() != n || vectors.len() != n {
|
||||
return Err(format!(
|
||||
"append: length mismatch (doc_ids={n}, chunk_idxs={}, chunk_texts={}, vectors={})",
|
||||
chunk_idxs.len(), chunk_texts.len(), vectors.len(),
|
||||
));
|
||||
}
|
||||
let dims = vectors[0].len();
|
||||
for (i, v) in vectors.iter().enumerate() {
|
||||
if v.len() != dims {
|
||||
return Err(format!("append: row {i} has {} dims, expected {}", v.len(), dims));
|
||||
}
|
||||
}
|
||||
|
||||
let t0 = Instant::now();
|
||||
let pre_bytes = dir_size_bytes(&strip_file_uri(&self.path));
|
||||
|
||||
let src_arr = StringArray::from(
|
||||
(0..n).map(|_| source.clone()).collect::<Vec<_>>()
|
||||
);
|
||||
let doc_id_arr = StringArray::from(doc_ids);
|
||||
let chunk_idx_arr = Int32Array::from(chunk_idxs);
|
||||
let chunk_text_arr = StringArray::from(chunk_texts);
|
||||
|
||||
let mut flat: Vec<f32> = Vec::with_capacity(n * dims);
|
||||
for v in vectors { flat.extend(v); }
|
||||
let values = Float32Array::from(flat);
|
||||
let item_field = Arc::new(Field::new("item", DataType::Float32, true));
|
||||
let vec_arr = FixedSizeListArray::try_new(
|
||||
item_field.clone(), dims as i32, Arc::new(values), None,
|
||||
).map_err(e)?;
|
||||
|
||||
let schema = Arc::new(Schema::new(vec![
|
||||
Field::new("source", DataType::Utf8, true),
|
||||
Field::new("doc_id", DataType::Utf8, false),
|
||||
Field::new("chunk_idx", DataType::Int32, true),
|
||||
Field::new("chunk_text", DataType::Utf8, true),
|
||||
Field::new("vector", DataType::FixedSizeList(item_field, dims as i32), false),
|
||||
]));
|
||||
|
||||
let arrays: Vec<ArrayRef> = vec![
|
||||
Arc::new(src_arr), Arc::new(doc_id_arr), Arc::new(chunk_idx_arr),
|
||||
Arc::new(chunk_text_arr), Arc::new(vec_arr),
|
||||
];
|
||||
let batch = RecordBatch::try_new(schema.clone(), arrays).map_err(e)?;
|
||||
let reader = RecordBatchIterator::new(vec![Ok(batch)].into_iter(), schema);
|
||||
|
||||
use lance::dataset::{Dataset, WriteMode, WriteParams};
|
||||
let params = WriteParams { mode: WriteMode::Append, ..Default::default() };
|
||||
Dataset::write(reader, &self.path, Some(params)).await.map_err(e)?;
|
||||
|
||||
Ok(AppendStats {
|
||||
rows_appended: n,
|
||||
disk_bytes_added: dir_size_bytes(&strip_file_uri(&self.path)).saturating_sub(pre_bytes),
|
||||
duration_secs: t0.elapsed().as_secs_f32(),
|
||||
})
|
||||
}
|
||||
|
||||
/// Build an IVF_PQ vector index. Replaces any prior index with the
|
||||
/// same name. Callers pass explicit params — sensible defaults for
|
||||
/// ~100K × 768d: num_partitions=316 (≈√N), num_bits=8, num_sub_vectors=48.
|
||||
pub async fn build_index(
|
||||
&self,
|
||||
num_partitions: u32,
|
||||
num_bits: u32,
|
||||
num_sub_vectors: u32,
|
||||
) -> Result<IndexStats, String> {
|
||||
use lance::dataset::Dataset;
|
||||
use lance::index::vector::VectorIndexParams;
|
||||
use lance_index::{DatasetIndexExt, IndexType};
|
||||
use lance_linalg::distance::MetricType;
|
||||
|
||||
let pre_bytes = dir_size_bytes(&strip_file_uri(&self.path));
|
||||
let t0 = Instant::now();
|
||||
|
||||
let mut dataset = Dataset::open(&self.path).await.map_err(e)?;
|
||||
let params = VectorIndexParams::ivf_pq(
|
||||
num_partitions as usize,
|
||||
num_bits as u8,
|
||||
num_sub_vectors as usize,
|
||||
MetricType::Cosine,
|
||||
50, // max_iterations — same as bench
|
||||
);
|
||||
dataset.create_index(
|
||||
&["vector"],
|
||||
IndexType::Vector,
|
||||
Some("vec_idx".into()),
|
||||
¶ms,
|
||||
true, // replace
|
||||
).await.map_err(e)?;
|
||||
|
||||
Ok(IndexStats {
|
||||
name: "vec_idx".into(),
|
||||
num_partitions,
|
||||
num_bits,
|
||||
num_sub_vectors,
|
||||
build_time_secs: t0.elapsed().as_secs_f32(),
|
||||
disk_bytes_added: dir_size_bytes(&strip_file_uri(&self.path)).saturating_sub(pre_bytes),
|
||||
})
|
||||
}
|
||||
|
||||
/// Search for top_k nearest neighbors of `query`. Uses the IVF_PQ
|
||||
/// index if one exists; otherwise does a full scan (slow but
|
||||
/// correct — useful during development before index build).
|
||||
pub async fn search(&self, query: &[f32], top_k: usize) -> Result<Vec<Hit>, String> {
|
||||
use lance::dataset::Dataset;
|
||||
|
||||
let dataset = Dataset::open(&self.path).await.map_err(e)?;
|
||||
let qarr = Float32Array::from(query.to_vec());
|
||||
|
||||
let mut scanner = dataset.scan();
|
||||
scanner.nearest("vector", &qarr, top_k as usize).map_err(e)?;
|
||||
scanner.project(&["doc_id", "chunk_text"]).map_err(e)?;
|
||||
|
||||
let mut stream = scanner.try_into_stream().await.map_err(e)?;
|
||||
let mut hits: Vec<Hit> = Vec::with_capacity(top_k);
|
||||
|
||||
while let Some(batch) = stream.next().await {
|
||||
let batch = batch.map_err(e)?;
|
||||
let doc_ids = batch.column_by_name("doc_id")
|
||||
.ok_or_else(|| "no doc_id column in search result".to_string())?
|
||||
.as_any().downcast_ref::<StringArray>()
|
||||
.ok_or_else(|| "doc_id is not StringArray".to_string())?;
|
||||
let chunk_texts = batch.column_by_name("chunk_text")
|
||||
.and_then(|c| c.as_any().downcast_ref::<StringArray>());
|
||||
// Lance tacks on a `_distance` column for nearest() queries.
|
||||
let distances = batch.column_by_name("_distance")
|
||||
.and_then(|c| c.as_any().downcast_ref::<Float32Array>());
|
||||
for row in 0..batch.num_rows() {
|
||||
let d = distances.map(|a| a.value(row));
|
||||
hits.push(Hit {
|
||||
doc_id: doc_ids.value(row).to_string(),
|
||||
chunk_text: chunk_texts.map(|a| a.value(row).to_string()).unwrap_or_default(),
|
||||
score: d.map(|d| 1.0 - d).unwrap_or(0.0), // cosine distance → similarity
|
||||
distance: d,
|
||||
});
|
||||
}
|
||||
}
|
||||
Ok(hits)
|
||||
}
|
||||
|
||||
/// Fetch one row by doc_id. Implementation: Lance filter-pushdown
|
||||
/// scan — O(1) with partition pruning on a proper btree index,
|
||||
/// O(N) on vector-only datasets (still far faster than reading
|
||||
/// the whole Parquet file). We don't build a scalar index on
|
||||
/// doc_id yet; that's a future optimization.
|
||||
pub async fn get_by_doc_id(&self, doc_id: &str) -> Result<Option<Row>, String> {
|
||||
use lance::dataset::Dataset;
|
||||
|
||||
let dataset = Dataset::open(&self.path).await.map_err(e)?;
|
||||
let filter = format!("doc_id = '{}'", doc_id.replace('\'', "''"));
|
||||
let mut scanner = dataset.scan();
|
||||
scanner.filter(&filter).map_err(e)?;
|
||||
scanner.limit(Some(1), None).map_err(e)?;
|
||||
let mut stream = scanner.try_into_stream().await.map_err(e)?;
|
||||
|
||||
while let Some(batch) = stream.next().await {
|
||||
let batch = batch.map_err(e)?;
|
||||
if batch.num_rows() == 0 { continue; }
|
||||
return Ok(Some(row_from_batch(&batch, 0)?));
|
||||
}
|
||||
Ok(None)
|
||||
}
|
||||
}
|
||||
|
||||
// ================= Internal helpers =================
|
||||
|
||||
fn e<T: std::fmt::Display>(err: T) -> String { err.to_string() }
|
||||
|
||||
/// `file:///abs/path` → `/abs/path`. Leave other URI schemes as-is for
|
||||
/// helpers that only work on local paths (dir_size_bytes, remove_dir_all).
|
||||
fn strip_file_uri(uri: &str) -> String {
|
||||
uri.strip_prefix("file://").unwrap_or(uri).to_string()
|
||||
}
|
||||
|
||||
async fn open_or_err(path: &str) -> Result<lance::dataset::Dataset, String> {
|
||||
lance::dataset::Dataset::open(path).await.map_err(e)
|
||||
}
|
||||
|
||||
fn dir_size_bytes(path: &str) -> u64 {
|
||||
fn recurse(p: &std::path::Path) -> u64 {
|
||||
let Ok(meta) = std::fs::metadata(p) else { return 0; };
|
||||
if meta.is_file() { return meta.len(); }
|
||||
let Ok(entries) = std::fs::read_dir(p) else { return 0; };
|
||||
entries.filter_map(|e| e.ok()).map(|e| recurse(&e.path())).sum()
|
||||
}
|
||||
recurse(std::path::Path::new(path))
|
||||
}
|
||||
|
||||
fn read_parquet(bytes: &[u8]) -> Result<(Arc<Schema>, Vec<RecordBatch>, usize), String> {
|
||||
use parquet::arrow::arrow_reader::ParquetRecordBatchReaderBuilder;
|
||||
let builder = ParquetRecordBatchReaderBuilder::try_new(bytes::Bytes::copy_from_slice(bytes))
|
||||
.map_err(e)?;
|
||||
let schema = builder.schema().clone();
|
||||
let reader = builder.build().map_err(e)?;
|
||||
let batches: Vec<RecordBatch> = reader.collect::<Result<_, _>>().map_err(e)?;
|
||||
let rows: usize = batches.iter().map(|b| b.num_rows()).sum();
|
||||
Ok((schema, batches, rows))
|
||||
}
|
||||
|
||||
fn detect_vector_dims(batches: &[RecordBatch]) -> Result<usize, String> {
|
||||
for batch in batches {
|
||||
let idx = batch.schema().index_of("vector")
|
||||
.map_err(|_| "no 'vector' column".to_string())?;
|
||||
let col = batch.column(idx);
|
||||
if let Some(binary) = col.as_any().downcast_ref::<BinaryArray>() {
|
||||
for i in 0..binary.len() {
|
||||
if !binary.is_null(i) {
|
||||
return Ok(binary.value(i).len() / 4);
|
||||
}
|
||||
}
|
||||
} else if let Some(fsl) = col.as_any().downcast_ref::<FixedSizeListArray>() {
|
||||
return Ok(fsl.value_length() as usize);
|
||||
}
|
||||
}
|
||||
Err("could not determine vector dimensions".into())
|
||||
}
|
||||
|
||||
fn convert_to_fixed_size_list(
|
||||
schema: &Arc<Schema>,
|
||||
batches: Vec<RecordBatch>,
|
||||
dims: usize,
|
||||
) -> Result<(Arc<Schema>, Vec<RecordBatch>), String> {
|
||||
let new_fields: Vec<Arc<Field>> = schema
|
||||
.fields()
|
||||
.iter()
|
||||
.map(|f| {
|
||||
if f.name() == "vector" {
|
||||
Arc::new(Field::new(
|
||||
"vector",
|
||||
DataType::FixedSizeList(
|
||||
Arc::new(Field::new("item", DataType::Float32, true)),
|
||||
dims as i32,
|
||||
),
|
||||
false,
|
||||
))
|
||||
} else {
|
||||
f.clone()
|
||||
}
|
||||
})
|
||||
.collect();
|
||||
let new_schema = Arc::new(Schema::new(new_fields));
|
||||
|
||||
let mut out = Vec::with_capacity(batches.len());
|
||||
for batch in batches {
|
||||
let vec_idx = batch.schema().index_of("vector").map_err(e)?;
|
||||
let mut new_cols: Vec<ArrayRef> = Vec::with_capacity(batch.num_columns());
|
||||
for (i, col) in batch.columns().iter().enumerate() {
|
||||
if i == vec_idx {
|
||||
if let Some(bin) = col.as_any().downcast_ref::<BinaryArray>() {
|
||||
new_cols.push(Arc::new(binary_to_fsl(bin, dims)?));
|
||||
} else if col.as_any().is::<FixedSizeListArray>() {
|
||||
// Already in the right shape — just clone.
