| 1 |
|
| 2 |
|
| 3 |
|
| 4 |
use super::{ |
| 5 |
BackendError, BackendResult, ClassifierBackend, DirectBackend, NodeId, Path, SearchBackend, |
| 6 |
SearchCommand, SearchFilter, SimilarityBackend, TrainedHeadInfo, VfsId, VfsNodeWithAnalysis, |
| 7 |
WaveformData, instrument, search, |
| 8 |
}; |
| 9 |
|
| 10 |
impl SearchBackend for DirectBackend { |
| 11 |
|
| 12 |
|
| 13 |
fn search_in_folder( |
| 14 |
&self, |
| 15 |
filter: &SearchFilter, |
| 16 |
vfs_id: VfsId, |
| 17 |
parent_id: Option<NodeId>, |
| 18 |
) -> BackendResult<Vec<VfsNodeWithAnalysis>> { |
| 19 |
let db = self.db.lock(); |
| 20 |
Ok(search::search_in_folder(&db, filter, vfs_id, parent_id)?) |
| 21 |
} |
| 22 |
|
| 23 |
fn search_global(&self, filter: &SearchFilter) -> BackendResult<Vec<VfsNodeWithAnalysis>> { |
| 24 |
let db = self.db.lock(); |
| 25 |
Ok(search::search_global(&db, filter)?) |
| 26 |
} |
| 27 |
} |
| 28 |
|
| 29 |
impl ClassifierBackend for DirectBackend { |
| 30 |
fn ml_auto_apply_all(&self, k: usize) -> BackendResult<usize> { |
| 31 |
use audiofiles_core::analysis::{exemplar, trained_head}; |
| 32 |
let db = self.db.lock(); |
| 33 |
|
| 34 |
|
| 35 |
|
| 36 |
if let Some(head) = trained_head::load(&db)? { |
| 37 |
Ok(trained_head::auto_apply_library(&db, &head)?) |
| 38 |
} else { |
| 39 |
Ok(exemplar::auto_apply_library(&db, k)?) |
| 40 |
} |
| 41 |
} |
| 42 |
|
| 43 |
fn train_classifier_head(&self) -> BackendResult<Option<TrainedHeadInfo>> { |
| 44 |
let db = self.db.lock(); |
| 45 |
Ok( |
| 46 |
audiofiles_core::analysis::trained_head::train_and_save(&db)?.map(|h| { |
| 47 |
TrainedHeadInfo { |
| 48 |
class_count: h.classes.len(), |
| 49 |
exemplar_count: h.exemplar_count, |
| 50 |
trained_at: h.trained_at, |
| 51 |
} |
| 52 |
}), |
| 53 |
) |
| 54 |
} |
| 55 |
|
| 56 |
fn classifier_head_info(&self) -> BackendResult<Option<TrainedHeadInfo>> { |
| 57 |
let db = self.db.lock(); |
| 58 |
Ok( |
| 59 |
audiofiles_core::analysis::trained_head::load(&db)?.map(|h| TrainedHeadInfo { |
| 60 |
class_count: h.classes.len(), |
| 61 |
exemplar_count: h.exemplar_count, |
| 62 |
trained_at: h.trained_at, |
| 63 |
}), |
| 64 |
) |
| 65 |
} |
| 66 |
|
| 67 |
fn clear_classifier_head(&self) -> BackendResult<()> { |
| 68 |
let db = self.db.lock(); |
| 69 |
Ok(audiofiles_core::analysis::trained_head::clear(&db)?) |
| 70 |
} |
| 71 |
|
| 72 |
fn classifier_head_readiness(&self) -> BackendResult<(usize, bool)> { |
| 73 |
use audiofiles_core::analysis::trained_head; |
| 74 |
let db = self.db.lock(); |
| 75 |
let n = trained_head::labeled_exemplar_count(&db)?; |
| 76 |
Ok((n, n >= trained_head::RECOMMENDED_MIN_EXEMPLARS)) |
| 77 |
} |
| 78 |
|
| 79 |
fn start_classifier_job(&self, job: crate::backend::ClassifierJob) -> BackendResult<()> { |
| 80 |
let db_path = self.data_dir.join("audiofiles.db"); |
| 81 |
|
| 82 |
|
| 83 |
|
| 84 |
|
| 85 |
|
| 86 |
if let Some(old) = self.classifier_worker.lock().take() { |
| 87 |
let _ = |
| 88 |
