* refactor(edge): split EdgeShard load into new() and load()
- new(path, config): create edge shard only when path has no existing segments
- load(path, config?): load from existing files; config optional (load from
edge_config.json or infer from segments)
- Helpers: has_existing_segments, ensure_dirs_and_open_wal, resolve_initial_config,
load_segments, ensure_appendable_segment
- Python: EdgeShard.create_new(path, config); __init__ still calls load()
- Examples use new() for creation and load(path, None) for reopen
- Error instead of panic on config mismatch; explicit load/create in Python
- fix: use OptimizerThresholds.deferred_internal_id for dev compatibility
Made-with: Cursor
* rollback threshold changes
* fix(edge): address dancixx review comments
- Persist inferred config in load() when edge_config.json does not exist
(SaveOnDisk::new only saves when file exists)
- Python: add #[new] delegating to load() for backward compatibility
- qdrant_edge.pyi: Optional return types for deleted_threshold,
vacuum_min_vector_number, default_segment_number; add __init__ doc
Made-with: Cursor
* Revert "fix(edge): address dancixx review comments"
This reverts commit 370e21a6c74c41210e1658f89814395cb86ed81c.
* fix: optional returns
* fix: save config it is not exist
* fix: save data on disk always
* fix: python examples
* chore: remove edge.close()
* fix: wal lock
* fix: rename of EdgeShardConfig -> EdgeConfig
---------
Co-authored-by: Cursor Agent <agent@cursor.com>
Co-authored-by: Andrey Vasnetsov <andrey@vasnetsov.com>
Co-authored-by: Daniel Boros <dancixx@gmail.com>
* refactor(edge): let edge re-export segment/shard/sparse
* chore(ast-grep-rules): handle path like `::shard::blah::Blah`
This commit was required during the refactoring. It turns out we don't
need it right now, but it might be useful in the future. Or not.
* refactor(edge-rs): Rehaul public API
* Introduce EdgeShardConfig for edge shard
- Add EdgeShardConfig and EdgeOptimizersConfig in lib/edge/src/config.rs
- Segment config (vector_data, sparse_vector_data, payload_storage_type)
- Global hnsw_config and per-vector HNSW in segment config
- Optimizer params: deleted_threshold, vacuum_min_vector_number,
default_segment_number, max_segment_size, indexing_threshold,
prevent_unoptimized (excludes memmap_threshold, flush_interval_sec,
max_optimization_threads)
- Persist/load as edge_config.json in shard path
- EdgeShard uses RwLock<EdgeShardConfig>; load() accepts Option<EdgeShardConfig>,
falls back to file or infer from segments; compatibility checked on load
- load_with_segment_config() for backward compatibility (SegmentConfig -> EdgeShardConfig)
- optimize() uses EdgeShardConfig for hnsw and optimizer thresholds
- Public methods: set_hnsw_config(), set_vector_hnsw_config(), set_optimizers_config()
(update and persist)
- Python and examples use load_with_segment_config with existing config API
Made-with: Cursor
* Refactor EdgeShardConfig: user-facing params only, config module
- Replace SegmentConfig inside EdgeShardConfig with user-facing fields:
- on_disk_payload (bool) instead of payload_storage_type
- vectors: HashMap<VectorNameBuf, EdgeVectorParams> with on_disk per vector,
no per-vector quantization; global quantization_config only
- sparse_vectors: HashMap<VectorNameBuf, EdgeSparseVectorParams> with on_disk
- EdgeVectorParams / EdgeSparseVectorParams use on_disk (bool) instead of
storage_type; conversion to VectorDataConfig/SparseVectorDataConfig in
to_segment_config()
- Add config module: mod.rs, optimizers.rs, vectors.rs, shard.rs
- from_segment_config(&SegmentConfig) fills all inferrable params
- to_segment_config() builds SegmentConfig for segments and optimize()
- load_with_segment_config takes Option<SegmentConfig>, uses from_segment_config
Made-with: Cursor
* Move optimizer threshold helpers to shard crate
- Add get_number_segments, get_indexing_threshold_kb, get_max_segment_size_kb,
get_deferred_points_threshold_bytes in shard::optimizers::config
- Collection OptimizersConfig and edge EdgeOptimizersConfig delegate to these
- Single place for threshold logic; collection and edge use shard helpers
Made-with: Cursor
* Use destructuring in config conversions to avoid missing new fields
- EdgeVectorParams: destructure VectorDataConfig in from_*, destructure self in to_vector_data_config
- EdgeSparseVectorParams: destructure SparseVectorDataConfig and SparseIndexConfig in from_*, destructure self in to_sparse_vector_data_config
- EdgeShardConfig: destructure SegmentConfig in from_segment_config, destructure self in to_segment_config
Adding new fields to source structs will now cause compile errors until conversions are updated.