|
||||
new_cols.push(col.clone());
|
||||
} else {
|
||||
return Err("vector column is neither Binary nor FixedSizeList".into());
|
||||
}
|
||||
} else {
|
||||
new_cols.push(col.clone());
|
||||
}
|
||||
}
|
||||
out.push(RecordBatch::try_new(new_schema.clone(), new_cols).map_err(e)?);
|
||||
}
|
||||
Ok((new_schema, out))
|
||||
}
|
||||
|
||||
fn binary_to_fsl(bin: &BinaryArray, dims: usize) -> Result<FixedSizeListArray, String> {
|
||||
let n = bin.len();
|
||||
let mut flat: Vec<f32> = Vec::with_capacity(n * dims);
|
||||
for i in 0..n {
|
||||
if bin.is_null(i) {
|
||||
flat.extend(std::iter::repeat(0.0).take(dims));
|
||||
continue;
|
||||
}
|
||||
let b = bin.value(i);
|
||||
if b.len() != dims * 4 {
|
||||
return Err(format!(
|
||||
"row {i}: {} bytes vs expected {} ({} × f32)",
|
||||
b.len(), dims * 4, dims,
|
||||
));
|
||||
}
|
||||
for c in b.chunks_exact(4) {
|
||||
flat.push(f32::from_le_bytes([c[0], c[1], c[2], c[3]]));
|
||||
}
|
||||
}
|
||||
let values = Float32Array::from(flat);
|
||||
let field = Arc::new(Field::new("item", DataType::Float32, true));
|
||||
FixedSizeListArray::try_new(field, dims as i32, Arc::new(values), None).map_err(e)
|
||||
}
|
||||
|
||||
async fn write_dataset(
|
||||
path: &str,
|
||||
schema: Arc<Schema>,
|
||||
batches: Vec<RecordBatch>,
|
||||
) -> Result<(), String> {
|
||||
use lance::dataset::{Dataset, WriteParams};
|
||||
let reader = RecordBatchIterator::new(batches.into_iter().map(Ok), schema);
|
||||
Dataset::write(reader, path, Some(WriteParams::default()))
|
||||
.await.map_err(e)?;
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn row_from_batch(batch: &RecordBatch, row: usize) -> Result<Row, String> {
|
||||
let doc_id = batch.column_by_name("doc_id")
|
||||
.and_then(|c| c.as_any().downcast_ref::<StringArray>())
|
||||
.map(|a| a.value(row).to_string())
|
||||
.ok_or_else(|| "missing doc_id".to_string())?;
|
||||
let chunk_text = batch.column_by_name("chunk_text")
|
||||
.and_then(|c| c.as_any().downcast_ref::<StringArray>())
|
||||
.map(|a| a.value(row).to_string())
|
||||
.unwrap_or_default();
|
||||
let source = batch.column_by_name("source")
|
||||
.and_then(|c| c.as_any().downcast_ref::<StringArray>())
|
||||
.and_then(|a| if a.is_null(row) { None } else { Some(a.value(row).to_string()) });
|
||||
let chunk_idx = batch.column_by_name("chunk_idx")
|
||||
.and_then(|c| c.as_any().downcast_ref::<Int32Array>())
|
||||
.and_then(|a| if a.is_null(row) { None } else { Some(a.value(row)) });
|
||||
|
||||
let vec_col = batch.column_by_name("vector")
|
||||
.ok_or_else(|| "no vector column in row fetch".to_string())?;
|
||||
let fsl = vec_col.as_any().downcast_ref::<FixedSizeListArray>()
|
||||
.ok_or_else(|| "vector column is not FixedSizeList".to_string())?;
|
||||
let inner = fsl.value(row);
|
||||
let floats = inner.as_any().downcast_ref::<Float32Array>()
|
||||
.ok_or_else(|| "vector inner not Float32".to_string())?;
|
||||
let mut v = Vec::with_capacity(floats.len());
|
||||
for i in 0..floats.len() { v.push(floats.value(i)); }
|
||||
|
||||
Ok(Row { doc_id, chunk_text, vector: v, source, chunk_idx })
|
||||
}
|
||||
@@ -8,6 +8,9 @@ shared = { path = "../shared" }
|
||||
storaged = { path = "../storaged" }
|
||||
aibridge = { path = "../aibridge" }
|
||||
catalogd = { path = "../catalogd" }
|
||||
# ADR-019 firewall — vectord-lance owns its own Arrow 57 / Lance 4 deps.
|
||||
# Public API uses only std types so no version conflict propagates here.
|
||||
vectord-lance = { path = "../vectord-lance" }
|
||||
tokio = { workspace = true }
|
||||
axum = { workspace = true }
|
||||
serde = { workspace = true }
|
||||
|
||||
@@ -0,0 +1,711 @@
|
||||
//! Phase 16.2 + 16.5 — The autotune agent.
|
||||
//!
|
||||
//! A long-running tokio task that watches the trial journal and
|
||||
//! autonomously proposes + runs new HNSW configs. Distinct from
|
||||
//! `autotune::run_autotune` which is synchronous (one HTTP call, grid
|
||||
//! of trials, done). The agent is the continuous version: it sleeps,
|
||||
//! wakes on triggers, proposes configs based on prior trial history,
|
||||
//! runs them one at a time, and auto-promotes when it finds an
|
||||
//! improvement.
|
||||
//!
|
||||
//! Design invariants:
|
||||
//! - Trials are data (ADR-018). Every proposal reads the journal; every
|
||||
//! attempt appends to it. The journal is the agent's memory.
|
||||
//! - One trial at a time. Bounded Ollama load — the agent never fires
|
||||
//! multiple parallel embeddings and respects `cooldown_between_trials_secs`.
|
||||
//! - Rate-limited. `max_trials_per_hour` is a hard ceiling so a
|
||||
//! misbehaving proposal function can't saturate the system.
|
||||
//! - Never promotes below `min_recall`. Same safety gate as
|
||||
//! `run_autotune` — we will not make the index worse.
|
||||
//! - Triggered OR periodic. Ingest enqueues a `DatasetAppended` event
|
||||
//! when a new batch lands; the agent also wakes periodically to keep
|
||||
//! exploring even when nothing changed externally.
|
||||
//! - Graceful shutdown via the `stop_tx` signal — the handle's Drop
|
||||
//! doesn't force-kill, but `stop()` requests a clean exit after the
|
||||
//! current trial.
|
||||
|
||||
use chrono::{DateTime, Utc};
|
||||
use object_store::ObjectStore;
|
||||
use serde::{Deserialize, Serialize};
|
||||
use std::collections::VecDeque;
|
||||
use std::sync::Arc;
|
||||
use tokio::sync::{Mutex, RwLock, mpsc, oneshot};
|
||||
|
||||
use aibridge::client::AiClient;
|
||||
use catalogd::registry::Registry as CatalogRegistry;
|
||||
|
||||
use crate::embedding_cache::EmbeddingCache;
|
||||
use crate::harness;
|
||||
use crate::hnsw::HnswStore;
|
||||
use crate::index_registry::IndexRegistry;
|
||||
use crate::promotion::{PromotionEntry, PromotionRegistry};
|
||||
use crate::trial::{HnswConfig, Trial, TrialJournal, TrialMetrics};
|
||||
|
||||
// -------- Public-facing types --------
|
||||
|
||||
/// Runtime configuration for the agent. Mirrored in shared::config under
|
||||
/// `[agent]`. Defaults are conservative — designed to tune slowly in the
|
||||
/// background without fighting real workloads for GPU time.
|
||||
#[derive(Debug, Clone, Serialize, Deserialize)]
|
||||
pub struct AgentConfig {
|
||||
/// Master switch. When false, `spawn` returns a handle but the loop
|
||||
/// doesn't run.
|
||||
pub enabled: bool,
|
||||
/// Periodic wake-up — even if the trigger queue is empty, every N
|
||||
/// seconds the agent picks an index with trials and proposes one
|
||||
/// more config. Keeps exploration alive on idle indexes.
|
||||
pub cycle_interval_secs: u64,
|
||||
/// Minimum gap between two trials on the SAME index. Prevents the
|
||||
/// agent from hammering Ollama when a hot index has many pending
|
||||
/// triggers in a row.
|
||||
pub cooldown_between_trials_secs: u64,
|
||||
/// Below this recall, a proposal is never promoted — even if it
|
||||
/// beats the champion on latency.
|
||||
pub min_recall: f32,
|
||||
/// Budget cap: hard ceiling on trials per hour across all indexes.
|
||||
/// When hit, the agent idles until the hour window rolls.
|
||||
pub max_trials_per_hour: u32,
|
||||
}
|
||||
|
||||
impl Default for AgentConfig {
|
||||
fn default() -> Self {
|
||||
Self {
|
||||
enabled: false, // opt-in — don't auto-start until J turns it on
|
||||
cycle_interval_secs: 60,
|
||||
cooldown_between_trials_secs: 30,
|
||||
min_recall: 0.9,
|
||||
max_trials_per_hour: 30,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// What caused the agent to look at a particular index. Recorded in the
|
||||
/// trial's note field so we can tell "new data arrived" trials from
|
||||
/// "periodic exploration" trials in the journal.
|
||||
#[derive(Debug, Clone, Serialize, Deserialize)]
|
||||
pub enum TriggerReason {
|
||||
/// Ingest just appended to a dataset that has attached HNSW indexes.
|
||||
DatasetAppended { dataset: String },
|
||||
/// A human or another agent hit `/agent/enqueue/{index}`.
|
||||
Manual,
|
||||
/// Periodic wake — no external event, just keep exploring.
|
||||
Periodic,
|
||||
}
|
||||
|
||||
/// One unit of work for the agent.
|
||||
#[derive(Debug, Clone)]
|
||||
pub struct TriggerEvent {
|
||||
pub index_name: String,
|
||||
pub reason: TriggerReason,
|
||||
pub enqueued_at: DateTime<Utc>,
|
||||
}
|
||||
|
||||
impl TriggerEvent {
|
||||
pub fn manual(index_name: impl Into<String>) -> Self {
|
||||
Self { index_name: index_name.into(), reason: TriggerReason::Manual, enqueued_at: Utc::now() }
|
||||
}
|
||||
pub fn dataset_appended(index_name: impl Into<String>, dataset: impl Into<String>) -> Self {
|
||||
Self {
|
||||
index_name: index_name.into(),
|
||||
reason: TriggerReason::DatasetAppended { dataset: dataset.into() },
|
||||
enqueued_at: Utc::now(),
|
||||
}
|
||||
}
|
||||
pub fn periodic(index_name: impl Into<String>) -> Self {
|
||||
Self { index_name: index_name.into(), reason: TriggerReason::Periodic, enqueued_at: Utc::now() }
|
||||
}
|
||||
}
|
||||
|
||||
/// Observable snapshot of the agent's state — what `/agent/status` returns.
