//! Face-detection pass for the file watcher.
//!
//! `process_new_files` calls [`run_face_detection_pass`] after the EXIF
//! registration loop. We walk the candidates (images, not yet face-scanned,
//! not excluded by EXCLUDED_DIRS), fan out parallel detect calls to Apollo,
//! and persist the results — detected faces, `no_faces` markers when Apollo
//! found nothing, `failed` markers on permanent decode errors, no marker on
//! transient failures so the next scan retries.
//!
//! The watcher runs in a plain `std::thread`, so we build a short-lived
//! tokio runtime per pass and `block_on` a join of K detect futures. K is
//! configurable via `FACE_DETECT_CONCURRENCY` (default 8). Apollo's
//! threadpool is bounded to 1–2 workers anyway, so the runs queue
//! server-side; the client-side fan-out is purely about overlapping IO
//! (file read + JSON encode) with someone else's inference.

use crate::ai::face_client::{DetectMeta, FaceClient, FaceDetectError};
use crate::exif;
use crate::faces::{self, FaceDao, InsertFaceDetectionInput};
use crate::file_types;
use crate::libraries::Library;
use crate::memories::PathExcluder;
use crate::tags::TagDao;
use log::{debug, info, warn};
use std::path::Path;
use std::sync::{Arc, Mutex};
use tokio::sync::Semaphore;

/// One file the watcher would like to face-scan. Built by the caller from
/// the EXIF batch (we need `content_hash` to key everything against).
#[derive(Debug, Clone)]
pub struct FaceCandidate {
    pub rel_path: String,
    pub content_hash: String,
}

/// Synchronous entry point. Returns once every candidate has been
/// processed (or definitively skipped). When `face_client.is_enabled()`
/// is false this is a no-op so the watcher can call unconditionally.
pub fn run_face_detection_pass(
    library: &Library,
    excluded_dirs: &[String],
    face_client: &FaceClient,
    face_dao: Arc<Mutex<Box<dyn FaceDao>>>,
    tag_dao: Arc<Mutex<Box<dyn TagDao>>>,
    candidates: Vec<FaceCandidate>,
) {
    if !face_client.is_enabled() {
        return;
    }
    if candidates.is_empty() {
        return;
    }

    let base = Path::new(&library.root_path);
    let filtered = filter_excluded(base, excluded_dirs, candidates, Some(&library.name));
    if filtered.is_empty() {
        return;
    }

    let concurrency: usize = std::env::var("FACE_DETECT_CONCURRENCY")
        .ok()
        .and_then(|s| s.parse().ok())
        .filter(|n: &usize| *n > 0)
        .unwrap_or(8);

    info!(
        "face_watch: running detection on {} candidates (library '{}', concurrency {})",
        filtered.len(),
        library.name,
        concurrency
    );

    // Per-pass tokio runtime. The watcher thread isn't in any pre-existing
    // async context — building one here keeps the rest of the watcher
    // sync-only. Worker count is small; the parallelism we care about is
    // task-level (semaphore) not thread-level.
    let rt = match tokio::runtime::Builder::new_multi_thread()
        .worker_threads(2)
        .enable_all()
        .build()
    {
        Ok(rt) => rt,
        Err(e) => {
            warn!("face_watch: failed to build tokio runtime: {e}");
            return;
        }
    };

    let library_id = library.id;
    let library_root = library.root_path.clone();
    rt.block_on(async move {
        let sem = Arc::new(Semaphore::new(concurrency));
        let mut handles = Vec::with_capacity(filtered.len());
        for cand in filtered {
            let permit_sem = sem.clone();
            let face_client = face_client.clone();
            let face_dao = face_dao.clone();
            let tag_dao = tag_dao.clone();
            let library_root = library_root.clone();
            handles.push(tokio::spawn(async move {
                // acquire_owned would let us drop the permit explicitly
                // before await points; for a one-shot call into Apollo
                // the simpler bounded acquire is enough.
                let _permit = permit_sem.acquire().await.expect("face semaphore");
                process_one(
                    library_id,
                    &library_root,
                    cand,
                    &face_client,
                    face_dao,
                    tag_dao,
                )
                .await;
            }));
        }
        for h in handles {
            // join; per-task panics are logged inside process_one before
            // they reach here, so we don't propagate.
            let _ = h.await;
        }
    });
}