Made-with: Cursor
* refactor: centralize on_disk_payload→payload_storage_type, on_disk→storage_type, and appendable quantization logic
- PayloadStorageType::from_on_disk_payload(bool) in segment (Mmap/InRamMmap)
- VectorStorageType::from_on_disk(bool) in segment (ChunkedMmap/InRamChunkedMmap)
- QuantizationConfig::for_appendable_segment(Option<&Self>) in segment (feature flag + supports_appendable)
- collection: use from_on_disk_payload in non-rocksdb branch
- edge shard/vectors: use new helpers; remove duplicated conditionals
- shard optimizers: use from_on_disk and for_appendable_segment
Made-with: Cursor
* refactor(edge): use EdgeShardConfig directly, drop segment_config
- Add plain_segment_config() for create_appendable_segment (no HNSW)
- Add segment_optimizer_config() built from EdgeShardConfig for blocking optimizers
- Add vector_data_config(name) for query/MMR
- build_blocking_optimizers: use segment_optimizer_config() instead of SegmentConfig
- create_appendable_segment: use plain_segment_config()
- search/query: use config().vectors and vector_data_config() instead of segment_config()
- Remove segment_config() from EdgeShardConfig and EdgeShard
- Add to_plain_vector_data_config on EdgeVectorParams
Made-with: Cursor
* [manual] review changes
* refactor(edge-py): wrap EdgeShardConfig, add EdgeVectorParams/EdgeSparseVectorParams
- PyEdgeConfig now wraps EdgeShardConfig (vectors, sparse_vectors, on_disk_payload, etc.)
- PyEdgeVectorParams / PyEdgeSparseVectorParams wrap edge config types
- PyEdgeOptimizersConfig for optional optimizer settings
- EdgeShard.load() uses EdgeShardConfig; edge::config made pub for Python crate
- cargo fmt + clippy (remove map_identity)
Made-with: Cursor
* refactor(edge-py): simplify config API, remove unused Py* types, add EdgeConfig
- Remove unused PyPayloadStorageType, PyVectorDataConfig, PyVectorStorageType,
PySparseVectorDataConfig, PySparseVectorStorageType from Python bindings
- Move PyEdgeOptimizersConfig to lib/edge/python/src/config/optimizers.rs
- Update qdrant_edge.pyi: EdgeConfig with vectors/sparse_vectors,
EdgeVectorParams, EdgeSparseVectorParams, EdgeOptimizersConfig
- Update examples (common.py, repr.py) to use new config API
- Run cargo fmt
Made-with: Cursor
* [manual] review changes
* [manual] review changes
* [manual] fix test
* Address CodeRabbit review comments for PR 8322 (#8324)
* Address CodeRabbit review comments for PR 8322
- Python examples: explicit imports (repr.py, common.py) and new EdgeConfig API
- HnswIndexConfig: add max_indexing_threads param and property in .pyi and Rust bindings
- EdgeConfig: make vectors optional for sparse-only configs; validate at least one of vectors/sparse_vectors
- EdgeShardConfig::load: use try_exists(), propagate I/O errors
- from_segment_config: infer hnsw_config from per-vector HNSW when all agree
- EdgeShard setters: atomic clone-mutate-save-then-replace; persist config save errors
- Segment compat: prefix vector name in error messages; resolve None datatype to Float32
- max_indexing_threads: preserve 0 (auto) sentinel in trait default; remove per-optimizer overrides
- SegmentOptimizerConfig:🆕 build plain and optimizer maps in single pass
- config_mismatch_optimizer tests: use VectorNameBuf::from() instead of .into()
- vectors.rs: doc updates for per-vector quantization
Made-with: Cursor