|
||||
#[derive(Debug, Clone, Serialize)]
|
||||
pub struct AgentStatus {
|
||||
pub running: bool,
|
||||
pub config: AgentConfig,
|
||||
pub queue_depth: usize,
|
||||
pub trials_run: u64,
|
||||
pub promotions: u64,
|
||||
pub trials_in_last_hour: u32,
|
||||
pub last_event: Option<AgentEvent>,
|
||||
pub started_at: Option<DateTime<Utc>>,
|
||||
}
|
||||
|
||||
/// Last thing that happened — useful for "why didn't it do anything?" debugging.
|
||||
#[derive(Debug, Clone, Serialize)]
|
||||
pub struct AgentEvent {
|
||||
pub at: DateTime<Utc>,
|
||||
pub kind: String, // "trial_completed" | "promoted" | "skipped_rate_limit" | etc
|
||||
pub index_name: Option<String>,
|
||||
pub detail: String,
|
||||
}
|
||||
|
||||
/// Handle returned by `spawn`. Holds the trigger sender + shared status +
|
||||
/// stop signal.
|
||||
#[derive(Clone)]
|
||||
pub struct AgentHandle {
|
||||
trigger_tx: mpsc::Sender<TriggerEvent>,
|
||||
inner: Arc<AgentInner>,
|
||||
}
|
||||
|
||||
struct AgentInner {
|
||||
status: RwLock<AgentStatus>,
|
||||
stop_tx: Mutex<Option<oneshot::Sender<()>>>,
|
||||
queue_len: Mutex<usize>, // mirror of the channel capacity — for status reporting
|
||||
recent_trials: Mutex<VecDeque<DateTime<Utc>>>, // ring of recent trial timestamps for rate limit
|
||||
}
|
||||
|
||||
impl AgentHandle {
|
||||
/// Enqueue a trigger. Returns Err if the agent isn't running or the
|
||||
/// queue is full (backpressure — dropping events is correct here
|
||||
/// since periodic exploration will pick up the slack).
|
||||
pub async fn enqueue(&self, event: TriggerEvent) -> Result<(), String> {
|
||||
self.trigger_tx.try_send(event).map_err(|e| format!("enqueue: {e}"))?;
|
||||
let mut guard = self.inner.queue_len.lock().await;
|
||||
*guard = guard.saturating_add(1);
|
||||
// Update queue_depth in status for observability.
|
||||
let mut s = self.inner.status.write().await;
|
||||
s.queue_depth = *guard;
|
||||
Ok(())
|
||||
}
|
||||
|
||||
pub async fn status(&self) -> AgentStatus {
|
||||
let mut s = self.inner.status.read().await.clone();
|
||||
// Refresh rate-limit window from ring buffer.
|
||||
let cutoff = Utc::now() - chrono::Duration::hours(1);
|
||||
let ring = self.inner.recent_trials.lock().await;
|
||||
s.trials_in_last_hour = ring.iter().filter(|t| **t >= cutoff).count() as u32;
|
||||
s
|
||||
}
|
||||
|
||||
/// Request a graceful stop. Returns immediately — the loop exits
|
||||
/// after its current trial completes.
|
||||
pub async fn stop(&self) -> bool {
|
||||
let mut guard = self.inner.stop_tx.lock().await;
|
||||
if let Some(tx) = guard.take() {
|
||||
let _ = tx.send(());
|
||||
true
|
||||
} else {
|
||||
false
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// -------- Agent state holder --------
|
||||
|
||||
/// Everything the agent needs to run a trial. Mirrors the fields of
|
||||
/// `VectorState` the agent actually uses. Kept separate so the service
|
||||
/// layer builds it explicitly — no clone of unneeded state.
|
||||
#[derive(Clone)]
|
||||
pub struct AgentDeps {
|
||||
pub store: Arc<dyn ObjectStore>,
|
||||
pub ai_client: AiClient,
|
||||
pub catalog: CatalogRegistry,
|
||||
pub index_registry: IndexRegistry,
|
||||
pub hnsw_store: HnswStore,
|
||||
pub embedding_cache: EmbeddingCache,
|
||||
pub trial_journal: TrialJournal,
|
||||
pub promotion_registry: PromotionRegistry,
|
||||
}
|
||||
|
||||
// -------- Spawn --------
|
||||
|
||||
/// Start the agent loop in a background tokio task. Returns a handle
|
||||
/// the caller uses to enqueue events and read status.
|
||||
pub fn spawn(config: AgentConfig, deps: AgentDeps) -> AgentHandle {
|
||||
let (trigger_tx, trigger_rx) = mpsc::channel::<TriggerEvent>(256);
|
||||
let (stop_tx, stop_rx) = oneshot::channel::<()>();
|
||||
|
||||
let status = AgentStatus {
|
||||
running: config.enabled,
|
||||
config: config.clone(),
|
||||
queue_depth: 0,
|
||||
trials_run: 0,
|
||||
promotions: 0,
|
||||
trials_in_last_hour: 0,
|
||||
last_event: None,
|
||||
started_at: if config.enabled { Some(Utc::now()) } else { None },
|
||||
};
|
||||
|
||||
let inner = Arc::new(AgentInner {
|
||||
status: RwLock::new(status),
|
||||
stop_tx: Mutex::new(Some(stop_tx)),
|
||||
queue_len: Mutex::new(0),
|
||||
recent_trials: Mutex::new(VecDeque::with_capacity(64)),
|
||||
});
|
||||
|
||||
if config.enabled {
|
||||
tracing::info!(
|
||||
"autotune agent started (cycle={}s, cooldown={}s, cap={}/hr, min_recall={})",
|
||||
config.cycle_interval_secs, config.cooldown_between_trials_secs,
|
||||
config.max_trials_per_hour, config.min_recall,
|
||||
);
|
||||
let loop_inner = inner.clone();
|
||||
let loop_deps = deps.clone();
|
||||
let loop_config = config.clone();
|
||||
tokio::spawn(async move {
|
||||
run_loop(loop_config, loop_deps, trigger_rx, stop_rx, loop_inner).await;
|
||||
});
|
||||
} else {
|
||||
// Agent disabled — still drain the channel so sends don't back up.
|
||||
tokio::spawn(async move {
|
||||
let mut rx = trigger_rx;
|
||||
while rx.recv().await.is_some() {}
|
||||
});
|
||||
tracing::info!("autotune agent configured but disabled (set [agent].enabled=true)");
|
||||
}
|
||||
|
||||
AgentHandle { trigger_tx, inner }
|
||||
}
|
||||
|
||||
// -------- Main loop --------
|
||||
|
||||
async fn run_loop(
|
||||
config: AgentConfig,
|
||||
deps: AgentDeps,
|
||||
mut trigger_rx: mpsc::Receiver<TriggerEvent>,
|
||||
mut stop_rx: oneshot::Receiver<()>,
|
||||
inner: Arc<AgentInner>,
|
||||
) {
|
||||
let mut periodic = tokio::time::interval(std::time::Duration::from_secs(config.cycle_interval_secs));
|
||||
// First tick fires immediately — skip it so we don't double-fire on startup.
|
||||
periodic.tick().await;
|
||||
|
||||
loop {
|
||||
let event = tokio::select! {
|
||||
_ = &mut stop_rx => {
|
||||
tracing::info!("autotune agent: stop signal received");
|
||||
let mut s = inner.status.write().await;
|
||||
s.running = false;
|
||||
return;
|
||||
}
|
||||
maybe = trigger_rx.recv() => match maybe {
|
||||
Some(ev) => {
|
||||
let mut guard = inner.queue_len.lock().await;
|
||||
*guard = guard.saturating_sub(1);
|
||||
let mut s = inner.status.write().await;
|
||||
s.queue_depth = *guard;
|
||||
ev
|
||||
}
|
||||
None => {
|
||||
tracing::info!("autotune agent: trigger channel closed");
|
||||
return;
|
||||
}
|
||||
},
|
||||
_ = periodic.tick() => {
|
||||
// Periodic wake — pick an index with existing trials.
|
||||
// If nothing's been tuned yet there's nothing to propose.
|
||||
match pick_periodic_target(&deps).await {
|
||||
Some(idx) => TriggerEvent::periodic(idx),
|
||||
None => continue,
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
// Rate limit: count recent trials, skip if over budget.
|
||||
if over_rate_limit(&inner, config.max_trials_per_hour).await {
|
||||
record_event(&inner, "skipped_rate_limit", Some(&event.index_name),
|
||||
format!("hit cap of {}/hour", config.max_trials_per_hour)).await;
|
||||
continue;
|
||||
}
|
||||
|
||||
// Per-index cooldown.
|
||||
if cooling_down(&inner, &event.index_name, config.cooldown_between_trials_secs).await {
|
||||
record_event(&inner, "skipped_cooldown", Some(&event.index_name),
|
||||
format!("last trial too recent (<{}s)", config.cooldown_between_trials_secs)).await;
|
||||
continue;
|
||||
}
|
||||
|
||||
// Run one trial.
|
||||
match run_one_cycle(&event, &deps, config.min_recall).await {
|
||||
Ok(outcome) => {
|
||||
mark_recent_trial(&inner).await;
|
||||
{
|
||||
let mut s = inner.status.write().await;
|
||||
s.trials_run += 1;
|
||||
if outcome.promoted { s.promotions += 1; }
|
||||
}
|
||||
record_event(&inner, if outcome.promoted { "promoted" } else { "trial_completed" },
|
||||
Some(&event.index_name),
|
||||
format!("config=ec{}/es{} recall={:.3} p50={:.0}us {}",
|
||||
outcome.trial.config.ef_construction,
|
||||
outcome.trial.config.ef_search,
|
||||
outcome.trial.metrics.recall_at_k,
|
||||
outcome.trial.metrics.search_latency_p50_us,
|
||||
if outcome.promoted { "★ PROMOTED" } else { "" })).await;
|
||||
}
|
||||
Err(e) => {
|
||||
record_event(&inner, "trial_error", Some(&event.index_name), e).await;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Result of one cycle — ran a trial, maybe promoted it.
|
||||
struct CycleOutcome {
|
||||
trial: Trial,
|
||||
promoted: bool,
|
||||
}
|
||||
|
||||
/// Core cycle: propose → build → bench → record → maybe promote.
|
||||
async fn run_one_cycle(
|
||||
event: &TriggerEvent,
|
||||
deps: &AgentDeps,
|
||||
min_recall: f32,
|
||||
) -> Result<CycleOutcome, String> {
|
||||
// Read history.
|
||||
let history = deps.trial_journal.list(&event.index_name).await
|
||||
.map_err(|e| format!("read journal: {e}"))?;
|
||||
if history.is_empty() {
|
||||
return Err(format!(
|
||||
"no trials yet for '{}' — seed with at least one POST /hnsw/trial first",
|
||||
event.index_name,
|
||||
));
|
||||
}
|
||||
|
||||
// Current champion (if any) is the promoted config.
|
||||
let champion = deps.promotion_registry.get_current(&event.index_name).await;
|
||||
let champion_trial = champion.as_ref().and_then(|p| {
|
||||
history.iter().find(|t| t.id == p.trial_id).cloned()
|
||||
});
|
||||
|
||||
// Propose the next config.
|
||||
let Some(next_config) = propose_next_config(&history, champion_trial.as_ref()) else {
|
||||
return Err("proposer returned None — search space exhausted".into());
|
||||
};
|
||||
|
||||
// Validate bounds defensively.
|
||||
if !(10..=400).contains(&next_config.ef_construction) {
|
||||
return Err(format!("proposed ef_construction={} out of bounds", next_config.ef_construction));
|
||||
}
|
||||
if !(10..=200).contains(&next_config.ef_search) {
|
||||
return Err(format!("proposed ef_search={} out of bounds", next_config.ef_search));
|
||||
}
|
||||
|
||||
// Need a harness to measure. Use the most recent one in history.
|
||||
// (A future refinement: remember per-index "canonical harness" on
|
||||
// the index metadata. For now: latest wins.)