audiofiles_core::worker_runtime::spawn_detached("classifier-reaper", move || { |
| 89 |
drop(old); |
| 90 |
}); |
| 91 |
} |
| 92 |
let handle = crate::classifier_worker::spawn_classifier_job(db_path, job) |
| 93 |
.map_err(|e| BackendError::Other(format!("failed to spawn classifier worker: {e}")))?; |
| 94 |
*self.classifier_worker.lock() = Some(handle); |
| 95 |
Ok(()) |
| 96 |
} |
| 97 |
|
| 98 |
fn export_afcl( |
| 99 |
&self, |
| 100 |
path: &Path, |
| 101 |
opts: &audiofiles_core::analysis::afcl::ExportOptions, |
| 102 |
) -> BackendResult<()> { |
| 103 |
let db = self.db.lock(); |
| 104 |
Ok(audiofiles_core::analysis::afcl::export_to_path( |
| 105 |
&db, path, opts, |
| 106 |
)?) |
| 107 |
} |
| 108 |
|
| 109 |
fn import_afcl( |
| 110 |
&self, |
| 111 |
path: &Path, |
| 112 |
) -> BackendResult<audiofiles_core::analysis::afcl::ImportSummary> { |
| 113 |
let db = self.db.lock(); |
| 114 |
Ok(audiofiles_core::analysis::afcl::import_from_path( |
| 115 |
&db, path, |
| 116 |
)?) |
| 117 |
} |
| 118 |
|
| 119 |
fn list_classifier_layers( |
| 120 |
&self, |
| 121 |
) -> BackendResult<Vec<audiofiles_core::analysis::afcl::ClassifierLayer>> { |
| 122 |
let db = self.db.lock(); |
| 123 |
Ok(audiofiles_core::analysis::afcl::list_layers(&db)?) |
| 124 |
} |
| 125 |
|
| 126 |
fn remove_classifier_layer(&self, id: &str) -> BackendResult<()> { |
| 127 |
let db = self.db.lock(); |
| 128 |
Ok(audiofiles_core::analysis::afcl::remove_layer(&db, id)?) |
| 129 |
} |
| 130 |
|
| 131 |
fn set_classifier_layer_enabled(&self, id: &str, enabled: bool) -> BackendResult<()> { |
| 132 |
let db = self.db.lock(); |
| 133 |
Ok(audiofiles_core::analysis::afcl::set_layer_enabled( |
| 134 |
&db, id, enabled, |
| 135 |
)?) |
| 136 |
} |
| 137 |
|
| 138 |
fn set_classifier_layer_weight(&self, id: &str, weight: f64) -> BackendResult<()> { |
| 139 |
let db = self.db.lock(); |
| 140 |
Ok(audiofiles_core::analysis::afcl::set_layer_weight( |
| 141 |
&db, id, weight, |
| 142 |
)?) |
| 143 |
} |
| 144 |
|
| 145 |
fn accept_ml_tag(&self, hash: &str, tag: &str) -> BackendResult<()> { |
| 146 |
let db = self.db.lock(); |
| 147 |
db.transaction_core(|tx| { |
| 148 |
audiofiles_core::rules::apply_tag_sourced(&db, tx, hash, tag, "ml").map(|_| ()) |
| 149 |
})?; |
| 150 |
Ok(()) |
| 151 |
} |
| 152 |
|
| 153 |
fn get_tag_policy( |
| 154 |
&self, |
| 155 |
tag: &str, |
| 156 |
) -> BackendResult<audiofiles_core::analysis::exemplar::TagPolicy> { |
| 157 |
let db = self.db.lock(); |
| 158 |
Ok(audiofiles_core::analysis::exemplar::get_policy(&db, tag)?) |
| 159 |
} |
| 160 |
|
| 161 |
#[instrument(skip(self))] |
| 162 |
fn set_tag_policy(&self, tag: &str, review: f64, auto: f64) -> BackendResult<()> { |
| 163 |
let db = self.db.lock(); |
| 164 |
Ok(audiofiles_core::analysis::exemplar::set_policy( |
| 165 |
&db, tag, review, auto, |
| 166 |
)?) |
| 167 |
} |
| 168 |
|
| 169 |
fn list_tag_policies( |
| 170 |
&self, |
| 171 |