* Address @generall review: SaveOnDisk for config, resolve num_rayon_threads in optimizer
- Use SaveOnDisk<EdgeShardConfig> for EdgeShard config (generall: 'We have SaveOnDisk struct for this')
- Create via SaveOnDisk::new() after resolving config; setters use .write() for atomic persist
- set_vector_hnsw_config: clone then mutate then write (fallible setter)
- max_indexing_threads: resolve 0 (auto) via num_rayon_threads inside impl (generall: 'proper solution would be to resolve num_rayon_threads inside the optimizer impl')
- max_indexing_threads_sentinel_aware() now returns Some(num_rayon_threads(raw)) so callers get actual thread count
Made-with: Cursor
* [manual] reorganize num_rayon_threads -> get_num_indexing_threads to better account per-vector configuration
---------
Co-authored-by: Cursor Agent <agent@cursor.com>
Co-authored-by: generall <andrey@vasnetsov.com>
* update docstring and pyi
* fmt
* fmt
* clipy
---------
Co-authored-by: Cursor Agent <agent@cursor.com>
Co-authored-by: generall <andrey@vasnetsov.com>
* introduce update_mode parameter for upsert operation to control if we want to insert, update, or upsert
* add test
* upd dockstring
* require resharding once all peers have updated version
* use service error
* fix clippy again
* wait for same version before resharding in tests
* Implement `__repr__` for `PyJsonPath`
* Implement `__repr__` for `PyFilter`
* Implement `__repr__` for `PyQuery`
* Implement `__repr__` for `PyQueryRequest`
* Implement `__repr__` for `PySearchRequest`
* Implement `__repr__` for `PyFilter` using `pyclass_repr` attribute
* Implement `__repr__` for `PyQuery` using `pyclass_repr` attribute
* Implement `__repr__` for `PyQueryRequest` using `pyclass_repr` attribute
* Implement `__repr__` for `PySearchRequest` using `pyclass_repr` attribute
* Refactor `PyUpdateOperation` constructors
* Add default parameters to `PyVectorDataConfig::new`
* Add `Repr` trait and `WriteExt` helper
* Implement `__repr__` for config types
* fixup! Implement `__repr__` for config types
Use `Copy` instead of `Clone`
* fixup! Implement `__repr__` for config types
Add basic test
* Implement `__repr__` for `PyPointId`
* Implement `__repr__` for `PyVector`
* Implement `__repr__` for `PyVectorInternal`
* Implement `__repr__` for `PyPayload`
* Implement `__repr__` for `PyValue`
* Implement `__repr__` for `PyPoint`
* Implement `__repr__` for `PyPointVectors`
* Implement `__repr__` for `PyRecord`
* Move `PyScoredPoint` into a separate file
* Implement `__repr__` for `PyScoredPoint`
* Cleanup examples
* fixup! Implement `__repr__` for `PyScoredPoint`
* Move `PyOrderValue` into separate file
* Add `PyScoredPoint::order_value`
* Implement `pyclass_repr` proc-macro attribute
* Implement `__repr__` for config types using `pyclass_repr` attribute
* Implement `__repr__` for `PySparseVector` using `pyclass_repr` attribute
* Implement `__repr__` for `PyPoint` using `pyclass_repr` attribute
* Implement `__repr__` for `PyPointVectors` using `pyclass_repr` attribute
* Implement `__repr__` for `PyRecord` using `pyclass_repr` attribute
* Implement `__repr__` for `PyScoredPoint` using `pyclass_repr` attribute
* Minor fixes and cleanups
* fixup! Minor fixes and cleanups
* rollback copy for quantization config
* rollback copy for quantization config
---------
Co-authored-by: generall <andrey@vasnetsov.com>