async fn process_one(
    library_id: i32,
    library_root: &str,
    cand: FaceCandidate,
    face_client: &FaceClient,
    face_dao: Arc<Mutex<Box<dyn FaceDao>>>,
    tag_dao: Arc<Mutex<Box<dyn TagDao>>>,
) {
    let abs = Path::new(library_root).join(&cand.rel_path);
    // Read the bytes off disk in a blocking-friendly task. Filesystem IO
    // is sync but cheap; a small spawn_blocking would be overkill.
    let bytes = match read_image_bytes_for_detect(&abs) {
        Ok(b) => b,
        Err(e) => {
            // Don't mark — file may have been moved/renamed mid-scan; let
            // the next pass try again. Future-bug check: a permanently
            // unreadable file would loop forever; we accept that for v1
            // because process_new_files already prunes vanished rows on
            // full scans.
            warn!(
                "face_watch: read failed for {} ({}): {}",
                cand.rel_path, library_id, e
            );
            return;
        }
    };

    let meta = DetectMeta {
        content_hash: cand.content_hash.clone(),
        library_id,
        rel_path: cand.rel_path.clone(),
        orientation: None,
        model_version: None,
    };
    let ctx = opentelemetry::Context::current();

    match face_client.detect(bytes, meta).await {
        Ok(resp) => {
            // Stage 1: persist detections, holding the dao lock only
            // across synchronous DB writes.
            let mut stored_for_autobind: Vec<(i32, Vec<f32>)> = Vec::new();
            {
                let mut dao = face_dao.lock().expect("face dao");
                if resp.faces.is_empty() {
                    if let Err(e) = dao.mark_status(
                        &ctx,
                        library_id,
                        &cand.content_hash,
                        &cand.rel_path,
                        "no_faces",
                        &resp.model_version,
                    ) {
                        warn!(
                            "face_watch: mark no_faces failed for {}: {:?}",
                            cand.rel_path, e
                        );
                    }
                    debug!(
                        "face_watch: {} → no faces (model {})",
                        cand.rel_path, resp.model_version
                    );
                } else {
                    let face_count = resp.faces.len();
                    for face in &resp.faces {
                        let emb = match face.decode_embedding() {
                            Ok(b) => b,
                            Err(e) => {
                                warn!("face_watch: bad embedding for {}: {:?}", cand.rel_path, e);
                                continue;
                            }
                        };
                        // Decode the f32 vector once for auto-bind comparison.
                        let emb_floats = faces::decode_embedding_bytes(&emb);
                        match dao.store_detection(
                            &ctx,
                            InsertFaceDetectionInput {
                                library_id,
                                content_hash: cand.content_hash.clone(),
                                rel_path: cand.rel_path.clone(),
                                bbox: Some((face.bbox.x, face.bbox.y, face.bbox.w, face.bbox.h)),
                                embedding: Some(emb),
                                confidence: Some(face.confidence),
                                source: "auto".to_string(),
                                person_id: None,
                                status: "detected".to_string(),
                                model_version: resp.model_version.clone(),
                            },
                        ) {
                            Ok(row) => {
                                if let Some(floats) = emb_floats {
                                    stored_for_autobind.push((row.id, floats));
                                }
                            }
                            Err(e) => warn!(
                                "face_watch: store_detection failed for {}: {:?}",
                                cand.rel_path, e
                            ),
                        }
                    }
                    info!(
                        "face_watch: {} → {} face(s) ({}ms, {})",
                        cand.rel_path, face_count, resp.duration_ms, resp.model_version
                    );
                }
            }