|
||||
let harness_name = history.last().unwrap().eval_set.clone();
|
||||
let mut harness_set = harness::EvalSet::load(&deps.store, &harness_name).await
|
||||
.map_err(|e| format!("load harness '{harness_name}': {e}"))?;
|
||||
|
||||
let embeddings = deps.embedding_cache.get_or_load(&event.index_name).await
|
||||
.map_err(|e| format!("embeddings: {e}"))?;
|
||||
|
||||
if !harness_set.ground_truth_built {
|
||||
harness::compute_ground_truth(&mut harness_set, &embeddings, &deps.ai_client).await
|
||||
.map_err(|e| format!("ground truth: {e}"))?;
|
||||
harness_set.save(&deps.store).await.ok();
|
||||
}
|
||||
|
||||
// Build + bench.
|
||||
let trial_id = Trial::new_id();
|
||||
let slot = format!("{}__{}", event.index_name, trial_id);
|
||||
let build = deps.hnsw_store
|
||||
.build_index_with_config(&slot, (*embeddings).clone(), &next_config)
|
||||
.await?;
|
||||
|
||||
let query_vectors: Vec<Vec<f32>> = harness_set.queries
|
||||
.iter().filter_map(|q| q.query_embedding.clone()).collect();
|
||||
let bench = deps.hnsw_store.bench_search(&slot, &query_vectors, harness_set.k).await?;
|
||||
|
||||
let mut recalls = Vec::with_capacity(harness_set.queries.len());
|
||||
for (q, hits) in harness_set.queries.iter().zip(bench.retrieved.iter()) {
|
||||
if let Some(gt) = &q.ground_truth {
|
||||
recalls.push(harness::recall_at_k(hits, gt, harness_set.k));
|
||||
}
|
||||
}
|
||||
let mean_recall = if recalls.is_empty() { 0.0 } else {
|
||||
recalls.iter().sum::<f32>() / recalls.len() as f32
|
||||
};
|
||||
|
||||
let mut lats = bench.latencies_us.clone();
|
||||
lats.sort_unstable_by(|a, b| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal));
|
||||
let p = |pct: f32| -> f32 {
|
||||
if lats.is_empty() { return 0.0; }
|
||||
let idx = ((lats.len() as f32 - 1.0) * pct).round() as usize;
|
||||
lats[idx.min(lats.len() - 1)]
|
||||
};
|
||||
|
||||
let dims = embeddings.first().map(|e| e.vector.len()).unwrap_or(0);
|
||||
let memory_bytes = (embeddings.len() * dims * std::mem::size_of::<f32>() + embeddings.len() * 128) as u64;
|
||||
|
||||
let note = match &event.reason {
|
||||
TriggerReason::DatasetAppended { dataset } => format!("agent: dataset_appended({dataset})"),
|
||||
TriggerReason::Manual => "agent: manual".to_string(),
|
||||
TriggerReason::Periodic => "agent: periodic".to_string(),
|
||||
};
|
||||
|
||||
let trial = Trial {
|
||||
id: trial_id,
|
||||
index_name: event.index_name.clone(),
|
||||
eval_set: harness_set.name.clone(),
|
||||
config: next_config.clone(),
|
||||
metrics: TrialMetrics {
|
||||
build_time_secs: build.build_time_secs,
|
||||
search_latency_p50_us: p(0.50),
|
||||
search_latency_p95_us: p(0.95),
|
||||
search_latency_p99_us: p(0.99),
|
||||
recall_at_k: mean_recall,
|
||||
memory_bytes,
|
||||
vectors: build.vectors,
|
||||
eval_queries: harness_set.queries.len(),
|
||||
brute_force_latency_us: 0.0,
|
||||
},
|
||||
created_at: Utc::now(),
|
||||
note: Some(note),
|
||||
};
|
||||
deps.trial_journal.append(&trial).await.ok();
|
||||
deps.hnsw_store.drop(&slot).await;
|
||||
|
||||
// Promotion decision: the new trial must meet recall gate AND beat
|
||||
// the current champion (higher recall OR same recall + lower p50).
|
||||
let promoted = if trial.metrics.recall_at_k < min_recall {
|
||||
false
|
||||
} else {
|
||||
let beats = match &champion_trial {
|
||||
None => true, // no champion yet — anything passing the gate wins
|
||||
Some(c) => beats_champion(&trial, c),
|
||||
};
|
||||
if beats {
|
||||
let entry = PromotionEntry {
|
||||
config: trial.config.clone(),
|
||||
trial_id: trial.id.clone(),
|
||||
promoted_at: Utc::now(),
|
||||
promoted_by: "agent".to_string(),
|
||||
note: Some(format!(
|
||||
"auto-promote: recall={:.3} p50={:.0}us (was {:.3}/{:.0}us)",
|
||||
trial.metrics.recall_at_k, trial.metrics.search_latency_p50_us,
|
||||
champion_trial.as_ref().map(|t| t.metrics.recall_at_k).unwrap_or(0.0),
|
||||
champion_trial.as_ref().map(|t| t.metrics.search_latency_p50_us).unwrap_or(0.0),
|
||||
)),
|
||||
};
|
||||
deps.promotion_registry.promote(&event.index_name, entry).await.is_ok()
|
||||
} else {
|
||||
false
|
||||
}
|
||||
};
|
||||
|
||||
Ok(CycleOutcome { trial, promoted })
|
||||
}
|
||||
|
||||
/// Champion-beat test: strictly higher recall, OR equal recall with
|
||||
/// lower p50. Same rule as autotune::pick_winner — kept consistent so the
|
||||
/// agent and the synchronous autotune agree on what "better" means.
|
||||
fn beats_champion(candidate: &Trial, champion: &Trial) -> bool {
|
||||
if candidate.metrics.recall_at_k > champion.metrics.recall_at_k {
|
||||
return true;
|
||||
}
|
||||
if (candidate.metrics.recall_at_k - champion.metrics.recall_at_k).abs() < 1e-4
|
||||
&& candidate.metrics.search_latency_p50_us < champion.metrics.search_latency_p50_us {
|
||||
return true;
|
||||
}
|
||||
false
|
||||
}
|
||||
|
||||
/// Propose the next HnswConfig given trial history and the current
|
||||
/// champion.
|
||||
///
|
||||
/// ============================================================
|
||||
/// J: THIS IS YOURS TO IMPLEMENT
|
||||
/// ============================================================
|
||||
///
|
||||
/// Inputs:
|
||||
/// - `history`: every trial ever run on this index, oldest first
|
||||
/// - `champion`: the currently-promoted trial, if any
|
||||
///
|
||||
/// Output:
|
||||
/// - `Some(HnswConfig)` with the config to try next
|
||||
/// - `None` if you decide there's nothing worth trying (agent logs
|
||||
/// "search space exhausted" and moves on)
|
||||
///
|
||||
/// Hard bounds the caller enforces: ef_construction ∈ [10, 400],
|
||||
/// ef_search ∈ [10, 200]. Stay inside those — configs outside get
|
||||
/// rejected and count as a wasted cycle.
|
||||
///
|
||||
/// Design options (pick one, or mix):
|
||||
///
|
||||
/// 1. LOCAL REFINEMENT (exploit-heavy):
|
||||
/// Sample near champion ± small delta. Converges fast, risks local
|
||||
/// minima. Good for "we know roughly where the sweet spot is."
|
||||
///
|
||||
/// 2. ε-GREEDY (mixed):
|
||||
/// With prob ε, random sample from full bounds (explore). Otherwise
|
||||
/// refinement around champion (exploit). ε=0.2 is a reasonable start.
|
||||
/// Good for long-running tune with no prior knowledge.
|
||||
///
|
||||
/// 3. COARSE→FINE (annealed):
|
||||
/// First N trials: wide random. Then shrink the neighborhood around
|
||||
/// champion as more trials accumulate. Mimics simulated annealing.
|
||||
///
|
||||
/// 4. DEDUP-AWARE:
|
||||
/// Whatever strategy, skip configs already in history. Prevents the
|
||||
/// agent from re-running the same (ec, es) pair twice.
|
||||
///
|
||||
/// A simple starter implementation is provided below (local refinement
|
||||
/// + dedup). Replace with your preferred strategy.
|
||||
pub fn propose_next_config(history: &[Trial], champion: Option<&Trial>) -> Option<HnswConfig> {
|
||||
// ε-greedy around the champion, dedup-aware.
|
||||
//
|
||||
// - With probability ε (≈0.25), sample a random config from the full
|
||||
// bounds. Keeps exploration alive so we don't get stuck hill-climbing
|
||||
// one axis.
|
||||
// - Otherwise: perturb the champion symmetrically on BOTH axes (not
|
||||
// just +20 / +40 like the starter did). Prefers small moves first
|
||||
// so recall stays near the current level.
|
||||
// - Always skip configs already in history — no point re-running.
|
||||
// - Deterministic per-history: RNG is seeded from history length so
|
||||
// the same journal state always proposes the same next config.
|
||||
// Makes tests + offline replay reproducible.
|
||||
|
||||
let base = champion
|
||||
.map(|t| t.config.clone())
|
||||
.or_else(|| history.last().map(|t| t.config.clone()))
|
||||
.unwrap_or_default();
|
||||
|
||||
let tried = |ec: usize, es: usize| -> bool {
|
||||
history.iter().any(|t|
|
||||
t.config.ef_construction == ec && t.config.ef_search == es
|
||||
)
|
||||
};
|
||||
let clamp = |ec: i32, es: i32| -> (usize, usize) {
|
||||
(ec.clamp(10, 400) as usize, es.clamp(10, 200) as usize)
|
||||
};
|
||||
|
||||
// Tiny xorshift — no rand crate dep. Seeded from history length so the
|
||||
// proposer is deterministic for a given journal state.
|
||||
let mut rng = (history.len() as u64).wrapping_mul(0x9E37_79B9_7F4A_7C15) | 1;
|
||||
let mut next_u = || {
|
||||
rng ^= rng << 13; rng ^= rng >> 7; rng ^= rng << 17;
|
||||
rng
|
||||
};
|
||||
|
||||
for _attempt in 0..32 {
|
||||
let explore = (next_u() % 100) < 25; // ε = 0.25
|
||||
let (ec, es) = if explore {
|
||||
clamp(10 + (next_u() % 391) as i32, 10 + (next_u() % 191) as i32)
|
||||
} else {
|
||||
// Symmetric perturbation — signed steps on both axes.
|
||||
let dec = [-40, -20, -10, 10, 20, 40][(next_u() % 6) as usize];
|
||||
let des = [-20, -10, -5, 5, 10, 20][(next_u() % 6) as usize];
|
||||
clamp(base.ef_construction as i32 + dec, base.ef_search as i32 + des)
|
||||
};
|
||||
if !tried(ec, es) {
|
||||
return Some(HnswConfig { ef_construction: ec, ef_search: es, seed: Some(42) });
|
||||
}
|
||||
}
|
||||
None // 32 attempts all landed on duplicates — likely saturated
|
||||
}
|
||||
|
||||
// -------- Helpers --------
|
||||
|
||||
/// Find an index to poke on a periodic wake. Strategy: the one with the
|
||||
/// most recent trial. If nothing's been trialed yet, return None.
|
||||
async fn pick_periodic_target(deps: &AgentDeps) -> Option<String> {
|
||||
// `/agent` runs against any index that has a trial journal. We don't
|
||||
// have a "list all journals" helper, so we derive candidates from the
|
||||
// promotion registry (indexes with a human ever promoting are live).
|
||||
let promos = deps.promotion_registry.list_all().await.ok()?;
|
||||
// Prefer the one most recently promoted — it's the one a human cares
|
||||
// about right now.
|
||||
promos.into_iter()
|
||||
.filter_map(|f| f.current.map(|c| (f.index_name, c.promoted_at)))
|
||||
.max_by_key(|(_, at)| *at)
|
||||
.map(|(name, _)| name)
|
||||
}
|
||||
|
||||
async fn over_rate_limit(inner: &Arc<AgentInner>, cap: u32) -> bool {
|
||||
let cutoff = Utc::now() - chrono::Duration::hours(1);
|
||||
let ring = inner.recent_trials.lock().await;
|
||||
ring.iter().filter(|t| **t >= cutoff).count() as u32 >= cap
|
||||
}
|
||||
|
||||
async fn cooling_down(inner: &Arc<AgentInner>, _index: &str, cooldown_secs: u64) -> bool {
|
||||
// Minimal impl: gate on global most-recent trial rather than per-index.
