Files
qdrant/lib/edge/python/examples/repr.py
qdrant-cloud-bot 4d23f32681 Introduce EdgeShardConfig for edge shard (#8322)
* 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>
2026-03-26 17:40:51 +01:00

27 lines
507 B
Python
Executable File

#!/usr/bin/env python3
from qdrant_edge import (
Distance,
EdgeConfig,
EdgeSparseVectorParams,
EdgeVectorParams,
Modifier,
VectorStorageDatatype,
)
config = EdgeConfig(
vectors=EdgeVectorParams(
size=128,
distance=Distance.Cosine,
),
sparse_vectors={
"sparse": EdgeSparseVectorParams(
full_scan_threshold=1024,
datatype=VectorStorageDatatype.Float32,
modifier=Modifier.Idf,
),
},
)
print(config)