            // Stage 2: auto-bind newly-stored faces against same-named
            // people-tags. Done outside the dao lock so the lookups don't
            // serialize with concurrent detect tasks.
            if !stored_for_autobind.is_empty() {
                try_auto_bind(
                    &ctx,
                    &cand.rel_path,
                    &resp.model_version,
                    stored_for_autobind,
                    &tag_dao,
                    &face_dao,
                );
            }
        }
        Err(FaceDetectError::Permanent(e)) => {
            warn!(
                "face_watch: permanent failure on {}: {} — marking failed",
                cand.rel_path, e
            );
            let mut dao = face_dao.lock().expect("face dao");
            // model_version is best-effort here — the engine that rejected
            // the bytes may not have echoed one. Empty string is fine; this
            // row is purely a "don't retry" sentinel.
            if let Err(e) = dao.mark_status(
                &ctx,
                library_id,
                &cand.content_hash,
                &cand.rel_path,
                "failed",
                "",
            ) {
                warn!(
                    "face_watch: mark failed errored for {}: {:?}",
                    cand.rel_path, e
                );
            }
        }
        Err(FaceDetectError::Transient(e)) => {
            // Don't mark anything; next scan tick retries naturally.
            // Demoted to debug because OOM and engine-not-ready are noisy
            // and self-resolving.
            debug!(
                "face_watch: transient on {}: {} (will retry next pass)",
                cand.rel_path, e
            );
        }
        Err(FaceDetectError::Disabled) => {
            // Caller already checked is_enabled(); this branch is defensive.
        }
    }
}

/// Auto-bind newly-detected faces to a same-named person, when a tag on the
/// photo unambiguously identifies one. Driven by `FACE_AUTOBIND_MIN_COS`
/// (default 0.4): the new face's embedding must reach this cosine
/// similarity against the L2-normalized mean of the person's existing
/// faces. The first face for a person binds unconditionally — there's
/// nothing to compare against, and the alternative ("never bind without
/// a reference") would mean bootstrap never kicks off.
///
/// Multi-match (the photo carries tags for two different known persons)
/// is intentionally a no-op — we can't tell which face is which without
/// additional matching. Those faces stay unassigned for the cluster
/// suggester (Phase 6) to handle.
fn try_auto_bind(
    ctx: &opentelemetry::Context,
    rel_path: &str,
    model_version: &str,
    new_faces: Vec<(i32, Vec<f32>)>, // (face_id, decoded embedding)
    tag_dao: &Arc<Mutex<Box<dyn TagDao>>>,
    face_dao: &Arc<Mutex<Box<dyn FaceDao>>>,
) {
    // 1. Pull the photo's tags.
    let tag_names: Vec<String> = {
        let mut td = tag_dao.lock().expect("tag dao");
        match td.get_tags_for_path(ctx, rel_path) {
            Ok(tags) => tags.into_iter().map(|t| t.name).collect(),
            Err(e) => {
                warn!(
                    "face_watch: get_tags_for_path failed for {}: {:?}",
                    rel_path, e
                );
                return;
            }
        }
    };
    if tag_names.is_empty() {
        return;
    }

    // 2. Find tags that map to existing persons (case-insensitive).
    let person_for_tag: std::collections::HashMap<String, i32> = {
        let mut fd = face_dao.lock().expect("face dao");
        match fd.find_persons_by_names_ci(ctx, &tag_names) {
            Ok(m) => m,
            Err(e) => {
                warn!(
                    "face_watch: find_persons_by_names_ci failed for {}: {:?}",
                    rel_path, e
                );
                return;
            }
        }
    };