|
||||
// Per-index cooldown would be easy to add — keep a HashMap<String, DateTime>
|
||||
// — but for Phase 16.2 MVP, global is fine. Ollama is the shared resource.
|
||||
let ring = inner.recent_trials.lock().await;
|
||||
if let Some(last) = ring.back() {
|
||||
let since = Utc::now().signed_duration_since(*last);
|
||||
return since < chrono::Duration::seconds(cooldown_secs as i64);
|
||||
}
|
||||
false
|
||||
}
|
||||
|
||||
async fn mark_recent_trial(inner: &Arc<AgentInner>) {
|
||||
let mut ring = inner.recent_trials.lock().await;
|
||||
ring.push_back(Utc::now());
|
||||
// Keep bounded.
|
||||
while ring.len() > 256 {
|
||||
ring.pop_front();
|
||||
}
|
||||
}
|
||||
|
||||
async fn record_event(
|
||||
inner: &Arc<AgentInner>,
|
||||
kind: &str,
|
||||
index: Option<&str>,
|
||||
detail: String,
|
||||
) {
|
||||
tracing::info!("agent: {} {}{}", kind,
|
||||
index.map(|i| format!("[{i}] ")).unwrap_or_default(), detail);
|
||||
let mut s = inner.status.write().await;
|
||||
s.last_event = Some(AgentEvent {
|
||||
at: Utc::now(),
|
||||
kind: kind.to_string(),
|
||||
index_name: index.map(String::from),
|
||||
detail,
|
||||
});
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
|
||||
fn mk_trial(ec: usize, es: usize, recall: f32, p50: f32) -> Trial {
|
||||
Trial {
|
||||
id: format!("t-{ec}-{es}"),
|
||||
index_name: "test".into(),
|
||||
eval_set: "eval".into(),
|
||||
config: HnswConfig { ef_construction: ec, ef_search: es, seed: Some(42) },
|
||||
metrics: TrialMetrics {
|
||||
build_time_secs: 1.0,
|
||||
search_latency_p50_us: p50,
|
||||
search_latency_p95_us: p50 * 1.5,
|
||||
search_latency_p99_us: p50 * 2.0,
|
||||
recall_at_k: recall,
|
||||
memory_bytes: 0, vectors: 1000, eval_queries: 10,
|
||||
brute_force_latency_us: 100.0,
|
||||
},
|
||||
created_at: Utc::now(),
|
||||
note: None,
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn propose_skips_duplicates() {
|
||||
let hist = vec![
|
||||
mk_trial(80, 30, 1.0, 500.0),
|
||||
mk_trial(100, 30, 1.0, 520.0), // ec+20
|
||||
];
|
||||
let next = propose_next_config(&hist, Some(&hist[0])).unwrap();
|
||||
// ec+20 is taken, so the proposer should skip it.
|
||||
assert!(next.ef_construction != 100 || next.ef_search != 30);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn beats_champion_strict_recall() {
|
||||
let champ = mk_trial(80, 30, 0.95, 500.0);
|
||||
let better_recall = mk_trial(80, 30, 0.99, 600.0);
|
||||
let worse_recall = mk_trial(80, 30, 0.90, 100.0);
|
||||
assert!(beats_champion(&better_recall, &champ));
|
||||
assert!(!beats_champion(&worse_recall, &champ));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn beats_champion_same_recall_lower_latency() {
|
||||
let champ = mk_trial(80, 30, 1.0, 500.0);
|
||||
let faster = mk_trial(60, 30, 1.0, 400.0);
|
||||
let slower = mk_trial(60, 30, 1.0, 600.0);
|
||||
assert!(beats_champion(&faster, &champ));
|
||||
assert!(!beats_champion(&slower, &champ));
|
||||
}
|
||||
}
|
||||
@@ -29,8 +29,21 @@ pub struct IndexMeta {
|
||||
pub created_at: DateTime<Utc>,
|
||||
pub build_time_secs: f32,
|
||||
pub chunks_per_sec: f32,
|
||||
/// Federation layer 2: which bucket holds this index's artifacts
|
||||
/// (trial journal + promotion file). Defaults to "primary" for
|
||||
/// pre-federation indexes — the serde default keeps old metadata
|
||||
/// files readable without migration.
|
||||
#[serde(default = "default_bucket")]
|
||||
pub bucket: String,
|
||||
/// ADR-019: which physical backend stores this index. `Parquet`
|
||||
/// means storage_key points at our binary-blob Parquet file;
|
||||
/// `Lance` means it points at a Lance dataset directory.
|
||||
#[serde(default)]
|
||||
pub vector_backend: shared::types::VectorBackend,
|
||||
}
|
||||
|
||||
fn default_bucket() -> String { "primary".to_string() }
|
||||
|
||||
/// Registry of all vector indexes.
|
||||
#[derive(Clone)]
|
||||
pub struct IndexRegistry {
|
||||
|
||||
@@ -0,0 +1,112 @@
|
||||
//! ADR-019 hybrid: routing layer for the Lance vector backend.
|
||||
//!
|
||||
//! Holds a `LanceRegistry` which maps an index name to its
|
||||
//! `LanceVectorStore` instance, lazy-creating on first touch. Path
|
||||
//! resolution: the index's bucket gives us a bucket root; we append
|
||||
//! `lance/{index_name}` and use that as the dataset URI. For local
|
||||
//! buckets that means a directory under the bucket's root.
|
||||
//!
|
||||
//! S3 buckets: in principle Lance accepts s3://... URIs, but the
|
||||
//! firewall crate (`vectord-lance`) doesn't pull the S3 feature in by
|
||||
//! default. When we promote profile buckets onto S3 in a future phase,
|
||||
//! enable that feature and update `lance_uri_for` accordingly.
|
||||
|
||||
use std::collections::HashMap;
|
||||
use std::path::PathBuf;
|
||||
use std::sync::Arc;
|
||||
use tokio::sync::RwLock;
|
||||
|
||||
use storaged::registry::BucketRegistry;
|
||||
use vectord_lance::LanceVectorStore;
|
||||
|
||||
use crate::index_registry::IndexRegistry;
|
||||
|
||||
/// Convert a bucket+index pair into the URI Lance should use as the
|
||||
/// dataset path. Local-only for MVP; S3 when we wire that backend.
|
||||
///
|
||||
/// Path resolution mirrors lakehouse.toml's convention for local
|
||||
/// buckets: ./data for primary, ./data/_rescue for rescue, ./data/_testing
|
||||
/// for testing, ./data/_profiles/{sanitized} for profile:* buckets, and
|
||||
/// ./data/_buckets/{sanitized} for everything else. Sanitization replaces
|
||||
/// `:` with `_` so paths are filesystem-safe.
|
||||
///
|
||||
/// Refuses unknown buckets so a typo doesn't silently land Lance data
|
||||
/// in a directory the rest of the system can't see.
|
||||
pub fn lance_uri_for(
|
||||
buckets: &BucketRegistry,
|
||||
bucket: &str,
|
||||
index_name: &str,
|
||||
) -> Result<String, String> {
|
||||
if !buckets.contains(bucket) {
|
||||
return Err(format!("bucket '{bucket}' not registered"));
|
||||
}
|
||||
let root: PathBuf = match bucket {
|
||||
"primary" => PathBuf::from("./data"),
|
||||
"rescue" => PathBuf::from("./data/_rescue"),
|
||||
"testing" => PathBuf::from("./data/_testing"),
|
||||
b if b.starts_with("profile:") => {
|
||||
let safe = b.replace(':', "_");
|
||||
PathBuf::from(format!("./data/_profiles/{safe}"))
|
||||
}
|
||||
b => PathBuf::from(format!("./data/_buckets/{}", b.replace(':', "_"))),
|
||||
};
|
||||
let dataset_dir = root.join("lance").join(index_name);
|
||||
// Pre-create the parent so Lance's first write doesn't trip on a
|
||||
// missing ancestor. Lance handles the dataset directory itself.
|
||||
let _ = std::fs::create_dir_all(root.join("lance"));
|
||||
// Canonicalize after the parent is guaranteed to exist; if the
|
||||
// dataset dir hasn't been created yet, canonicalize the parent and
|
||||
// tack on the leaf name.
|
||||
let abs = match std::fs::canonicalize(&root) {
|
||||
Ok(p) => p.join("lance").join(index_name),
|
||||
Err(_) => dataset_dir.clone(),
|
||||
};
|
||||
Ok(abs.to_string_lossy().to_string())
|
||||
}
|
||||
|
||||
/// Lookup-by-index registry of `LanceVectorStore` handles. One handle
|
||||
/// per index, lazy-created on first call. Cheap to keep alive — it's
|
||||
/// just a path string + handle to Lance's metadata cache.
|
||||
#[derive(Clone)]
|
||||
pub struct LanceRegistry {
|
||||
buckets: Arc<BucketRegistry>,
|
||||
indexes: IndexRegistry,
|
||||
stores: Arc<RwLock<HashMap<String, LanceVectorStore>>>,
|
||||
}
|
||||
|
||||
impl LanceRegistry {
|
||||
pub fn new(buckets: Arc<BucketRegistry>, indexes: IndexRegistry) -> Self {
|
||||
Self {
|
||||
buckets,
|
||||
indexes,
|
||||
stores: Arc::new(RwLock::new(HashMap::new())),
|
||||
}
|
||||
}
|
||||
|
||||
/// Get (or lazy-create) the LanceVectorStore for an index.
|
||||
/// Resolves bucket → URI via the registry; backend stays whatever
|
||||
/// IndexMeta says (no enforcement here — caller decides whether to
|
||||
/// route to Lance based on profile/index backend choice).
|
||||
pub async fn store_for(&self, index_name: &str) -> Result<LanceVectorStore, String> {
|
||||
if let Some(s) = self.stores.read().await.get(index_name) {
|
||||
return Ok(s.clone());
|
||||
}
|
||||
let bucket = self.indexes
|
||||
.get(index_name).await
|
||||
.map(|m| m.bucket)
|
||||
.unwrap_or_else(|| "primary".to_string());
|
||||
let uri = lance_uri_for(&self.buckets, &bucket, index_name)?;
|
||||
let store = LanceVectorStore::new(uri);
|
||||
self.stores.write().await.insert(index_name.to_string(), store.clone());
|
||||
Ok(store)
|
||||
}
|
||||
|
||||
/// For freshly-created indexes that don't have IndexMeta yet — caller
|
||||
/// supplies the bucket explicitly.
|
||||
pub async fn store_for_new(&self, index_name: &str, bucket: &str) -> Result<LanceVectorStore, String> {
|
||||
let uri = lance_uri_for(&self.buckets, bucket, index_name)?;
|
||||
let store = LanceVectorStore::new(uri);
|
||||
self.stores.write().await.insert(index_name.to_string(), store.clone());
|
||||
Ok(store)
|
||||
}
|
||||
}
|
||||
@@ -1,4 +1,6 @@
|
||||
pub mod agent;
|
||||
pub mod autotune;
|
||||
pub mod lance_backend;
|
||||
pub mod chunker;
|
||||
pub mod embedding_cache;
|
||||
pub mod harness;
|
||||
|
||||
@@ -19,13 +19,14 @@
|
||||
//! - Agent loop — lives in `vectord::autotune`.
|
||||
|
||||
use chrono::{DateTime, Utc};
|
||||
use object_store::ObjectStore;
|
||||
use serde::{Deserialize, Serialize};
|
||||
use std::collections::HashMap;
|
||||
use std::sync::Arc;
|
||||
use storaged::ops;
|
||||
use storaged::registry::BucketRegistry;
|
||||
use tokio::sync::RwLock;
|
||||
|
||||
use crate::index_registry::IndexRegistry;
|
||||
use crate::trial::HnswConfig;
|
||||
|
||||
const PROMOTION_PREFIX: &str = "_hnsw_promotions";
|
||||
@@ -55,14 +56,16 @@ pub struct PromotionFile {
|
||||
|
||||
#[derive(Clone)]
|
||||
pub struct PromotionRegistry {
|
||||
store: Arc<dyn ObjectStore>,
|
||||
buckets: Arc<BucketRegistry>,
|
||||
index_registry: IndexRegistry,
|
||||
cache: Arc<RwLock<HashMap<String, PromotionFile>>>,
|
||||
}
|
||||
|
||||
impl PromotionRegistry {
|
||||
pub fn new(store: Arc<dyn ObjectStore>) -> Self {
|
||||
pub fn new(buckets: Arc<BucketRegistry>, index_registry: IndexRegistry) -> Self {
|
||||
Self {
|
||||
store,
|
||||
buckets,
|
||||
index_registry,
|
||||
cache: Arc::new(RwLock::new(HashMap::new())),
|
||||
}
|
||||
}
|
||||
@@ -76,13 +79,26 @@ impl PromotionRegistry {
|
||||
format!("{PROMOTION_PREFIX}/{safe}.json")
|
||||
}
|
||||
|
||||
/// Resolve which bucket's store holds this index's promotion file.