) -> BackendResult<Vec<(String, audiofiles_core::analysis::exemplar::TagPolicy)>> { |
| 172 |
let db = self.db.lock(); |
| 173 |
Ok(audiofiles_core::analysis::exemplar::list_policies(&db)?) |
| 174 |
} |
| 175 |
|
| 176 |
fn cluster_library( |
| 177 |
&self, |
| 178 |
k: usize, |
| 179 |
) -> BackendResult<Vec<audiofiles_core::analysis::cluster::Cluster>> { |
| 180 |
let db = self.db.lock(); |
| 181 |
Ok(audiofiles_core::analysis::cluster::cluster_library(&db, k, 50)?.clusters) |
| 182 |
} |
| 183 |
|
| 184 |
fn apply_cluster_tag(&self, members: &[String], tag: &str) -> BackendResult<usize> { |
| 185 |
let db = self.db.lock(); |
| 186 |
Ok(audiofiles_core::analysis::cluster::apply_cluster_tag( |
| 187 |
&db, members, tag, |
| 188 |
)?) |
| 189 |
} |
| 190 |
|
| 191 |
fn harvest_folder_labels(&self) -> BackendResult<Vec<audiofiles_core::harvest::FolderLabel>> { |
| 192 |
let db = self.db.lock(); |
| 193 |
Ok(audiofiles_core::harvest::harvest_folder_labels(&db)?) |
| 194 |
} |
| 195 |
|
| 196 |
fn apply_harvested_tag(&self, hashes: &[String], tag: &str) -> BackendResult<usize> { |
| 197 |
let db = self.db.lock(); |
| 198 |
Ok(audiofiles_core::harvest::apply_harvested_tag( |
| 199 |
&db, hashes, tag, |
| 200 |
)?) |
| 201 |
} |
| 202 |
|
| 203 |
fn remove_tags_by_source(&self, source: &str) -> BackendResult<usize> { |
| 204 |
let db = self.db.lock(); |
| 205 |
Ok(audiofiles_core::rules::remove_tags_by_source(&db, source)?) |
| 206 |
} |
| 207 |
|
| 208 |
fn get_waveform(&self, hash: &str) -> BackendResult<Option<WaveformData>> { |
| 209 |
let db = self.db.lock(); |
| 210 |
Ok(audiofiles_core::analysis::waveform::load_waveform( |
| 211 |
&db, hash, |
| 212 |
)) |
| 213 |
} |
| 214 |
} |
| 215 |
|
| 216 |
impl SimilarityBackend for DirectBackend { |
| 217 |
|
| 218 |
|
| 219 |
fn start_find_similar(&self, hash: &str, limit: usize) -> BackendResult<()> { |
| 220 |
self.ensure_search_worker()?; |
| 221 |
let mut guard = self.search_worker.lock(); |
| 222 |
let delivered = guard.as_ref().is_some_and(|w| { |
| 223 |
w.send(SearchCommand::FindSimilar { |
| 224 |
hash: hash.to_string(), |
| 225 |
limit, |
| 226 |
}) |
| 227 |
}); |
| 228 |
|
| 229 |
|
| 230 |
|
| 231 |
if !delivered { |
| 232 |
*guard = None; |
| 233 |
return Err(BackendError::Other( |
| 234 |
"search worker is not running".to_string(), |
| 235 |
)); |
| 236 |
} |
| 237 |
Ok(()) |
| 238 |
} |
| 239 |
|
| 240 |
fn start_find_near_duplicates(&self, hash: &str, limit: usize) -> BackendResult<()> { |
| 241 |
self.ensure_search_worker()?; |
| 242 |
let mut guard = self.search_worker.lock(); |
| 243 |
let delivered = guard.as_ref().is_some_and(|w| { |
| 244 |
w.send(SearchCommand::FindNearDuplicates { |
| 245 |
hash: hash.to_string(), |
| 246 |
limit, |
| 247 |
}) |
| 248 |
}); |
| 249 |
if !delivered { |
| 250 |
*guard = None; |
| 251 |
return Err(BackendError::Other( |
| 252 |
"search worker is not running".to_string(), |
| 253 |
)); |
| 254 |
} |
| 255 |
Ok(()) |
| 256 |
} |
| 257 |
} |
| 258 |
|