    // 3. Multi-match: ambiguous, skip. Single match: candidate person.
    let unique_person_ids: std::collections::HashSet<i32> =
        person_for_tag.values().copied().collect();
    if unique_person_ids.len() != 1 {
        if !unique_person_ids.is_empty() {
            debug!(
                "face_watch: {} carries tags for {} different persons; skipping auto-bind",
                rel_path,
                unique_person_ids.len()
            );
        }
        return;
    }
    let person_id = *unique_person_ids.iter().next().expect("nonempty set");

    let threshold: f32 = std::env::var("FACE_AUTOBIND_MIN_COS")
        .ok()
        .and_then(|s| s.parse().ok())
        .filter(|t: &f32| *t >= 0.0 && *t <= 1.0)
        .unwrap_or(0.4);

    // 4. Reference embedding (if any) under the same model_version.
    let reference: Option<Vec<f32>> = {
        let mut fd = face_dao.lock().expect("face dao");
        match fd.person_reference_embedding(ctx, person_id, model_version) {
            Ok(r) => r,
            Err(e) => {
                warn!(
                    "face_watch: person_reference_embedding failed for person {}: {:?}",
                    person_id, e
                );
                return;
            }
        }
    };

    // 5. Bind each new face that meets the criterion. Hold the lock once
    // for the whole batch; assign_face_to_person uses its own short
    // transaction internally.
    let mut fd = face_dao.lock().expect("face dao");
    for (face_id, emb) in new_faces {
        let bind = match &reference {
            None => {
                // Person has no faces yet — first one wins so bootstrap
                // can ever produce a usable reference. After this row
                // commits, future faces evaluate against it.
                debug!(
                    "face_watch: auto-binding first face {} → person {} (no reference yet)",
                    face_id, person_id
                );
                true
            }
            Some(ref_vec) => {
                let sim = faces::cosine_similarity(&emb, ref_vec);
                if sim >= threshold {
                    debug!(
                        "face_watch: auto-binding face {} → person {} (cos={:.3} ≥ {:.3})",
                        face_id, person_id, sim, threshold
                    );
                    true
                } else {
                    debug!(
                        "face_watch: leaving face {} unassigned (cos={:.3} < {:.3} for person {})",
                        face_id, sim, threshold, person_id
                    );
                    false
                }
            }
        };
        if bind && let Err(e) = fd.assign_face_to_person(ctx, face_id, person_id) {
            warn!(
                "face_watch: assign_face_to_person failed (face={}, person={}): {:?}",
                face_id, person_id, e
            );
        }
    }
}

/// Drop candidates whose path matches the watcher's `EXCLUDED_DIRS` rules.
/// Pulled out for unit testing — the same `PathExcluder` /memories uses,
/// just applied at the face-detect candidate set instead of the memories
/// listing. Skip @eaDir / .thumbnails / user-defined paths before we burn
/// a detect call (and Apollo's GPU memory) on junk.
pub(crate) fn filter_excluded(
    base: &Path,
    excluded_dirs: &[String],
    candidates: Vec<FaceCandidate>,
    library_name: Option<&str>,
) -> Vec<FaceCandidate> {
    if excluded_dirs.is_empty() {
        return candidates;
    }
    let excluder = PathExcluder::new(base, excluded_dirs);
    candidates
        .into_iter()
        .filter(|c| {
            let abs = base.join(&c.rel_path);
            if excluder.is_excluded(&abs) {
                debug!(
                    "face_watch: skipping excluded path {} (library {})",
                    c.rel_path,
                    library_name.unwrap_or("<unknown>")
                );
                return false;
            }
            true
        })
        .collect()
}

/// Read image bytes for face detection. Insightface (via opencv) can't
/// decode RAW or HEIC — for those we extract the embedded JPEG preview
/// the way the thumbnail pipeline does. Plain JPEG/PNG/WebP/etc. go
/// through a direct read.
pub(crate) fn read_image_bytes_for_detect(path: &Path) -> std::io::Result<Vec<u8>> {
    if file_types::needs_ffmpeg_thumbnail(path)
        && let Some(preview) = exif::extract_embedded_jpeg_preview(path)
    {
        return Ok(preview);
    }
    // Plain read for everything else. RAW/HEIC files without an embedded
    // preview fall through here too; Apollo will then 422 and the caller
    // marks the row failed. That's fine; we tried.
    std::fs::read(path)
}