|
||||
/// Same rules as TrialJournal::bucket_for — follows IndexMeta.bucket,
|
||||
/// defaults to primary when metadata is missing.
|
||||
async fn store_for(&self, index_name: &str) -> Result<Arc<dyn object_store::ObjectStore>, String> {
|
||||
let bucket = self.index_registry
|
||||
.get(index_name)
|
||||
.await
|
||||
.map(|m| m.bucket)
|
||||
.unwrap_or_else(|| "primary".to_string());
|
||||
self.buckets.get(&bucket)
|
||||
}
|
||||
|
||||
/// Load (and cache) the promotion file for an index.
|
||||
pub async fn load(&self, index_name: &str) -> Result<PromotionFile, String> {
|
||||
if let Some(cached) = self.cache.read().await.get(index_name) {
|
||||
return Ok(cached.clone());
|
||||
}
|
||||
let store = self.store_for(index_name).await?;
|
||||
let key = Self::key(index_name);
|
||||
let file = match ops::get(&self.store, &key).await {
|
||||
let file = match ops::get(&store, &key).await {
|
||||
Ok(bytes) => serde_json::from_slice::<PromotionFile>(&bytes)
|
||||
.map_err(|e| format!("parse promotion file: {e}"))?,
|
||||
Err(_) => PromotionFile {
|
||||
@@ -118,9 +134,10 @@ impl PromotionRegistry {
|
||||
file.current = Some(entry);
|
||||
file.index_name = index_name.to_string();
|
||||
|
||||
let store = self.store_for(index_name).await?;
|
||||
let key = Self::key(index_name);
|
||||
let json = serde_json::to_vec_pretty(&file).map_err(|e| e.to_string())?;
|
||||
ops::put(&self.store, &key, json.into()).await?;
|
||||
ops::put(&store, &key, json.into()).await?;
|
||||
|
||||
self.cache.write().await.insert(index_name.to_string(), file.clone());
|
||||
tracing::info!(
|
||||
@@ -146,9 +163,10 @@ impl PromotionRegistry {
|
||||
file.current = None;
|
||||
}
|
||||
}
|
||||
let store = self.store_for(index_name).await?;
|
||||
let key = Self::key(index_name);
|
||||
let json = serde_json::to_vec_pretty(&file).map_err(|e| e.to_string())?;
|
||||
ops::put(&self.store, &key, json.into()).await?;
|
||||
ops::put(&store, &key, json.into()).await?;
|
||||
self.cache.write().await.insert(index_name.to_string(), file.clone());
|
||||
tracing::info!("rolled back promotion for '{}'", index_name);
|
||||
Ok(file)
|
||||
@@ -169,19 +187,34 @@ impl PromotionRegistry {
|
||||
}
|
||||
|
||||
/// List every index that has a promotion recorded (for operator UI).
|
||||
///
|
||||
/// Federation: scans EVERY registered bucket for promotion files.
|
||||
/// Per-profile buckets each have their own `_hnsw_promotions/` so we
|
||||
/// aggregate across them. Dedups by index_name — if the same index
|
||||
/// somehow has promotion files in multiple buckets, the one from the
|
||||
/// bucket recorded in IndexMeta wins.
|
||||
pub async fn list_all(&self) -> Result<Vec<PromotionFile>, String> {
|
||||
let keys = ops::list(&self.store, Some(&format!("{PROMOTION_PREFIX}/"))).await.unwrap_or_default();
|
||||
let mut out = Vec::new();
|
||||
for key in keys {
|
||||
if !key.ends_with(".json") { continue; }
|
||||
let bytes = match ops::get(&self.store, &key).await {
|
||||
Ok(b) => b,
|
||||
let bucket_infos = self.buckets.list().await;
|
||||
let mut by_name: HashMap<String, PromotionFile> = HashMap::new();
|
||||
|
||||
for b in &bucket_infos {
|
||||
let store = match self.buckets.get(&b.name) {
|
||||
Ok(s) => s,
|
||||
Err(_) => continue,
|
||||
};
|
||||
if let Ok(f) = serde_json::from_slice::<PromotionFile>(&bytes) {
|
||||
out.push(f);
|
||||
let keys = ops::list(&store, Some(&format!("{PROMOTION_PREFIX}/")))
|
||||
.await.unwrap_or_default();
|
||||
for key in keys {
|
||||
if !key.ends_with(".json") { continue; }
|
||||
let bytes = match ops::get(&store, &key).await {
|
||||
Ok(b) => b,
|
||||
Err(_) => continue,
|
||||
};
|
||||
if let Ok(f) = serde_json::from_slice::<PromotionFile>(&bytes) {
|
||||
by_name.insert(f.index_name.clone(), f);
|
||||
}
|
||||
}
|
||||
}
|
||||
Ok(out)
|
||||
Ok(by_name.into_values().collect())
|
||||
}
|
||||
}
|
||||
|
||||
@@ -305,6 +305,8 @@ async fn try_update_index_meta(
|
||||
created_at: chrono::Utc::now(),
|
||||
build_time_secs: 0.0,
|
||||
chunks_per_sec: 0.0,
|
||||
bucket: "primary".to_string(),
|
||||
vector_backend: shared::types::VectorBackend::Parquet,
|
||||
};
|
||||
index_registry.register(meta).await
|
||||
}
|
||||
|
||||
@@ -11,7 +11,8 @@ use std::sync::Arc;
|
||||
|
||||
use aibridge::client::{AiClient, EmbedRequest};
|
||||
use catalogd::registry::Registry as CatalogRegistry;
|
||||
use crate::{autotune, chunker, embedding_cache, harness, hnsw, index_registry, jobs, promotion, rag, refresh, search, store, supervisor, trial};
|
||||
use storaged::registry::BucketRegistry;
|
||||
use crate::{agent, autotune, chunker, embedding_cache, harness, hnsw, index_registry, jobs, lance_backend, promotion, rag, refresh, search, store, supervisor, trial};
|
||||
|
||||
#[derive(Clone)]
|
||||
pub struct VectorState {
|
||||
@@ -27,6 +28,33 @@ pub struct VectorState {
|
||||
pub catalog: CatalogRegistry,
|
||||
/// Phase 16: promoted HNSW configs. Activation + autotune read/write here.
|
||||
pub promotion_registry: promotion::PromotionRegistry,
|
||||
/// Phase 16.2: handle to the background autotune agent. Always
|
||||
/// present — if the agent is disabled in config, the handle drops
|
||||
/// incoming triggers silently.
|
||||
pub agent_handle: agent::AgentHandle,
|
||||
/// Phase B (federation layer 2): bucket registry for per-profile
|
||||
/// bucket auto-provisioning on activation.
|
||||
pub bucket_registry: Arc<BucketRegistry>,
|
||||
/// Phase C (two-profile VRAM gate): tracks which profile is currently
|
||||
/// "active" on the GPU. Singleton — one profile at a time holds its
|
||||
/// model in VRAM. Swapping profiles with different ollama_name unloads
|
||||
/// the previous one (keep_alive=0) before preloading the new one.
|
||||
///
|
||||
/// `None` = no profile has been activated this session; any first
|
||||
/// activation just preloads and takes the slot.
|
||||
pub active_profile: Arc<tokio::sync::RwLock<Option<ActiveProfileSlot>>>,
|
||||
/// ADR-019 hybrid: handles to Lance datasets keyed by index name.
|
||||
/// Lazy-created on first /vectors/lance/* call.
|
||||
pub lance: lance_backend::LanceRegistry,
|
||||
}
|
||||
|
||||
/// What the active-profile singleton records. Narrow — we don't need the
|
||||
/// full ModelProfile here, just enough to know what to unload on swap.
|
||||
#[derive(Debug, Clone, Serialize)]
|
||||
pub struct ActiveProfileSlot {
|
||||
pub profile_id: String,
|
||||
pub ollama_name: String,
|
||||
pub activated_at: chrono::DateTime<chrono::Utc>,
|
||||
}
|
||||
|
||||
pub fn router(state: VectorState) -> Router {
|
||||
@@ -59,12 +87,26 @@ pub fn router(state: VectorState) -> Router {
|
||||
// Phase 17: profile activation — pre-load caches + HNSW for this
|
||||
// model's bound data. First search after activate is warm.
|
||||
.route("/profile/{id}/activate", post(activate_profile))
|
||||
.route("/profile/{id}/deactivate", post(deactivate_profile))
|
||||
.route("/profile/{id}/search", post(profile_scoped_search))
|
||||
// Phase 17 VRAM gate: which profile currently owns the GPU?
|
||||
.route("/profile/active", get(get_active_profile))
|
||||
// Phase 16: promotion + autotune
|
||||
.route("/hnsw/promote/{index}/{trial_id}", post(promote_trial))
|
||||
.route("/hnsw/rollback/{index}", post(rollback_promotion))
|
||||
.route("/hnsw/promoted/{index}", get(get_promoted))
|
||||
.route("/hnsw/autotune", post(run_autotune_endpoint))
|
||||
// Phase 16.2: background autotune agent
|
||||
.route("/agent/status", get(agent_status))
|
||||
.route("/agent/stop", post(agent_stop))
|
||||
.route("/agent/enqueue/{index_name}", post(agent_enqueue))
|
||||
// ADR-019: Lance hybrid backend
|
||||
.route("/lance/migrate/{index_name}", post(lance_migrate))
|
||||
.route("/lance/index/{index_name}", post(lance_build_index))
|
||||
.route("/lance/search/{index_name}", post(lance_search))
|
||||
.route("/lance/doc/{index_name}/{doc_id}", get(lance_get_doc))
|
||||
.route("/lance/append/{index_name}", post(lance_append))
|
||||
.route("/lance/stats/{index_name}", get(lance_stats))
|
||||
.with_state(state)
|
||||
}
|
||||
|
||||
@@ -81,6 +123,11 @@ struct CreateIndexRequest {
|
||||
documents: Vec<DocInput>,
|
||||
chunk_size: Option<usize>,
|
||||
overlap: Option<usize>,
|
||||
/// Federation layer 2: optional bucket to hold this index's trial
|
||||
/// journal + promotion file. Defaults to "primary" — pre-existing
|
||||
/// clients that don't know about federation keep working unchanged.
|
||||
#[serde(default)]
|
||||
bucket: Option<String>,
|
||||
}
|
||||
|
||||
#[derive(Deserialize)]
|
||||
@@ -117,6 +164,7 @@ async fn create_index(
|
||||
let n_docs = req.documents.len();
|
||||
let n_chunks = chunks.len();
|
||||
let index_name = req.index_name.clone();
|
||||
let bucket = req.bucket.clone().unwrap_or_else(|| "primary".to_string());
|
||||
|
||||
// Create job and return immediately
|
||||
let job_id = state.job_tracker.create(&index_name, n_chunks).await;
|
||||
@@ -157,6 +205,8 @@ async fn create_index(
|
||||
created_at: chrono::Utc::now(),
|
||||
build_time_secs: elapsed,
|
||||
chunks_per_sec: rate,
|
||||
bucket: bucket.clone(),
|
||||
vector_backend: shared::types::VectorBackend::Parquet,
|
||||
};
|
||||
let _ = registry.register(meta).await;
|
||||
|
||||
@@ -753,6 +803,11 @@ struct ActivateReport {
|
||||
failures: Vec<String>,
|
||||
total_vectors: usize,
|
||||
duration_secs: f32,
|
||||
/// Phase C: did we successfully preload the Ollama model?
