1dca9d7d05
Phase 2 increment 5: - FaceIndexingService: a FileLifecycleHook that, on image upload, detects + embeds faces in a background task and stores them. Dedup-aware (clones an identical blob's faces instead of re-running inference), reindexes on overwrite, and relies on the DB cascade for deletes. Completely inert when no model is ready. - DI: registers the hook in the FileLifecycleService chain and exposes PeopleService in AppState — both gated on OXICLOUD_ENABLE_FACES, both using the default no-op analyzer until the operator wires a real ONNX model. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01JW6ghFMDtnRYuYNzZhb47M
192 lines
6.1 KiB
Rust
192 lines
6.1 KiB
Rust
//! Face indexing as a `FileLifecycleHook`.
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//!
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//! On image upload it detects + embeds faces (off the request path, in a
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//! background task) and stores them. It mirrors `MediaMetadataService`: reads
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//! the blob from the local `.blobs` tree, is dedup-aware (identical uploads
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//! clone an existing file's faces instead of re-running inference), and is
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//! completely inert when no model is configured (`FaceAnalyzerPort::is_ready()
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//! == false`) — so the feature compiles and runs with the default no-op
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//! analyzer until the operator wires a real ONNX model.
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use std::path::{Path, PathBuf};
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use std::sync::Arc;
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use chrono::Utc;
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use sqlx::PgPool;
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use uuid::Uuid;
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use crate::application::ports::face_ports::{FaceAnalyzerPort, FaceRepository};
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use crate::application::ports::file_lifecycle::FileLifecycleHook;
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use crate::common::errors::DomainError;
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use crate::domain::entities::face::Face;
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use crate::infrastructure::repositories::pg::FacePgRepository;
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/// Minimum detector confidence for a face to be stored.
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const MIN_DET_SCORE: f32 = 0.6;
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fn is_image(content_type: &str) -> bool {
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content_type.starts_with("image/")
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}
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pub struct FaceIndexingService {
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pool: Arc<PgPool>,
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repo: Arc<FacePgRepository>,
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analyzer: Arc<dyn FaceAnalyzerPort>,
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blob_root: PathBuf,
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}
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impl FaceIndexingService {
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pub fn new(pool: Arc<PgPool>, blob_root: PathBuf, analyzer: Arc<dyn FaceAnalyzerPort>) -> Self {
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let repo = Arc::new(FacePgRepository::new(pool.clone()));
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Self {
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pool,
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repo,
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analyzer,
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blob_root,
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}
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}
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/// Local path of a blob: `.blobs/{prefix}/{hash}.blob`.
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fn blob_path(&self, hash: &str) -> PathBuf {
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let prefix = if hash.len() >= 2 { &hash[0..2] } else { hash };
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self.blob_root.join(prefix).join(format!("{hash}.blob"))
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}
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/// Spawn a background indexing task. `reuse_dedup` clones faces from an
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/// existing file with the same blob hash instead of re-running inference;
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/// `delete_first` clears prior faces (used on overwrite).
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fn spawn_index(&self, file_id: Uuid, blob_hash: String, reuse_dedup: bool, delete_first: bool) {
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let pool = self.pool.clone();
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let repo = self.repo.clone();
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let analyzer = self.analyzer.clone();
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let blob_path = self.blob_path(&blob_hash);
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tokio::spawn(async move {
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if delete_first {
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let _ = repo.delete_faces_for_file(file_id).await;
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}
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if let Err(e) = index_file(
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&pool,
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&repo,
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analyzer.as_ref(),
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file_id,
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&blob_path,
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&blob_hash,
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reuse_dedup,
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)
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.await
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{
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tracing::warn!(target: "oxicloud::faces", "face indexing failed for {file_id}: {e}");
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}
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});
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}
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}
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impl FileLifecycleHook for FaceIndexingService {
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fn on_file_created(
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&self,
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file_id: &str,
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blob_hash: &str,
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content_type: &str,
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is_new_blob: bool,
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) {
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if !is_image(content_type) || !self.analyzer.is_ready() {
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return;
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}
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if let Ok(fid) = file_id.parse::<Uuid>() {
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// Dedup hit (blob already existed) → clone an existing file's faces.
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self.spawn_index(fid, blob_hash.to_string(), !is_new_blob, false);
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}
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}
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fn on_file_copied(
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&self,
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file_id: &str,
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blob_hash: &str,
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content_type: &str,
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_source_file_id: &str,
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) {
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if !is_image(content_type) || !self.analyzer.is_ready() {
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return;
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}
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if let Ok(fid) = file_id.parse::<Uuid>() {
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self.spawn_index(fid, blob_hash.to_string(), true, false);
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}
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}
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fn on_file_updated(&self, file_id: &str, blob_hash: &str, content_type: &str) {
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if !is_image(content_type) || !self.analyzer.is_ready() {
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return;
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}
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if let Ok(fid) = file_id.parse::<Uuid>() {
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self.spawn_index(fid, blob_hash.to_string(), false, true);
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}
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}
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fn on_file_deleted(&self, _file_id: &str) {
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// faces.faces.file_id has ON DELETE CASCADE — the DB cleans up.
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}
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}
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async fn lookup_user(pool: &PgPool, file_id: Uuid) -> Result<Uuid, DomainError> {
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let row: (Uuid,) = sqlx::query_as("SELECT user_id FROM storage.files WHERE id = $1")
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.bind(file_id)
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.fetch_one(pool)
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.await
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.map_err(|e| DomainError::internal_error("Faces", format!("lookup user: {e}")))?;
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Ok(row.0)
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}
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async fn index_file(
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pool: &PgPool,
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repo: &FacePgRepository,
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analyzer: &dyn FaceAnalyzerPort,
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file_id: Uuid,
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blob_path: &Path,
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blob_hash: &str,
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reuse_dedup: bool,
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) -> Result<(), DomainError> {
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let user_id = lookup_user(pool, file_id).await?;
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// Dedup-aware fast path: reuse faces already computed for an identical blob.
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if reuse_dedup {
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let peers = repo.faces_for_blob(user_id, blob_hash).await?;
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let cloned: Vec<Face> = peers
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.into_iter()
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.filter(|f| f.file_id != file_id)
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.map(|f| Face {
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id: Uuid::new_v4(),
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file_id,
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..f
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})
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.collect();
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if !cloned.is_empty() {
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repo.save_faces(&cloned).await?;
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return Ok(());
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}
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// No peer found — fall through and analyze.
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}
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let bytes = tokio::fs::read(blob_path)
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.await
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.map_err(|e| DomainError::internal_error("Faces", format!("read blob: {e}")))?;
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let detected = analyzer.analyze(&bytes).await?;
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let faces: Vec<Face> = detected
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.into_iter()
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.filter(|d| d.det_score >= MIN_DET_SCORE)
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.map(|d| Face {
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id: Uuid::new_v4(),
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file_id,
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user_id,
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person_id: None,
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bbox: d.bbox,
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det_score: d.det_score,
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quality: d.quality,
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embedding: d.embedding,
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blob_hash: Some(blob_hash.to_string()),
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created_at: Utc::now(),
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})
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.collect();
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repo.save_faces(&faces).await
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}
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