#[cfg(test)]
mod tests {
    use super::*;
    use std::fs;

    fn cand(rel_path: &str) -> FaceCandidate {
        FaceCandidate {
            rel_path: rel_path.to_string(),
            content_hash: format!("hash-{rel_path}"),
        }
    }

    #[test]
    fn filter_excluded_pattern_drops_dir_components() {
        // A pattern matches a path *component* under base, not a substring.
        // Phase 3 needs this for @eaDir / .thumbnails skipping.
        let tmp = tempfile::tempdir().unwrap();
        let base = tmp.path();
        let candidates = vec![
            cand("photos/a.jpg"),                  // keep
            cand("photos/@eaDir/SYNOPHOTO_THUMB"), // drop (component match)
            cand("photos/eaDir-not-a-thing.jpg"),  // keep (substring, not component)
        ];
        let kept = filter_excluded(base, &["@eaDir".to_string()], candidates, Some("test"));
        let kept_paths: Vec<_> = kept.iter().map(|c| c.rel_path.as_str()).collect();
        assert_eq!(
            kept_paths,
            vec!["photos/a.jpg", "photos/eaDir-not-a-thing.jpg"]
        );
    }

    #[test]
    fn filter_excluded_absolute_dir_drops_subtree() {
        // Absolute (under-base) entries drop the whole subtree.
        let tmp = tempfile::tempdir().unwrap();
        let base = tmp.path();
        let candidates = vec![
            cand("public/a.jpg"),
            cand("private/a.jpg"),
            cand("private/sub/b.jpg"),
        ];
        let kept = filter_excluded(base, &["/private".to_string()], candidates, None);
        let kept_paths: Vec<_> = kept.iter().map(|c| c.rel_path.as_str()).collect();
        assert_eq!(kept_paths, vec!["public/a.jpg"]);
    }

    #[test]
    fn filter_excluded_empty_rules_passes_all() {
        // Skip the PathExcluder build entirely on the common path where
        // EXCLUDED_DIRS is unset — saves an allocation per pass.
        let tmp = tempfile::tempdir().unwrap();
        let base = tmp.path();
        let candidates = vec![cand("a.jpg"), cand("b.jpg")];
        let kept = filter_excluded(base, &[], candidates, None);
        assert_eq!(kept.len(), 2);
    }

    #[test]
    fn read_bytes_passes_through_for_jpeg() {
        // JPEG goes through plain read — we DON'T want to lose orientation
        // metadata or re-encode here; insightface's exif_transpose handles
        // orientation on its end.
        let tmp = tempfile::tempdir().unwrap();
        let path = tmp.path().join("test.jpg");
        let mut buf = Vec::new();
        // Tiny 4x4 grey JPEG — encoded by image crate so we know it round-trips.
        let img = image::DynamicImage::ImageRgb8(image::RgbImage::from_pixel(
            4,
            4,
            image::Rgb([128, 128, 128]),
        ));
        img.write_to(
            &mut std::io::Cursor::new(&mut buf),
            image::ImageFormat::Jpeg,
        )
        .unwrap();
        fs::write(&path, &buf).unwrap();

        let read = read_image_bytes_for_detect(&path).expect("read jpeg");
        assert_eq!(read, buf, "JPEG bytes must pass through verbatim");
    }

    #[test]
    fn read_bytes_falls_back_when_raw_has_no_preview() {
        // A `.nef` file with non-RAW bytes won't have an embedded preview —
        // the helper falls through to plain read rather than refusing. This
        // matches the docstring contract; Apollo will then 422 and we'll
        // mark the row as failed.
        let tmp = tempfile::tempdir().unwrap();
        let path = tmp.path().join("not_really.nef");
        fs::write(&path, b"definitely-not-a-raw-file").unwrap();

        let read = read_image_bytes_for_detect(&path).expect("fallback read");
        assert_eq!(read, b"definitely-not-a-raw-file");
    }
}