|
||||
model_preloaded: bool,
|
||||
/// Phase C: which profile previously held the GPU slot, if any.
|
||||
/// Useful for observability of the swap.
|
||||
previous_profile: Option<String>,
|
||||
}
|
||||
|
||||
#[derive(Serialize)]
|
||||
@@ -788,6 +843,64 @@ async fn activate_profile(
|
||||
let mut failures = Vec::new();
|
||||
let mut total_vectors = 0usize;
|
||||
|
||||
// Phase 17 / C: VRAM-aware swap. If another profile currently holds
|
||||
// the GPU and uses a DIFFERENT Ollama model than the one being
|
||||
// activated, unload it first (keep_alive=0). Same-model activations
|
||||
// skip the unload — no point churning a model that's already loaded.
|
||||
let previous_slot = {
|
||||
let guard = state.active_profile.read().await;
|
||||
guard.clone()
|
||||
};
|
||||
if let Some(prev) = &previous_slot {
|
||||
if prev.ollama_name != profile.ollama_name {
|
||||
match state.ai_client.unload_model(&prev.ollama_name).await {
|
||||
Ok(_) => tracing::info!(
|
||||
"profile swap: unloaded '{}' ({} -> {})",
|
||||
prev.ollama_name, prev.profile_id, profile.id,
|
||||
),
|
||||
Err(e) => failures.push(format!(
|
||||
"unload previous model '{}': {e}", prev.ollama_name,
|
||||
)),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Federation layer 2: if this profile declares its own bucket and
|
||||
// that bucket isn't registered yet, auto-provision it under the
|
||||
// configured profile_root. This is the moment a "dormant" profile
|
||||
// becomes live — its bucket exists and is readable/writable.
|
||||
if let Some(bucket_name) = profile.bucket.clone() {
|
||||
if !state.bucket_registry.contains(&bucket_name) {
|
||||
let root = format!(
|
||||
"{}/{}",
|
||||
state.bucket_registry.profile_root().trim_end_matches('/'),
|
||||
bucket_name.replace(':', "_"),
|
||||
);
|
||||
let bc = shared::config::BucketConfig {
|
||||
name: bucket_name.clone(),
|
||||
backend: "local".to_string(),
|
||||
root: Some(root.clone()),
|
||||
bucket: None,
|
||||
region: None,
|
||||
endpoint: None,
|
||||
secret_ref: None,
|
||||
};
|
||||
match state.bucket_registry.add_bucket(bc).await {
|
||||
Ok(info) => {
|
||||
tracing::info!(
|
||||
"profile '{}' activated bucket '{}' (root={}, reachable={})",
|
||||
profile.id, bucket_name, root, info.reachable,
|
||||
);
|
||||
}
|
||||
Err(e) => {
|
||||
failures.push(format!(
|
||||
"auto-provision bucket '{}': {}", bucket_name, e,
|
||||
));
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
let all_indexes = state.index_registry.list(None, None).await;
|
||||
|
||||
for binding in &profile.bound_datasets {
|
||||
@@ -847,6 +960,30 @@ async fn activate_profile(
|
||||
}
|
||||
}
|
||||
|
||||
// Preload the new profile's Ollama model proactively. Same-model
|
||||
// re-activations are cheap (Ollama no-ops if already loaded).
|
||||
let mut model_preloaded = false;
|
||||
match state.ai_client.preload_model(&profile.ollama_name).await {
|
||||
Ok(_) => {
|
||||
model_preloaded = true;
|
||||
tracing::info!("profile '{}' preloaded ollama model '{}'",
|
||||
profile.id, profile.ollama_name);
|
||||
}
|
||||
Err(e) => failures.push(format!(
|
||||
"preload ollama model '{}': {e}", profile.ollama_name,
|
||||
)),
|
||||
}
|
||||
|
||||
// Take the GPU slot.
|
||||
{
|
||||
let mut guard = state.active_profile.write().await;
|
||||
*guard = Some(ActiveProfileSlot {
|
||||
profile_id: profile.id.clone(),
|
||||
ollama_name: profile.ollama_name.clone(),
|
||||
activated_at: chrono::Utc::now(),
|
||||
});
|
||||
}
|
||||
|
||||
Ok(Json(ActivateReport {
|
||||
profile_id: profile.id,
|
||||
ollama_name: profile.ollama_name,
|
||||
@@ -854,9 +991,52 @@ async fn activate_profile(
|
||||
failures,
|
||||
total_vectors,
|
||||
duration_secs: t0.elapsed().as_secs_f32(),
|
||||
model_preloaded,
|
||||
previous_profile: previous_slot.map(|s| s.profile_id),
|
||||
}))
|
||||
}
|
||||
|
||||
/// Unload this profile's model and clear the active slot. No-op if the
|
||||
/// caller isn't the currently-active profile.
|
||||
async fn deactivate_profile(
|
||||
State(state): State<VectorState>,
|
||||
Path(profile_id): Path<String>,
|
||||
) -> impl IntoResponse {
|
||||
let profile = match state.catalog.get_profile(&profile_id).await {
|
||||
Some(p) => p,
|
||||
None => return Err((StatusCode::NOT_FOUND, format!("profile not found: {profile_id}"))),
|
||||
};
|
||||
|
||||
let was_active = {
|
||||
let mut guard = state.active_profile.write().await;
|
||||
match guard.as_ref() {
|
||||
Some(s) if s.profile_id == profile_id => {
|
||||
let prev = s.clone();
|
||||
*guard = None;
|
||||
Some(prev)
|
||||
}
|
||||
_ => None,
|
||||
}
|
||||
};
|
||||
|
||||
// Regardless of whether it held the slot, we can still try to unload —
|
||||
// the operator's intent is "get this model out of VRAM."
|
||||
let unload_result = state.ai_client.unload_model(&profile.ollama_name).await;
|
||||
|
||||
Ok(Json(serde_json::json!({
|
||||
"profile_id": profile.id,
|
||||
"ollama_name": profile.ollama_name,
|
||||
"was_active": was_active.is_some(),
|
||||
"unloaded": unload_result.is_ok(),
|
||||
"unload_error": unload_result.err(),
|
||||
})))
|
||||
}
|
||||
|
||||
async fn get_active_profile(State(state): State<VectorState>) -> impl IntoResponse {
|
||||
let slot = state.active_profile.read().await.clone();
|
||||
Json(slot)
|
||||
}
|
||||
|
||||
#[derive(Deserialize)]
|
||||
struct ProfileSearchRequest {
|
||||
index_name: String,
|
||||
@@ -1013,3 +1193,232 @@ async fn run_autotune_endpoint(
|
||||
Err(e) => Err((StatusCode::INTERNAL_SERVER_ERROR, e)),
|
||||
}
|
||||
}
|
||||
|
||||
// --- Phase 16.2: autotune agent endpoints ---
|
||||
|
||||
async fn agent_status(State(state): State<VectorState>) -> impl IntoResponse {
|
||||
Json(state.agent_handle.status().await)
|
||||
}
|
||||
|
||||
async fn agent_stop(State(state): State<VectorState>) -> impl IntoResponse {
|
||||
let stopped = state.agent_handle.stop().await;
|
||||
Json(serde_json::json!({ "stopped": stopped }))
|
||||
}
|
||||
|
||||
async fn agent_enqueue(
|
||||
State(state): State<VectorState>,
|
||||
Path(index_name): Path<String>,
|
||||
) -> impl IntoResponse {
|
||||
let event = agent::TriggerEvent::manual(index_name);
|
||||
match state.agent_handle.enqueue(event).await {
|
||||
Ok(()) => Ok(Json(serde_json::json!({ "enqueued": true }))),
|
||||
Err(e) => Err((StatusCode::SERVICE_UNAVAILABLE, e)),
|
||||
}
|
||||
}
|
||||
|
||||
// --- ADR-019: Lance hybrid backend HTTP surface ---
|
||||
//
|
||||
// Lance routes operate on the same `index_name` as the Parquet/HNSW path,
|
||||
// but materialize the data as a Lance dataset on disk under
|
||||
// `{bucket_root}/lance/{index_name}/`. The two backends are independent:
|
||||
// you can have an index in both formats simultaneously. `IndexMeta.vector_backend`
|
||||
// records which one is canonical for that index.
|
||||
|
||||
#[derive(Deserialize)]
|
||||
struct LanceMigrateRequest {
|
||||
/// Optional bucket override. Defaults to whatever the existing
|
||||
/// IndexMeta says, or "primary" for indexes that don't exist yet.
|
||||
#[serde(default)]
|
||||
bucket: Option<String>,
|
||||
}
|
||||
|
||||
/// Read the existing Parquet vector file for `index_name` from object
|
||||
/// storage, hand the bytes to vectord-lance, return migration stats.
|
||||
/// The original Parquet file is left intact — both backends coexist
|
||||
/// after migration.
|
||||
async fn lance_migrate(
|
||||
State(state): State<VectorState>,
|
||||
Path(index_name): Path<String>,
|
||||
Json(req): Json<LanceMigrateRequest>,
|
||||
) -> impl IntoResponse {
|
||||
let meta = state.index_registry.get(&index_name).await
|
||||
.ok_or((StatusCode::NOT_FOUND, format!("index not found: {index_name}")))?;
|
||||
let bucket = req.bucket.unwrap_or(meta.bucket.clone());
|
||||
|
||||
// Pull the Parquet bytes via storaged::ops — same path as the
|
||||
// existing embedding loader uses.
|
||||
let store = state.bucket_registry.get(&bucket)
|
||||
.map_err(|e| (StatusCode::BAD_REQUEST, e))?;
|
||||
let bytes = storaged::ops::get(&store, &meta.storage_key).await
|
||||
.map_err(|e| (StatusCode::NOT_FOUND, format!("read parquet: {e}")))?;
|
||||
|
||||
let lance_store = state.lance.store_for_new(&index_name, &bucket).await
|
||||
.map_err(|e| (StatusCode::BAD_REQUEST, e))?;
|
||||
|
||||
let stats = lance_store.migrate_from_parquet_bytes(&bytes).await
|
||||
.map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, e))?;
|
||||
|
||||
tracing::info!(
|
||||
"lance migrate '{}': {} rows, {}d, {} bytes on disk, {:.2}s",
|
||||
index_name, stats.rows_written, stats.dimensions,
|
||||
stats.disk_bytes, stats.duration_secs,
|
||||
);
|
||||
|
||||
Ok::<_, (StatusCode, String)>(Json(serde_json::json!({
|
||||
"index_name": index_name,
|
||||
"bucket": bucket,
|
||||
"lance_path": lance_store.path(),
|
||||
"stats": stats,
|
||||
})))
|
||||
}
|
||||
|
||||
#[derive(Deserialize)]
|
||||
struct LanceIndexRequest {
|
||||
#[serde(default = "default_partitions")]
|
||||
num_partitions: u32,
|
||||
#[serde(default = "default_bits")]
|
||||
num_bits: u32,
|
||||
#[serde(default = "default_subvectors")]
|
||||
num_sub_vectors: u32,
|
||||
}
|
||||
|
||||
fn default_partitions() -> u32 { 316 } // ≈√100K — sane for the reference dataset
|
||||
fn default_bits() -> u32 { 8 }
|
||||
fn default_subvectors() -> u32 { 48 } // 768/48 = 16 dims per subvector
|
||||
|
||||
/// Build the IVF_PQ index on the Lance dataset.
|
||||
async fn lance_build_index(
|
||||
State(state): State<VectorState>,
|
||||
Path(index_name): Path<String>,
|
||||
Json(req): Json<LanceIndexRequest>,
|
||||
) -> impl IntoResponse {
|
||||
let lance_store = state.lance.store_for(&index_name).await
|
||||
.map_err(|e| (StatusCode::BAD_REQUEST, e))?;
|
||||
match lance_store.build_index(req.num_partitions, req.num_bits, req.num_sub_vectors).await {
|
||||
Ok(stats) => Ok(Json(stats)),
|
||||
Err(e) => Err((StatusCode::INTERNAL_SERVER_ERROR, e)),
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Deserialize)]
|
||||
struct LanceSearchRequest {
|
||||
/// Plain text query — embedded server-side for symmetry with the
|
||||
/// existing /vectors/search path.
