docs.rs failed to build frankensearch-storage-0.2.1
Please check the build logs for more information.
See Builds for ideas on how to fix a failed build, or Metadata for how to configure docs.rs builds.
If you believe this is docs.rs' fault, open an issue.
Please check the build logs for more information.
See Builds for ideas on how to fix a failed build, or Metadata for how to configure docs.rs builds.
If you believe this is docs.rs' fault, open an issue.
Visit the last successful build:
frankensearch-storage-0.2.0
frankensearch-storage
FrankenSQLite-backed metadata and embedding job storage for frankensearch.
Overview
This crate owns the persistent storage layer for frankensearch, backed by FrankenSQLite. It manages schema bootstrapping, document metadata persistence, content-hash deduplication, an embedding job queue, search history, bookmarks, index build metadata, and staleness detection. It serves as the bridge between frankensearch's in-memory search pipeline and durable on-disk state.
Key Types
Storage and Connection
Storage- main storage handle wrapping a FrankenSQLite connectionStorageConfig- configuration for storage initialization
Document Management
DocumentRecord- stored document metadata recordupsert_document- insert or update a document with deduplist_document_ids/count_documents- document enumeration and countingEmbeddingStatus/StatusCounts- per-document embedding state tracking
Content Hashing and Deduplication
ContentHasher- SHA-256 content hashing for change detectionDeduplicationDecision- whether to re-embed or skip a documentlookup_content_hash/record_content_hash- hash lookup and persistence
Job Queue
PersistentJobQueue- durable embedding job queue with claim/complete/fail lifecycleClaimedJob/EnqueueRequest- job queue request and claim typesJobQueueConfig/JobQueueMetrics- queue configuration and telemetryQueueDepth- current queue depth by status
Pipeline
StorageBackedJobRunner- orchestrates document ingestion through the embedding pipelineIngestRequest/IngestResult/IngestAction- ingestion request/result typesPipelineConfig/PipelineMetrics- pipeline configuration and performance metricsEmbeddingVectorSink/InMemoryVectorSink- sinks for produced embedding vectors
History and Bookmarks
record_search/list_search_history- search history recording and retrievaladd_bookmark/list_bookmarks/is_bookmarked- document bookmarking
Index Metadata and Staleness
IndexMetadata/IndexBuildRecord- index build trackingStalenessCheck/StalenessReport- index freshness detectionStorageBackedStaleness- staleness checking backed by stored metadata
Schema
bootstrap- creates/migrates the storage schemaSCHEMA_VERSION/current_version- schema versioning
Features
| Feature | Description |
|---|---|
fts5 |
Enables Fts5LexicalSearch adapter using FrankenSQLite FTS5 |
Usage
use ;
// Open or create a storage database
let config = default;
let storage = open
.expect;
// Bootstrap schema
bootstrap.expect;
// Upsert a document
// upsert_document(&storage, &doc).expect("upsert");
Dependency Graph Position
frankensearch-core
^
|
frankensearch-storage
^
|-- frankensearch-fsfs
|-- frankensearch (root, optional, feature: storage)
License
MIT