|
||||
query: String,
|
||||
#[serde(default = "default_top_k")]
|
||||
top_k: usize,
|
||||
}
|
||||
|
||||
fn default_top_k() -> usize { 5 }
|
||||
|
||||
/// Vector search against a Lance dataset. Embeds the query text via the
|
||||
/// sidecar then calls Lance's nearest-neighbor scanner.
|
||||
async fn lance_search(
|
||||
State(state): State<VectorState>,
|
||||
Path(index_name): Path<String>,
|
||||
Json(req): Json<LanceSearchRequest>,
|
||||
) -> impl IntoResponse {
|
||||
let embed_resp = state.ai_client
|
||||
.embed(EmbedRequest { texts: vec![req.query.clone()], model: None })
|
||||
.await
|
||||
.map_err(|e| (StatusCode::BAD_GATEWAY, format!("embed: {e}")))?;
|
||||
if embed_resp.embeddings.is_empty() {
|
||||
return Err((StatusCode::BAD_GATEWAY, "no embedding returned".into()));
|
||||
}
|
||||
let qv: Vec<f32> = embed_resp.embeddings[0].iter().map(|&x| x as f32).collect();
|
||||
|
||||
let lance_store = state.lance.store_for(&index_name).await
|
||||
.map_err(|e| (StatusCode::BAD_REQUEST, e))?;
|
||||
|
||||
let t0 = std::time::Instant::now();
|
||||
let hits = lance_store.search(&qv, req.top_k).await
|
||||
.map_err(|e| (StatusCode::INTERNAL_SERVER_ERROR, e))?;
|
||||
|
||||
Ok(Json(serde_json::json!({
|
||||
"index_name": index_name,
|
||||
"query": req.query,
|
||||
"method": "lance_ivf_pq",
|
||||
"latency_us": t0.elapsed().as_micros() as u64,
|
||||
"results": hits,
|
||||
})))
|
||||
}
|
||||
|
||||
/// Random-access fetch by doc_id — the O(1) lookup that's basically
|
||||
/// impossible in our Parquet path without scanning the whole file.
|
||||
async fn lance_get_doc(
|
||||
State(state): State<VectorState>,
|
||||
Path((index_name, doc_id)): Path<(String, String)>,
|
||||
) -> impl IntoResponse {
|
||||
let lance_store = state.lance.store_for(&index_name).await
|
||||
.map_err(|e| (StatusCode::BAD_REQUEST, e))?;
|
||||
let t0 = std::time::Instant::now();
|
||||
match lance_store.get_by_doc_id(&doc_id).await {
|
||||
Ok(Some(row)) => Ok(Json(serde_json::json!({
|
||||
"index_name": index_name,
|
||||
"doc_id": doc_id,
|
||||
"latency_us": t0.elapsed().as_micros() as u64,
|
||||
"row": row,
|
||||
}))),
|
||||
Ok(None) => Err((StatusCode::NOT_FOUND, format!("doc_id not found: {doc_id}"))),
|
||||
Err(e) => Err((StatusCode::INTERNAL_SERVER_ERROR, e)),
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Deserialize)]
|
||||
struct LanceAppendRequest {
|
||||
/// Optional source tag — set on every appended row.
|
||||
#[serde(default)]
|
||||
source: Option<String>,
|
||||
rows: Vec<LanceAppendRow>,
|
||||
}
|
||||
|
||||
#[derive(Deserialize)]
|
||||
struct LanceAppendRow {
|
||||
doc_id: String,
|
||||
#[serde(default)]
|
||||
chunk_idx: Option<i32>,
|
||||
chunk_text: String,
|
||||
/// Pre-computed embedding. Caller is responsible for ensuring it
|
||||
/// matches the dataset's dimensions and embedding model.
|
||||
vector: Vec<f32>,
|
||||
}
|
||||
|
||||
async fn lance_append(
|
||||
State(state): State<VectorState>,
|
||||
Path(index_name): Path<String>,
|
||||
Json(req): Json<LanceAppendRequest>,
|
||||
) -> impl IntoResponse {
|
||||
if req.rows.is_empty() {
|
||||
return Err((StatusCode::BAD_REQUEST, "rows array is empty".into()));
|
||||
}
|
||||
let lance_store = state.lance.store_for(&index_name).await
|
||||
.map_err(|e| (StatusCode::BAD_REQUEST, e))?;
|
||||
|
||||
let mut doc_ids = Vec::with_capacity(req.rows.len());
|
||||
let mut chunk_idxs = Vec::with_capacity(req.rows.len());
|
||||
let mut chunk_texts = Vec::with_capacity(req.rows.len());
|
||||
let mut vectors = Vec::with_capacity(req.rows.len());
|
||||
for r in req.rows {
|
||||
doc_ids.push(r.doc_id);
|
||||
chunk_idxs.push(r.chunk_idx.unwrap_or(0));
|
||||
chunk_texts.push(r.chunk_text);
|
||||
vectors.push(r.vector);
|
||||
}
|
||||
|
||||
match lance_store.append(req.source, doc_ids, chunk_idxs, chunk_texts, vectors).await {
|
||||
Ok(stats) => Ok(Json(stats)),
|
||||
Err(e) => Err((StatusCode::INTERNAL_SERVER_ERROR, e)),
|
||||
}
|
||||
}
|
||||
|
||||
async fn lance_stats(
|
||||
State(state): State<VectorState>,
|
||||
Path(index_name): Path<String>,
|
||||
) -> impl IntoResponse {
|
||||
let lance_store = state.lance.store_for(&index_name).await
|
||||
.map_err(|e| (StatusCode::BAD_REQUEST, e))?;
|
||||
match lance_store.stats().await {
|
||||
Ok(s) => Ok(Json(s)),
|
||||
Err(e) => Err((StatusCode::INTERNAL_SERVER_ERROR, e)),
|
||||
}
|
||||
}
|
||||
|
||||
+45
-18
@@ -17,6 +17,9 @@ use std::sync::Arc;
|
||||
use tokio::sync::RwLock;
|
||||
|
||||
use storaged::append_log::AppendLog;
|
||||
use storaged::registry::BucketRegistry;
|
||||
|
||||
use crate::index_registry::IndexRegistry;
|
||||
|
||||
/// HNSW build/search parameters the agent can tune.
|
||||
#[derive(Debug, Clone, Serialize, Deserialize)]
|
||||
@@ -86,18 +89,28 @@ impl Trial {
|
||||
}
|
||||
|
||||
/// Per-index append log, lazy-created on first write.
|
||||
///
|
||||
/// Federation layer 2: the journal resolves each index's bucket from the
|
||||
/// index registry and writes its JSONL batches to THAT bucket, not
|
||||
/// primary. Back-compat is preserved by `IndexMeta::bucket` defaulting
|
||||
/// to "primary" for pre-federation indexes. Indexes the registry has
|
||||
/// never heard of (edge case — trials run before first register) fall
|
||||
/// through to primary as well.
|
||||
#[derive(Clone)]
|
||||
pub struct TrialJournal {
|
||||
store: Arc<dyn ObjectStore>,
|
||||
/// Cache per-index AppendLog instances so the in-memory buffer persists
|
||||
/// across calls.
|
||||
logs: Arc<RwLock<HashMap<String, Arc<AppendLog>>>>,
|
||||
buckets: Arc<BucketRegistry>,
|
||||
index_registry: IndexRegistry,
|
||||
/// Cache per (bucket, index) AppendLog so the in-memory buffer persists
|
||||
/// across calls. Keyed by `(bucket, index_name)` so moving an index
|
||||
/// between buckets is clean — the old journal stays intact.
|
||||
logs: Arc<RwLock<HashMap<(String, String), Arc<AppendLog>>>>,
|
||||
}
|
||||
|
||||
impl TrialJournal {
|
||||
pub fn new(store: Arc<dyn ObjectStore>) -> Self {
|
||||
pub fn new(buckets: Arc<BucketRegistry>, index_registry: IndexRegistry) -> Self {
|
||||
Self {
|
||||
store,
|
||||
buckets,
|
||||
index_registry,
|
||||
logs: Arc::new(RwLock::new(HashMap::new())),
|
||||
}
|
||||
}
|
||||
@@ -106,35 +119,49 @@ impl TrialJournal {
|
||||
format!("_hnsw_trials/{}", index_name)
|
||||
}
|
||||
|
||||
async fn log_for(&self, index_name: &str) -> Arc<AppendLog> {
|
||||
if let Some(log) = self.logs.read().await.get(index_name) {
|
||||
return log.clone();
|
||||
/// Resolve which bucket holds this index's trial artifacts.
|
||||
/// Falls back to primary for indexes without recorded metadata.
|
||||
async fn bucket_for(&self, index_name: &str) -> String {
|
||||
self.index_registry
|
||||
.get(index_name)
|
||||
.await
|
||||
.map(|m| m.bucket)
|
||||
.unwrap_or_else(|| "primary".to_string())
|
||||
}
|
||||
|
||||
async fn log_for(&self, index_name: &str) -> Result<Arc<AppendLog>, String> {
|
||||
let bucket = self.bucket_for(index_name).await;
|
||||
let key = (bucket.clone(), index_name.to_string());
|
||||
|
||||
if let Some(log) = self.logs.read().await.get(&key) {
|
||||
return Ok(log.clone());
|
||||
}
|
||||
let mut guard = self.logs.write().await;
|
||||
if let Some(log) = guard.get(index_name) {
|
||||
return log.clone();
|
||||
if let Some(log) = guard.get(&key) {
|
||||
return Ok(log.clone());
|
||||
}
|
||||
let store = self.buckets.get(&bucket)?;
|
||||
// Trials arrive one at a time during human/agent iteration — a low
|
||||
// threshold gives "hit /trials and see my latest attempt" immediacy
|
||||
// without creating one file per event.
|
||||
let log = Arc::new(
|
||||
AppendLog::new(self.store.clone(), Self::prefix(index_name))
|
||||
AppendLog::new(store, Self::prefix(index_name))
|
||||
.with_flush_threshold(4),
|
||||
);
|
||||
guard.insert(index_name.to_string(), log.clone());
|
||||
log
|
||||
guard.insert(key, log.clone());
|
||||
Ok(log)
|
||||
}
|
||||
|
||||
/// Append a trial record. In-memory buffered; persisted in batches.
|
||||
pub async fn append(&self, trial: &Trial) -> Result<(), String> {
|
||||
let line = serde_json::to_vec(trial).map_err(|e| e.to_string())?;
|
||||
let log = self.log_for(&trial.index_name).await;
|
||||
let log = self.log_for(&trial.index_name).await?;
|
||||
log.append(line).await
|
||||
}
|
||||
|
||||
/// Read all trials for an index (flushed batches + unflushed buffer).
|
||||
pub async fn list(&self, index_name: &str) -> Result<Vec<Trial>, String> {
|
||||
let log = self.log_for(index_name).await;
|
||||
let log = self.log_for(index_name).await?;
|
||||
let lines = log.read_all().await?;
|
||||
let mut trials = Vec::with_capacity(lines.len());
|
||||
for line in lines {
|
||||
@@ -149,13 +176,13 @@ impl TrialJournal {
|
||||
/// Explicit flush for callers that want write-through semantics
|
||||
/// (e.g. an agent that wants to commit a trial before querying stats).
|
||||
pub async fn flush(&self, index_name: &str) -> Result<(), String> {
|
||||
let log = self.log_for(index_name).await;
|
||||
let log = self.log_for(index_name).await?;
|
||||
log.flush().await
|
||||
}
|
||||
|
||||
/// Compact all batch files for an index into one.
|
||||
pub async fn compact(&self, index_name: &str) -> Result<storaged::append_log::CompactStats, String> {
|
||||
let log = self.log_for(index_name).await;
|
||||
let log = self.log_for(index_name).await?;
|
||||
log.compact().await
|
||||
}
|
||||
|
||||
|
||||
Reference in New Issue
Block a user